부산대학교 도서관

The power-torque characteristics of the magnetless switched reluctance motor (SRM) are well-suited for electric vehicle traction motor applications. However, the SRM faces a significant challenge in the form of high torque ripple, attributed to the improper selection of turn-on and turn-off switching states. Additionally, commutation torque ripple can contribute to overall torque fluctuations. To address these issues, this paper introduces a finite control set model predictive control (FCS-MPC) for SRM drives. This control strategy aims to minimize torque and flux ripple, providing improved performance in both steady and dynamic states. In comparison to classical direct torque control (DTC) and model predictive control (MPC) techniques, the proposed methods exhibit reduced torque and flux ripples. The efficacy of the FCS-MPC with a single prediction horizon is validated through simulations in MATLAB/Simulink, considering both static and dynamic behaviors. The simulations enable an in-depth analysis of flux ripple and torque ripple, demonstrating the effectiveness of the proposed control approach.