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Published in:
2010 | OriginalPaper | Chapter
Multi-Objective Optimal Design of Switch Reluctance Motors Using Adaptive Genetic Algorithm
Authors : Mehran Rashidi, Farzan Rashidi
Published in: Swarm, Evolutionary, and Memetic Computing
Publisher: Springer Berlin Heidelberg
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In this paper a design methodology based on multi objective genetic algorithm (MOGA) is presented to design the switched reluctance motors with multiple conflicting objectives such as efficiency, power factor, full load torque, and full load current, specified dimension, weight of cooper and iron and also manufacturing cost. The optimally designed motor is compared with an industrial motor having the same ratings. Results verify that the proposed method gives better performance for the multi-objective optimization problems. The results of optimal design show the reduction in the specified dimension, weight and manufacturing cost, and the improvement in the power factor, full load torque, and efficiency of the motor.A major advantage of the method is its quite short response time in obtaining the optimal design.