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Identification and Suppression of Electromagnetic Noise of Variable Reluctance Resolver for Hybrid Electric Vehicle

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dc.contributor.authorKim, Hwigon-
dc.contributor.authorLee, Joohyun-
dc.contributor.authorLim, Jae Sang-
dc.contributor.authorKim, Young Un-
dc.contributor.authorSul, Seung-Ki-
dc.date.accessioned2022-10-11T02:11:21Z-
dc.date.available2022-10-11T02:11:21Z-
dc.date.created2022-09-30-
dc.date.issued2022-06-
dc.identifier.citation2022 IEEE/AIAA TRANSPORTATION ELECTRIFICATION CONFERENCE AND ELECTRIC AIRCRAFT TECHNOLOGIES SYMPOSIUM (ITEC+EATS 2022), pp.13-17-
dc.identifier.urihttps://hdl.handle.net/10371/185782-
dc.description.abstractFollowing the development of electric and hybrid vehicles, permanent-magnet synchronous machines (PMSMs) have been widely used as traction motors. In most PMSM drives, the rotor position sensor is required for reliable torque control. A variable reluctance resolver has been adopted as a position sensor in automotive industries thanks to its mechanical reliability in a harsh environment. Because the resolver signal is analog, the signal is vulnerable to the noise caused by electromagnetic interference such as common-mode voltage and external magnetic field. In this paper, the source of electromagnetic noise in the target motor system is identified experimentally. From finite element analysis ( FEA), the noise path to the position signal of the resolver is identified. Furthermore, a strategy to suppress the noise is devised and evaluated with FEA and verified experimentally with an actual motor.-
dc.language영어-
dc.publisherIEEE-
dc.titleIdentification and Suppression of Electromagnetic Noise of Variable Reluctance Resolver for Hybrid Electric Vehicle-
dc.typeArticle-
dc.identifier.doi10.1109/ITEC53557.2022.9813901-
dc.citation.journaltitle2022 IEEE/AIAA TRANSPORTATION ELECTRIFICATION CONFERENCE AND ELECTRIC AIRCRAFT TECHNOLOGIES SYMPOSIUM (ITEC+EATS 2022)-
dc.identifier.wosid000848063600003-
dc.identifier.scopusid2-s2.0-85134658789-
dc.citation.endpage17-
dc.citation.startpage13-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorSul, Seung-Ki-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
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