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 improved by identifying seven pertinent design variables, including rotor height. The optimal design variables are revealed by analyzing 18 experiments determined by the Taguchi method for the minimum torque ripple, minimum total harmonic distortion of the induced voltage, and maximum average torque. In addition, the optimal design variables are obtained very quickly by using fuzzy inference mechanism and genetic algorithm based on the Taguchi method with 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 of the two optimizations. Performance improvements of 20.3%, 32.8%, and 25.2% are obtained for the average torque, the torque ripple, and the total harmonic distortion of the back-EMF, respectively.

Keywords:

Torque Ripple, Taguchi Method, Fuzzy Inference System, Multi-Response Performance Index Genetic Algorithm,

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