Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105329
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Title: Design optimization and comparative study of a novel halbach permanent magnet vernier machine with alternate flux bridge
Authors: Huang, Z 
Chau, AMH
Niu, S 
Zhao, X
Xue, Z 
Issue Date: Jan-2023
Source: Applied sciences, Jan. 2023, v. 13, no. 2, 764
Abstract: The purpose of this paper is to investigate the effect of the alternate flux bridge combining Halbach array in Vernier machines. The key novelty is that integrated with the Halbach array PM, the alternate flux bridge design can not only provide a flux path for low-order harmonics but also effectively improve the torque density of the machine. Together with the other three traditional structures under the same overall size, current density, and PM usage, the proposed structure is optimized by genetic algorithm (GA) to maximize the average torque and minimize the torque ripple. With the winding configuration of full-pitch (FP) and short-pitch (SP), the back-EMF, efficiency, power factor, and other performances of four machines with different topologies are analyzed and compared, respectively. With 2D time stepping finite element analysis (FEA) and experimental verification, the torque density of the proposed design reaches 40.11 KNm/m3, which is significantly higher than that of its existing counterparts.
Keywords: Flux bridge
Genetic algorithm (GA)
Halbach array
Permanent magnet (PM)
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Applied sciences 
EISSN: 2076-3417
DOI: 10.3390/app13020764
Rights: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Huang Z, Chau AMH, Niu S, Zhao X, Xue Z. Design Optimization and Comparative Study of a Novel Halbach Permanent Magnet Vernier Machine with Alternate Flux Bridge. Applied Sciences. 2023; 13(2):764 is available at https://doi.org/10.3390/app13020764.
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