Date of Award
Summer 2005
Document Type
Thesis - Restricted
Degree Name
Master of Science (MS)
Department
Electrical and Computer Engineering
First Advisor
Arkadan, Abdul-Rahman A.
Second Advisor
Yaz, Edwin E.
Third Advisor
Johnson, Michael
Abstract
An integrated Team Artificial Intelligence Electromagnetic, T-AI-EM environment is developed to accurately determine the performance characteristics of synchronous reluctance machines, SynRM, with Axially Laminated Anisotropic (ALA) rotor configurations. This T-AI-EM approach is also used to develop an optimum design of SynRM for traction applications. The main objective of this optimization is to minimize the torque ripple, and ohmic and core losses while maximizing the output torque to ensure high acceleration and smooth operation. Furthermore, this model will enable the SynRM motor to easily interact in real time with the control unit of the Hybrid-Electric Vehicle, HEV. The T-AI-EM is composed of two main blocks. The first block 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 Lead Member, LM.
Recommended Citation
Hanbali, Ameed A., "Design Optimization of SynRM with ALA Rotor Configuration" (2005). Master's Theses (1922-2009) Access restricted to Marquette Campus. 4831.
https://epublications.marquette.edu/theses/4831