Multi-Objective Optimization Design of Bearingless Permanent Magnet Synchronous Generator

In order to realize the design objectives of high power generation performance and stable suspension capability, a multi-objective optimization method based on a response surface (RS) model and an improved multi-objective particle swarm optimization (MOPSO) algorithm is proposed and utilized to the multi-objective optimization design of a bearingless permanent magnet synchronous generator (BPMSG). Firstly, the operating principle and the mathematical model of the BPMSG are introduced. Secondly, the design variables and the design objectives are determined and the design space is reduced by the sensitivity analysis. Thirdly, the RS models of design objectives are constructed and the improved MOPSO algorithm is applied to get the Pareto optimal sets. Finally, the initial generator and the optimal generator are compared using the finite element analysis software. Compared with the initial generator, the average suspension force of the optimal generator is increased by 21% and the suspension force ripple is decreased by 52%.