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Mudit Chordia’s Licentiate Seminar: Taking Stock of Large-scale Lithium-ion Battery Production Using Life Cycle Assessment
29 September, 2022,13:00-15:00
Mudit Chordia is a third-year PhD student at the Division of Environmental Systems Analysis, Chalmers. Mudit’s main area of research is understanding the environmental implications of upscaling lithium-ion battery (LIB) production. Further, to understand the impacts of upscaling LIB production on the supply chain of battery materials, Mudit has investigated the current and future supply routes of lithium. He is currently working on a cross-disciplinary project to develop a physics-based model for filling data gaps in the life cycle assessment of LIBs. Post-licentiate, Mudit aims to investigate the effects of upscaling LIB recycling. Mudit’s project is connected to the thematic area, “Environment and Society”.
Battery electric vehicles are being increasingly favored as an alternative to internal combustion engine vehicles (ICEVs). This is mainly due to their lower environmental impact when compared to ICEVs over the vehicle’s lifetime. Life cycle assessment (LCA) studies focusing specifically on battery electric vehicles (BEVs) have identified battery cell production as an environmental hotspot in the BEV’s life cycle. However, lack of primary or industrial data, different technical scopes, and varying data quality, limit a thorough understanding of the environmental impacts of cell production. Further, with scaling- up of battery production (to meet the rising demand for BEVs), the source and level of impacts are expected to change. In response, the main aim of this thesis is to explore and understand the implications of upscaling in battery production. An example of such a change is provided at the mining sites where raw materials for lithium used in batteries are extracted and produced. As mining continues, over time, the ore grades at these sites decline. Thus, this thesis also aims to investigate the effect of declining ore grades on the overall impacts from cell production. A sub-goal is to understand the relevance of background data in LCA studies and its effect on overall results.
The technical scope of this thesis is the production of a graphite-NMC:811 21700 type cylindrical cell. To assess the environmental impacts of upscaling, production in a small-scale facility is compared to production in a large-scale facility. Next, the impact of declining ore grades on overall cell production is estimated by analyzing the data from multiple mining sites for lithium, with varying ore grades and different types of sources – spodumene and brine. To assess the effect of background database on overall results, the LCA model for cell production was coupled with different versions of the Ecoinvent background database. Lastly, a physics-based model platform, developed in cross-disciplinary collaboration, is proposed with the objective of filling data gaps in LCA of lithium-ion batteries (LIBs). The model platform will help link the cell design aspects such as power or energy optimization to changes in the individual cell production processes. Further, the model platform will help expand the technical scope to broadened set of cell geometries and chemistries, and increase the precision in use phase modeling as well.
The results show that the upscaling leads to a reduction in environmental impacts from cell production. This is due to higher energy and material efficiency of cell production at large scale. Further, when low- carbon intensive sources are used, then the impacts from cell production shift almost entirely to the raw material extraction and production phase. In the context of declining ore grades, the type of source and grade of lithium account for 5-15% of the global warming impacts from cell production. This implies that future environmental impacts from LIB production could increase, due to increased chemical and energy inputs, in response to declining ore grades at mining sites. The changes in the background data have a significant bearing on the overall results. These are due to evolving technical systems and an improved representation of these systems in terms of data quality and geo-spatial representativeness. Lastly, preliminary results from the physics-based model platform show that accounting for variations in cell design can further add variability in results.
Link to the licentiate thesis: https://research.chalmers.se/en/publication/531923
Discussion leader: Jennifer Dunn, Associate Professor, Northwestern University, USA
Venue: HA2 is located on Chalmers’ Campus Johanneberg. Go to building Hörsalar HA. Entrance from Hörsalsvägen 4.
Supervisors: Anders Nordelöf and Rickard Arvidsson
Examiner: Björn Sandén
For further information please contact firstname.lastname@example.org