Fuzzy-Kalman-Filter-Based Short-Circuit Fault Diagnosis Design for Lithium-Ion Battery
Haodong Zhang, Zhitao Liu, Hongye Su
Abstract
In this article, the health difference feedback model (HDFM) is proposed to diagnose the internal short-circuit fault of a lithium-ion battery. The HDFM combines the mean model with the median model. The algorithm uses the fuzzy Kalman filter with feedback to solve the problem of inaccurate estimation in the low-state-of-charge region and the influence of short-circuit current on the battery model. Through comparison and verification, the HDFM algorithm has all the advantages of the mean model and the median model and effectively avoids the disadvantages of both. Furthermore, it is shown in experiments that the HDFM algorithm can complete accurate diagnosis in a discharge cycle no matter what level of short-circuit fault it encounters.