Driven by the global energy transition and the “dual carbon” goals, lithium‐ion battery energy storage systems (BESS) have become critical infrastructure for stabilizing new power systems, owing to their high energy density and rapid response. However, their safe operation faces significant challenges, necessitating the development of fast, accurate, and reliable fault diagnosis and early warning technologies. This article systematically reviews typical fault types and their causes in BESS, from individual cells to the system level. Based on the temporal fault evolution sequence—early‐stage anomalies, transient faults, to system failures—it analyzes the failure mechanisms under multiphysics coupling effects. The study focuses on reviewing research progress and application status of fault monitoring and early warning methods, including threshold‐based and multisensor techniques, data‐driven approaches, and model‐based strategies. Finally, it identifies current bottlenecks in sensor deployment, real‐time diagnosis, and model fusion, and proposes future research directions focusing on intelligent sensing, cloud‐edge coordination, and the deep integration of AI algorithms with physical models, aiming to provide theoretical support and methodological references for enhancing BESS safety.
Yao et al. (Sun,) studied this question.