become shallower as battery technology is expected to mature in MY 2033
and beyond. Applying learning curves to the battery pack DMC in
subsequent analysis years reduces costs such that battery pack costs
are believed to represent the manufacturing costs for any future pack,
regardless of cell chemistry, cell format, or production volume.
    Unlike the rest of the electrification technologies, however, the
SS12V micro hybrid system uses a shallower learning curve, as shown in
TSD Chapter <IP_ADDRESS>. This shallow curve reflects the maturity of the
technology; as we discuss in TSD Chapter 3.3.2, 50 percent of the MY
2020 fleet utilizes a SS12V micro hybrid system.
    TSD Chapter <IP_ADDRESS> includes more detail about the process to
develop battery costs for this analysis. In addition, all BatPaC-
generated direct manufacturing costs for all technology keys can be
found in the CAFE Model's Battery Costs file, and the Argonne BatPaC
Assumptions file includes the assumptions used to generate the costs,
pack costs, pack mass, cell capacity, $/kW at the pack level, and W/kg
at the pack level for all vehicle classes.
    A range of parameters can ultimately influence battery pack
manufacturing costs, including other vehicle improvements (e.g., mass
reduction technology, aerodynamic improvements, or tire rolling
resistance improvements all affect the size and energy of a battery
required to propel a vehicle where all else is equal), and the
availability of materials required to manufacture the
battery.369 370 Or, if manufacturers adopt more
electrification technology than projected in this analysis, increases
in battery pack production volume will likely lower actual battery pack
costs.
---------------------------------------------------------------------------

    \369\ The cost of raw material also has a meaningful influence
on the future cost of the battery pack. As the production volume
goes up, the demand for battery critical raw materials also goes up,
which has an offsetting impact on the efficiency gains achieved
through economies of scale, improved plant efficiency, and advanced
battery cell chemistries, at least while supply is readjusting to
demand. We do not consider future battery raw material price
fluctuations for this analysis, however that may be an area for
further exploration in future analyses.
    \370\ See, e.g., Jacky Wong, EV Batteries: The Next Victim of
High Commodity Prices?, The Wall Street Journal (July 22, 2021),
https://www.wsj.com/articles/ev-batteries-the-next-victim-of-high-commodity-prices-11626950276.
---------------------------------------------------------------------------

    In the NPRM, we compared our battery pack costs in future years to
battery pack costs from a non-exhaustive list of other sources that may
or may not account for some of these additional parameters, including
varying potential future battery chemistry and learning rates. As
discussed in TSD Chapter <IP_ADDRESS>.4, our battery pack costs in 2025 and
2030 fell fairly well in the middle of other sources' cost projections,
with Bloomberg New Energy Finance (BNEF) projections presenting the
highest year-over-year cost reductions, and one scenario in MIT's
Insights into Future Mobility report providing an upper bound of
potential future costs of the studies surveyed to create this
comparison.371 372 ICCT presented a similar comparison of
costs from several sources in its 2019 working paper and predicted
battery pack costs in 2025 and 2030 would drop to approximately $104/
kWh and $72/kWh, respectively, which put their projections slightly
higher than BNEF's 2019 projections.\373\ BNEF's 2020 Electric Vehicle
Outlook projected average pack cost to fall below $100/kWh by 2024,
while the 2021 NAS Report projected pack costs to reach $90-115/kWh by
2025.374 375 Since the NPRM, BNEF released its 2021 Electric
Vehicle Outlook, which estimated average pack prices in 2021 at $132/
kwh.\376\ In addition, Bloomberg weighed in on recent supply chain
impacts on battery materials availability, which is discussed in more
detail below.
---------------------------------------------------------------------------

    \371\ See Logan Goldie-Scot, A Behind the Scenes Take on
Lithium-ion Battery Prices, Bloomberg New Energy Finance (March 5,
2019), https://about.bnef.com/blog/behind-scenes-take-lithium-ion-battery-prices/.
    \372\ MIT Energy Initiative. 2019. Insights into Future
Mobility. Cambridge, MA: MIT Energy Initiative. Available at http://energy.mit.edu/insightsintofuturemobility.
    \373\ Nic Lutsey and Michael Nicholas, ``Update on electric
vehicle costs in the United States through 2030'', ICCT (April 2,
2019), available at https://theicct.org/publications/update-US-2030-electric-vehicle-cost.
    \374\ Bloomberg New Energy Finance (BNEF), ``Electric Vehicle
Outlook 2020,'' https://about.bnef.com/electric-vehicle-outlook/,
last accessed July 29, 2021.
    \375\ 2021 NAS Report, at 114. The 2021 NAS Report assumed a 7
percent cost reduction per year from 2018 through 2030.
    \376\ BloombergNEF. ``Battery Pack Prices Fall to an Average of
$132/kWh, But Rising Commodity Prices Start to Bite.'' November 30,
2021. https://about.bnef.com/blog/battery-pack-prices-fall-to-an-average-of-132-kwh-but-rising-commodity-prices-start-to-bite/#_ftn1.
(Last accessed: January 10, 2022)
---------------------------------------------------------------------------

    We concluded in the NPRM that our projected costs seemed to fall
between several projections, giving confidence that the costs used in
the analysis could reasonably represent future battery pack costs
across the industry during the rulemaking time frame. We emphasized
that battery technology is currently under intensive development, and
that characteristics such as cost, and capability are rapidly changing.
These advances are reflected in recent aggressive projections, like
those from ICCT, BNEF, and the 2021 NAS Report.
    We sought comment on several elements of the battery modeling
analysis in the NPRM, including on battery direct manufacturing costs,
or DMCs (and inputs and assumptions

used in BatPaC to estimate those costs), battery learning curves, and
other battery-related materials. More specifically, we first sought
comments on DMC assumptions, including comments supported by data
elements on different assumptions for battery chemistry, plant
manufacturing volume, or plant efficiency in MY 2020.\377\ To align
with our guiding principle that each technology model employed in the
analysis be representative of a wide range of specific technology
applications used in the industry, we requested that commenters explain
how these assumptions reasonably represent applications across the
industry in MY 2020.\378\ This is important to ensure that the CAFE
Model's simulation of manufacturer compliance pathways results in
impacts that we would reasonably expect to see in the real world. In
addition, we sought comment on the scaling used to generate direct
manufacturing costs for BEV400 and BEV500 technologies; in particular,
we were interested in any additional data or information on the
relationship between cost and weight for heavier battery packs used for
these higher-range BEV applications, particularly in light truck
vehicle segments.
---------------------------------------------------------------------------

    \377\ Note that stakeholders had commented on the 2020 final
rule that batteries using NMC811 chemistry had either recently come
into the market or was imminently coming into the market, and
therefore DOT should have selected NMC811 as the appropriate
chemistry for modeling battery pack costs. Similar to the other
technologies considered in this analysis, DOT endeavors to use
technology that is a reasonable representation of what the industry
could achieve in the model year or years under consideration, in
this case the base DMC year of 2020, as discussed above. At the time
of this current analysis, the referenced A2Mac1 teardown reports and
other reports provided the best available information about the
range of battery chemistry actually employed in the industry. At the
time of writing for this final rule, DOT still has not found
examples of NMC811 in commercial application across the industry in
a way that DOT believes selecting NMC811 would have represented
industry average performance in MY 2020. As discussed in TSD Chapter
<IP_ADDRESS>.4, DOT did analyze the potential future cost of NMC811 in
the composite learning curve generated to ensure the battery
learning curve projections are reasonable.
    \378\ Again, some vehicle manufacturer's systems may perform
better and cost less than our modeled systems and some may perform
worse and cost more. However, employing this approach will ensure
that, on balance, the analysis captures a reasonable level of costs
and benefits that would result from any manufacturer applying the
technology.
---------------------------------------------------------------------------

    We also sought comment on the learning rates applied to battery
pack costs and on battery pack costs in future years. We recognized
that any battery pack cost projections for future years from our
analysis or external analyses will involve assumptions that may or may
not come to pass and stated that it would be most helpful if commenters
thoroughly explained the basis for any recommended learning rates,
including references to publicly available data or models (and if such
models are peer reviewed) where appropriate. We also noted that it
would be helpful for commenters to note where external analyses may or
may not take into account certain parameters in their battery pack cost
projections, and whether we should attempt to incorporate those
parameters in our analysis. For example, as discussed above, our
analysis does not consider long-term trends in raw material prices;
however, the price of raw materials may put a lower bound on NMC-based
battery prices.\379\
---------------------------------------------------------------------------

    \379\ See, e.g., MIT Energy Initiative. 2019. Insights into
Future Mobility. Cambridge, MA: MIT Energy Initiative. Available at
http://energy.mit.edu/insightsintofuturemobility, at pp. 78-79.
---------------------------------------------------------------------------

    We also stated that it would also be helpful if commenters
explained how learning rates or future cost projections could represent
the state of battery technology across the industry. Like other
technologies considered in this analysis, some battery and vehicle
manufacturers have more experience manufacturing electric vehicle
battery packs, and some have less, meaning that different manufacturers
will be at different places along the learning curve in future years.
We also stated that comments should specify whether their referenced
costs, either for MY 2020 or for future years, are for the battery cell
or the battery pack. We requested the information to ensure our
learning rates encompass these diverse parameters and to ensure that
the analysis best predicts the costs and benefits associated with
standards.
    Tesla commented that the battery pack costs we projected in the
SAFE rule were too high, citing lower estimates published in the UBS-
sponsored Volkswagen ID 3 teardown report, among other studies.\380\
Tesla also commented that we unnecessarily constrained the analysis by
assuming that the drivetrain and other components are unique to each
vehicle and not shared by another vehicle.\381\
---------------------------------------------------------------------------

    \380\ Tesla, at p. 9; DNV-GL, Tesla's Battery Day and the Energy
Transition (Oct. 26, 2020); BNEF, Electric Vehicle Outlook 2021
(June 9, 2021).; BNEF, Hitting the Inflection Point: Electric
Vehicle Price Parity and Phasing Out Combustion Vehicle Sales in
Europe (May 5, 2021); 2021 NAS Report; UBS, EVs Shifting into
Overdrive: VW ID.3 teardown--How will electric cars re-shape the
auto industry? (March 2, 2021).
    \381\ Tesla, at p. 10.
---------------------------------------------------------------------------

    To be clear, the battery pack DMCs used in our 2021 proposal and
this final rule are different than the battery pack DMCs used in the
SAFE rule that Tesla refers to in their comments. While our battery
pack DMCs have decreased since the 2020 final rule, our projected costs
are still higher than the sources that Tesla identifies. In the NPRM,
we provided a detailed explanation of how we developed those costs
using the BatPaC model and the specific inputs and assumptions used to
do so. We explained that we also expected those costs to represent the
range of costs across the industry. We acknowledged that each
manufacturer has different strategies associated with each vehicle line
based on several factors such as performance, costs, technology class,
utility among others, and this affects manufacturers strategy on
sourcing only certain components of battery pack or the complete
battery pack. We acknowledge that the cost of the battery pack as
measured in $/kWh can vary for each manufacturer with different form,
fit, and function requirements.\382\ BatPaC's inputs and assumptions,
including those developed specifically to support this rule,\383\ are
based on various and extended teardown reports available to the public
for predominant batteries that use robust and safe battery
chemistries.\384\ We understand that some mass market and premium
luxury BEVs have already achieved $/kWh values that are lower than our
projected costs, however others have not. To investigate the
sensitivity of our analysis to this cost we performed additional
analyses considering a 20 percent reduction in battery direct
manufacturing costs. And as discussed further below, this additional
cost reduction had a minimal impact on the overall vehicle cost and
increased electrification technology penetration. Therefore, we believe
the cost estimates from the BatPaC model represent a reasonable average
across all manufacturers for all vehicle technology classes.
---------------------------------------------------------------------------

    \382\ Form, fit, and function is the identification and
description of characteristics of a part or assembly. Each defines a
specific aspect of the part to help engineers match parts to needs.
    \383\ See Autonomie Model Documentation.
    \384\ Ahmed, S., Nelson, P., Kubal, J., Liu, Z., Knehr, K. Dees,
D., ``Estimated cost of EV Batteries.'' Argonne. August 12, 2021.
https://www.anl.gov/cse/batpac-model-software. Last accessed January
20, 2022.
---------------------------------------------------------------------------

    In contrast, the Auto Innovators submitted extensive comments on
our assumptions that the costs of battery electric vehicles will
continue to decline because of decreases in costs to produce battery
packs and other non-battery electrification components.\385\ Auto
Innovators stated that ``the traditional method of accounting for
possible future changes in battery-pack

costs is to apply a learning curve in future years based on production
volume, and then make a somewhat arbitrary assumption about when the
rate of decline decelerates or stops (technological maturity).'' Auto
Innovators identified that we characterized our learning curve as a
proxy for changes in battery chemistry, changes in energy density,
further gains in plant efficiency, and additional economies of scale in
production due to higher production volumes, but stated that we and NAS
do not ``confront the real possibility that counteracting, unanalyzed
factors could work to restrain the future decline in battery-pack
costs.'' \386\
---------------------------------------------------------------------------

    \385\ Auto Innovators, at pp. 94-121.
    \386\ Id., at pp. 94-95.
---------------------------------------------------------------------------

    Auto Innovators and also the Alliance for Vehicle Efficiency (AVE)
requested that we consider potential impacts to battery raw materials
costs in the analysis.\387\ Auto Innovators provided a lengthy
qualitative survey of the state of raw materials extraction issues,
including their perspective on political and environmental obstacles to
further supply development. Auto Innovators also provided estimates of
battery materials costs that assumed a doubling of raw materials prices
and stated that ``a pre-2032 doubling of raw material prices could
substantially erode the `learning-curve' cost reductions assumed in the
RIAs.'' Auto Innovators stated that the battery sensitivity cases
presented in the PRIA are not large enough to account for simultaneous
increases in several raw materials prices, and that ``there is no basis
for believing that raw material prices will decline for a sustained
period prior to 2032.'' Accordingly, Auto Innovators stated that much
more careful analysis of raw material prices is necessary in the final
RIAs.
---------------------------------------------------------------------------

    \387\ AVE, NHTSA-2021-0053-1488, at pp. 6-7.
---------------------------------------------------------------------------

    With respect to analytical tools available to perform such an
analysis, Auto Innovators stated that ``less than a handful of the
dozens of published battery-forecasting models include any formal
analysis of global trends in raw material prices'' and stated that
``none of the published battery-forecasting models have accounted for
the surge in material price experienced in 2021.'' \388\ Auto
Innovators stated that ``BatPaC does not include a formal global model
of the market for each raw material used in battery packs,'' and
instead provides a best estimate of raw materials prices at the time of
version release.\389\ Auto Innovators stated that the version of BatPaC
we used did not account for the 2021 surge in raw material prices. Auto
Innovators stated that the MIT's Insights into Future Mobility report
took an important step to forecasting battery pack costs by using a
two-stage model, one for the cost of materials and the second for the
costs to manufacture the battery pack.\390\ However, Auto Innovators
stated that we erroneously characterized MIT's estimate as an ``upper
bound'' of battery pack costs, while the report actually provides best
estimates based on different scenarios.
---------------------------------------------------------------------------

    \388\ Auto Innovators, at pp. 97-98.
    \389\ Id., at pp. 119-121.
    \390\ Insights into Future Mobility, MIT Energy Initiative
(2019), Cambridge, MA: MIT Energy Initiative, https://energy.mit.edu/research/mobilityofthefuture/ at p. 76. Accessed
January 19, 2022.
---------------------------------------------------------------------------

    Auto Innovators made three explicit requests in regards to future
battery materials costs and chemistry impacts; first, Auto Innovators
stated that we should work with National Laboratories, DOE, and others
to produce sensitivity cases for raw and processed material costs,
material efficiency in battery construction, and other considerations;
next, Auto Innovators stated that we should remove changes in battery
chemistry from the near-term learning factor and analyze it separately
and explicitly in our RIA; and finally, Auto Innovators stated that
``instead of choosing one battery chemistry as representative of the
entire industry, as the [a]gencies do with the Argonne battery model,
the [a]gencies should forecast the penetration of different battery
chemistries in the fleet from 2021 to 2032 and estimate applicable
costs for each of them.''
    As a reminder, the learning rate that we used in the NPRM and this
final rule, carried forward from work done for the 2018 NPRM, is based
on an assessment of cost reductions due to production volume increases.
As we described in the TSD, we identified the change in cost for the
estimated changes in production volumes linked to model years and used
this rate to develop the learning curves used out to MY 2032, which
resulted in an approximately 4.5 percent year over year cost reduction.
For MYs 2033 to 2050, we scaled down the learning rate in steps based
on literature values and market research.
    The parametric analysis presented in the NPRM TSD was meant to
confirm that looking at any one potential factor that could have an
impact on the battery pack direct manufacturing costs would not have
significantly changed this original near-term (i.e., through MY 2032)
4.5 percent production-volume-based learning rate. The parametric
analysis showed that considering two factors by themselves--increasing
production volume and improving manufacturing plant efficiency--would
result in a slightly shallower learning curve (3.26 and 3.5 percent
near-term, year-over-year reductions in cost), while changing battery
chemistry by itself would result in a steeper learning curve (5.15
percent near-term, year-over-year cost reductions). Constructing a
composite learning curve to consider these three factors in tandem,
assuming that the predominant battery chemistry will change over the
course of this decade, and also that battery manufacturing plants will
become better at producing battery cells--two widely accepted
assumptions--confirmed that our original learning curve based on year-
over-year production volume increases could reasonably encompass these
changes.\391\ Furthermore, while Auto Innovators asserted that our
production-based learning curve could miss several important factors,
as discussed in Section III.C.6 above and in recent literature,\392\ a
production-volume-based learning curve is an accepted and reasonable
method for projecting future costs.
---------------------------------------------------------------------------

    \391\ See, e.g., MIT Insights into Future Mobility Report, at 77
(``A clear trend within the EV LIB industry is to increase nickel
content to boost energy density (for increased driving range) while
reducing the amount of expensive cobalt required.'').
    \392\ Lukas Mauler, Fabian Duffner, Wolfgang G Zeier, Jens
Leker, ``Battery Cost Forecasting: A Review of Methods and Results
with an Outlook to 2050,'' Energy and Environmental Science, 14
(2021) at p. 4724.
---------------------------------------------------------------------------

    Regarding Auto Innovators' extensive comments about the impact of
materials availability on battery costs, we are aware that the outlook
for battery materials has remained uncertain since we released the
NPRM. At this time, studies and organizations have provided projections
about the impact of battery materials price increases due to supply
chain factors and the consensus seems to be that the overall impact on
prices will be minimal for the predominant battery chemistries.\393\
Our estimated future battery costs are fairly conservative compared to
leading analysis firms, even accounting for materials price impacts
since the

NPRM.394 395 This makes us confident that our projected
battery costs, presented in this final rule, still fall within the
scope of reasonable projections for the near-term model years covered
by this analysis.
---------------------------------------------------------------------------

    \393\ Lukas Mauler, Fabian Duffner, Wolfgang G Zeier, Jens
Leker, ``Battery Cost Forecasting: A Review of Methods and Results
with an Outlook to 2050,'' Energy and Environmental Science, 14
(2021) at p. 4734 (``Every single study that provides time-based
projections expects LIB cost to fall, even if increasing raw and
battery material prices are taken into account.''); Henze, V.,
``Battery Pack Prices Fall to an Average of $132/kWh, But Rising
Commodity Prices Start to Bite''. BloombergNEF. November 30, 2021.
https://about.bnef.com/blog/battery-pack-prices-fall-to-an-average-of-132-kwh-but-rising-commodity-prices-start-to-bite/. Last accessed
January 23, 2022.
    \394\ See NPRM TSD at 296, Table 3-86--Battery Cost Estimates
from Other Sources.
    \395\ Henze, V., ``Battery Pack Prices Fall to an Average of
$132/kWh, But Rising Commodity Prices Start to Bite''. BloombergNEF.
November 30, 2021. https://about.bnef.com/blog/battery-pack-prices-fall-to-an-average-of-132-kwh-but-rising-commodity-prices-start-to-bite/. Last accessed January 23, 2022.
---------------------------------------------------------------------------

    Nonetheless, we do appreciate Auto Innovators' data and analysis
submitted on raw materials cost impacts on battery pack costs. We also
appreciate the enormity of the task of integrating forecasts of global
trends in raw materials prices in our analysis, given that only a
minority of the dozens of published battery-forecasting models include
any formal analysis of global trends in raw materials prices and none
of the published forecasting models have accounted for the increase in
material price experienced in 2021. MIT's two-stage model, and
multidimensional mathematical models are more refined than single
dimensional models due to the use of numerous parameters. However, this
comes at the expense of needing to obtain high quality and accurate
data for these parameters, potentially at the cost of reduced
transparency. For example, MIT's two-stage model requires data from
mining companies, materials producers, cell producers, and battery pack
producers.\396\ However, detailed data on these specifics are not
readily publicly available.\397\ \398\ \399\
---------------------------------------------------------------------------

    \396\ Insights into Future Mobility, MIT Energy Initiative
(2019), Cambridge, MA: MIT Energy Initiative, https://energy.mit.edu/research/mobilityofthefuture/ at p. 77. Accessed
January 19, 2022.
    \397\ S. Matteson and E. Williams, Learning dependent subsidies
for lithium-ion electric vehicle batteries, Technol. Forecast. Soc.
Change, 2015, 92, 322-331.
    \398\ B. Nykvist, F. Sprei and M. Nilsson, Assessing the
progress toward lower priced long range battery electric vehicles,
Energy Policy, 2019, 124, 144-155.
    \399\ Lukas Mauler, Fabian Duffner, Wolfgang G Zeier, Jens
Leker, ``Battery Cost Forecasting: A Review of Methods and Results
with an Outlook to 2050,'' Energy and Environmental Science, 14
(2021) at p. 4715 (``However, details on company-specific prices,
costs and profit margins are not publicly available and differences
are difficult to assess.'').
---------------------------------------------------------------------------

    Developing a multi-stage model that can perform the calculations we
need for the number of large-scale simulations required by our
analysis, with data and assumptions that are transparent and can be
made publicly available, would be a difficult task. As discussed above,
BatPaC is a publicly available model and the inputs and assumptions
used to develop and populate BatPaC are publicly available. More
specifically, we included detailed data from teardown reports that we
used to generate the battery pack inputs for this analysis in the TSD
and Argonne Model Documentation. The battery pack designs and cell
chemistry that we modeled in BatPaC represented the most common battery
pack parameters in the market in MY 2020, our base year for calculating
direct manufacturing costs. This approach reflects the same approach we
use across our analysis; we do not currently model, for example, the
penetration rate of Toyota's HCR engine separately from Mazda's HCR
engine. Again, modeling an industry-average system will ensure that, on
balance, the analysis captures a reasonable level of costs and benefits
that would result from any manufacturer applying the technology. In
addition, while Auto Innovators presents important points about the
uncertainty regarding the predominant battery chemistry beyond MY 2027,
the battery chemistries that we analyzed--NMC622 and NMC811--are still
expected to be the dominant chemistries in this rulemaking timeframe.
The sensitivity analyses presented in the TSD accompanying the NPRM and
this final rule show that analyzing both chemistries separately results
in only a small difference in cost between the two options. We see only
a small difference in costs because we consider a narrow range of
battery pack power and energy sizes in the respective vehicle
technology classes.
    At this time, we believe that our battery pack costs in this final
rule still could reasonably represent costs to the industry during the
model years under consideration taking into account the factors
mentioned by Auto Innovators. In addition, as discussed further below,
our sensitivity cases show that BEV prices remain within a fairly
narrow range in the rulemaking timeframe considering potentially higher
direct manufacturing costs or shallower learning rates.
    We will continue to investigate further refinements to input data
and models that we use to assess battery costs as the input data and
models continue to develop. We understand that battery technologies and
manufacturing processes are undergoing significant development and we
will continue to monitor and evaluate battery cost and performance, and
how to reflect those trends in our modeling.
    For future actions, we would welcome any additional information on
the impact of raw materials prices on battery pack costs, including
information on a CBI or public basis on the impact of long-term supply
contracts on battery costs.\400\ In particular, we would be interested
in more information on whether manufacturers that had contracted for
battery packs prior to the 2021 materials supply chain disruptions were
insulated from materials cost increases and if there is a contractual
or other mechanism within the vehicle manufacturer's control through
which vehicle manufacturers could insulate themselves from such
disruptions moving forward.\401\
---------------------------------------------------------------------------

    \400\ C. Xu, et al., Future material demand for automotive
lithium-based batteries, Commun. Mater., 2020, 1, 99.; H. Hao, et
al., Impact of transport electrification on critical metal
sustainability with a focus on the heavy-duty segment, Nat. Commun.,
2019, 10, 5398.; Reuters. ``Stellantis, LG Energy Solution to form
battery JV for North America.'' Automotive News. October 18, 2021.
https://www.autonews.com/manufacturing/stellantis-lg-energy-solution-form-battery-jv-north-america. Last accessed 01/20/2022.;
``Daimler, Stellantis enter agreement with battery maker Factorial
Energy.'' Automotive News. November 30, 2021. https://www.autonews.com/suppliers/why-daimler-stellantis-are-investing-battery-maker. Last accessed January 20, 2022.; ``FORD COMMITS TO
MANUFACTURING BATTERIES, TO FORM NEW JOINT VENTURE WITH SK
INNOVATION TO SCALE NA BATTERY DELIVERIES.' Ford Media Center. May
20, 2021. https://media.ford.com/content/fordmedia/fna/us/en/news/2021/05/20/ford-commits-to-manufacturing-batteries.html. Last
accessed January 20, 2022.; ``Toyota Selects North Carolina for New
U.S. Automotive Battery Plant.'' Toyota Newsroom. December 7, 2021.
https://global.toyota/en/newsroom/corporate/36418723.html. Last
accessed January 20, 2022.
    \401\ See, e.g., Lukas Mauler, Fabian Duffner, Wolfgang G Zeier,
Jens Leker, ``Battery Cost Forecasting: A Review of Methods and
Results with an Outlook to 2050,'' Energy and Environmental Science,
14 (2021) at p. 4724; (``In the battery industry-prices are further
influenced by strategic pricing, long-term contracts and rebates to
utilize excess production capacity.'').
---------------------------------------------------------------------------

    As in any large-scale analysis, uncertainties exist. Recognizing
that there could be additional factors that constrain battery learning
rates, as Auto Innovators suggests, we performed four sensitivity
studies around battery pack costs that are described in FRIA Chapter
<IP_ADDRESS>. The sensitivity studies examined the impacts of increasing and
decreasing the direct cost of batteries and battery learning costs by
20 percent from central analysis levels, based on our survey of
external analyses' battery pack cost projections that fell generally
within 20 percent of our central analysis costs. The
average difference in vehicle cost between the reference case and four
battery sensitivity cases ranged from -$52 to $128. This means that,
even accounting for potential unanalyzed factors related to battery
prices, we expect battery electric vehicle prices to remain within a
fairly narrow range in the rulemaking timeframe. These sensitivity
outcomes are similar

to those we showed in the NPRM sensitivity analysis. Although Auto
Innovators showed how an increase in individual raw material cost could
impact the final cost, we believe that at the total pack level the 20
percent high sensitivity case encompasses these situations in the
rulemaking time frame. Again, these results, in addition to the
consensus in literature regarding the impact of rising materials prices
on future costs described above, make us comfortable that our approach
to estimating battery costs is a reasonable approach for this final
rule analysis.
    After pointing out the BatPaC model's limitations regarding future
potential increases in materials costs, Auto Innovators commented that
we should use BatPaC to estimate battery pack costs for BEV400 and
BEV500 technologies instead of scaling up BEV300 battery pack
costs.\402\ Beyond the request to do so, we received no updated real-
world data on the cost and weight of battery packs used in 400- and
500-mile range electric vehicles. As discussed above, and as originally
stated in the NPRM, initial values from BatPaC could not be validated
by real-world data, leading us to continue using the scaled values for
the final rule.
---------------------------------------------------------------------------

    \402\ Auto Innovators, at p. 119.
---------------------------------------------------------------------------

    Auto Innovators identified other costs related to electric vehicles
(EVs) that they stated our analysis does not consider; specifically,
they stated that our battery-price estimates are industry averages that
do not exclude supply chains that fail environmental, social, and
governance (ESG) tests. Auto Innovators stated that ``for the major
global automakers that operate in the [U.S.] auto market, the RIAs
should not assume that low-cost suppliers with poor ESG profiles can be
utilized in EV supply chains.'' Auto Innovators also identified the
shift from recycling engines and transmissions to recycling EV
batteries, as well as the price of electricity to produce EV batteries,
as costs that we do not currently account for. In addition, Auto
Innovators stated that the BEVs and PHEVs are a new technology type for
many drivers and, as a result, drivers may incur some costs and
inconveniences that we should consider as part of our analysis.\403\
They provided three examples of costs to the user beyond the purchase
price: (1) Costs of charging stations for BEVs and PHEVs; (2) costs to
the user of a vehicle that has a shorter driving range than the typical
conventional IC engine and that requires a long time to charge, and (3)
the time spent charging.
---------------------------------------------------------------------------

    \403\ Id., at pp. 119-121.
---------------------------------------------------------------------------

    We applaud Auto Innovators members for including serious ESG
considerations in their planning for developing battery supply chains.
However, like the issues surrounding raw materials impacts discussed
above, we currently do not have a specific mechanism to account for the
cost of supply chains that pass basic ESG tests, as Auto Innovators
suggests. To the extent that Auto Innovators members have already
entered into contracts with battery suppliers and have included ESG
terms in those contracts, and have data or other information on how
that increases the costs for EV production over and above an industry
average that we would project quantitatively, we welcome that
information for future analysis. We will continue to research these
factors and consider whether to include them in the cost-benefit
analysis. We support Auto Innovators and any individual component or
vehicle manufacturer providing the agency with supporting material for
these specific topics.
    As a reminder, our analysis considers technology costs that vehicle
manufacturers ultimately pass to the buyer separately from the user
costs for a technology, like fueling from either gasoline or
electricity. We consider many externalities that accrue cost for the
consumer in the analysis, and these are discussed in Section III.E. We
specifically identified a cost to the user for time spent charging an
EV, which is discussed further in that section. However, regardless of
where we account for those costs in the analysis, we believe those
costs would be minimal in the timeframe of this rulemaking considering
the standard-setting projections of EV and PHEV penetration rates,
which are discussed further in FRIA Chapter 6.3.1. That said, for
future rules we appreciate any new data Auto Innovators and other
stakeholders can provide to develop more precise electric vehicle user
costs.
    Next, ICCT commented that we ``erroneously inflated battery costs
by applying the retail price equivalent (RPE) markup to base costs that
already include indirect costs.'' \404\ We disagree. The indirect costs
represented in BatPaC output are those that apply to the battery
supplier, and do not represent the indirect costs experienced by the
OEM who purchases the battery and integrates it into the vehicle. NHTSA
has always considered RPE markup to be applicable to purchased items.
---------------------------------------------------------------------------

    \404\ ICCT, at p. 8.
---------------------------------------------------------------------------

    We also believe that the warranty costs are appropriately marked up
with the BatPaC outputs. The RPE markup factor is based on an
examination of historical financial data contained in 10-K reports
filed by manufacturers with the Securities and Exchange Commission. It
represents the ratio between the retail price of motor vehicles and the
direct costs of all activities that manufacturers engage in, including
the design, development, manufacturing, assembly, and sales of new
vehicles, refreshed vehicle designs, and modifications to meet safety
or fuel economy standards. An RPE of 1.5 does not imply that
manufacturers automatically mark up each vehicle by exactly 50 percent.
Rather, it means that, over time, the competitive marketplace has
resulted in pricing structures that average out to this relationship
across the entire industry. Prices for any individual model may be
marked up at a higher or lower rate depending on market demand. The
consumer who buys a popular vehicle may, in effect, subsidize the
installation of a new technology in a less marketable vehicle. But, on
average, over time and across the vehicle fleet, the retail price paid
by consumers has risen by about $1.50 for each dollar of direct costs
incurred by manufacturer.
    The direct costs associated with any specific technology will
change over time as some combination of learning and resource price
changes occurs. Resource costs, such as the price of steel, can
fluctuate over time and can experience real long-term trends in either
direction, depending on supply and demand. However, the normal learning
process generally reduces direct production costs as manufacturers
refine production techniques and seek out less costly parts and
materials for increasing production volumes. By contrast, this learning
process does not generally influence indirect costs. To be consistent
with the basis for the RPE multiplier, we apply learning to direct
costs, and then mark up the resulting learned direct costs using the
RPE multiplier.
    We consulted Argonne and the BatPaC manual and as shown in the
BatPaC documentation, the final cost provided by the BatPaC model
includes two-part variable costs (what we consider direct costs) and
fixed expenses (what we consider indirect costs). Table 8.7 in the
BatPaC Model Documentation shows the breakdown of the costs and the
approximate percentage of each cost.
    These costs combine to provide the overall cost of the battery pack
from the supplier to the OEM. The cost of the battery pack from the
supplier to the OEM is considered a direct cost to the OEM, like any
other part that an OEM

acquires from other suppliers. In turn, while using the battery pack in
the finished vehicle, the OEM will incur indirect costs including
research and development (R&D), general sales and administrative costs
(GSA), as well as warranty and profit. Thus, the indirect costs
associated with components or subsystems incurred by the automotive
suppliers should not be conflated with vehicle manufacturer indirect
costs.
    Supplier warranty costs should reflect losses they experience to
replace defective battery packs or parts. Likewise, OEM warranty costs
should reflect actual losses they incur in replacing defective parts.
OEM losses are partially reimbursed by supplier warranties. Both OEM
warranty costs and supplier warranty costs should thus represent the
net loss to each business due to warranty coverage. OEM warranty costs
should thus already reflect reimbursement to OEMs from supplier
warranties, implying that reflecting warranty costs within the direct
cost of the product and separate warranty costs at the OEM level is not
double counting. Accordingly, we did not make any changes to how
indirect cost markups are applied to the BatPaC costs for this final
rule.
    In sum, after considering the comments received on how we modeled
battery pack costs, we determined that it was appropriate to use the
same battery costs for this final rule. We will perform additional
research and update our analysis accordingly for future analyses.
    Turning to electrification costs that are non-battery related, each
vehicle powertrain type receives different non-battery electrification
components. When researching costs for different non-battery
electrification components, we found that different reports vary in
components considered and cost breakdown. This is not surprising, as
vehicle manufacturers use different non-battery electrification
components in different vehicle's systems, or even in the same vehicle
type, depending on the application.\405\ We use costs for the major
non-battery electrification components on a dollar per kilowatt basis
based on the costs presented in two reports. We use a $/kW cost metric
for non-battery components to align with the normalized costs for a
system's peak power rating as presented in U.S. DRIVE's Electrical and
Electronics Technical Team (EETT) Roadmap report.\406\ This approach
captures components in some manufacturer's systems, but not all
systems; however, we believe this is a reasonable metric and approach
to use for this analysis given the differences and complexities in non-
battery electrification systems. This approach allows us to scale the
cost of non-battery electrification components based on the
requirements of the system to meet vehicle utility and performance
requirements. We also rely on a MY 2016 Chevrolet Bolt teardown study
for some categories of strong hybrid component costs and all other PHEV
and BEV non-battery component costs that were not explicitly estimated
in the EETT Roadmap report.\407\
---------------------------------------------------------------------------

    \405\ For example, the MY 2020 Nissan Leaf does not have an
active cooling system whereas Chevy Bolt uses an active cooling
system.
    \406\ U.S. DRIVE, Electrical and Electronics Technical Team
Roadmap (Oct. 2017), available at https://www.energy.gov/sites/prod/files/2017/11/f39/EETT%20Roadmap%2010-27-17.pdf.
    \407\ Hummel et al., UBS Evidence Lab Electric Car Teardown--
Disruption Ahead?, UBS (May 18, 2017), https://neo.ubs.com/shared/d1wkuDlEbYPjF/ (accessed: Feb. 11, 2022).
---------------------------------------------------------------------------

    We received several comments specific to strong hybrid non-battery
electrification technology costs, in particular regarding the costs of
eCVTs and high voltage cables.
    Tesla stated that it believes that non-battery electrification
components that add to the total cost required to electrify a vehicle
continue to decrease in price and are utilized across vehicle types and
EVs are rapidly approaching price parity with ICE technology.\408\
---------------------------------------------------------------------------

    \408\ Tesla, at pp. 9-10.
---------------------------------------------------------------------------

    American Council for an Energy-Efficient Economy (ACEEE) commented
that the cost to manufacture hybrid vehicles has fallen significantly
in recent years, more so than NHTSA's analysis assumes.\409\ They
stated that the incremental hybridization costs used in this rule are
significantly higher than those assessed by the 2021 NAS Report.
Specifically, they stated that when accounting for differing
assumptions, the costs assumed by this rule are 20 percent higher.
---------------------------------------------------------------------------

    \409\ ACEEE, Docket No. NHTSA-2021-0053-0074, at p. 5.
---------------------------------------------------------------------------

    Toyota commented that ``NHTSA's estimated costs are significantly
higher than Toyota's understanding based on our current products and
experience developing and marketing hybrids systems over the last two
decades. The estimated costs for power split hybrids used as an input
to compliance modeling for the proposed standards are more than twice
the cost estimates in the National Academies of Science Engineering and
Medicine (NASEM) 2025-2035 CAFE Study.'' \410\ They added ``NHTSA's
projected power split system costs are always significantly higher than
P2 system costs for the same vehicle class. Toyota's experience is that
the relative cost of the power split and P2 systems depends on vehicle
class and operational requirements, and that for many applications
power split and P2 system costs are much more similar than NHTSA's
estimates suggest.'' They further added ``Once adjusted for future cost
savings, NHTSA's 2020 hybrid costs are still typically double the NASEM
estimates. Further, the NASEM committee estimates the incremental cost
of midsize and crossover strong hybrids in 2020 model year to be $2,000
to 3,000 more than a conventional vehicle which is well below NHTSA's
2020 power split estimate,'' and ``Toyota believes the NASEM 2025 model
year cost values are more representative of hybrid vehicle costs
through the 2026 model year, including any accompanying engine
developments and normalization for differences in component sizes and
assessment methodologies. We disagree that engine upgrades should
account for a large portion of the difference between the NASEM and
NHTSA cost estimates. Such a significant cost difference does not exist
for Toyota's 2.5L Dynamic Force engine used in the hybrid and non-
hybrid versions of the 2021 model year Camry referenced by NHTSA.''
---------------------------------------------------------------------------

    \410\ Toyota, at pp. 7-8.
---------------------------------------------------------------------------

    ICCT also commented on cost estimates for the power-split hybrid,
stating that ``NHTSA has substantially overestimated the costs of full
hybrid vehicles, as eCVT costs are far lower than the CVTL2 costs
assumed by NHTSA; NHTSA's high-voltage cable cost is more than twice
that of both NAS and FEV; NHTSA's battery size and cost are overstated,
as they do not take into account power density improvements that cut
the size and cost of strong hybrid battery packs in half; and NHTSA's
analysis has $432 for power electronics and thermal management that
appear to be already be included in motor/inverter/generator/regen
brake costs for NAS and FEV.'' \411\
---------------------------------------------------------------------------

    \411\ ICCT, at p. 10.
---------------------------------------------------------------------------

    We agree with Tesla that there are many non-battery components that
are shared across different vehicle lines, and this provides an
opportunity for cost reductions over time from economies of scale. We
capture cost reductions for non-battery electrification components
through a learning curve Section III.C.6. We will continue to monitor
trends and other information related to non-battery components.
    Based on the comments specific to hybrid vehicle non-battery
component costs, as well as data from the 2021 NAS Report, we
reexamined the costs for

non-battery components. For this final rule, we updated the cost of an
eCVT for SHEVPS vehicles, as well as the costs of high voltage cables
for all strong hybrid vehicles.
    Previously, we had used the cost of a CVTL2 as a proxy for the
eCVT; for this final rule, the eCVT cost comes from data in the EPA-
sponsored teardown study of a 2011 Ford Fusion strong hybrid,\412\ and
has been adjusted to 2018$. This cost also aligns with the eCVT cost
presented in the 2021 NAS Report.
---------------------------------------------------------------------------

    \412\ EPA. ``Light Duty Technology Cost Analysis, Power-Split
and P2 HEV Case Studies.' November 2011. EPA-420-R-11-015. https://nepis.epa.gov/Exe/ZyPDF.cgi/P100EG1R.PDF?Dockey=P100EG1R.PDF.
(Accessed: Dec. 3, 2021)
---------------------------------------------------------------------------

    We also used data from the 2011 Ford Fusion teardown study to
adjust the cost of SHEVP2 and SHEVPS high voltage cables. This
adjustment brought our high voltage cable costs in closer proximity to
the 2021 NAS Report high voltage cable costs. More details about the
updated costs can be found in TSD Chapter <IP_ADDRESS>. The resulting cost
differences between the SHEVP2 and SHEVPS hybrid systems is mainly
associated with the fact that our analysis considers two motors/
generators for SHEVPS and one motor/generator for SHEVP2. We discuss
how SHEVPS and SHEVP2 are characterized in our analysis in Section
III.D.3.a).
    As a reminder, the assumptions that we use to model and simulate
strong hybrid vehicles in Autonomie are not specific to any one
manufacturer's vehicle type. The engines and/or electric motors are
sized to meet different characteristics like utility, performance, and
other key designs to provide the highest system efficiency. These key
characteristics and attributes are discussed in detail in Section
III.C.4. This results in costs that may not match one specific vehicle
teardown. However, we still believe that on average the system cost
estimates are appropriate.
    We agree with Toyota that in some cases a vehicle's engine does not
change when going from a conventional powertrain to hybrid powertrain,
like Toyota's example of the 2.5L naturally aspirated engine in the
RAV4 and RAV4 hybrid. However, the analysis fleet consists of vehicles
with an assortment of engines that are as basic as VVT-only to as
advanced as VCR. In some cases, a vehicle that starts with a basic
conventional engine that adopts SHEVP2 system could also adopt a more
advanced engine. For example, the 2022 Hyundai Tucson base engine is a
2.5L naturally aspirated engine and its hybrid version engine is a
downsized turbocharged engine.\413\ We allow the CAFE Model to both
upgrade and downgrade the engine associated with SHEVP2 powertrains to
apply the ICE engine that is most cost effective with the hybrid
system. The details of these scenarios discussed further in Sections
III.D.3.a) and III.D.3.c) for SHEVs.
---------------------------------------------------------------------------

    \413\ Lorio, J., ''Tested: 2022 Hyundai Tucson Hybrid Aids
Mileage and Performance.'' Car and Driver. December 22, 2021.
https://www.caranddriver.com/reviews/a38591574/2022-hyundai-tucson-hybrid-by-the-numbers/. (Accessed: Dec. 29, 2021)
---------------------------------------------------------------------------

    Finally, we use Autonomie and BatPaC to model the size and cost of
batteries used in strong hybrid vehicles. More details on the sizing
algorithm and battery costs can be found in the Argonne model
documentation as well as in TSD Chapter <IP_ADDRESS>.
    We received another comment from ICCT stating that ``for 2018 Mid
Term Evaluation, non-battery BEV and PHEV costs were updated based on
more recent teardown data from California Air Resources Board, UBS, and
other references, but these updated costs were not used in the proposed
NHTSA rule.'' \414\
---------------------------------------------------------------------------

    \414\ ICCT, at pp. 7-8.
---------------------------------------------------------------------------

    Although ICCT references multiple studies in their comment, they do
not provide any specific BEV and PHEV component costs that they believe
are estimated incorrectly in our analysis. As discussed earlier and in
TSD Chapter <IP_ADDRESS>, we have used the most recent public data available
to estimate the cost of non-battery electrification components. In
particular, we rely on the UBS teardown study that ICCT references for
some BEV and PHEV components.
    To develop the learning curves for non-battery electrification
components, we used cost information from Argonne's 2016 Assessment of
Vehicle Sizing, Energy Consumption, and Cost through Large-Scale
Simulation of Advanced Vehicle Technologies report.\415\ The report
provided estimated cost projections from the 2010 lab year to the 2045
lab year for individual vehicle components.416 417 We
considered the component costs used in electrified vehicles, and
determined the learning curve by evaluating the year over year cost
change for those components. Argonne published a 2020 version of the
same report that included high and low-cost estimates for many of the
same components, that also included a learning rate.\418\ Our learning
estimates generated using the 2016 report fall fairly well in the
middle of these two ranges, and therefore we decided that continuing to
apply the learning curve estimates based on the 2016 report was
reasonable. There are many sources that we could have picked to develop
learning curves for non-battery electrification component costs,
however given the uncertainty surrounding the complexity of the systems
and extrapolating costs out to MY 2050, we believe these learning
curves provide a reasonable estimate.
---------------------------------------------------------------------------

    \415\ Moawad, Ayman, Kim, Namdoo, Shidore, Neeraj, and Rousseau,
Aymeric. Assessment of Vehicle Sizing, Energy Consumption and Cost
Through Large Scale Simulation of Advanced Vehicle Technologies
(ANL/ESD-15/28). United States (2016). Available at https://www.autonomie.net/pdfs/Report%20ANL%20ESD-1528%20-%20Assessment%20of%20Vehicle%20Sizing,%20Energy%20Consumption%20and%20Cost%20through%20Large%20Scale%20Simulation%20of%20Advanced%20Vehicle%20Technologies%20-%201603.pdf, (accessed: Feb. 11, 2022).
    \416\ ANL/ESD-15/28, at p. 116.
    \417\ DOE's lab year equates to five years after a model year,
e.g., DOE's 2010 lab year equates to MY 2015.
    \418\ Islam, E., Kim, N., Moawad, A., Rousseau, A. ``Energy
Consumption and Cost Reduction of Future Light-Duty Vehicles through
Advanced Vehicle Technologies: A Modeling Simulation Study Through
2050'', Report to the U.S. Department of Energy, Contract ANL/ESD-
19/10, June 2020 https://www.autonomie.net/pdfs/ANL%20-%20Islam%20-%202020%20-%20Energy%20Consumption%20and%20Cost%20Reduction%20of%20Future%20Light-Duty%20Vehicles%20through%20Advanced%20Vehicle%20Technologies%20A%20Modeling%20Simulation%20Study%20Through%202050.pdf, (accessed: Feb.
11, 2022).
---------------------------------------------------------------------------

    Table III-19 shows an example of how the non-battery
electrification component costs are computed for the Medium Car and
Medium SUV non-performance vehicle classes for the final rule analysis.
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[GRAPHIC] [TIFF OMITTED] TR02MY22.083

    TSD Chapter <IP_ADDRESS> contains more information about the non-battery
electrification components relevant to each specific electrification
technology and the sources used to develop these costs.
    Finally, the cost of electrifying a vehicle depends on the other
powertrain components that must be added or removed from a vehicle with
the addition of the electrification technology. Table III-20 below
provides a breakdown of each electrification component included for
each electrification technology type, as well as where to find the
costs in each CAFE Model input file.
[GRAPHIC] [TIFF OMITTED] TR02MY22.084

    The following example in Table III-21 shows how the costs are
computed for a vehicle that progresses from a lower level to a higher
level of electrified powertrain. The table shows the components that
are removed and the components that are added as a GMC Acadia
progresses from a MY 2024 vehicle with only SS12V electrification
technology to a BEV300 in MY 2025.\420\ The total cost in MY 2025 is a
net cost addition to the vehicle. The same methodology could be used
for any other technology advancement in the electric technology tree
path. For the final rule analysis, the cost of the SS12V battery was
updated as discussed earlier, and this example has been updated to show
the new cost.
---------------------------------------------------------------------------

    \419\ As discussed in section <IP_ADDRESS> of the TSD, we no longer
use the BatPaC SS12V battery cost and use a cheaper AGM battery
instead, and the updated cost is reflected in the battery_costs.csv
file.
    \420\ Vehicle code 11001008 in the Vehicle Report output file.

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

[GRAPHIC] [TIFF OMITTED] TR02MY22.085

    TSD Chapter <IP_ADDRESS> includes more details about how the costs
associated with the internal combustion engine, transmission, electric
machine(s), non-battery electrification components, and battery pack
for each electrified technology type are combined to create a full
electrification system cost.
---------------------------------------------------------------------------

    \421\ Please note that in this calculation the CAFE Model
accounts for the air conditioning and off-cycle technologies (g/
mile) applied to each vehicle model. The cost for the AC/OC
adjustments are located in the CAFE Model Scenarios file. The air
conditioning and off-cycle cost values are discussed further in TSD
Chapter 3.8.
---------------------------------------------------------------------------

Mass Reduction
    Mass reduction is a relatively cost-effective means of improving
fuel economy, and vehicle manufacturers are expected to apply various
mass reduction technologies to meet fuel economy standards. Reducing
vehicle mass is accomplished through several different techniques, such
as modifying and optimizing vehicle component and system designs, part
consolidation, and adopting lighter weight materials (advanced high
strength steel, aluminum, magnesium, and plastics including carbon
fiber reinforced plastics).
    The cost for mass reduction depends on the type and amount of
materials used, the manufacturing and assembly processes required, and
the degree to which changes to plants and new manufacturing and
assembly equipment is needed. In addition, manufacturers may develop
expertise and invest in certain mass reduction strategies that may
affect the approaches for mass reduction they consider and the
associated costs. Manufacturers may also consider vehicle attributes
like noise-vibration-harshness (NVH), ride quality, handling, crash
safety and various acceleration metrics when considering how to
implement any mass reduction strategy. These are considered to be
aspects of performance, and for this analysis any identified pathways
to compliance are intended to maintain performance neutrality.
Therefore, mass reduction via elimination of, for example, luxury items
such as climate control, or interior vanity mirrors, leather padding,
etc., is not considered in the mass reduction pathways for this
analysis.
    The automotive industry uses different metrics to measure vehicle
weight. Some commonly used measurements are vehicle curb weight,\422\
gross vehicle weight (GVW),\423\ gross vehicle weight rating
(GVWR),\424\ gross combined weight (GCVW),\425\ and equivalent test
weight (ETW),\426\ among others. The vehicle curb weight is the most
commonly used

measurement when comparing vehicles. A vehicle's curb weight is the
weight of the vehicle including fluids, but without a driver,
passengers, and cargo. A vehicle's glider weight, which is vehicle curb
weight minus the powertrain weight, is used to track the potential
opportunities for weight reduction not including the powertrain. A
glider's subsystems may consist of the vehicle body, chassis, interior,
steering, electrical accessory, brake, and wheels systems. The
percentage of weight assigned to the glider will remain constant for
any given rule but may change overall. For example, as electric
powertrains including motors, batteries, inverters, etc. become a
greater percent of the fleet, glider weight percentage will change
compared to earlier fleets with higher dominance of ICE powertrains.
---------------------------------------------------------------------------

    \422\ This is the weight of the vehicle with all fluids and
components but without the drivers, passengers, and cargo.
    \423\ This weight includes all cargo, extra added equipment, and
passengers aboard.
    \424\ This is the maximum total weight of the vehicle,
passengers, and cargo to avoid damaging the vehicle or compromising
safety.
    \425\ This weight includes the vehicle and a trailer attached to
the vehicle, if used.
    \426\ For the EPA two-cycle regulatory test on a dynamometer, an
additional weight of 300 lbs. is added to the vehicle curb weight.
This additional 300 lbs. represents the weight of the driver,
passenger, and luggage. Depending on the final test weight of the
vehicle (vehicle curb weight plus 300 lbs.), a test weight category
is identified using the table published by EPA according to 40 CFR
1066.805. This test weight category is called ``Equivalent Test
Weight'' (ETW).
---------------------------------------------------------------------------

    For this analysis, NHTSA considers six levels of mass reduction
technology that include increasing amounts of advanced materials and
mass reduction techniques applied to the glider. NHTSA accounts for
changes in mass associated with powertrain changes separately. The
following sections discuss the assumptions for the six mass reduction
technology levels, the process used to assign initial analysis fleet
mass reduction assignments, the effectiveness for applying mass
reduction technology, and mass reduction costs.
(a) Mass Reduction in the CAFE Model
    The CAFE Model considers six levels of mass reduction technologies
that manufacturers could use to comply with CAFE standards. The
magnitude of mass reduction in percent for each of these levels is
shown in Table III-22 for mass reductions for light trucks, passenger
cars and for gliders.
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[GRAPHIC] [TIFF OMITTED] TR02MY22.086

    For this analysis, NHTSA considers mass reduction opportunities
from the glider subsystems of a vehicle first, and then consider
associated opportunities to downsize the powertrain, which are
accounted for separately.\427\ As explained below, in the Autonomie
simulations, the glider system includes both primary and secondary
systems from which a percentage of mass is reduced for different glider
weight reduction levels; specifically, the glider includes the body,
chassis, interior, electrical accessories, steering, brakes and wheels.
In this analysis, NHTSA assumes the glider share is 71 percent of
vehicle curb weight. The Autonomie model sizes the powertrain based on
the glider weight and the mass of some of the powertrain components in
an iterative process. The mass of the powertrain depends on the
powertrain size. Therefore, the weight of the glider impacts the weight
of the powertrain.\428\
---------------------------------------------------------------------------

    \427\ When the mass of the vehicle is reduced by an appropriate
amount, the engine may be downsized to maintain performance. See
Section III.C.4 for more details.
    \428\ Since powertrains are sized based on the glider weight for
the analysis, glider weight reduction beyond a threshold amount
during a redesign will lead to re-sizing of the powertrain. For the
analysis, the glider was used as a base for the application of any
type of powertrain. A conventional powertrain consists of an engine,
transmission, exhaust system, fuel tank, radiator, and associated
components. A hybrid powertrain also includes a battery pack,
electric motor(s), generator, high voltage wiring harness, high
voltage connectors, inverter, battery management system(s), battery
pack thermal system, and electric motor thermal system.
---------------------------------------------------------------------------

    NHTSA uses glider weight to apply non-powertrain mass reduction
technology in the CAFE Model and use Autonomie simulations to determine
the size of the powertrain and corresponding powertrain weight for the
respective glider weight. The combination of glider weight (after mass
reduction) and re-sized powertrain weight equal the vehicle curb
weight.
    While there are a range of specific mass reduction technologies
that may be applied to vehicles to achieve each of the six mass
reduction levels, there are some general trends that are helpful to
illustrate some of the more widely used approaches. Typically, MR0
reflects vehicles with widespread use of mild steel structures and body
panels, and very little or no use of high strength steel or aluminum.
MR0 reflects materials applied to average vehicles in the MY 2008
timeframe. MR1-MR3 can be achieved with a steel body structure. In
going from MR1 to MR3, expect that mild steel to be replaced by high
strength and then advanced high strength steels. In going from MR3 to
MR4 aluminum is required. This will start at using aluminum closure
panels and then to get to MR4 the vehicle's primary structure will need
to be mostly made from aluminum. In the vast majority of cases, carbon
fiber technology is necessary to reach MR5, perhaps with a mix of some
aluminum. MR6 requires nearly every primary structural component of the
vehicle, like body structure and closure panels, be made from carbon
fiber. There may be some use of aluminum in the suspension components.
TSD Chapter 3.4 includes more discussion of the challenges involved
with adopting large amounts of carbon fiber in the vehicle fleet.
    Arconic Corporation commented that ``the NPRM makes specific
references to aluminum, which are accurate and consistent with
practical automotive industry experience and future program
expectations. Mass reduction utilizing advanced materials like aluminum
is recognized as one of the technology options to achieve safe, fuel-
efficient

and cost-effective vehicles that meet or exceed consumer demands.''
\429\
---------------------------------------------------------------------------

    \429\ Arconic, Docket No. NHTSA-2021-0053-1560, at p. 1.
---------------------------------------------------------------------------

    The American Chemistry Council (ACC) commented on the agency's
statements about vehicle light-weighting in several respects, but
particularly disagreeing with our analysis of mass reduction technology
levels.\430\ Specifically, ACC stated that ``as written, the NPRM could
be construed as NHTSA discouraging the use of carbon fiber composites
as well as an endorsement for utilizing steel and aluminum-based
designs to achieve mass reduction.'' \431\ ACC also provided updated
data on carbon fiber costs from DOE ORNL studies that they asked the
agency to consider in the final rule.
---------------------------------------------------------------------------

    \430\ ACC, Docket No. NHTSA-2021-0053-1564, at p. 5.
    \431\ Id.
---------------------------------------------------------------------------

    To be clear, our analysis does not endorse any specific technology
solution or pathway over another. However, our analysis does need to
accurately reflect trends that are developing in the real-world
automotive marketplace and potential fuel economy improving technology
to appropriately estimate the costs and benefits of more stringent
standards. It also does need to consider what could reasonably occur in
the future of the market given automotive development timelines for
implementing new technology into real passenger vehicles. Precursor
materials technologies that potentially offer game-changing dry carbon
fiber cost reductions are still under development and therefore we
would not expect them to end up in a production vehicle program beyond
what our adoption features allow in the rulemaking timeframe.
    In addition, while carbon fiber composites are considered a
potential pathway to compliance, wholly carbon fiber primary structure,
which is what is necessary to reduce mass enough to achieve the highest
mass reduction levels in the analysis, simply have not materialized.
While the number and mass of discrete applications of carbon fiber has
expanded the fleet--for example, adding carbon fiber decorative
interior trim pieces or carbon fiber roof panels to medium and high-end
luxury cars--these discrete applications do not contribute to
substantial mass reduction required to meet the highest levels of mass
reduction in this analysis. The price to apply carbon fiber technology
to produce wholly carbon fiber composite primary structure with the
precursor material available today has not yet dropped to a price that
would make it cost-effective for the industry to apply to meet more
stringent fuel economy standards. This fact is corroborated by the 2021
NAS Report, which provided updated data for carbon fiber composite
costs that show the technology has not yet dropped to a price that
would make it cost-effective for the industry to apply to meet more
stringent fuel economy standards. This is discussed further in Section
III.D.4.c) below. We also appreciate ACC's inclusion of the DOE ORNL
technoeconomic analysis on carbon fiber and discuss the study further
in Section III.D.4.e) below.
    As discussed further below, the cost studies used to generate the
cost curves assume mass can be reduced in levels that require utilizing
different materials and modifying different components, in a specific
order. NHTSA's mass reduction levels are loosely based on what
materials and component modifications are required for each percent of
mass reduction, based on the conclusions of those studies.
(b) Mass Reduction Analysis Fleet Assignments
    To assign baseline mass reduction levels (MR0 through MR6) for
vehicles in the MY 2020 analysis fleet, NHTSA uses previously developed
regression models to estimate curb weight for each vehicle based on
observable vehicle attributes. NHTSA uses these models to establish a
baseline (MR0) curb weight for each vehicle, and then determines the
existing mass reduction technology level by finding the difference
between the vehicles actual curb weight to the estimated regression-
based value, and comparing the difference to the values in Table III-
22. NHTSA originally developed the mass reduction regression models
using MY 2015 fleet data; for this analysis, NHTSA used MY 2016 and
2017 analysis fleet data to update the models.
    NHTSA believes the regression methodology is a technically sound
approach for estimating mass reduction levels in the analysis fleet.
For a detailed discussion about the regression development and use
please see TSD Chapter 3.4.2.
    Manufacturers generally apply mass reduction technology at a
vehicle platform level (i.e., using the same components across multiple
vehicle models that share a common platform) to leverage economies of
scale and to manage component and manufacturing complexity, so
conducting the regression analysis at the platform level leads to more
accurate estimates for the real-world vehicle platform mass reduction
levels. The platform approach also addresses the impact of potential
weight variations that might exist for specific vehicle models, as all
the individual vehicle models are aggregated into the platform group,
and are effectively averaged using sales weighting, which minimizes the
impact of any outlier vehicle configurations.
(c) Mass Reduction Adoption Features
    Given the degree of commonality among the vehicle models built on a
single platform, manufacturers do not have complete freedom to apply
unique mass reduction technologies to each vehicle model that shares
the platform. While some technologies (e.g., low rolling resistance
tires) are very nearly ``bolt-on'' technologies, others involve
substantial changes to the structure and design of the vehicle, and
therefore affect all vehicle models that share a platform. In most
cases, mass reduction technologies are applied to platform level
components and therefore the same design and components are used on all
vehicle models that share the platform.
    Each vehicle in the analysis fleet is associated with a specific
platform. Similar to the application of engine and transmission
technologies, the CAFE Model defines a platform ``leader'' as the
vehicle variant of a given platform that has the highest level of
observed mass reduction present in the analysis fleet. If there is a
tie, the CAFE Model begins mass reduction technology on the vehicle
with the highest sales volume in MY 2020. If there remains a tie, the
model begins by choosing the vehicle with the highest manufacturer
suggested retail price (MSRP) in MY 2020. As the model applies
technologies, it effectively levels up all variants on a platform to
the highest level of mass reduction technology on the platform. For
example, if the platform leader model is already at MR3 in MY 2020, and
a ``follower'' platform model starts at MR0 in MY 2020, the follower
platform model will get MR3 at its next redesign, assuming no further
mass reduction technology is applied to the leader model before the
follower model's next redesign.
    In addition to the platform-sharing logic employed in the model,
NHTSA applies phase-in caps for MR5 and MR6 (15 percent and 20 percent
reduction of a vehicle's curb weight, respectively), based on the
current state of mass reduction technology. As discussed above, for
nearly every type of vehicle, a manufacturer's strategy to achieve mass
reduction consistent with MR5 and MR6 will require extensive use of
carbon fiber technologies in the vehicles' primary structures. For
example, one way of using carbon fiber

technology to achieve MR6 is to develop a carbon fiber monocoque
structure.\432\
---------------------------------------------------------------------------

    \432\ A monocoque structure is one where the outer most skins
support the primary loads of the vehicle. For example, they do not
have separate non-load bearing aero surfaces. All of the vehicle's
primary loads are supported by the monocoque. In the most
structurally efficient automotive versions, the monocoque is made
from multiple well-consolidated plies of carbon fiber infused with
resin. Such structures would likely require a few hundred kilograms
of carbon fiber for most passenger vehicles.
---------------------------------------------------------------------------

    High CAFE stringency levels will push the CAFE Model to select
compliance pathways that include these higher levels of mass reduction
for vehicles produced in the mid and high hundreds of thousands of
vehicles per year. NHTSA assumes, based on material costs and
availability, that achieving MR6 levels of mass reduction will cost
over ten thousand dollars per car. The cost of achieving MR6 in the
CAFE Model is consistent with our understanding of the real-world costs
to produce a carbon fiber monocoque structure.\433\ Therefore,
application of such technology to high volume vehicles is unrealistic
today and will, with certainty, remain so for the next several years.
---------------------------------------------------------------------------

    \433\ In simplest terms, the cost to produce a component made
from carbon fiber composite materials is the sum of the cost of dry
carbon fiber, resin, amortized tooling, direct labor, and factor
overhead. A BMW i3 monocoque contains between 100 and 150 kg of
carbon fiber composite material depending on source (see article on
https://www.marklines.com/en/report_all/rep1419_201506, (accessed:
Feb. 11, 2022). ``Recent Trends in CFRP Development: Increased Usage
in European Vehicles, July 2015, and see book: ``Lightweight and
Sustainable Materials for Automotive Applications,'' Chapter 8,
2017, CRC Press). Assuming a very typical 60/40 mix of carbon fiber
to resin, and assuming the price of dry carbon fiber is $20-$40 per
kilogram and the price of resin is $5-$10 per kilogram, the cost of
direct materials alone in an i3's carbon fiber monocoque is already
approaching $4,200. Adding direct labor, factory overhead (which
scales with cycle time) and the amortized cost of tooling can easily
bring the cost for components made from composite materials in the
i3 to a higher level. Note that the BMW i3 is on the small end of
the size spectrum in the 2020 fleet and these costs would increase
faster than proportional to vehicle footprint because of the mass
compounding effect. Therefore, the cost of a monocoque for a large
sedan (the current BMW 7-series has a foot-print that is 30 percent
higher than that of the i3) could easily cost over ten thousand
dollars.
---------------------------------------------------------------------------

    The CAFE Model applies technologies to vehicles that provide a
cost-effective pathway to compliance. In some cases, the direct
manufacturing cost, indirect costs, and applied learning factor do not
capture all the considerations that make a technology more or less
costly for manufacturers to apply in the real world. For example, there
are direct labor, R&D overhead, manufacturing overhead and tooling
costs. Due to the complexities of manufacturing composite components,
many of these are more expensive for manufacturing carbon fiber
components than for manufacturing metal components. Next, as of yet, no
one has found an effective way to recycle carbon fiber composites,
which means there saving money through re-using material is a
challenge. In addition, R&D overhead will also increase because of the
knowledge base for composite materials in automotive applications is
simply not as deep as it is for steel and aluminum.
    ACC commented on this characterization of potential costs for
carbon fiber technology, using it as an example of where, as discussed
above, they believed the NPRM could be construed as NHTSA discouraging
the use of carbon fiber composites.\434\ However, the views stated in
the previous paragraph explaining why carbon fiber technologies are not
widespread are not indicative of NHTSA discouraging the use of or
further development carbon fiber technologies. Rather, they reflect
what has actually occurred in the automotive market and views shared by
others. In fact, BMW decided that a mixed materials solution is a more
financially effective way to reduce mass and will not build a wholly
carbon fiber composite successor to the i3.\435\ \436\ \437\ \438\
\439\
---------------------------------------------------------------------------

    \434\ ACC, at p. 5.
    \435\ Brosius, Dale, ``Carbon Fiber in Automotive: At a Dead
End?'' Composites World, December 20, 2021.
    \436\ Sloan, Jeff, ``AutoComposites and the Myth of $5/lb.
Carbon Fiber,'' Composites World, February 24, 2017.
    \437\ Taylor, Edward and Sage, Alexandria, ``BMW Limits
Lightweight Carbon Fibre Use to Juice Profits,'' Reuters, October
2016.
    \438\ Bunkley, Nick, ``BMW Limits Carbon Fiber Use to Protect
Profits,'' Autonews Gasgoo, October 31, 2016.
    \439\ Schlosser, Andreas, Coskun Baban, Samith, and Siedel
Phillipp, ``After the Hype: Where is the Carbon Car?'' Arthur D.
Little, January 2019.
---------------------------------------------------------------------------

    Indeed, the intrinsic anisotropic mechanical properties of
composite materials compared to the isotropic properties of metals
complicates the design process. Added testing of these novel
anisotropic structures and their associated costs will be necessary for
decades. Adding up all these contributing costs, the price tag for a
passenger car or truck monocoque would likely be multiple tens of
thousands of dollars per vehicle. This would be significantly more
expensive than transitioning to hybrid or fully electric powertrains
and potentially less effective at achieving CAFE compliance.
    In addition, the CAFE Model does not currently enable direct
accounting for the stranded capital associated with a transition away
from stamped sheet metal construction to molded composite materials
construction. For decades, or in some cases half-centuries, car
manufacturers have invested billions of dollars in capital for
equipment that supports the industry's sheet metal forming paradigm. A
paradigm change to tooling and equipment developed to support molding
carbon fiber panels and monocoque chassis structures would leave that
capital stranded in equipment that would be rendered obsolete. Doing
this is possible, but the financial ramifications are not currently
reflected in the CAFE Model for MR5 and MR6 compliance pathways.
    Financial matters aside, carbon fiber technology and how it is best
used to produce light-weight primary automotive structures is far from
mature. In fact, no car company knows for sure the best way to use
carbon fiber to make a passenger car's primary structure. Using this
technology in passenger cars is far more complex than using it in
racing cars where passenger egress, longevity, corrosion protection,
crash protection, etc. are lower on the list of priorities for the
design team. BMW may be the one manufacturer most able accurately opine
on the viability of carbon fiber technology for primary structure on
high-volume passenger cars, and even it decided to use a mixed
materials solution for their next generation of EVs (the iX and i4)
after the i3, thus eschewing a wholly carbon fiber monocoque structure.
    Another factor limiting the application of carbon fiber technology
to mass volume passenger vehicles is indeed the availability of dry
carbon fibers. There is high global demand from a variety of industries
for a limited supply of carbon fibers. Aerospace, military/defense, and
industrial applications demand most of the carbon fiber currently
produced. Today, only roughly 10 percent of the global dry fiber supply
goes to the automotive industry, which translates to the global supply
base only being able to support approximately 80,000 cars.\440\
---------------------------------------------------------------------------

    \440\ J. Sloan, ``Carbon Fiber Suppliers Gear up for Next
Generation Growth,'' compositesworld.com, February 11, 2020.
---------------------------------------------------------------------------

    To account for these cost and production considerations, including
the limited global supply of dry carbon fiber, NHTSA applied phase-in
caps that limited the number of vehicles that can achieve MR5 and M6
levels of mass reduction in the CAFE Model. NHTSA applied a phase-in
cap for MR5 level technology so that 75 percent of the vehicle fleet
starting in 2020 could employ the technology, and the technology could
be applied to 100

percent of the fleet by MY 2022. NHTSA also applied a phase-in cap for
MR6 technology so that five percent of the vehicle fleet starting in MY
2020 could employ the technology, and the technology could be applied
to 10 percent of the fleet by MY 2025.
    To develop these phase-in caps, NHTSA chose a 40,000-unit threshold
for both MR5 and MR6 technology (80,000 units total), because it
roughly reflects the number of BMW i3 cars produced per year
worldwide.\441\ As discussed above, the BMW i3 is the only high-volume
vehicle currently produced with a primary structure mostly made from
carbon fiber (except the skateboard, which is aluminum). Because mass
reduction is applied at the platform level (meaning that every car of a
given platform would receive the technology, not just special low
volume versions of that platform), only platforms representing 40,000
vehicles or less are eligible to apply MR5 and MR6 toward CAFE
compliance. Platforms representing high volume sales, like a Chevrolet
Traverse, for example, where hundreds of thousands are sold per year,
are therefore blocked from access to MR5 and MR6 technology. There are
no phase in caps for mass reduction levels MR1, MR2, MR3 or MR4.
---------------------------------------------------------------------------

    \441\ However, even this number is optimistic because only a
small fraction of i3 cars are sold in the U.S. market, and combining
MR5 and MR6 allocations equates to 80k vehicles, not 40k.
Regardless, if the auto industry ever seriously committed to using
carbon fiber in mainstream high-volume vehicles, competition with
the other industries would rapidly result in a dramatic increase in
price for dry fiber. This would further stymie the deployment of
this technology in the automotive industry.
---------------------------------------------------------------------------

    In addition to determining that the caps were reasonable based on
current global carbon fiber production, NHTSA determined that the MR5
phase-in cap is consistent with the NHTSA light-weighting study that
found that a 15 percent curb weight reduction for the fleet is possible
within the rulemaking timeframe.\442\
---------------------------------------------------------------------------

    \442\ Singh, Harry. (2012, August). Mass Reduction for Light-
Duty Vehicles for Model Years 2017-2025. (Report No. NHTSA HS 811
666). Program Reference: NHTSA Contract DTNH22-11-C-00193. Contract
Prime: Electricore, Inc, at 356, Figure 397.
---------------------------------------------------------------------------

    These phase-in caps appropriately function as a proxy for the cost
and complexity currently required (and that likely will continue to be
required until manufacturing processes evolve) to produce carbon fiber
components. Again, MR6 technology in this analysis reflects the use of
a significant share of carbon fiber content, as seen through the BMW i3
and Alfa Romeo 4c as discussed above.
    Given the uncertainty and fluid nature of knowledge around higher
levels of mass reduction technology, we welcomed comments on how to
most cost effectively use carbon fiber technology in high-volume
passenger cars. We also stated that financial implementation estimates
for this technology are equally as welcome.
    NHTSA received comment involving the ability of auto industry
suppliers to procure dry carbon fiber materials in quantities
consistent with supplying high-volume platforms. Commenters suggested
that the industry that produces dry carbon fiber could readily ramp-up
fiber production at a rate fast enough to accommodate the demands of
multiple high volume automotive platforms such as the Chevrolet
Traverse or Volvo XC90, all within the time frame in which this rule
applies.\443\ Commenters did not mention specific achievable production
volumes or detail a production volume trajectory as a function of time.
In addition, ACC commented that it was misleading for NHTSA to state
that only roughly 10 percent of the global dry fiber supply goes to the
automotive industry, that 10 percent would only be enough for roughly
70,000 vehicles and that producers of dry carbon fiber would not scale
their output to support high volume production automotive programs.
Based on available literature, engineering judgment and the composition
of the current fleet, we continue to believe that MR5 or MR6 will not
be achievable for large volume platforms in the rulemaking
timeframe.\444\ Sources in the literature indicate that if only three
mass volume auto makers used 8-9 kg of carbon fiber (which would not
meet MR5 or MR6 levels) in each of their vehicles, the carbon fiber
industry would need to double its output. Using only 8-9 kg of carbon
fiber per vehicle will never enable mass reduction consistent with MR5
or MR6. The amount of carbon fiber required for this would require at
least an order of magnitude more than 8-9 kg. Fiber producers cannot
double their output in the rulemaking timeframe let alone increase it
by twenty-fold within the same timeframe.\445\
---------------------------------------------------------------------------

    \443\ ACC, at p. 5.
    \444\ Bill, Bregar, ``Prices Keep Carbon Fiber from Mass
Adoption,'' Plastic News, August 5, 2014.
    \445\ ``How to Turn Pitch into Carbon Fiber for Automotive
Applications,'' https://www.azom.com/article.aspx?ArticleID=19200
(accessed: Feb. 11, 2022).
---------------------------------------------------------------------------

    In addition, since publication of the NPRM, BMW stopped producing
its i3 vehicle, the only mass-volume vehicle built with nearly full
carbon fiber construction. The i3 was replaced with a vehicle
containing only a small fraction of the amount carbon fiber composite
materials as its predecessor. BMW decided a multi-materials solution
was more cost effective.\446\ \447\ Currently, the few vehicles that
continue to use carbon fiber do so in only small fractions or they are
not mass-market vehicles.\448\ We are not currently aware of any high-
volume cars planned for the near future with nearly full carbon fiber
construction. If that remains the case, there is no incentive to
dramatically boost production of dry carbon fiber to support the auto
industry.
---------------------------------------------------------------------------

    \446\ Taylor, Edward and Sage, Alexandria, ``BMW Limits
Lightweight Carbon Fibre Use to Juice Profits,'' Reuters, October
2016.
    \447\ Bunkley, Nick, ``BMW Limits Carbon Fiber Use to Protect
Profits,'' Autonews Gasgoo, October 31, 2016.
    \448\ See, e.g., the BMW iX and i4, and some Lamborghini
vehicles.
---------------------------------------------------------------------------

    There may be some emerging methods to provide a lower cost pathway
to MR6, like selectively applying high-modulus carbon fiber tapes to
lower cost structures primarily made from fiberglass composites.\449\
Although these methods may reduce the cost of direct materials, the do
not alleviate slow production cycle times and the costs associated with
them.
---------------------------------------------------------------------------

    \449\ By strategic application of carbon fiber in areas of
highest stress in a given structure, it is often possible to achieve
sufficient structural performance at a lower cost. However, this
strategy does not solve the aforementioned issues surrounding the
high costs associated with the relatively long production cycle
times of composite materials composites.
---------------------------------------------------------------------------

    The analysis herein uses the 2020 fleet to evaluate the level of
mass reduction (MR0-MR6) achieved by individual vehicle platforms. In
total, a little more than 25,000 vehicles of a fleet containing roughly
16 million vehicles achieved MR5 and MR6. It is expected that achieving
MR5 will require at least some carbon fiber technology and achieving
MR6 will require nearly full carbon fiber construction. Of the 25,000
vehicles, about 5,000 vehicles have nearly full carbon fiber
construction. These vehicles are produced by BMW (the i3 and i8), the
VW Group (Bugatti and Lamborghini) and few others that are not big
enough to be included in the 2020 fleet. Noteworthy is that there are
service vans in the fleet that achieve the highest MR levels, but only
for the reason that they have large footprints (wheelbase times average
track) and do not include interior trim and luxury items. Given this
small representation of vehicles with nearly full carbon fiber
construction, and current trends in

automotive carbon fiber application, discussed above, we do not believe
that multiple large-volume platforms would be able to reach MR6 in the
rulemaking timeframe.
    We will continue to monitor carbon fiber investments from the
automotive sector, whether for full carbon fiber construction bodies or
carbon fiber parts, and on the implications of such investments for
automotive application carbon fiber demand, capacity, and supply. Based
on these observations, however, we declined to update any of our mass
reduction adoption features for this final rule.
(d) Mass Reduction Effectiveness Modeling
    As discussed in Section III.C.4, Argonne developed a database of
vehicle attributes and characteristics for each vehicle technology
class that included over 100 different attributes. Some examples from
these 100 attributes include frontal area, drag coefficient, fuel tank
weight, transmission housing weight, transmission clutch weight, hybrid
vehicle components, and weights for components that comprise engines
and electric machines, tire rolling resistance, transmission gear
ratios, and final drive ratio. Argonne used these attributes to
``build'' each vehicle that it used for the effectiveness modeling and
simulation. Important for precisely estimating the effectiveness of
different levels of mass reduction is an accurate list of initial
component weights that make up each vehicle subsystem, from which
Autonomie considered potential mass reduction opportunities.
    As stated above, NHTSA uses glider weight, or the vehicle curb
weight minus the powertrain weight, to determine the potential
opportunities for weight reduction irrespective of the type of
powertrain.\450\ This is because weight reduction can vary depending on
the type of powertrain. For example, an 8-speed transmission may weigh
more than a 6-speed transmission, and a basic engine without variable
valve timing may weigh more than an advanced engine with variable valve
timing. Autonomie simulations account for the weight of the powertrain
system inherently as part of the analysis, and the powertrain mass
accounting is separate from the application and accounting for mass
reduction technology levels that are applied to the glider in the
simulations. Similarly, Autonomie also accounts for battery and motor
mass used in hybrid and electric vehicles separately. This secondary
mass reduction is discussed further below.
---------------------------------------------------------------------------

    \450\ Depending on the powertrain combination, the total curb
weight of the vehicle includes glider, engine, transmission and/or
battery pack and motor(s).
---------------------------------------------------------------------------

    Accordingly, in the Autonomie simulations, mass reduction
technology is simulated as a percentage of mass removed from the
specific subsystems that make up the glider, as defined for that set of
simulations (including the non-powertrain secondary mass systems such
as the brake system). For the purposes of determining a reasonable
percentage for the glider, NHTSA in consultation with Argonne examined
glider weight data available in the A2Mac1 database,\451\ in addition
to the NHTSA MY 2014 Chevrolet Silverado light-weighting study
(discussed further below). Based on these studies, NHTSA assumes that
the glider weight comprised 71 percent of the vehicle curb weight. TSD
Chapter 3.4.4 includes a detailed breakdown of the components that
NHTSA considered to arrive at the conclusion that a glider, on average,
represents 71 percent of a vehicle's curb weight.
---------------------------------------------------------------------------

    \451\ A2Mac1: Automotive Benchmarking, https://a2mac1.com.
---------------------------------------------------------------------------

    Any mass reduction due to powertrain improvements is accounted for
separately from glider mass reduction. Autonomie considers several
components for powertrain mass reduction, including engine downsizing,
and transmission, fuel tank, exhaust systems, and cooling system light-
weighting.
    The 2015 NAS Report suggested an engine downsizing opportunity
exists when the glider mass is light-weighted by at least 10 percent.
The 2015 NAS Report also suggested that 10 percent light-weighting of
the glider mass alone would boost fuel economy by 3 percent and any
engine downsizing following the 10 percent glider mass reduction would
provide an additional 3 percent increase in fuel economy.\452\ The 2011
Honda Accord and 2014 Chevrolet Silverado light-weighting studies
applied engine downsizing (for some vehicle types but not all) when the
glider weight was reduced by 10 percent. Accordingly, this analysis
limited engine resizing to several specific incremental technology
steps as in the 2018 NPRM and 2020 final rule; important for this
discussion, engines in the analysis were only resized when mass
reduction of 10 percent or greater was applied to the glider mass, or
when one powertrain architecture was replaced with another
architecture.
---------------------------------------------------------------------------

    \452\ 2015 NAS Report. National Research Council. 2015. Cost,
Effectiveness, and Deployment of Fuel Economy Technologies for
Light-Duty Vehicles. Washington, DC--The National Academies Press.
https://doi.org/10.17226/21744, (accessed: Feb. 11, 2022).
---------------------------------------------------------------------------

    Specifically, we allow engine resizing upon adoption of 7.1, 10.7,
14.2, and 20 percent curb weight reduction, but not at 3.6 and 5.3
percent.\453\ Resizing is also allowed upon changes in powertrain type
or the inheritance of a powertrain from another vehicle in the same
platform. The increments of these higher levels of mass reduction, or
complete powertrain changes, more appropriately match the typical
engine displacement increments that are available in a manufacturer's
engine portfolio.
---------------------------------------------------------------------------

    \453\ These curb weight reductions equate to the following
levels of mass reduction as defined in the analysis: MR3, MR4, MR5
and MR6, but not MR1 and MR2; additional discussion of engine
resizing for mass reduction can be found in Section III.C.4 and TSD
Chapter 2.4.
---------------------------------------------------------------------------

    Argonne performed a regression analysis of engine peak power versus
weight for a previous analysis based on attribute data taken from the
A2Mac1 benchmarking database, to account for the difference in weight
for different engine types. For example, to account for weight of
different engine sizes like 4-cylinder versus 8-cylinder, Argonne
developed a relationship curve between peak power and engine weight
based on the A2Mac1 benchmarking data. We use this relationship to
estimate mass for all engine types regardless of technology type (e.g.,
variable valve lift and direct injection). NHTSA applies weight
associated with changes in engine technology by using this linear
relationship between engine power and engine weight from the A2Mac1
benchmarking database. When a vehicle in the analysis fleet with an 8-
cylinder engine adopts a more fuel-efficient 6-cylinder engine, the
total vehicle weight reflects the updated engine weight with two less
cylinders based on the peak power versus engine weight relationship.
    When Autonomie selects a powertrain combination for a light-
weighted glider, the engine and transmission are selected such that
there is no degradation in the performance of the vehicle relative to
the baseline vehicle. The resulting curb weight is a combination of the
mass reduced glider with the resized and potentially new engine and
transmission. This methodology also helps in accurately accounting for
the cost of the glider and cost of the engine and transmission in the
CAFE Model.
    Secondary mass reduction is possible from some of the components in
the glider after mass reduction is applied to the primary subsystems
(body, chassis, and interior). Similarly, engine

downsizing and powertrain secondary mass reduction is possible after
certain level of mass reduction is incorporated in the glider. For the
analysis, the agencies include both primary mass reduction, and when
there is sufficient primary mass reduction, additional secondary mass
reduction. The Autonomie simulations account for the aggregate of both
primary and secondary glider mass reduction, and separately for
powertrain mass.
    Note that secondary mass reduction is integrated into the mass
reduction cost curves. Specifically, the NHTSA studies, upon which the
cost curves depend, first generated costs for light-weighting the
vehicle body, chassis, interior, and other primary components, and then
calculated costs for light-weighting secondary components. Accordingly,
the cost curves reflect that, for example, secondary mass reduction for
the brake system is only applied after there has been sufficient
primary mass reduction to allow the smaller brake system to provide
safe braking performance and to maintain mechanical functionality.
    NHTSA enhances the accuracy of estimated engine weights by using
two curves to represent separately naturally aspirated engine designs
and turbocharged engine designs.\454\ This achieves two benefits.
First, small naturally aspirated 4-cylinder engines that adopt
turbocharging technology reflects the increased weight of associated
components like ducting, clamps, the turbocharger itself, a charged air
cooler, wiring, fasteners, and a modified exhaust manifold. Second,
larger cylinder count engines like naturally aspirated 8-cylinder and
6-cylinder engines that adopt turbocharging and downsizing technologies
have lower weight due to having fewer engine cylinders. For this
analysis, a naturally aspirated 8-cylinder engine that adopts
turbocharging technology and is downsized to a 6-cylinder turbocharged
engine appropriately reflects the added weight of the turbocharging
components, and the lower weight of fewer cylinders.
---------------------------------------------------------------------------

    \454\ See Autonomie model documentation, Chapter 5.2.9, Engine
Weight Determination.
---------------------------------------------------------------------------

    The range of effectiveness values for the mass reduction
technologies, for all ten vehicle technology classes are shown in
Figure III-14. In the graph, the box shows the inner quartile range
(IQR) of the effectiveness values and whiskers extend out 1.5 x IQR.
The NHTSAs outside of the whiskers show a few values outside these
ranges. As discussed earlier, Autonomie simulates all possible
combinations of technologies for fuel consumption improvements. For a
few technology combinations mass reduction has minimal impact on
effectiveness on the regulatory 2-cycle test. For example, if an engine
is operating in an efficient region of the fuel map on the 2-cycle test
further reduction of mass may have smaller improvement on the
regulatory cycles. Figure III-14 shows the range improvements based on
the full range of other technology combinations considered in the
analysis.
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[GRAPHIC] [TIFF OMITTED] TR02MY22.087

(e) Mass Reduction Costs
    The CAFE Model analysis handles mass reduction technology costs
differently than all other technology costs. Mass reduction costs are
calculated as an average cost per pound over the baseline (MR0) for a
vehicle's glider weight. While the definitions of glider may vary,
NHTSA uses the same dollar per pound of curb weight to develop costs
for different glider definitions. In translating these values, NHTSA
takes care to track units ($/kg vs. $/lb.) and the reference for
percentage improvements (glider vs. curb weight).
    NHTSA calculates the cost of mass reduction on a glider weight
basis so that the weight of each powertrain configuration can be
directly and separately accounted for. This approach provides the true
cost of mass reduction without conflating the mass change and costs
associated with downsizing a powertrain or adding additional advanced
powertrain technologies. Hence, the mass reduction costs in this final
rule reflect the cost of mass reduction in the glider and do not
include the mass reduction associated with engine downsizing. The mass
reduction and costs associated with engine downsizing are accounted for
separately.
    A second reason for using glider share instead of curb weight is
that it affects the absolute amount of curb weight reduction applied,
and therefore cost per pound for the mass reduction changes with the
change in the glider share. The cost for removing 20 percent of the
glider weight when the glider represents 75 percent of a vehicle's curb
weight is not the same as the cost for removing 20 percent of the
glider weight when the glider represents 50 percent of the vehicle's
curb weight. For example, the glider share of 79 percent of a 3,000-
pound curb weight vehicle is 2,370 lbs., while the glider share of 50
percent of a 3,000-pound curb weight vehicle is 1,500 lbs., and the
glider share of 71 percent of a 3,000-pound curb weight vehicle is
2,130 lbs. The mass change associated with 20 percent mass reduction is
474 lbs. for 79 percent glider share (= [3,000 lbs. x 79% x 20%]), 300
lbs. for 50 percent glider share (= [3,000 lbs. x 50% x 20%]), and 426
lbs. for 71 percent glider share (= [3,000 lbs. x 71% x 20%]). The mass
reduction cost studies that NHTSA relies on to develop mass reduction
costs for this analysis show that the cost for mass reduction varies
with the amount of mass reduction. Therefore, for a fixed glider mass
reduction percentage, different glider share assumptions will have
different costs.
    NHTSA considered several sources to develop the mass reduction
technology cost curves. Several mass reduction studies have used either
a mid-size passenger car or a full-size pickup truck as an exemplar
vehicle to demonstrate the technical and cost feasibility of mass
reduction. While the findings of these studies may not apply directly
to different vehicle classes, the cost estimates derived for the mass
reduction technologies identified in these studies can be useful for
formulating general estimates of costs. As discussed further below, the
mass reduction cost curves developed for this analysis are based on two
light-weighting studies, and NHTSA also updated the curves based

on more recent studies to better account for the cost of carbon fiber
needed for the highest levels of mass reduction technology. The two
studies used for MR1 through MR4 costs included the teardown of a MY
2011 Honda Accord and a MY 2014 Chevrolet Silverado pickup truck, and
the carbon fiber costs required for MR5 and MR6 were updated based on
the 2021 NAS Report.\455\
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    \455\ This analysis applied the cost estimates per pound derived
from passenger cars to all passenger car segments, and the cost
estimates per pound derived from full-size pickup trucks to all
light-duty truck and SUV segments. The cost estimates per pound for
carbon fiber (MR5 and MR6) were the same for all segments.
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    Both teardown studies are structured to derive the estimated cost
for each of the mass reduction technology levels. NHTSA relies on the
results of those studies because they considered an extensive range of
material types, material gauge, and component redesign while taking
into account real world constraints such as manufacturing and assembly
methods and complexity, platform-sharing, and maintaining vehicle
utility, functionality and attributes, including safety, performance,
payload capacity, towing capacity, handling, NVH, and other
characteristics. In addition, NHTSA believes that the baseline vehicles
and mass reduction technologies assessed in the studies are still
reasonably representative of the technologies that may be applied to
vehicles in the MY 2020 analysis fleet to achieve up to MR4 level mass
reduction in the rulemaking timeframe. NHTSA adjusted the cost
estimates derived from the two studies to reflect the assumption that a
vehicle's glider weight consisted of 71 percent of the vehicle's curb
weight, and mass reduction as it pertains to achieving MR0-MR6 levels
would only come from the glider.
    As discussed above, achieving the highest levels of mass reduction
often necessitates extensive use of advanced materials like higher
grades of aluminum, magnesium, or carbon fiber. We provided a survey of
information available regarding carbon fiber costs based on the Honda
Accord and Chevrolet Silverado teardown studies. In the Honda Accord
study, the estimated cost of carbon fiber was $5.37/kg, and the cost of
carbon fiber used in the Chevy Silverado study was $15.50/kg. The
$15.50 estimate closely matched the cost estimates from a BMW i3
teardown analysis,\456\ the cost figures provided by Oak Ridge National
Laboratory for a study from the IACMI Composites Institute,\457\ and
from a Ducker Worldwide presentation at the CAR Management Briefing
Seminar.\458\
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    \456\ Singh, Harry, FSV Body Structure Comparison with 2014 BMW
i3, Munro and Associates for World Auto Steel (June 3, 2015).
    \457\ IACMI Baseline Cost and Energy Metrics (March 2017),
available at https://iacmi.org/wp-content/uploads/2016/10/Dale-Brosius-IACMI-1.pdf (accessed Feb. 11, 2022).
    \458\ Ducker Worldwide, The Road Ahead--Automotive Materials
(2016), https://societyofautomotiveanalysts.wildapricot.org/resources/Pictures/SAA%20Sumit%20slides%20for%20Abey%20Abraham%20of%20Ducker.pdf,
(accessed: Feb. 11, 2022).
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    However, for this analysis, NHTSA relies on the cost estimates for
carbon fiber construction that NAS detailed in the 2021 Assessment of
Technologies for Improving Fuel Economy of Light-Duty Vehicles--Phase 3
recently completed by NAS.\459\ The study indicates that the sum of
direct materials costs plus manufacturing costs for carbon fiber
composite automotive components is $25.97 per pound in high volume
production. In order to use this cost in the CAFE Model it must be put
in terms of dollars per pound saved. Using an average vehicle curb
weight of 4000 lbs., a 71 percent glider share and the percent mass
savings associated with MR5 and MR6, it is possible to calculate the
number of pounds to be removed to attain MR5 and MR6. Also taken from
the NAS study is the assertion that carbon fiber substitution for steel
in an automotive component results in a 50 percent mass reduction.
Combining all this together, carbon fiber technology offers weight
savings at $24.60 per pound saved. This dollar per pound savings figure
must also be converted to a retail price equivalent (RPE) to account
for various commercial costs associated with all automotive components.
This is accomplished by multiplying $24.60 by the factor 1.5. This
brings the cost per pound saved for using carbon fiber to $36.90 per
pound saved.\460\ The analysis uses this cost for achieving MR5 and
MR6.
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    \459\ 2021 NAS Report, at p. 219.
    \460\ See MR5 and MR6 CFRP Cost Increase Calculator.xlsx in the
docket for this action.
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    Table III-23 and Table III-24 show the cost values (in dollars per
pound) used in the CAFE Model with MR1-4 costs based on the cost curves
developed from the MY 2011 Honda Accord and MY 2014 Chevrolet Silverado
studies, and the updated MR5 and MR6 values that account for the
updated carbon fiber costs from the 2021 NAS Report. Both tables assume
a 71 percent higher glider share.
[GRAPHIC] [TIFF OMITTED] TR02MY22.088

[GRAPHIC] [TIFF OMITTED] TR02MY22.089

    There is a dramatic increase in cost going from MR4 to MR5 and MR6
for all classes of vehicles. However, while the increase in cost going
from MR4 to MR5 and MR6 is dramatic, the MY 2011 Honda Accord study,
the MY 2014 Chevrolet Silverado study, and the 2021 NAS Report all
included a steep increase to achieve the highest levels of mass
reduction technology.
    Table III-25 provides an example of mass reduction costs in 2018$
over select model years for the medium car and pickup truck technology
classes as a dollar per pound value. The table shows how the $/lb.
value for each mass reduction level decreases over time because of cost
learning. For a full list of the $/lb. mass reduction costs used in the
analysis across all model years, see the Technologies file.
[GRAPHIC] [TIFF OMITTED] TR02MY22.090

BILLING CODE 4910-59-C
    NHTSA received comment from the ACC regarding the costs used in the
analysis for carbon fiber technology and how new precursors will soon
be available with high potential to reduce the cost of dry carbon
fibers.\461\ These precursor materials include, lignin, mesophase pitch
and textile-grade polyacrylonitrile (TG-PAN). Commenters specifically
referenced research conducted into these precursor materials conducted
at the Carbon Fiber Technology Facility at Oak Ridge National
Laboratory.
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    \461\ ACC, at p. 5.
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    Indeed, a factor that dominates the price of dry carbon fibers is
the precursor materials from which it is made. Dry carbon fibers that
are used in the mainstream automotive industry today, like those used
by BMW,\462\ are derived from high-molecular weight PAN fibers. The
high molecular weight of these materials not only makes the material
expensive, but it makes it more expensive to convert to carbon fiber
because it takes much longer to pyrolyze the fibers. However, the
result is a consistently stiff and incredibly high-strength fiber.
Prices today for traditional 3K tow (tow refers to the width of a
strand) PAN-based carbon fiber fall within the $20/kg to $40/kg
range.463 464 These price levels are consistent with NHTSA's
understanding and with the recent 2021 NAS Report.\465\
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    \462\ J. Sloan, ``Carbon Fiber Suppliers Gear up for Next
Generation Growth,'' compositesworld.com, February 11, 2020.
    \463\ Schlosser, Andreas, Coskun Baban, Samith, and Siedel
Phillipp, ``After the Hype: Where is the Carbon Car?'' Arthur D.
Little, January 2019.
    \464\ 2021 NAS Report, at pp. 218, 219, 419.
    \465\ Id.
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    The commenters mentioned several other advancements in carbon fiber
technologies that are under development; however, we do not believe
these materials will be available for use in the rulemaking timeframe.
Lignin, which is an organic substance found in the cells of plants, has
great potential to achieve affordable carbon fibers and could
potentially be a lower-cost alternative to PAN.466 467 While
lignin is renewable, recyclable, sustainable, and cost effective, there
are stiffness and cost issues with lignin and research into lignin-
based carbon fiber has significantly slowed.\468\ Similarly, mesophase
pitch and TG-PAN are encouraging mass reduction technologies; \469\
however, based on

their developmental nature we do not believe they will be available for
commercial application in this rulemaking timeframe. Therefore, we do
not believe that the lower costs cited in the ORNL studies are
representative of the costs to industry for carbon fiber technology in
the rulemaking timeframe. We will continue to closely monitor these new
fiber precursor materials and how they may enable low-cost carbon fiber
technology with competitive mechanical properties.
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    \466\ Azarova, M.T., Semakina, N.S., Konkin, A.A. Tikhomirova,
M.V. ``Carbon Fiber Based on Meso-Phase-Pitches,'' Fiber Chemistry,
1982, pp. 103-110.
    \467\ Kadla, J.F, et al., ``Lignin-Based Carbon Fibers for
Composite Applications,'' Carbon, Vol. 20, 2002, pp. 2913-2920.
    \468\ For example, one issue with lignin-based carbon fiber is
that the density specific stiffness of fully pyrolyzed lignin-based
carbon fiber laminated in an epoxy matrix (which is a materials
property that often dominates mass reduction potential) is barely
competitive with that of steel. Yet steel costs about $1/kg--$3/kg.
Furthermore, because the absolute stiffness of lignin-based carbon
fiber composite material is low, a component made with lignin-based
carbon fiber composite material will require more packaging space
than a steel component to achieve equivalent component level
stiffness.
    \469\ Mesophase pitch is made from coal which is plentiful and
therefore low cost, and the material has a density specific
stiffness better than steel, aluminum, and magnesium. TG-PAN has a
molecular weight that is about half that of traditional PAN
materials used from making carbon fiber and consequently requires
less time to pyrolyze, thus reducing its costs. In addition, textile
grade PAN is available in much wider tows (>= 50k) than traditional
PAN which means that more material can be converted to carbon fiber
in less time.
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    Aside from precursor materials issues, how dry carbon fibers are
processed into usable carbon fiber composite components is also an
important cost driver that we do not believe is represented in the
lower cited cost estimates. As an example, the carbon fiber composite
parts used on the BMW i3 are manufactured with cycle times between five
and ten minutes,\470\ while precise and accurate metallic parts are
produced in seconds.
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    \470\ Sloan, Jeff, ``BMW Leipzig: The Epicenter of i3
Production,'' Composites World, May 31, 2014.
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    Again, we will continue to monitor composite materials processing
technology advances and make cost adjustments in future analysis to
reflect advances in this field.
Aerodynamics
    The energy required to overcome aerodynamic drag accounts for a
significant portion of the energy consumed by a vehicle and can become
the dominant factor for a vehicle's energy consumption at high speeds.
Reducing aerodynamic drag can, therefore, be an effective way to reduce
fuel consumption and emissions.
    Aerodynamic drag is proportional to the frontal area (A) of the
vehicle and coefficient of drag (Cd), such that aerodynamic performance
is often expressed as the product of the two values, CdA, which is also
known as the drag area of a vehicle. The coefficient of drag (Cd) is a
dimensionless value that essentially represents the aerodynamic
efficiency of the vehicle shape. The frontal area (A) is the cross-
sectional area of the vehicle as viewed from the front. It acts with
the coefficient of drag as a sort of scaling factor, representing the
relative size of the vehicle shape that the coefficient of drag
describes. The force imposed by aerodynamic drag increases with the
square of vehicle velocity, accounting for the largest contribution to
road loads at higher speeds.
    Aerodynamic drag reduction can be achieved via two approaches,
either by reducing the drag coefficient or reducing vehicle frontal
area, with two different categories of technologies, passive and active
aerodynamic technologies. Passive aerodynamics refers to aerodynamic
attributes that are inherent to the shape and size of the vehicle,
including any components of a fixed nature. Active aerodynamics refers
to technologies that variably deploy in response to driving conditions.
These include technologies such as active grille shutters, active air
dams, and active ride height adjustment. It is important to note that
manufacturers may employ both passive and active aerodynamic
technologies to achieve aerodynamic drag improvements.
    The greatest opportunity for improving aerodynamic performance is
during a vehicle redesign cycle when the manufacturer can make
significant changes to the shape and size of the vehicle. A
manufacturer may also make incremental improvements during mid-cycle
vehicle refresh using restyled exterior components and add-on devices.
Some examples of potential technologies that a manufacturer could apply
during mid-cycle refresh are restyled front and rear fascia, modified
front air dams and rear valances, addition of rear deck lips and
underbody panels, and low-drag exterior mirrors. While manufacturers
may nudge the frontal area of the vehicle during redesigns, large
changes in the frontal area are typically not possible without
impacting the utility and interior space of the vehicle. Similarly,
manufacturers may improve Cd by changing the frontal shape of the
vehicle or lowering the height of the vehicle, among other approaches,
but the form drag of certain body styles and airflow needs for engine
cooling often limit how much manufacturers can improve Cd.
    The following sections discuss the four levels of aerodynamic
improvements that we consider in the CAFE Model, how we assign baseline
aerodynamic technology levels to vehicles in the MY 2020 fleet, the
effectiveness improvements for the addition of aerodynamic technologies
to vehicles, and the costs for adding that aerodynamic technology.
(a) Aerodynamic Technologies in the CAFE Model
    We bin aerodynamic improvements into four levels--5, 10, 15, and 20
percent aerodynamic drag improvement values over a baseline computed
for each vehicle body style--which correspond to AERO5, AERO10, AERO15,
and AERO20, respectively.
    The aerodynamic improvements technology pathway consists of a
linear progression, with each level superseding all previous levels, as
seen in Figure III-15.
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[GRAPHIC] [TIFF OMITTED] TR02MY22.091

    While the four levels of aerodynamic improvements are technology-
agnostic, we built a pathway to compliance for each level based on
aerodynamic data from a National Research Council (NRC) of Canada-
sponsored wind tunnel testing program. The program included an
extensive review of production vehicles utilizing these technologies,
and industry comments.471 472 Again, these technology
combinations are intended to show a potential way for a manufacturer to
achieve each aerodynamic improvement level; however, in the real world,
manufacturers may implement different combinations of aerodynamic
technologies to achieve a percentage improvement over their baseline
vehicles.
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    \471\ Larose, G., Belluz, L., Whittal, I., Belzile, M. et al.,
``Evaluation of the Aerodynamics of Drag Reduction Technologies for
Light-duty Vehicles--a Comprehensive Wind Tunnel Study,'' SAE Int.
J. Passeng. Cars--Mech. Syst. 9(2):772-784, 2016, https://doi.org/10.4271/2016-01-1613, (accessed: Feb. 11, 2022).
    \472\ Larose, Guy & Belluz, Leanna & Whittal, Ian & Belzile,
Marc & Klomp, Ryan & Schmitt, Andreas. (2016). Evaluation of the
Aerodynamics of Drag Reduction Technologies for Light-duty
Vehicles--a Comprehensive Wind Tunnel Study. SAE International
Journal of Passenger Cars--Mechanical Systems. 9. 10.4271/2016-01-
1613.
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    Table III-26 and Table III-27 show the aerodynamic technologies
that could be used to achieve 5, 10, 15, and 20 percent improvements in
passenger cars, SUVs, and pickup trucks. As discussed further in
Section III.D.5.c), the model does not apply AERO20 to pickup trucks,
which is why there is no pathway to AERO20 shown in Table III-27. While
manufacturers can apply some aerodynamic improvement technologies
across vehicle classes, like active grille shutters (used in the 2015
Chevrolet Colorado),\473\ we determined that there are limitations that
make it infeasible for vehicles with some body styles to achieve a 20
percent reduction in the coefficient of drag from their baseline. This
technology path is an example of how a manufacturer could reach each
AERO level, but they would not necessarily be required to use the
technologies.
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    \473\ Chevrolet Product Information, available at https://media.chevrolet.com/content/media/us/en/chevrolet/vehicles/colorado/2015/_jcr_content/iconrow/textfile/file.res/15-PG-Chevrolet-Colorado-082218.pdf, (accessed: Feb. 11, 2022).

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[GRAPHIC] [TIFF OMITTED] TR02MY22.093

    As discussed further in Section III.D.8, this analysis assumes
manufacturers apply off-cycle technology at rates defined in the Market
Data file. While the AERO levels in the analysis are technology-