An Improved Model Predictive Control Method of Switched Reluctance Motor Based on Direct Torque Control

This paper proposes a model predictive control (MPC) method based on selecting candidate voltage vectors in different regions to reduce torque ripple and improve the power factor of switched reluctance motors (SRM). Six regions are employed in the machine electric cycle of the SRM. Candidate voltage vectors of each sector are determined according to phase torque characteristics of SRM in different regions. The constraint function is designed to select the optimal voltage vector from candidate voltage vectors which minimize the torque pulsation and copper loss. This new control method avoids mass useless computation and no longer relies on hysteresis signals which are different to direct torque control (DTC). The simulation results of DTC method are compared to the improved MPC method in a three-phase 12/8 poles SRM.