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

Year 2018, Volume: 31 Issue: 1, 82 - 98, 01.03.2018

Yusuf Özoğlu

Abstract

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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