Multi-objective Optimization of High Efficiency PMa-SynRMs Based on Search Space Decay Method for Surrogate Model

Abstract

This work proposes a search space decay way to improve the efficiency of optimization for the most-frequent operational zone of magnet assisted synchronous reluctance motors (PMa-SynRMs). In order to decay the global search space, an analytical model (AM) is built by the simplified magnetic equivalent circuit (MEC) of the rotor and stator. Then the radial basis function (RBF) model is established by the sampling in the local space to predict the performance of the motor which combined with nondominated sorting genetic algorithm II(NSGA-II). Finally, the effectiveness of the optimized result is verified by finite element analysis (FEA).