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Multiobjective optimization method based on a genetic algorithm for switched reluctance motor design

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4 Author(s)
B. Mirzaeian ; Dept. of Electr. Eng., Isfahan Univ. of Technol., Iran ; M. Moallem ; V. Tahani ; C. Lucas

In this paper, a novel multiobjective optimization method based on a genetic-fuzzy algorithm (GFA) is proposed. The new GFA method is used for optimal design of a switched reluctance motor (SRM) with two objective functions: high efficiency and low torque ripple. The results of the optimal design for an 8/6, four-phase, 4 kW, 250 V, 1500 r.p.m. SRM show improvement in both efficiency and torque ripple of the motor

Published in:

IEEE Transactions on Magnetics  (Volume:38 ,  Issue: 3 )