LAUSR

During the usage of electric vehicles, the battery decays and the cell variations expand in the battery pack. In the discharge process, both the low-capacity cell and the micro-short-circuit (MSC) cell have the abnormal feature that the state-of-charge (SOC) differences increase continuously. Hence, a low-capacity cell is likely to be misdiagnosed as an MSC cell, and vice versa. In this article, a fault identification approach based on mutual information is proposed to detect the MSC cell and low-capacity cell. A decision tree for fault identification is established by analyzing the battery fault characteristics of the short circuit, low capacity, and the abnormality of initial SOC difference. It is pointed out that the SOC deviation of the low-capacity cell is related to the mean SOC, while that of the MSC cell is related to time. A low-pass filter is used to get internal resistance differences in order to achieve the SOC deviations based on the cell different model. Finally, the MSC cell and the low-capacity cell can be identified using the mutual information which can quantitatively calculate the correlation between the SOC deviation and the mean SOC. Experimental results prove that the proposed method is reliable to identify the MSC cell and the low-capacity cell.