Distance-Based Intelligent Particle Swarm Optimization for Optimal Design of Permanent Magnet Synchronous Machine

作者：Lee Jin Hwan; Kim Jong Wook; Song Jun Young; Kim Dae Woo; Kim Yong Jae; Jung Sang Yong^*

来源：IEEE Transactions on Magnetics, 2017, 53(6): 7206804.

DOI：10.1109/TMAG.2017.2658027

• Intelligent algorithm
• interior permanent magnet synchronous machine (IPMSM)
• optimal design
• particle swarm optimization (PSO)

In this paper, we propose a novel particle swarm optimization (PSO), which is based on the Euclidian distance of particles. In the conventional PSO, the convergence speed is decreased, since several particles that are far from swarm does not converge but wander around search area. The proposed algorithm, which is named after distance based intelligent PSO, assigns a new position and velocity to the furthest particle. Therefore, all particles gather around global optimum, and it is able to search for global optimum faster than that of the conventional PSO. To validate effectiveness of the proposed algorithm, we compare it to the conventional PSO using three numerical test functions. In addition, interior permanent magnet synchronous motor (IPMSM), which has characteristic of magnetic saturation in magnetic steel sheet, is chosen as target model of optimal design. Total harmonic distortion of back-electromotive force is optimized by optimization of rotor topology. Through optimal design of IPMSM, effectiveness of the proposed algorithm for electric machine design is verified.

• 出版日期2017-6