Rotor Temperature Online Estimation of Built-in Permanent Magnet Synchronous Motor for Electric Vehicle
Realizing the online monitoring of the rotor temperature of the permanent magnet synchronous motor used in electric vehicles is not only crucial to ensure the normal operation of the motor, but also increases the duration of the motor's peak torque and maximizes the motor's working potenti...
Gespeichert in:
Veröffentlicht in: | Ji xie gong cheng xue bao 2023, Vol.59 (24), p.209 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 24 |
container_start_page | 209 |
container_title | Ji xie gong cheng xue bao |
container_volume | 59 |
creator | Xiao, Zongxin Hu, Minghui Shi, Liwang Zhou, Anjian |
description | Realizing the online monitoring of the rotor temperature of the permanent magnet synchronous motor used in electric vehicles is not only crucial to ensure the normal operation of the motor, but also increases the duration of the motor's peak torque and maximizes the motor's working potential. Therefore, based on the idea of magneto-thermal bidirectional coupling, a specific magnetic-thermal bidirectional coupling technical route for estimating the rotor temperature of the built-in permanent magnet synchronous motor(IPMSM) for vehicles is proposed. Firstly, on the basis of the traditional motor lumped parameter model, a lumped parameter electromagnetic model considering the influence of motor temperature is established; then, based on the temperature characteristics of the resistance, magnetic density, and electrical conductivity of the IPMSM material, a motor loss model considering the influence of motor temperature is established. Finally, according to the principle of heat transfer and the distribution of motor loss, the motor is divided into nodes, an equivalent thermal network model of IPMSM is established, and the thermal parameters in the thermal network model are identified by particle swarm optimization algorithm. Combined with the electromagnetic model, loss model and equivalent thermal network model, a magneto-thermal bidirectional coupled rotor temperature online estimation model is constructed, which realizes the rapid online estimation of the rotor temperature of the motor. The accuracy of the rotor temperature estimation model is verified by bench tests and real vehicle road tests under different ambient temperatures and working conditions. The test results show that the proposed rotor temperature estimation model has high estimation accuracy, and the rotor temperature estimation errors are all within ±3 ℃, which can greatly increase the rotor temperature threshold, prolong the peak torque duration, and improve the motor performance. |
doi_str_mv | 10.3901/JME.2023.24.209 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3037077817</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3037077817</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1559-b0f1b3781710474e41f9765d56c4b6e61638ad52b3c95ceddd8fe31877560ecf3</originalsourceid><addsrcrecordid>eNotkD1PwzAURT2ARCnMrJaY09pxbCcjVOFLjYqgsFqJ89ymSu1iO0P_PSlleDrL1bl6F6E7SmasIHT-VpWzlKRslmYjiws0IVzKRIhcXKHrEHaEsEKmdII2Hy46j9ewP4Cv4-ABr2zfWcBliN2-jp2z2Bn8OHR9TDqL38Hvaws24qreWIj482j11jvrhoCrP5kZr-xBR99p_A3bTvdwgy5N3Qe4_ecUfT2V68VLslw9vy4elommnBdJQwxtmMyppCSTGWTUFFLwlgudNQIEFSyvW542TBdcQ9u2uQFGcym5IKANm6L7s_fg3c8AIaqdG7wdKxUjTBJ5co-p-TmlvQvBg1EHPz7rj4oSdVpQjQuq04IqzUYW7BewW2ZF</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3037077817</pqid></control><display><type>article</type><title>Rotor Temperature Online Estimation of Built-in Permanent Magnet Synchronous Motor for Electric Vehicle</title><source>Alma/SFX Local Collection</source><creator>Xiao, Zongxin ; Hu, Minghui ; Shi, Liwang ; Zhou, Anjian</creator><creatorcontrib>Xiao, Zongxin ; Hu, Minghui ; Shi, Liwang ; Zhou, Anjian</creatorcontrib><description>Realizing the online monitoring of the rotor temperature of the permanent magnet synchronous motor used in electric vehicles is not only crucial to ensure the normal operation of the motor, but also increases the duration of the motor's peak torque and maximizes the motor's working potential. Therefore, based on the idea of magneto-thermal bidirectional coupling, a specific magnetic-thermal bidirectional coupling technical route for estimating the rotor temperature of the built-in permanent magnet synchronous motor(IPMSM) for vehicles is proposed. Firstly, on the basis of the traditional motor lumped parameter model, a lumped parameter electromagnetic model considering the influence of motor temperature is established; then, based on the temperature characteristics of the resistance, magnetic density, and electrical conductivity of the IPMSM material, a motor loss model considering the influence of motor temperature is established. Finally, according to the principle of heat transfer and the distribution of motor loss, the motor is divided into nodes, an equivalent thermal network model of IPMSM is established, and the thermal parameters in the thermal network model are identified by particle swarm optimization algorithm. Combined with the electromagnetic model, loss model and equivalent thermal network model, a magneto-thermal bidirectional coupled rotor temperature online estimation model is constructed, which realizes the rapid online estimation of the rotor temperature of the motor. The accuracy of the rotor temperature estimation model is verified by bench tests and real vehicle road tests under different ambient temperatures and working conditions. The test results show that the proposed rotor temperature estimation model has high estimation accuracy, and the rotor temperature estimation errors are all within ±3 ℃, which can greatly increase the rotor temperature threshold, prolong the peak torque duration, and improve the motor performance.</description><identifier>ISSN: 0577-6686</identifier><identifier>DOI: 10.3901/JME.2023.24.209</identifier><language>eng</language><publisher>Beijing: Chinese Mechanical Engineering Society (CMES)</publisher><subject>Algorithms ; Ambient temperature ; Coupling ; Electric vehicles ; Electrical resistivity ; Equivalence ; Estimation ; Mathematical models ; Parameter identification ; Particle swarm optimization ; Permanent magnets ; Road tests ; Rotors ; Synchronous motors ; Temperature ; Thermodynamic properties ; Torque</subject><ispartof>Ji xie gong cheng xue bao, 2023, Vol.59 (24), p.209</ispartof><rights>Copyright Chinese Mechanical Engineering Society (CMES) 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c1559-b0f1b3781710474e41f9765d56c4b6e61638ad52b3c95ceddd8fe31877560ecf3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,4010,27904,27905,27906</link.rule.ids></links><search><creatorcontrib>Xiao, Zongxin</creatorcontrib><creatorcontrib>Hu, Minghui</creatorcontrib><creatorcontrib>Shi, Liwang</creatorcontrib><creatorcontrib>Zhou, Anjian</creatorcontrib><title>Rotor Temperature Online Estimation of Built-in Permanent Magnet Synchronous Motor for Electric Vehicle</title><title>Ji xie gong cheng xue bao</title><description>Realizing the online monitoring of the rotor temperature of the permanent magnet synchronous motor used in electric vehicles is not only crucial to ensure the normal operation of the motor, but also increases the duration of the motor's peak torque and maximizes the motor's working potential. Therefore, based on the idea of magneto-thermal bidirectional coupling, a specific magnetic-thermal bidirectional coupling technical route for estimating the rotor temperature of the built-in permanent magnet synchronous motor(IPMSM) for vehicles is proposed. Firstly, on the basis of the traditional motor lumped parameter model, a lumped parameter electromagnetic model considering the influence of motor temperature is established; then, based on the temperature characteristics of the resistance, magnetic density, and electrical conductivity of the IPMSM material, a motor loss model considering the influence of motor temperature is established. Finally, according to the principle of heat transfer and the distribution of motor loss, the motor is divided into nodes, an equivalent thermal network model of IPMSM is established, and the thermal parameters in the thermal network model are identified by particle swarm optimization algorithm. Combined with the electromagnetic model, loss model and equivalent thermal network model, a magneto-thermal bidirectional coupled rotor temperature online estimation model is constructed, which realizes the rapid online estimation of the rotor temperature of the motor. The accuracy of the rotor temperature estimation model is verified by bench tests and real vehicle road tests under different ambient temperatures and working conditions. The test results show that the proposed rotor temperature estimation model has high estimation accuracy, and the rotor temperature estimation errors are all within ±3 ℃, which can greatly increase the rotor temperature threshold, prolong the peak torque duration, and improve the motor performance.</description><subject>Algorithms</subject><subject>Ambient temperature</subject><subject>Coupling</subject><subject>Electric vehicles</subject><subject>Electrical resistivity</subject><subject>Equivalence</subject><subject>Estimation</subject><subject>Mathematical models</subject><subject>Parameter identification</subject><subject>Particle swarm optimization</subject><subject>Permanent magnets</subject><subject>Road tests</subject><subject>Rotors</subject><subject>Synchronous motors</subject><subject>Temperature</subject><subject>Thermodynamic properties</subject><subject>Torque</subject><issn>0577-6686</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNotkD1PwzAURT2ARCnMrJaY09pxbCcjVOFLjYqgsFqJ89ymSu1iO0P_PSlleDrL1bl6F6E7SmasIHT-VpWzlKRslmYjiws0IVzKRIhcXKHrEHaEsEKmdII2Hy46j9ewP4Cv4-ABr2zfWcBliN2-jp2z2Bn8OHR9TDqL38Hvaws24qreWIj482j11jvrhoCrP5kZr-xBR99p_A3bTvdwgy5N3Qe4_ecUfT2V68VLslw9vy4elommnBdJQwxtmMyppCSTGWTUFFLwlgudNQIEFSyvW542TBdcQ9u2uQFGcym5IKANm6L7s_fg3c8AIaqdG7wdKxUjTBJ5co-p-TmlvQvBg1EHPz7rj4oSdVpQjQuq04IqzUYW7BewW2ZF</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Xiao, Zongxin</creator><creator>Hu, Minghui</creator><creator>Shi, Liwang</creator><creator>Zhou, Anjian</creator><general>Chinese Mechanical Engineering Society (CMES)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>2023</creationdate><title>Rotor Temperature Online Estimation of Built-in Permanent Magnet Synchronous Motor for Electric Vehicle</title><author>Xiao, Zongxin ; Hu, Minghui ; Shi, Liwang ; Zhou, Anjian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1559-b0f1b3781710474e41f9765d56c4b6e61638ad52b3c95ceddd8fe31877560ecf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Ambient temperature</topic><topic>Coupling</topic><topic>Electric vehicles</topic><topic>Electrical resistivity</topic><topic>Equivalence</topic><topic>Estimation</topic><topic>Mathematical models</topic><topic>Parameter identification</topic><topic>Particle swarm optimization</topic><topic>Permanent magnets</topic><topic>Road tests</topic><topic>Rotors</topic><topic>Synchronous motors</topic><topic>Temperature</topic><topic>Thermodynamic properties</topic><topic>Torque</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xiao, Zongxin</creatorcontrib><creatorcontrib>Hu, Minghui</creatorcontrib><creatorcontrib>Shi, Liwang</creatorcontrib><creatorcontrib>Zhou, Anjian</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Ji xie gong cheng xue bao</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xiao, Zongxin</au><au>Hu, Minghui</au><au>Shi, Liwang</au><au>Zhou, Anjian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Rotor Temperature Online Estimation of Built-in Permanent Magnet Synchronous Motor for Electric Vehicle</atitle><jtitle>Ji xie gong cheng xue bao</jtitle><date>2023</date><risdate>2023</risdate><volume>59</volume><issue>24</issue><spage>209</spage><pages>209-</pages><issn>0577-6686</issn><abstract>Realizing the online monitoring of the rotor temperature of the permanent magnet synchronous motor used in electric vehicles is not only crucial to ensure the normal operation of the motor, but also increases the duration of the motor's peak torque and maximizes the motor's working potential. Therefore, based on the idea of magneto-thermal bidirectional coupling, a specific magnetic-thermal bidirectional coupling technical route for estimating the rotor temperature of the built-in permanent magnet synchronous motor(IPMSM) for vehicles is proposed. Firstly, on the basis of the traditional motor lumped parameter model, a lumped parameter electromagnetic model considering the influence of motor temperature is established; then, based on the temperature characteristics of the resistance, magnetic density, and electrical conductivity of the IPMSM material, a motor loss model considering the influence of motor temperature is established. Finally, according to the principle of heat transfer and the distribution of motor loss, the motor is divided into nodes, an equivalent thermal network model of IPMSM is established, and the thermal parameters in the thermal network model are identified by particle swarm optimization algorithm. Combined with the electromagnetic model, loss model and equivalent thermal network model, a magneto-thermal bidirectional coupled rotor temperature online estimation model is constructed, which realizes the rapid online estimation of the rotor temperature of the motor. The accuracy of the rotor temperature estimation model is verified by bench tests and real vehicle road tests under different ambient temperatures and working conditions. The test results show that the proposed rotor temperature estimation model has high estimation accuracy, and the rotor temperature estimation errors are all within ±3 ℃, which can greatly increase the rotor temperature threshold, prolong the peak torque duration, and improve the motor performance.</abstract><cop>Beijing</cop><pub>Chinese Mechanical Engineering Society (CMES)</pub><doi>10.3901/JME.2023.24.209</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0577-6686 |
ispartof | Ji xie gong cheng xue bao, 2023, Vol.59 (24), p.209 |
issn | 0577-6686 |
language | eng |
recordid | cdi_proquest_journals_3037077817 |
source | Alma/SFX Local Collection |
subjects | Algorithms Ambient temperature Coupling Electric vehicles Electrical resistivity Equivalence Estimation Mathematical models Parameter identification Particle swarm optimization Permanent magnets Road tests Rotors Synchronous motors Temperature Thermodynamic properties Torque |
title | Rotor Temperature Online Estimation of Built-in Permanent Magnet Synchronous Motor for Electric Vehicle |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T04%3A24%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Rotor%20Temperature%20Online%20Estimation%20of%20Built-in%20Permanent%20Magnet%20Synchronous%20Motor%20for%20Electric%20Vehicle&rft.jtitle=Ji%20xie%20gong%20cheng%20xue%20bao&rft.au=Xiao,%20Zongxin&rft.date=2023&rft.volume=59&rft.issue=24&rft.spage=209&rft.pages=209-&rft.issn=0577-6686&rft_id=info:doi/10.3901/JME.2023.24.209&rft_dat=%3Cproquest_cross%3E3037077817%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3037077817&rft_id=info:pmid/&rfr_iscdi=true |