Design Optimization of ALA Rotor SynRM Drives using T-AI-EM Environment

An integrated team-artificial intelligence-electromagnetic, T-AI-EM, environment is developed to accurately determine the performance characteristics of synchronous reluctance motors (SynRM) with axially laminated anisotropic (ALA) rotor configurations. This T-AI-EM is used to train a fuzzy logic system that predicts the optimal solution of the machine for any given input torque. The main objective of this optimization is to minimize the torque ripple corresponding to a given torque-load condition. The T-AI-EM is composed of two main blocks. The first consists of electromagnetic module utilizing indirectly coupled finite element state space (FE-SS) model. The second consists of an AI based model inspired from team member concept, that consists of several adaptive network fuzzy inference systems, ANFISs, supervised by a radial based network, RBN