several components can add up to a measurable fuel efficiency
improvement.
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    \476\ ``Impact of Friction Reduction Technologies on Fuel
Economy,'' Fenske, G. Presented at the March 2009 Chicago Chapter
Meeting of the `Society of Tribologists and Lubricated Engineers'
Meeting, March 18th, 2009. Available at: http://www.chicagostle.org/program/2008-2009/Impact%20of%20Friction%20Reduction%20Technologies%20on%20Fuel%20Economy%20-%20with%20VGs%20removed.pdf (last accessed July 9, 2009).
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(iii) Engine Parasitic Demand Reduction
    In addition to physical engine friction reduction, manufacturers
can reduce the mechanical load on the engine from parasitics, such as
oil, fuel, and coolant pumps. The high-pressure fuel pumps of direct-
injection gasoline and diesel engines have particularly high demand.
Example improvements include variable speed or variable displacement
water pumps, variable displacement oil pumps, more efficient high
pressure fuel pumps, valvetrain upgrades and shutting off piston
cooling when not needed.
(iv) Coupled Cam Phasing
    Valvetrains with coupled (or coordinated) cam phasing can modify
the timing of both the inlet valves and the exhaust valves an equal
amount by phasing the camshaft of an overhead valve engine.\477\ For
overhead valve engines, which have only one camshaft to actuate both
inlet and exhaust valves, couple cam phasing is the only variable valve
timing (VVT) implementation option available and requires only one cam
phaser.\478\ We also considered variable valve lift (VVL), which alters
the intake valve lift in order to reduce pumping losses and more
efficiently ingest air.
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    \477\ Although couple cam phasing appears only in the single
overhead cam and overhead valve branches of the decision tree, it is
noted that a single phaser with a secondary chain drive would allow
couple cam phasing to be applied to direct overhead cam engines.
Since this would potentially be adopted on a limited number of
direct overhead cam engines NHTSA did not include it in that branch
of the decision tree.
    \478\ It is also noted that coaxial camshaft developments would
allow other variable valve timing options to be applied to overhead
valve engines. However, since they would potentially be adopted on a
limited number of overhead valve engines, NHTSA did not include them
in the decision tree.
---------------------------------------------------------------------------

(v) Cylinder Deactivation
    In conventional spark-ignited engines throttling the airflow
controls engine torque output. At partial loads, efficiency can be
improved by using cylinder deactivation instead of throttling. Cylinder
deactivation can improve engine efficiency by disabling or deactivating
(usually) half of the cylinders when the load is less than half of the
engine's total torque capability--the valves are kept closed, and no
fuel is injected--as a result, the trapped air within the deactivated
cylinders is simply compressed and expanded as an air spring, with
reduced friction and

heat losses. The active cylinders combust at almost double the load
required if all of the cylinders were operating. Pumping losses are
significantly reduced as long as the engine is operated in this ``part-
cylinder'' mode.
    Cylinder deactivation control strategy relies on setting maximum
manifold absolute pressures or predicted torque within a range in which
it can deactivate the cylinders. Noise and vibration issues reduce the
operating range to which cylinder deactivation is allowed, although
manufacturers are exploring vehicle changes that enable increasing the
amount of time that cylinder deactivation might be suitable. Some
manufacturers may choose to adopt active engine mounts and/or active
noise cancellations systems to address Noise Vibration and Harshness
(NVH) concerns and to allow a greater operating range of activation.
    Cylinder deactivation has seen a recent resurgence thanks to better
valvetrain designs and engine controls. General Motors and Fiat
Chrysler have incorporated cylinder deactivation across a substantial
portion of their V8-powered lineups, including some heavy duty
applications.
(vi) Stoichiometric Gasoline Direct Injection
    SGDI engines inject fuel at high pressure directly into the
combustion chamber (rather than the intake port in port fuel
injection). SGDI requires changes to the injector design, an additional
high pressure fuel pump, new fuel rails to handle the higher fuel
pressures and changes to the cylinder head and piston crown design.
Direct injection of the fuel into the cylinder improves cooling of the
air/fuel charge within the cylinder, which allows for higher
compression ratios and increased thermodynamic efficiency without the
onset of combustion knock. Recent injector design advances, improved
electronic engine management systems and the introduction of multiple
injection events per cylinder firing cycle promote better mixing of the
air and fuel, enhance combustion rates, increase residual exhaust gas
tolerance and improve cold start emissions. SGDI engines achieve higher
power density and match well with other technologies, such as boosting
and variable valvetrain designs.
    Most manufacturers have introduced vehicles with SGDI engines in
light duty sectors, including GM and Ford and have announced their
plans to increase dramatically the number of SGDI engines in their
portfolios. SGDI has not been introduction on heavy duty applications
at this time however as these largely dedicated heavy duty engines
approach their redesign window, they are expected to become SGDI
engines.
(vii) Turbocharging and Downsizing
    The specific power of a naturally aspirated engine is primarily
limited by the rate at which the engine is able to draw air into the
combustion chambers. Turbocharging and supercharging (grouped together
here as boosting) are two methods to increase the intake manifold
pressure and cylinder charge-air mass above naturally aspirated levels.
Boosting increases the airflow into the engine, thus increasing the
specific power level, and with it the ability to reduce engine
displacement while maintaining performance. This effectively reduces
the pumping losses at lighter loads in comparison to a larger,
naturally aspirated engine.
    Almost every major manufacturer currently markets a vehicle with
some form of boosting. While boosting has been a common practice for
increasing performance for several decades, turbocharging has
considerable potential to improve fuel economy and reduce
CO2 emissions when the engine displacement is also reduced.
Specific power levels for a boosted engine often exceed 100 hp/L,
compared to average naturally aspirated engine power densities of
roughly 70 hp/L. As a result, engines can be downsized roughly 30
percent or higher while maintaining similar peak output levels. In the
last decade, improvements to turbocharger turbine and compressor design
have improved their reliability and performance across the entire
engine operating range. New variable geometry turbines and ball-bearing
center cartridges allow faster turbocharger spool-up (virtually
eliminating the once-common ``turbo lag'') while maintaining high flow
rates for increased boost at high engine speeds. Low speed torque
output has been dramatically improved for modern turbocharged engines.
However, even with turbocharger improvements, maximum engine torque at
very low engine speed conditions, for example launch from standstill,
is increased less than at mid and high engine speed conditions. The
potential to downsize engines may be less on vehicles with low
displacement to vehicle mass ratios for example a very small
displacement engine in a vehicle with significant curb weight, in order
to provide adequate acceleration from standstill, particularly up
grades or at high altitudes.
    The use of GDI in combination with turbocharging and charge air
cooling reduces the fuel octane requirements for knock limited
combustion enabling the use of higher compression ratios and boosting
pressures. Recently published data with advanced spray-guided injection
systems and more aggressive engine downsizing targeted towards reduced
fuel consumption and CO2 emissions reductions indicate that
the potential for reducing CO2 emissions for turbocharged,
downsized GDI engines may be as much as 15 to 30 percent relative to
port-fuel-injected engines.14 15 16 17 18 Confidential
manufacturer data suggests an incremental range of fuel consumption and
CO2 emission reduction of 4.8 to 7.5 percent for
turbocharging and downsizing. Other publicly-available sources suggest
a fuel consumption and CO2 emission reduction of 8 to 13
percent compared to current-production naturally-aspirated engines
without friction reduction or other fuel economy technologies: A joint
technical paper by Bosch and Ricardo suggesting fuel economy gain of 8
to 10 percent for downsizing from a 5.7 liter port injection V8 to a
3.6 liter V6 with direct injection using a wall-guided direct injection
system; a Renault report suggesting a 11.9 percent NEDC fuel
consumption gain for downsizing from a 1.4 liter port injection in-line
4-cylinder engine to a 1.0 liter in-line 4-cylinder engine, also with
wall-guided direct injection; and a Robert Bosch paper suggesting a 13
percent NEDC gain for downsizing to a turbocharged DI engine, again
with wall-guided injection. These reported fuel economy benefits show a
wide range depending on the SGDI technology employed.
    Note that for this analysis the agencies determined that this
technology path is only applicable to heavy duty applications that have
operating conditions more closely associated with light duty vehicles.
This includes vans designed mainly for cargo volume or modest payloads
and having similar GCWR to light duty applications. These vans cannot
tow trailers heavier than similar light duty vehicles and are largely
already sharing engines of significantly smaller displacement and
cylinder count compared to heavy duty vehicles designed mainly for
trailer towing.
    ACEEE commented that 10 percent of pick-ups in the heavy duty
sector are candidates for turbocharging and downsizing if they do not
require higher payloads or towing capacity. Other commenters suggested
that downsizing that has occurred in light duty could also occur in
heavy duty. As discussed above, the agencies evaluated turbocharging
and downsizing in

vehicles like vans which are not typically designed for extensive
trailer towing. When we looked at pick-ups, we determined that
consumers needing a pick-up without higher payload or trailer towing
requirements would migrate to the lower cost light-duty versions which
are typically identical in cabin size and seating as the heavy-duty
versions but have less work capability. Because of this, in the
agencies' assessment, the heavy-duty pickups retained the high trailer
towing and payload requirements and the corresponding larger engines.
AAPC comments supported this approach as the correct combination of
engine to intended use and even provided in their comments data
indicating that turbocharged and downsized engines are more fuel
efficient at lighter loads however under working conditions expected of
a heavy-duty pick-up they are actually less fuel efficient than the
larger engines.
(viii) Cooled Exhaust-Gas Recirculation
    Cooled exhaust gas recirculation or Boosted EGR is a combustion
concept that involves utilizing EGR as a charge diluent for controlling
combustion temperatures and cooling the EGR prior to its introduction
to the combustion system. Higher exhaust gas residual levels at part
load conditions reduce pumping losses for increased fuel economy. The
additional charge dilution enabled by cooled EGR reduces the incidence
of knocking combustion and obviates the need for fuel enrichment at
high engine power. This allows for higher boost pressure and/or
compression ratio and further reduction in engine displacement and both
pumping and friction losses while maintaining performance. Engines of
this type use GDI and both dual cam phasing and discrete variable valve
lift. The EGR systems considered in this final rule, consistent with
the rule, will use a dual-loop system with both high and low pressure
EGR loops and dual EGR coolers. The engines will also use single-stage,
variable geometry turbocharging with higher intake boost pressure
available across a broader range of engine operation than conventional
turbocharged SI engines. Such a system is estimated to be capable of an
additional 3 to 5 percent effectiveness relative to a turbocharged,
downsized GDI engine without cooled-EGR. The agencies have also
considered a more advanced version of such a cooled EGR system that
employs very high combustion pressures by using dual stage
turbocharging.
(ix) Lean-Burn Combustion
    The agencies considered the concept that gasoline engines that are
normally stoichiometric mainly for emission reasons can run lean over a
range of operating conditions and utilize diesel like aftertreatment
systems to control NOX. For this analysis, we determined
that the modal operation nature of this technology is currently only
beneficial at light loads and will not be appropriate for a heavy duty
application purchase specifically for its high work and load capacity.
(b) Diesel Engine Technologies
    Diesel engines have several characteristics that give them superior
fuel efficiency compared to conventional gasoline, spark-ignited
engines. Pumping losses are much lower due to lack of (or greatly
reduced) throttling. The diesel combustion cycle operates at a higher
compression ratio, with a very lean air/fuel mixture, and turbocharged
light-duty diesels typically achieve much higher torque levels at lower
engine speeds than equivalent-displacement naturally-aspirated gasoline
engines. Additionally, diesel fuel has a higher energy content per
gallon.\479\ However, diesel fuel also has a higher carbon to hydrogen
ratio, which increases the amount of CO2 emitted per gallon
of fuel used by approximately 15 percent over a gallon of gasoline.
---------------------------------------------------------------------------

    \479\ Burning one gallon of diesel fuel produces about 15
percent more carbon dioxide than gasoline due to the higher density
and carbon to hydrogen ratio.
---------------------------------------------------------------------------

    Based on confidential business information and the 2010 NAS Report,
two major areas of diesel engine design could be improved during the
timeframe of this final rule. These areas include aftertreatment
improvements and a broad range of engine improvements.
(i) Aftertreatment Improvements
    The HD diesel pickup and van segment has largely adopted the SCR
type of aftertreatment system to comply with criteria pollutant
emission standards. As the experience base for SCR expands over the
next few years, many improvements in this aftertreatment system such as
construction of the catalyst, thermal management, and reductant
optimization may result in a reduction in the amount of fuel used in
the process. However, due to uncertainties with these improvements
regarding the extent of current optimization and future criteria
emissions obligations, the agencies are not considering aftertreatment
improvements as a fuel-saving technology in the rulemaking analysis.
(ii) Engine Improvements
    Diesel engines in the HD pickup and van segment are expected to
have several improvements in their base design in the 2021-2027
timeframe. These improvements include items such as improved combustion
management, optimal turbocharger design, and improved thermal
management.
(c) Transmission Technologies
    The agencies have also reviewed the transmission technology
estimates used in the 2017-2015 light-duty and 2014-2018 heavy-duty
final rules. In doing so, NHTSA and EPA considered or reconsidered all
available sources including the 2015 NHTSA Technology Study and updated
the estimates as appropriate. The section below describes each of the
transmission technologies considered for this rule.
(i) Automatic 8-Speed Transmissions
    Manufacturers can also choose to replace 6-speed automatic
transmissions with 8-speed automatic transmissions. Additional ratios
allow for further optimization of engine operation over a wider range
of conditions, but this is subject to diminishing returns as the number
of speeds increases. As additional gear sets are added, additional
weight and friction are introduced requiring additional countermeasures
to offset these losses. Some manufacturers are replacing 6-speed
automatics already, and 7 to 10-speed automatics have entered
production.
(ii) High Efficiency Transmission
    For this rule, a high efficiency transmission refers to some or all
of a suite of incremental transmission improvement technologies that
should be available within the 2019 to 2027 timeframe. The majority of
these improvements address mechanical friction within the transmission.
These improvements include but are not limited to: Shifting clutch
technology improvements, improved kinematic design, dry sump
lubrication systems, more efficient seals, bearings and clutches
(reducing drag), component superfinishing and improved transmission
lubricants.
(iii) Secondary Axle Disconnect
    The ability to disconnect some of the rotating components in the
front axle on 4wd vehicles when the secondary axle is not needed for
traction. This will reduce friction and increase fuel economy.

(d) Electrification/Accessory Technologies
(i) Electrical Power Steering or Electrohydraulic Power Steering
    Electric power steering (EPS) or Electrohydraulic power steering
(EHPS) provides a potential reduction in CO2 emissions and
fuel consumption over hydraulic power steering because of reduced
overall accessory loads. This eliminates the parasitic losses
associated with belt-driven power steering pumps which consistently
draw load from the engine to pump hydraulic fluid through the steering
actuation systems even when the wheels are not being turned. EPS is an
enabler for all vehicle hybridization technologies since it provides
power steering when the engine is off. EPS may be implemented on most
vehicles with a standard 12V system. Some heavier vehicles may require
a higher voltage system which may add cost and complexity.
(ii) Improved Accessories
    The accessories on an engine, including the alternator, coolant and
oil pumps are traditionally mechanically-driven. A reduction in
CO2 emissions and fuel consumption can be realized by
driving them electrically, and only when needed (``on-demand'').
    Electric water pumps and electric fans can provide better control
of engine cooling. For example, coolant flow from an electric water
pump can be reduced and the radiator fan can be shut off during engine
warm-up or cold ambient temperature conditions which will reduce warm-
up time, reduce warm-up fuel enrichment, and reduce parasitic losses.
    Indirect benefit may be obtained by reducing the flow from the
water pump electrically during the engine warm-up period, allowing the
engine to heat more rapidly and thereby reducing the fuel enrichment
needed during cold operation and warm-up of the engine. Faster oil
warm-up may also result from better management of the coolant warm-up
period. Further benefit may be obtained when electrification is
combined with an improved, higher efficiency engine alternator used to
supply power to the electrified accessories.
    Intelligent cooling can more easily be applied to vehicles that do
not typically carry heavy payloads, so larger vehicles with towing
capacity present a challenge, as these vehicles have high cooling fan
loads.\480\ However, towing vehicles tend to have large cooling system
capacity and flow scaled to required heat rejection levels when under
full load situations such as towing at GCWR in extreme ambient
conditions. During almost all other situations, this design
characteristic may result in unnecessary energy usage for coolant
pumping and heat rejection to the radiator.
---------------------------------------------------------------------------

    \480\ In the CAFE model, improved accessories refers solely to
improved engine cooling.
---------------------------------------------------------------------------

    The agencies considered whether to include electric oil pump
technology for the rulemaking. Because it is necessary to operate the
oil pump any time the engine is running, electric oil pump technology
has insignificant effect on efficiency. Therefore, the agencies decided
to not include electric oil pump technology.
(iii) Mild Hybrid
    Mild hybrid systems offer idle-stop functionality and a limited
level of regenerative braking and power assist. These systems replace
the conventional alternator with a belt or crank driven starter/
alternator and may add high voltage electrical accessories (which may
include electric power steering and an auxiliary automatic transmission
pump). The limited electrical requirements of these systems allow the
use of lead-acid batteries or supercapacitors for energy storage, or
the use of a small lithium-ion battery pack.
(iv) Strong Hybrid
    A hybrid vehicle is a vehicle that combines two significant sources
of propulsion energy, where one uses a consumable fuel (like gasoline),
and one is rechargeable (during operation, or by another energy
source). Hybrid technology is well established in the U.S. light-duty
market and more manufacturers are adding hybrid models to their
lineups. Hybrids reduce fuel consumption through three major
mechanisms:
     The internal combustion engine can be optimized (through
downsizing, modifying the operating cycle, or other control techniques)
to operate at or near its most efficient point more of the time. Power
loss from engine downsizing can be mitigated by employing power assist
from the secondary power source.
     A significant amount of the energy normally lost as heat
while braking can be captured and stored in the energy storage system
for later use.
     The engine is turned off when it is not needed, such as
when the vehicle is coasting or when stopped.
    Hybrid vehicles utilize some combination of the three above
mechanisms to reduce fuel consumption and CO2 emissions. The
effectiveness of fuel consumption and CO2 reduction depends
on the utilization of the above mechanisms and how aggressively they
are pursued. One area where this variation is particularly prevalent is
in the choice of engine size and its effect on balancing fuel economy
and performance. Some manufacturers choose not to downsize the engine
when applying hybrid technologies. In these cases, overall performance
(acceleration) is typically improved beyond the conventional engine.
However, fuel efficiency improves less than if the engine was downsized
to maintain the same performance as the conventional version. The non-
downsizing approach is used for vehicles like trucks where towing and/
or hauling are an integral part of their performance requirements. In
these cases, if the engine is downsized, the battery can be quickly
drained during a long hill climb with a heavy load, leaving only a
downsized engine to carry the entire load. Because towing capability is
currently a heavily-marketed truck attribute, manufacturers are
hesitant to offer a truck with a downsized engine, which can lead to a
significantly diminished towing performance when the battery state of
charge level is low, and therefore engines are traditionally not
downsized for these vehicles. In assessing the cost of this technology,
the agencies consequently assumed the cost of a full size engine.
    Strong Hybrid technology utilizes an axial electric motor connected
to the transmission input shaft and connected to the engine crankshaft
through a clutch. The axial motor is a motor/generator that can provide
sufficient torque for launch assist, all electric operation, and the
ability to recover significant levels of braking energy.
(e) Vehicle Technologies
(i) Mass Reduction
    Mass reduction is a technology that can be used in a manufacturer's
strategy to meet the Heavy Duty Greenhouse Gas Phase 2 standards.
Vehicle mass reduction (also referred to as ``down-weighting'' or
``light-weighting''), decreases fuel consumption and GHG emissions by
reducing the energy demand needed to overcome inertia forces, and
rolling resistance. Automotive companies have worked with mass
reduction technologies for many years and a lot of these technologies
have been used in production vehicles. The weight savings achieved by
adopting mass reduction technologies offset weight gains due to
increased vehicle size, larger powertrains, and increased feature
content (sound insulation,

entertainment systems, improved climate control, panoramic roof, etc.).
Sometimes mass reduction has been used to increase vehicle towing and
payload capabilities.
    Manufacturers employ a systematic approach to mass reduction, where
the net mass reduction is the addition of a direct component or system
mass reduction, also referred to as primary mass reduction, plus the
additional mass reduction taken from indirect ancillary systems and
components, also referred to as secondary mass reduction or mass
compounding. There are more secondary mass reductions achievable for
light-duty vehicles compared to heavy-duty vehicles, which are limited
due to the higher towing and payload requirements for these vehicles.
    Mass reduction can be achieved through a number of approaches, even
while maintaining other vehicle functionalities. As summarized by NAS
in its 2011 light duty vehicle report,\481\ there are two key
strategies for primary mass reduction: (1) Changing the design to use
less material; (2) substituting lighter materials for heavier
materials.
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    \481\ Committee on the Assessment of Technologies for Improving
Light-Duty Vehicle Fuel Economy; National Research Council,
``Assessment of Fuel Economy Technologies for Light-Duty Vehicles,''
2011. Available at http://www.nap.edu/catalog.php?record_id=12924
(last accessed Jun 27, 2012).
---------------------------------------------------------------------------

    The first key strategy of using less material compared to the
baseline component can be achieved by optimizing the design and
structure of vehicle components, systems and vehicle structure. Vehicle
manufacturers have long used these continually-improving CAE tools to
optimize vehicle designs. For example, the Future Steel Vehicle (FSV)
project \482\ sponsored by WorldAutoSteel used three levels of
optimization: Topology optimization, low fidelity 3G (Geometry Grade
and Gauge) optimization, and subsystem optimization, to achieve 30
percent mass reduction in the body structure of a vehicle with a mild
steel unibody structure. Using less material can also be achieved
through improving the manufacturing process, such as by using improved
joining technologies and parts consolidation. This method is often used
in combination with applying new materials.
---------------------------------------------------------------------------

    \482\ SAE World Congress, ``Focus B-pillar `tailor rolled' to 8
different thicknesses,'' Feb. 24, 2010. Available at http://www.sae.org/mags/AEI/7695 (last accessed Jun. 10, 2012).
---------------------------------------------------------------------------

    The second key strategy to reduce mass of an assembly or component
involves the substitution of lower density and/or higher strength
materials. Material substitution includes replacing materials, such as
mild steel, with higher-strength and advanced steels, aluminum,
magnesium, and composite materials. In practice, material substitution
tends to be quite specific to the manufacturer and situation. Some
materials work better than others for particular vehicle components,
and a manufacturer may invest more heavily in adjusting to a particular
type of advanced material, thus complicating its ability to consider
others. The agencies recognize that like any type of mass reduction,
material substitution has to be conducted not only with consideration
to maintaining equivalent component strength, but also to maintaining
all the other attributes of that component, system or vehicle, such as
crashworthiness, durability, and noise, vibration and harshness (NVH).
    If vehicle mass is reduced sufficiently through application of the
two primary strategies of using less material and material substitution
described above, secondary mass reduction options may become available.
Secondary mass reduction is enabled when the load requirements of a
component are reduced as a result of primary mass reduction. If the
primary mass reduction reaches a sufficient level, a manufacturer may
use a smaller, lighter, and potentially more efficient powertrain while
maintaining vehicle acceleration performance. If a powertrain is
downsized, a portion of the mass reduction may be attributed to the
reduced torque requirement which results from the lower vehicle mass.
The lower torque requirement enables a reduction in engine
displacement, changes to transmission torque converter and gear ratios,
and changes to final drive gear ratio. The reduced powertrain torque
enables the downsizing and/or mass reduction of powertrain components
and accompanying reduced rotating mass (e.g., for transmission,
driveshafts/halfshafts, wheels, and tires) without sacrificing
powertrain durability. Likewise, the combined mass reductions of the
engine, drivetrain, and body in turn reduce stresses on the suspension
components, steering components, wheels, tires, and brakes, which can
allow further reductions in the mass of these subsystems. Reducing the
un-sprung masses such as the brakes, control arms, wheels, and tires
further reduce stresses in the suspension mounting points, which will
allow for further optimization and potential mass reduction. However,
pickup trucks have towing and hauling requirements which must be taken
into account when determining the amount of secondary mass reduction
that is possible and so it is less than that of passenger cars.
    In 2015, EPA completed a multi-year study with FEV North America,
Inc. on the lightweighting of a light-duty pickup truck, a 2011 GMC
Silverado, titled ``Mass Reduction and Cost Analysis--Light-Duty Pickup
Trucks Model Years 2020-2025.'' \483\ Results contain a cost curve for
various mass reduction percentages with the main solution being
evaluated for a 20.8 percent (510 kg/1122 lb.) mass reduction resulting
in an increased direct incremental manufacturing cost of $2228. In
addition, the report outlines the compounding effect that occurs in a
vehicle with performance requirements including hauling and towing.
Secondary mass evaluation was performed on a component level based on
an overall 20 percent vehicle mass reduction. Results revealed 84 kg of
the 510 kg, or 20 percent of the overall mass reduction, were from
secondary mass reduction. Information on this study is summarized in
SAE paper 2015-01-0559. NHTSA has also sponsored an on-going pickup
truck lightweighting project. This project uses a more recent baseline
vehicle, a MY 2014 GMC Silverado, and the project will be finished in
2016. Both projects will be utilized for the light-duty GHG and CAFE
Midterm Evaluation mass reduction baseline characterization and may be
used to update assumptions of mass reduction for HD pickups and vans
for the final Phase 2 rulemaking.
---------------------------------------------------------------------------

    \483\ ``Mass Reduction and Cost Analysis--Light-Duty Pickup
Trucks Model Years 2020-2025,'' FEV, North America, Inc., April
2015, Document no. EPA-420-R-15-006.
---------------------------------------------------------------------------

    In order to determine if technologies identified on light duty
trucks are applicable to heavy-duty pickups, EPA contracted with FEV
North America, Inc. to perform a scaling study in order to evaluate
whether the technologies identified for the light-duty truck would be
applicable for a heavy-duty pickup truck. In this study a 2013MY
Silverado 2500, a 2007 Mercedes Sprinter and a 2010 Renault Master
\484\ were analyzed. A 2013MY Silverado 2500 was purchased and torn
down. The mass reduction results were 18.9 percent mass reduction at a
cost of $2,372 and focused on aluminum intensive with AHSS frame. The
Mercedes Sprinter and Renault Master analyses were performed based on
information from the A2Mac1 database. The results were 18.15 percent
mass reduction at a cost add of $2,293 for the Mercedes Sprinter

and 18.55 percent mass reduction at a cost add of $2,293 for the
Master.
---------------------------------------------------------------------------

    \484\ ``Mass Reduction and Cost Analysis Heavy Duty Pickup Truck
and Light Commercial Vans,'' 2016, EPA-420-D-16-003.
---------------------------------------------------------------------------

    In September 2015, Ford announced that its MY 2017 F-Series Super
duty pickup (F250) would be manufactured with an aluminum body and
overall the truck will be 350 lbs. lighter (5 percent-6 percent) than
the current generation truck with steel.485 486 This is less
overall mass reduction than the resultant lightweighting effort on the
MY 2015 F-150, which achieved up to 750 lb. decrease in curb weight (12
percent-13 percent) per vehicle.\487\ Strategies were employed by Ford
in the F250 to ``improve the productivity of the Super Duty.'' In
addition, Ford added several safety systems (and consequent mass)
including cameras, lane departure warning, brake assist, etc. More
details on the F250 will be known once it is released; however, a
review of the F150 vehicle aluminum intensive design shows that it has
an aluminum cab structure, body panels, and suspension components, as
well as a high strength steel frame and a smaller, lighter and more
efficient engine. The Executive Summary to Ducker Worldwide's 2014
report \488\ states that the MY 2015 F-150 contains 1080 lbs. of
aluminum with at least half being aluminum sheet and extrusions for
body and closures. Ford's engine range for its light duty truck fleet
includes a 2.7L EcoBoost V-6. The integrated loop, between Ford and the
aluminum sheet suppliers, of aluminum manufacturing scrap and new
aluminum sheet is integral to making aluminum a feasible lightweighting
technology option for Ford. It is also possible that the strategy of
aluminum body panels will be applied to the heavy duty F-350 version
when it is redesigned.\489\
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    \485\ http://www.techtimes.com/articles/87961/20150925/ford-s-2017-f-250-super-duty-with-an-aluminum-body-is-the-toughest-smartest-and-most-capable-super-duty-ever.htm, September 25, 2015.
    \486\ https://www.ford.com/trucks/superduty/2017/ 2017/.
    \487\ ``2008/9 Blueprint for Sustainability,'' Ford Motor
Company. Available at: http://www.ford.com/go/sustainability (last
accessed February 8, 2010).
    \488\ ``2015 North American Light Vehicle Aluminum Content
Study--Executive Summary,'' June 2014, http://www.drivealuminum.org/research-resources/PDF/Research/2014/2014-ducker-report (last
accessed February 26, 2015).
    \489\ http://www.foxnews.com/leisure/2014/09/30/ford-confirms-increased-aluminum-use-on-next-gen-super-duty-pickups/.
---------------------------------------------------------------------------

    The RIA for this rulemaking shows that 10 percent or less mass
reduction is part of the projected strategy for compliance for HD
pickups and vans. The cost and effectiveness assumptions for mass
reduction technology are described in the RIA.
(ii) Low Rolling Resistance Tires
    Tire rolling resistance is the frictional loss associated mainly
with the energy dissipated in the deformation of the tires under load
and thus influences fuel efficiency and CO2 emissions. Other
tire design characteristics (e.g., materials, construction, and tread
design) influence durability, traction (both wet and dry grip), vehicle
handling, and ride comfort in addition to rolling resistance. A typical
LRR tire's attributes will include: Increased tire inflation pressure,
material changes, and tire construction with less hysteresis, geometry
changes (e.g., reduced aspect ratios), and reduction in sidewall and
tread deflection. These changes will generally be accompanied with
additional changes to suspension tuning and/or suspension design.
(iii) Aerodynamic Drag Reduction
    Many factors affect a vehicle's aerodynamic drag and the resulting
power required to move it through the air. While these factors change
with air density and the square and cube of vehicle speed,
respectively, the overall drag effect is determined by the product of
its frontal area and drag coefficient, Cd. Reductions in these
quantities can therefore reduce fuel consumption and CO2
emissions. Although frontal areas tend to be relatively similar within
a vehicle class (mostly due to market-competitive size requirements),
significant variations in drag coefficient can be observed. Significant
changes to a vehicle's aerodynamic performance may need to be
implemented during a redesign (e.g., changes in vehicle shape).
However, shorter-term aerodynamic reductions, with a somewhat lower
effectiveness, may be achieved through the use of revised exterior
components (typically at a model refresh in mid-cycle) and add-on
devices that currently being applied. The latter list will include
revised front and rear fascias, modified front air dams and rear
valances, addition of rear deck lips and underbody panels, and lower
aerodynamic drag exterior mirrors.
(f) Air Conditioning Technologies
    These technologies include improved hoses, connectors and seats for
leakage control. They also include improved compressors, expansion
valves, heat exchangers and the control of these components for the
purposes of improving tailpipe CO2 emissions as a result of
A/C use.\490\
---------------------------------------------------------------------------

    \490\ See RIA Chapter 2.3 for more detailed technology
descriptions.
---------------------------------------------------------------------------

(5) How did the agencies determine the costs and effectiveness of each
of these technologies?
    Building on the technical analysis underlying the 2017-2025 MY
light-duty vehicle rule, the 2014-2018 MY heavy-duty vehicle rule, and
the 2015 NHTSA Technology Study, the agencies took a fresh look at
technology cost and effectiveness values for purposes of this rule. For
costs, the agencies reconsidered both the direct (or ``piece'') costs
and indirect costs of individual components of technologies. For the
direct costs, the agencies followed a bill of materials (BOM) approach
employed by the agencies in the light-duty rule as well as referencing
costs from the 2014-2018 MY heavy-duty vehicle rule and a new cost
survey performed by Tetra Tech in 2014.
    For two technologies, stoichiometric gasoline direct injection
(SGDI) and turbocharging with engine downsizing, the agencies relied to
the extent possible on the available tear-down data and scaling
methodologies used in EPA's ongoing study with FEV, Incorporated. This
study consists of complete system tear-down to evaluate technologies
down to the nuts and bolts to arrive at very detailed estimates of the
costs associated with manufacturing them.\491\
---------------------------------------------------------------------------

    \491\ U.S. Environmental Protection Agency, ``Draft Report--
Light-Duty Technology Cost Analysis Pilot Study,'' Contract No. EP-
C-07-069, Work Assignment 1-3, September 3, 2009.
---------------------------------------------------------------------------

    For the other technologies, considering all sources of information
and using the BOM approach, the agencies worked together intensively to
determine component costs for each of the technologies and build up the
costs accordingly. Where estimates differ between sources, we have used
engineering judgment to arrive at what we believe to be the best cost
estimate available today, and explained the basis for that exercise of
judgment.
    Once costs were determined, they were adjusted to ensure that they
were all expressed in 2012 dollars, and indirect costs were accounted
for using a methodology consistent with the new ICM approach developed
by EPA and used in the Phase 1 rule, and the 2012-2016 and 2017-2025
light-duty rules. NHTSA and EPA also reconsidered how costs should be
adjusted by modifying or scaling content assumptions to account for
differences across the range of vehicle sizes and functional
requirements, and adjusted the associated material cost impacts to
account for the revised content. We present the individual technology
costs used in this analysis in Chapter 2.11 of the RIA.

    Regarding estimates for technology effectiveness, the agencies used
the estimates from the 2014 Southwest Research Institute study as a
baseline, which was designed specifically to inform this rulemaking. In
addition, the agencies used 2017-2025 light-duty rule as a reference,
and adjusted these estimates as appropriate, taking into account the
unique requirement of the heavy-duty test cycles to test at curb weight
plus half payload versus the light-duty requirement of curb plus 300
lbs. The adjustments were made on an individual technology basis by
assessing the specific impact of the added load on each technology when
compared to the use of the technology on a light-duty vehicle. The
agencies also considered other sources such as the 2010 NAS Report,
recent compliance data, and confidential manufacturer estimates of
technology effectiveness. The agencies reviewed effectiveness
information from the multiple sources for each technology and ensured
that such effectiveness estimates were based on technology hardware
consistent with the BOM components used to estimate costs. Together,
the agencies compared the multiple estimates and assessed their
validity, taking care to ensure that common BOM definitions and other
vehicle attributes such as performance and drivability were taken into
account.
    The agencies note that the effectiveness values estimated for the
technologies may represent average values applied to the baseline fleet
described earlier, and do not reflect the potentially limitless
spectrum of possible values that could result from adding the
technology to different vehicles. For example, while the agencies have
estimated an effectiveness of 0.5 percent for low friction lubricants,
each vehicle could have a unique effectiveness estimate depending on
the baseline vehicle's oil viscosity rating. Similarly, the reduction
in rolling resistance (and thus the improvement in fuel efficiency and
the reduction in CO2 emissions) due to the application of
LRR tires depends not only on the unique characteristics of the tires
originally on the vehicle, but on the unique characteristics of the
tires being applied, characteristics which must be balanced between
fuel efficiency, safety, and performance. Aerodynamic drag reduction is
much the same--it can improve fuel efficiency and reduce CO2
emissions, but it is also highly dependent on vehicle-specific
functional objectives. For purposes of this final rule, the agencies
believe that employing average values for technology effectiveness
estimates is an appropriate way of recognizing the potential variation
in the specific benefits that individual manufacturers (and individual
vehicles) might obtain from adding a fuel-saving technology.
    The assessment of the technology effectiveness and costs was
determined from a combination of sources. First an assessment was
performed by SwRI under contract with the agencies to determine the
effectiveness and costs on several technologies that were generally not
considered in the Phase 1 GHG rule time frame. Some of the technologies
were common with the light-duty assessment but the effectiveness and
costs of individual technologies were appropriately adjusted to match
the expected effectiveness and costs when implemented in a heavy-duty
application. Finally, the agencies performed extensive outreach to
suppliers of engine, transmission and vehicle technologies applicable
to heavy-duty applications to get industry input on cost and
effectiveness of potential GHG and fuel consumption reducing
technologies. The agencies did not receive comments disputing the
expected technology effectiveness values or costs developed with input
from industry.
    To achieve the levels of the Phase 2 standards for gasoline and
diesel powered heavy-duty vehicles, a combination of the technologies
previously discussed will be required respective to unique gasoline and
diesel technologies and their challenges. Although some of the
technologies may already be implemented in a portion of heavy-duty
vehicles, none of the technologies discussed are considered ubiquitous
in the heavy-duty fleet. Also, as will be expected, the available test
data show that some vehicle models will not need the full complement of
available technologies to achieve these standards. Furthermore, many
technologies can be further improved (e.g., aerodynamic improvements)
from today's best levels, and so allow for compliance without needing
to apply a technology that a manufacturer might deem less desirable.
    Technology costs for HD pickups and vans are shown in Table VI-4.
These costs reflect direct and indirect costs to the vehicle
manufacturer for the 2021 model year. See Chapter 2.11. of the RIA for
a more complete description of the basis of these costs.

Table VI-4--Technology Costs for HD Pickups & Vans Inclusive of Indirect
                        Cost Markups for MY 2021
                                 [2012$]
------------------------------------------------------------------------
               Technology                    Gasoline         Diesel
------------------------------------------------------------------------
Engine changes to accommodate low                      6               6
 friction lubes.........................
Engine friction reduction--level 1......             116             116
Engine friction reduction--level 2......             254             254
Dual cam phasing........................             183             183
Cylinder deactivation...................             196             N/A
Stoichiometric gasoline direct injection             451             N/A
Turbo improvements......................             N/A              16
Cooled EGR..............................             373             373
Turbocharging & downsizing \a\..........             671             N/A
``Right-sized'' diesel from larger                   N/A               0
 diesel.................................
8s automatic transmission (increment to              457             457
 6s automatic transmission).............
Improved accessories--level 1...........              82              82
Improved accessories--level 2...........             132             132
Low rolling resistance tires--level 1...              10              10
Passive aerodynamic improvements (aero                51              51
 1).....................................
Passive plus Active aerodynamic                      230             230
 improvements (aero 2)..................
Electric (or electro/hydraulic) power                151             151
 steering...............................
Mass reduction (10% on a 6500 lb                     318             318
 vehicle)...............................
Driveline friction reduction............             139             139
Stop-start (no regenerative braking)....             539             539
Mild HEV................................            2730            2730

Strong HEV, without inclusion of any                6779            6779
 engine changes.........................
------------------------------------------------------------------------
Note:
\a\ Cost to downsize from a V8 OHC to a V6 OHC engine with twin turbos.

    As explained above, the CAFE model works by adding technologies in
an incremental fashion to each particular vehicle in a manufacturer's
fleet until that fleet complies with the imposed standards. It does
this by following a predefined set of decision trees whereby the
particular vehicle is placed on the appropriate decision tree and it
follows the predefined progression of technology available on that
tree. At each step along the tree, a decision is made regarding the
cost of a given technology relative to what already exists on the
vehicle along with the fuel consumption improvement it provides
relative to the fuel consumption at the current location on the tree,
prior to deciding whether to take that next step on the tree or remain
in the current location. Because the model works in this way, the input
files must be structured to provide costs and effectiveness values for
each technology relative to whatever technologies have been added in
earlier steps along the tree. Table VI-5 presents the cost and
effectiveness values used in the CAFE model input files.

             Table VI-5--CAFE Model Input Values for Cost & Effectiveness for Given Technologies \a\
----------------------------------------------------------------------------------------------------------------
                                                                          Incremental cost (2012$) a b c
                   Technology                     FC savings (%) -----------------------------------------------
                                                                       2021            2025            2027
----------------------------------------------------------------------------------------------------------------
Improved Lubricants and Engine Friction                     1.60              24              24              23
 Reduction......................................
Coupled Cam Phasing (SOHC)......................            3.82              48              43              39
Dual Variable Valve Lift (SOHC).................            2.47              42              37              34
Cylinder Deactivation (SOHC)....................            3.70              34              30              27
Intake Cam Phasing (DOHC).......................            0.00              48              43              39
Dual Cam Phasing (DOHC).........................            3.82              46              40              37
Dual Variable Valve Lift (DOHC).................            2.47              42              37              34
Cylinder Deactivation (DOHC)....................            3.70              34              30              27
Stoichiometric Gasoline Direct Injection (OHC)..            0.50              71              61              56
Cylinder Deactivation (OHV).....................            3.90             216             188             172
Variable Valve Actuation (OHV)..................            6.10              54              47              43
Stoichiometric Gasoline Direct Injection (OHV)..            0.50              71              61              56
Engine Turbocharging and Downsizing
    Small Gasoline Engines......................            8.00             518             441             407
    Medium Gasoline Engines.....................            8.00             -12             -62             -44
    Large Gasoline Engines......................            8.00             623             522             456
Cooled Exhaust Gas Recirculation................            3.04             382             332             303
Cylinder Deactivation on Turbo/downsized Eng....            1.70              33              29              26
Lean-Burn Gasoline Direct Injection.............            4.30           1,758           1,485           1,282
Improved Diesel Engine Turbocharging............            2.51              22              19              18
Engine Friction & Parasitic Reduction
    Small Diesel Engines........................            3.50             269             253             213
    Medium Diesel Engines.......................            3.50             345             325             273
    Large Diesel Engines........................            3.50             421             397             334
Downsizing of Diesel Engines (V6 to I-4)........           11.10               0               0               0
8-Speed Automatic Transmission \d\..............            5.00             482             419             382
Electric Power Steering.........................            1.00             160             144             130
Improved Accessories (Level 1)..................            0.93              93              83              75
Improved Accessories (Level 2)..................            0.93              57              54              46
Stop-Start System...............................            1.10             612             517             446
Integrated Starter-Generator....................            3.20           1,040             969             760
Strong Hybrid Electric Vehicle..................           17.20           3,038           2,393           2,133
Mass Reduction (5%).............................            1.50            0.28            0.24            0.21
Mass Reduction (additional 5%)..................            1.50            0.87            0.75            0.66
Reduced Rolling Resistance Tires................            1.10              10               9               9
Low-Drag Brakes.................................            0.40             106             102             102
Driveline Friction Reduction....................            0.50             153             137             124
Aerodynamic Improvements (10%)..................            0.70              58              52              47
Aerodynamic Improvements (add'l 10%)............            0.70             193             182             153
----------------------------------------------------------------------------------------------------------------
Notes:
\a\ Values for other model years available in CAFE model input files available at NHTSA Web site.
\b\ For mass reduction, cost reported on mass basis (per pound of curb weight reduction).
\c\ The model output has been adjusted to 2013$.
\d\ 8-speed automatic transmission costs include costs for high efficiency gearbox and aggressive shift logic
  whereas those costs were kept separate in prior analyses.

    In addition to the base technology cost and effectiveness inputs
described above, the CAFE model accommodates inputs to adjust
accumulated effectiveness under circumstances when combining multiple
technologies could result in underestimation or overestimation of total
incremental effectiveness relative to an ``unevolved'' baseline
vehicle. These so-called synergy factors may be positive, where the
combination of the technologies results in greater improvement than the
additive improvement of each technology, or negative, where the
combination of the technologies is lower than the additive improvement
of each technology. The synergy factors used in the NPRM and Method B
of the FRM are described in Table VI-6 Method A of the FRM uses
synergies derived from a simulation project NHTSA undertook with
Autnomie Argonne National Lab. A description of these changes is given
in Section D.(8).

                Table VI-6--Technology Pair Effectiveness Synergy Factors for HD Pickups and Vans
----------------------------------------------------------------------------------------------------------------
                                                  Adjustment                                        Adjustment
                Technology pair                       (%)                Technology pair                (%)
----------------------------------------------------------------------------------------------------------------
8SPD/CCPS.....................................           -4.60  IATC/CCPS.......................           -1.30
8SPD/DEACO....................................           -4.60  IATC/DEACO......................           -1.30
8SPD/ICP......................................           -4.60  IATC/ICP........................           -1.30
8SPD/TRBDS1...................................            4.60  IATC/TRBDS1.....................            1.30
AERO2/SHEV1...................................            1.40  MR1/CCPS........................            0.40
CCPS/IACC1....................................           -0.40  MR1/DCP.........................            0.40
CCPS/IACC2....................................           -0.60  MR1/VVA.........................            0.40
DCP/IACC1.....................................           -0.40  MR2/ROLL1.......................           -0.10
DCP/IACC2.....................................           -0.60  MR2/SHEV1.......................           -0.40
DEACD/IATC....................................           -0.10  NAUTO/CCPS......................           -1.70
DEACO/IACC2...................................           -0.80  NAUTO/DEACO.....................           -1.70
DEACO/MHEV....................................           -0.70  NAUTO/ICP.......................           -1.70
DEACS/IATC....................................           -0.10  NAUTO/SAX.......................           -0.40
DTURB/IATC....................................            1.00  NAUTO/TRBDS1....................            1.70
DTURB/MHEV....................................           -0.60  ROLL1/AERO1.....................            0.10
DTURB/SHEV1...................................           -1.00  ROLL1/SHEV1.....................            1.10
DVVLD/8SPD....................................           -0.60  ROLL2/AERO2.....................            0.20
DVVLD/IACC2...................................           -0.80  SHFTOPT/MHEV....................           -0.30
DVVLD/IATC....................................           -0.60  TRBDS1/MHEV.....................            0.80
DVVLD/MHEV....................................           -0.70  TRBDS1/SHEV1....................           -3.30
DVVLS/8SPD....................................           -0.60  TRBDS1/VVA......................           -8.00
DVVLS/IACC2...................................           -0.80  TRBDS2/EPS......................           -0.30
DVVLS/IATC....................................           -0.50  TRBDS2/IACC2....................           -0.30
DVVLS/MHEV....................................           -0.70  TRBDS2/NAUTO....................           -0.50
                                                ..............  VVA/IACC1.......................           -0.40
                                                ..............  VVA/IACC2.......................           -0.60
                                                ..............  VVA/IATC........................           -0.60
----------------------------------------------------------------------------------------------------------------

    The CAFE model also accommodates inputs to adjust accumulated
incremental costs under circumstances when the application sequence
could result in underestimation or overestimation of total incremental
costs relative to an ``unevolved'' baseline vehicle. For today's
analysis, the agencies have applied one such adjustment, increasing the
cost of medium-sized gasoline engines by $513 in cases where
turbocharging and engine downsizing is applied with variable valve
actuation.
    The analysis performed using Method A also applied cost inputs to
address some costs encompassed neither by the agencies' estimates of
the direct cost to apply these technologies, nor by the agencies'
methods for ``marking up'' these costs to arrive at increases in the
new vehicle purchase costs. To account for the additional costs that
could be incurred if a technology is applied and then quickly replaced,
the CAFE model accommodates inputs specifying a ``stranded capital
cost'' specific to each technology. For this analysis, the model was
run with inputs to apply about $78 of additional cost (per engine) if
gasoline engine turbocharging and downsizing (separately for each
``level'' considered) is applied and then immediately replaced,
declining steadily to zero by the tenth model year following initial
application of the technology. The model also accommodates inputs
specifying any additional changes owners might incur in maintenance and
post-warranty repair costs. For this analysis, the model was run with
inputs indicating that vehicles equipped with less rolling-resistant
tires could incur additional tire replacement costs equivalent to $21-
$23 (depending on model year) in additional costs to purchase the new
vehicle. The agencies did not, however, include inputs specifying any
potential changes repair costs that might accompany application of any
of the above technologies. A sensitivity analysis using Method A,
discussed below, includes a case in which repair costs are estimated
using factors consistent with those underlying the indirect cost
multipliers used to markup direct costs for the agencies' central
analysis.
(6) Regulatory Alternatives Considered by the Agencies
    As discussed above, the model considers regulatory alternatives.
The results of regulatory alternatives are considered relative to a
``no action'' alternative where existing standards persist, but no
further regulatory action is taken (in this case the MY 2018 standards
from Phase I are the last regulatory action taken). The agencies also
considered four regulatory alternatives. The preferred alternative with
a standard that increases 2.5 percent in stringency annually for MY's
2021-2027, and three others with annual increases in stringency of: 2.0
percent, 3.5 percent, and 4.0 percent for MY's 2021-2025. For each of
the ``action alternatives'' (i.e., those involving stringency increases
beyond the no-action alternative), the annual

stringency increases are applied as follows: An annual stringency
increase of r is applied by multiplying the model year 2020 target
functions (identical to those applicable to model year 2018) by 1-r to
define the model year 2021 target functions, multiplying the model year
2021 target functions by 1-r to define the model year 2022 target
functions, continuing through 2025 for all alternatives except for the
preferred Alternative 3 which extends through 2027. In summary, the
agencies have considered the following five regulatory alternatives in
the CAFE model.

                                 Table VI-7--Considered Regulatory Alternatives
----------------------------------------------------------------------------------------------------------------
                                                               Annual stringency increase
        Regulatory alternative        --------------------------------------------------------------------------
                                              2019-2020                2021-2025                2026-2027
----------------------------------------------------------------------------------------------------------------
1: No Action.........................  None...................  None...................  None.
2: 2.0%/y............................  None...................  2.0%...................  None.
3: 2.5%/y............................  None...................  2.5%...................  2.5%
4: 3.5%/y............................  None...................  3.5%...................  None.
5: 4.0%/y............................  None...................  4.0%...................  None.
----------------------------------------------------------------------------------------------------------------

(7) NPRM Modifications of the Model
    The NPRM analysis (and the current analysis) reflect several
changes made to the model since 2012, when NHTSA used the model to
estimate the effects, costs, and benefits of final CAFE standards for
light-duty vehicles produced during MYs 2017-2021, and augural
standards for MYs 2022-2025. Some of these changes specifically enable
analysis of potential fuel consumption standards (and, hence,
CO2 emissions standards harmonized with fuel consumption
standards) for heavy-duty pickups and vans; other changes implement
more general improvements to the model. Key changes include the
following:
     Changes to accommodate standards for heavy-duty pickups
and vans, including attribute-based standards involving targets that
vary with ``work factor.''
     Explicit calculation of test weight, taking into account
test weight ``bins'' and differences in the definition of test weight
for light-duty vehicles (curb weight plus 300 pound) and heavy-duty
pickups and vans (average of GVWR and curb weight).
     Procedures to estimate increases in payload when curb
weight is reduced, increases in towing capacity if GVWR is reduced, and
calculation procedures to correspondingly update calculated work
factors.
     Expansion of model inputs, procedures, and outputs to
accommodate technologies not included in prior analyses.
     Changes to the algorithm used to apply technologies,
enabling more explicit accounting for shared vehicle platforms and
adoption and ``inheritance'' of major engine changes.
    These changes are reflected in updated model documentation
available at NHTSA's Web site, the documentation also providing more
information about the model's purpose, scope, structure, design,
inputs, operation, and outputs. The agencies invited but did not
receive comments on the CAFE model used for the NPRM analysis and used
in this final rule for the Method B analysis.
(a) Product Cadence
    Past comments on the CAFE model have stressed the importance of
product cadence--i.e., the development and periodic redesign and
freshening of vehicles--in terms of involving technical, financial, and
other practical constraints on applying new technologies, and NHTSA has
steadily made changes to the model with a view toward accounting for
these considerations. For example, early versions of the model added
explicit ``carrying forward'' of applied technologies between model
years, subsequent versions applied assumptions that most technologies
would be applied when vehicles are freshened or redesigned, and more
recent versions applied assumptions that manufacturers would sometimes
apply technology earlier than ``necessary'' in order to facilitate
compliance with standards in ensuing model years. Thus, for example, if
a manufacturer is expected to redesign many of its products in model
years 2018 and 2023, and the standard's stringency increases
significantly in model year 2021, the CAFE model will estimate the
potential that the manufacturer will add more technology than necessary
for compliance in MY 2018, in order to carry those product changes
forward through the next redesign and contribute to compliance with the
MY 2021 standard.
    The model also accommodates estimates of overall limits (expressed
as ``phase-in caps'' in model inputs) on the rates at which
manufacturers' may practicably add technology to their respective
fleets. So, for example, even if a manufacturer is expected to redesign
half of its production in MY 2016, if the manufacturer is not already
producing any strong hybrid electric vehicles (SHEVs), a phase-in cap
can be specified in order to assume that manufacturer will stop
applying SHEVs in MY 2016 once it has done so to at least 3 percent of
its production in that model year.
    After the light-duty rulemaking analysis accompanying the 2012
final rule regarding post-2016 CAFE standards and related GHG emissions
standards, NHTSA staff began work on CAFE model changes expected to
better reflect additional considerations involved with product planning
and cadence. These changes, summarized below, interact with preexisting
model characteristics discussed above.
(b) Platforms and Technology
    The term ``platform'' is used loosely in industry, but generally
refers to a common structure shared by a group of vehicle variants. The
degree of commonality varies, with some platform variants exhibiting
traditional ``badge engineering'' where two products are differentiated
by little more than insignias, while other platforms be used to produce
a broad suite of vehicles that bear little outer resemblance to one
another.
    Given the degree of commonality between variants of a single
platform, manufacturers do not have complete freedom to apply
technology to a vehicle: while some technologies (e.g. low rolling
resistance tires) are very nearly ``bolt-on'' technologies, others
involve substantial changes to the structure and design of the vehicle,
and therefore necessarily are constant between vehicles that share a
common platform. NHTSA staff has, therefore, modified the CAFE model
such that all mass reduction and aero technologies are forced to be
constant between variants of a platform. The agencies requested but did
not receive comment on the suitability of this viewpoint, and

which technologies can deviate from one platform variant to another.
    Within the analysis fleet, each vehicle is associated with a
specific platform. As the CAFE model applies technology, it first
defines a platform ``leader'' as the vehicle variant of a platform with
the highest technology utilization vehicle of mass reduction and
aerodynamic technologies. As the vehicle applies technologies, it
effectively harmonizes to the highest common denominator of the
platform. If there is a tie, the CAFE model begins applying aerodynamic
and mass reduction technology to the vehicle with the lowest average
sales across all available model years. If there remains a tie, the
model begins by choosing the vehicle with the highest average MSRP
across all available model years. The model follows this formulation
due to previous market trends suggesting that many technologies begin
deployment at the high-end, low-volume end of the market as
manufacturers build their confidence and capability in a technology,
and later expand the technology across more mainstream product lines.
    In the HD pickup and van market, there is a relatively small amount
of diversity in platforms produced by manufacturers: Typically 1-2
truck platforms and 1-2 van platforms. However, accounting for
platforms will take on greater significance in future analyses
involving the light-duty fleet. The agency requested but did not
receive comments on the general use of platforms within CAFE
rulemaking.
(c) Engine and Transmission Inheritance
    In practice, manufacturers are limited in the number of engines and
transmissions that they produce. Typically a manufacturer produces a
number of engines--perhaps six or eight engines for a large
manufacturer--and tunes them for slight variants in output for a
variety of car and truck applications. Manufacturers limit complexity
in their engine portfolio for much the same reason as they limit
complexity in vehicle variants: They face engineering manpower
limitations, and supplier, production and service costs that scale with
the number of parts produced.
    In previous usage of the CAFE model, engines and transmissions in
individual models were allowed relative freedom in technology
application, potentially leading to solutions that would, if followed,
involve unaccounted-for costs associated with increased complexity in
the product portfolio. The lack of a constraint in this area allowed
the model to apply different levels of technology to the engine in each
vehicle at the time of redesign or refresh, independent of what was
done to other vehicles using a previously identical engine.
    In the current version of the CAFE model, engines and transmissions
that are shared between vehicles must apply the same levels of
technology in all technologies dictated by engine or transmission
inheritance. This forced adoption is referred to as ``engine
inheritance'' in the model documentation.
    As with platform-shared technologies, the model first chooses an
``engine leader'' among vehicles sharing the same engine. The leader is
selected first by the vehicle with the lowest average sales across all
available model years. If there is a tie, the vehicle with the highest
average MSRP across model years is chosen. The model applies the same
logic with respect to the application of transmission changes. As with
platforms, this is driven by the concept that vehicle manufacturers
typically deploy new technologies in small numbers prior to deploying
widely across their product lines.
(d) Interactions Between Regulatory Classes
    Like earlier versions, the current CAFE model provides for
integrated analysis spanning different regulatory classes, accounting
both for standards that apply separately to different classes and for
interactions between regulatory classes. Light vehicle CAFE standards
are specified separately for passenger cars and light trucks. However,
there is considerable sharing between these two regulatory classes.
Some specific engines and transmissions are used in both passenger cars
and light trucks, and some vehicle platforms span these regulatory
classes. For example, some sport-utility vehicles are offered in 2WD
versions classified as passenger cars and 4WD versions classified as
light trucks. Integrated analysis of manufacturers' passenger car and
light truck fleets provides the ability to account for such sharing and
reduce the likelihood of finding solutions that could involve
impractical levels of complexity in manufacturers' product lines. In
addition, integrated analysis provides the ability to simulate the
potential that manufactures could earn CAFE credits by over complying
with one standard and use those credits toward compliance with the
other standard (i.e., to simulate credit transfers between regulatory
classes).
    HD pickups and vans are regulated separately from light-duty
vehicles. While manufacturers cannot transfer credits between light-
duty and MDHD classes, there is some sharing of engineering and
technology between light-duty vehicles and HD pickups and vans. For
example, some passenger vans with GVWR over 8,500 lbs. are classified
as medium-duty passenger vehicles (MDPVs) and thus included in
manufacturers' light-duty truck fleets, while cargo vans sharing the
same nameplate are classified as HD vans.
(e) Phase-In Caps
    The CAFE model retains the ability to use phase-in caps (specified
in model inputs) as proxies for a variety of practical restrictions on
technology application. Unlike vehicle-specific restrictions related to
redesign, refreshes or platforms/engines, phase-in caps constrain
technology application at the vehicle manufacturer level. They are
intended to reflect a manufacturer's overall resource capacity
available for implementing new technologies (such as engineering and
development personnel and financial resources), thereby ensuring that
resource capacity is accounted for in the modeling process.
    In previous CAFE rulemakings, redesign/refresh schedules and phase-
in caps were the primary mechanisms to reflect an OEM's limited pool of
available resources during the rulemaking time frame and the years
leading up to the rulemaking time frame, especially in years where many
models may be scheduled for refresh or redesign. The newly-introduced
representation platform-, engine-, and transmission-related
considerations discussed above augment the model's preexisting
representation of redesign cycles and accommodation of phase-in caps.
Considering these new constraints, inputs for today's analysis de-
emphasize reliance on phase-in caps.
    In the NPRM and Method B of the FRM application of the CAFE model,
phase-in caps are used only for the most advanced technologies included
in the analysis, i.e., SHEVs and lean-burn GDI engines, considering
that these technologies are most likely to involve implementation costs
and risks not otherwise accounted for in corresponding input estimates
of technology cost. For these two technologies, the agencies have
applied caps that begin at 3 percent (i.e., 3 percent of the
manufacturer's production) in MY 2017, increase at 3 percent annually
during the ensuing nine years (reaching 30 percent in the MY 2026), and
subsequently increasing at 5 percent annually for four years (reaching
50 percent in MY 2030). Note that the agencies did not feel that lean-
burn engines were feasible in the

timeframe of this rulemaking, so decided to reject any model runs where
they were selected. (In any case, due to the cost ineffectiveness of
this technology, it was never chosen). The agencies did not receive
comments specifically on this approach for phase-in caps. The agencies
received comments regarding the general feasibility of SHEVs in this
market segment, with some commenters commenting that SHEVs are not
feasible for HD pickups and vans. These comments are discussed in
Section C.8. While the agencies have retained the above approach for
SHEV phase-in caps, the agencies have conducted a sensitivity analysis
setting the SHEV caps at zero, showing that the Phase 2 standards are
feasible and appropriate without the use of SHEVs. This sensitivity
analysis is described in Section E.
    For Method A of the NPRM the phase-in caps have been set to 100
percent, so that the model no longer relies on phase-in caps to limit
the early-year application of advanced technologies. This changes is
further described in the Method B of the FRM specific section below.
(f) Impact of Vehicle Technology Application Requirements
    Compared to prior analyses of light-duty standards, these model
changes, along with characteristics of the HD pickup and van fleet
result in some changes in the broad characteristics of the model's
application of technology to manufacturers' fleets. First, since the
number of HD pickup and van platforms in a portfolio is typically
small, compliance with standards may appear especially ``lumpy''
(compared to previous applications of the CAFE model to the more highly
segmented light-duty fleet), with significant over compliance when
widespread redesigns precede stringency increases, and/or significant
application of carried-forward (aka ``banked'') credits.
    Second, since the use of phase-in caps has been de-emphasized and
manufacturer technology deployment remains tied strongly to estimated
product redesign and freshening schedules, technology penetration rates
may jump more quickly as manufacturers apply technology to high-volume
products in their portfolio.
    By design, restrictions that enforce commonality of mass reduction
and aerodynamic technologies on variants of a platform, and those that
enforce engine inheritance, will result in fewer vehicle-technology
combinations in a manufacturer's future modeled fleet. These
restrictions are expected to more accurately capture the true costs
associated with producing and maintaining a product portfolio.
(g) Accounting for Test Weight, Payload, and Towing Capacity
    As mentioned above, NHTSA has also revised the CAFE model to
explicitly account for the regulatory ``binning'' of test weights used
to certify light-duty fuel economy and HD pickup and van fuel
consumption for purposes of evaluating fleet-level compliance with fuel
economy and fuel consumption standards. For HD pickups and vans, test
weight (TW) is based on adjusted loaded vehicle weight (ALVW), which is
defined as the average of gross vehicle weight rating (GVWR) and curb
weight (CW). TW values are then rounded, resulting in TW ``bins'':

ALVW <= 4,000 lb.: TW rounded to nearest 125 lb.
4000 lb. < ALVW <= 5,500 lb.: TW rounded to nearest 250 lb.
ALVW > 5,500 lb.: TW rounded to nearest 500 lb.

    This ``binning'' of TW is relevant to calculation of fuel
consumption reductions accompanying mass reduction. Model inputs for
mass reduction (as an applied technology) are expressed in terms of a
percentage reduction of curb weight and an accompanying estimate of the
percentage reduction in fuel consumption, setting aside rounding of
test weight. Therefore, to account for rounding of test weight, NHTSA
has modified these calculations as follows:
[GRAPHIC] [TIFF OMITTED] TR25OC16.013

Where:

[Delta]CW = % change in curb weight (from model input),
[Delta]FCunrounded_TW = % change in fuel consumption
(from model input), without TW rounding,
[Delta]TW = % change in test weight (calculated), and
[Delta]FCrounded_TW = % change in fuel consumption
(calculated), with TW rounding.

    As a result, some applications of vehicle mass reduction will
produce no compliance benefit at all, in cases where the changes in
ALVW are too small to change test weight when rounding is taken into
account. On the other hand, some other applications of vehicle mass
reduction will produce significantly more compliance benefit than when
rounding is not taken into account, in cases where even small changes
in ALVW are sufficient to cause vehicles' test weights to increase by,
e.g., 500 lbs. when rounding is accounted for. Model outputs now
include initial and final TW, GVWR, and GCWR (and, as before, CW) for
each vehicle model in each model year. The agencies invited but did not
receive comment on how TW is modeled.
    In addition, considering that the regulatory alternatives in the
agencies' analysis all involve attribute-based standards in which
underlying fuel consumption targets vary with ``work factor'' (defined
by the agencies as the sum of three quarters of payload, one quarter of
towing capacity, and 500 lb. for vehicles with 4WD), NHTSA has modified
the CAFE model to apply inputs defining shares of curb weight reduction
to be ``returned'' to payload and shares of GVWR reduction to be
returned to towing capacity. The standards' dependence on work factor
provides some incentive to increase payload and towing capacity, both
of which are buyer-facing measures of vehicle utility. In the agencies'
judgment, this provides reason to assume that if vehicle mass is
reduced, manufacturers are likely to ``return'' some of the change to
payload and/or towing capacity. For this analysis, the agencies have
applied the following assumptions:
     GVWR will be reduced by half the amount by which curb
weight is reduced. In other words, 50 percent of the curb weight
reduction will be returned to payload.
     GCWR will not be reduced. In other words, 100 percent of
any GVWR reduction will be returned to towing capacity.
     GVWR/CW and GCWR/GVWR will not increase beyond levels
observed among the majority of similar vehicles (or, for outlier
vehicles, initial values):

    Table VI-8 Ratios for Modifying GVW and GCW as a Function of Mass
                                Reduction
------------------------------------------------------------------------
                                              Maximum ratios assumed
                                             enabled by mass reduction
                  Group                  -------------------------------
                                              GVWR/CW        GCWR/GVWR
------------------------------------------------------------------------
Unibody.................................            1.75            1.50
Gasoline pickups > 13k GVWR.............            2.00            1.50
Other gasoline pickups..................            1.75            2.25
Diesel SRW pickups......................            1.75            2.50
All other...............................            1.75            2.25
------------------------------------------------------------------------

    The first of two of these inputs are specified along with standards
for each regulatory alternative, and the GVWR/CW and GCWR/GVWR ``caps''
are specified separately for each vehicle model in the analysis fleet.
    In addition, NHTSA has changed the model to prevent HD pickup and
van GVWR from falling below 8,500 lbs. when mass reduction is applied
(because doing so will cause vehicles to be reclassified as light-duty
vehicles), and to treat any additional mass for hybrid electric
vehicles as reducing payload by the same amount (e.g., if adding a
strong HEV package to a vehicle involves a 350 pound penalty, GVWR is
assumed to remain unchanged, such that payload is also reduced by 350
lbs).
    The agencies invited but did not receive comment on estimating how
changes in vehicle mass may impact fuel consumption, GVWR, and GCWR.
(8) Subsequent Changes to the CAFE Model (for Method A)
    Since issuing the NPRM, NHTSA has made further changes to the CAFE
model, in order to estimate the potential impacts of simultaneous
standards for both light-duty vehicles and HD pickups and vans. Among
the updates most relevant to analysis supporting the final standards
for HD pickups and vans, the current model: includes refinements to
enable accounting for platforms, engines, and transmissions sharing
between light-duty and HD pickups and vans; reflects refinements to how
models for the first application of new technology are identified among
shared platforms, engines, and transmissions; allows payback period,
discount rate, survival rates, and mileage accumulation schedules to be
specified separately for each vehicle class; makes use of large scale
simulation modeling to more accurately account for synergies among
technologies to estimate the fuel consumption impact of different
combinations of technologies; provides the ability to selectively
exclude fine payment from the ``effective cost'' calculation used to
simulation manufacturers' decisions regarding the application of fuel-
saving technologies; and expands the use of forward planning to
estimate decisions to use credits that would otherwise expire. Changes
to the CAFE model are discussed at greater length below and in the CAFE
model documentation.
    Also since issuing the NPRM, NHTSA has revised many model inputs to
reflect information that has become available since the proposal. Among
the updates most relevant to analysis supporting the final rule, these
inputs reflect: an updated vehicle-level market forecast based on data
regarding the 2015 model year fleet and a new commercially-available
manufacturer- and segment-level market forecast, and spanning light-
duty vehicles and HD pickups and vans; newer fuel prices and total
vehicle production volumes from the Energy Information Administration's
Annual Energy Outlook 2015; a database, based on a large-scale full
vehicle simulation study, of estimates of the effect of thousands of
different combinations of technologies on fuel consumption; and updated
mileage accumulation schedules based on a database of more than 70
million odometer readings.
    NHTSA implemented these changes to the CAFE model and accompanying
inputs to support both today's final rule promulgating new fuel
consumption standards for HD pickups and vans and the Draft Technical
Assessment Report regarding agency's consideration of CAFE standards
for light duty vehicles for model years 2022-2025. This provided a
basis to analyze the fleets simultaneously, accounting for interactions
between the fleets; the draft RIA (p. 10-18) accompanying the NPRM
identified this as a planned improvement for the final rule, and some
stakeholders' comments (e.g., CARB,\492\ UCS,\493\ and CBD \494\)
indicated that such interactions should be accounted for.
---------------------------------------------------------------------------

    \492\ CARB, Docket No. NHTSA-2014-0132-0125, at 17-18; 52-53.
    \493\ UCS, Docket No. EPA-HQ-OAR-2014-0827-1329, at pages 23-24.
    \494\ CBD, Docket No. NHTSA-2014-0132-0101 at pages 8-9.
---------------------------------------------------------------------------

    The remainder of this section summarizes changes to the CAFE model
and inputs made subsequent to the NPRM analysis, summarizes results of
the updated analysis, and discusses.
(a) Interactions Between Regulatory Classes
    Like earlier versions, the current CAFE model provides for
integrated analysis spanning different regulatory classes, accounting
both for standards that apply separately to different classes and for
interactions between regulatory classes. Light vehicle CAFE standards
are specified separately for passenger cars and light trucks. However,
there is considerable sharing between these two regulatory classes.
Some specific engines and transmissions are used in both passenger cars
and light trucks, and some vehicle platforms span these regulatory
classes. For example, some sport-utility vehicles are offered in 2WD
versions classified as passenger cars and 4WD versions classified as
light trucks. Integrated analysis of manufacturers' passenger car and
light truck fleets provides the ability to account for such sharing and
reduce the likelihood of finding solutions that could involve
impractical levels of complexity in manufacturers' product lines. In
addition, integrated analysis provides the ability to simulate the
potential that manufactures could earn CAFE credits by over complying
with one standard and use those credits toward compliance with the
other standard (i.e., to simulate credit transfers between regulatory
classes).
    HD pickups and vans are regulated separately from light-duty
vehicles. While manufacturers cannot transfer credits between light-
duty and MDHD classes, there is some sharing of engineering and
technology between light-duty vehicles and HD pickups and vans. For
example, some passenger vans with GVWR over 8,500 pounds are classified
as medium-duty passenger vehicles (MDPVs) and thus included in
manufacturers' light-duty truck fleets,

while cargo vans sharing the same nameplate are classified as HD vans.
    The FRM Method A analysis uses an overall analysis fleet spanning
both the light-duty and HD pickup and van fleets. As discussed below,
doing so shows some technology ``spilling over'' to HD pickups and vans
due, for example, to the application of technology in response to
current light-duty standards. For most manufacturers, these
interactions appear relatively small. For Nissan, however, they appear
considerable, because Nissan's heavy-duty vans use engines also used in
Nissan's light-duty SUVs. Unlike the Method A analysis, the Method B
analysis is independent from the light-duty program.
    In the NPRM proposing new standards for heavy-duty pickups and
vans, NHTSA and EPA requested comment on the expansion of the analysis
fleet such that the impacts of new HD pickup and van standards can be
estimated within the context of an integrated analysis of light-duty
vehicles and HD pickups and vans, accounting for interactions between
the fleets. As mentioned above, some environmental organizations
specifically cited commonalities and overlap between light- and heavy-
duty products.
(b) Phase-In Caps
    The model also accommodates estimates of overall limits (expressed
as ``phase-in caps'' in model inputs) on the rates at which
manufacturers' may practicably add technology to their respective
fleets. So, for example, even if a manufacturer is expected to redesign
half of its production in MY 2016, if the manufacturer is not already
producing any strong hybrid electric vehicles (SHEVs), a phase-in cap
can be specified in order to assume that manufacturer will stop
applying SHEVs in MY 2016 once it has done so to at least 3 percent of
its production in that model year. Today's analysis sets all of these
caps at 100 percent, relying on other model constraints (in particular,
the assumption that many technologies are most practicably applied as
part of a vehicle freshening or redesign) to estimate practicable
technology application pathways.
    The CAFE model retains the ability to use phase-in caps (specified
in model inputs) as proxies for a variety of practical restrictions on
technology application. Unlike vehicle-specific restrictions related to
redesign, refreshes or platforms/engines, phase-in caps constrain
technology application at the vehicle manufacturer level. Introduced in
the 2006 version of the CAFE model, they were intended to reflect a
manufacturer's overall resource capacity available for implementing new
technologies (such as engineering and development personnel and
financial resources), thereby ensuring that resource capacity is
accounted for in the modeling process.
    In previous fuel efficiency rulemakings, redesign/refresh schedules
and phase-in caps were the primary mechanisms to reflect an OEM's
limited pool of available resources during the rulemaking time frame
and the years leading up to the rulemaking time frame, especially in
years where many models may be scheduled for refresh or redesign. The
newly-introduced representation platform-, engine-, and transmission-
related considerations discussed above augment the model's preexisting
representation of redesign cycles, and as discussed above, inputs for
today's analysis de-emphasize reliance on phase-in caps.
(c) Accounting for Credits
    The changes discussed above relate specifically to the model's
approach to simulating manufacturers' potential addition of fuel-saving
technology in response to fuel efficiency standards and fuel prices
within an explicit product planning context. The model's approach to
simulating compliance decisions also accounts for the potential to earn
and use fuel consumption credits, as provided by EPCA/EISA. Like past
versions, the current CAFE model can be used to simulate credit carry-
forward (a.k.a. banking) between model years and transfers between the
passenger car and light truck fleets, but not credit carry-back (a.k.a.
borrowing) between model years or trading between manufacturers. Unlike
past versions, the current CAFE model provides a basis to specify (in
model inputs) fuel consumption credits available from model years
earlier than those being simulated explicitly. For example, with
today's analysis representing model years 2015-2032 explicitly, credits
specified as being available from model year 2014 are made available
for use through model year 2019 (given the current 5-year limit on
carry-forward of credits).
    As discussed in the CAFE model documentation, the model's default
logic attempts to maximize credit carry-forward--that is to ``hold on''
to credits for as long as possible.\495\ Although the model uses
credits before expiry if needed to cover shortfalls when insufficient
opportunity to add technology is available to achieve compliance with a
standard, the model will otherwise carry forward credits until they are
about to expire, at which point it will use them before adding
technology. As further discussed in the CAFE model documentation, model
inputs can be used to adjust this logic to shift the use of credits
ahead by one or more model years.
---------------------------------------------------------------------------

    \495\ Volpe CAFE Model Documentation, July 2016, pg 64.
Available at http://www.nhtsa.gov/Laws%20&%20Regulations/CAFE%20-%20Fuel%20Economy/cafe-volpe-model.
---------------------------------------------------------------------------

    The example presented below illustrates how some of aspects of the
current model logic around credits impacts estimation of technology
application by a manufacturer within the context of a specified set of
standards, focusing here on the model's estimate of Ford's potential
technology application under the preferred alternative. Overall results
for Ford and other manufacturers are summarized in Section VI.D.

[GRAPHIC] [TIFF OMITTED] TR25OC16.014

    Several aspects of the estimated achieved and required fuel
consumption levels shown above are notable. First, the characteristics
of Ford's fleet as represented in today's analysis fleet are such that
the heavy duty pickup and van fleet falls short of average fuel
efficiency standard in MY's 2023 through 2027. However, they exceed
their standard for MY's 2016 through 2022. The current analysis uses
logic that reflect the potential that Ford could use the 5-year carry
forward provision to use fuel efficiency credits earned in MY's 2018
through MY 2022, to cover the shortfalls for MY's 2023 to 2027. The
model assumes Ford will use as many of the MY 2018 expiring credits as
necessary to cover the shortfall in MY 2023. For MY 2024 they will use
all available MY 2019 credits before applying any additional MY 2020
credits necessary to cover the shortfall (in this particular case there
are enough MY 2019 credits to cover the shortfall in MY 2024). This
pattern continues for all model years where there is a shortfall--the
model applies the oldest remaining credits first. Even so, today's
analysis indicates Ford could be required to pay civil penalties for
noncompliance without the addition of modest fuel savings in MY 2027.
The change to the model which accounts for credits earned prior to MY
2015 is not illustrated in this example. However, Ford comes in with
fuel consumption credits from MY's prior to MY 2015; if they had come
in with an initial shortfall, they could have used these banked credits
to cover, at least a portion, of that shortfall.
    As discussed above, these results provide an estimate, based on
analysis inputs, of one way General Motors could add fuel-saving
technologies to its products under the preferred alternative considered
here, and are not a prediction of what General Motors would do under
this alternative. In addition, it should be recognized that specific
results vary among manufacturers and among regulatory alternatives (and
under different analytical inputs). Still, the example should serve to
illustrate how the ability to model credit banking can impact results.
(d) Integrating Vehicle Simulation Results Into the Synergy Values
    The CAFE model does not itself evaluate which technologies will be
available, nor does it evaluate how effective or reliable they will be.
The technological availability and effectiveness rather, are predefined
inputs to the model based on the agencies' judgements and not outputs
from the model, which is simply a tool for calculating the effects of
combining input assumptions.
    In previous versions of the CAFE Model, technology effectiveness
values entered into the model as a single number for each technology
(for each of several classes), intended to represent the incremental
improvement in fuel consumption achieved by applying that technology to
a vehicle in a particular class. At a basic level, this implied that
successive application of new vehicle technologies resulted in an
improvement in fuel consumption (as a percentage) that was the product
of the individual incremental effectiveness of each technology applied.
Since this construction fails to capture interactive effects--cases
where a given technology either improves or degrades the impact of
subsequently applied technologies--the CAFE Model applied ``synergy
factors.'' The synergy factors were defined for a relatively small
number of technology pairs, and were intended to represent the result
of physical interactions among pairs of technologies--attempting to
account for situations where 2 x 2 [ne] 4.
    For a more specific example, for a vehicle with an initial fuel
consumption of FC0, if two technologies are applied, one
with an incremental effectiveness of 5 percent, and a second with an
incremental effectiveness of 10 percent, the effectiveness after the
application of both technologies without consideration of synergies
could be expressed as follows:

FC0*(1-.05)*(1-.1)

Which is equivalent to:

FC0*(1-.145)

    This suggests that the combined effectiveness of the two
technologies is 14.5 percent. The synergy factors aim to correct for
cases where fuel consumption improvements are not perfectly
multiplicative, and the combined fuel consumption in the example above
is either greater than or less than 14.5 percent.

    For this analysis, the CAFE Model has been modified to accommodate
the results of the large-scale vehicle simulation study conducted by
Argonne National Laboratory (described in more detail in the light-duty
Draft TAR). While Autonomie, Argonne's vehicle simulation model,
produces absolute fuel consumption values for each simulation record,
the results have been modified in a way that preserves much of the
existing structure of the CAFE Model's compliance logic, but still
faithfully reproduces the totality of the simulation outcomes present
in the database. Fundamentally, the implementation represents a
translation of the absolute values in the simulation database into
incremental improvements and a substantially expanded set of synergy
factors.
    Since the simulation efforts only included light-duty vehicles, the
effectiveness values for heavy duty were not integrated into the heavy-
duty fleet; for future rule-makings NHTSA hopes to extend the vehicle
simulation efforts to include simulations that would be relevant for
heavy-duty pickups and vans. While the effectiveness values for
individual technologies remain the same, the synergies between two or
more technologies incorporate information from Autonomie Argonne's
light-duty pickup simulations. While these synergy values are not a
perfect approximation of the interaction of technology applications
particular to heavy-duty vehicles, it is consistent with what we did in
the NPRM (where we also used synergy values from light-duty pickups).
    Updating the synergy values to use Argonne's simulation efforts
does two things: (1) It allows that these synergies may occur between
more than two technologies, and (2) because the synergies are
multiplicative, rather than additive, it allows for the consideration
that the order of other technology applications matter in determining
the incremental percentage improvement correction of the synergy value.
Instead of having one additive incremental percentage synergy value for
a pair of technologies, regardless of the order of technology
application between these pair of technologies, the synergy values are
dependent on the initial state and ending point of a vehicle within the
database.
    As stated, in the past, synergy values in the Volpe model were
represented as pairs. However, the new values are 7-tuples and there is
one for every point in the database. The synergy factors are based
(entirely) on values in the Argonne database, producing one for each
unique technology combination for each technology class, and are
calculated as
[GRAPHIC] [TIFF OMITTED] TR25OC16.015

where Sk is the synergy factor for technology combination k,
FC0 is the fuel consumption of the reference vehicle (in the
database), xi is the fuel consumption improvement of each
technology i represented in technology combination k (where some
technologies are present in combination k, and some are precedent
technologies that were applied, incrementally, before reaching the
current state on one of the paths).
    In order to incorporate the results of the Argonne database, while
still preserving the basic structure of the CAFE model's technology
module, it was necessary to translate the points in the database into
locations on the technology tree.\496\ By recognizing that most of the
paths on the technology tree are unrelated, or separable, it is
possible to decompose the technology tree into a small number of paths
and branches by technology type. To achieve this level of linearity, we
define technology groups--only one of which is new. They are: engine
cam configuration (CONFIG), engine technologies (ENG), transmission
technologies (TRANS), electrification (ELEC), mass reduction levels
(MR), aerodynamic improvements (AERO), and rolling resistance (ROLL).
The combination of technology levels along each of these paths define a
unique technology combination that corresponds to a single point in the
database for each technology class. These technology state definitions
are more important for defining synergies than for determining
incremental effectiveness, but the paths are incorporated into both.
Again, because we did not simulate results applicable to the heavy-duty
fleet, we did not use the database to define the incremental technology
effectiveness, but only to adjust for the unique interaction of
different combinations of technology.
---------------------------------------------------------------------------

    \496\ The technology tree used to create the synergies for this
rule are presented in the light-duty draft TAR.
---------------------------------------------------------------------------

    As an example, a technology state vector describing a vehicle with
a SOHC engine, variable valve timing (only), a 6-speed automatic
transmission, a belt-integrated starter generator, mass reduction
(level 1), aerodynamic improvements (level 2), and rolling resistance
(level 1) would be specified as SOHC;VVT;AT6;BISG;MR1;AERO2;ROLL1. Once
a vehicle is assigned a technology state (one of the tens of thousands
of unique 7-tuples, defined as CONFIG;ENG;TRANS;ELEC;MR;AERO;ROLL),
adding a new technology to the vehicle simply represents progress from
one technology state to another. The vehicle's fuel consumption is:

FCi = FC0 [middot] (1 - FCIi) [middot] SK/0

where FCi is the fuel consumption resulting from the
application of technology i, FC0 is the vehicle's fuel
consumption before technology i is applied, FCIi is the
incremental fuel consumption (percentage) improvement associated with
technology i, Sk is the synergy factor associated with the
combination, k, of technologies the vehicle technology i is applied,
and S0 the synergy factor associated with the technology
state that produced fuel consumption FC0. The synergy factor
is defined in a way that captures the incremental improvement of moving
between points in the database, where each point is defined uniquely as
a 7-tuple describing its cam configuration, highest engine technology,
transmission, electrification type, mass reduction level, and level of
aerodynamic or rolling resistance improvement. For the current heavy-
duty adoption, it is only these synergy values that were used in the
current analysis. While, like with the individual fuel consumption
improvements, there is likely not a simple mapping from light-duty
pickups to heavy-duty pickups (size and power matter), the previous
synergy values were also an adoption from light-duty pickups. The
integration of the simulation data allows for a more complete set of
synergies that account for the order of technology application and the
interaction of more than two individual technologies.
(e) Updating Mileage Accumulation Schedules
    In order to develop new mileage accumulation schedules for vehicles
regulated under NHTSA's fuel efficiency and CAFE programs (classes 1-
3), NHTSA purchased a data set of vehicle odometer readings from IHS/
Polk (Polk). Polk collects odometer readings from registered vehicles
when they encounter maintenance facilities, state inspection programs,
or interactions with dealerships and OEMs. The (average) odometer
readings in the data set NHTSA purchased are based on over 74 million
unique odometer readings across 16 model years (2000-2015) and vehicle
classes present in the data purchase (all registered vehicles less than
14,000 lbs. GVW).
    The Polk data provide a measure of the cumulative lifetime vehicle
miles

traveled (VMT) for vehicles, at the time of measurement, aggregated by
the following parameters: make, model, model year, fuel type, drive
type, door count, and ownership type (commercial or personal). Within
each of these subcategories they provide the average odometer reading,
the number of odometer readings in the sample from which Polk
calculated the averages, and the total number of that subcategory of
vehicles in operation. From these NHTSA was able to develop new
estimates of vehicle miles traveled by age as inputs for the CAFE
Model.
(f) Impact of Vehicle Technology Application Requirements
    Compared to prior analyses of light-duty standards, these model
changes result in some changes in the broad characteristics of the
model's application of technology to manufacturers' fleets. Since the
use of phase-in caps has been de-emphasized and manufacturer technology
deployment remains tied strongly to estimated product redesign and
freshening schedules, technology penetration rates may jump more
quickly as manufacturers apply technology to high-volume products in
their portfolio.
    By design, restrictions that enforce commonality of mass reduction
and aerodynamic technologies on variants of a platform, and those that
enforce engine inheritance, will result in fewer vehicle-technology
combinations in a manufacturer's future modeled fleet. As explained in
the NPRM proposing new standards for HD pickups and vans, these
restrictions are expected to more accurately capture the true costs
associated with producing and maintaining a product portfolio.
(i) Updated Schedules
    The new medium-duty van/pickup schedule in Figure VI-6 predicts
higher annual VMT for vehicles between ages one through five years, and
lower annual VMT for all other vehicle ages, than the old schedule.
Over the first 30-year span, the new schedule predicts that medium-duty
vans/pickups drive 24,249 (9 percent) fewer miles than the old
schedule. We predict the maximum average annual VMT for medium-duty
vehicles (23,307 miles) at age two. These changes to the schedule will
have important implications on certain benefits of the standards. More
monetary fuel savings will occur during the first five years of a
vehicle's life under the new schedule, but a decrease in fuel savings
will occur overall while using these schedules. For payback periods
shorter than 5 years, the new schedule will show shorter payback
periods than the old schedule. Section 10 of the RIA offers similar
figures for light-duty vehicles types. It also offers further
explanation about the shape of the new annual VMT schedule.
[GRAPHIC] [TIFF OMITTED] TR25OC16.016

    Table VI-9 offers a summary of the comparison of lifetime VMT (by
class) under the new schedule, compared with lifetime VMT under the old
schedule. In addition to the total lifetime VMT expected under each
schedule for vehicles that survive to their full useful life, Table VI-
9also shows the survival-weighted lifetime VMT for both schedules. This
represents the average lifetime VMT for all vehicles, not only those
that survive to their full useful life. The percentage difference
between the two schedules is not as stark for the survival-weighted
schedules: The percentage decrease of survival-weighted lifetime VMT
under the new schedules range from 6.5 percent (for medium-duty trucks
and vans) to 21.2 percent (for passenger vans).

                                       Table VI-9--Summary Comparison of Lifetime VMT of the New and Old Schedules
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Survival-Weighted
                                                         -----------------------------------------------------------------------------------------------
                                                                           Lifetime VMT                                    Lifetime VMT
                                                         -----------------------------------------------------------------------------------------------
                                                                New             Old        % difference         New             Old        % difference
--------------------------------------------------------------------------------------------------------------------------------------------------------
Car.....................................................         204,233         301,115            32.2         142,119         179,399            20.8
Van.....................................................         237,623         362,482            34.4         155,115         196,725            21.2
SUV.....................................................         237,623         338,646            29.8         155,115         193,115            19.7
Pickup..................................................         265,849         360,982            26.4         157,991         188,634            16.2
2b/3....................................................         246,413         270,662             9.0         176,807         189,020             6.5
--------------------------------------------------------------------------------------------------------------------------------------------------------

(ii) Data Description
    While the Polk data set contains model-level average odometer
readings, the CAFE model assigns lifetime VMT schedules at a lower
resolution based on vehicle body style. For the purposes of VMT
accounting, the CAFE model classifies every vehicle in the analysis
fleet as being one of the following: passenger car, SUV, pickup truck,
passenger van, or medium-duty pickup/van. In order to use the Polk data
to develop VMT schedules for each of the (VMT) classes in the CAFE
model, we constructed a mapping between the classification of each
model in the Polk data and the classes in the CAFE model. The only
difference between the mapping for the VMT schedules and the rest of
the CAFE model is that we merged the SUV and van body styles into one
class (for reasons described in our discussion of the SUV/van schedule
in Section 10 of the RIA). This mapping allowed us to predict the
lifetime miles traveled, by the age of a vehicle, for the categories in
the CAFE model.
    In estimating the VMT models, we weighted each data point (make/
model classification) by the share of each make/model in the total
population of the corresponding CAFE class. This weighting ensures that
the predicted odometer readings, by class and model year, represent
each of vehicle classification among observed vehicles (i.e., the
vehicles for which Polk has odometer readings), based on each vehicles'
representation in the registered vehicle population of its class.
Implicit in this weighting scheme, is the assumption that the samples
used to calculate each average odometer reading by make, model, and
model year are representative of the total population of vehicles of
that type. Several indicators suggest that this is a reasonable
assumption.
    First, the majority of each vehicle make/model is well-represented
in the sample. For more than 85 percent of make/model combinations, the
average odometer readings are collected for 20 percent or more of the
total population. Most make/model observations have sufficient sample
sizes, relative to their representation in the vehicle population, to
produce meaningful average odometer totals at that level.
    We also considered whether the representativeness of the odometer
sample varies by vehicle age, since VMT schedules in the CAFE model are
specific to each age. To investigate, we calculated the percentage of
vehicle types (by make, model, and model year) that did not have
odometer readings. All model years, apart from 2015, have odometer
readings for 96 percent or more of the total types of vehicles observed
in the fleet.
    While the preceding discussion supports the coverage of the
odometer sample across makes/models by each model year, it is possible
that, for some of those models, an insufficient number of odometer
readings is recorded to create an average that is likely to be
representative of all of those models in operation for a given year.
For all model years other than 2015, about 95 percent or more of
vehicles types are represented by at least 5 percent of their
population. For this reason, we included observations from all model
years, other than 2015, in the estimation of the new VMT schedules.
    It is possible that the odometer sample is biased. If certain
vehicles are over-represented in the sample of odometer readings
relative to the registered vehicle population, a simple average, or
even one weighted by the number of odometer observations will be
biased. However, while weighting by the share of each vehicle in the
population will account for this bias, it would not correct for a
sample that entirely omits a large number of makes/models within a
model year. We tested for this by computing the proportion of the count
of odometer readings for each individual vehicle type--within a class
and model year--to the total count of readings for that class and model
year. We also compared the population of each make/model--within each
class and model year--to the population of the corresponding class and
model year. The difference of these two ratios shows the difference of
the representation of a vehicle type--in its respective class and model
year--in the sample versus the population. All vehicle types are
represented in the sample within 10 percent of their representation in
the population, and the variance between the two representations is
normally distributed. This suggests that, on average, the likelihood
that a vehicle is in the sample is comparable to its proportion in the
relevant population, and that there is little under or over sampling of
certain vehicle makes/models.\497\
---------------------------------------------------------------------------

    \497\ For figures that support the conclusions about the
representativeness of the IHS/Polk data see Section 10 of the RIA.
---------------------------------------------------------------------------

(iii) Estimation
    Since model years are sold in in the fall of the previous calendar
year, throughout the same calendar year, and even into the following
calendar year--not all registered vehicles of a make/model/model year
will have been registered for at least a year (or more) until age 3.
The result is that some MY 2014 vehicles may have been driven for
longer than one year, and some less, at the time the odometer was
observed. In order to consider this in our definition of age, we assign
the age of a vehicle to be the difference between the average reading
date of a make/model and the average first registration date of that
make/model. The result is that the continuous age variable reflects the
amount of time that a car has been registered at the time of odometer
reading, and presumably the time span that the car has accumulated the
miles.
    After creating the ``Age'' variable, we fit the make/model lifetime
VMT data points to a weighted quartic polynomial regression of the age
of the vehicle (stratified by class). The predicted values of the
quartic regressions are used to calculate the marginal annual VMT by
age for each class by calculating differences in estimated lifetime
mileage accumulation by age. However, the Polk data acquired by NHTSA
only contains

observations for vehicles newer than 16 years of age. In order to
estimate the schedule for vehicles older than the age 15 vehicles in
the Polk data, we combined information about that portion of the
schedule from the VMT schedules used in both the 2017-2021 Final Light
Duty Rule and 2019-2025 Medium-Duty NPRM. The light-duty schedules were
derived from the survey data contained in the 2009 National Household
Travel Survey (NHTS) and the 2001 Vehicle in Use Survey (VIUS), for
medium-duty trucks.
    Based on the vehicle ages for which we have data (from the Polk
purchase), the newly estimated annual schedules differ from the
previous version in important ways. Perhaps most significantly, the
annual mileage associated with ages beyond age 8 begin to, and continue
to, trend much lower. The approach taken here attempts to preserve the
results obtained through estimation on the Polk observations, while
leveraging the existing (NHTS-based) schedules to support estimation of
the higher ages (age 16 and beyond). Since the two schedules are so far
apart, simply splicing them together would have created not only a
discontinuity, but also precluded the possibility of a monotonically
decreasing scale with age (which is consistent with previous schedules,
the data acquired from Polk, and common sense).
    From the old schedules, we expect that the annual VMT is decreasing
for all ages. Towards the end of our sample, the predictions for annual
VMT increase. In order to force the expected monotonicity, we perform a
triangular smoothing algorithm until the schedule is monotonic. This
performs a weighted average which weights the observations close to the
observation more than those farther from it. The result is a monotonic
function, which predicts similar lifetime VMT for the sample span as
the original function. Since we do not have data beyond 15 years of
age, we are not able to correctly capture that part of the annual VMT
curve using only the new dataset. For this reason, we use trends in the
old data to extrapolate the new schedule for ages beyond the sample
range.
    In order to use the VMT information from the newer data source for
ages outside of the sample, we use the final in-sample age (15 years)
as a seed and then apply the proportional trend from the old schedules
to extrapolate the new schedules out to age 30. To do this, we
calculated the annual percentage difference in VMT of the old schedule
for ages 15-30. The same annual percentage difference in VMT is applied
to the new schedule to extend beyond the final in-sample value. This
assumes that the overall proportional trend in the outer years is
correctly modeled in the old VMT schedule, and imposes this same trend
for the outer years of the new schedule. The extrapolated schedules are
the final input for the VMT schedules in the CAFE model.
(iv) Comparison to Previous Schedules
    The new VMT data suggests that the VMT schedule used in the last
Light-Duty CAFE Final Rule likely does not represent current annual VMT
rates. Across all classes, the previous VMT schedules overestimate the
average annual VMT. The previous schedules are based on data that is
outdated and self-reported, while the observations from Polk are
between 5 and 7 years newer than those in the NHTS and represent valid
odometer readings (rather than self-reported information).
    Additionally, while the NHTS may be a representative sample of
households, it is less likely to be a representative sample of
vehicles. However, by properly accounting for vehicle population
weights in the new averages and models, we corrected for this issue in
the derivation of the new schedules.
    Insofar as these changes better represent actual VMT, they lead to
better estimates of actual impacts, such as avoided fuel consumption
and GHG emissions, safety impacts, and monetized benefits.
(v) Future Direction
    In consultation with other agencies closely involved with VMT
estimation (e.g., FHWA), NHTSA will continue to seek means to further
refine estimated mileage accumulation schedules. For example, one
option under consideration would be to obtain odometer reading data
from successive calendar years, thus providing a more robust basis to
consider, for example, the influence of changing fuel prices or
economic conditions on the accumulation of miles by vehicles of a given
age.
(g) Updated Analysis Fleet
    For the current analysis we updated the reference fleet from MY
2014, to the latest available MY 2015. The projection of total sales
volumes for the Class 2b and 3 market segment was based on the total
volumes in the 2015 AEO Reference Case. For the purposes of this
analysis, the AEO2015 calendar year volumes have been used to represent
the corresponding model-year volumes. While AEO2015 provides enough
resolution in its projections to separate the volumes for the Class 2b
and 3 segments, the agencies deferred to the vehicle manufacturers and
chose to rely on the relative shares present in the pre-model-year
compliance data.
    The relative sales share by vehicle type (van or pickup truck, in
this case) was derived from a sales forecast that the agencies
purchased from IHS Automotive, and applied to the total volumes in the
AEO2015 projection. Table VI-10 shows the implied shares of the total
new 2b/3 vehicle market broken down by manufacturer and vehicle type.

                                        Table VI-10--2015 IHS Automotive Market Share Forecast for 2b/3 Vehicles
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Model year market share
           Manufacturer                     Style        -----------------------------------------------------------------------------------------------
                                                               2016            2017            2018            2019            2020            2021
--------------------------------------------------------------------------------------------------------------------------------------------------------
Daimler...........................  Van.................              2%              2%              2%              3%              3%              3%
Fiat Chrysler.....................  Van.................               3               3               3               3               3               3
Ford..............................  Van.................              16              16              16              17              18              19
General Motors....................  Van.................               7               7               7               7               8               8