rulemaking. The passenger car and light truck CAFE standards for MYs
2022-2025 will be determined with finality in a subsequent, de novo
notice and comment rulemaking conducted in full compliance with EPCA/
EISA and other applicable law--beyond simply reviewing the analysis and
findings in the present rulemaking to see whether they are still
accurate and applicable, and taking a fresh look at all relevant
factors based on the best and most current information available at
that future time.
---------------------------------------------------------------------------

    \610\ 49 U.S.C. 32902(b)(3)(B).
---------------------------------------------------------------------------

    To facilitate that future effort, NHTSA and EPA will conduct a
comprehensive mid-term evaluation. Up to date information will be
developed and compiled for the evaluation, through a collaborative,
robust, and transparent process, including notice and comment. The
agencies fully expect to conduct the mid-term evaluation in close
coordination with the California Air Resources Board (CARB), consistent
with the agencies' commitment to maintaining a single national
framework for regulation of fuel economy and GHG emissions.\611\ Prior
to beginning NHTSA's rulemaking process and EPA's mid-term evaluation,
the agencies will jointly prepare a draft Technical Assessment Report
(TAR) to examine afresh the issues and, in doing so, conduct similar
analyses and projections as those considered in the current rulemaking,
including technical and other analyses and projections relevant to each
agency's authority to set standards as well as any relevant new issues
that may present themselves. The agencies will provide an opportunity
for public comment on the draft TAR, and appropriate peer review will
be performed of underlying analyses in the TAR. The assumptions and
modeling underlying the TAR will be available to the public, to the
extent consistent with law. The draft TAR is expected to be issued no
later than November 15, 2017. After the draft TAR and public comment,
the agencies will consult and coordinate as NHTSA develops its NPRM.
NHTSA will ensure that the subsequent final rule will be timed to
provide sufficient lead time for industry to make whatever changes to
their products that the rulemaking analysis deems maximum feasible
based on the new information available. At the very latest, NHTSA will
complete its subsequent rulemaking on the standards with at least 18
months lead time as required by EPCA,\612\ but additional lead time may
be provided.
---------------------------------------------------------------------------

    \611\ The agencies also fully expect that any adjustments to the
standards as a result of the mid-term evaluation process from the
levels enumerated in the current rulemaking will be made with the
participation of CARB and in a manner that continues the
harmonization of state and Federal vehicle standards.
    \612\ 49 U.S.C. 32902(a).
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B. Background

1. Chronology of Events Since the MY 2012-2016 Final Rule Was Issued
    Section I above covers the chronology of events in considerable
detail, and we refer the reader there.
2. How has NHTSA developed the proposed CAFE standards since the
President's announcement?
    The CAFE standards proposed in this NPRM are based on much more
analysis conducted by the agencies since July 29, including in-depth
modeling analysis by DOT/NHTSA to support the proposed CAFE standards,
and further refinement of a number of our baseline, technology, and
economic assumptions used to evaluate the proposed standards and their
impacts. This NPRM, the draft joint TSD, and NHTSA's PRIA and EPA's
DRIA contain much more information about the analysis underlying these
proposed standards. The following sections provide the basis for
NHTSA's proposed passenger car and light truck CAFE standards for MYs
2017-2025, the standards themselves, the estimated impacts of the
proposed standards, and much more information about the CAFE program
relevant to the 2017-2025 timeframe.

C. Development and Feasibility of the Proposed Standards

1. How was the baseline vehicle fleet developed?
a. Why do the agencies establish a baseline and reference vehicle
fleet?
    As also discussed in Section II.B above, in order to determine what
levels of stringency are feasible in future model years, the agencies
must project what vehicles will exist in those model years, and then
evaluate what technologies can feasibly be applied to those vehicles in
order to raise their fuel economy and lower their CO2
emissions. The agencies therefore established a ``baseline'' vehicle
fleet representing those vehicles, based on the best available
transparent information. The agencies then developed a ``reference''
fleet, projecting the baseline fleet sales into MYs 2017-2025 and
accounting for the effect that the MY 2012-2016 CAFE standards have on
the baseline fleet.\613\ This

reference fleet is then used for comparisons of technologies'
incremental cost and effectiveness, as well as for other relevant
comparisons in the rule.
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    \613\ In order to calculate the impacts of the proposed future
GHG and CAFE standards, it is necessary to estimate the composition
of the future vehicle fleet absent those proposed standards in order
to conduct comparisons. The first step in this process was to
develop a fleet based on model year 2008 data. This 2008-based fleet
includes vehicle sales volumes, GHG/fuel economy performance, and
contains a listing of the base technologies on every 2008 vehicle
sold. The second step was to project that 2008-based fleet volume
into MYs 2017-2025. This is called the reference fleet, and it
represents the fleet volumes (but, until later steps, not levels of
technology) that the NHTSA and EPA expect would exist in MYs 2017-
2025 absent any change due to regulation in 2017-2025.
    After determining the reference fleet, a third step is needed to
account for technologies (and corresponding increases in cost and
reductions in fuel consumption and CO2 emissions) that
could be added to MY 2008-technology vehicles in the future, taking
into previously-promulgated standards, and assuming MY 2016
standards are extended through MY2025. NHTSA accomplished this by
using the CAFE model to add technologies to that MY 2008-based
market forecast such that each manufacturer's car and truck CAFE and
average CO2 levels reflect baseline standards. The
model's output, the reference case (or adjusted baseline, or no-
action alternative), is the light-duty fleet estimated to exist in
MYs 2017-2025 without new GHG/CAFE standards covering MYs 2017-2025.
---------------------------------------------------------------------------

b. What data did the agencies use to construct the baseline, and how
did they do so?
    As explained in the draft joint TSD, both agencies used a baseline
vehicle fleet constructed beginning with EPA fuel economy certification
data for the 2008 model year, the most recent model year for which
final data is currently available from manufacturers. These data were
used as the source for MY 2008 production volumes and some vehicle
engineering characteristics, such as fuel economy compliance ratings,
engine sizes, numbers of cylinders, and transmission types.
    For this NPRM, NHTSA and EPA chose again to use MY 2008 vehicle
data as the basis of the baseline fleet. MY 2008 is now the most recent
model year for which the industry had what the agencies would consider
to be ``normal'' sales. Complete MY 2009 data is now available for the
industry, but the agencies believe that the model year was disrupted by
the economic downturn and the bankruptcies of both General Motors and
Chrysler. CAFE compliance data shows that there was a significant
reduction in the number of vehicles sold by both companies and by the
industry as a whole. These abnormalities led the agencies to conclude
that MY 2009 data was likely not representative for projecting the
future fleet for purposes of this analysis. While MY 2010 data is
likely more representative for projecting the future fleet, it was not
complete and available in time for it to be used for the NPRM analysis.
Therefore, for purposes of the NPRM analysis, NHTSA and EPA chose to
use MY 2008 CAFE compliance data for the baseline since it was the
latest, most representative transparent data set that we had available.
However, the agencies plan to use the MY 2010 data, if available, to
develop an updated market forecast for use in the final rule. If and
when the MY 2010 data becomes available, NHTSA will place a copy of
this data into its rulemaking docket.
    Some information important for analyzing new CAFE standards is not
contained in the EPA fuel economy certification data. EPA staff
estimated vehicle wheelbase and track widths using data from
Motortrend.com and Edmunds.com. This information is necessary for
estimating vehicle footprint, which is required for the analysis of
footprint-based standards.
    Considerable additional information regarding vehicle engineering
characteristics is also important for estimating the potential to add
new technologies in response to new CAFE standards. In general, such
information helps to avoid ``adding'' technologies to vehicles that
already have the same or a more advanced technology. Examples include
valvetrain configuration (e.g., OHV, SOHC, DOHC), presence of cylinder
deactivation, and fuel delivery (e.g., MPFI, SIDI). To the extent that
such engineering characteristics were not available in certification
data, EPA staff relied on data published by Ward's Automotive,
supplementing this with information from Internet sites such as
Motortrend.com and Edmunds.com. NHTSA staff also added some more
detailed engineering characteristics (e.g., type of variable valve
timing) using data available from ALLDATA[reg] Online. Combined with
the certification data, all of this information yielded the MY 2008
baseline vehicle fleet. NHTSA also reviewed information from
manufacturers' confidential product plans submitted to the agency, but
did not rely on that information for developing the baseline or
reference fleets.
    After the baseline was created the next step was to project the
sales volumes for 2017-2025 model years. EPA used projected car and
truck volumes for this period from Energy Information Administration's
(EIA's) 2011 Interim Annual Energy Outlook (AEO).\614\ However, AEO
projects sales only at the car and truck level, not at the manufacturer
and model-specific level, which are needed in order to estimate the
effects new standards will have on individual manufacturers. Therefore,
EPA purchased data from CSM-Worldwide and used their projections of the
number of vehicles of each type predicted to be sold by manufacturers
in 2017-2025.\615\ This provided the year-by-year percentages of cars
and trucks sold by each manufacturer as well as the percentages of each
vehicle segment. Using these percentages normalized to the AEO
projected volumes then provided the manufacturer-specific market share
and model-specific sales for model years 2011-2016.
---------------------------------------------------------------------------

    \614\ Department of Energy, Energy Information Administration,
Annual Energy Outlook (AEO) 2011, Early Release. Available at http://www.eia.gov/forecasts/aeo/. Both agencies regard AEO a credible
source not only of such forecasts, but also of many underlying
forecasts, including forecasts of the size of the future light
vehicle market. The agencies used the early release version of AEO
2011 and confirmed later that changes reflected in the final version
were insignificant with respect to the relative volumes of passenger
cars and light trucks.
    \615\ The agencies explain in Chapter I of the draft Joint TSD
why data from CSM was chosen for creating the baseline for this
rulemaking.
---------------------------------------------------------------------------

    The processes for constructing the MY 2008 baseline vehicle fleet
and subsequently adjusting sales volumes to construct the MY 2017-2025
baseline vehicle fleet are presented in detail in Chapter 1 of the
Joint Technical Support Document accompanying today's proposed rule.
    The agencies assume that without adoption of the proposed rule,
that during the 2017-2025 period, manufacturers will not improve fuel
economy levels beyond the levels required in the MY 2016 standards.
However, it is possible that manufacturers may be driven by market
forces to raise the fuel economy of their fleets. The recently-adopted
fuel economy and environment labels (``window stickers''), for example,
may make consumers more aware of the benefits of higher fuel economy,
and may cause them to demand more fuel-efficient vehicles during that
timeframe. Moreover, the agencies' analysis indicates that some fuel-
saving technologies may save money for manufacturers. In Chapter X of
the PRIA, NHTSA examines the impact of an alternative ``market-driven''
baseline, which allows for some increases in fuel economy due to
``voluntary overcompliance'' beyond the MY 2016 levels. NHTSA seeks
comment on what assumptions about fuel economy increases are most
likely to accurately predict what would happen in the absence of the
proposed rule.
    NHTSA invites comment on the process used to develop the market
forecast, and on whether the agencies should consider alternative
approaches to producing a forecast at the level of detail we need for
modeling. If commenters wish to offer alternatives, we ask that they
address how manufacturers' future fleets would be

defined in terms of specific products, and the sales volumes and
technical characteristics (e.g., fuel economy, technology content,
vehicle weight, and other engineering characteristics) of those
products. The agency also invites comment regarding what sensitivity
analyses--if any--we should do related to the market forecast. For
example, should the agency evaluate the extent to which its analysis is
sensitive to projections of the size of the market, manufacturers'
respective market shares, the relative growth of different market
segments, and or the relative growth of the passenger car and light
truck markets? If so, how would commenters suggest that we do that?
c. How is the development of the baseline fleet for this rule different
from the baseline fleet that NHTSA used for the MY 2012-2016 (May 2010)
final rule?
    The development of the baseline fleet for this rulemaking utilizes
the same procedures used in the development of the baseline fleet for
the MY 2012-2016 rulemaking. Compared to that rulemaking, the change in
the baseline is much less dramatic--the MY 2012-2016 rulemaking was the
first rulemaking in which NHTSA did not use manufacturer product plan
data to develop the baseline fleet,\616\ so evaluating the difference
between the baseline fleet used in the MY 2011 final rule and in the MY
2012-2016 rulemaking was informative at that time regarding some of the
major impacts of that switch. In this proposal, we are using basically
the same MY 2008 based file as the starting point in the MY 2012-2016
analysis, and simply using an updated AEO forecast and an updated CSM
forecast. Of those, most differences are in input assumptions rather
than the basic approach and methodology. These include changes in
various macroeconomic assumptions underlying the AEO and CSM forecasts
and the use of results obtained by using DOE's National Energy Modeling
System (NEMS) to repeat the AEO 2011 analysis without forcing increased
passenger car volumes, and without assuming post-MY 2016 increases in
the stringency of CAFE standards.\617\
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    \616\ The agencies' reasons for not relying on product plan data
for the development of the baseline fleet were discussed in the
Regulatory Impact Analysis for the MYs 2012-2016 rulemaking and at
74 FR 49487-89. While a baseline developed using publicly and
commercially available sources has both advantages and disadvantages
relative to a baseline developed using manufacturers' product plans,
NHTSA currently concludes, as it did in the course of that prior
rulemaking, that the advantages outweigh the disadvantages.
Commenters generally supported the more transparent approach
employed in the MYs 2012-2016 rulemaking.
    \617\ Similar to the analyses supporting the MYs 2012-2016
rulemaking, the agencies have used the Energy Information
Administration's (EIA's) National Energy Modeling System (NEMS) to
estimate the future relative market shares of passenger cars and
light trucks. However, NEMS methodology includes shifting vehicle
sales volume, starting after 2007, away from fleets with lower fuel
economy (the light-truck fleet) towards vehicles with higher fuel
economies (the passenger car fleet) in order to facilitate
compliance with CAFE and GHG MYs 2012-2016 standards. Because we use
our market projection as a baseline relative to which we measure the
effects of new standards, and we attempt to estimate the industry's
ability to comply with new standards without changing product mix,
the Interim AEO 2011-projected shift in passenger car market share
as a result of required fuel economy improvements creates a
circularity. Therefore, for the current analysis, the agencies
developed a new projection of passenger car and light truck sales
shares by running scenarios from the Interim AEO 2011 reference case
that first deactivate the above-mentioned sales-volume shifting
methodology and then hold post-2017 CAFE standards constant at MY
2016 levels. Incorporating these changes reduced the projected
passenger car share of the light vehicle market by an average of
about 5 percent during 2017-2025. NHTSA and EPA refer to this as the
``Unforced Reference Case.''
---------------------------------------------------------------------------

    Another change in the baseline fleet from the last rulemaking
involved our redefinition of the list of manufacturers to account for
realignment and ownership changes taking place within the industry. The
reported results supporting this rulemaking recognize that Volvo
vehicles are no longer a part of Ford, but are reported as a separate
company, Geely; that Saab vehicles are no longer part of GM, but are
reported as part of Spyker which purchased Saab from GM in 2010; and
that Chrysler, along with Ferrari and Maserati, are reported as Fiat.
    In addition, low volume specialty manufacturers omitted from the
analysis supporting the MY 2012-2016 rulemaking have been included in
the analysis supporting this rulemaking. These include Aston Martin,
Lotus, and Tesla.
d. How is this baseline different quantitatively from the baseline that
NHTSA used for the MY 2012-2016 (May 2010) final rule?
    As discussed above, the current baseline was developed from
adjusted MY 2008 compliance data and covers MY 2017-2025. This section
describes, for the reader's comparison, some of the differences between
the current baseline and the MY 2012-2016 CAFE rule baseline. This
comparison provides a basis for understanding general characteristics
and measures of the difference between the two baselines. The current
baseline, while developed using the same methods as the baseline used
for MY 2012-2016 rulemaking, reflects updates to the underlying
commercially-available forecast of manufacturer and market segment
shares of the future passenger car and light truck market. Again, the
differences are in input assumptions rather than the basic approach and
methodology. It also includes changes in various macroeconomic
assumptions underlying the AEO forecasts and the use of the AEO
Unforced Reference Case. Another change in the market input data from
the last rulemaking involved our redefinition of the list of
manufacturers to account for realignment taking place within the
industry.
    Estimated vehicle sales:
    The sales forecasts, based on the Energy Information
Administration's (EIA's) Early Annual Energy Outlook for 2011 (Interim
AEO 2011), used in the current baseline indicate that the total number
of light vehicles expected to be sold during MYs 2012-2016 is 79
million, or about 15.8 million vehicles annually. NHTSA's MY 2012-2016
final rule forecast, based on AEO 2010, of the total number of light
vehicles likely to be sold during MY 2012 through MY 2016 was 80
million, or about 16 million vehicles annually. Light trucks are
expected to make up 37 percent of the MY 2016 baseline market forecast
in the current baseline, compared to 34 percent of the baseline market
forecast in the MY 2012-2016 final rule. These changes in both the
overall size of the light vehicle market and the relative market shares
of passenger cars and light trucks reflect changes in the economic
forecast underlying AEO, changes in AEO's forecast of future fuel
prices, and use of the Unforced Reference Case.
    Estimated manufacturer market shares:
    These changes are reflected below in Table IV-1, which shows the
agency's sales forecasts for passenger cars and light trucks under the
current baseline and the MY 2012-2016 final rule. There has been a
general decrease in MY 2016 forecast overall sales (from AEO) and for
all manufacturers (reflecting CSM's forecast of manufacturers' market
shares), with the exception of Chrysler, when the current baseline is
compared to that used in the MY 2012-2016 rulemaking. There were no
significant shifts in manufacturers' market shares between the two
baselines. The effect of including the low volume specialty
manufacturers and accounting for known corporate realignments in the
current baseline appear to be negligible. For individual manufacturers,
there have been shifts in the shares of passenger car and light trucks,
as would

be expected given that the agency is relying on different underlying
assumptions as discussed above and in Chapter 1 of the joint TSD.
---------------------------------------------------------------------------

    \618\ Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotus
and Tesla were not included in the baseline of the MY 2012-2016
rulemaking; Volvo vehicles were reported under Ford and Saab
vehicles were reported under GM; and Chrysler was reported as a
separate company whereas now it is reported as part of Fiat and
includes Alfa Romeo, Ferrari, and Maserati.

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[GRAPHIC] [TIFF OMITTED] TP01DE11.157

    Estimated achieved fuel economy levels:
    The current baseline market forecast shows industry-wide average
fuel economy levels somewhat lower in MY 2016 than shown in the
baseline market forecast for the MY 2012-2016 rulemaking. Under the
current baseline, average fuel economy for MY 2016 is 27.0 mpg, versus
27.3 mpg under the baseline in the MY 2012-2016 rulemaking. The 0.3 mpg
change relative to the MY 2012-2016 rulemaking's baseline is the result
of changes in the shares of passenger car

and light trucks in the MY 2016 market as noted above--more light
trucks generally equals lower average fuel economy--and not the result
of changes in the capabilities of the car and truck fleets.
    These differences are shown in greater detail below in Table IV-2,
which shows manufacturer-specific CAFE levels (not counting FFV credits
that some manufacturers expect to earn) from the current baseline
versus the MY 2012-2016 rulemaking baseline for passenger cars and
light trucks. Table IV-3 shows the combined averages of these planned
CAFE levels in the respective baseline fleets. These tables demonstrate
that there are no significant differences in CAFE for either passenger
cars or light trucks at the manufacturer level between the current
baseline and the MY 2012-2016 rulemaking baseline. The differences
become more significant at the manufacturer level when combined CAFE
levels are considered. Here we see a general decline in CAFE at the
manufacturer level due to the increased share of light trucks. Because
the agencies have, as for the MY 2012-2016 rulemaking, based this
market forecast on vehicles in the MY 2008 fleet, these changes in CAFE
levels reflect changes in vehicle mix, not changes in the fuel economy
achieved by individual vehicle models.
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---------------------------------------------------------------------------

    \619\ Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotus
and Tesla were not included in the baseline of the MY 2012-2016
rulemaking; Volvo vehicles were reported under Ford and Saab
vehicles were reported under GM; and Chrysler was reported as a
separate company whereas now it is reported as part of Fiat and
includes Alfa Romeo, Ferrari, and Maserati.

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

[GRAPHIC] [TIFF OMITTED] TP01DE11.159

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

    \620\ Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotus
and Tesla were not included in the baseline of the MY 2012-2016
rulemaking; Volvo vehicles were reported under Ford and Saab
vehicles were reported under GM; and Chrysler was reported as a
separate company whereas now it is reported as part of Fiat and
includes Alfa Romeo, Ferrari, and Maserati.
---------------------------------------------------------------------------

BILLING CODE 4910-59-C
e. How does manufacturer product plan data factor into the baseline
used in this rule?
    In December 2010, NHTSA requested that manufacturers provide
information regarding future product plans, as well as information
regarding the context for those plans (e.g., estimates of future fuel
prices), and estimates of the future availability, cost, and efficacy
of fuel-saving technologies.\621\ The purpose of this request was to
acquire updated information regarding vehicle manufacturers' future
product plans to assist the agency in assessing what corporate CAFE
standards should be established for passenger cars and light trucks
manufactured in model years 2017 and beyond. The request was being
issued in preparation for today's joint NPRM.
---------------------------------------------------------------------------

    \621\ 75 FR 80430.
---------------------------------------------------------------------------

    NHTSA indicated that it requested information for MYs 2010-2025
primarily as a basis for subsequent discussions with individual
manufacturers regarding their capabilities for the MYs 2017-2025 time
frame as it worked to develop today's NPRM. NHTSA indicated that the
information received would supplement other information to be used by
NHTSA to develop a realistic forecast of the vehicle market in MY 2017
and beyond, and to evaluate what technologies may feasibly be applied
by manufacturers to

achieve compliance with potential future standards. NHTSA further
indicated that information regarding later model years could help the
agency gain a better understanding of how manufacturers' plans through
MY 2025 relate to their longer-term expectations regarding foreseeable
regulatory requirements, market trends, and prospects for more advanced
technologies.
    NHTSA also indicated that it would consider information regarding
the model years requested when considering manufacturers' planned
schedules for redesigning and freshening their products, in order to
examine how manufacturers anticipate tying technology introduction to
product design schedules. In addition, the agency requested information
regarding manufacturers' estimates of the future vehicle population,
and fuel economy improvements and incremental costs attributed to
technologies reflected in those plans.
    Given the importance that responses to this request for comment may
have in informing NHTSA's proposed CAFE rulemaking, whether as part of
the basis for the standards or as an independent check on them, NHTSA
requested that commenters fully respond to each question, particularly
by providing information regarding the basis for technology costs and
effectiveness estimates.
    We have already noted that in past CAFE rulemakings, NHTSA used
manufacturers' product plans--and other information--to build market
forecasts providing the foundation for the agency's rulemaking
analysis. This issue has been the subject of much debate over the past
several rulemakings since NHTSA began actively working on CAFE again
following the lifting of the appropriations riders in 2001. The agency
continues to believe that these market forecasts reflected the most
technically sound forecasts the agency could have then developed for
this purpose. Because the agency could not disclose confidential
business information in manufacturers' product plans, NHTSA provided
summarized information, such as planned CAFE levels and technology
application rates, rather than the fuel economy levels and technology
content of specific vehicle model types.
    In preparing the MY 2012-2016 rule jointly with EPA, however, NHTSA
revisited this practice, and concluded that for that rulemaking, it was
important that all reviewers have equal access to all details of
NHTSA's analysis. NHTSA provided this level of transparency by
releasing not only the agency's CAFE modeling system, but also by
releasing all model inputs and outputs for the agency's analysis, all
of which are available on NHTSA's Web site at http://www.nhtsa.gov/fuel-economy. Therefore, NHTSA worked with EPA, as it did in preparing
for analysis supporting today's proposal, to build a market forecast
based on publicly- and commercially-available sources. NHTSA continues
to believe that the potential technical benefits of relying on
manufacturers' plans for future products are outweighed by the
transparency gained in building a market forecast that does not rely on
confidential business information, but also continues to find product
plan information to be an important point of reference for meetings
with individual manufacturers. We seek comment on what value
manufacturer product plan might have in the future, and whether it
continues to be useful to request manufacturer product plans to inform
rulemaking analyses, specifically the baseline forecast used in
rulemaking analyses.
f. What sensitivity analyses is NHTSA conducting on the baseline?
    As discussed below in Section IV.G, when evaluating the potential
impacts of new CAFE standards, NHTSA considered the potential that,
depending on how the cost and effectiveness of available technologies
compare to the price of fuel, manufacturers would add more fuel-saving
technology than might be required solely for purposes of complying with
CAFE standards. This reflects that agency's consideration that there
could, in the future, be at least some market for fuel economy
improvements beyond the required MY 2016 CAFE levels. In this
sensitivity analysis, this causes some additional technology to be
applied, more so under baseline standards than under the more stringent
standards proposed today by the agency. Results of this sensitivity
analysis are summarized in Section IV.G and in NHTSA's PRIA
accompanying today's notice.
g. How else is NHTSA considering looking at the baseline for the final
rule?
    Beyond the sensitivity analysis discussed above, NHTSA is also
considering developing and using a vehicle choice model to estimate the
extent to which sales volumes would shift in response to changes in
vehicle prices and fuel economy levels. As discussed IV.C.4, the agency
is currently sponsoring research directed toward developing such a
model. If that effort is successful, the agency will consider
integrating the model into the CAFE modeling system and using the
integrated system for future analysis of potential CAFE standards. If
the agency does so, we expect that the vehicle choice model would
impact estimated fleet composition not just under new CAFE standards,
but also under baseline CAFE standards.
2. How were the technology inputs developed?
    As discussed above in Section II.E, for developing the technology
inputs for these proposed MYs 2017-2025 CAFE and GHG standards, the
agencies primarily began with the technology inputs used in the MYs
2012-2016 CAFE final rule and in the 2010 TAR. The agencies have also
updated information based on newly completed FEV tear down studies and
new vehicle simulation work conducted by Ricardo Engineering, both of
which were contracted by EPA. Additionally, the agencies relied on a
model developed by Argonne National Laboratory to estimate hybrid,
plug-in hybrid and electric vehicle battery costs. More detail is
available regarding how the agencies developed the technology inputs
for this proposal above in Section II.E, in Chapter 3 of the Joint TSD,
and in Section V of NHTSA's PRIA.
a. What technologies does NHTSA consider?
    Section II.E.1 above describes the fuel-saving technologies
considered by the agencies that manufacturers could use to improve the
fuel economy of their vehicles during MYs 2017-2025. Many of the
technologies described in this section are readily available, well
known, and could be incorporated into vehicles once production
decisions are made. Other technologies, added for this rulemaking
analysis, are considered that are not currently in production, but are
beyond the initial research phase, under development and are expected
to be in production in the next 5-10 years. As discussed, the
technologies considered fall into five broad categories: engine
technologies, transmission technologies, vehicle technologies,
electrification/accessory technologies, and hybrid technologies. Table
IV-4 below lists all the technologies considered and provides the
abbreviations used for them in the CAFE model,\622\ as well as their
year of availability, which for purposes of NHTSA's analysis means the
first model year in the rulemaking

period that the CAFE model is allowed to apply a technology to a
manufacturer's fleet.\623\ ``Year of availability'' recognizes that
technologies must achieve a level of technical viability before they
can be implemented in the CAFE model, and are thus a means of
constraining technology use until such time as it is considered to be
technologically feasible. For a more detailed description of each
technology and their costs and effectiveness, we refer the reader to
Chapter 3 of the Joint TSD and Section V of NHTSA's PRIA.
---------------------------------------------------------------------------

    \622\ The abbreviations are used in this section both for
brevity and for the reader's reference if they wish to refer to the
expanded decision trees and the model input and output sheets, which
are available in Docket No. NHTSA-2010-0131 and on NHTSA's Web site.
    \623\ A date of 2012 means the technology can be applied in all
model years, while a date of 2020 means the technology can only be
applied in model years 2020 through 2025.
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BILLING CODE 4910-59-C
    For purposes of this proposal and as discussed in greater detail in
the Joint TSD, NHTSA and EPA built upon the list of technologies used
by agencies for the MYs 2017-2025 CAFE and GHG standards. NHTSA and EPA
had additional technologies to the list that that the agencies expect
to be in production during the MYs 2017-2025 timeframe. These new
technologies included higher BMEP turbocharged and downsized engines,
advanced diesel engines, higher efficiency transmissions, additional
mass reduction levels, PHEVs, EVs, etc.
    b. How did NHTSA determine the costs and effectiveness of each of
these technologies for use in its modeling analysis?
    Building on cost estimates developed for the MYs 2012-2016 CAFE and
GHG final rule and the 2010 TAR, the agencies incorporated new cost and
effectiveness estimates for the new technologies being considered and
some of the technologies carried over from the MYs 2012-2016 final rule
and 2010 TAR. This joint work is reflected in Chapter 3 of the Joint
TSD and in Section II of this preamble, as summarized below. For more
detailed information on the effectiveness and cost of fuel-saving
technologies, please refer to Chapter 3 of the Joint TSD and Section V
of NHTSA's PRIA.
    For this proposal the FEV tear down work was expanded to include an
8-speed DCT, a power-split hybrid, which was used to determine a P2
hybrid cost, and a mild hybrid with stop-start technology.
Additionally, battery costs have been revised using Argonne National
Laboratory's battery cost model. The model developed by ANL allows
users to estimate unique battery pack cost using user customized input
sets for different hybridization applications, such as strong hybrid,
PHEV and EV. Based on staff input and public feedback EPA and NHTSA
have modified how the indirect costs, using ICMs, were derived and
applied. The updates are discussed at length in Chapter 3 of the Joint
TSD and in Chapter 5 of NHTSA's PRIA.
    Some of the effectiveness estimates for technologies applied in MYs
2012-2016 and 2010 TAR have remained the same. However, nearly all of
the effectiveness estimates for carryover technologies have been
updated based on a newer version of EPA's lumped parameter model, which
was calibrated by the vehicle simulation work performed by Ricardo
Engineering. The Ricardo simulation study was also used to estimate the
effectiveness for the technologies newly considered for this proposal
like higher BMEP turbocharged and downsized engine, advanced
transmission technologies and P2 Hybrids. While NHTSA and EPA apply
technologies differently, the agencies have sought to ensure that the
resultant effectiveness of applying technologies is consistent between
the two agencies.
    NHTSA notes that, in developing technology cost and effectiveness
estimates, the agencies have made every effort to hold constant aspects
of vehicle performance and utility typically valued by consumers, such
as horsepower, carrying capacity, drivability, durability, noise,
vibration and harshness (NVH) and towing and hauling capacity. For
example, NHTSA includes in its analysis technology cost and
effectiveness estimates that are specific to performance passenger cars
(i.e., sports cars), as compared to nonperformance passenger cars.
NHTSA seeks comment on the extent to which commenters believe that the
agencies have been successful in holding constant these elements of
vehicle performance and utility in developing the technology cost and
effectiveness estimates.
    The agency notes that the technology costs included in this
proposal take into account only those associated with the initial build
of the vehicle. Although comments were received to the MYs

2012-2016 rulemaking that suggested there could be additional
maintenance required with some new technologies (e.g., turbocharging,
hybrids, etc.), and that additional maintenance costs could occur as a
result, the agencies have not explicitly incorporated maintenance costs
(or potential savings) as a separate element in this analysis. The
agency requests comments on this topic and will undertake a more
detailed review of these potential costs for the final rule.
    For some of the technologies, NHTSA's inputs, which are designed to
be as consistent as practicable with EPA's, indicate negative
incremental costs. In other words, the agency is estimating that some
technologies, if applied in a manner that holds performance and utility
constant, will, following initial investment (for, e.g., R&D and
tooling) by the manufacturer and its suppliers, incrementally improve
fuel savings and reduce vehicle costs. Nonetheless, in the agency's
central analysis, these and other technologies are applied only insofar
as is necessary to achieve compliance with standards defining any given
regulatory alternative (where the baseline no action alternative
assumes CAFE standards are held constant after MY 2016). The agency has
also performed a sensitivity analysis involving market-based
application of technology--that is, the application of technology
beyond the point needed to achieve compliance, if the cost of the
technology is estimated to be sufficiently attractive relative to the
accompanying fuel savings. NHTSA has invited comment on all of its
technology estimates, and specifically requests comment on the
likelihood that each technology will, if applied in a manner that holds
vehicle performance and utility constant, be able to both deliver the
estimated fuel savings and reduce vehicle cost. The agency also invites
comment on whether, for the final rule, its central analysis should be
revised to include estimated market-driven application of technology.
    The tables below provide examples of the incremental cost and
effectiveness estimates employed by the agency in developing this
proposal, according to the decision trees used in the CAFE modeling
analysis. Thus, the effectiveness and cost estimates are not absolute
to a single reference vehicle, but are incremental to the technology or
technologies that precede it.
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c. How does NHTSA use these assumptions in its modeling analysis?
    NHTSA relies on several inputs and data files to conduct the
compliance analysis using the CAFE model, as discussed further below
and in Chapter 5 of the PRIA. For the purposes of applying
technologies, the CAFE model primarily uses three data files, one that
contains data on the vehicles expected to be manufactured in the model
years covered by the rulemaking and identifies the appropriate stage
within the vehicle's life-cycle for the technology to be applied, one
that contains data/parameters regarding the available technologies the
model can apply, and one that contains economic assumption inputs for
calculating the costs and benefits of the standards. The inputs for the
first two data files are discussed below.
    As discussed above, the CAFE model begins with an initial state of
the domestic vehicle market, which in this case is the market for
passenger cars and light trucks to be sold during the period covered by
the proposed standards. The vehicle market is defined on a year-by-
year, model-by-model, engine-by-engine, and transmission-by-
transmission basis, such that each defined vehicle model refers to a
separately defined engine and a separately defined transmission.
Comparatively, EPA's OMEGA model defines the vehicle market using
representative vehicles at the vehicle platform level, which are binned
into 5 year timeframes instead of year-by-year.
    For the current standards, which cover MYs 2017-2025, the light-
duty vehicle (passenger car and light truck) market forecast was
developed jointly by NHTSA and EPA staff using MY 2008 CAFE compliance
data. The MY 2008 compliance data includes about 1,100 vehicle models,
about 400 specific engines, and about 200 specific transmissions, which
is a somewhat lower level of detail in the representation of the
vehicle market than that used by NHTSA in prior CAFE analyses--previous
analyses would count a vehicle as ``new'' in any year when significant
technology differences are made, such as at a redesign.\624\ However,
within the limitations of information that can be made available to the
public, it provides the foundation for a reasonable analysis of
manufacturer-specific costs and the analysis of attribute-based CAFE
standards, and is much greater than the level of detail used by many
other models and analyses relevant to light-duty vehicle fuel
economy.\625\
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    \624\ The market file for the MY 2011 final rule, which included
data for MYs 2011-2015, had 5500 vehicles, about 5 times what we are
using in this analysis of the MY 2008 certification data.
    \625\ Because CAFE standards apply to the average performance of
each manufacturer's fleet of cars and light trucks, the impact of
potential standards on individual manufacturers cannot be credibly
estimated without analysis of the fleets that manufacturers can be
expected to produce in the future. Furthermore, because required
CAFE levels under an attribute-based CAFE standard depend on
manufacturers' fleet composition, the stringency of an attribute-
based standard cannot be predicted without performing analysis at
this level of detail.
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    In addition to containing data about each vehicle, engine, and
transmission, this file contains information for each technology under
consideration as it pertains to the specific vehicle (whether the
vehicle is equipped with it or not), the estimated model year the
vehicle is undergoing a refresh or redesign, and information about the
vehicle's subclass for purposes of technology application. In essence,
the model considers whether it is appropriate to apply a technology to
a vehicle.
Is a vehicle already equipped, or can it not be equipped, with a
particular technology?
    The market forecast file provides NHTSA the ability to identify, on
a technology-by-technology basis, which technologies may already be
present (manufactured) on a particular vehicle, engine, or
transmission, or which technologies are not applicable (due to
technical considerations or engineering constraints) to a particular
vehicle, engine, or transmission. These identifications are made on a
model-by-model, engine-by-engine, and transmission-by-transmission
basis. For example, if the market forecast file indicates that
Manufacturer X's Vehicle Y is manufactured with Technology Z, then for
this vehicle Technology Z will be shown as used. Additionally, NHTSA
has determined that some technologies are only suitable or unsuitable
when certain vehicle, engine, or transmission conditions exist. For
example, secondary axle disconnect is only suitable for 4WD vehicles
and cylinder deactivation is unsuitable for any engine with fewer than
6 cylinders. Similarly, comments received to the 2008 NPRM indicated
that cylinder deactivation could not likely be applied to vehicles
equipped with manual transmissions during the rulemaking timeframe, due
primarily to the cylinder deactivation system not being able to
anticipate gear shifts. The CAFE model employs ``engineering
constraints'' to address issues like these, which are a programmatic
method of controlling technology application that is independent of
other constraints. Thus, the market forecast file would indicate that
the technology in question should not be applied to the particular
vehicle/engine/transmission (i.e., is unavailable). Since multiple
vehicle models may be equipped with an engine or transmission, this may
affect multiple models. In using this aspect of the market forecast
file, NHTSA ensures the CAFE model only applies technologies in an
appropriate manner, since before any application of a technology can
occur, the model checks the market forecast to see if it is either
already present or unavailable. NHTSA seeks comment on the continued
appropriateness of the engineering constraints used by the model, and
specifically whether many of the technical constraints will be resolved
(and therefore the engineering constraints should be changed) given the
increased focus of engineering resources that will be working to solve
these technical challenges.
    Whether a vehicle can be equipped with a particular technology
could also theoretically depend on certain technical considerations
related to incorporating the technology into particular vehicles. For
example, GM commented on the MY 2012-2016 NPRM that there are certain
issues in implementing turbocharging and downsizing technologies on
full-size trucks, like concerns related to engine knock, drivability,
control of boost pressure, packaging complexity, enhanced cooling for
vehicles that are designed for towing or hauling, and noise, vibration
and harshness. NHTSA stated in response that we believed that such
technical considerations are well recognized within the industry and it
is standard industry practice to address each during the design and
development phases of applying turbocharging and downsizing
technologies. The cost and effectiveness estimates used in the final
rule for MYs 2012-2016, as well as the cost and effectiveness estimates
employed in this NPRM, are based on analysis that assumes each of these
factors is addressed prior to production implementation of the
technologies. NHTSA continues to believe that these issues are
accounted for by industry, but we seek comment on whether the
engineering constraints should be used to address concerns like these
(and if so, how), or alternatively, whether some of the things that the
agency currently treats as engineering constraints should be (or
actually are) accounted for in the cost and effectiveness estimates
through assumptions like those described above, and whether the agency
might be double-constraining the application of technology.
Is a vehicle being redesigned or refreshed?
    Manufacturers typically plan vehicle changes to coincide with
certain stages

of a vehicle's life cycle that are appropriate for the change, or in
this case the technology being applied. In the automobile industry
there are two terms that describe when technology changes to vehicles
occur: Redesign and refresh (i.e., freshening). Vehicle redesign
usually refers to significant changes to a vehicle's appearance, shape,
dimensions, and powertrain. Redesign is traditionally associated with
the introduction of ``new'' vehicles into the market, often
characterized as the ``next generation'' of a vehicle, or a new
platform. Vehicle refresh usually refers to less extensive vehicle
modifications, such as minor changes to a vehicle's appearance, a
moderate upgrade to a powertrain system, or small changes to the
vehicle's feature or safety equipment content. Refresh is traditionally
associated with mid-cycle cosmetic changes to a vehicle, within its
current generation, to make it appear ``fresh.'' Vehicle refresh
generally occurs no earlier than two years after a vehicle redesign, or
at least two years before a scheduled redesign. To be clear, this is a
general description of how manufacturers manage their product lines and
refresh and redesign cycles but in some cases the timeframes could be
shorter and others longer depending on market factors, regulations,
etc. For the majority of technologies discussed today, manufacturers
will only be able to apply them at a refresh or redesign, because their
application would be significant enough to involve some level of
engineering, testing, and calibration work.\626\
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    \626\ For example, applying material substitution through weight
reduction, or even something as simple as low rolling-resistance
tires, to a vehicle will likely require some level of validation and
testing to ensure that the vehicle may continue to be certified as
compliant with NHTSA's Federal Motor Vehicle Safety Standards
(FMVSS). Weight reduction might affect a vehicle's crashworthiness;
low rolling-resistance tires might change a vehicle's braking
characteristics or how it performs in crash avoidance tests.
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    Some technologies (e.g., those that require significant revision)
are nearly always applied only when the vehicle is expected to be
redesigned, like turbocharging and engine downsizing, or conversion to
diesel or hybridization. Other technologies, like cylinder
deactivation, electric power steering, and low rolling resistance tires
can be applied either when the vehicle is expected to be refreshed or
when it is expected to be redesigned, while low friction lubricants,
can be applied at any time, regardless of whether a refresh or redesign
event is conducted. Accordingly, the model will only apply a technology
at the particular point deemed suitable. These constraints are intended
to produce results consistent with how we assume manufacturers will
apply technologies in the future based on how they have historically
implemented new technologies. For each technology under consideration,
NHTSA specifies whether it can be applied any time, at refresh/
redesign, or only at redesign. The data forms another input to the CAFE
model. NHTSA develops redesign and refresh schedules for each of a
manufacturer's vehicles included in the analysis, essentially based on
the last known redesign year for each vehicle and projected forward
using a 5 to 8-year redesign and a 2-3 year refresh cycle, and this
data is also stored in the market forecast file. While most vehicles
are projected to follow a 5-year redesign a few of the niche market or
small-volume manufacturer vehicles (i.e. luxury and performance
vehicles) and large trucks are assumed to have 6- to 8-year redesigns
based on historic redesign schedules and the agency's understanding of
manufacturers' intentions moving forward. This approach is used because
of the nature of the current baseline, which as a single year of data
does not contain its own refresh and redesign cycle cues for future
model years, and to ensure the complete transparency of the agency's
analysis. We note that this approach is different from what NHTSA has
employed previously for determining redesign and refresh schedules,
where NHTSA included the redesign and refresh dates in the market
forecast file as provided by manufacturers in confidential product
plans. Vehicle redesign/refresh assumptions are discussed in more
detail in Chapter 5 of the PRIA and in Chapter 3 of the TSD.
    NHTSA has previously received comments stating that manufacturers
do not necessarily adhere to strict five-year redesign cycles, and may
add significant technologies by redesigning vehicles at more frequent
intervals, albeit at higher costs. Conversely, other comments received
stated that as compared to full-line manufacturers, small-volume
manufacturers in fact may have 7 to 8-year redesign cycles.\627\ The
agency believes that manufacturers can and will accomplish much
improvement in fuel economy and GHG reductions while applying
technology consistent with their redesign schedules.
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    \627\ In the MY 2011 final rule, NHTSA noted that the CAR report
submitted by the Alliance, prepared by the Center for Automotive
Research and EDF, stated that ``For a given vehicle line, the time
from conception to first production may span two and one-half to
five years,'' but that ``The time from first production
(``Job1'') to the last vehicle off the line (``Balance
Out'') may span from four to five years to eight to ten years or
more, depending on the dynamics of the market segment.'' The CAR
report then stated that ``At the point of final production of the
current vehicle line, a new model with the same badge and similar
characteristics may be ready to take its place, continuing the
cycle, or the old model may be dropped in favor of a different
product.'' See NHTSA-2008-0089-0170.1, Attachment 16, at 8 (393 of
pdf). NHTSA explained that this description, which states that a
vehicle model will be redesigned or dropped after 4-10 years, was
consistent with other characterizations of the redesign and
freshening process, and supported the 5-year redesign and 2-3 year
refresh cycle assumptions used in the MY 2011 final rule. See id.,
at 9 (394 of pdf). Given that the situation faced by the auto
industry today is not so wholly different from that in March 2009,
when the MY 2011 final rule was published, and given that the
commenters did not present information to suggest that these
assumptions are unreasonable (but rather simply that different
manufacturers may redesign their vehicles more or less frequently,
as the range of cycles above indicates), NHTSA believes that the
assumptions remain reasonable for purposes of this NPRM analysis.
See also ``Car Wars 2009-2012, The U.S. automotive product
pipeline,'' John Murphy, Research Analyst, Merrill Lynch research
paper, May 14, 2008 and ``Car Wars 2010-2013, The U.S. automotive
product pipeline,'' John Murphy, Research Analyst, Bank of America/
Merrill Lynch research paper, July 15, 2009. Available at http://www.autonews.com/assets/PDF/CA66116716.PDF (last accessed October
11, 2011).
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    Once the model indicates that a technology should be applied to a
vehicle, the model must evaluate which technology should be applied.
This will depend on the vehicle subclass to which the vehicle is
assigned; what technologies have already been applied to the vehicle
(i.e., where in the ``decision tree'' the vehicle is); when the
technology is first available (i.e., year of availability); whether the
technology is still available (i.e., ``phase-in caps''); and the costs
and effectiveness of the technologies being considered. Technology
costs may be reduced, in turn, by learning effects and short- vs. long-
term ICMs, while technology effectiveness may be increased or reduced
by synergistic effects between technologies. In the technology input
file, NHTSA has developed a separate set of technology data variables
for each of the twelve vehicle subclasses. Each set of variables is
referred to as an ``input sheet,'' so for example, the subcompact
passenger car input sheet holds the technology data that is appropriate
for the subcompact subclass. Each input sheet contains a list of
technologies available for members of the particular vehicle subclass.
The following items are provided for each technology: The name of the
technology, its abbreviation, the decision tree with which it is
associated, the (first) year in which it is available, the year-by-year
cost estimates and effectiveness (fuel consumption reduction)
estimates, its applicability and the consumer value

loss. The phase-in values and the potential stranded capital costs are
common for all vehicle subclasses and are thus listed in a separate
input sheet that is referenced for all vehicle subclasses.
To which vehicle subclass is the vehicle assigned?
    As part of its consideration of technological feasibility, the
agency evaluates whether each technology could be implemented on all
types and sizes of vehicles, and whether some differentiation is
necessary in applying certain technologies to certain types and sizes
of vehicles, and with respect to the cost incurred and fuel consumption
and CO2 emissions reduction achieved when doing so. The 2010
NAS Report differentiated technology application using eight vehicle
``classes'' (4 car classes and 4 truck classes).\628\ NAS's purpose in
separating vehicles into these classes was to create groups of ``like''
vehicles, i.e., vehicles similar in size, powertrain configuration,
weight, and consumer use, and for which similar technologies are
applicable. NAS also used these vehicle classes along with powertrain
configurations (e.g..4 cylinder, 6 cylinder or 8 cylinder engines) to
determine unique cost and effectiveness estimates for each class of
vehicles.
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    \628\ The NAS classes included two-seater convertibles and
coupes; small cars; intermediate and large cars; high-performance
sedans; unit-body standard trucks; unit-body high-performance
trucks; body-on-frame small and midsize trucks; and body.
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    NHTSA similarly differentiates vehicles by ``subclass'' for the
purpose of applying technologies to ``like'' vehicles and assessing
their incremental costs and effectiveness. NHTSA assigns each vehicle
manufactured in the rulemaking period to one of 12 subclasses: For
passenger cars, Subcompact, Subcompact Performance, Compact, Compact
Performance, Midsize, Midsize Performance, Large, and Large
Performance; and for light trucks, Small SUV/Pickup/Van, Midsize SUV/
Pickup/Van, Large SUV/Pickup/Van, and Minivan. The agency seeks comment
on the appropriateness of these 12 subclasses for the MYs 2017-2025
timeframe. The agency is also seeking comment on the continued
appropriateness of maintaining separate ``performance'' vehicle classes
or if as fuel economy stringency increases the market for performance
vehicles will decrease.
    For this NPRM, NHTSA divides the vehicle fleet into subclasses
based on model inputs, and applies subclass-specific estimates, also
from model inputs, of the applicability, cost, and effectiveness of
each fuel-saving technology. The model's estimates of the cost to
improve the fuel economy of each vehicle model thus depend upon the
subclass to which the vehicle model is assigned. Each vehicle's
subclass is stored in the market forecast file. When conducting a
compliance analysis, if the CAFE model seeks to apply technology to a
particular vehicle, it checks the market forecast to see if the
technology is available and if the refresh/redesign criteria are met.
If these conditions are satisfied, the model determines the vehicle's
subclass from the market data file, which it then uses to reference
another input called the technology input file. NHTSA reviewed its
methodology for dividing vehicles into subclasses for purposes of
technology application that it used in the MY 2011 final rule and for
the MYs 2012-2016 rulemaking, and concluded that the same methodology
would be appropriate for this NPRM for MYs 2017-2025. Vehicle
subclasses are discussed in more detail in Chapter 5 of the PRIA and in
Chapter 3 of the TSD.
    For the reader's reference, the subclasses and example vehicles
from the market forecast file are provided in the tables below.

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What technologies have already been applied to the vehicle (i.e., where
in the ``decision trees'' is it)?
    NHTSA's methodology for technology analysis evaluates the
application of individual technologies and their incremental costs and
effectiveness. Individual technologies are assessed relative to the
prior technology state, which means that it is crucial to understand
what technologies are already present on a vehicle in order to
determine correct incremental cost and effectiveness values. The
benefit of the incremental approach is transparency in accounting,
insofar as when individual technologies are added incrementally to
individual vehicles, it is clear and easy to determine how costs and
effectiveness add up as technology levels increase and explicitly
accounting for any synergies that exist between technologies which are
already present on the vehicle and new technologies being applied.
    To keep track of incremental costs and effectiveness and to know
which technology to apply and in which order, the CAFE model's
architecture uses a logical sequence, which NHTSA refers to as
``decision trees,'' for applying fuel economy-improving technologies to
individual vehicles. For purposes of this proposal, NHTSA reviewed the
MYs 2012-2016 final rule's technology sequencing architecture, which
was based on the MY 2011 final rule's decision trees that were jointly
developed by NHTSA and Ricardo, and, as appropriate, updated the
decision trees to include new technologies that have been defined for
the MYs 2017-2025 timeframe.
    In general, and as described in great detail in Chapter 5 of the
current PRIA,\629\ each technology is assigned to one of the five
following categories based on the system it affects or impacts: Engine,
transmission, electrification/accessory, hybrid or

vehicle. Each of these categories has its own decision tree that the
CAFE model uses to apply technologies sequentially during the
compliance analysis. The decision trees were designed and configured to
allow the CAFE model to apply technologies in a cost-effective, logical
order that also considers ease of implementation. For example, software
or control logic changes are implemented before replacing a component
or system with a completely redesigned one, which is typically a much
more expensive and integration intensive option. In some cases, and as
appropriate, the model may combine the sequential technologies shown on
a decision tree and apply them simultaneously, effectively developing
dynamic technology packages on an as-needed basis. For example, if
compliance demands indicate, the model may elect to apply LUB, EFR, and
ICP on a dual overhead cam engine, if they are not already present, in
one single step. An example simplified decision tree for engine
technologies is provided below; the other simplified decision trees may
be found in Chapter 5 of the PRIA. Expanded decision trees are
available in the docket for this NPRM.
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    \629\ Additional details about technologies are categorized can
be found in the MY 2011 final rule.
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    Each technology within the decision trees has an incremental cost
and an incremental effectiveness estimate associated with it, and
estimates are specific to a particular vehicle subclass (see the tables
in Chapter 5 of the PRIA).

Each technology's incremental estimate takes into account its position
in the decision tree path. If a technology is located further down the
decision tree, the estimates for the costs and effectiveness values
attributed to that technology are influenced by the incremental
estimates of costs and effectiveness values for prior technology
applications. In essence, this approach accounts for ``in-path''
effectiveness synergies, as well as cost effects that occur between the
technologies in the same path. When comparing cost and effectiveness
estimates from various sources and those provided by commenters in this
and the previous CAFE rulemakings, it is important that the estimates
evaluated are analyzed in the proper context, especially as concerns
their likely position in the decision trees and other technologies that
may be present or missing. Not all estimates available in the public
domain or that have been (or will be) offered for the agencies'
consideration can be evaluated in an ``apples-to-apples'' comparison
with those used by the CAFE model, since in some cases the order of
application, or included technology content, is inconsistent with that
assumed in the decision tree.
    The MY 2011 final rule discussed in detail the revisions and
improvements made to the CAFE model and decision trees during that
rulemaking process, including the improved handling and accuracy of
valve train technology application and the development and
implementation of a method for accounting path-dependent correction
factors in order to ensure that technologies are evaluated within the
proper context. The reader should consult the MY 2011 final rule
documents for further information on these modeling techniques, all of
which continued to be utilized in developing this proposal.\630\ To the
extent that the decision trees have changed for purposes of the MYs
2012-2016 final rule and this NPRM, it was due not to revisions in the
order of technology application, but rather to redefinitions of
technologies or addition or subtraction of technologies.
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    \630\ See, e.g., 74 FR 14238-46 (Mar. 30, 2009) for a full
discussion of the decision trees in NHTSA's MY 2011 final rule, and
Docket No. NHTSA-2009-0062-0003.1 for an expanded decision tree used
in that rulemaking.
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Is the next technology available in this model year?
    Some of technologies considered are available on vehicles today,
and thus will be available for application (albeit in varying degrees)
in the model starting in MY 2017. Other technologies, however, will not
become available for purposes of NHTSA's analysis until later in the
rulemaking time frame. When the model is considering whether to add a
technology to a vehicle, it checks its year of availability--if the
technology is available, it may be added; if it is not available, the
model will consider whether to switch to a different decision tree to
look for another technology, or will skip to the next vehicle in a
manufacturer's fleet. The year of availability for each technology is
provided above in Table IV-4.
    The agency has received comments previously stating that if a
technology is currently available or available prior to the rulemaking
timeframe that it should be immediately made available in the model. In
response, as discussed above, technology ``availability'' is not
determined based simply on whether the technology exists, but depends
also on whether the technology has achieved a level of technical
viability that makes it appropriate for widespread application. This
depends in turn on component supplier constraints, capital investment
and engineering constraints, and manufacturer product cycles, among
other things. Moreover, even if a technology is available for
application, it may not be available for every vehicle. Some
technologies may have considerable fuel economy benefits, but cannot be
applied to some vehicles due to technological constraints--for example,
cylinder deactivation cannot be applied to vehicles with current 4-
cylinder engines (because not enough cylinders are present to
deactivate some and continue moving the vehicle) or on vehicles with
manual transmissions within the rulemaking timeframe. The agencies have
provided for increases over time to reach the mpg level of the MY 2025
standards precisely because of these types of constraints, because they
have a real effect on how quickly manufacturers can apply technology to
vehicles in their fleets. NHTSA seeks comment on the appropriateness of
the assumed years of availability.
Has the technology reached the phase-in cap for this model year?
    Besides the refresh/redesign cycles used in the CAFE model, which
constrain the rate of technology application at the vehicle level so as
to ensure a period of stability following any modeled technology
applications, the other constraint on technology application employed
in NHTSA's analysis is ``phase-in caps.'' Unlike vehicle-level cycle
settings, phase-in caps constrain technology application at the vehicle
manufacturer level.\631\ They are intended to reflect a manufacturer's
overall resource capacity available for implementing new technologies
(such as engineering and development personnel and financial
resources), thereby ensuring that resource capacity is accounted for in
the modeling process. At a high level, phase-in caps and refresh/
redesign cycles work in conjunction with one another to avoid the
modeling process out-pacing an OEM's limited pool of available
resources during the rulemaking time frame and the years leading up to
the rulemaking time frame, especially in years where many models may be
scheduled for refresh or redesign. Even though this rulemaking is being
proposed 5 years before it takes effect, OEM's will still be utilizing
their limited resources to meet the MYs 2012-2016 CAFE standards. This
helps to ensure technological feasibility and economic practicability
in determining the stringency of the standards.
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    \631\ While phase-in caps are expressed as specific percentages
of a manufacturer's fleet to which a technology may be applied in a
given model year, phase-in caps cannot always be applied as precise
limits, and the CAFE model in fact allows ``override'' of a cap in
certain circumstances. When only a small portion of a phase-in cap
limit remains, or when the cap is set to a very low value, or when a
manufacturer has a very limited product line, the cap might prevent
the technology from being applied at all since any application would
cause the cap to be exceeded. Therefore, the CAFE model evaluates
and enforces each phase-in cap constraint after it has been exceeded
by the application of the technology (as opposed to evaluating it
before application), which can result in the described overriding of
the cap.
---------------------------------------------------------------------------

    NHTSA has been developing the concept of phase-in caps for purposes
of the agency's modeling analysis over the course of the last several
CAFE rulemakings, as discussed in greater detail in the MY 2011 final
rule,\632\ in the MY 2012-2016 final rule and in Chapter 5 of the PRIA
and Chapter 3 of the Joint TSD. The MYs 2012-2016 final rule like the
MY 2011 final rule employed non-linear phase-in caps (that is, caps
that varied from year to year) that were designed to respond to
previously received comments on technology deployment.
---------------------------------------------------------------------------

    \632\ NEED A FOOTNOTE HERE
---------------------------------------------------------------------------

    For purposes of this NPRM for MYs 2017-2025, as in the MY 2011 and
MYs 2012-2016 final rules, NHTSA combines phase-in caps for some groups
of similar technologies, such as valve phasing technologies that are
applicable to different forms of engine design (SOHC, DOHC, OHV), since
they are very similar from an engineering and implementation
standpoint. When the phase-in caps for two technologies are combined,
the maximum total

application of either or both to any manufacturer's fleet is limited to
the value of the cap.\633\
---------------------------------------------------------------------------

    \633\ See 74 FR at 14270 (Mar. 30, 2009) for further discussion
and examples.
---------------------------------------------------------------------------

    In developing phase-in cap values for purposes of this NPRM, NHTSA
reviewed the MYs 2012-2016 final rule's phase-in caps, which for the
majority of technologies were set to reach 85 or 100 percent by MY
2016, although more advanced technologies like diesels and strong
hybrids reach only 15 percent by MY 2016. The phase-in caps used in the
MYs 2012-2016 final were developed to harmonize with EPA's proposal and
consider the fact that manufacturers, as part of the information shared
during the discussions that occurred during summer 2011, appeared to be
anticipating higher technology application rates than assumed in prior
rules. NHTSA determined that these phase-in caps for MY 2016 were still
reasonable and thus used those caps as the starting point for the MYs
2017-2025 phase-in caps. For many of the carryover technologies this
means that for MYs 2017-2025 the phase-in caps are assumed to be 100
percent. NHTSA along with EPA used confidential OEM submissions, trade
press articles, company publications and press releases to estimate the
phase-in caps for the newly defined technologies that will be entering
the market just before or during the MYs 2017-2025 time frame. For
example, advanced cooled EGR engines have a phase-in cap of 3 percent
per year through MY 2021 and then 10 percent per year through 2025. The
agency seeks comment on the appropriateness of both the carryover
phase-in caps and the newly defined ones proposed in this NPRM.
Is the technology less expensive due to learning effects?
    In the past two rulemakings NHTSA has explicitly accounted for the
cost reductions a manufacturer might realize through learning achieved
from experience in actually applying a technology. These cost
reductions, due to learning effects, were taken into account through
two kinds of mutually exclusive learning, ``volume-based'' and ``time-
based.'' NHTSA and EPA included a detailed description of the learning
effect in the MYs 2012-2016 final rule and the more recent heavy-duty
rule.\634\
---------------------------------------------------------------------------

    \634\ 76 FR 57106, 57320 (Sept. 15, 2011).
---------------------------------------------------------------------------

    Most studies of the effect of experience or learning on production
costs appear to assume that cost reductions begin only after some
initial volume threshold has been reached, but not all of these studies
specify this threshold volume. The rate at which costs decline beyond
the initial threshold is usually expressed as the percent reduction in
average unit cost that results from each successive doubling of
cumulative production volume, sometimes referred to as the learning
rate. Many estimates of experience curves do not specify a cumulative
production volume beyond which cost reductions would no longer occur,
instead depending on the asymptotic behavior of the effect for learning
rates below 100 percent to establish a floor on costs.
    In past rulemaking analyses, as noted above, both agencies have
used a learning curve algorithm that applied a learning factor of 20
percent for each doubling of production volume. NHTSA has used this
approach in analyses supporting recent CAFE rules. In its analyses, EPA
has simplified the approach by using an ``every two years'' based
learning progression rather than a pure production volume progression
(i.e., after two years of production it was assumed that production
volumes would have doubled and, therefore, costs would be reduced by 20
percent).\635\
---------------------------------------------------------------------------

    \635\ To clarify, EPA has simplified the steep portion of the
volume learning curve by assuming that production volumes of a given
technology will have doubled within two years time. This has been
done largely to allow for a presentation of estimated costs during
the years of implementation, without the need to conduct a feedback
loop that ensures that production volumes have indeed doubled. If
EPA was to attempt such a feedback loop, it would need to estimate
first year costs, feed those into OMEGA, review the resultant
technology penetration rate and volume increase, calculate the
learned costs, feed those into OMEGA (since lower costs would result
in higher penetration rates, review the resultant technology
penetration rate and volume increase, etc., until an equilibrium was
reached. To do this for the dozens of technologies considered in the
analysis for this rulemaking was deemed not feasible. Instead, EPA
estimated the effects of learning on costs, fed those costs into
OMEGA, and reviewed the resultant penetration rates. The assumption
that volumes have doubled after two years is based solely on the
assumption that year two sales are of equal or greater number than
year one sales and, therefore, have resulted in a doubling of
production. This could be done on a daily basis, a monthly basis, or
a yearly basis as was done for this analysis.
---------------------------------------------------------------------------

    In the MYs 2012-2016 light-duty rule, the agencies employed an
additional learning algorithm to reflect the volume-based learning cost
reductions that occur further along on the learning curve. This
additional learning algorithm was termed ``time-based'' learning simply
as a means of distinguishing this algorithm from the volume-based
algorithm mentioned above, although both of the algorithms reflect the
volume-based learning curve supported in the literature. To avoid
confusion, we are now referring to this learning algorithm as the
``flat portion'' of the learning curve. This way, we maintain the
clarity that all learning is, in fact, volume-based learning, and that
the level of cost reductions depend only on where on the learning curve
a technology's learning progression is. We distinguish the flat portion
of the curve from the ``steep portion'' of the curve to indicate the
level of learning taking place in the years following implementation of
the technology. The agencies have applied the steep portion learning
algorithm for those technologies considered to be newer technologies
likely to experience rapid cost reductions through manufacturer
learning, and the flat portion learning algorithm for those
technologies considered to be mature technologies likely to experience
only minor cost reductions through manufacturer learning. As noted
above, the steep portion learning algorithm results in 20 percent lower
costs after two full years of implementation (i.e., the MY 2016 costs
are 20 percent lower than the MYs 2014 and 2015 costs). Once two steep
portion learning steps have occurred (for technologies having the steep
portion learning algorithm applied while flat portion learning would
begin in year 2 for technologies having the flat portion learning
algorithm applied), flat portion learning at 3 percent per year becomes
effective for 5 years. Beyond 5 years of learning at 3 percent per
year, 5 years of learning at 2 percent per year, then 5 at 1 percent
per year become effective.
    Technologies assumed to be on the steep portion of the learning
curve are hybrids and electric vehicles, while no learning is applied
to technologies likely to be affected by commodity costs (LUB, ROLL) or
that have loosely-defined BOMs (EFR, LDB), as was the case in the MY
2012-2016 final rule. Chapter 3 of the Joint TSD and the PRIA shows the
specific learning factors that NHTSA has applied in this analysis for
each technology, and discusses learning factors and each agency's use
of them further. EPA and NHTSA included discussion of learning cost
assumptions in the RIAs and TSD Chapter 3. Since the agencies had to
project how learning will occur with new technologies over a long
period of time, we request comments on the assumptions of learning
costs and methodology. In particular, we are interested in input on the
assumptions for advanced 27-bar BMEP cooled EGR engines, which are
currently still in the experimental stage and not expected to be
available in

volume production until 2017. For our analysis, we have based estimates
of the costs of high-BMEP engines on current (or soon to be current)
production engines, and assumed that learning (and the associated cost
reductions) begins as early as 2012. We seek comment on the
appropriateness of these pre-production applications of learning.
Is the technology more or less effective due to synergistic effects?
    When two or more technologies are added to a particular vehicle
model to improve its fuel efficiency and reduce CO2
emissions, the resultant fuel consumption reduction may sometimes be
higher or lower than the product of the individual effectiveness values
for those items.\636\ This may occur because one or more technologies
applied to the same vehicle partially address the same source (or
sources) of engine, drivetrain or vehicle losses. Alternately, this
effect may be seen when one technology shifts the engine operating
points, and therefore increases or reduces the fuel consumption
reduction achieved by another technology or set of technologies. The
difference between the observed fuel consumption reduction associated
with a set of technologies and the product of the individual
effectiveness values in that set is referred to for purposes of this
rulemaking as a ``synergy.'' Synergies may be positive (increased fuel
consumption reduction compared to the product of the individual
effects) or negative (decreased fuel consumption reduction). An example
of a positive synergy might be a vehicle technology that reduces road
loads at highway speeds (e.g., lower aerodynamic drag or low rolling
resistance tires), that could extend the vehicle operating range over
which cylinder deactivation may be employed. An example of a negative
synergy might be a variable valvetrain system technology, which reduces
pumping losses by altering the profile of the engine speed/load map,
and a six-speed automatic transmission, which shifts the engine
operating points to a portion of the engine speed/load map where
pumping losses are less significant.
---------------------------------------------------------------------------

    \636\ More specifically, the products of the differences between
one and the technology-specific levels of effectiveness in reducing
fuel consumption. For example, not accounting for interactions, if
technologies A and B are estimated to reduce fuel consumption by 10
percent (i.e., 0.1) and 20 percent (i.e., 0.2) respectively, the
``product of the individual effectiveness values'' would be 1-0.1
times 1-0.2, or 0.9 times 0.8, which equals 0.72, corresponding to a
combined effectiveness of 28 percent rather than the 30 percent
obtained by adding 10 percent to 20 percent. The ``synergy factors''
discussed in this section further adjust these multiplicatively
combined effectiveness values.
---------------------------------------------------------------------------

    As the complexity of the technology combinations is increased, and
the number of interacting technologies grows accordingly, it becomes
increasingly important to account for these synergies. NHTSA and EPA
determined synergistic impacts for this proposed rule using EPA's
``lumped parameter'' analysis tool, which EPA describes at length in
Chapter 3 of the TSD. The lumped parameter tool is a spreadsheet model
that represents energy consumption in terms of average performance over
the fuel economy test procedure, rather than explicitly analyzing
specific drive cycles. The tool begins with an apportionment of fuel
consumption across several loss mechanisms and accounts for the average
extent to which different technologies affect these loss mechanisms
using estimates of engine, drivetrain and vehicle characteristics that
are averaged over the 2-cycle CAFE drive cycle. Results of this
analysis were generally consistent with those of full-scale vehicle
simulation modeling performed in 2010-2011 for EPA by Ricardo, Inc.
    For the current rulemaking, NHTSA is using an updated version of
lumped parameter tool that incorporates results from simulation
modeling performed in 2010-2011 by Ricardo, Inc. NHTSA and EPA
incorporate synergistic impacts in their analyses in slightly different
manners. Because NHTSA applies technologies individually in its
modeling analysis, NHTSA incorporates synergistic effects between
pairings of individual technologies. The use of discrete technology
pair incremental synergies is similar to that in DOE's National Energy
Modeling System (NEMS).\637\ Inputs to the CAFE model incorporate NEMS-
identified pairs, as well as additional pairs from the set of
technologies considered in the CAFE model.
---------------------------------------------------------------------------

    \637\ U.S. Department of Energy, Energy Information
Administration, Transportation Sector Module of the National Energy
Modeling System: Model Documentation 2007, May 2007, Washington, DC,
DOE/EIAM070(2007), at 29-30. Available at http://tonto.eia.doe.gov/ftproot/modeldoc/m070(2007).pdf (last accessed Sept. 25, 2011).
---------------------------------------------------------------------------

    NHTSA notes that synergies that occur within a decision tree are
already addressed within the incremental values assigned and therefore
do not require a synergy pair to address. For example, all engine
technologies take into account incremental synergy factors of preceding
engine technologies, and all transmission technologies take into
account incremental synergy factors of preceding transmission
technologies. These factors are expressed in the fuel consumption
improvement factors in the input files used by the CAFE model.
    For applying incremental synergy factors in separate path
technologies, the CAFE model uses an input table (see the tables in
Chapter 3 of the TSD and in the PRIA) that lists technology pairings
and incremental synergy factors associated with those pairings, most of
which are between engine technologies and transmission/electrification/
hybrid technologies. When a technology is applied to a vehicle by the
CAFE model, all instances of that technology in the incremental synergy
table which match technologies already applied to the vehicle (either
pre-existing or previously applied by the CAFE model) are summed and
applied to the fuel consumption improvement factor of the technology
being applied. Many of the synergies for the strong hybrid technology
fuel consumption reductions are included in the incremental value for
the specific hybrid technology block since the model applies all
available electrification, engine and transmission technologies before
applying strong hybrid technologies.
    The U.S. DOT Volpe Center has entered into a contract with Argonne
National Laboratory (ANL) to provide full vehicle simulation modeling
support for this MYs 2017-2025 rulemaking. While this modeling was not
completed in time for use in this NPRM, NHTSA intends to use this
modeling to validate/update technology effectiveness estimates and
synergy factors for the final rulemaking analysis. This simulation
modeling will be accomplished using ANL's full vehicle simulation tool
called ``Autonomie,'' which is the successor to ANL's Powertrain System
Analysis Toolkit (PSAT) simulation tool, and ANL's expertise with
advanced vehicle technologies.
d. Where can readers find more detailed information about NHTSA's
technology analysis?
    Much more detailed information is provided in Chapter 5 of the
PRIA, and a discussion of how NHTSA and EPA jointly reviewed and
updated technology assumptions for purposes of this NPRM is available
in Chapter 3 of the TSD. Additionally, all of NHTSA's model input and
output files are now public and available for the reader's review and
consideration. The technology input files can be found in the docket
for this NPRM, Docket No. NHTSA-2010-0131, and on NHTSA's Web site. And
finally, because much of NHTSA's technology analysis for

purposes of this proposal builds on the work that was done for the MY
2011 and MYs 2012-2016 final rules, we refer readers to those documents
as well for background information concerning how NHTSA's methodology
for technology application analysis has evolved over the past several
rulemakings, both in response to comments and as a result of the
agency's growing experience with this type of analysis.\638\
---------------------------------------------------------------------------

    \638\ 74 FR 14233-308 (Mar. 30, 2009).
---------------------------------------------------------------------------

3. How did NHTSA develop its economic assumptions?
    NHTSA's analysis of alternative CAFE standards for the model years
covered by this rulemaking relies on a range of forecast variables,
economic assumptions, and parameter values. This section describes the
sources of these forecasts, the rationale underlying each assumption,
and the agency's choices of specific parameter values. These economic
values play a significant role in determining the benefits of
alternative CAFE standards, as they have for the last several CAFE
rulemakings. Under those alternatives where standards would be
established by reference to their costs and benefits, these economic
values also affect the levels of the CAFE standards themselves. Some of
these variables have more important effects on the level of CAFE
standards and the benefits from requiring alternative increases in fuel
economy than do others, and the following discussion places more
emphasis on these inputs.
    In reviewing these variables and the agency's estimates of their
values for purposes of this proposed rule, NHTSA reconsidered comments
it had previously received on the NPRM for MYs 2012-16 CAFE standards
and to the NOI/Interim Joint TAR, and also reviewed newly available
literature. The agency elected to revise some of its economic
assumptions and parameter estimates for this rulemaking, while
retaining others. For the reader's reference, Table IV-7 below
summarizes the values used to calculate the economic benefits from each
alternative.
BILLING CODE 4910-59-P

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[GRAPHIC] [TIFF OMITTED] TP01DE11.176

BILLING CODE 4910-59-C
a. Costs of Fuel Economy-Improving Technologies
    Building on cost estimates developed for the MYs 2012-2016 CAFE and
GHG final rule and the 2010 TAR, the agencies incorporated new cost
estimates for the new technologies being considered and some of the
technologies carried over from the MYs 2012-2016 final rule and 2010
TAR. This joint work is reflected in Chapter 3 of the Joint TSD and in
Section II of this preamble, as summarized below. For more detailed
information on cost of fuel-saving technologies, please refer to
Chapter 3 of the Joint TSD and Chapter V of NHTSA's PRIA.
    The technology cost estimates used in this analysis are intended to
represent manufacturers' direct costs for high-volume production of
vehicles with these technologies. NHTSA explicitly accounts for the
cost reductions a manufacturer might realize through

learning achieved from experience in actually applying a technology,
which means that technologies become cheaper over the rulemaking time
frame; learning effects are described above and in Chapter 3 of the
draft joint TSD and Chapters V and VII of NHTSA's PRIA. NHTSA notes
that, in developing technology cost estimates, the agencies have made
every effort to hold constant aspects of vehicle performance and
utility typically valued by consumers, such as horsepower, carrying
capacity, drivability, durability, noise, vibration and harshness (NVH)
and towing and hauling capacity. For example, NHTSA includes in its
analysis technology cost estimates that are specific to performance
passenger cars (i.e., sports cars), as compared to nonperformance
passenger cars. NHTSA seeks comment on the extent to which commenters
believe that the agencies have been successful in holding constant
these elements of vehicle performance and utility in developing the
technology cost estimates. Additionally, the agency notes that the
technology costs included in this proposal take into account only those
associated with the initial build of the vehicle. Although comments
were received to the MYs 2012-2016 rulemaking that suggested there
could be additional maintenance required with some new technologies
(e.g., turbocharging, hybrids, etc.), and that additional maintenance
costs could occur as a result. The agency requests comments on this
topic and will undertake a more detailed review of these potential
costs for the final rule.
    Additionally, NHTSA recognizes that manufacturers' actual costs for
employing these technologies include additional outlays for
accompanying design or engineering changes to models that use them,
development and testing of prototype versions, recalibrating engine
operating parameters, and integrating the technology with other
attributes of the vehicle. Manufacturers' indirect costs for employing
these technologies also include expenses for product development and
integration, modifying assembly processes and training assembly workers
to install them, increased expenses for operation and maintaining
assembly lines, higher initial warranty costs for new technologies, any
added expenses for selling and distributing vehicles that use these
technologies, and manufacturer and dealer profit. These indirect costs
have been accounted for in this rulemaking through use of ICMs, which
have been revised for this rulemaking as discussed above, in Chapter 3
of the draft joint TSD, and in Chapters V and VII of NHTSA's PRIA.
b. Potential Opportunity Costs of Improved Fuel Economy
    An important concern is whether achieving the fuel economy
improvements required by the proposed CAFE standards will require
manufacturers to modify the performance, carrying capacity, safety, or
comfort of some vehicle models. To the extent that it does so, the
resulting sacrifice in the value of those models represents an
additional cost of achieving the required improvements in fuel economy.
(This possibility is addressed in detail in Section IV.G.6.) Although
exact dollar values that potential buyers attach to specific vehicle
attributes are difficult to infer, differences in vehicle purchase
prices and buyers' choices among competing models that feature varying
combinations of these characteristics clearly demonstrate that changes
in these attributes affect the utility and economic value they offer to
potential buyers.\639\
---------------------------------------------------------------------------

    \639\ See, e.g., Kleit A.N., 1990. ``The Effect of Annual
Changes in Automobile Fuel Economy Standards.'' Journal of
Regulatory Economics 2: 151-172 (Docket EPA-HQ-OAR-2009-0472-0015);
Berry, Steven, James Levinsohn, and Ariel Pakes, 1995. ``Automobile
Prices in Market Equilibrium,'' Econometrica 63(4): 841-940 (Docket
NHTSA-2009-0059-0031); McCarthy, Patrick S., 1996.
---------------------------------------------------------------------------

    NHTSA and EPA have approached this potential problem by developing
cost estimates for fuel economy-improving technologies that include any
additional manufacturing costs that would be necessary to maintain the
originally planned levels of performance, comfort, carrying capacity,
and safety of any light-duty vehicle model to which those technologies
are applied. In doing so, the agencies followed the precedent
established by the 2002 NAS Report, which estimated ``constant
performance and utility'' costs for fuel economy technologies. NHTSA
has followed this precedent in its efforts to refine the technology
costs it uses to analyze alternative passenger car and light truck CAFE
standards for MYs 2017-2025. Although the agency has reduced its
estimates of manufacturers' costs for most technologies for use in this
rulemaking, these revised estimates are still intended to represent
costs that would allow manufacturers to maintain the performance,
carrying capacity, and utility of vehicle models while improving their
fuel economy.
    While we believe that our cost estimates for fuel economy-improving
technologies include adequate provisions for accompanying costs that
are necessary to prevent any degradation in other vehicle attributes,
it is possible that they do not include adequate allowance to prevent
sacrifices in these attributes on all vehicle models. If this is the
case, the true economic costs of achieving higher fuel economy should
include the opportunity costs to vehicle owners of any accompanying
reductions vehicles' performance, carrying capacity, and utility, and
omitting these will cause the agency's estimated technology costs to
underestimate the true economic costs of improving fuel economy.
    It would be desirable to estimate explicitly the changes in vehicle
buyers' welfare from the combination of higher prices for new vehicle
models, increases in their fuel economy, and any accompanying changes
in other vehicle attributes. The net change in buyer's welfare that
results from the combination of these changes would provide a more
accurate estimate of the true economic costs for improving fuel
economy. The agency is in the process of developing a model of
potential vehicle buyers' decisions about whether to purchase a new car
or light truck and their choices from among the available models, which
will allow it to conduct such an analysis. This process is expected to
be completed for use in analyzing final CAFE standards for MY 2017-25;
in the meantime, Section IV.G.6 below includes a detailed analysis and
discussion of how omitting possible changes in vehicle attributes other
than their prices and fuel economy might affect its estimates of
benefits and costs resulting from the standards proposed in this NPRM.
c. The On-Road Fuel Economy ``Gap''
    Actual fuel economy levels achieved by light-duty vehicles in on-
road driving fall somewhat short of their levels measured under the
laboratory-like test conditions used by EPA to establish its published
fuel economy ratings for different models. In analyzing the fuel
savings from alternative CAFE standards, NHTSA has previously adjusted
the actual fuel economy performance of each light truck model downward
from its rated value to reflect the expected size of this on-road fuel
economy ``gap.'' On December 27, 2006, EPA adopted changes to its
regulations on fuel economy labeling, which were intended to bring
vehicles' rated fuel economy levels closer to their actual on-road fuel
economy levels.\640\
---------------------------------------------------------------------------

    \640\ 71 FR 77871 (Dec. 27, 2006).
---------------------------------------------------------------------------

    In its Final Rule, however, EPA estimated that actual on-road fuel

economy for light-duty vehicles averages approximately 20 percent lower
than published fuel economy levels, somewhat larger than the 15 percent
shortfall it had previously assumed. For example, if the overall EPA
fuel economy rating of a light truck is 20 mpg, EPA estimated that the
on-road fuel economy actually achieved by a typical driver of that
vehicle is expected to be only 80 percent of that figure, or 16 mpg
(20*.80). NHTSA employed EPA's revised estimate of this on-road fuel
economy gap in its analysis of the fuel savings resulting from
alternative CAFE standards evaluated in the MY 2011 final rule.
    In the course of developing its CAFE standards for MY 2012-16,
NHTSA conducted additional analysis of this issue. The agency used data
on the number of passenger cars and light trucks of each model year
that were registered for use during calendar years 2000 through 2006,
average rated fuel economy for passenger cars and light trucks produced
during each model year, and estimates of average miles driven per year
by cars and light trucks of different ages. These data were combined to
develop estimates of the average fuel economy that the U.S. passenger
vehicle fleet would have achieved from 2000 through 2006 if cars and
light trucks of each model year achieved the same fuel economy levels
in actual on-road driving as they did under test conditions when new.
    Table IV-8 compares NHTSA's estimates of fleet-wide average fuel
economy under test conditions for 2000 through 2006 to the Federal
Highway Administration's (FHWA) published estimates of actual on-road
fuel economy achieved by passenger cars and light trucks during each of
those years.\641\ As it shows, FHWA's estimates of actual fuel economy
for passenger cars ranged from 21-23 percent lower than NHTSA's
estimates of its fleet-wide average value under test conditions over
this period, and FHWA's estimates of actual fuel economy for light
trucks ranged from 16-18 percent lower than NHTSA's estimates of its
fleet-wide average value under test conditions. Thus, these results
appear to confirm that the 20 percent on-road fuel economy gap
represents a reasonable estimate for use in evaluating the fuel savings
likely to result from more stringent fuel economy and CO2
standards in MYs 2017-2025.
---------------------------------------------------------------------------

    \641\ Federal Highway Administration, Highway Statistics, 2000
through 2006 editions, Table VM-1; See http://www.fhwa.dot.gov/policy/ohpi/hss/hsspubs.cfm (last accessed March 1, 2010).

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[GRAPHIC] [TIFF OMITTED] TP01DE11.177

    The comparisons reported in this table must be interpreted with
some caution, however, because the estimates of annual car and truck
use used to develop these estimates are submitted to FHWA by individual
states, which use differing definitions of passenger cars and light
trucks. (For example, some states classify minivans as cars, while
others define them as light trucks.) At the same time, while total
gasoline consumption can be reasonably estimated from excise tax
receipts, separate estimates of gasoline consumption by cars and trucks
are not available. For these reasons, NHTSA has chosen not to rely on
its separate estimates of the on-road fuel economy gap for cars and
light trucks. However, the agency does believe that these results
confirm that the 20 percent on-road fuel economy discount represents a
reasonable estimate for use in evaluating the fuel savings likely to
result from CAFE standards for both cars and light trucks. NHTSA
employs this value for vehicles operating on liquid fuels (gasoline,
diesel, and gasoline/alcohol blends), and uses it to analyze the
impacts of proposed CAFE standards for model years 2017-25 on the use
of these fuels.
    In the recent TAR, EPA and NHTSA assumed that the overall energy
shortfall for the vehicles employing electric drivetrains, including
plug-in hybrid and battery-powered electric vehicles, is 30 percent.
This value was derived from the agencies' engineering judgment based on
the limited available information. During the stakeholder meetings
conducted prior to the technical assessment, confidential business
information (CBI) was supplied by several manufacturers which indicated
that electrically powered vehicles had greater variability in their on-
road energy consumption than vehicles powered by internal combustion
engines, although other manufacturers suggested that the on-road/
laboratory differential attributable to electric operation should
approach that of liquid fuel operation in the future. Second, data from
EPA's 2006 analysis of the ``five cycle'' fuel economy label as part of
the rulemaking discussed above supported a larger on-road shortfall for
vehicles with hybrid-electric drivetrains, partly because real-world
driving tends to have higher acceleration/deceleration rates than are
employed on the 2-cycle test. This

diminishes the fuel economy benefits of regenerative braking, which can
result in a higher test fuel economy for hybrids than is achieved under
normal on-road conditions.\642\ Finally, heavy accessory load,
extremely high or low temperatures, and aggressive driving have
deleterious impacts of unknown magnitudes on battery performance.
Consequently, the agencies judged that 30 percent was a reasonable
estimate for use in the TAR, and NHTSA believes that it continues to
represent the most reliable estimate for use in the current analysis.
---------------------------------------------------------------------------

    \642\ EPA, Fuel Economy Labeling of Motor Vehicles: Revisions To
Improve Calculation of Fuel Economy Estimates; Final Rule, 40 CFR
parts 86 and 600, 71 FR 77872, 77879 (Dec. 27, 2006). Available at
http://www.epa.gov/fedrgstr/EPA-AIR/2006/December/Day-27/a9749.pdf.
---------------------------------------------------------------------------

    One of the most significant factors responsible for the difference
between test and on-road fuel economy is the use of air conditioning.
While the air conditioner is turned off during the FTP and HFET tests,
drivers often use air conditioning under warm, humid conditions. The
air conditioning compressor can also be engaged during ``defrost''
operation of the heating system.\643\ In the MYs 2012-2016 rulemaking,
EPA estimated the impact of an air conditioning system at approximately
14.3 grams CO2/mile for an average vehicle without any of
the improved air conditioning technologies discussed in that
rulemaking. For a 27 mpg (330 g CO2/mile) vehicle, this
would account for is approximately 20 percent of the total estimated
on-road gap (or about 4 percent of total fuel consumption).
---------------------------------------------------------------------------

    \643\ EPA, Final Technical Support Document: Fuel Economy
Labeling of Motor Vehicle Revisions to Improve Calculation of Fuel
Economy Estimates, at 70. Office of Transportation and Air Quality
EPA420-R-06-017 December 2006, Chapter II, http://www.epa.gov/fueleconomy/420r06017.pdf.
---------------------------------------------------------------------------

    In the MY 2012-2016 rule, EPA estimated that 85 percent of MY 2016
vehicles would reduce their tailpipe CO2 emissions
attributable to air conditioner efficiency by 40 percent through the
use of advanced air conditioning technologies, and that incorporating
this change would reduce the average on-road gap by about 2
percent.\644\ However, air conditioning-related fuel consumption does
not decrease proportionally as engine efficiency improves, because the
engine load due attributable to air conditioner operation is
approximately constant across engine efficiency and technology. As a
consequence, air conditioning operation represents an increasing
percentage of vehicular fuel consumption as engine efficiency
increases.\645\ Because these two effects are expected approximately to
counterbalance each other, NHTSA has elected not to adjust its estimate
of the on-road gap for use in this proposal.
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    \644\ 4% of the on-road gap x 40% reduction in air conditioning
fuel consumption x 85% of the fleet = ~2%.
    \645\ As an example, the air conditioning load of 14.3 g/mile of
CO2 is a smaller percentage (4.3%) of 330 g/mile than 260
(5.4%).
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d. Fuel Prices and the Value of Saving Fuel
    Future fuel prices are the single most important input into the
economic analysis of the benefits of alternative CAFE standards because
they determine the value of future fuel savings, which account for
approximately 90% of total economic benefits from requiring higher fuel
economy. NHTSA relies on the most recent fuel price projections from
the U.S. Energy Information Administration's (EIA) Annual Energy
Outlook (AEO) 2011 Reference Case to estimate the economic value of
fuel savings projected to result from alternative CAFE standards for MY
2017-25. The AEO 2011 Reference Case forecasts of gasoline and diesel
fuel prices represents EIA's most up-to-date estimate of the most
likely course of future prices for petroleum products. EIA is widely
recognized as an impartial and authoritative source of analysis and
forecasts of U.S. energy production, consumption, and prices, and its
forecasts are widely relied upon by federal agencies for use in
regulatory analysis and for other purposes. Its forecasts are derived
using EIA's National Energy Modeling System (NEMS), which includes
detailed representations of supply pathways, sources of demand, and
their interaction to determine prices for different forms of energy.
    As compared to the gasoline prices used in NHTSA's Final Rule
establishing CAFE standards for MY 2012-2016 (which relied on forecasts
from AEO 2010), the AEO 2011 Reference Case fuel prices are slightly
higher through the year 2020, but slightly lower for most years
thereafter. Expressed in constant 2009 dollars, the AEO 2011 Reference
Case forecast of retail gasoline prices (which include federal, state,
and local taxes) during 2017 is $3.25 per gallon, rising gradually to
$3.71 by the year 2035. However, valuing fuel savings over the full
lifetimes of passenger cars and light trucks affected by the standards
proposed for MYs 2017-25 requires fuel price forecasts that extend
through 2060, approximately the last year during which a significant
number of MY 2025 vehicles will remain in service.\646\ To obtain fuel
price forecasts for the years 2036 through 2060, the agency assumes
that retail fuel prices will continue to increase after 2035 at the
average annual rate (0.7%) projected for 2017-2035 in the AEO 2011
Reference Case. This assumption results in a projected retail price of
gasoline that reaches $4.16 in 2050. Over the entire period from 2017-
2050, retail gasoline prices are projected to average $3.67, as Table
IV-7 reported previously.
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    \646\ The agency defines the maximum lifetime of vehicles as the
highest age at which more than 2 percent of those originally
produced during a model year remain in service. In the case of light
trucks, for example, this age has typically been 36 years for recent
model years.
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    The value of fuel savings resulting from improved fuel economy to
buyers of light-duty vehicles is determined by the retail price of
fuel, which includes Federal, State, and any local taxes imposed on
fuel sales. Because fuel taxes represent transfers of resources from
fuel buyers to government agencies, however, rather than real resources
that are consumed in the process of supplying or using fuel, NHTSA
deducts their value from retail fuel prices to determine the value of
fuel savings resulting from more stringent CAFE standards to the U.S.
economy.
    NHTSA follows the assumptions used by EIA in AEO 2011 that State
and local gasoline taxes will keep pace with inflation in nominal
terms, and thus remain constant when expressed in constant dollars. In
contrast, EIA assumes that Federal gasoline taxes will remain unchanged
in nominal terms, and thus decline throughout the forecast period when
expressed in constant dollars. These differing assumptions about the
likely future behavior of Federal and State/local fuel taxes are
consistent with recent historical experience, which reflects the fact
that Federal as well as most State motor fuel taxes are specified on a
cents-per-gallon rather than an ad valorem basis, and typically require
legislation to change. Subtracting fuel taxes from the retail prices
forecast in AEO 2011 results in projected values for saving gasoline of
$3.29 per gallon during 2017, rising to $3.48 per gallon by the year
2035, and to $3.65 by the year 2050. Over this entire period, pre-tax
gasoline prices are projected to average $3.32 per gallon.
    EIA also includes forecasts reflecting high and low global oil
prices in each year's complete AEO, which reflect uncertainties
regarding OPEC behavior as well as future levels of oil production and
demand. These alternative scenarios project retail gasoline prices that
range from a low of $2.30 to a high

of $4.85 per gallon during 2020, and from $2.12 to $5.36 per gallon
during 2035 (all figures in 2009 dollars). In conjunction with our
assumption that fuel taxes will remain constant in real or inflation-
adjusted terms over this period, these forecasts imply pre-tax values
of saving fuel ranging from $1.91 to $4.46 per gallon during 2020, and
from $1.77 to $5.01 per gallon in 2035 (again, all figures are in
constant 2009 dollars). In conducting the analysis of uncertainty in
benefits and costs from alternative CAFE standards required by OMB,
NHTSA evaluated the sensitivity of its benefits estimates to these
alternative forecasts of future fuel prices; detailed results and
discussion of this sensitivity analysis can be found in the agency's
PRIA. Generally, this analysis confirms that the primary economic
benefit resulting from the rule--the value of fuel savings--is
extremely sensitive to alternative forecasts of future fuel prices.
e. Consumer Valuation of Fuel Economy and Payback Period
    The agency uses slightly different assumptions about the length of
time over which potential vehicle buyers consider fuel savings from
higher fuel economy, and about how they discount those future fuel
savings, in different aspects of its analysis. For most purposes, the
agency assumes that buyers value fuel savings over the first five years
of a new vehicle's lifetime; the five-year figure represents
approximately the current average term of consumer loans to finance the
purchase of new vehicles.
    To simulate manufacturers' assessment of the net change in the
value of an individual vehicle model to prospective buyers from
improving its fuel economy, NHTSA discounts fuel savings over the first
five years of its lifetime using a 7 percent rate. The resulting value
is deducted from the technology costs that would be incurred by its
manufacturer to improve that model's fuel economy, in order to
determine the change in its value to potential buyers. Since this is
also the additional amount its manufacturer could expect to receive
when selling the vehicle after improving its fuel economy, this can
also be viewed as the ``effective cost'' of the improvement from its
manufacturers' perspective. The CAFE model uses these estimates of
effective costs to identify the sequence in which manufacturers are
likely to select individual models for improvements in fuel economy, as
well as to identify the most cost-effective technologies for doing so.
    The average of effective cost to its manufacturer for increasing
the fuel economy of a model also represents the change in its value
from the perspective of potential buyers. Under the assumption that
manufacturers change the selling price of each model by this amount,
its average value also represents the average change in its net or
effective price to would-be buyers. As part of our sensitivity case
analyzing the potential for manufacturers to over-comply with CAFE
standards--that is, to produce a lineup of vehicle models whose sales-
weighted average fuel economy exceeds that required by prevailing
standards--NHTSA used the extreme assumption that potential buyers
value fuel savings only during the first year they expect to own a new
vehicle.
    The agency notes that these varying assumptions about future time
horizons and discount rates for valuing fuel savings are used only to
analyze manufacturers' responses to requiring higher fuel economy and
buyers' behavior in response to manufacturers' compliance strategies.
When estimating the aggregate value to the U.S. economy of fuel savings
resulting from alternative increases in CAFE standards--or the
``social'' value of fuel savings--the agency includes fuel savings over
the entire expected lifetimes of vehicles that would be subject to
higher standards, rather than over the shorter periods we assume
manufacturers employ to represent the preferences of vehicle buyers, or
that buyers use to assess changes in the net price or new vehicles.
    Valuing fuel savings over vehicles' entire lifetimes recognizes the
savings in fuel costs that subsequent owners of vehicles will
experience from higher fuel economy, even if their initial purchasers
do not expect to recover the remaining value of fuel savings when they
re-sell those vehicles, or for other reasons do not value fuel savings
beyond the assumed five-year time horizon. The agency acknowledges that
it has not accounted for any effects of increased costs for financing,
insuring, or maintaining vehicles with higher fuel economy, over either
this limited payback period or the full lifetimes of vehicles.
    The procedure the agency uses for calculating lifetime fuel savings
is discussed in detail in the following section, while discussion about
the time horizon over which potential buyers may consider fuel savings
in their vehicle purchasing decisions is provided in more detail in
Section IV.G.6 below.
f. Vehicle Survival and Use Assumptions
    NHTSA's analysis of fuel savings and related benefits from adopting
more stringent fuel economy standards for MYs 2017-2025 passenger cars
and light trucks begins by estimating the resulting changes in fuel use
over the entire lifetimes of the affected vehicles. The change in total
fuel consumption by vehicles produced during each model year is
calculated as the difference between their total fuel use over their
lifetimes with a higher CAFE standard in effect, and their total
lifetime fuel consumption under a baseline in which CAFE standards
remained at their 2016 levels. The first step in estimating lifetime
fuel consumption by vehicles produced during a model year is to
calculate the number expected to remain in service during each year
following their production and sale.\647\ This is calculated by
multiplying the number of vehicles originally produced during a model
year by the proportion typically expected to remain in service at their
age during each later year, often referred to as a ``survival rate.''
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    \647\ Vehicles are defined to be of age 1 during the calendar
year corresponding to the model year in which they are produced;
thus for example, model year 2000 vehicles are considered to be of
age 1 during calendar year 2000, age 2 during calendar year 2001,
and to reach their maximum age of 26 years during calendar year
2025. NHTSA considers the maximum lifetime of vehicles to be the age
after which less than 2 percent of the vehicles originally produced
during a model year remain in service. Applying these conventions to
vehicle registration data indicates that passenger cars have a
maximum age of 26 years, while light trucks have a maximum lifetime
of 36 years. See Lu, S., NHTSA, Regulatory Analysis and Evaluation
Division, ``Vehicle Survivability and Travel Mileage Schedules,''
DOT HS 809 952, 8-11 (January 2006). Available at http://www-nrd.nhtsa.dot.gov/Pubs/809952.pdf (last accessed Sept. 26, 2011).
---------------------------------------------------------------------------

    As discussed in more detail in Section II.B.3 above and in Chapter
1 of the TSD, to estimate production volumes of passenger cars and
light trucks for individual manufacturers, NHTSA relied on a baseline
market forecast constructed by EPA staff beginning with MY 2008 CAFE
certification data. After constructing a MY 2008 baseline, EPA and
NHTSA used projected car and truck volumes for this period from Energy
Information Administration's (EIA's) Annual Energy Outlook (AEO) 2011
in the NPRM analysis.\648\ However,

Annual Energy Outlook forecasts only total car and light truck sales,
rather than sales at the manufacturer and model-specific level, which
the agencies require in order to estimate the effects new standards
will have on individual manufacturers.\649\
---------------------------------------------------------------------------

    \648\ Available at http://www.eia.gov/forecasts/aeo/index.cfm
(last accessed Sept. 26, 2011). NHTSA and EPA made the simplifying
assumption that projected sales of cars and light trucks during each
calendar year from 2012 through 2016 represented the likely
production volumes for the corresponding model year. The agency did
not attempt to establish the exact correspondence between projected
sales during individual calendar years and production volumes for
specific model years.
    \649\ Because AEO 2011's ``car'' and ``truck'' classes did not
reflect NHTSA's recent reclassification (in March 2009 for
enforcement beginning MY 2011) of many two wheel drive SUVs from the
non-passenger (i.e., light truck) fleet to the passenger car fleet,
EPA staff made adjustments to account for such vehicles in the
baseline.
---------------------------------------------------------------------------

    To estimate sales of individual car and light truck models produced
by each manufacturer, EPA purchased data from CSM Worldwide and used
its projections of the number of vehicles of each type (car or truck)
that will be produced and sold by manufacturers in model years 2011
through 2015.\650\ This provided year-by-year estimates of the
percentage of cars and trucks sold by each manufacturer, as well as the
sales percentages accounted for by each vehicle market segment. (The
distributions of car and truck sales by manufacturer and by market
segment for the 2016 model year and beyond were assumed to be the same
as CSM's forecast for the 2015 calendar year.) Normalizing these
percentages to the total car and light truck sales volumes projected
for 2017 through 2025 in AEO 2011 provided manufacturer-specific market
share and model-specific sales estimates for those model years. The
volumes were then scaled to AEO 2011 total volume for each year.
---------------------------------------------------------------------------

    \650\ EPA also considered other sources of similar information,
such as J.D. Powers, and concluded that CSM was better able to
provide forecasts at the requisite level of detail for most of the
model years of interest.
---------------------------------------------------------------------------

    To estimate the number of passenger cars and light trucks
originally produced during model years 2017 through 2025 that will
remain in use during subsequent years, the agency applied age-specific
survival rates for cars and light trucks to its forecasts of passenger
car and light truck sales for each of those model years. In 2008, NHTSA
updated its previous estimates of car and light truck survival rates
using the most current registration data for vehicles produced during
recent model years, in order to ensure that they reflected recent
increases in the durability and expected life spans of cars and light
trucks.\651\ However, the agency does not attempt to forecast changes
in those survival rates over the future.
---------------------------------------------------------------------------

    \651\ Lu, S., NHTSA, Regulatory Analysis and Evaluation
Division, ``Vehicle Survivability and Travel Mileage Schedules,''
DOT HS 809 952, 8-11 (January 2006). Available at http://www-nrd.nhtsa.dot.gov/Pubs/809952.pdf (last accessed Sept. 26, 2011).