Production Volume Assumptions

Studies of industrial learning-by-doing (or impact of research and development [R&D] and spillovers from other industries) have found industries tend to improve with production volume; the resulting learning curves can be used to estimate future improvement based on historical trends. The effects of learning curves saturate, declining as the volume of production increases. In the Transportation Annual Technology Baseline (ATB), learning effects are considered for both vehicles and fuels.

For vehicles, the threshold for high volume is 100,000 units/year, as assumed by James et al. (James et al., 2023). Above this threshold, additional volume of vehicle production is assumed not to affect modeled vehicle price. This threshold is a small fraction of light-duty vehicle sales in the United States. In the light-duty market, hybrid, plug-in-hybrid, and battery electric vehicles (BEVs) have already reached this threshold as of 2022 and are therefore assumed to be manufactured at high volume. We also assume medium- and heavy-duty hybrid, plug-in hybrid, and BEVs benefit from the economies of scale achieved by light-duty BEVs. Battery assumptions in the Autonomie model refer to the International Council on Clean Transportation (ICCT) E-Truck Virtual Teardown Study (ICCT, 2021) for the difference in the Base Year costs (Islam et al., 2023). Not all powertrains may reach high production volume if certain powertrains appeal to the same, smaller consumer segment. Notably, fuel cell electric vehicles are assumed to be produced at low volumes and their costs include a low production volume cost multiplier that decays with increasing assumed production volume. Vehicle assumptions in the Autonomie model are adjusted to reflect U.S. Department of Energy (DOE) National Clean Hydrogen Strategy and Roadmap values (DOE, 2022) (Islam et al., 2023). The details are discussed previously in the definition for Fuel Cell Electric Vehicles.

For fuels, we specify high or low volume of production of the specific fuel pathway; see Fuel Scenarios.

References

The following references are specific to this page; for all references in this ATB, see References.

James, Brian, Jennie M Huya-Kouadio, Cassidy Houchins, Rajesh Ahluwalia, Xiaohua Wang, Michael Ulsh, Gary Robb, David Masten, Christian Appel, and Vivek Murthi. “Heavy-Duty Fuel Cell System Cost – 2022.” DOE Hydrogen Program Record. DOE Hydrogen and Fuel Cells Technology Office, May 30, 2023. https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/23002-hd-fuel-cell-system-cost-2022.pdf?Status=Master.

ICCT. “E-Truck Virtual Teardown Study,” June 11, 2021. https://theicct.org/wp-content/uploads/2022/01/Final-Report-eTruck-Virtual-Teardown-Public-Version.pdf.

Islam, Ehsan Sabri, Daniela Nieto Prada, Ram Vijayagopal, Charbel Mansour, Paul Phillips, Namdoo Kim, Michel Alhajjar, and Aymeric Rousseau. “Detailed Simulation Study to Evaluate Future Transportation Decarbonization Potential.” Report to the US Department of Energy, Contract ANL/TAPS-23/3. Argonne National Laboratory (ANL), Argonne, IL (United States), October 2023. https://anl.app.box.com/s/hv4kufocq3leoijt6v0wht2uddjuiff4.

DOE. “DOE National Clean Hydrogen Strategy and Roadmap,” September 2022. https://www.hydrogen.energy.gov/docs/hydrogenprogramlibraries/pdfs/clean-hydrogen-strategy-roadmap.pdf?Status=Master.