Multiobjective Optimization of Yokeless Axial-Field Flux-Switching Permanent Magnet Motor Using the Hybrid Taguchi Genetic Algorithm for Expanded Speed Range

Multiobjective Optimization of Yokeless Axial-Field Flux-Switching Permanent Magnet Motor Using the Hybrid Taguchi Genetic Algorithm for Expanded Speed Range

This paper proposes a multiobjective hybrid Taguchi genetic algorithm (HTGA) to optimize the speed range of a yokeless axial-field flux-switching permanent magnet (YASA-AFFSPM) motor. HTGA combines Taguchi’s local optimization with the global optimization of traditional genetic algorithms (GAs), fac...

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Bibliographic Details
Main Authors: Javad Rahmani-Fard, Saeed Hasanzadeh
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:International Transactions on Electrical Energy Systems
Online Access:http://dx.doi.org/10.1155/2024/6855758
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