Genetic Algorithm and Fuzzy Based on The Taguchi Optimization to Improve The Torque Behavior of An Outer-Rotor Permanent-Magnet Machine

Genetic Algorithm and Fuzzy Based on The Taguchi Optimization to Improve The Torque Behavior of An Outer-Rotor Permanent-Magnet Machine

The torque behavior of an outer-rotor surface-mounted permanent-magnet machine is improvedby identifying seven pertinent design variables, including rotor height. The optimal designvariables are revealed by analyzing 18 experiments determined by the Taguchi method for theminimum torque ripple, minimum total harmonic distortion of the induced voltage, andmaximum average torque. In addition, the optimal design variables are obtained very quickly byusing fuzzy inference mechanism and genetic algorithm (GA) based on the Taguchi methodwith the single response of the multi-response performance index instead of multiple responses.A considerable amount of multi-response improvement is achieved according to the results ofthe two optimizations.

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