New energy electric vehicle charging safety hazard identification method based on clustering algorithm

In order to improve the charging safety of new energy electric vehicles and accurately identify the charging safety hazards, a new charging safety hazard identification method of new energy electric vehicles based on clustering algorithm is proposed in this paper. The charging safety hazard data set is constructed, the charging safety hazard data are preliminarily clustered by clustering algorithm, and the preliminary clustering results are optimized and trained combined with generalized regression neural network, so as to improve the identification accuracy of charging safety hazards of new energy electric vehicles. According to the clustering results of safety hazard data, the deep neural network is used to identify the charging safety hazard, and the output result of the deep neural network is the safety hazard identification result. The experimental results show that compared with the traditional identification methods, this method can improve the identification accuracy on the basis of reducing the time-consuming of potential safety hazards identification.