Advanced data-driven fault diagnosis in lithium-ion battery management systems for electric vehicles: Progress, challenges, and future perspectives

Hazards in electric vehicles (EVs) often stem from lithium-ion battery (LIB) packs during operation, aging, or charging. Robust early fault diagnosis algorithms are essential for enhancing safety, efficiency, and reliability. LIB fault types involve internal batteries, sensors, actuators, and system...

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Bibliographic Details

Main Authors:	Abdolrasol M.G.M., Ayob A., Lipu M.S.H., Ansari S., Kiong T.S., Saad M.H.M., Ustun T.S., Kalam A.
Other Authors:	35796848700
Format:	Review
Published:	Elsevier B.V. 2025
Subjects:	Battery management systems Battery Management Data driven Data-driven fault diagnosis Fault types Faults diagnosis Future perspectives Ion batteries Lithium ions Machine-learning Management systems Battery Pack
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