Predictive Direct Torque Control of Switched Reluctance Motor for Electric Vehicles Drives

Abstract

The electrical drive systems utilized in Electric Vehicles (EVs) applications must be reliable and high performance. To providing these specifications, it is essential to design high-efficiency electric motors and develop high-performance controllers. This study introduces direct torque control of Switched Reluctance Motor (SRM) for electric vehicle applications using Model Predictive Control (MPC) technique. The direct torque control using MPC is proposed to maintain the motor torque and motor speed to tracking desired signals with a satisfactory response. In this study, the MPC algorithm was programmed in C- language, and the simulation tests were performed using a non-linear model of 6/4 - 60 kW SRM that is fed with the symmetrical converter. The proposed controller was tested under different load conditions to verify the robustness of the controller, as well as at variable speeds to investigate the tracking performance. Thanks to the proposed method, the SRM torque ripples, stator copper losses, and average switching frequency of the power converter can reduce effectively due to applying a cost function that combines multiple objectives. The obtained outcomes show the effectiveness of the suggested approach compared to conventional direct torque control techniques.