Research of Fault Diagnosis Model for Electric Vehicle Permanent Magnet Synchronous Motor on BP Neural Network
As widely used driving motor in electric vehicles,the fault diagnosis technology of permanent magnet synchronous motors is crucial for the safe and reliable operation of electric vehicles.To achieve accurate diagnosis of permanent magnet synchronous motor faults,a fault diagnosis model for permanent magnet synchronous motors based on improved genetic algorithm optimized back propagation(BP)neural network is constructed.The model extracts the fault characteristic signal of the motor stator winding current through wavelet packet decomposition as the input of the BP neural network,and uses the improved genetic algorithm to optimize the training of the BP neural network.Simulation experiment analysis shows that compared with BP algorithm and genetic algorithm,the improved genetic algorithm optimizing the BP neural network model for motor fault diagnosis with fast speed,high precision,provides a new technical solution and application tool for fault diagnosis of electric vehicle drive motor.
万方数据
维普
