GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses
This paper, starting from recent papers in the scientific literature dealing with Rotating Induction Motor (RIM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; The main original aspects of the proposed model are th...
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Veröffentlicht in: | IEEE open journal of industry applications 2020, Vol.1, p.135-147 |
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description | This paper, starting from recent papers in the scientific literature dealing with Rotating Induction Motor (RIM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; The main original aspects of the proposed model are the following: 1) the magnetic saturation of the iron core has been described on the basis of both current versus flux and flux versus current functions, 3) it includes the iron losses, separating them in hysteresis and eddy current ones, 4) it includes the effect of the load on the magnetic saturation. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a Finite Element Analysis (FEA) of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up. |
doi_str_mv | 10.1109/OJIA.2020.3024567 |
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Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a Finite Element Analysis (FEA) of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up.</description><identifier>ISSN: 2644-1241</identifier><identifier>EISSN: 2644-1241</identifier><identifier>DOI: 10.1109/OJIA.2020.3024567</identifier><identifier>CODEN: IOJIBK</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Core loss ; Cost function ; Dynamic models ; Eddy currents ; Finite element method ; Genetic algorithms ; Identification ; Induction motors ; Iron ; iron losses ; Magnetic cores ; Magnetic hysteresis ; Magnetic induction ; Magnetic saturation ; Magnetic separation ; Magnetism ; Parameter estimation ; rotating induction motor (rim) ; Rotors ; Saturation magnetization ; space-vector dynamic model ; Stators</subject><ispartof>IEEE open journal of industry applications, 2020, Vol.1, p.135-147</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c468t-63e14da9a4c680a07d2481872251c427e66be547ee734b7e96463899ae2cd9513</citedby><cites>FETCH-LOGICAL-c468t-63e14da9a4c680a07d2481872251c427e66be547ee734b7e96463899ae2cd9513</cites><orcidid>0000-0003-1325-2648 ; 0000-0002-3324-4314</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9200694$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,2102,4024,27633,27923,27924,27925,54933</link.rule.ids></links><search><creatorcontrib>Accetta, Angelo</creatorcontrib><creatorcontrib>Alonge, Francesco</creatorcontrib><creatorcontrib>Cirrincione, Maurizio</creatorcontrib><creatorcontrib>D'Ippolito, Filippo</creatorcontrib><creatorcontrib>Pucci, Marcello</creatorcontrib><creatorcontrib>Sferlazza, Antonino</creatorcontrib><title>GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses</title><title>IEEE open journal of industry applications</title><addtitle>OJIA</addtitle><description>This paper, starting from recent papers in the scientific literature dealing with Rotating Induction Motor (RIM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; The main original aspects of the proposed model are the following: 1) the magnetic saturation of the iron core has been described on the basis of both current versus flux and flux versus current functions, 3) it includes the iron losses, separating them in hysteresis and eddy current ones, 4) it includes the effect of the load on the magnetic saturation. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a Finite Element Analysis (FEA) of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up.</description><subject>Core loss</subject><subject>Cost function</subject><subject>Dynamic models</subject><subject>Eddy currents</subject><subject>Finite element method</subject><subject>Genetic algorithms</subject><subject>Identification</subject><subject>Induction motors</subject><subject>Iron</subject><subject>iron losses</subject><subject>Magnetic cores</subject><subject>Magnetic hysteresis</subject><subject>Magnetic induction</subject><subject>Magnetic saturation</subject><subject>Magnetic separation</subject><subject>Magnetism</subject><subject>Parameter estimation</subject><subject>rotating induction motor (rim)</subject><subject>Rotors</subject><subject>Saturation magnetization</subject><subject>space-vector dynamic model</subject><subject>Stators</subject><issn>2644-1241</issn><issn>2644-1241</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1LJDEUbGQFRf0B4iWw555N0ul8HGfF1V5GRtj1HN4kr8cexo4m6YP_3owt4iV5FFX16lFVdcnogjFqfq3_dssFp5wuGspFK9VRdcqlEDXjgv34Np9UFyntKKW8ZYxxc1q93i7r35DQk3Xf16thRPIAEZ4xYyQ3KQ_PkIcwktCT_ISkG_3kPoD7kEMsr8d9Qd1-8sO4JfewHTEPjvyDPMVZCqMnXSzDKqSE6bw67mGf8OLzP6se_9z8v76rV-vb7nq5qp2QOteyQSY8GBBOagpUeS4004qX6E5whVJusBUKUTVio9BIIRttDCB33rSsOau62dcH2NmXWC6JbzbAYD-AELcWYom6R6tAOia1BKWVwGYDsjdObLBXXHvt-uL1c_Z6ieF1wpTtLkxxLPEtbxteStBUFRabWS6WSyP2X1sZtYei7KEoeyjKfhZVNFezZkDEL77hlEojmnd5TI08</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Accetta, Angelo</creator><creator>Alonge, Francesco</creator><creator>Cirrincione, Maurizio</creator><creator>D'Ippolito, Filippo</creator><creator>Pucci, Marcello</creator><creator>Sferlazza, Antonino</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-1325-2648</orcidid><orcidid>https://orcid.org/0000-0002-3324-4314</orcidid></search><sort><creationdate>2020</creationdate><title>GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses</title><author>Accetta, Angelo ; Alonge, Francesco ; Cirrincione, Maurizio ; D'Ippolito, Filippo ; Pucci, Marcello ; Sferlazza, Antonino</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c468t-63e14da9a4c680a07d2481872251c427e66be547ee734b7e96463899ae2cd9513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Core loss</topic><topic>Cost function</topic><topic>Dynamic models</topic><topic>Eddy currents</topic><topic>Finite element method</topic><topic>Genetic algorithms</topic><topic>Identification</topic><topic>Induction motors</topic><topic>Iron</topic><topic>iron losses</topic><topic>Magnetic cores</topic><topic>Magnetic hysteresis</topic><topic>Magnetic induction</topic><topic>Magnetic saturation</topic><topic>Magnetic separation</topic><topic>Magnetism</topic><topic>Parameter estimation</topic><topic>rotating induction motor (rim)</topic><topic>Rotors</topic><topic>Saturation magnetization</topic><topic>space-vector dynamic model</topic><topic>Stators</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Accetta, Angelo</creatorcontrib><creatorcontrib>Alonge, Francesco</creatorcontrib><creatorcontrib>Cirrincione, Maurizio</creatorcontrib><creatorcontrib>D'Ippolito, Filippo</creatorcontrib><creatorcontrib>Pucci, Marcello</creatorcontrib><creatorcontrib>Sferlazza, Antonino</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE open journal of industry applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Accetta, Angelo</au><au>Alonge, Francesco</au><au>Cirrincione, Maurizio</au><au>D'Ippolito, Filippo</au><au>Pucci, Marcello</au><au>Sferlazza, Antonino</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses</atitle><jtitle>IEEE open journal of industry applications</jtitle><stitle>OJIA</stitle><date>2020</date><risdate>2020</risdate><volume>1</volume><spage>135</spage><epage>147</epage><pages>135-147</pages><issn>2644-1241</issn><eissn>2644-1241</eissn><coden>IOJIBK</coden><abstract>This paper, starting from recent papers in the scientific literature dealing with Rotating Induction Motor (RIM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; The main original aspects of the proposed model are the following: 1) the magnetic saturation of the iron core has been described on the basis of both current versus flux and flux versus current functions, 3) it includes the iron losses, separating them in hysteresis and eddy current ones, 4) it includes the effect of the load on the magnetic saturation. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a Finite Element Analysis (FEA) of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/OJIA.2020.3024567</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-1325-2648</orcidid><orcidid>https://orcid.org/0000-0002-3324-4314</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Core loss Cost function Dynamic models Eddy currents Finite element method Genetic algorithms Identification Induction motors Iron iron losses Magnetic cores Magnetic hysteresis Magnetic induction Magnetic saturation Magnetic separation Magnetism Parameter estimation rotating induction motor (rim) Rotors Saturation magnetization space-vector dynamic model Stators |
title | GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses |
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