Voltage-correlation based multi-fault diagnosis of lithium-ion battery packs considering inconsistency

Fast and accurate fault diagnosis is of great significance for the safe operation of lithium-ion batteries. The fault diagnosis method based on correlation coefficients solves the problem of the heavy calculation burden of the model-based diagnostic method. However, the inconsistencies that affect the accuracy and speed of diagnosis are ignored in the existing studies on correlation-based fault diagnosis. In this study, the influence of inconsistencies in resistance and state of charge on the correlation coefficients was considered to improve the accuracy and speed of diagnosis. Voltage sensor faults, connection faults, and short-circuit faults were detected and isolated according to the correlation coefficients and variation in the voltage difference. The cells were arranged in ascending order of the initial voltages, and every three cells were divided into a group. Only two correlation coefficients were calculated for each group. The accuracy and speed of diagnosis were improved by considering the inconsistencies. By grouping cells and introducing a new fault index, which is the variation in the voltage difference, the calculation burden was reduced by more than 50%. The diagnostic method was validated through experiments on a series-connected battery pack.