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DC poleHodnotaJazyk
dc.contributor.authorJamshidi, Mohammad
dc.contributor.authorTalla, Jakub
dc.contributor.authorPeroutka, Zdeněk
dc.contributor.authorRoshani, Saeed
dc.date.accessioned2022-01-31T11:00:26Z-
dc.date.available2022-01-31T11:00:26Z-
dc.date.issued2021
dc.identifier.citationJAMSHIDI, M. TALLA, J. PEROUTKA, Z. ROSHANI, S. Neuro-fuzzy approaches to estimating thermal overstress behavior of IGBTs. In 2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC) : /proceedings/. Piscaway: IEEE, 2021. s. 843-850. ISBN: 978-1-72815-660-6cs
dc.identifier.isbn978-1-72815-660-6
dc.identifier.uri2-s2.0-85107490862
dc.identifier.urihttp://hdl.handle.net/11025/46661
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherIEEEen
dc.relation.ispartofseries2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC) : /proceedings/en
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights© IEEEen
dc.titleNeuro-fuzzy approaches to estimating thermal overstress behavior of IGBTsen
dc.typekonferenční příspěvekcs
dc.typeConferenceObjecten
dc.rights.accessrestrictedAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThe Thermal overstress behavior of power semiconductor components is a determining factor to evaluate the reliability and performance of power electronic devices. Many theoretical and empirical methods have been presented to address the thermal effects of power electronics components on the quality of power systems. However, analyzing temperature brings to us a large number of uncertainties and nonlinearities affecting the accuracy of modeling. This paper proposes three neuro-fuzzy based techniques to estimate the temperature of Insulated Gate Bipolar Transistors (IGBTs). These techniques include grid partitioning clustering, Fuzzy C-Means (FCM) clustering, and subtractive clustering. An experimental dataset containing over 1.5 million data points is used to develop and train the proposed neuro-fuzzy approaches. This dataset is obtained during a comprehensive investigation on IGBTs and thermal effects by scientists at Ames Research Center of NASA. Preliminary results have demonstrated that the applied approaches are superior to estimating the thermal overstress behavior of IGBTs.en
dc.subject.translatedIGBTen
dc.subject.translatedfuzzy systemsen
dc.subject.translatedmachine learningen
dc.subject.translatedsystem identificationen
dc.subject.translatedthermal modelen
dc.subject.translatedANFISen
dc.identifier.doi10.1109/PEMC48073.2021.9432584
dc.type.statusPeer-revieweden
dc.identifier.document-number723843000120
dc.identifier.obd43933328
dc.project.IDEF18_069/0009855/Elektrotechnické technologie s vysokým podílem vestavěné inteligencecs
Vyskytuje se v kolekcích:Konferenční příspěvky / Conference papers (RICE)
Konferenční příspěvky / Conference Papers (KEV)
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