An Online Torque Sharing Function Method Involving Current Dynamics for Switched Reluctance Motor Drives

Abstract

This article proposes an online torque sharing function (TSF) method for torque ripple reduction in switched reluctance machines (SRMs). The proposed TSF takes the current dynamics and induced electromotive force (EMF) into account by establishing a new online current profile generation technique. First, a primary phase current reference derived from the torque reference is applied to the SRM. Then, the decaying phase current after the turn-off angle is sampled and it is used to update the current reference. A new online optimization strategy is performed to shape the current reference during the operation of the machine. Due to the proposed current profile generation technique, the optimization process is decoupled to independently minimize the torque ripple by optimizing the turn-on angle and minimizing copper losses by optimizing the turn-off angle. Compared to the conventional TSFs and existing optimization-based TSFs, the proposed TSF achieves accurate torque control, improved torque–speed capability, reduced torque ripple, and better current tracking performance. Simulations and experiments are performed on a three-phase 12/8 SRM under various operating conditions to validate the proposed online TSF method.