Optimized Model Torque Prediction Control Strategy for Switched Reluctance Motor Torque Error and Speed Error Reduction System

In order to reduce the torque pulsation problem of switched reluctance motors, this paper proposes an improved finite-set model predictive direct torque control algorithm that combines Model Predictive Control (MPC) with Direct Torque Control (DTC) and introduces hysteresis loop rules into the model predictive control. The traditional tracking error minimization is transformed into the longest extension step in the hysteresis loop to further reduce the high torque pulsation problem of switched reluctance motors due to the biconvex pole structure and improve the system’s dynamic and static performance. Finally, the algorithm used in this paper has better torque suppression effect and speed performance under low and high speeds as well as sudden load changes, as verified by comparison with the traditional control algorithm through simulation.