Particle Swarm Design Optimization of ALA Rotor SynRM for Traction Applications

被引：34

作者：

Arkadan, A. A. ^{[1
,2
]}

ElBsat, M. N. ^{[2
]}

Mneimneh, A. A. ^{[2
]}

机构：

[1] Hariri Canadian Univ, Mechref 2010, Lebanon

[2] Marquette Univ, Milwaukee, WI 53203 USA

来源：

IEEE TRANSACTIONS ON MAGNETICS | 2009年 / 45卷 / 03期

关键词：

Artificial intelligence; fuzzy logic; optimization methods; reluctance machines; synchronous machines;

D O I：

10.1109/TMAG.2009.2012482

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Particle swarm optimization (PSO) algorithm is applied to the design optimization problem of axially laminated anisotropic (ALA) rotor synchronous reluctance motor (SynRM) drive. The objective of the optimization is to maximize the developed torque while minimizing the torque ripple as well as the Ohmic and core losses for traction applications. The number of flux paths, stator tooth width, and rotor flux path width define the 3-D search space for the optimization problem. An artificial intelligence modeling approach utilizing PSO and finite element-state space (FE-SS) models is used for the characterization and design optimization of a prototype ALA rotor SynRM drive for traction applications.

引用

页码：956 / 959

页数：4

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