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Energies
Volume 10
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10.3390/en10091314
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Article

Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030

by
Gert Berckmans
*,
Maarten Messagie
,
Jelle Smekens
,
Noshin Omar
,
Lieselot Vanhaverbeke
and
Joeri Van Mierlo
MOBI Research Group, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
*
Author to whom correspondence should be addressed.
Energies 2017, 10(9), 1314; https://doi.org/10.3390/en10091314
Submission received: 20 July 2017 / Revised: 22 August 2017 / Accepted: 24 August 2017 / Published: 1 September 2017
(This article belongs to the Section D: Energy Storage and Application)
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Abstract

The negative impact of the automotive industry on climate change can be tackled by changing from fossil driven vehicles towards battery electric vehicles with no tailpipe emissions. However their adoption mainly depends on the willingness to pay for the extra cost of the traction battery. The goal of this paper is to predict the cost of a battery pack in 2030 when considering two aspects: firstly a decade of research will ensure an improvement in material sciences altering a battery’s chemical composition. Secondly by considering the price erosion due to the production cost optimization, by maturing of the market and by evolving towards to a mass-manufacturing situation. The cost of a lithium Nickel Manganese Cobalt Oxide (NMC) battery (Cathode: NMC 6:2:2 ; Anode: graphite) as well as silicon based lithium-ion battery (Cathode: NMC 6:2:2 ; Anode: silicon alloy), expected to be on the market in 10 years, will be predicted to tackle the first aspect. The second aspect will be considered by combining process-based cost calculations with learning curves, which takes the increasing battery market into account. The 100 dollar/kWh sales barrier will be reached respectively between 2020-2025 for silicon based lithium-ion batteries and 2025–2030 for NMC batteries, which will give a boost to global electric vehicle adoption.
Keywords: process-based cost modeling; NMC battery; silicon lithium-ion battery; market prediction; learning curves process-based cost modeling; NMC battery; silicon lithium-ion battery; market prediction; learning curves

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MDPI and ACS Style

Berckmans, G.; Messagie, M.; Smekens, J.; Omar, N.; Vanhaverbeke, L.; Van Mierlo, J. Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030. Energies 2017, 10, 1314. https://doi.org/10.3390/en10091314

AMA Style

Berckmans G, Messagie M, Smekens J, Omar N, Vanhaverbeke L, Van Mierlo J. Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030. Energies. 2017; 10(9):1314. https://doi.org/10.3390/en10091314

Chicago/Turabian Style

Berckmans, Gert, Maarten Messagie, Jelle Smekens, Noshin Omar, Lieselot Vanhaverbeke, and Joeri Van Mierlo. 2017. "Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030" Energies 10, no. 9: 1314. https://doi.org/10.3390/en10091314

APA Style

Berckmans, G., Messagie, M., Smekens, J., Omar, N., Vanhaverbeke, L., & Van Mierlo, J. (2017). Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030. Energies, 10(9), 1314. https://doi.org/10.3390/en10091314

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