A particle swarm optimization based maximum torque per ampere control for a switched reluctance motor

The Switched Reluctance Machine (SRM) is known for being one of the oldest electric machine designs. Unfortunately, it is usually assumed that this implies that the machine is outdated. However with the advent of microprocessors, the SRM has become a suitable option for a number of applications because the shortcomings of the machine can be mitigated with control. Compared to other machines, the SRM is more rugged, has a simpler structure, and is less expensive to manufacture. The method presented is concerned with finding the turn-on and turn-off angles needed to generate maximum torque per ampere (MTPA). The method applies a particle swarm optimization (PSO) technique that searches for the angles that maximize the inductance of the SRM in order to achieve MTPA. The inductance function was obtained experimentally. The method was applied to a 4-phase 8/6 SRM. The proposed method was found to be effective at both low speeds (beneath the base speed) and high speeds (above the base speed), but MTPA could only be asserted for low speeds. The switched reluctance motor was modeled in Simulink.