Life Cycle Assessment of Lithium-Ion Batteries

Abstract

The rapid growth of electric vehicles (EVs) has increased the importance of understanding the environmental impacts associated with lithium-ion battery (LIB) production. Life cycle assessment (LCA) is widely used to evaluate these impacts, but previous studies report large variations in results due to differences in methodological choices, such as system boundaries, data sources, and modelling assumptions. In addition, module and pack assembly processes are often inconsistently and insufficiently represented in existing literature. This thesis investigates how existing LIB LCA studies differ regarding methodological approaches, data gaps, and reported environmental impacts, while also suggesting how the modelling of module and pack assembly processes can be improved. The study was carried out through three main steps: a state-of-the-art review, benchmarking of selected LIB LCA studies, and the development of a model for module and pack assembly. The benchmarking compared studies across several parameters, such as system boundaries, functional units (FUs), electricity mixes, life cycle impact assessment (LCIA) methods, transparency, and environmental impacts across several impact categories. In addition, process mapping and data collection were carried out for module and pack assembly to develop a more transparent and structured modelling approach for these stages. The results show large methodological variations across the reviewed studies and the differences strongly influenced the reported environmental impacts and often limited comparability between studies. In some cases, variation within the same battery chemistry was larger than the variation between different chemistries, indicating that methodological choices can influence results as much as the battery chemistry itself. Cathode production was identified as the most common environmental hotspot. The analysis also highlighted significant challenges related to data availability and transparency. Many studies relied heavily on secondary data, while representative industrial primary data remained limited. The findings of this thesis demonstrate the need for improved transparency, consistent methodological approaches, and better access to representative primary data in order to increase the robustness and comparability of future LIB LCAs.