Control Optimization of a Slotted Switched Reluctance Generator for High-torque Applications

Abstract This article describes the control optimization of a slotted switched reluctance generator for low-speed applications. The machine is simulated with the finite-element method. The turn-off and turn-on angles are optimized by means of a genetic algorithm to maximize the output power and minimize the torque ripple. First, these two criteria are optimized separately with a mono-objective genetic algorithm, and then a multi-objective Pareto genetic algorithm is used. An analysis of optimized parameters and resulting current waveforms is also performed. Experimental results based on a 6/4 switched reluctance generator are also presented.

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