Optimization for Airgap Flux Density Waveform of Flywheel Motor Using NSGA-2 and Kriging Model Based on MaxPro Design

Abstract

The performance of flywheel motor is decided by the airgap flux density waveform. This paper establishes an efficient model to optimize the airgap flux density waveform and provides the Pareto optimal solutions, which give the design boundary of airgap flux density waveform for flywheel motor. The key elements of the structure of permanent magnet and the airgap are considered to optimize the sinusoidal distortion rate and the fundamental amplitude of the airgap flux density waveform. The brief optimization process is three steps: (1) sampling by maximum projection design; (2) building surrogate model by the Kriging method; and (3) multi-objective optimization by non-dominated sorting genetic algorithm with elitism approach (NSGA-2) based on the Kriging model. Then, the Pareto optimal solutions are obtained. The three cases optimized by different strategies are compared, and the optimization method is verified by finite-element method.