Fault Diagnosis for Parallel Lithium-Ion Battery Packs with Main Current Sensor Fault and Internal Resistance Fault

This paper investigates the fault diagnosis scheme for parallel lithium-ion battery packs with main current sensor fault and battery internal resistance (BIR) fault. First of all, an equivalent circuit model of a single cell battery is established, which paves the way for constructing a state space model of parallel lithium-ion battery packs. Based on it, an adaptive Kalman filter is designed to estimate the gain loss coefficient of the main current sensor fault. More importantly, the proposed method enables to use the estimated fault information to achieve the fault-tolerant estimate for state-of-charge. For a BIR fault, a data-driven fault detection approach using stable kernel representation is developed from a residual generation point of view. To reduce fault false alarms, a detection residual evaluator is designed to meet the desired performance requirement. Finally, experiments and comparisons are implemented to indicate the effectiveness of our scheme and its outperformance over existing fault detection methods.