Aiming at the problems of large prediction errors and low confidence in the existing abnormal operation prediction methods of charging piles, a generalized regression model-based method for predicting abnormal operation of charging piles is proposed. Divide the abnormal type and abnormal area of the charging pile, and set the abnormal type characteristics as the standard for judging the abnormal operation of the equipment. According to the working principle of the charging pile, collect its dynamic multi-dimensional operating data. The factors affecting the operation of the charging pile are determined from two aspects: human operation and environmental weather. Construct a supplier evaluation model for charging piles to determine the initial quality of charging piles. Under the premise of considering the initial quality and influencing factors of the charging pile, use the collected operating data and use the generalized regression model to estimate the operating parameters such as power load and charging capacity. Finally, after comparing with the set standard features, the abnormal operation prediction result of the charging pile is obtained. Through the performance test experiment, it is concluded that in the two experimental environments, the power load forecast error of the design method is less than 0.5KW, the confidence is always higher than 85%, and the recognition time is 24s.
