AI-driven sustainability assessment for greener lithium-ion batteries

Abstract

Lithium-ion batteries (LIBs) are pivotal for electric vehicles and energy storage, yet their sustainability assessment is hindered by methodological limitations. Artificial intelligence (AI) is poised to transform lifecycle assessment (LCA) paradigms for LIBs. This study employs strengths, weaknesses, opportunities and threats analysis to comprehensively examine the role and prospects of AI for LCA in LIBs. The objective is to capitalize on the technology's strengths, mitigate its weaknesses, and identify potential opportunities and threats. Furthermore, this research proposes future studies to enhance the application of AI in the LCA of LIBs, including the establishment of unified standards for data collection, processing, and sharing, improving data transparency, promoting interdisciplinary collaboration, and developing more robust AI models. This study will provide a scientific reference for the research on efficient, scalable, and automated sustainability assessment methods in LIBs, driving the battery and transportation toward more sustainable development.

Keywords

Artificial intelligence / life cycle assessment / lithium-ion battery / SWOT analysis

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