Multiobjective Optimisation of Switched Reluctance Motor Using Fuzzy-Genetic-Simplex Algorithm

Abstract

This paper presents a new method for multiobjective optimisation of a switched reluctance motor. Four objective functions regarding motor efficiency, power factor, torque ripples and outer volume are considered. The proposed method combines fuzzy logic, genetic algorithm and simplex technique as a general global optimisation technique. The new technique is searching for the best compromise solution, which maximises the designer total degree of satisfaction. In order to predict the motor performance accurately , a hybrid FEA-analytical simulation model has been adopted. The model combines some of the FEA accuracy with the simplicity of analytical model. A full time stepping FEA analysis for the optimised motor has been done to verify the final design of the motor.