Manufacturers make improvements to production processes over time,
which often result in lower costs. ``Cost learning'' reflects the
effect of experience and volume on the cost of production, which
generally results in better utilization of resources, leading to higher
and more efficient production. As manufacturers gain experience through
production, they refine production techniques, raw material and
component sources, and assembly methods to maximize efficiency and
reduce production costs. Typically, a representation of this cost
learning, or learning curves, reflects initial learning rates that are
relatively high, followed by slower learning as additional improvements
are made and production efficiency peaks. This eventually produces an
asymptotic shape to the learning curve, as small percent decreases are
applied to gradually declining cost levels. These learning curve
estimates are applied to various technologies that are used to meet
CAFE standards.
    We estimate cost learning by considering methods established by
T.P. Wright and later expanded upon by J.R. Crawford.148 149
Wright, examining aircraft production, found that every doubling of
cumulative production of airplanes resulted in decreasing labor hours
at a fixed percentage. This fixed percentage is commonly referred to as
the progress rate or progress ratio, where a lower rate implies faster
learning as cumulative production increases. J.R. Crawford expanded
upon Wright's learning curve theory to develop a single unit cost
model, which estimates the cost of the nth unit produced
given the following information is known: (1) Cost to produce the first
unit; (2) cumulative production of n units; and (3) the progress ratio.
---------------------------------------------------------------------------

    \148\ Wright, T. P., Factors Affecting the Cost of Airplanes.
Journal of Aeronautical Sciences, Vol. 3 (1936), at pp. 124-25.
Available at https://www.uvm.edu/pdodds/research/papers/others/1936/wright1936a.pdf. (Accessed: February 16, 2022)
    \149\ Crawford, J.R., Learning Curve, Ship Curve, Ratios,
Related Data, Burbank, California-Lockheed Aircraft Corporation
(1944).
---------------------------------------------------------------------------

    As pictured in Figure III-5, Wright's learning curve shows the
first unit is produced at a cost of $1,000. Initially cost per unit
falls rapidly for each successive unit produced. However, as production
continues, cost falls more gradually at a decreasing rate. For each
doubling of cumulative production at any level, cost per unit declines
20 percent, so that 80 percent of cost is retained. The CAFE Model uses
the basic approach by Wright, where cost reduction is estimated by
applying a fixed percentage to the projected cumulative production of a
given fuel economy technology.
[GRAPHIC] [TIFF OMITTED] TR02MY22.060

    The analysis accounts for learning effects with model year-based
cost learning forecasts for each technology that reduces direct
manufacturing costs over time. We evaluate the historical use of
technologies, and reviews industry forecasts to estimate future volumes
to develop the model year-based technology cost learning curves.
    The following section discusses the development of model year-based
cost learning forecasts for this analysis, including how the approach
has evolved from the 2012 rulemaking for MY 2017-2025 vehicles, and how
the progress ratios were developed for different technologies
considered in the analysis. Finally, we discuss how these learning
effects are applied in the CAFE Model.
(l) Time Versus Volume-Based Learning
    For the 2012 joint CAFE and GHG rulemaking, DOT developed learning
curves as a function of vehicle model year.\150\ Although the concept
of this methodology is derived from Wright's cumulative production
volume-based learning curve, its application for CAFE technologies was
more of a function of time. More than a dozen learning curve schedules
were developed, varying

between fast and slow learning, and assigned to each technology
corresponding to its level of complexity and maturity. The schedules
were applied to the base year of direct manufacturing cost and
incorporate a percentage of cost reduction by model year, declining at
a decreasing rate through the technology's production life. Some newer
technologies experience 20 percent cost reductions for introductory
model years, while mature or less complex technologies experience 0-3
percent cost reductions over a few years.
---------------------------------------------------------------------------

    \150\ 77 FR 62624 (Oct. 15, 2012).
---------------------------------------------------------------------------

    In their 2015 report to Congress, NAS recommended NHTSA should
``continue to conduct and review empirical evidence for the cost
reductions that occur in the automobile industry with volume,
especially for large-volume technologies that will be relied on to meet
the CAFE/GHG standards.'' \151\
---------------------------------------------------------------------------

    \151\ 2015 NAS Report.
---------------------------------------------------------------------------

    In response, we incorporated statically projected cumulative volume
production data of fuel economy-improving technologies, representing an
improvement over the previously used time-based method. Dynamic
projections of cumulative production are not feasible with current CAFE
Model capabilities, so one set of projected cumulative production data
for most vehicle technologies was developed for the purpose of
determining cost impact. We obtained historical cumulative production
data for many technologies produced and/or sold in the U.S. to
establish a starting point for learning schedules. Groups of similar
technologies or technologies of similar complexity may share identical
learning schedules.
    The slope of the learning curve, which determines the rate at which
cost reductions occur, has been estimated using research from an
extensive literature review and automotive cost tear-down reports (see
below). The slope of the learning curve is derived from the progress
ratio of manufacturing automotive and other mobile source technologies.
(2) Deriving the Progress Ratio Used in This Analysis
    Learning curves vary among different types of manufactured
products. Progress ratios can range from 70 to 100 percent, where 100
percent indicates no learning can be achieved.\152\ Learning effects
tend to be greatest in operations where workers often touch the
product, while effects are less substantial in operations consisting of
more automated processes. As automotive manufacturing plant processes
become increasingly automated, a progress ratio towards the higher end
would seem more suitable. We incorporated findings from automotive
cost-teardown studies with EPA's 2015 literature review of learning-
related studies to estimate a progress ratio used to determine learning
schedules of fuel economy-improving technologies.
---------------------------------------------------------------------------

    \152\ Martin, J., ``What is a Learning Curve?'' Management and
Accounting Web, University of South Florida, available at: https://www.maaw.info/LearningCurveSummary.htm. (Accessed: February 16,
2022)
---------------------------------------------------------------------------

    EPA's literature review examined and summarized 20 studies related
to learning in manufacturing industries and mobile source
manufacturing.\153\ The studies focused on many industries, including
motor vehicles, ships, aviation, semiconductors, and environmental
energy. Based on several criteria, EPA selected five studies providing
quantitative analysis from the mobile source sector (progress ratio
estimates from each study are summarized in Table III-5, below).
Further, those studies expand on Wright's learning curve function by
using cumulative output as a predictor variable, and unit cost as the
response variable. As a result, EPA determined a best estimate of 84
percent as the progress ratio in mobile source industries. However, of
those five studies, EPA at the time placed less weight on the Epple et
al. (1991) study, because of a disruption in learning due to incomplete
knowledge transfer from the first shift to introduction of a second
shift at a North American truck plant. While learning may have
decelerated immediately after adding a second shift, we note that unit
costs continued to fall as the organization gained experience operating
with both shifts. We recognize that disruptions are an essential part
of the learning process and should not, in and of themselves, be
discredited. For this reason, the analysis uses a re-estimated average
progress ratio of 85 percent from those five studies (equally
weighted).
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    \153\ Cost Reduction through Learning in Manufacturing
Industries and in the Manufacture of Mobile Sources, U.S.
Environmental Protection Agency (2015). Prepared by ICF
International and available at https://19january2017snapshot.epa.gov/sites/production/files/2016-11/documents/420r16018.pdf. (Accessed: February 16, 2022)
    \154\ Argote, L., Epple, D., Rao, R. D., & Murphy, K., The
acquisition and depreciation of knowledge in a manufacturing
organization--Turnover and plant productivity, Working paper,
Graduate School of Industrial Administration, Carnegie Mellon
University (1997).
    \155\ Benkard, C. L., Learning and Forgetting--The Dynamics of
Aircraft Production, The American Economic Review, Vol. 90(4), at
1034-54 (2000).
    \156\ Epple, D., Argote, L., & Devadas, R., Organizational
Learning Curves--A Method for Investigating Intra-Plant Transfer of
Knowledge Acquired through Learning by Doing, Organization Science,
Vol. 2(1), at 58-70 (1991).
    \157\ Epple, D., Argote, L., & Murphy, K., An Empirical
Investigation of the Microstructure of Knowledge Acquisition and
Transfer through Learning by Doing, Operations Research, Vol. 44(1),
at 77-86 (1996).
    \158\ Levitt, S. D., List, J. A., & Syverson, C., Toward an
Understanding of Learning by Doing--Evidence from an Automobile
Assembly Plant, Journal of Political Economy, Vol. 121 (4), at 643-
81 (2013).
[GRAPHIC] [TIFF OMITTED] TR02MY22.061

    In addition to EPA's literature review, this progress ratio
estimate was informed based on findings from automotive cost-teardown
studies. NHTSA routinely performs evaluations of costs of previously
issued Federal Motor Vehicle Safety Standards (FMVSS) for new motor
vehicles and equipment. NHTSA engages contractors to perform detailed
engineering ``tear-down'' analyses for representative samples of
vehicles, to estimate how much specific FMVSS add to the weight and
retail price of a vehicle. As part of the effort, the agency examines
cost and production volume for automotive safety technologies. In
particular, we estimated costs from multiple cost tear-down studies for
technologies with actual production data from the Cost and weight added
by the Federal Motor Vehicle Safety Standards for MY 1968-2012
passenger cars and LTVs (2017).\159\
---------------------------------------------------------------------------

    \159\ Simons, J. F., Cost and weight added by the Federal Motor
Vehicle Safety Standards for MY 1968-2012 Passenger Cars and LTVs
(Report No. DOT HS 812 354). Washington, DC--National Highway
Traffic Safety Administration (November 2017), at pp. 30-33.
---------------------------------------------------------------------------

    We chose five vehicle safety technologies with sufficient data to
estimate progress ratios of each, because these technologies are large-
volume technologies and are used by almost all vehicle manufacturers.
Table III-6 includes these five technologies and yields an average
progress rate of 92 percent.
[GRAPHIC] [TIFF OMITTED] TR02MY22.062

    For the final progress ratio used in the CAFE Model, the five
progress rates from EPA's literature review and five progress rates
from NHTSA's evaluation of automotive safety technologies results were
averaged. This resulted in an average progress rate of approximately 89
percent. We placed equal weight on progress ratios from all 10 sources.
More specifically, we placed equal weight on the Epple et al. (1991)
study, because disruptions have more recently been recognized as an
essential part in the learning process, especially in an effort to
increase the rate of output.
(3) Obtaining Appropriate Baseline Years for Direct Manufacturing Costs
    DOT obtained direct manufacturing costs for each fuel economy-
improving technology from various sources, as discussed above. To
establish a consistent basis for direct manufacturing costs in the
rulemaking analysis, we adjusted each technology cost to MY 2018
dollars. For each technology, the DMC is associated with a specific
model year, and sometimes a specific production volume, or cumulative
production volume. The base model year is established as the model year
in which direct manufacturing costs were assessed (with learning factor
of 1.00). With the aforementioned data on cumulative production volume
for each technology and the assumption of a 0.89 progress ratio for all
automotive technologies, we can solve for an implied cost for the first
unit produced. For some technologies, we used modestly different
progress ratios to match detailed cost projections if available from
another source (for instance, batteries for plug-in hybrids and battery
electric vehicles).
    This approach produces reasonable estimates for technologies
already in production, and some additional steps are required to set
appropriate learning rates for technologies not yet in production.
Specifically, for technologies not yet in production in MY 2017, the
cumulative production volume in MY 2017 is zero, because manufacturers
have not yet produced the technologies. For pre-production cost
estimates in previous CAFE rulemakings, we often relied on confidential
business information sources to predict future costs. Many sources for
pre-production cost estimates include significant learning effects,
often providing cost estimates assuming high volume production, and
often for a timeframe late in the first production generation or early
in the second generation of the technology. Rapid doubling and re-
doubling of a low cumulative volume base with Wright's learning curves
can provide unrealistic cost estimates. In addition, direct
manufacturing cost projections can vary depending on the initial
production volume assumed. Accordingly, we carefully examined direct
costs with learning, and made adjustments to the starting point for
those technologies on the learning curve to better align with the
assumptions used for the initial direct cost estimate.
(4) Cost Learning Applied in the CAFE Model
    For this analysis, we apply learning effects to the incremental
cost over the null technology state on the applicable technology tree.
After this step, we calculate year-by-year incremental costs over
preceding technologies on the tech tree to create the CAFE Model
inputs.\160\ The shift from incremental cost accounting to absolute
cost accounting in recent CAFE analyses made cost inputs more
transparently relatable to detailed model output, and relevant to this
discussion, made it easier to apply learning curves in the course of
developing inputs to the CAFE Model.
---------------------------------------------------------------------------

    \160\ These costs are located in the CAFE Model Technologies
file.
---------------------------------------------------------------------------

    We group certain technologies, such as advanced engines, advanced
transmissions, and non-battery electric components and assign them to
the same learning schedule. While these grouped technologies differ in
operating characteristics and design, we chose to group them based on
their complexity, technology integration, and economies of scale across
manufacturers. The low volume of certain advanced technologies, such as
hybrid and electric technologies, poses a significant issue for
suppliers and prevents them

from producing components needed for advanced transmissions and other
technologies at more efficient high scale production. The technology
groupings consider market availability, complexity of technology
integration, and production volume of the technologies that can be
implemented by manufacturers and suppliers. The details of these
technologies are discussed in Section III.D.
    In addition, we expanded model inputs to extend the explicit
simulation of technology application through MY 2050. Accordingly, we
updated the learning curves for each technology group to cover MYs
through 2050. For MYs 2017-2032, we expect incremental improvements in
all technologies, particularly in electrification technologies because
of increased production volumes, labor efficiency, improved
manufacturing methods, specialization, network building, and other
factors. While these and other factors contribute to continual cost
learning, we believe that many fuel economy-improving technologies
considered in this rule will approach a flat learning level by the
early 2030s. Specifically, older, and less complex internal combustion
engine technologies and transmissions will reach a flat learning curve
sooner when compared to electrification technologies, which have more
opportunity for improvement. For batteries and non-battery
electrification components, we estimated a steeper learning curve that
will gradually flatten after MY 2040. For a more detailed discussion of
the electrification learning curves, see Section III.D.3.
    Each technology in the CAFE Model is assigned a learning schedule
developed from the methodology explained previously. For example, the
following chart shows learning rates for several technologies
applicable to midsize sedans, demonstrating that while we estimate that
such learning effects have already been almost entirely realized for
engine turbocharging (a technology that has been in production for many
years), we estimate that significant opportunities to reduce the cost
of the greatest levels of mass reduction (e.g., MR5) remain, and even
greater opportunities remain to reduce the cost of batteries for HEVs,
PHEVs, BEVs. In fact, for certain advanced technologies, we determined
that the results predicted by the standard learning curves progress
ratio was not realistic, based on unusual market price and production
relationships. For these technologies, we developed specific learning
estimates that may diverge from the 0.89 progress rate. As shown in
Figure III-6, these technologies include: Turbocharging and downsizing
level 1 (TURBO1), variable turbo geometry electric (VTGE), aerodynamic
drag reduction by 15 percent (AERO15), mass reduction level 5 (MR5), 20
percent improvement in low-rolling resistance tire technology (ROLL20)
over the baseline, and belt integrated starter/generator (BISG).
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TR02MY22.063

BILLING CODE 4910-59-C
    CFA noted that the inputs we use for learning rates produce less
optimistic results than those used by EPA. They cite these differing
results as evidence that NHTSA should use the EPA values. CFA states
that, ``EPA's benefit cost ratios are much higher affirming that their
analysis is more appropriate.'' \161\ CFA provided no new data or
discussion to justify a conclusion that their preferred values are
justified empirically, and NHTSA continues to believe that the
appropriate values to use in estimating the impacts of CAFE standards
are those most justified by empirical evidence and research, consistent
with E.O. 12866, without reference to the outcomes they produce. We
have provided a full description of the basis for choosing the learning
values that we use in Chapter 2.6.4 of the TSD accompanying this final
rule, as well as in the FRIA accompanying the 2020 final rule.
---------------------------------------------------------------------------

    \161\ CFA, at p. 5.
---------------------------------------------------------------------------

(e) Cost Accounting
    To facilitate specification of detailed model inputs and review of
detailed model outputs, the CAFE Model continues to use absolute cost
inputs relative to a known base component cost, such that the estimated
cost of each technology is specified relative to a common reference
point for the relevant technology pathway. For example, the cost of a
7-speed transmission is specified relative to a 5-speed transmission,
as is the cost of every other transmission technology. Conversely, in
some earlier versions of the CAFE Model, incremental cost inputs were
estimated relative to the technology immediately preceding on the
relevant technology pathway. For our 7-speed transmission example, the
incremental cost would be relative to a 6-speed transmission. This
change in the structure of cost inputs does not, by itself, change
model results, but it does make the connection between these inputs and
corresponding outputs more transparent. The CAFE Model Documentation
accompanying our analysis presents details of the structure for model
cost inputs.\162\ The individual technology sections in Section III.D
provide a detailed discussion of cost accounting for each technology.
---------------------------------------------------------------------------

    \162\ CAFE Model Documentation, S4.7.
---------------------------------------------------------------------------

7. Manufacturer's Credit Compliance Positions
    This rule involves a variety of provisions regarding ``credits''
and other compliance flexibilities. Some regulatory provisions allow a
manufacturer to earn ``credits'' that will be counted toward a
vehicle's rated CO2 emissions level, or toward a fleet's
rated average CO2 or CAFE level, without reference to
required levels for these average levels of performance. Such
flexibilities effectively modify emissions and fuel economy test
procedures or methods for calculating fleets' CAFE and average
CO2 levels. Other provisions (for CAFE, statutory
provisions) allow manufacturers to earn credits by achieving CAFE or
average CO2 levels beyond required levels; these provisions
may hence more appropriately be termed ``compliance credits.'' We
described in the 2020 final rule how the CAFE Model simulates these
compliance credit provisions for both the CAFE program and for EPA's
CO2 standards.\163\ For this analysis, we modeled the No-
Action and Action Alternatives as a set of CAFE standards in place
simultaneously with EPA's 2020 final rule CO2
standards,\164\ related CARB agreements with five manufacturers, and
ZEV mandates in place in California and some other states. The modeling
of CO2 standards and standard-like contractual obligations
includes our representation of applicable credit provisions.
---------------------------------------------------------------------------

    \163\ See 85 FR 24174, 24303 (April 30, 2020).
    \164\ The baseline for this analysis is the set of standards in
place when NHTSA initiated this rulemaking.
---------------------------------------------------------------------------

    EPCA has long provided that, by exceeding the CAFE standard
applicable to a given fleet in a given model year, a manufacturer may
earn corresponding ``credits'' that the same manufacturer may, within
the same regulatory class, apply toward compliance in a different model
year. EISA amended these provisions by providing that manufacturers
may, subject to specific statutory limitations, transfer compliance
credits between regulatory classes and trade compliance credits with
other manufacturers. Under the CAA, EPA has broad standard-setting
authority and has long provided for averaging, banking, and trading
programs in certain circumstances, and in particular for GHGs.
    EPCA also specifies that NHTSA may not consider the availability of
CAFE credits (for transfer, trade, or direct application) toward
compliance with new standards when establishing the standards
themselves.\165\ Therefore, this analysis excludes MYs 2024-2026 from
those in which carried-forward or transferred credits can be applied
for the CAFE program.
---------------------------------------------------------------------------

    \165\ 49 U.S.C. 32902(h)(3).
---------------------------------------------------------------------------

    The ``unconstrained'' perspective acknowledges that these
flexibilities exist as part of the program and, while not considered by
NHTSA in setting standards, are nevertheless important to consider when
attempting to estimate the real impact of any alternative. Under the
``unconstrained'' perspective, credits may be earned, transferred, and
applied to deficits in the CAFE program throughout the full range of
model years in the analysis. The Final SEIS accompanying this rule
presents ``unconstrained'' modeling results. Also, consistent with the
program EPA established under the CAA, this analysis includes
simulation of carried-forward and transferred CO2 credits in
all model years.
    The CAFE Model, therefore, does provide means to simulate
manufacturers' potential application of some compliance credits, and
both the analysis of CO2 standards and the NEPA analysis of
CAFE standards do make use of this aspect of the model. On the other
hand, 49 U.S.C. 32902(h) prevents NHTSA from, in its standard setting
analysis, considering the potential that manufacturers could use
compliance credits in model years for which the agency is establishing
maximum feasible CAFE standards. Further, as discussed below, we also
continue to find it appropriate for the analysis largely to refrain
from simulating two of the mechanisms allowing the use of compliance
credits.
    The CAFE Model's approach to simulating compliance decisions
accounts for the potential to earn and use CAFE credits as provided by
EPCA/EISA. The model similarly accumulates and applies CO2
credits when simulating compliance with EPA's standards. Like past
versions, the current CAFE Model can simulate credit carry-forward
(i.e., banking) between model years and transfers between the passenger
car and light truck fleets but not credit carry-back (i.e., borrowing)
from future model years or trading between manufacturers.
    While NHTSA's ``unconstrained'' evaluation can consider the
potential to carry back compliance credits from later to earlier model
years, past examples of failed attempts to carry back CAFE credits
(e.g., a MY 2014 carry back default leading to a civil penalty payment)
underscore the riskiness of such ``borrowing.'' Recent evidence
indicates manufacturers are disinclined to take such risks, and we find
it reasonable and prudent to refrain from attempting to simulate such
``borrowing'' in rulemaking analysis.
    Like the previous version, the current CAFE Model provides a basis
to specify (in model inputs) CAFE credits available from model years
earlier than

those being explicitly simulated. For example, with this analysis
representing MYs 2020-2050 explicitly, credits earned in the MY 2015
are made available for use through the MY 2020 (given the current five-
year limit on carry-forward of credits). The banked credits are
specific to both the model year and fleet in which they were earned.
    To increase the realism with which the model transitions between
the early model years (MYs 2020-2023) and the later years that are the
subject of this action, we have accounted for the potential that some
manufacturers might trade credits earned prior to 2020 to other
manufacturers. However, the analysis refrains from simulating the
potential that manufacturers might continue to trade credits during and
beyond the model years covered by this action. In 2018 and 2020, the
analysis included idealized cases simulating ``perfect'' (i.e., wholly
unrestricted) trading of CO2 compliance credits by treating
all vehicles as being produced by a single manufacturer. Even for
CO2 compliance credit trading, these scenarios were not
plausible, because it is exceedingly unlikely that some pairs of
manufacturers would trade compliance credits. NHTSA did not include
such cases for CAFE compliance credits, because EPCA provisions (such
as the minimum domestic passenger car standard requirement) make such
scenarios impossible. At this time, we remain concerned that any
realistic simulation of such trading would require assumptions
regarding which specific pairs of manufacturers might trade compliance
credits, and the evidence to date makes it clear that the credit market
is far from fully ``open.'' \166\
---------------------------------------------------------------------------

    \166\ See, Automotive Innovators, NHTSA-2021-0053-1492, at p.
73.
---------------------------------------------------------------------------

    We also remain concerned that to set standards based on an analysis
that presumes the use of program flexibilities risks making the
corresponding actions mandatory. Some flexibilities--credit carry-
forward (banking) and transfers between fleets in particular--involve
little risk because they are internal to a manufacturer and known in
advance. As discussed above, credit carry-back involves significant
risk because it amounts to borrowing against future improvements,
standards, and production volume and mix. Similarly, credit trading may
also involve significant risk, because the ability of manufacturer A to
acquire credits from manufacturer B depends not just on manufacturer B
actually earning the expected amount of credit, but also on
manufacturer B being willing to trade with manufacturer A, and on
potential interest by other manufacturers. Manufacturers' compliance
plans have already evidenced cases of compliance credit trades that
were planned and subsequently aborted, reinforcing our judgment that,
like credit borrowing, credit trading involves too much risk to be
included in an analysis that informs decisions about the stringency of
future standards. NHTSA will continue to carefully monitor
manufacturers' practices regarding use of credit trading and other
flexibilities to ensure that future analyses appropriately account for
realistic market conditions and statutory requirements as applicable.
    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. If a manufacturer needs to
cover a shortfall that occurs when insufficient opportunities exist to
add technology to achieve compliance with a standard, the model will
apply credits. Otherwise, the manufacturer carries forward credits
until they are about to expire, at which point it will use them before
adding technology that is not considered cost-effective. The model
attempts to use credits that will expire within the next three years as
a means to smooth out technology applications over time to avoid both
compliance shortfalls and high levels of over-compliance that can
result in a surplus of credits. Although it remains impossible
precisely to predict the manufacturer's actual earning and use of
compliance credits, and this aspect of the model may benefit from
future refinement as manufacturers and regulators continue to gain
experience with these provisions, this approach is generally consistent
with manufacturers' observed practices.
    NHTSA introduced the CAFE Public Information Center (PIC) to
provide public access to a range of information regarding the CAFE
program,\167\ including manufacturers' credit balances. However, there
is a data lag in the information presented on the CAFE PIC that may not
capture credit actions across the industry for as much as several
months. Furthermore, CAFE credits that are traded between manufacturers
are adjusted to preserve the gallons saved that each credit
represents.\168\ The adjustment occurs at the time of application
rather than at the time the credits are traded. This means that a
manufacturer who has acquired credits through trade, but has not yet
applied them, may show a credit balance that is either considerably
higher or lower than the real value of the credits when they are
applied. For example, a manufacturer that buys 40 million credits from
Tesla may show a credit balance in excess of 40 million. However, when
those credits are applied, they may be worth only \1/10\ as much--
making that manufacturer's true credit balance closer to 4 million than
40 million (e.g., when another manufacturer uses credits acquired from
Tesla, the manufacturer may only be able to offset a 1 mpg compliance
shortfall, even though the credits' ``face value'' suggests the
manufacturer could offset a 10-mpg compliance shortfall).
---------------------------------------------------------------------------

    \167\ CAFE Public Information Center, https://one.nhtsa.gov/cafe_pic/home (accessed: March 6, 2022).
    \168\ CO2 credits for EPA's program are denominated
in metric tons of CO2 rather than gram/mile compliance
credits and require no adjustment when traded between manufacturers
or fleets.
---------------------------------------------------------------------------

    Specific inputs accounting for manufacturers' accumulated
compliance credits are discussed in TSD Chapter 2.
    In addition to the inclusion of these existing credit banks, the
CAFE Model also updated its treatment of credits in the rulemaking
analysis. EPCA requires that NHTSA set CAFE standards at maximum
feasible levels for each model year without consideration of the
program's credit mechanisms. However, as recent CAFE rulemakings have
evaluated the effects of standards over longer time periods, the early
actions taken by manufacturers required more nuanced representation.
Accordingly, the CAFE Model now provides means to exclude the simulated
application of CAFE compliance credits only from specific model years
for which standards are being set (for this analysis, 2024-2026), while
allowing CAFE credits to be applied in other model years.
    In addition to more rigorous accounting of CAFE and CO2
compliance credits, the model also accounts for air conditioning
efficiency and off-cycle adjustments. NHTSA's program considers those
adjustments in a manufacturer's compliance calculation starting in MY
2017, and specific estimates of each manufacturer's reliance on these
adjustments are discussed above in Section III.C.2.a). Because air
conditioning efficiency and off-cycle adjustments are not credits in
NHTSA's program, but rather adjustments to compliance fuel economy,
they may be included under either a ``standard setting'' or
``unconstrained'' analysis perspective.

    The manner in which the CAFE Model treats the EPA and CAFE AC
efficiency and off-cycle credit programs is similar, but the model also
accounts for AC leakage (which is not part of NHTSA's program). When
determining the compliance status of a manufacturer's fleet (in the
case of EPA's program, PC and LT are the only fleet distinctions), the
CAFE Model weighs future compliance actions against the presence of
existing (and expiring) CO2 credits resulting from over-
compliance with earlier years' standards, AC efficiency credits, AC
leakage credits, and off-cycle credits.
    The model currently accounts for any off-cycle adjustments
associated with technologies that are included in the set of fuel-
saving technologies simulated explicitly (for example, start-stop
systems that reduce fuel consumption during idle or active grille
shutters that improve aerodynamic drag at highway speeds) and
accumulates these adjustments up to levels defined in the Market Data
file. As discussed further in Section III.D.8, this analysis considers
that some manufacturers may apply up to 15.0 g/mi of off-cycle credit
by MY 2032. We considered the potential to model the application of
off-cycle technologies explicitly. However, doing so would require data
regarding which vehicle models already possess these improvements as
well as the cost and expected value of applying them to other models in
the future. Such data are currently too limited to support explicit
modeling of these technologies and adjustments.
    When establishing maximum feasible fuel economy standards, NHTSA is
prohibited from considering the availability of alternatively fueled
vehicles,\169\ and credit provisions related to AFVs that significantly
increase their fuel economy for CAFE compliance purposes. Under the
``standard setting'' perspective, these technologies (pure battery
electric vehicles and fuel cell vehicles \170\) are not available in
the compliance simulation to improve fuel economy. Under the
``unconstrained'' perspective, such as is documented in the Final SEIS,
the CAFE Model considers these technologies in the same manner as other
available technologies and may apply them if they represent cost-
effective compliance pathways. However, under both perspectives, the
analysis continues to include dedicated AFVs that could be produced in
response to CAFE standards outside the model years for which standards
are being set, or for other reasons (e.g., ZEV mandates, as accounted
for in this analysis).
---------------------------------------------------------------------------

    \169\ 49 U.S.C. 32902(h).
    \170\ Dedicated compressed natural gas (CNG) vehicles should
also be excluded in this perspective but are not considered as a
compliance strategy under any perspective in this analysis.
---------------------------------------------------------------------------

    EPCA also provides that CAFE levels may, subject to limitations, be
adjusted upward to reflect the sale of flexible fuel vehicles (FFVs).
Because these adjustments ended in MY 2020, this analysis assumes no
manufacturer will earn FFV credits within the modeling horizon.
    In contrast, the CAA allows consideration of alternative fuels, and
EPA has provided that manufacturers selling PHEVs, BEVs, and FCVs may,
when calculating fleet average CO2 levels, ``count'' each
unit of production as more than a single unit. The CAFE Model accounts
for these ``multipliers.''
    There were no natural gas vehicles in the baseline fleet, and the
analysis did not apply natural gas technology due to cost
effectiveness. The application of production multipliers for natural
gas vehicles for MY 2022 would have no impact on the analysis because
given the state of natural gas vehicle refueling infrastructure, the
cost to equip vehicles with natural gas tanks, the outlook for
petroleum prices, and the outlook for battery prices, we have little
basis to project more than an inconsequential response to this
incentive in the foreseeable future.

D. Technology Pathways, Effectiveness, and Cost

    Vehicle manufacturers meet increasingly stringent fuel economy
standards by applying additional fuel-economy-improving technologies to
their vehicles. To assess what increases in fuel economy standards
could be achievable at what cost, we first need accurate
characterizations of fuel-economy-improving technologies. We collected
data on over 50 fuel-economy-improving technologies that manufacturers
could apply to their vehicles to meet future stringency levels. This
includes determining technology effectiveness values, technology costs,
and how we realistically expect manufacturers could apply the
technologies in the rulemaking timeframe. The characterizations of
these fuel-economy-improving technologies are built on work performed
by DOT, EPA, NAS, and other Federal and state government agencies
including the Department of Energy's Argonne National Laboratory and
the California Air Resources Board.
    In the NPRM we described spending approximately a decade refining
the technology pathways, effectiveness, and cost assumptions used in
successive CAFE Model analyses. We discussed developing guiding
principles to ensure the CAFE Model reasonably simulates manufacturers'
possible real-world compliance behavior. These guiding principles are
as follows:
    The fuel economy improvement from any individual technology must be
considered in conjunction with any other fuel-economy-improving
technologies applied to the vehicle. Certain technologies will have
complementary or non-complementary interactions with the full vehicle
technology system. For example, there is an obvious fuel economy
benefit that results from converting a vehicle with a traditional
internal combustion engine to a battery electric vehicle; however, the
benefit of the electrification technology depends on the other road
load reducing technologies (i.e., mass reduction, aerodynamic, and
rolling resistance) on the vehicle.
    Technologies added in combination to a vehicle will not result in a
simply additive fuel economy improvement from each individual
technology. As discussed in Section III.C.4, full vehicle modeling and
simulation provides the required degree of accuracy to project how
different technologies will interact in the vehicle system. For
example, as discussed further in Sections III.D.1 and III.D.3, a
parallel hybrid architecture powertrain improves fuel economy, in part,
by allowing the internal combustion engine to spend more time operating
at efficient engine speed and load conditions. This reduces the
advantage of adding advanced internal combustion engine technologies,
which also improve fuel economy, by broadening the range of speed and
load conditions for the engine to operate at high efficiency. This
redundancy in fuel savings mechanism results in a reduced effectiveness
improvement when the technologies are added to each other.
    The effectiveness of a technology depends on the type of vehicle
the technology is being applied to. For example, applying mass
reduction technology results in varying effectiveness as the absolute
mass reduced is a function of the starting vehicle mass, which varies
across vehicle technology classes. See Section III.D.4 for more
details.
    The cost and effectiveness values for each technology should be
reasonably representative of what can be achieved across the entire
industry. Each technology model employed in the analysis is designed to
be representative of a wide range of specific technology applications
used in industry. Some vehicle manufacturer's systems may

perform better and cost less than our modeled systems and some may
perform worse and cost more. However, employing this approach will
ensure that, on balance, the analysis captures a reasonable level of
costs and benefits that would result from any manufacturer applying the
technology.
    The baseline for cost and effectiveness values must be identified
before assuming that a cost or effectiveness value could be employed
for any individual technology. For example, as discussed further in
Section III.D.1.d) below, this analysis uses a set of engine map models
that were developed by starting with a small number of baseline engine
configurations, and then, in a very systematic and controlled process,
adding specific well-defined technologies to create a new map for each
unique technology combination.
    Historically, we have received comments concerned with specific
technology assumptions, such as technology effectiveness or cost, or
how we applied adoption features. In response to this proposal,
however, commenters instead focused on broader portions of our modeling
approach. Specifically, we received comments about the range of
technologies considered on the advanced engine technology pathway and
hybrid/electric pathway, considering the potential future of light duty
vehicle fuel economy and greenhouse gas emissions regulations. We did
still receive some comments regarding specific technology values, but
fewer than previous rules.\171\
---------------------------------------------------------------------------

    \171\ Comments regarding specific technology modeling values,
such as battery cost, strong hybrid electric vehicle costs, and high
compression ratio engine adoptions features are addressed under
their respective paragraphs below.
---------------------------------------------------------------------------

    Vehicle manufacturers emphasized the diminishing returns to
investing in advanced internal combustion engine technologies, and a
current trend of shifting resources from ICE development into
electrification technologies. Ford Motor Company (Ford) commented that
``[t]he transformation of the light-duty fleet toward electrification
will require unprecedented levels of ingenuity and investment to
succeed. Over the last 10 years, rapid improvements in internal
combustion engine (ICE) fuel efficiency and criteria emissions
performance have been accomplished. Further improvements are possible,
but will be marginal, and will come at high cost.'' \172\ Similarly,
Volkswagen Group of America (Volkswagen) commented that they have
``publicly stated that investments into combustion technologies will
wane with a point in the next several years where there will be no new
combustion engine families developed for the Group. Volkswagen
recognizes that remaining combustion models will continue to be sold in
high volume for the next several years and that it is important to
preserve the fuel economy of remaining ICEs as electrification volumes
increase. As noted earlier, Volkswagen's remaining ICE engines will
[sic]primary focus on evolutions of existing downsized, charged engines
to incorporate incremental hardware and software improvements.'' \173\
Toyota Motor North America, Inc. (Toyota) also commented that ``data
has consistently documented that even advanced ICE-only powertrains
will fall short of the proposed standards and that while future
advancements are possible, a point of diminishing returns is in part
driving the transition to electrified powertrains, including
conventional hybrids.'' \174\
---------------------------------------------------------------------------

    \172\ Ford, Docket No. NHTSA-2021-0053-1545-A1, at p. 1.
    \173\ Volkswagen, Docket No. NHTSA-2021-0053-1548-A1, at pp. 21-
22.
    \174\ Toyota, Docket No. NHTSA-2021-0053-1568, at p. 2.
---------------------------------------------------------------------------

    In contrast, Union of Concerned Scientists (UCS) acknowledged that
``given automaker investments and future product plans, it is likely
that manufacturers' compliance strategies will include increased
electrification. However, there are significant opportunities for
improvements to internal combustion engine vehicles as well.'' \175\
Similarly, ICCT provided examples of vehicle technologies that can
``boost ICE efficiency well beyond even HCR2 efficiency levels,''
including technologies that are not modeled in the analysis like
negative valve overlap (NVO) fuel reforming, passive prechamber
engines, and high energy ignition systems.\176\ Borg Warner also
provided hydrogen combustion as ``an advanced technology that has been
under development for some time and could be more rapidly deployed in
high volumes to make an impact.'' \177\
---------------------------------------------------------------------------

    \175\ UCS, Docket No. NHTSA-2021-0053-1567-A1, at p. 6.
    \176\ ICCT, Docket No. NHTSA-2021-0053-1581-A1, at p. 2.
    \177\ BorgWarner Inc. (BorgWarner), Docket No. NHTSA-2021-0053-
1473, at p. 2.
---------------------------------------------------------------------------

    First and foremost, we want to emphasize that the purpose of this
regulation is to set maximum feasible CAFE standards for passenger cars
and light trucks that improve energy conservation, and not to advocate
for specific technology solutions. We acknowledge that the industry is
not going to quickly abandon ICE technologies and we anticipate
improvements in those vehicles for years to come; however, we also
acknowledge that many manufacturers have announced significant shifts
in product line-up, moving toward electrification technologies and
likely slowing the rate of new ICE technology introduction.\178\ That
said, we agree with comments urging us to staying abreast of the
feasibility of advanced engine and other powertrain technologies. For
this analysis we evaluated over 50 different technologies for
effectiveness and cost and continue to research the feasibility of
additional technology models. However, we also agree with comments
regarding constraining some advanced technology options as an
acknowledgment of the realities of limited investment resources.
Accordingly, we expect an actual pathway to compliance in the
rulemaking timeframe to fall somewhere between the extremes suggested
by the commenters above. This expectation is discussed further in the
results/legal justification section \179\ and in the engine technology
section.\180\
---------------------------------------------------------------------------

    \178\ ``Mercedes-Benz Prepares to Go All-Electric,'' Mercedes-
Benz Media Newsroom USA (Jul. 22, 2021), https://media.mbusa.com/releases/release-ee5a810c1007117e79e1c871354679e4-mercedes-benz-prepares-to-go-all-electric (accessed: February 16, 2022).
``Investments into combustion engines and plug-in hybrid
technologies will drop by 80% between 2019 and 2026.''; Hannah Lutz,
``Shifting into E,'' Automotive News (Jul. 26, 2021). ``Some
existing vehicles, such as the Chevy Malibu and Camaro, won't stick
to the standard cadence of face-lifts and redesigns. Instead,
they'll ride out the current generation before making way for EVs.''
Jordyn Grzelewski, ``Ford Slated to Spend More On EVs Than On
Internal Combustion Engine Vehicles in 2023,'' The Detroit News
(Aug. 2, 2021).; Lindsay Chappell, ``All-In On EVs,'' Automotive
News (May 17, 2021). ``Mini will become an all-electric brand by
early 2030, and the British marque will roll out its last new
combustion engine variant in 2025.'' (Emphasis added); Bibhu
Pattnaik, ``Audi Will Not Introduce ICE Vehicles After 2026, No
Hybrid Vehicles Either,'' Benzinga (Jun. 19, 2021), https://finance.yahoo.com/news/audi-not-introduce-ice-vehicles-160320055.html (accessed February 16, 2022); Mike Colias, ``Gas
Engines, and the People Behind Them, Are Cast Aside for Electric
Vehicles,'' The Wall Street Journal (Jul. 23, 2021). ``Auto
executives have concluded, to varying degrees, that they can't meet
tougher tailpipe-emission rules globally by continuing to improve
gas or diesel engines . . . Over the past several decades, auto
makers in most years rolled out between 20 and 70 new engines
globally, according to research firm IHS Markit. That number will
fall below 10 this year, and then essentially go to zero, the
research firm said.''
    \179\ See Section VI.
    \180\ See Section III.D.1.
---------------------------------------------------------------------------

    As a result, we believe the range of technologies modeled on the
advanced engine technologies and hybrid/electric pathways appropriately
represent the range of technologies that will be available in the
rulemaking time frame. The technologies in our analysis are

based on guidance from NAS \181\ and align with technologies considered
by the EPA as part of their final rulemaking for MYs 2023-2026.\182\
---------------------------------------------------------------------------

    \181\ 2021 NAS Report.
    \182\ For detailed discussions on all the technologies used in
this analysis see TSD Chapter 3, For more detailed discussion of the
comments discussed here see Section III.D.1.
---------------------------------------------------------------------------

    However, the CAFE Model is a tool that offers many ways to evaluate
a cost-effective technology pathway for vehicle manufacturers to reach
given levels of CAFE standards, based on user-provided inputs and
constraints. As a result of the concerns expressed in the comments
above, we included a sensitivity analysis with inputs assuming that
vehicle manufacturers would no longer deploy advanced engine
technologies.\183\ The sensitivity analysis demonstrates a technology
path where manufacturers choose to stop applying additional ICE
improvements and only invest in partial or full electrification
technologies going forward.\184\ Our ``no advanced engines''
sensitivity analysis shows a modest increase in strong hybrid (SHEV)
and plug-in hybrid (PHEV) technology adoption compared to the reference
analysis. This modest increase, about 5-6 percent increased technology
penetration of SHEVs and PHEVs, enables the manufacturers to meet more
stringent standards without the adoption of additional advanced ICE
technology. The ``no advanced engine'' technology pathway increases the
estimated average vehicle costs by $25 over the reference analysis by
MY 2029.\185\
---------------------------------------------------------------------------

    \183\ See TSD Chapter 3.1 for a definition of advanced engine
technologies.
    \184\ See FRIA Chapter 7.1 for more details; the sensitivity
case ``conv-tech-imprlimited'' is referred to as ``no advanced
engine'' in this discussion.
    \185\ Effects of standards on the fleet out to MY 2029 are
considered to account for years the regulation covers, and years of
potential carry back credit use.
---------------------------------------------------------------------------

    In consideration of comments received on the NPRM analysis and the
results of additional sensitivity analysis, we believe that the
technologies included in the CAFE Model's technology tree are currently
appropriate, and we have made no changes in the technology tree for the
analysis supporting this final rule. We believe the selected
technologies provide a realistic representation of options that
manufacturers have to comply with standards in the rulemaking
timeframe.
    We made changes to just three technology inputs from the NPRM to
this final rule. The changes are discussed in detail in the respective
technology sections, and include:
     Decreased eCVT and cable costs associated with strong
hybrid electric vehicle technologies;
     Decreased start/stop micro hybrid battery costs; and
     Correction of the high compression ratio with cylinder
deactivations setting in the Technologies input file.
    The following sections discuss the engine, transmission,
electrification, mass reduction, aerodynamic, tire rolling resistance,
and other vehicle technologies considered in this analysis. Each
section discusses how we define the technology in the CAFE Model,\186\
how we assign the technology to vehicles in the MY 2020 analysis fleet
used as a starting point for this analysis, any adoption features that
we apply to the technology so the analysis better represents
manufacturers' real-world decisions, the technology effectiveness
values, and technology cost. In addition, each section discusses the
comments received for that technology pathway, and the changes made to
input values because of comments.
---------------------------------------------------------------------------

    \186\ Note, due to the diversity of definitions industry uses
for technology terms, or in describing the specific application of
technology, the terms defined here may differ from how the
technology is defined in the industry.
---------------------------------------------------------------------------

    Please note that the following technology effectiveness sections
provide examples of the range of effectiveness values that a technology
could achieve when applied to the entire vehicle system, in conjunction
with the other fuel-economy-improving technologies already in use on
the vehicle.\187\ To see the incremental effectiveness values for any
particular vehicle moving from one technology key to a more advanced
technology key, see the FE_1 and FE_2 Adjustments files that are
integrated in the CAFE Model executable file. Similarly, the technology
costs provided in each section are examples of absolute costs seen in
specific model years (MYs 2020, 2025, and 2030 for most technologies),
for specific vehicle classes.\188\ Please refer to the Technologies
file to see all absolute technology costs used in the analysis across
all model years.
---------------------------------------------------------------------------

    \187\ This serves as a visual example of the conditional
effectiveness of adding `one technology at a time' discussed in the
guiding principles above.
    \188\ The values shown serve as examples of cost origins and how
cost values were treated to account for changes due to learning or
time value of money.
---------------------------------------------------------------------------

1. Engine Paths
    We classified the extensive variety of light duty vehicle internal
combustion (IC) engine technologies into discrete engine technology
paths for this analysis. These engine technology paths model the most
representative characteristics, costs, and performance of the fuel-
economy improving technologies likely available during the rulemaking
time frame. It is our intent that the technology paths be
representative of the range of potential performance levels for each of
the technologies. We also acknowledge that some new and pre-production
technologies are not part of this analysis because of uncertainties in
the cost and capabilities of these emerging technologies. As a result,
we did not include technologies unlikely to be feasible in the
rulemaking timeframe, technologies unlikely to be compatible with U.S.
fuels, or technologies where there were not appropriate data available
to allow the simulation of effectiveness across all vehicle technology
classes in this analysis.
    We briefly discuss IC engine technologies considered in this
analysis, the CAFE Model's general engine technology categories, and
how we assign engine technologies in the analysis fleet in the
following sections. We also touch on engine technologies' adoption
features, costs, and effectiveness when used as part of a full vehicle
model. For a complete discussion on all of these topics please see the
TSD.\189\
---------------------------------------------------------------------------

    \189\ See TSD Chapter 3.1.
---------------------------------------------------------------------------

(a) Engine Modeling in the CAFE Model
    Engine modeling in the CAFE Model involves the application of
internal combustion engine technologies that manufacturers use to
improve fuel economy. Of the engine technologies we model, some can be
incorporated into existing engines with minor or moderate changes, but
many require an entirely new engine architecture. As a result, we
divide engine technologies into two categories, ``basic engine
technologies'' and ``advanced engine technologies.'' ``Basic engine
technologies'' refer to technologies adaptable to an existing engine
with minor or moderate changes to the engine. ``Advanced engine
technologies'' refer to technologies that generally require significant
changes or an entirely new engine architecture.
    We do not intend for the words ``basic'' and ``advanced'' to confer
any information about the level of sophistication of the technology or
to indicate relative cost. Many advanced engine technology definitions
include some basic engine technologies in their design, and these basic
technologies are accounted for in the costs and effectiveness values of
the advance engine. Figure III-7 shows how we organize the engine
technologies pathways evaluated in the compliance simulation. We
briefly describe each

engine technology below. It is important to note the ``Basic Engine
Path'' shows that every engine starts with VVT and can add one, some,
or all of the technologies in the dotted box, as discussed in Section
III.D.1.a)(1).
[GRAPHIC] [TIFF OMITTED] TR02MY22.064

    In response to our proposal, some commenters, particularly in the
automotive industry, commented in support of the number of advanced
engine technologies in the engine tree especially in light of
forthcoming electrification investments. Other commenters, in
particular some environmental groups, commented with examples of
advanced engine technologies that they believed we should consider in
the analysis.
    More specifically, the automotive industry believes that the future
of ICE technology is very limited, as manufacturers turn their focus to
the electrification of the fleet. The new focus would result in
limitation or even removal of resources dedicated to further ICE
development. Major manufacturers provided information indicating that
they will not develop advanced engine technologies beyond the current
generation. Commenters who provided information suggesting engine
technology may stagnate as manufacturers dedicate resources to
electrification technology included Ford, Toyota, Volkswagen, and the
Auto Innovators.
    Ford stated:

    Over the last 10 years, rapid improvements in internal
combustion engine (ICE) fuel efficiency and criteria emissions
performance have been accomplished. Further improvements are
possible, but will be marginal, and will come at high cost. Ford
requests that the agencies carefully weigh these considerations in
the current and future rulemakings to ensure that resources and
investment are not diverted from our primary objective: Fulfilling
President Biden's goal of achieving 40-50 [percent] ZEV sales by
2030.\190\
---------------------------------------------------------------------------

    \190\ Ford, Docket No. NHTSA-2021-0053-1545-A1, at p. 1.

---------------------------------------------------------------------------
    Toyota stated:

    Toyota has provided extensive information, in public comments
and under CBI, on the effectiveness of [CO2] reduction
technologies including those for advanced gasoline engines.\191\ The
data has consistently documented that even advanced ICE-only
powertrains will fall short of the proposed standards and that while
future advancements are possible, a point of diminishing returns is
in part driving the transition to electrified powertrains, including
conventional hybrids. EPA notes manufacturer plans and announcements
of ``a rapidly growing shift in investment away from internal-
combustion technologies and toward high levels of electrification.''
192 193
---------------------------------------------------------------------------

    \191\ Toyota comments on: Draft Technical Assessment Report on
2022-2025 Model Year Light-Duty Vehicle Greenhouse Gas Emission
Standards and Corporate Average Fuel Economy Standards, EPA-420-D-
16-900 pp. 2-5 and Appendix 1; Proposed Determination on the
Appropriateness of the Model Year 2022-2025 Light-Duty Vehicle
Greenhouse Gas Emissions Standards under the Midterm Evaluation,
EPA-420-R-16-020, pp. 3-8; Request for Comment on Reconsideration of
the Final Determination of the Mid-Term Evaluation of Greenhouse Gas
Emissions Standards for Model Year 2022-2025 Light-Duty Vehicles;
Request for Comment on Model Year 2021 Greenhouse Gas Emissions
Standards, EPA-HQ-OAR-2015-0827, pp. 3-9; Safer Affordable Fuel-
Efficient (SAFE) Vehicles Rule For Model Years 2020-2026 Model Year
Passenger Cars and Light Trucks, NHTSA-2018-0067; EPA-HQ-OAR-2018-
0283, pp. 2-9 and Appendices A-C.
    \192\ U.S. EPA. Revised 2023 and Later Model Year Light-Duty
Vehicle GHG Emissions Standards, EPA-HQ-OAR-2021-0208, August 2021,
at p. 43766.
    \193\ Toyota, Docket No. NHTSA-2021-0053-1568, at p. 2.

---------------------------------------------------------------------------
    Volkswagen stated:

    As noted earlier, Volkswagen has implemented a capital spending
plan and technology roadmap that primary focuses on electrification
as our main pathway for achieving deep decarbonization and petroleum
reduction goals. In parallel with increasing consumer demand for
electrification, the increase in States with ZEV mandates and the
emergence and recent passage of State legislation banning
combustion, it is unlikely that OEMs will invest significant
resources in researching new combustion technologies or developing
all new powertrains.
    Engine development programs are long-lead time, often requiring
5 years to fully design and validate new engines. Powertrain
production is also capital intensive, and the

high upfront costs often consider 10 plus years of steady volume to
amortize the production and development costs. The effects have been
studied extensively by NHTSA and the National Academies and are
reflected in such factors as Retail Price Equivalency (RPE) values.
However, with the shift to legislative and regulatory programs that
are reducing and eliminating future market volumes for combustion
technologies, it is unlikely that OEMs will make significant
investments in this space.
    Volkswagen has publicly stated that investments into combustion
technologies will wane with a point in the next several years where
there will be no new combustion engine families developed for the
Group. Volkswagen recognizes that remaining combustion models will
continue to be sold in high volume for the next several years and
that it is important to preserve the fuel economy of remaining ICEs
as electrification volumes increase. As noted earlier, Volkswagen's
remaining ICE engines will primarily focus on evolutions of existing
downsized, charged engines to incorporate incremental hardware and
software improvements.\194\
---------------------------------------------------------------------------

    \194\ Volkswagen, Docket No. NHTSA-2021-0053-1548-A1, at pp. 21-
22.

---------------------------------------------------------------------------
    Auto Innovators stated:

    Manufacturers are also already announcing plans to reduce or
eliminate investments in ICEs. Some automotive executives are saying
that they no longer intend to develop new ICEs, are no longer
setting aside significant money for new ICEs, or that ICEs will only
get incremental work. Others, such as policymakers, may suggest that
little or no investment is needed in ICE technologies because they
are ``off-the-shelf'' or present in the fleet today. This view
ignores that technologies can't simply be ``bolted on'' to existing
engines. Instead, they must be carefully integrated into existing
designs, requiring engineering resources, and in many cases, new
engine designs. A new engine design can cost as much as $1
billion.\195\
---------------------------------------------------------------------------

    \195\ Auto Innovators, Docket No. NHTSA-2021-0053-0021-A1, at 8
(citing ``Mercedes-Benz Prepares to Go All-Electric,'' Mercedes-Benz
Media Newsroom USA (Jul. 22, 2021), https://media.mbusa.com/releases/release-ee5a810c1007117e79e1c871354679e4-mercedes-benz-prepares-to-go-all-electric (accessed: February 16, 2022).
``Investments into combustion engines and plug-in hybrid
technologies will drop by 80% between 2019 and 2026.''; Hannah Lutz,
``Shifting into E,'' Automotive News (Jul. 26, 2021). ``Some
existing vehicles, such as the Chevy Malibu and Camaro, won't stick
to the standard cadence of face-lifts and redesigns. Instead,
they'll ride out the current generation before making way for
EVs.''; Jordyn Grzelewski, ``Ford Slated to Spend More On EVs Than
On Internal Combustion Engine Vehicles in 2023,'' The Detroit News
(Aug. 2, 2021).; Lindsay Chappell, ``All-In On EVs,'' Automotive
News (May 17, 2021). ``Mini will become an all-electric brand by
early 2030, and the British marque will roll out its last new
combustion engine variant in 2025.'' (Emphasis added.); Bibhu
Pattnaik, ``Audi Will Not Introduce ICE Vehicles After 2026, No
Hybrid Vehicles Either,'' Benzinga (Jun. 19, 2021), https://finance.yahoo.com/news/audi-not-introduce-ice-vehicles-160320055.html (accessed: February 16, 2022), Mike Colias, ``Gas
Engines, and the People Behind Them, Are Cast Aside for Electric
Vehicles,'' The Wall Street Journal (Jul. 23, 2021). ``Auto
executives have concluded, to varying degrees, that they can't meet
tougher tailpipe-emission rules globally by continuing to improve
gas or diesel engines . . . Over the past several decades, auto
makers in most years rolled out between 20 and 70 new engines
globally, according to research firm IHS Markit. That number will
fall below 10 this year, and then essentially go to zero, the
research firm said.'').

    These comments reflect an increasing industry trend to divest from
internal combustion engine technology, to increase investments in
alternative powertrains such as electrification or fuel cells. The
provided comments also support NAS's finding: ICE technology
advancements are seeing diminishing returns, with future gains
requiring significant investment, driving manufacturers to alternative
technology development in place of further ICE development, such as
electrification.\196\
---------------------------------------------------------------------------

    \196\ 2021 NAS Report, Finding 4.7, at p. 70.
---------------------------------------------------------------------------

    On the other hand, some commenters were concerned that our modeled
technology paths do not adequately keep pace with potential significant
improvements in ICE technologies that manufacturers will continue to
make. ICCT and UCS suggested that additional advanced versions of
modeled technologies as well as additional technologies should be added
to the engine technology paths. Both commenters provided information on
emerging technologies currently in the research phase, and the
commenters stated these new technologies should be included in the
engine technology path options.
    ICCT stated, ``two recent reports demonstrate that further
technology improvements are coming that can boost ICE efficiency well
beyond even HCR2 efficiency levels.'' \197\ ICCT further stated,
``Indeed, it appears that no technology improvements or cost reductions
from EPA's independent evaluations or from any comments submitted to
NHTSA or new studies over the last 5 years were included in the
proposed rule, beyond the additional of DEAC to HCR1. This basis for
NHTSA's analysis is an overly conservative assessment of the costs of
the standards.''
---------------------------------------------------------------------------

    \197\ ICCT, Docket No. NHTSA-2021-0053-1581-A1, at 2 (citing AVL
Webinar on Passenger Car powertrain 4.x--Fuel Consumption,
Emissions, and Cost on June 2, 2020 https://www.avl.com/-/passenger-car-powertrain-4.x-fuel-consumption-emissions-and-cost plus slides
are attached to these comments (AVL 2020); Roush report on Gasoline
Engine Technologies for Improved Efficiency (Roush 2021 LDV) https://www.regulations.gov/comment/EPA-HQ-OAR-2021-0208-0210).
---------------------------------------------------------------------------

    UCS also provided a comment suggesting the need for more advanced
engine technology models:

    Given automaker investments and future product plans, it is
likely that manufacturers' compliance strategies will include
increased electrification. However, there are significant
opportunities for improvements to internal combustion engine
vehicles as well. The importance of both strategies is evident in
our own modeling. Internal combustion engine vehicles will continue
to improve in the timeframe considered under this rule and show no
sign of exhausting their potential. While our modeling suggests that
manufacturers will deploy a significant number of EVs due to the
improvement they can make in a fleet's performance, this is by no
means the only path available, as indicated by the relatively low
levels of vehicle technology modeled as being deployed in the
remaining gasoline-powered fleet, which leave many other options
open.\198\
---------------------------------------------------------------------------

    \198\ UCS, Docket No. NHTSA-2021-0053-1567-A1, at 6 (citing
Murphy, John. 2021. ``US Automotive Product Pipeline: Car Wars 2022-
2025 (Electric Vehicles shock the product pipeline).'' Media
briefing, June 10, 2021, on behalf of Bank of America Securities.
https://s3-prod.autonews.com/2021-06/BofA%20Global%20Research%20Car%20Wars.pdf).

    For this final rule analysis, the agency has made no changes to the
Engine technology pathway.\199\ While we agree with the potential of
the technologies as they are described in the provided comments,\200\
we do not believe that the application of the technologies is feasible
in the rulemaking timeframe. As stated in the NPRM and discussed above,
we did not include technologies unlikely to be feasible in the
rulemaking timeframe, technologies unlikely to be compatible with U.S.
fuels, or technologies for which there were not appropriate data
available to allow the simulation of effectiveness across all vehicle
technology classes used in the analysis. For example, ICCT recommended
the inclusion of passive prechamber combustion in our analysis.
Currently, the technology is under development by two vendors, but
neither vendor has indicated the system has progressed past the
technology demonstration phase, or the technology is currently only
used for specialty purposes.201 202
---------------------------------------------------------------------------

    \199\ See TSD Chapter 3.1 for a detailed discussion of the
engine technology pathways used in the final rule analysis.
    \200\ ICCT comments at pp. 8-10.
    \201\ https://www.iav.com/en/what-moves-us/pre-chamber-ignition-small-spark-great-effect/--Accessed 10DEC2021.
    \202\ https://www.mahle-powertrain.com/en/experience/mahle-jet-ignition/--Accessed 10DEC2021.
---------------------------------------------------------------------------

    In light of the comments provided by manufacturers, such as
Volkswagen's comment above, it is very unlikely that major
manufacturers will introduce these technologies in the time frame of
the regulation.203 204 We also believe this

approach is in agreement with the assessments on ICE technologies
provided by NAS, discussed above.\205\
---------------------------------------------------------------------------

    \203\ Volkswagen, at 21-22 (``Engine development programs are
long-lead time, often requiring 5 years to fully design and validate
new engines. Powertrain production is also capital intensive and the
high upfront costs often consider 10 plus years of steady volume to
amortize the production and development costs.'').
    \204\ Auto Innovators, at 8 (``Others, such as policymakers, may
suggest that little or no investment is needed in ICE technologies
because they are ``off-the-shelf'' or present in the fleet today.
This view ignores that technologies can't simply be ``bolted on'' to
existing engines. Instead, they must be carefully integrated into
existing designs, requiring engineering resources, and in many
cases, new engine designs. A new engine design can cost as much as
$1 billion.'').
    \205\ 2021 NAS Report, at 369 (``Internal combustion engines
(ICEs) will continue to play a significant role in the new vehicle
fleet in MY 2025-2035 in ICE-only vehicles, as well as in hybrid
electric vehicles (HEVs) from mild hybrids to plug-in hybrids, but
will decrease in number with increasing battery electric vehicle
(BEV) and fuel cell electric vehicle penetration. In this period,
manufacturers will continue to develop and deploy technologies to
further improve the efficiency of conventional powertrains, for ICE-
only vehicles and as implemented in HEVs. Developments in the ICE
for hybrids will advance toward engines optimized for a limited
range of engine operating conditions, with associated efficiency
benefits. Major automakers are on differing paths, with some
focusing their research and development and advanced technology
deployment more squarely on BEVs, and others more focused on
advanced HEVs to maximize ICE efficiency.'').
---------------------------------------------------------------------------

(1) Basic Engines
    We applied basic engine technologies individually or in combination
with other basic engine technologies in the CAFE Model. The basic
engine technologies we used include variable valve timing (VVT),
variable valve lift (VVL), stoichiometric gasoline direct injection
(SGDI), and cylinder deactivation. The cylinder deactivation
technologies we used includes a basic level (DEAC) and an advanced
level (ADEAC). DOT applies the basic engine technologies across two
engine architectures: Dual over-head camshaft (DOHC) engine
architecture and single over-head camshaft (SOHC) engine architecture.
    VVT: Variable valve timing is a family of valve-train designs that
dynamically adjusts the timing of the intake valves, exhaust valves, or
both, in relation to piston position. VVT can reduce pumping losses,
provide increased engine torque and horsepower over a broad engine
operating range, and allow unique operating modes, such as Atkinson
cycle operation, to further enhance efficiency.\206\ VVT is nearly
universally used in the MY 2020 fleet. VVT enables more control of in-
cylinder air flow for exhaust scavenging and combustion relative to
fixed valve timing engines. Engine parameters such as volumetric
efficiency, effective compression ratio, and internal exhaust gas
recirculation (iEGR) can all be enabled and controlled by a VVT system.
---------------------------------------------------------------------------

    \206\ 2015 NAS Report, at p. 31.
---------------------------------------------------------------------------

    VVL: Variable valve lift dynamically adjusts the distance a valve
travels from the valve seat. The dynamic adjustment can optimize
airflow over a broad range of engine operating conditions. The
technology can increase effectiveness by reducing pumping losses and by
affecting the fuel and air mixture motion and combustion in-
cylinder.\207\ VVL is less common in the MY 2020 fleet than VVT, but
still prevalent. Some manufacturers have implemented a limited,
discrete approach to VVL. The discrete approach allows only limited
(e.g., two) valve lift profiles versus allowing a continuous range of
lift profiles.
---------------------------------------------------------------------------

    \207\ 2015 NAS Report, at p. 32.
---------------------------------------------------------------------------

    SGDI: Stoichiometric gasoline direct injection sprays fuel at high
pressure directly into the combustion chamber, which provides cooling
of the in-cylinder charge via in-cylinder fuel vaporization to improve
spark knock tolerance and enable an increase in compression ratio and/
or more optimal spark timing for improved efficiency.\208\ SGDI is
common in the MY 2020 fleet, and the technology is used in many
advanced engines as well.
---------------------------------------------------------------------------

    \208\ 2015 NAS Report, at p. 34.
---------------------------------------------------------------------------

    DEAC: Basic cylinder deactivation disables intake and exhaust
valves and turns off fuel injection for the deactivated cylinders
during light load operation. DEAC is characterized by a small number of
discrete operating configurations.\209\ The engine runs temporarily as
though it were a smaller engine, reducing pumping losses and improving
efficiency. DEAC is present in the MY 2020 baseline fleet.
---------------------------------------------------------------------------

    \209\ 2015 NAS Report, at p. 33.
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    ADEAC: Advanced cylinder deactivation systems, also known as
rolling or dynamic cylinder deactivation systems, allow a further
degree of cylinder deactivation than the base DEAC. ADEAC allows the
engine to vary the percentage of cylinders deactivated and the sequence
in which cylinders are deactivated, essentially providing
``displacement on demand'' for low load operations. A small number of
vehicles have ADEAC in the MY 2020 baseline fleet.
    Section III.D.1.d) contains additional information about each basic
engine technology used in this analysis, including information about
the engine map models used in the full vehicle technology effectiveness
modeling.
(2) Advanced Engines
    We define advanced engine technologies in the analysis as
technologies that require significant changes in engine structure, or
an entirely new engine architecture.\210\ Currently there are two types
of advanced engine technologies, the application of alternate
combustion cycles or application of forced induction to the engine.
Each advanced engine technology has a discrete pathway for progression
to improved versions of the technology, as seen above in Figure III-7.
The advanced engine technology pathways include a turbocharged pathway,
a high compression ratio (Atkinson) engine pathway, a variable turbo
geometry (Miller Cycle) engine pathway, a variable compression ratio
pathway, and a diesel engine pathway. Although the CAFE Model includes
a compressed natural gas (CNG) pathway, that technology is a baseline-
only technology and was not included in the analysis; there are no
dedicated CNG vehicles in the MY 2020 analysis fleet.
---------------------------------------------------------------------------

    \210\ Examples of this include but are not limited to changes in
cylinder count, block geometry or combustion cycle changes.
---------------------------------------------------------------------------

    TURBO: Forced induction engines, or turbocharged downsized engines,
are characterized by technology that can create greater-than-
atmospheric pressure in the engine intake manifold when higher output
is needed. The raised pressure results in an increased amount of
airflow into the cylinder supporting combustion, increasing the
specific power of the engine. Increased specific power means the engine
can generate more power per unit of cylinder volume. The higher power
per cylinder volume allows the overall engine volume to be reduced,
while maintaining performance. The overall engine volume decrease
results in an increase in fuel efficiency by reducing parasitic loads
associated with larger engine volumes.\211\
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    \211\ 2015 NAS Report, at p. 34.
---------------------------------------------------------------------------

    Cooled exhaust gas recirculation is also part of the advanced
forced induction technology path. The basic recycling of exhaust gases
using VVT is called internal EGR (iEGR) and is included as part of the
performance improvements provided by the VVT basic engine technology.
Cooled EGR (cEGR) is a second method for diluting the incoming air that
takes exhaust gases, passes them through a heat exchanger to reduce
their temperature, and then mixes them with incoming air in the intake
manifold.\212\ As discussed

in Section III.D.1.d), many advanced engine maps include EGR.
---------------------------------------------------------------------------

    \212\ 2015 NAS Report, at p. 35.
---------------------------------------------------------------------------

    Five levels of turbocharged engine downsizing technologies are
considered in this analysis: A `basic' level of turbocharged downsized
technology (TURBO1), an advanced turbocharged downsized technology
(TURBO2), an advanced turbocharged downsized technology with cooled
exhaust gas recirculation applied (cEGR), a turbocharged downsized
technology with basic cylinder deactivation applied (TURBOD), and a
turbocharged downsized technology with advanced cylinder deactivation
applied (TURBOAD).
    HCR: Atkinson engines, or high compression ratio engines, represent
a class of engines that achieve a higher level of fuel efficiency by
implementing an alternate combustion cycle.\213\ Historically, the Otto
combustion cycle has been used by most gasoline-based spark ignition
engines. Increased research into improving fuel economy has resulted in
the application of alternate combustion cycles that allow for greater
levels of thermal efficiency. One such alternative combustion cycle is
the Atkinson cycle. Atkinson cycle operation is achieved by allowing
the expansion stroke of the engine to overextend, allowing the
combustion products to achieve the lowest possible pressure before the
exhaust stroke.214 215 216
---------------------------------------------------------------------------

    \213\ See the 2015 NAS Report, Appendix D, for a short
discussion on thermodynamic engine cycles.
    \214\ Otto cycle is a four-stroke cycle that has four piston
movements over two engine revolutions for each cycle. First stroke:
Intake or induction; seconds stroke: Compression; third stroke:
Expansion or power stroke; and finally, fourth stroke: Exhaust.
    \215\ Compression ratio is the ratio of the maximum to minimum
volume in the cylinder of an internal combustion engine.
    \216\ Expansion ratio is the ratio of maximum to minimum volume
in the cylinder of an IC engine when the valves are closed (i.e.,
the piston is traveling from top to bottom to produce work).
---------------------------------------------------------------------------

    Descriptions of Atkinson cycle engines and Atkinson mode or
Atkinson-enabled engine technologies have been used interchangeably in
association with high compression ratio (HCR) engines, for past
rulemaking analyses. Both technologies achieve a higher thermal
efficiency than traditional Otto cycle-only engines, however, the two
engine types operate differently. For purposes of this analysis,
Atkinson technologies can be categorized into two groups to reduce
confusion: (1) Atkinson-enabled engines and (2) Atkinson engines.
    Atkinson-enabled engines, or high compression ratio (HCR) engines,
dynamically swing between an Otto cycle like behavior (very little
expansion over-stroke) to a more Atkinson cycle intensive behavior
(large expansion over-stroke) based on engine demand. During high loads
the engine will reduce the Atkinson level behavior by increasing the
dynamic compression ratio, reducing over-stroke, sacrificing efficiency
for increased power density. While at low loads the engine will
increase the Atkinson level behavior by reducing the dynamic
compression ratio, increasing the over-stroke, improve efficiency but
reduce power density. The hybrid combustion cycle can be used to
address, but not eliminate, the low power density issues that can
constrain the application of an Atkinson-only engine and allow for a
wider application of the technology.
    The level of efficiency improvement experienced by a vehicle
employing an Atkinson-enabled engine is directly related to how much of
the engine's operation time is spent at high Atkinson levels. Vehicles
that must maintain a high level of torque reserve, that experience
operation at a high load for long portions of their operating cycle, or
that have high base road loads, will see little to no benefit from this
technology compared with other advanced engine technologies. This power
density constraint results in manufacturers typically limiting the
application of this technology to vehicles with a lower road load, and
lower relative need for torque reserves.
    Three HCR or Atkinson-enabled engines are available in the
analysis: (1) The baseline Atkinson-enabled engine (HCR0), (2) the
enhanced Atkinson enabled engine (HCR1), and finally, (3) the enhanced
Atkinson enabled engine with cylinder deactivation (HCR1D).
    Next, Atkinson engines (as opposed to Atkinson-enabled engines,
discussed above) in this analysis are defined as engines that operate
full-time in Atkinson cycle. The most common method of achieving
Atkinson operation is the use of late intake valve closing. This method
allows backflow from the combustion chamber into the intake manifold,
reducing the dynamic compression ratio, and providing a higher over-
expansion ratio during the expansion stroke. The higher expansion ratio
improves thermal efficiency but reduces power density. The low power
density relegates these engines to hybrid vehicle (SHEVPS) applications
only in this analysis. Coupling the engines to electric motors and
significantly reducing road loads compensates for the lower power
density and maintains desired performance levels for the vehicle.\217\
The Toyota Prius is an example of a vehicle that uses an Atkinson
engine. The 2017 Toyota Prius achieved a peak thermal efficiency of 40
percent.\218\
---------------------------------------------------------------------------

    \217\ Toyota. ``Under the Hood of the All-new Toyota Prius.''
Oct. 13, 2015. Available at https://global.toyota/en/detail/9827044.
(Accessed: February 17, 2022)
    \218\ Matsuo, S., Ikeda, E., Ito, Y., and Nishiura, H., ``The
New Toyota Inline 4 Cylinder 1.8L ESTEC 2ZR-FXE Gasoline Engine for
Hybrid Car,'' SAE Technical Paper 2016-01-0684, 2016, https://doi.org/10.4271/2016-01-0684.
---------------------------------------------------------------------------

    VTG: The Miller cycle is another type of overexpansion combustion
cycle, similar to the Atkinson cycle. The Miller cycle, however,
operates in combination with a forced induction system that helps
address the impacts of reduced power density during high load operating
conditions. Miller cycle-enabled engines use a similar technology
approach as seen in Atkinson-enabled engines to effectively create an
expanded expansion stroke of the combustion cycle.
    In the analysis, the baseline Miller cycle-enabled engine includes
the application of a variable turbo geometry technology (VTG). The
advanced Miller cycle enabled system includes the application of a 48V-
based electronic boost system (VTGE). VTG technology allows the system
to vary boost level based on engine operational needs. The use of a
variable geometry turbocharger also supports the use of cooled exhaust
gas recirculation.\219\ An electronic boost system has an electric
motor added to assist a turbocharger at low engine speeds. The motor
assist mitigates turbocharger lag and low boost pressure at low engine
speeds. The electronic assist system can provide extra boost needed to
overcome the torque deficits at low engine speeds.\220\
---------------------------------------------------------------------------

    \219\ 2015 NAS Report, at p. 116.
    \220\ 2015 NAS Report, at p. 62.
---------------------------------------------------------------------------

    ICCT provided comments regarding Miller Cycle technology as part of
its comments about technologies that may not have been incorporated in
NHTSA's proposal, stating that, ``VW is already using Miller Cycle
engines as the base engine in the Passat, Arteon, Atlas, and Tiguan and
a hybrid-specific version of this engine with cEGR and VGT is under
development by VW that demonstrates a peak BTE of 41.5 percent. The
fact that Miller cycle is already included on the standard engine for
many of VW's most popular vehicles supports that Miller cycle is a
cost-effective addition to turbocharged engines. Yet there are no
Miller cycle applications in 2026 beyond the specific Mazda and Volvo
models that already had Miller cycle in 2017.'' \221\
---------------------------------------------------------------------------

    \221\ ICCT, at p. 4.

---------------------------------------------------------------------------

    NHTSA's NPRM used a MY 2020 fleet that appropriately characterized
Volkswagen, Volvo, and Mazda engines with VTG and VTGe technology.\222\
We believe our use of the MY 2020 baseline fleet addresses some of the
concerns expressed by ICCT. As far as additional application of the
technology in the MY 2026 fleet results, we did not place any adoption
restrictions on the use of VTG and VTGe technology and it can be
applied to any basic and turbocharged engine. This means that while VTG
and VTGe may be a cost-effective technology for some manufacturers in
the real world--particularly for Volkswagen, a manufacturer that
already has the technology refined for use on its vehicles--the CAFE
Model did not consider it to be a cost-effective pathway to compliance
for manufacturers in the analysis, that did not already use the
technology in MY 2020. NHTSA does not have any alternative relative
effectiveness \223\ data or cost estimates to consider that would
affect the CAFE Model's compliance pathway. Therefore, we have made no
changes to this engine technology's inputs in the final rule analysis
from what was used in the NPRM. We will continue to follow any updates
on the effectiveness and cost of VTG and VTGe technology for future
actions.
---------------------------------------------------------------------------

    \222\ See Section III.C.2, The Market Data File.
    \223\ As a reminder, our analysis considers the relative
technology effectiveness improvement from a previously applied
technology. Therefore, while VW may be developing a hybrid version
of its Miller engine technology with a peak BTE of 41.5 percent, the
relevant data point for our analysis would be the relative
effectiveness improvement from the previous version of the
technology.
---------------------------------------------------------------------------

    VCR: Variable compression ratio (VCR) engines work by changing the
length of the piston stroke of the engine to optimize the compression
ratio and improve thermal efficiency over the full range of engine
operating conditions. Engines using VCR technology are currently in
production, but appear to be targeted primarily towards limited
production, high performance applications. Nissan is the only
manufacturer to use this technology in the MY 2020 baseline fleet. Few
manufacturers and suppliers provided information about VCR
technologies, and we reviewed several design concepts that could
achieve a similar functional outcome. In addition to design concept
differences, intellectual property ownership complicates the ability to
define a VCR hardware system that could be widely adopted across the
industry. Because of these issues, adoption of the VCR engine
technology is limited to specific OEMs only.
    ADSL: Diesel engines have several characteristics that result in
superior fuel efficiency over traditional gasoline engines. These
advantages include reduced pumping losses due to lack of (or greatly
reduced) throttling, high pressure direct injection of fuel, a more
efficient combustion cycle,\224\ and a very lean air/fuel mixture
relative to an equivalent-performance gasoline engine.\225\ However,
diesel technologies require additional enablers, such as a
NOX adsorption catalyst system or a urea/ammonia selective
catalytic reduction system, for control of NOX emissions.
---------------------------------------------------------------------------

    \224\ Diesel cycle is also a four-stroke cycle like the Otto
Cycle, except in the intake stroke no fuel is injected and fuel is
injected late in the compression stroke at higher pressure and
temperature.
    \225\ See the 2015 NAS Report, Appendix D, for a short
discussion on thermodynamic engine cycles.
---------------------------------------------------------------------------

    DOT considered three levels of diesel engine technology: The
baseline diesel engine technology (ADSL) is based on a standard 2.2L
turbocharged diesel engine; the more advanced diesel engine (DSLI)
starts with the ADSL system and incorporates a combination of low
pressure and high pressure EGR, reduced parasitic loss, friction
reduction, a highly integrated exhaust catalyst with low temp light off
temperatures, and closed loop combustion control; and finally the most
advanced diesel system (DSLIAD) is the DSLI system with advanced
cylinder deactivation technology added.
    EFR: Engine friction reduction technology is a general engine
improvement meant to represent future technologies that reduce the
internal friction of an engine. EFR technology is not available for
application until MY 2023. The future technologies do not significantly
change the function or operation of the engine but reduce the energy
loss due to the rotational or rubbing friction experienced in the
bearings or cylinder during normal operation. These technologies can
include improved surface coatings, lower-tension piston rings, roller
cam followers, optimal thermal management and piston surface
treatments, improved bearing design, reduced inertial loads, improved
materials, or improved geometry.
(b) Engine Analysis Fleet Assignments
    As a first step in assigning baseline levels of engine technologies
in the analysis fleet, DOT uses data for each manufacturer to determine
which platforms share engines. Within each manufacturer's fleet, DOT
assigns unique identification designations (engine codes) based on
configuration, technologies applied, displacement, compression ratio,
and power output. DOT uses power output to distinguish between engines
that might have the same displacement and configuration but
significantly different horsepower ratings.
    The CAFE Model identifies leaders and followers for a
manufacturer's vehicles that use the same engine, indicated by sharing
the same engine code. The model automatically determines which engines
are leaders by using the highest sales volume row of the highest sales
volume nameplate that is assigned an engine code. This leader-follower
relationship allows the CAFE Model simulation to maintain engine
sharing as more technology is applied to engines.
    DOT accurately represents each engine using engine technologies and
engine technology classes. The first step is to assign engine
technologies to each engine code. Technology assignment is based on the
identified characteristics of the engine being modeled, and based on
technologies assigned, the engine will be aligned with a technology key
that most closely corresponds.
    The engine technology classes are a second identifier used to
accurately account for engine costs. The engine technology class is
formatted as number of cylinders followed by the letter C, number of
banks followed by the letter B, and an engine head configuration
designator, which is _SOHC for single overhead cam, _ohv for overhead
valve, or blank for dual overhead cam. As an example, one variant of
the GMC Acadia has a naturally aspirated DOHC inline 4-cylinder engine,
so DOT assigned the vehicle to the `4C1B' engine technology class and
assigned the technology VVT and SGDI. Table III-7 shows examples of
observed engines with their corresponding assigned engine technologies
as well as engine technology classes.

[GRAPHIC] [TIFF OMITTED] TR02MY22.065

    The cost tables for a given engine class include downsizing (to an
engine architecture with fewer cylinders) when turbocharging technology
is applied, and therefore, the turbocharged engines observed in the
2020 fleet (that have already been downsized) often map to an engine
class with more cylinders. For instance, an observed TURBO1 V6 engine
would map to an 8C2B (V8) engine class, because the turbo costs on the
8C2B engine class worksheet assume a V6 (6C2B) engine architecture.
Diesel engines map to engine technology classes that match the observed
cylinder count since naturally aspirated diesel engines are not found
in new light duty vehicles in the U.S. market. Similarly, as indicated
above, the TURBO1 I3 in the Ford Escape maps to the 4C1B_L (I4) engine
class, because the turbo costs on the 4C1B_L engine class worksheet
assume a I3 (3C1B) engine architecture. Some instances can be more
complex, including low horsepower variants for 4 cylinder engines, and
are shown in Table III-8.
    For this analysis, we allow additional downsizing beyond what has
been previously modeled in prior rulemaking analyses. We allow enhanced
downsizing because manufacturers have downsized low output naturally
aspirated engines to turbo engines with smaller architectures than
traditionally observed.226 227 228 To capture this new level
of turbo downsizing we created a new category of low output naturally
aspirated engines, which is only applied to 4-cylinder engines in the
MY 2020 fleet. These engines use the costing tabs in the Technologies
file with the `L' designation and are assumed to downsize to
turbocharged 3-cylinder engines for costing purposes. We sought comment
regarding the expected further application of this technology to larger
cylinder count engines, such as 8-cylinder engines that may be turbo
downsized to 4-cylinder engines. We also sought comment on how to
define the characteristic of an engine that may be targeted for
enhanced downsizing. We received no additional comments regarding
enhanced downsizing.
---------------------------------------------------------------------------

    \226\ Richard Truett, ``GM Bringing 3-Cylinder back to North
America.'' Automotive News, December 01, 2019. https://www.autonews.com/cars-concepts/gm-bringing-3-cylinder-back-na.
(Accessed: February 17, 2022)
    \227\ Stoklosa, Alexander, ``2021 Mini Cooper Hardtop.'' Car and
Driver, December 2, 2014. https://www.caranddriver.com/reviews/a15109143/2014-mini-cooper-hardtop-manual-test-review/. (Accessed:
February 17, 2022)
    \228\ Leanse, Alex, ``2020 For Escape Options: Hybrid vs. 3-
Cylinder EcoBoost vs. 4-Cylinder EcoBoost.'' MotorTrend, Sept 24,
2019. https://www.motortrend.com/news/2020-ford-escape-engine-options-pros-and-cons-comparison/. (Accessed: February 17, 2022)

---------------------------------------------------------------------------

[GRAPHIC] [TIFF OMITTED] TR02MY22.066

    TSD Chapter 3.1.2 includes more details about baseline engine
technology assignment logic, and details about the levels of engine
technology penetration in the MY 2020 fleet.
(c) Engine Adoption Features
    We defined engine adoption features through a combination of (1)
refresh and redesign cycles, (2) technology path logic, (3) phase-in
capacity limits, and (4) SKIP logic. Figure III-7 above shows the
technology paths available for engines in the CAFE Model. Engine
technology development and application typically results in an engine
design moving from the basic engine tree to one of the advanced engine
trees. Once an engine design moves to the advanced engine tree it is
not allowed to move to alternate advanced engine trees. Specific path
logic, phase-in caps, and SKIP logic applied to each engine technology
are discussed by engine technology, in turn.
    Refresh and redesign cycles dictate when we apply engine
technology. Technologies applicable only during a platform redesign can
be applied during a platform refresh if another vehicle platform that
shares engine codes (uses the same engine) has already applied the
technology during a redesign. For example, models of the GMC Acadia and
the Cadillac XT4 use the same engine (assigned engine code 112011 in
the Market Data file); if the XT4 adds a new engine technology during a
redesign, then the Acadia may also add the same engine technology
during the next refresh or redesign. This allows the model to maintain
engine sharing relationships while also maintaining refresh and
redesign schedules.\229\ For engine technologies, DOHC, OHV, VVT, and
CNG engine technologies are baseline only, while all other engine
technologies can only be applied at a vehicle redesign.
---------------------------------------------------------------------------

    \229\ See Section III.C.2.a) for more discussion on platform
refresh and redesign cycles.
---------------------------------------------------------------------------

    Basic engine technologies in the CAFE Model are represented by four
technologies: VVT, VVL, SGDI, and DEAC. DOT assumes that 100 percent of
basic engine platforms use VVT as a baseline, based on wide
proliferation of the technology in the U.S. fleet. The remaining three
technologies, VVL, SGDI, and DEAC, can all be applied individually or
in any combination of the three. An engine can jump from the basic
engines path to any other engine path except the Alternative Fuel
Engine Path.
    Turbo downsizing allows manufacturers to maintain vehicle
performance characteristics while reducing engine displacement and
cylinder count. Any basic engine can adopt one of the turbo engine
technologies (TURBO1, TURBO2, and CEGR1). Vehicles that have
turbocharged engines in the baseline fleet will stay on the turbo
engine path to prevent unrealistic engine technology change in the
short timeframe considered in the rulemaking analysis. Turbo technology
is a mutually exclusive technology in that it cannot be adopted for
HCR, diesel, ADEAC, or CNG engines.
    Non-HEV Atkinson enabled engines are a collection of engines in the
HCR engine pathway (HCR0, HCR1, HCR1D, and HCR2). Atkinson enabled
engines excel in lower power applications for lower load conditions,
such as driving around a city or steady state highway driving without
large payloads. As a result, their adoption is more limited than some
other technologies. We expanded the availability of HCR technology
compared to the 2020 final rule because of new observed applications in
the market.\230\ However, there are three categories of adoption
features specific to the HCR engine pathway: \231\
---------------------------------------------------------------------------

    \230\ For example, the Hyundai Palisade and Kia Telluride have a
291 hp V6 HCR1 engine. The specification sheets for these vehicles
are located in the docket for this action.
    \231\ See Section III.D.1.d)(1) (Engine Maps), for a discussion
of why HCR2 and P2HCR2 were not used in the central analysis.
``SKIP'' logic was used to remove this engine technology from
application, however as discussed below, we maintain HCR2 and P2HCR2
in the model architecture for sensitivity analysis and for future
engine map model updates.
---------------------------------------------------------------------------

     We currently do not allow vehicles with 405 or more
horsepower to adopt HCR engines due to their prescribed duty cycle
being more demanding and likely not supported by the lower power
density found in HCR-based engines.\232\
---------------------------------------------------------------------------

    \232\ Heywood, John B. Internal Combustion Engine Fundamentals.
McGraw-Hill Education, 2018. Chapter 5.
---------------------------------------------------------------------------

     Pickup trucks and vehicles that share engines with pickup
trucks are currently excluded from receiving HCR engines; the duty
cycle for these heavy vehicles, particularly the need for large torque
reserves, results in an engine calibration that minimizes the advantage
of Atkinson cycle use.\233\
---------------------------------------------------------------------------

    \233\ This is based on CBI conversation with manufacturers that
currently employ HCR-based technology but saw no benefit when the
technology was applied to truck platforms in their fleet.
---------------------------------------------------------------------------

     HCR engine application is also currently restricted for
some manufacturers that are heavily

performance-focused and have demonstrated a significant commitment to
power dense technologies such as turbocharged downsizing.\234\
---------------------------------------------------------------------------

    \234\ There are three manufacturers that met the criteria (near
100 percent turbo downsized fleet, and future hybrid systems are
based on turbo-downsized engines) described and were excluded: BMW,
Daimler, and Jaguar Land Rover.
---------------------------------------------------------------------------

    Advanced cylinder deactivation technology (ADEAC), or dynamic
cylinder deactivation (e.g., Dynamic Skip Fire), can be applied to any
engine with basic technology. This technology represents a naturally
aspirated engine with ADEAC. Additional technology can be applied to
these engines by moving to the Advanced Turbo Engine Path.
    Miller cycle (VTG and VTGe) engines can be applied to any basic and
turbocharged engine. VTGe technology is enabled by the use of a 48V
system that presents an improvement from traditional turbocharged
engines, and accordingly VTGe includes the application of a mild hybrid
(BISG) system.
    VCR engines can be applied to basic and turbocharged engines, but
the technology is limited to specific OEMs.\235\ VCR technology
requires a complete redesign of the engine, and in the analysis fleet,
only two platforms had incorporated this technology. The agency does
not believe any other manufacturers will invest to develop and market
this technology in their fleet in the rulemaking time frame.
---------------------------------------------------------------------------

    \235\ Nissan and Mitsubishi are strategic partners and members
of the Renault-Nissan-Mitsubishi Alliance.
---------------------------------------------------------------------------

    Advanced turbo engines are becoming more prevalent as the
technologies mature. TURBOD combines TURBO1 and DEAC technologies and
represents the first advanced turbo. TURBOAD combines TURBO1 and ADEAC
technologies and is the second and last level of advanced turbos.
Engines from either the Turbo Engine Path or the ADEAC Engine Path can
adopt these technologies.
    Any basic engine technologies (VVT, VVL, SGDI, and DEAC) can adopt
ADSL and DSLI engine technologies. Any basic engine and diesel engine
can adopt DSLIAD technology in this analysis; however, we applied a
phase in cap and year for this technology at 34 percent and MY 2023,
respectively. In our engineering judgement, this is a rather complex
and costly technology to adopt and it would take significant investment
for a manufacturer to develop. For more than a decade, diesel engine
technologies have been used in less than one percent of the total
light-duty fleet production and have been found mostly on medium and
heavy-duty vehicles.
    Finally, we allow the CAFE Model to apply EFR to any engine
technology except for DSLI and DSLIAD. DSLI and DSLIAD inherently have
incorporated engine friction technologies from ADSL. In addition,
friction reduction technologies that apply to gasoline engines cannot
necessarily be applied to diesel engines due to the higher temperature
and pressure operation in diesel engines.
    We sought comment on the appropriateness of engine adoption
features, specifically for the HCR engines, and received feedback. Some
commenters felt the constraints on application of HCR technology in the
CAFE Model were too strict. Specifically, comments on this issue were
received from ICCT, California Air Resources Board (CARB), a coalition
of States and Cities, and a joint group of non-governmental
organizations.236 237 238 239 240 ICCT described NHTSA's
characterization of HCR with respect to the duty cycle requirements of
high horsepower or high towing vehicles as ``backwards and wrong,''
stating that:
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    \236\ ICCT, at p. 11.
    \237\ CARB, Docket No. NHTSA-2021-0053-1521-A2, at pp. 6-8.
    \238\ States of California, Colorado, Connecticut, Delaware,
Hawaii, Illinois, Maine, Maryland, Michigan, Minnesota, Nevada, New
Jersey, New Mexico, New York, North Carolina, Oregon, Rhode Island,
Vermont, Washington, and Wisconsin; the Commonwealths of
Massachusetts and Pennsylvania; the District of Columbia; the Cities
and Counties of Denver and San Francisco; and the Cities of Los
Angeles, New York, Oakland, and San Jose (NHTSA-2021-0053-1499)
(California Attorney General et al.), Docket No. NHTSA-2021-0053-
1499-A1, at p. 33.
    \239\ Natural Resources Defense Council (NRDC), Docket No.
NHTSA-2021-0053-1572-A1, at p. 7.
    \240\ NRDC, A2, at pp. 46-47.

engines in pickup trucks and high-performance vehicles are sized and
powered to handle higher peak loads and, thus, operate at lower
loads relative to their maximum capacity. According to supplemental
tables for the 2020 EPA FE Trends report found online, pickups have
18 [percent] to 19 [percent] higher power to weight than both cars
and truck SUVs, which means that pickup trucks and high-performance
vehicles will spend more time in Atkinson Cycle operation than lower
performance vehicles on both the test cycles and in the real world,
not less. Any need for ``additional torque reserve'' is met by
switching to Otto cycle. The one exception is towing, which does
impose constant high loads on the engine. However, Strategic Vision
data finds that ``percent of [pickup] truck owners use their truck
for towing one time a year or less''. The large majority of pickup
trucks spend the vast majority of driving at low loads relative to
the engine's capability, where Atkinson Cycle engines are very
effective. Thus, all restrictions on HCR engines should be
removed.\241\
---------------------------------------------------------------------------

    \241\ ICCT, at p. 11.

    We disagree with ICCT's and other comments regarding the
appropriateness of the HCR technology constraints. Current HCR engines
achieve the effects of a longer expansion stroke, necessary for
Atkinson operation, using continuous variable valve timing. The timing
of the intake valve closure is based on the current load demand on the
engine. Under higher loads, the intake values will close sooner in the
cycle, increasing the dynamic compression ratio and decreasing the
over-stroke of the expansion cycle, decreasing thermal efficiency, and
increasing torque. This causes the engine to operate closer to an Otto
combustion cycle than an Atkinson cycle. However, under these
conditions, the engine is not able to completely achieve a traditional
Otto cycle due to knock limitations and maintains a minimum of over-
expansion behavior. While under lower loads the engine decreases the
dynamic compression ratio, closing the intake valve later, and
increasing the over-stroke of the expansion stroke reducing torque
while increasing efficiency. Having the ability to continuously adjust
the shape of the combustion cycle significantly improves the engine
efficiency but does not give the engine the functional flexibility
suggested by ICCT's interpretation of the technology description.
    This is exemplified by Toyota's comment to the 2018 CAFE NPRM on
the application of the HCR-based engine to the Tacoma platform, where
Toyota stated that:

    Tacoma has a greater coefficient of drag from a larger frontal
area, greater tire rolling resistance from larger tires with a more
aggressive tread, and higher driveline losses from 4WD. Similarly,
the towing, payload, and off-road capability of pick-up trucks
necessitate greater emphasis on engine torque and horsepower over
fuel economy. This translates into engine specifications such as a
larger displacement and a higher stroke-to-bore ratio. Tacoma's
higher road load and more severe utility requirements push engine
operation more frequently to the less efficient regions of the
engine map and limit the level of Atkinson operation.\242\
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    \242\ Toyota, Docket No. NHTSA-2018-0067-12376-A1, at pp. 8-9.

    In addition to operating issues, comments such as those provided by
the Auto Innovators, also to the 2018 NPRM (83 FR 42986, Aug. 24,
2018), highlight packaging issues that make the application of HCR in
high horsepower/high torque applications less practical. Specifically,
the Alliance of Automobile

Manufacturer's \243\ comments to the 2018 NPRM stated that ``[t]he
Alliance agrees with the more restrained application of HCR1 in the
Proposed Rule,'' and agreed with the agencies' rationale for the
restrictions that included ``[p]ackaging and emission constraints
associated with intricate exhaust manifolds needed to mitigate high
load/low revolutions per minute knock'' and ``Inherent performance
limitations of Atkinson cycle engines.'' \244\ Ford echoed this
concern, stating that ``Ford supports the more restrained application
of HCR1 in the Proposed Rule, an approach that recognizes the
investment, packaging, performance and emissions factors that will
limit penetration of this technology.'' \245\
---------------------------------------------------------------------------

    \243\ Now Alliance for Automotive Innovation, also referred to
as Auto Innovators.
    \244\ Auto Innovators, Docket No. NHTSA-2018-0067-12073-A1, at
p. 139.
    \245\ Ford, Docket No. NHTSA-2018-0067-11928-A1, at p. 8.
---------------------------------------------------------------------------

    Based on this discussion, and previously provided data, we have
kept the HCR adoptions features used in the NPRM for the final rule,
except for a correction to the HCR1D application. Keeping the
constraints in place also aligns us with the most recent EPA rulemaking
analysis.\246\ We do intend to continue research into the
appropriateness of HCR technology applications in future analysis, as
we look at timeframes beyond the current rulemaking.
---------------------------------------------------------------------------

    \246\ See U.S. EPA, ``Revised 2023 and Later Model Year Light-
Duty Vehicle GHG Emissions Standards: Regulatory Impact Analysis.''
December 2021. EPA-420-R-21-028. https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1013ORN.pdf. (Accessed: March 9, 2022)
---------------------------------------------------------------------------

    Regarding the application of the HCR1D technology, a joint group of
NGO comments, and others, pointed out an error in the CAFE Model input
files used in the NPRM. The HCR1D technology was not set to `true' for
the central analysis.\247\ We agree the setting was left blank in error
and is correctly assigned a `true' value in the technology input file
for the final rule analysis.
---------------------------------------------------------------------------

    \247\ NRDC, at pp. 46-47.
---------------------------------------------------------------------------

(d) Engine Effectiveness Modeling
    Engine effectiveness values used for engine technologies in two
ways. The values are either calculated based on the difference in full
vehicle simulation results created using the Autonomie modeling tool,
or determined by the effectiveness values using an alternate
calculation method, including analogous improvement or fuel economy
improvement factors.
(1) Engine Maps
    Effectiveness values used as inputs for the CAFE Model are
determined by comparing results of full vehicle simulations using the
Autonomie simulation tool. For a full discussion about how Autonomie
was used, see Section III.C.4 and TSD Chapter 2.4, in addition to the
Autonomie model documentation. Engine map models are the primary inputs
used to simulate the effects of different engine technologies in the
Autonomie full vehicle simulations.
    Engine maps provide a three-dimensional representation of engine
performance characteristics at each engine speed and load point across
the operating range of the engine. Engine maps have the appearance of
topographical maps, typically with engine speed on the horizontal axis
and engine torque, power, or brake mean effective pressure (BMEP) \248\
on the vertical axis. A third engine characteristic, such as brake-
specific fuel consumption (BSFC),\249\ is displayed using contours
overlaid across the speed and load map. The contours provide the values
for the third characteristic in the regions of operation covered on the
map. Other characteristics typically overlaid on an engine map include
engine emissions, engine efficiency, and engine power. The engine maps
developed to model the behavior of the engines used in this analysis
are referred to as engine map models.
---------------------------------------------------------------------------

    \248\ Brake mean effective pressure is an engineering measure,
independent of engine displacement, which indicates the actual work
an engine performs.
    \249\ Brake-specific fuel consumption is the rate of fuel
consumption divided by the power being produced.
---------------------------------------------------------------------------

    The engine map models used in this analysis are representative of
technologies that are currently in production or are expected to be
available in the rulemaking timeframe. The engine map models are
developed to be representative of the performance achievable across
industry for a given technology and are not intended to represent the
performance of a single manufacturer's specific engine. The broadly
representative performance level was targeted because the same
combination of technologies produced by different manufacturers will
have differences in performance, due to manufacturer-specific designs
for engine hardware, control software, and emissions calibration.
    Accordingly, we expect that the engine maps developed for this
analysis will differ from engine maps for manufacturers' specific
engines. However, we intend and expect that the incremental changes in
performance modeled for this analysis, due to changes in technologies
or technology combinations, will be similar to the incremental changes
in performance observed in manufacturers' engines for the same changes
in technologies or technology combinations.
    The analysis never applies absolute BSFC levels from the engine
maps to any vehicle model or configuration for the rulemaking analysis.
The absolute fuel economy values from the full vehicle Autonomie
simulations are used only to determine incremental effectiveness for
switching from one technology to another technology. The incremental
effectiveness is applied to the absolute fuel economy of vehicles in
the analysis fleet, which are based on CAFE compliance data. For
subsequent technology changes, incremental effectiveness is applied to
the absolute fuel economy level of the previous technology
configuration. Therefore, for a technically sound analysis, it is most
important that the differences in BSFC among the engine maps be
accurate, and not the absolute values of the individual engine maps.
    For this analysis, we use a small number of baseline engine
configurations with well-defined BSFC maps, and then, in a very
systematic and controlled process, add specific well-defined
technologies to create a BSFC map for each unique technology
combination. This can theoretically be done using engine or vehicle
testing, but testing would need to be conducted on a single engine, and
each configuration would require physical parts and associated engine
calibrations to assess the impact of each technology configuration,
which is impractical for the rulemaking analysis because of the
extensive design, prototype part fabrication, development, and
laboratory resources that are required to evaluate each unique
configuration. Modeling is an approach used by industry to assess an
array of technologies with more limited testing. Modeling offers the
opportunity to isolate the effects of individual technologies by using
a single or small number of baseline engine configurations and
incrementally adding technologies to those baseline configurations.
This provides a consistent reference point for the BSFC maps for each
technology and for combinations of technologies that enables the
differences in effectiveness among technologies to be carefully
identified and quantified.

    The Autonomie model documentation provides a detailed discussion on
how the engine map models were used as inputs to the full vehicle
simulations performed using the Autonomie tool. The Autonomie model
documentation contains the engine map model topographic figures, and
additional engine map model data can be found in the Autonomie input
files.\250\
---------------------------------------------------------------------------

    \250\ See additional Autonomie supporting materials in docket
number NHTSA-2021-0053 for this rule.
---------------------------------------------------------------------------

    We received a comment from the High Octane Low Carbon Fuel Alliance
regarding the potential use of high octane fuels. The High Octane Low
Carbon Fuel Alliance stated, ``Higher octane enables greater engine
efficiency and improved vehicle performance through higher compression
ratios and/or more aggressive turbocharging and downsizing--also
facilitated by ethanol's cylinder ``charge cooling'' effect due to its
high heat of vaporization.\251\ Raising the engine's compression ratio
from 10:1 to 12:1 could increase vehicle efficiency by 5 to 7
percent.'' 252 253
---------------------------------------------------------------------------

    \251\ J.E. Anderson et al., ``High octane number ethanol-
gasoline blends: Quantifying the potential benefits in the United
States,'' Fuel (2012): 97: pp. 585-594: https://www.sciencedirect.com/science/article/pii/S0016236112002268.
(Accessed: February 17, 2022)
    \252\ David S. Hirshfeld et al., ``Refining Economics of U.S.
Gasoline: Octane Ratings and Ethanol Content,'' Environmental
Science & Technology (2014): 48(19): pp. 11064-11071: https://pubs.acs.org/doi/pdf/10.1021/es5021668. (Accessed: February 17,
2022)
    \253\ Thomas G. Leone et al., ``The Effect of Compression Ratio,
Fuel Octane Rating, and Ethanol Content on Spark- Ignition Engine
Efficiency,'' Environmental Science & Technology (2015): 49(18): pp.
10778-10789: https://pubs.acs.org/doi/abs/10.1021/acs.est.5b01420.
(Accessed: February 17, 2022)
---------------------------------------------------------------------------

    We agree with the data provided; however, we simulate the use of
Tier 3 fuel in our engine technology models to represent the fuel
available and most commonly used by consumers.\254\ If we assumed that
high octane fuel was used in the engine map models, we would be
assuming a greater fuel economy benefit than would actually be achieved
in the real world, which would overestimate the benefits of more
stringent standards. Moreover, to date, vehicle manufacturers do not
appear to be pursuing this technology path. As we have stated
previously, regulation of fuels is also outside of the scope of NHTSA's