Research on State of Health for the Series Battery Module Based on the Weibull Distribution

Abstract

The state of health (SOH) of the battery module is one of the important parameters in the battery management system. Accurately grasping the SOH of the battery module can provide the basis for its detection and diagnosis. In this work, the series battery module SOH is taken as the research object. Firstly, based on the characteristics of the series battery module, a two-parameter Weibull distribution is selected as the module failure data distribution form. Secondly, linearize the reliability function of the Weibull distribution and preprocess the module failure data. The least square method is used to identify the unknown parameters of the linear equation and carry out correlation analysis and model verification. The result shows the correlation coefficient ρ X , Y = 0.9725 , indicating that the variables X and Y are significantly correlated. The selected model is tested by the Kolmogorov-Smirnov (K–S) method, and the K-S test statistic D achieves the maximum value D max = 0.0371 , which is much smaller than the Dc = 0.301 obtained by checking the K-S D critical value table. In the reliability analysis, the failure data are evenly distributed on both sides of the reliability function, indicating that the selected model can well reflect the SOH transformation trend of the series battery module.