Robust SOC estimation for lithium-ion batteries under faulty charging scenarios using sliding mode observer techniques

Abstract

With the growing demand for electric vehicles, embedded electronics, and renewable energy applications, lithium-ion batteries have become an essential component in modern energy storage systems. Accurate state of charge (SOC) estimation is crucial for ensuring battery reliability, longevity, and safety, particularly under faulty charging conditions—a challenge where many conventional estimation techniques fall short due to model limitations or lack of robustness. In this study, we propose an advanced SOC estimation approach based on a sliding mode observer (SMO) integrated with a third-order equivalent circuit model (ECM). Unlike conventional methods, which either focus on SOC estimation without considering battery voltage or apply SMO techniques only to second-order models, our approach enhances estimation accuracy by incorporating a higher-order model that better captures the complex battery dynamics. The proposed methodology is tested under both normal and faulty charging conditions, demonstrating superior performance in estimating both SOC and terminal voltage over extended periods. The simulation results confirm the robustness of the method, with accurate SOC tracking even in the presence of charging current faults, making it a viable solution for real-world applications in battery management systems (BMS). This work contributes to improving fault-tolerant SOC estimation strategies, advancing the development of safer and more efficient energy storage technologies.