Multi nobjective design optimization of switched reluctance machine

Abstract

Switched Reluctance Machine SRM is emerging as a potential newlinecontender for a number of drive applications in industrial and consumer newlineproducts The design of SRM for a specific application is a compromise newlinebetween various performance criteria This makes the design of SRM multiobjective newlinein nature a situation where a designer searches for solutions that are newlinefeasible with respect to all conflicting objectives This work investigates the newlineapplication of evolutionary computation and swarm intelligence techniques newlinefor two kinds of SRM design optimizations The first kind of optimization newlineaims at achieving optimal pole arc configuration with the objective of newlinemaximizing average torque minimizing torque ripple and copper loss The newlinesecond one focuses on structural optimization of SRM to determine the newlinedimensions of stator and rotor laminations with fixed external diameter and newlineaxial length as is the case in the design of the machine for automotive and Electric VehicleEV applications