Publication Detail
Battery Prognostics and Health Management for Electric Vehicles Under Industry 4.0
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UCD-ITS-RP-23-92 Journal Article Sustainable Transportation Energy Pathways (STEPS)
Available online at
https://doi.org/10.1016/j.jechem.2023.04.042
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Suggested Citation:
Zhao, Jingyuan and Andrew Burke (2023) Battery Prognostics and Health Management for Electric Vehicles Under Industry 4.0. Journal of Energy Chemistry 84
Industry 4.0 has brought about breakthroughs in battery prognostics and health management, ensuring the reliability, safety, and optimal performance of batteries in electric vehicle applications.
Key words: lithium-ion battery, prognostics and health management, machine learning, cloud, artificial intelligence, digital twins, lifelong learning
Key words: lithium-ion battery, prognostics and health management, machine learning, cloud, artificial intelligence, digital twins, lifelong learning