Model Predictive Control of Switched Reluctance Machines for Suppressing Torque and Source Current Ripples Under Bus Voltage Fluctuation

Abstract

This article presents a novel model predictive method for torque ripple and source current ripple suppression in switched reluctance machines (SRMs) when the bus voltage fluctuates. Based on the measured rotor position, phase current, and phase voltage, the states, including bus voltage, capacitor current, and phase flux-linkage, are calculated for the preparation of the prediction. On this basis, the machine torque and inverter current for all the possible switching states are predicted to construct the cost function. The operating state with the minimum value of cost function is considered as the optimal switch signal and applied to the control power converter, thus achieving the effect of simultaneous reduction of torque ripple and source current ripple. Experimental results show the proposed method has a significant effect on the suppression of both torque ripple and source current ripple even with bus voltage fluctuation, which verifies the effectiveness of the proposed method. The influence of the key factors, such prediction horizon, parametric variation, and weight coefficient, on the machine performance are further investigated. The proposed method is easy to be implemented in the control logic as well as robust to bus voltage fluctuations, enabling to promote the competitiveness of SRMs in electric vehicle application.