基于改进决策树的充电桩故障预测方法

Fault Prediction Method of Charging Pile Based on Improved Decision Tree

为了保证电动汽车充电桩的安全稳定运行,提高充电桩故障预测准确性,提出一种基于改进决策树的充电桩故障预测方法。首先,对充电桩的运行参数进行预处理,将处理后的数据作为模型输入;其次,建立基于粒子群算法改进的决策树的充电桩故障预测模型;最后,采用真实充电桩故障的数据集进行仿真分析。仿真结果表明,所提出的方法能有效提高模型预测准确性。

In order to ensure the safe and stable operation of electric vehicle charging piles and improve the accuracy of charging pile fault prediction,a charging pile fault prediction method based on improved decision tree was proposed.Firstly,the operation parameters of the charging pile were preprocessed,and the processed data was used as the model input;secondly,the fault prediction model of charging pile was established based on the improved decision tree of particle swarm optimization;finally,the data set of real charging pile fault was used for simulation analysis.The simulation results show that the proposed method can effectively improve the accuracy of model prediction.