TY - JOUR
T1 - Distance-Based Intelligent Particle Swarm Optimization for Optimal Design of Permanent Magnet Synchronous Machine
AU - Lee, Jin Hwan
AU - Kim, Jong Wook
AU - Song, Jun Young
AU - Kim, Dae Woo
AU - Kim, Yong Jae
AU - Jung, Sang Yong
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6
Y1 - 2017/6
N2 - 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.
AB - 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.
KW - Intelligent algorithm
KW - interior permanent magnet synchronous machine (IPMSM)
KW - optimal design
KW - particle swarm optimization (PSO)
UR - https://www.scopus.com/pages/publications/85028757038
U2 - 10.1109/TMAG.2017.2658027
DO - 10.1109/TMAG.2017.2658027
M3 - Article
AN - SCOPUS:85028757038
SN - 0018-9464
VL - 53
JO - IEEE Transactions on Magnetics
JF - IEEE Transactions on Magnetics
IS - 6
M1 - 7833062
ER -
