Bi Input-extended Kalman filter based estimation technique for speed-sensorless control of induction motors

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dc.contributor.authorBarut, Murat
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2010
dc.departmentNiğde ÖHÜ
dc.description.abstractThis study offers a novel extended Kalman filter (EKF) based estimation technique for the solution of the on-line estimation problem related to uncertainties in the stator and rotor resistances inherent to the speed-sensorless high efficiency control of induction motors (IMs) in the wide speed range as well as extending the limited number of states and parameter estimations possible with a conventional single EKF algorithm. For this aim, the introduced estimation technique in this work utilizes a single EKF algorithm with the consecutive execution of two inputs derived from the two individual extended IM models based on the stator resistance and rotor resistance estimation, differently from the other approaches in past studies, which require two separate EKF algorithms operating in a switching or braided manner: thus, it has superiority over the previous EKE schemes in this regard. The proposed EKF based estimation technique performing the on-line estimations of the stator currents, the rotor flux, the rotor angular velocity, and the load torque involving the viscous friction term together with the rotor and stator resistance is also used in the combination with the speed-sensorless direct vector control of IM and tested with simulations under the challenging 12 scenarios generated instantaneously via step and/or linear variations of the velocity reference, the load torque, the stator resistance, and the rotor resistance in the range of high and zero speed, assuming that the measured stator phase currents and voltages are available. Even under those variations, the performance of the speed-sensorless direct vector control system established on the novel EKF based estimation technique is observed to be quite good. (C) 2010 Elsevier Ltd. All tights reserved.
dc.description.sponsorshipScientific and Technical Research Council of Turkey (Turkiye Bilimsel ve Teknolojik Arastirma Kurumu - TUBITAK) [EEAG-108E18]
dc.description.sponsorshipThis work was supported by the Scientific and Technical Research Council of Turkey (Turkiye Bilimsel ve Teknolojik Arastirma Kurumu - TUBITAK) under the Research Grant of EEAG-108E187.
dc.identifier.doi10.1016/j.enconman.2010.02.037
dc.identifier.endpage2040
dc.identifier.issn0196-8904
dc.identifier.issue10
dc.identifier.scopus2-s2.0-77955324707
dc.identifier.scopusqualityQ1
dc.identifier.startpage2032
dc.identifier.urihttps://dx.doi.org/10.1016/j.enconman.2010.02.037
dc.identifier.urihttps://hdl.handle.net/11480/4836
dc.identifier.volume51
dc.identifier.wosWOS:000278730100024
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorBarut, Murat
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartofENERGY CONVERSION AND MANAGEMENT
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectInduction motor
dc.subjectExtended Kalman filter
dc.subjectRotor and stator resistance estimation
dc.subjectLoad torque estimation
dc.subjectSensorless control
dc.subjectZero speed operation
dc.titleBi Input-extended Kalman filter based estimation technique for speed-sensorless control of induction motors
dc.typeArticle

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