Learning only buys you so much: practical limits on battery price reduction
Name
LearningOnlyBuysSoMuch_revised.pdf
Description
Accepted version
Size
901.74 KB
Format
Adobe PDF
Checksum (MD5)
86200218b897f3c8868beb73912d957f
Author(s)
Hsieh, I-Yun Lisa
Pan, Menghsuan Sam
Chiang, Yet-Ming
Green Jr, William H
Alternative Title
Learning only buys you so much: Practical limits on battery price reduction
Date Issued
April 2019
Journal
Applied Energy
Publisher
Elsevier BV
Citation
Hsieh, I-Yun Lisa et al. "Learning only buys you so much: Practical limits on battery price reduction." Applied Energy, 239 (April 2019): 218-224.
Version
Author's final manuscript
Abstract
Wide deployment of electric vehicles (EVs) would greatly facilitate global de-carbonization, but achieving the emission targets depends on future battery prices. Conventional learning curves for manufacturing costs, used in many battery projections, unrealistically predict battery prices will fall below $100/kWh by 2030, pushing EVs to hit price parity with internal combustion engine vehicles (ICEVs) in the absence of incentives. However, in reality, essential materials costs set practical lower bounds on battery prices. Our 2-stage learning curve model projects the active material costs and NMC-based Lithium-ion battery pack price with mineral and material costs as the respective price floors. The improved model predicts nickel-manganese-cobalt (NMC) battery prices will fall only to about $124/kWh by 2030 – much cheaper than today, but still too expensive to truly compete with ICEVs, due primarily to the high prices of cobalt, nickel, and lithium. Our results suggest that stabilizing raw materials prices and/or stimulating R&D activities on alternative battery chemistries will be important to achieve environmentally sustainable EV-based ground transportation at an attractive price. Keyword: Energy science; Battery technology; Energy storage; Energy economics; Electro mobility
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.apenergy.2019.01.138
