Fault mitigation and diagnosis for lithium-ion batteries: a review

Due to their high energy density, long life cycle, minimal self-discharge (SD), and environmental benefits, lithium-ion batteries (LIBs) have become increasingly prevalent in electronics, electric vehicles (EVs), and grid support systems. However, their usage also brings about heightened safety concerns and potential hazards. Therefore, it is crucial to promptly identify and diagnose any issues arising within these batteries to mitigate risks. Early detection and diagnosis of faults such as Battery Management Systems (BMS) malfunctions, internal short circuits (ISC), overcharging, over-discharging, aging effects, and thermal runaway (TR) are essential for mitigating these risks and preventing accidents. This study aims to provide a comprehensive overview of fault diagnosis by meticulously examining prior research in the field. It begins with an introduction to the significance of LIBs, followed by discussions on safety concerns, fault diagnosis, and the benefits of such diagnostic approaches. Subsequently, each fault is thoroughly examined, along with discussions on methods for detection and diagnosis, including both model-based and non-model-based approaches. Additionally, the study elevates the role of cloud-based technologies for real-time monitoring and enhancing fault mitigation strategies. The results show how well these approaches work to increase LIB systems’ safety, dependability, and economic feasibility while emphasizing the necessity for sophisticated diagnostic methods to support their growing use in a variety of applications.