Micro-short circuit fault diagnosis of the parallel battery module based on increment capacity curve

Compared to individual cells and series packs, parallel battery modules (PBM) bring more difficult challenges to fault diagnosis due to the particularity of their structure and the self-balancing of each cell. In this paper, the PBM's micro-short circuit (MSC) fault diagnosis tests are firstly designed. Experimental results show that the smaller the short circuit resistance is, the greater the voltage curve deviates between the short circuit and the standard conditions. Moreover, the fault voltage curve of the parallel module shows less deviation from the standard voltage curve compared to the cells under the same conditions. Then, a fault simulation model for the PBM is built which is taken the resistance of the connector into consideration. Subsequently, the terminal voltage curve and incremental capacity (IC) curve characteristics of the PBM at different micro-shorted fault are analyzed. The results show that the difference of the fault characteristic peaks of the charge IC curve at a low C-rate is more noticeable. Next, effective feature peaks for fault diagnosis are obtained by discussing the feasibility of different peaks. Further, the MSC fault of the parallel module is quantitatively diagnosed by analyzing the relationship between the amplitude of Peak III and Peak IV on the IC curve and short circuit resistance. It is found that the results of Peak IV diagnosis are more stable. Finally, a model-driven online calculated process of short circuit resistance in application is proposed and it has been verified for accuracy and robustness, with maximum diagnostic error of 6.06 %. •A simulation model of the PBM is built considering the connector resistance.•Number of batteries and charge rate on IC curve characteristic is analyzed.•A quantitative diagnostic method based on the amplitude of the peak is proposed.•A model-driven online diagnosis process is proposed in application.