Particle swarm design optimization of ALA rotor SynRM for traction applications

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. Index Terms--Artificial intelligence, fuzzy logic, optimization methods, reluctance machines, synchronous machines.