Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93418
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Title: Design optimization of a pole-changing biased flux machine based on sensitivity analysis
Authors: Mao, Y 
Niu, S 
Fu, W 
Issue Date: 2019
Source: 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 11-14 August 2019, Harbin, China, p. 1-6
Abstract: In this paper, a novel pole-changing biased flux machine is proposed. With special rotor pole and permanent magnetic pole design, this machine has pole-changing effect. By controlling the excitation current's polarity the pole number of this machine can switch back and forth between three pole pair and six pole pair. The armature winding is designed in concentrated structure to realize higher utilization ratio of flux linkage under both pole modes. To further improve the performance of the proposed machine, topology optimization is conducted. In order to verify the feasibility of this design, electromagnetic characteristics, including coil flux linkage distribution, air gap flux density and harmonics analysis are studied under finite element method.
Keywords: Biased flux machine
Finite element method
Permanent magnet machine
Pole-changing
Sensitivity analysis
Publisher: Institute of Electrical and Electronics Engineers
ISBN: 978-1-7281-3398-0 (Electronic ISBN)
978-1-7281-3397-3 (USB ISBN)
978-1-7281-3399-7 (Print on Demand(PoD) ISBN)
DOI: 10.1109/ICEMS.2019.8922487
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication Y. Mao, S. Niu and W. Fu, "Design Optimization of a Pole-Changing Biased Flux Machine Based on Sensitivity Analysis," 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019, pp. 1-6 is available at https://doi.org/10.1109/ICEMS.2019.8922487
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