LAUSR

Abstract For the safe operation of electric vehicles, it is of critical importance to quickly detect and accurately identify different types of faults in battery packs. However, the performance characteristics of many faults in the battery system are hidden and similar, therefore a false positive fault detection happens occasionally. This paper presents a multi-fault diagnostic strategy based on an interleaved voltage measurement topology and improved correlation coefficient method, which can diagnose several types of faults (i.e. the internal/external short circuit, sensor faults and connection faults). The proposed voltage measurement method can correlate each battery and contact resistance with two different sensors respectively, so as to accurately identify the location and type of the faults. In order to eliminate the effect of battery inconsistencies and measurement error, the improved correlation coefficient method is utilized to monitor fault signatures. The non-model method proposed in this paper can avoid the aliasing phenomenon and has high sensitivity and robustness. Both theoretical analysis and experimental results validate the feasibility and advantages of the multi-fault diagnostic method.