Electro-magnetic modeling and design optimization of synchronous reluctance machines and single-phase induction machines

Synchronous reluctance machines;Maxwell's equations;Magnetic equivalent circuit;Finite element analysis;Particle swarm optimization;Differential evolution;Pareto front;Single-phase induction machines;Multi-objective optimization

Shao, Hang ; Habetler, Thomas G. Electrical and Computer Engineering Saeedifard, Maryam Molzahn, Daniel K. Mayor, J. Rhett He, Lijun ; Habetler, Thomas G.

University:Georgia Institute of Technology

Department:Electrical and Computer Engineering

关键词: Synchronous reluctance machines;    Maxwell's equations;    Magnetic equivalent circuit;    Finite element analysis;    Particle swarm optimization;    Differential evolution;    Pareto front;    Single-phase induction machines;    Multi-objective optimization;   

Others  :  https://smartech.gatech.edu/bitstream/1853/62272/1/SHAO-DISSERTATION-2019.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

The objective of the proposed research is to develop the analytical electro-magnetic (EM) models for synchronous reluctance machines (SynRMs) and single-phase induction machines (IMs), so as to generate the optimal designs to improve their performances. For the SynRM, a universal analytical model is proposed based on Maxwell’s equations and conformal mapping. Saturation effect is modeled with the help of the magnetic equivalent circuit (MEC) model. For the single-phase IM, the equivalent circuit model is adopted in order to analyze the machine performance from the design parameters.Evolutionary algorithms are used to conduct the multi-objective optimization (MOO) for the SynRM and single-phase IM. The optimal designs show improved performance compared with the original designs, and the time consumed is acceptable due to the time efficiency of the analytical model.The ultimate goal of this research is to create a computationally efficient design tool that has the ability to rapidly locate an optimal design candidate which satisfies the design specifications and objectives. Once the optimal design candidate is located, a final design can be easily completed by further refinement using the commercially available finite element analysis (FEA) software.