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Design and Optimization of a Novel Dual-Stator Flux-Switching Permanent Magnet Machine
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Wang, Y. | - |
| dc.contributor.author | Zhao, W. | - |
| dc.contributor.author | Yu, M. | - |
| dc.contributor.author | Yang, Y. | - |
| dc.contributor.author | Kwon, B.-I. | - |
| dc.date.accessioned | 2021-07-28T08:13:10Z | - |
| dc.date.available | 2021-07-28T08:13:10Z | - |
| dc.date.created | 2021-07-14 | - |
| dc.date.issued | 2020 | - |
| dc.identifier.issn | 0000-0000 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/105821 | - |
| dc.description.abstract | In this paper, a 24-slot/25-pol e dual-stator flux switching permanent magnet machine (DSFSPMM) is designed and optimized to improve electromagnetic performance by combining the spoke-type magnet configurations, phase-group concentrated coil windings and an unaligned arrangement of rotor teeth. The design concept and operation principle of the machine are introduced in detail. Due to the complex dualstator structure, the proposed DSFSPMM model is established and analyzed by using the finite element method software. To achieve the optimal structure size of the machine, the multiobjective genetic algorithm (MOGA) is carried out based on the single-parameter scanning. As a result, it shows that the optimized model exhibits high torque density, low torque ripple, and high efficiency. © 2020 IEEE. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
| dc.title | Design and Optimization of a Novel Dual-Stator Flux-Switching Permanent Magnet Machine | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Kwon, B.-I. | - |
| dc.identifier.doi | 10.1109/SCEMS48876.2020.9352278 | - |
| dc.identifier.scopusid | 2-s2.0-85101981499 | - |
| dc.identifier.wosid | 000680418500016 | - |
| dc.identifier.bibliographicCitation | 2020 IEEE Student Conference on Electric Machines and Systems, SCEMS 2020, pp.89 - 93 | - |
| dc.relation.isPartOf | 2020 IEEE Student Conference on Electric Machines and Systems, SCEMS 2020 | - |
| dc.citation.title | 2020 IEEE Student Conference on Electric Machines and Systems, SCEMS 2020 | - |
| dc.citation.startPage | 89 | - |
| dc.citation.endPage | 93 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Proceedings Paper | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Engineering | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
| dc.subject.keywordPlus | Electric windings | - |
| dc.subject.keywordPlus | Genetic algorithms | - |
| dc.subject.keywordPlus | Rotors (windings) | - |
| dc.subject.keywordPlus | Stators | - |
| dc.subject.keywordPlus | Structural optimization | - |
| dc.subject.keywordPlus | Concentrated coil | - |
| dc.subject.keywordPlus | Design and optimization | - |
| dc.subject.keywordPlus | Electromagnetic performance | - |
| dc.subject.keywordPlus | Finite element method softwares | - |
| dc.subject.keywordPlus | High torque density | - |
| dc.subject.keywordPlus | Magnet configurations | - |
| dc.subject.keywordPlus | Multi-objective genetic algorithm | - |
| dc.subject.keywordPlus | Optimal structures | - |
| dc.subject.keywordPlus | Permanent magnets | - |
| dc.subject.keywordAuthor | finite element method | - |
| dc.subject.keywordAuthor | flux switching permanent magnet machine | - |
| dc.subject.keywordAuthor | multi-objective genetic algorithm | - |
| dc.identifier.url | https://ieeexplore.ieee.org/document/9352278 | - |
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