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Optimal design of electric machine using genetic algorithms coupled with direct method

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DC Field Value Language
dc.contributor.authorOh, Y.H.-
dc.contributor.authorChung, T.K.-
dc.contributor.authorKim, M.K.-
dc.contributor.authorJung, H.K.-
dc.date.accessioned2022-01-07T05:49:45Z-
dc.date.available2022-01-07T05:49:45Z-
dc.date.issued1999-05-
dc.identifier.issn0018-9464-
dc.identifier.issn1941-0069-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/53039-
dc.description.abstractThis paper discusses the development of a new optimization algorithm for DC motor design. In principle, the new algorithm utilizes a mixed method that consists of genetic algorithms in conjunction with direct search method. The genetic algorithms are used for locating the global optimum region while the direct search method is used to achieve objective function convergence. In order to validate the effectiveness, the new algorithm has been applied to an actual DC motor. Field and torque characteristics of the DC motor are computed using finite element method and the principle of virtual work, respectively.-
dc.format.extent4-
dc.language영어-
dc.language.isoENG-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleOptimal design of electric machine using genetic algorithms coupled with direct method-
dc.typeArticle-
dc.identifier.doi10.1109/20.767366-
dc.identifier.bibliographicCitationIEEE TRANSACTIONS ON MAGNETICS, v.35, no.3, pp 1742 - 1745-
dc.description.isOpenAccessN-
dc.identifier.wosid000080490900162-
dc.identifier.scopusid2-s2.0-0033121691-
dc.citation.endPage1745-
dc.citation.number3-
dc.citation.startPage1742-
dc.citation.titleIEEE TRANSACTIONS ON MAGNETICS-
dc.citation.volume35-
dc.type.docTypeArticle; Proceedings Paper-
dc.publisher.location미국-
dc.subject.keywordAuthoroptimization method-
dc.subject.keywordAuthorgenetic algorithm-
dc.subject.keywordAuthorDC motor-
dc.subject.keywordPlusOPTIMIZATION-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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