Torque Ripple Minimization in a Switched Reluctance Drive by Neuro-Fuzzy Compensation

TL;DR

This paper introduces a neuro-fuzzy based method to shape motor currents for reducing torque ripple in switched reluctance motors, enhancing performance with a novel control approach.

Contribution

It proposes a new neuro-fuzzy compensator integrated with a PI controller to effectively minimize torque ripple in SRM drives.

Findings

Significant reduction in torque ripple demonstrated

Effectiveness of neuro-fuzzy compensator analyzed

Impact of membership function variation studied

Abstract

Simple power electronic drive circuit and fault tolerance of converter are specific advantages of SRM drives, but excessive torque ripple has limited its use to special applications. It is well known that controlling the current shape adequately can minimize the torque ripple. This paper presents a new method for shaping the motor currents to minimize the torque ripple, using a neuro-fuzzy compensator. In the proposed method, a compensating signal is added to the output of a PI controller, in a current-regulated speed control loop. Numerical results are presented in this paper, with an analysis of the effects of changing the form of the membership function of the neuro-fuzzy compensator.