Optimal Current Waveforms for Switched-Reluctance Motors

TL;DR

This paper develops a method to determine optimal current waveforms for switched reluctance motors that minimize torque ripple and RMS current, accounting for complex motor characteristics, using a global optimization approach.

Contribution

It introduces a mixed-integer convex programming framework to find globally optimal waveforms for complex SRM models, including saturation and unconventional geometries.

Findings

Successfully finds globally optimal waveforms at high rotor speeds.

Demonstrates effectiveness on experimentally verified motor models.

Addresses complex magnetic and electrical constraints in optimization.

Abstract

In this paper, we address the problem of finding current waveforms for a switched reluctance motor that minimize a user-defined combination of torque ripple and RMS current. The motor model we use is fairly general, and includes magnetic saturation, voltage and current limits, and highly coupled magnetics (and therefore, unconventional geometries and winding patterns). We solve this problem by approximating it as a mixed-integer convex program, which we solve globally using branch and bound. We demonstrate our approach on an experimentally verified model of a fully pitched switched reluctance motor, for which we find the globally optimal waveforms, even for high rotor speeds.