Breaking it down: A techno-economic assessment of the impact of battery pack design on disassembly costs
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Published version
Author(s)
Type
Journal Article
Abstract
The electrification of the transport sector is a critical part of the net-zero transition. The mass adoption of electric vehicles (EVs) powered by lithium-ion batteries in the coming decade will inevitably lead to a large amount of battery waste, which needs handling in a safe and environmentally friendly manner. Battery recycling is a sustainable treatment option at the battery end-of-life that supports a circular economy. However, heterogeneity in pack designs across battery manufacturers are hampering the establishment of an efficient disassembly process, hence making recycling less viable. A comprehensive techno-economic assessment of the disassembly process was conducted, which identified cost hotspots in battery pack designs and to guide design optimisation strategies that help save time and cost for end-of-life treatment. The analyses include six commercially available EV battery packs: Renault Zoe, Nissan Leaf, Tesla Model 3, Peugeot 208, BAIC and BYD Han. The BAIC and BYD battery packs exhibit lower disassembly costs (US$50.45 and US$47.41 per pack, respectively), compared to the Peugeot 208 and Nissan Leaf (US$186.35 and US$194.11 per pack, respectively). This variation in disassembly cost is due mostly to the substantial differences in number of modules and fasteners. The economic assessment suggests that full automation is required to make disassembly viable by 2040, as it could boost disassembly capacity by up to 600 %, while substantially achieving cost savings of up to US$190 M per year.
Date Issued
2023-02
Date Acceptance
2022-11-25
Citation
Applied Energy, 2023, 331, pp.1-9
ISSN
0306-2619
Publisher
Elsevier BV
Start Page
1
End Page
9
Journal / Book Title
Applied Energy
Volume
331
Copyright Statement
© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
https://www.sciencedirect.com/science/article/pii/S0306261922016944?via%3Dihub
Publication Status
Published
Article Number
120437
Date Publish Online
2022-12-05