Control Strategy of Permanent Magnet Synchronous Motor for Electric Vehicle Based on Wavelet Neural Network

Three phase permanent magnet synchronous motor is a typical nonlinear, strong coupling, multi-input and multi-output system. Aiming at the problem of system function degradation caused by motor parameter variation and load fluctuation in permanent magnet synchronous motor control system, an adaptive control algorithm based on wavelet neural network is adopted. The wavelet function is combined with the neural network, and the gradient descent algorithm is used to continuously train and optimize the network to realize the optimal prediction of the sudden change of the running state. The simulation results show that the algorithm has the characteristics of high control precision, strong adaptability, fast dynamic response and good robustness.