Dynamic induction machine models including magnetic saturation and iron losses

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Hinkkanen, Marko, Prof., Aalto University, Department of Electrical Engineering, Finland
dc.contributor.author Ranta, Mikaela
dc.date.accessioned 2013-11-14T10:00:23Z
dc.date.available 2013-11-14T10:00:23Z
dc.date.issued 2013
dc.identifier.isbn 978-952-60-5396-7 (electronic)
dc.identifier.isbn 978-952-60-5395-0 (printed)
dc.identifier.issn 1799-4942 (electronic)
dc.identifier.issn 1799-4934 (printed)
dc.identifier.issn 1799-4934 (ISSN-L)
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/11343
dc.description.abstract Dynamic induction machine models are used as the basis for the design and implementation of control algorithms. Costs can be reduced by applying speed-sensorless control, and advanced control strategies open up for the possibility of using an induction machine in demanding applications. However, a reliable and good control performance requires more detailed induction machine models. This thesis deals with models including the magnetic saturation and iron losses. A small-signal model, which includes the saturation due to variations in the main flux magnitude and the load torque, is used to analyze the transient behavior of the machine. Due to the magnetic saturation, the inductances vary as a function of the operating point, and the machine appears to be salient in transients. Based on the model, an identification method for the leakage inductance is proposed. The identification is based on signal injection and can be performed as the machine is running under different load conditions. A model for the skin effect of the rotor bars can be used in combination with the leakage inductance identification in the case of an induction machine equipped with deep rotor bars. The magnetizing curve can be modeled using a simple power function. An adaptive identification method is developed for the identification of magnetizing curve parameters. Identification of the leakage inductance prior to the magnetizing curve identification improves the results in case a no-load condition cannot be reached. The stator hysteresis and eddy current losses are modeled using a nonlinear resistance. The resistance is not dependent on any frequency, and is thus defined also during transients. The resistance model is experimentally investigated both for the case of an induction machine and a nonlinear inductor. The iron loss model is used in a loss-minimizing control algorithm for the induction machine. en
dc.description.abstract Dynamiska modeller av induktionsmotorn används som grund for att utforma och tillämpa styralgoritmer. Kostnadseffektiva lösningar kan uppnås genom att tillämpa styrsystem utan varvtalsmatare, dessutom har avancerade styrsystem möjliggjort att induktionsmotorn aven används i mer kravande användningsområden. For att åstadkomma bra prestanda behovs emellertid mer detaljerade modeller av induktionsmotorn. Denna avhandling handlar om modeller som inkluderar magnetisk mättnad och kärnförluster. Maskinens transienta egenskaper analyseras med hjälp av en småsignalmodell som inkluderar magnetisk mättnad orsakad av variationer i det magnetiska flödet och vridmomentet. Induktanserna i modellen varierar som funktion av arbetspunkten p.g.a. den magnetiska mättnaden, och maskinen förefaller ha utpräglade poler vid transienta förlopp. En identifieringsmetod for lackinduktansen föreslås på basen av modellen. Identifieringsmetoden baseras på injicerade signaler och kan utföras under normal användning av maskinen och vid olika grad av belastning. En modell for skineffekten i rotorn kan användas i kombination med identifieringsmetoden for maskiner som har djupa rotorspar. Magnetiseringskurvan kan beskrivas med en enkel potensfunktion. En adaptiv identifieringsmetod utvecklas för att identifiera magnetiseringskurvans parametrar. Om identifieringen inte kan utföras utan belastning, förbättras resultatet genom att identifiera lackinduktansen före magnetiseringskurvan. Hysteres- och virvelströmsförluster i statorn modelleras genom att använda en icke-linjär resistans. Frekvensen ingår ej som parameter i resistansfunktionen och resistansen ar därmed definerbar ocksa i transienta förlopp. Modellen for kärnförluster undersöks experimentellt både for en induktionsmotor och en icke-linjär induktor. Modellen implementeras aven i en algoritm for minimering av förlusterna i en induktionsmotor. sv
dc.format.extent 59 + app. 84
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Aalto University en
dc.publisher Aalto-yliopisto fi
dc.relation.ispartofseries Aalto University publication series DOCTORAL DISSERTATIONS en
dc.relation.ispartofseries 171/2013
dc.relation.haspart [Publication 1]: M. Ranta, M. Hinkkanen, A.-K. Repo, and J. Luomi. Small-signal analysis of a saturated induction motor. In Nordic Workshop on Power and Industrial Electronics (NORPIE) 2008, Espoo, Finland, June 2008.
dc.relation.haspart [Publication 2]: M. Ranta, M. Hinkkanen, and J. Luomi. Inductance identification of an induction machine taking load-dependent saturation into account. In International Conference on Electrical Machines (ICEM) 2008, Vilamoura, Portugal, September 2008.
dc.relation.haspart [Publication 3]: M. Ranta, M. Hinkkanen, E. Dlala, A.-K. Repo, and J. Luomi. Inclusion of hysteresis and eddy current losses in dynamic induction machine models. In IEEE International Electric Machines & Drives Conference (IEMDC) 2009, Miami, Florida, May 2009.
dc.relation.haspart [Publication 4]: M. Ranta, M. Hinkkanen, and J. Luomi. Rotor parameter identification of saturated induction machines. In IEEE Energy Conversion Congress and Exposition (ECCE) 2009, San Jose, California, September 2009.
dc.relation.haspart [Publication 5]: M. Hinkkanen, A.-K. Repo, M. Ranta, and J. Luomi. Small-signal modeling of mutual saturation in induction machines. IEEE Transactions on Industry Applications, vol. 46, issue 3, pp. 965–973, May-June 2010.
dc.relation.haspart [Publication 6]: M. Ranta, M. Hinkkanen, A. Belahcen, and J. Luomi. Inclusion of hysteresis and eddy current losses in nonlinear time-domain inductance models. In 37th Annual Conference of the IEEE Industrial Electronics Society (IECON) 2011, Melbourne, Australia, November 2011.
dc.relation.haspart [Publication 7]: Z. Qu, M. Ranta, M. Hinkkanen, and J. Luomi. Loss-minimizing flux level control of induction motor drives. IEEE Transactions on Industry Applications, vol. 48, issue 3, pp. 952–961, May-June 2012.
dc.relation.haspart [Publication 8]: M. Ranta and M. Hinkkanen. Online identification of parameters defining the saturation characteristics of induction machines. IEEE Transactions on Industry Applications, vol. 49, issue 5, pp. 2136–2145, Sept.- Oct. 2013.
dc.subject.other Electrical engineering en
dc.title Dynamic induction machine models including magnetic saturation and iron losses en
dc.type G5 Artikkeliväitöskirja fi
dc.contributor.school Sähkötekniikan korkeakoulu fi
dc.contributor.school School of Electrical Engineering en
dc.contributor.department Sähkötekniikan laitos fi
dc.contributor.department Department of Electrical Engineering en
dc.subject.keyword induction machines en
dc.subject.keyword dynamic models en
dc.subject.keyword magnetic saturation en
dc.subject.keyword iron losses en
dc.subject.keyword induktionsmotor sv
dc.subject.keyword dynamiska modeller sv
dc.subject.keyword magnetisk mättnad sv
dc.subject.keyword kärnförluster sv
dc.identifier.urn URN:ISBN:978-952-60-5396-7
dc.type.dcmitype text en
dc.type.ontasot Doctoral dissertation (article-based) en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.contributor.supervisor Luomi, Jorma, Prof., Aalto University, Department of Electrical Engineering, Finland
dc.contributor.supervisor Hinkkanen, Marko, Prof., Aalto University, Department of Electrical Engineering, Finland
dc.opn Thiringer,Torbjörn, Prof., Chalmers University of Technology, Sweden
dc.contributor.lab Electric drives en
dc.rev Melkebeek, Jan, Prof., Ghent University, Belgium
dc.rev Pedra, Joaquín, Prof., Universitat Politècnica de Catalunya, Spain
dc.date.defence 2013-11-29


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