Online Monitoring of Interturn Short Circuit Current in PMSMs

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dc.contributor.authorZezula, Lukášcs
dc.contributor.authorBlaha, Petrcs
dc.date.accessioned2025-04-04T11:56:21Z
dc.date.available2025-04-04T11:56:21Z
dc.date.issued2025-03-10cs
dc.description.abstractThis paper extends the previously published parameter estimation-based approach to interturn short circuit diagnostics in permanent magnet synchronous motors by real-time monitoring of hidden machine states after fault occurrence. The designed monitoring method relies on an adaptive formulation of the Kalman filter, which assumes interdependence between measurement and process noise variables. A variable forgetting factor not only mitigates the impact of the process model uncertainty but also facilitates the simultaneous operation of the monitoring algorithm and fault indicator estimation. Furthermore, contributions of fault current and healthy machine model to stationary reference frame currents are estimated from an advanced discrete-time motor description reflecting a stator winding arrangement inside a motor's case. The monitoring algorithm is validated in steady state, torque load transient, and velocity transient laboratory experiments with diverse fault severity values.en
dc.formattextcs
dc.format.extent6cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationIECON 2024: 50th Annual Conference of the IEEE Industrial Electronics Society. 2025, 6 p.en
dc.identifier.doi10.1109/IECON55916.2024.10905190cs
dc.identifier.isbn978-1-6654-6454-3cs
dc.identifier.orcid0000-0002-3183-2438cs
dc.identifier.orcid0000-0001-5534-2065cs
dc.identifier.other193484cs
dc.identifier.researcheridD-6854-2012cs
dc.identifier.scopus7006825993cs
dc.identifier.urihttps://hdl.handle.net/11012/250727
dc.language.isoencs
dc.publisherIEEEcs
dc.relation.ispartofIECON 2024: 50th Annual Conference of the IEEE Industrial Electronics Societycs
dc.relation.urihttps://ieeexplore.ieee.org/document/10905190cs
dc.rights(C) IEEEcs
dc.rights.accessopenAccesscs
dc.subjectdiscrete-time systemsen
dc.subjectfault currentsen
dc.subjectfault diagnosisen
dc.subjectKalman filtersen
dc.subjectpermanent magnet machinesen
dc.subjectshort-circuit currentsen
dc.subjectstate estimationen
dc.titleOnline Monitoring of Interturn Short Circuit Current in PMSMsen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionacceptedVersionen
sync.item.dbidVAV-193484en
sync.item.dbtypeVAVen
sync.item.insts2025.04.04 13:56:21en
sync.item.modts2025.04.03 13:32:12en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav automatizace a měřicí technikycs
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Kybernetika a robotikacs
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