An Early Battery Fault Diagnosis Method Based on Multi-Source Information Fusion Theory

While the power battery playing a more and more important role in the society, its security is under an extremely strict requirement. But traditional fault diagnosis methods can’t ensure the safety of the batteries, since they are week in the detection of early minor battery fault. Therefore, a high-precision and low-cost battery diagnosis method is proposed. This method is based on the fusion of three individual sub-methods, that is modified correlation coefficient method, sample entropy and modified threshold method. The three sub-methods above are sensitive to different types of faults. By integrating their diagnosis result, the fusion method has a strong fault diagnosis ability for all types of faults. Meanwhile, it can largely shorten the early warning time of major faults. Result of experiments verifies that the method proposed does well in early minor fault diagnosis and can detect the fault at least 5 minutes in advance.