Fault diagnosis method of high power charging equipment based on Neural Network

High power charging equipment is the necessary supporting facilities in the electric vehicle industry, but failure will inevitably occur in the process of equipment use. Through the research on the structure and principle of charging equipment, the influencing factors and causes of equipment failure are analyzed. In this paper, BP neural network algorithm is used to establish the nonlinear relationship between the fault influencing factors and fault causes of the charging equipment with the input and output of the neural network, and the fault diagnosis is carried out for the high-power charging equipment of electric vehicles. Through the simulation, the BP neural network fault diagnosis model has higher fault diagnosis accuracy. The model is applied to the condition monitoring and fault diagnosis system of high-power charging equipment of electric vehicles, and good diagnosis results are obtained, which has practical application value.