In recent years, with the development of new energy technology and the country’s strong support for electric vehicles, there is a lack of effective electric vehicle charging fault analysis and diagnosis methods at this stage. A comprehensive analysis of the working principle of the charging process of electric vehicles, based on the clarification of the failure mechanism of the power battery and charging equipment, analyzes the fault-related factors affecting the power battery and charging equipment from multiple angles, and summarizes the relationship between the power battery and charging equipment. The feature parameters related to equipment failure are discretized by the k-means clustering algorithm. Using the optimized FP-Growth algorithm based on weights, the association rules between the power battery and charging equipment failures and the characteristic parameters of the failure factors are mined, and the correlation of the failures is analyzed based on the association rules, and the correlation between the failure factors and the failures is obtained relevant level.

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