A Genetic-Taguchi Global Design Optimization Strategy for Surface-Mounted PM Machine

This paper presents a novel step-optimization strategy for the multi-objective tradeoffs in surface-mounted permanent magnet synchronous machines (SPMSMs), i.e. genetic-Taguchi global optimization (GTGO). Specifically, the electromagnetic performances are accurately predicted by sub-domain (SD) mode...

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Bibliographic Details
Main Authors: Dai, Litao, Gao, Jian, Zhang, Wenjuan, Huang, Shoudao
Format: Conference Proceeding
Language:English
Subjects:
Air gaps
Analytical models
design optimization
genetic algorithm (GA)
Genetic algorithms
Mathematical model
Optimization
Stator cores
Surface-mounted permanent magnet (PM) machine
Taguchi method
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Summary:This paper presents a novel step-optimization strategy for the multi-objective tradeoffs in surface-mounted permanent magnet synchronous machines (SPMSMs), i.e. genetic-Taguchi global optimization (GTGO). Specifically, the electromagnetic performances are accurately predicted by sub-domain (SD) model, and the objective functions of cost, efficiency and total harmonic distortion (THD) of back electromotive force (emf) are solved by genetic algorithm (GA) based on constraint conditions. Next, the Taguchi method optimizes local variables which are difficult to model by SD model, such as magnetic pole shift, magnet eccentricity and segmentation. The last, the effectiveness of proposed GTGO has been verified by finite-element analysis (FEA).
ISSN:2642-5513
DOI:10.1109/ICEMS.2019.8921774