Background
Type: Article

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

Journal: IEEE Transactions on Magnetics (00189464)Year: 2002/05/01Volume: Issue: 3
Mirzaeian B.a Moallem M.Tahani V. Lucas C.
a :University of Isfahan - IRAN(IR) - Isfahan
DOI:10.1109/20.999126Language: English

Abstract

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 rpm SRM show improvement in both efficiency and torque ripple of the motor.

Author Keywords

Multiobjective optimizationSRM designEfficiencyFunctionsFuzzy setsOptimizationReluctance motorsTorqueVectors