Review of Abnormality Detection and Fault Diagnosis Methods for Lithium-Ion Batteries

Electric vehicles are developing prosperously in recent years. Lithium-ion batteries have become the dominant energy storage device in electric vehicle application because of its advantages such as high power density and long cycle life. To ensure safe and efficient battery operations and to enable timely battery system maintenance, accurate and reliable detection and diagnosis of battery faults are necessitated. In this paper, the state-of-the-art battery fault diagnosis methods are comprehensively reviewed. First, the degradation and fault mechanisms are analyzed and common abnormal behaviors are summarized. Then, the fault diagnosis methods are categorized into the statistical analysis-, model-, signal processing-, and data-driven methods. Their distinctive characteristics and applications are summarized and compared. Finally, the challenges facing the existing fault diagnosis methods are discussed and the future research directions are pointed out.