An Adaptive Optimization Algorithm Based on Kriging Interpolation with Spherical Model and its Application to Optimal Design of Switched Reluctance Motor

In this paper, an adaptive optimization strategy utilizing Kriging model and geneticalgorithm is proposed for the optimal design of electromagnetic devices. The ordinary Kriging assistedby the spherical covariance model is used to construct surrogate models. In order to improve thecomputational efficiency, the adaptive uniform sampling strategy is applied to generate samplingpoints in design space. Through several iterations and gradual refinement process, the global optimalpoint can be found by genetic algorithm. The proposed algorithm is validated by application to theoptimal design of a switched reluctance motor, where the stator pole face and shape of pole shoeattached to the lateral face of the rotor pole are optimized to reduce the torque ripple. KCI Citation Count: 3