Multiresponse optimization to improve the torque behavior of an outer-rotor permanent-magnet machine using gray relational analysis based on the Taguchi method

Abstract

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 gray relational analysis based on the Taguchi method with the single response of the gray relational grade instead of multiple responses. A considerable amount of multiresponse improvement is achieved according to the results of the two optimizations. Performance improvements of 20.6%, 32.0%, and 24.5% are obtained for the average torque, the torque ripple, and the total harmonic distortion of the back-EMF, respectively.

Bulletin of the Polish Academy of Sciences: Technical Sciences

“…In the literature, Taguchi experimental design methods are optimized by using factor graphs [20,25,29] and signal to noise ratio [22,30] methods. In some studies, impact rates are determined according to both methods [21].…”

“…Özoğlu proposed a genetic and fuzzy logic based on Taguchi optimization method for mean torque, cogging torque and total harmonic distortion (THd) of induced EMF (electro motor force) in a permanent magnet machine with external stator. In the optimization with Taguchi, they used L18 orthogonal array for 7 factors and 3 levels [22]. Shirazi et al used the Taguchi experimental design method to minimize the cogging torque of permanent magnet machines.…”