Author(s)

Gang Yang^1,2, Xiao Jiang³, Shuaishuai Lv³

¹First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China.
²Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao, China.
³School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China.

Aiming at the torque and flux ripples in the direct torque control and the time-varying parameters for permanent magnet synchronous motor (PMSM), a model predictive direct torque control with online parameter estimation based on the extended Kalman filter for PMSM is designed. By predicting the errors of torque and flux based on the model and the current states of the system, the optimal voltage vector is selected to minimize the error of torque and flux. The stator resistance and inductance are estimated online via EKF to reduce the effect of model error and the current estimation can reduce the error caused by measurement noise. The stability of the EKF is proved in theory. The simulation experiment results show the method can estimate the motor parameters, reduce the torque, and flux ripples and improve the performance of direct torque control for permanent magnet synchronous motor (PMSM).

Model Predictive Direct Torque Control, Extended Kalman Filter, Parameter Estimation, Permanent Magnet Synchronous Motor, Filter’s Stability

Yang, G. , Jiang, X. and Lv, S. (2022) Model Predictive Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) with Online Parameter Estimation Based on Extended Kalman Filter. International Journal of Communications, Network and System Sciences, 15, 79-93. doi: 10.4236/ijcns.2022.157007.