Adaptive Extended Kalman Filter Based Fault Detection and Isolation for a Lithium-Ion Battery Pack

To monitor the battery system, a well-designed battery management system with a set of current and voltage sensors is demanded to properly track the battery properties. It is imperative to design a reliable and robust diagnostic scheme in case of the employed sensors faults occurred. This paper presents a model-based fault diagnosis scheme to detect and isolate the faults of the current and voltage sensors applied in the series battery pack based on an adaptive extended kalman filter, and the robustness of the proposed diagnostic strategy is ensured. The diagnostic scheme is validated in the Matlab/Simulink, and the simulation results show the effectiveness of the proposed strategy in detecting and isolating various fault scenarios using the real-world driving cycles.