A Current Hysteresis Control Strategy for Switched Reluctance Machine Based on Genetic Algorithms and Finite Elements Analysis

Abstract

Many applications require efficient, low torque ripple motors; therefore, using a switched reluctance motor (SRM) in these cases requires a control technique that takes it into account. This paper proposes a novel control strategy that uses optimal reference phase currents obtained by Genetic Algorithm (GA) that minimize torque ripple while maintaining the overall stator current. The Genetic Algorithm (GA) used a Finite Element Analysis (FEA) model to choose the ideal phase currents for a set of rotor positions and reference torques. That model took mutual inductances, cross-coupling effects, and saturation into account. Upon determination of the ideal phase currents to track, a current hysteresis control strategy was proposed to maintain a load torque of 2Nm at 300rpm. To validate the proposed technique, a comparison with a Direct Instantaneous Torque Control (DITC) strategy was performed, proving which it maintains the machine efficiency and reduces torque ripple.