Transfer Learning-Based Design Method for Cogging Torque Reduction in PMSM with Step-Skew Considering 3-D Leakage Flux
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Won, Yun-Jae | - |
dc.contributor.author | Kim, Jae-Hyun | - |
dc.contributor.author | Park, Soo-Hwan | - |
dc.contributor.author | Lee, Ji-Hyeon | - |
dc.contributor.author | An, Soo-Min | - |
dc.contributor.author | Kim, Doo-Young | - |
dc.contributor.author | Lim, Myung Seop | - |
dc.date.accessioned | 2023-09-11T01:52:21Z | - |
dc.date.available | 2023-09-11T01:52:21Z | - |
dc.date.created | 2023-07-20 | - |
dc.date.issued | 2023-05 | - |
dc.identifier.issn | 0018-9464 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/190379 | - |
dc.description.abstract | Step-skew is a common technique for eliminating the cogging torque of a target harmonic order in permanent magnet synchronous motors (PMSMs). However, when step-skew is applied to the rotor, the cogging torque of the target harmonic order is not completely eliminated due to 3-D leakage flux. Therefore, the 3-D leakage flux should be considered in designing a PMSM with step-skew for cogging torque reduction. The most accurate way to consider the 3-D leakage flux is to perform 3-D finite element analysis (FEA), but it has the disadvantage of high computation time. To resolve this challenge, this paper proposes a design method that utilizes transfer learning to reduce the time for 3-D FEA while maintaining accuracy. Through the proposed method, a large amount of 2-D FEA-based data and a small amount of 3-D FEA-based data are used instead of a large amount of 3-D FEA-based data, with similar accuracy as using a large amount of 3-D FEA-based data, and the computational time is highly reduced. Finally, a prototype is fabricated and tested to verify the validity of the proposed design method for cogging torque reduction. IEEE | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INSTITUTE OF ELECTRICAL and ELECTRONICS ENGINEERS | - |
dc.title | Transfer Learning-Based Design Method for Cogging Torque Reduction in PMSM with Step-Skew Considering 3-D Leakage Flux | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lim, Myung Seop | - |
dc.identifier.doi | 10.1109/TMAG.2023.3294601 | - |
dc.identifier.scopusid | 2-s2.0-85165277209 | - |
dc.identifier.bibliographicCitation | IEEE International Conference on Magnetics (INTERMAG), pp.1 - 5 | - |
dc.relation.isPartOf | IEEE International Conference on Magnetics (INTERMAG) | - |
dc.citation.title | IEEE International Conference on Magnetics (INTERMAG) | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 5 | - |
dc.type.rims | ART | - |
dc.type.docType | Proceeding | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | 3-D leakage flux | - |
dc.subject.keywordPlus | Cogging torque | - |
dc.subject.keywordPlus | Deep neural network | - |
dc.subject.keywordPlus | Design Methodology | - |
dc.subject.keywordPlus | Forging | - |
dc.subject.keywordPlus | Leakage flux | - |
dc.subject.keywordPlus | Permanent magnet synchronoi motor | - |
dc.subject.keywordPlus | Permanent Magnet Synchronous Motor | - |
dc.subject.keywordPlus | Step skews | - |
dc.subject.keywordPlus | Transfer learning | - |
dc.subject.keywordAuthor | 3-D leakage flux | - |
dc.subject.keywordAuthor | Cogging torque | - |
dc.subject.keywordAuthor | deep neural network (DNN) | - |
dc.subject.keywordAuthor | Design methodology | - |
dc.subject.keywordAuthor | Forging | - |
dc.subject.keywordAuthor | Geometry | - |
dc.subject.keywordAuthor | Harmonic analysis | - |
dc.subject.keywordAuthor | permanent magnet synchronous motors (PMSMs) | - |
dc.subject.keywordAuthor | Rotors | - |
dc.subject.keywordAuthor | step-skew | - |
dc.subject.keywordAuthor | Torque | - |
dc.subject.keywordAuthor | transfer learning | - |
dc.subject.keywordAuthor | Transfer learning | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/10184449 | - |
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