Predicting SoH and RUL of Li-ion Batteries in Electric Vehicles: A Comprehensive Review and Chemistry Insights

The State-of-Health (SoH) and Remaining Useful Life (RUL) estimation of Lithium-Ion Batteries (LIBs) in Electric Vehicles (EVs) is a critical aspect of Battery Management Systems (BMS) to ensure reliable and efficient operation. This comprehensive review presents an overview of the various methods and techniques employed for predicting the SoH and RUL of LIBs in EVs, with a focus on the chemistry insights involved. The review covers different approaches such as data-driven and physics-based, highlighting their advantages and limitations. Key indicators used for SoH and RUL estimation are discussed, including capacity fade, impedance analysis, voltage decay, and aging mechanisms. Furthermore, the influence of operating conditions, such as temperature, cycling profiles, and Depth of Discharge (DoD), on battery degradation and performance degradation are examined. The review also delves into the challenges and future directions in SoH and RUL prediction, emphasizing the need for advanced modeling, real-time monitoring, and integration of multiple data sources for accurate and reliable predictions. The insights provided in this review aim to contribute to the development of more effective strategies for assessing and managing the health and lifespan of LIBs in the context of EV applications.