Dual Model Predictive Torque Control Scheme for Online Torque Ripple Reduction in Switched Reluctance Machines

A novel dual model predictive torque control scheme is proposed for the switched reluctance machine (SRM) in this paper. Based on the conventional torque sharing function (TSF), we first develop a continuous-time model predictive current controller for current tracking in each phase, then design an online model predictive current compensator for torque ripple minimization. Verified in Simulink, the proposed dual MPC scheme intelligently minimizes torque ripples over a wide speed range while maintaining constant switching frequency. The numerical comparison results show the effectiveness of the dual MPC scheme in torque ripple minimization with comparisons to the state-of-art online torque ripple reduction scheme.

I. Introduction

The switched reluctance machine (SRM) exhibits higher torque ripples due to its double salient structure, which restricts its application in industry. Consequently, extensive research has been conducted on torque control strategies for SRMs, making it a popular research area [1]–[3].