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

This article investigates the fault diagnosis scheme for parallel lithium-ion battery packs with main current sensor fault and battery internal resistance (BIR) fault. First, 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 (AKF) is designed to estimate the gain loss coefficient (GLC) of the main current sensor fault. More importantly, the proposed method enables to use the estimated fault information to achieve the fault-tolerant estimate (FTE) for state-of-charge. For a BIR fault, a data-driven fault detection (FD) approach using stable kernel representation is developed from a residual generation point of view. To reduce fault false alarms, a detection residual evaluator (DRE) 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 FD methods.