Improved Position Observer Using Adaptive Training Control-based Filter for Interior Permanent Magnet Synchronous Motor Drives
Rotor position is the key information to achieve superior performance for sensorless control of interior permanent magnet synchronous motor (IPMSM). Nevertheless, the back electromotive force (EMF) model-based position estimation suffers from severe contamination from the fifth and seventh harmonics...
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| Veröffentlicht in: | IEEE transactions on power electronics 2023-08, Vol.38 (8), p.1-10 |
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| creator | Wu, Xuan Yang, Dan Yu, Xu Lu, Kaiyuan Wu, Ting Huang, Shoudao Cui, Hesong |
| description | Rotor position is the key information to achieve superior performance for sensorless control of interior permanent magnet synchronous motor (IPMSM). Nevertheless, the back electromotive force (EMF) model-based position estimation suffers from severe contamination from the fifth and seventh harmonics resulting from inverter nonlinearity and flux spatial harmonics. Therefore, an adaptive training control-based adaptive filter combined with a sliding-mode observer (SMO) is presented for harmonics rejection in the estimated back-EMF, and thus improving the rotor position estimation performance. This method, based on the steepest descent algorithm, is capable of self-adjusting harmonic coefficients to obtain the fundamental component online under various frequency conditions adaptively. Additionally, the proposed method has simpler structure and less calculation burden since its reference signal is self-generated without external injection compared to the conventional method. The effectiveness is verified by experiments at a 1.5-kW IPMSM drive platform. |
| doi_str_mv | 10.1109/TPEL.2023.3280254 |
| format | Article |
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Nevertheless, the back electromotive force (EMF) model-based position estimation suffers from severe contamination from the fifth and seventh harmonics resulting from inverter nonlinearity and flux spatial harmonics. Therefore, an adaptive training control-based adaptive filter combined with a sliding-mode observer (SMO) is presented for harmonics rejection in the estimated back-EMF, and thus improving the rotor position estimation performance. This method, based on the steepest descent algorithm, is capable of self-adjusting harmonic coefficients to obtain the fundamental component online under various frequency conditions adaptively. Additionally, the proposed method has simpler structure and less calculation burden since its reference signal is self-generated without external injection compared to the conventional method. The effectiveness is verified by experiments at a 1.5-kW IPMSM drive platform.</description><identifier>ISSN: 0885-8993</identifier><identifier>EISSN: 1941-0107</identifier><identifier>DOI: 10.1109/TPEL.2023.3280254</identifier><identifier>CODEN: ITPEE8</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive control ; Adaptive filters ; Adaptive training control ; Algorithms ; Back electromotive force ; Digital filters ; Electromotive forces ; Estimation ; Harmonic analysis ; Harmonics ; interior permanent magnet synchronous motor (IPMSM) ; Permanent magnets ; position estimation ; Power harmonic filters ; Reference signals ; Rotors ; sensorless ; sliding mode observer (SMO) ; Synchronous motors ; Training</subject><ispartof>IEEE transactions on power electronics, 2023-08, Vol.38 (8), p.1-10</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c294t-66baec3b68779dc121feeadbba789b605bc1faffeff1f7fde4ccc0efd5eff3c73</citedby><cites>FETCH-LOGICAL-c294t-66baec3b68779dc121feeadbba789b605bc1faffeff1f7fde4ccc0efd5eff3c73</cites><orcidid>0000-0002-6923-9605 ; 0000-0003-0763-3313 ; 0000-0002-6051-8595 ; 0000-0001-5601-9884 ; 0000-0003-4012-2611 ; 0000-0001-5737-0879</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10136782$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10136782$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wu, Xuan</creatorcontrib><creatorcontrib>Yang, Dan</creatorcontrib><creatorcontrib>Yu, Xu</creatorcontrib><creatorcontrib>Lu, Kaiyuan</creatorcontrib><creatorcontrib>Wu, Ting</creatorcontrib><creatorcontrib>Huang, Shoudao</creatorcontrib><creatorcontrib>Cui, Hesong</creatorcontrib><title>Improved Position Observer Using Adaptive Training Control-based Filter for Interior Permanent Magnet Synchronous Motor Drives</title><title>IEEE transactions on power electronics</title><addtitle>TPEL</addtitle><description>Rotor position is the key information to achieve superior performance for sensorless control of interior permanent magnet synchronous motor (IPMSM). Nevertheless, the back electromotive force (EMF) model-based position estimation suffers from severe contamination from the fifth and seventh harmonics resulting from inverter nonlinearity and flux spatial harmonics. Therefore, an adaptive training control-based adaptive filter combined with a sliding-mode observer (SMO) is presented for harmonics rejection in the estimated back-EMF, and thus improving the rotor position estimation performance. This method, based on the steepest descent algorithm, is capable of self-adjusting harmonic coefficients to obtain the fundamental component online under various frequency conditions adaptively. Additionally, the proposed method has simpler structure and less calculation burden since its reference signal is self-generated without external injection compared to the conventional method. The effectiveness is verified by experiments at a 1.5-kW IPMSM drive platform.</description><subject>Adaptive control</subject><subject>Adaptive filters</subject><subject>Adaptive training control</subject><subject>Algorithms</subject><subject>Back electromotive force</subject><subject>Digital filters</subject><subject>Electromotive forces</subject><subject>Estimation</subject><subject>Harmonic analysis</subject><subject>Harmonics</subject><subject>interior permanent magnet synchronous motor (IPMSM)</subject><subject>Permanent magnets</subject><subject>position estimation</subject><subject>Power harmonic filters</subject><subject>Reference signals</subject><subject>Rotors</subject><subject>sensorless</subject><subject>sliding mode observer (SMO)</subject><subject>Synchronous motors</subject><subject>Training</subject><issn>0885-8993</issn><issn>1941-0107</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkE1rAjEQhkNpodb2BxR6CPS8Nsl-ZY9itRUUhep5yWYnNqKJTaLgpb-9WfTQ0wzD884wD0LPlAwoJdXbajmeDRhh6SBlnLA8u0E9WmU0IZSUt6hHOM8TXlXpPXrwfksIzXJCe-h3uj84e4IWL63XQVuDF40HdwKH116bDR624hD0CfDKCW26ycia4OwuaYSPuYnehQgr6_DUxE7HZgluLwyYgOdiYyDgr7OR384ae_R4bkNE3l3c6R_RnRI7D0_X2kfryXg1-kxmi4_paDhLJKuykBRFI0CmTcHLsmolZVQBiLZpRMmrpiB5I6kSSoFSVJWqhUxKSUC1eZykskz76PWyNz77cwQf6q09OhNP1owzHkVFdZGiF0o6670DVR-c3gt3rimpO811p7nuNNdXzTHzcsloAPjH07QoOUv_AO86fgk</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Wu, Xuan</creator><creator>Yang, Dan</creator><creator>Yu, Xu</creator><creator>Lu, Kaiyuan</creator><creator>Wu, Ting</creator><creator>Huang, Shoudao</creator><creator>Cui, Hesong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Nevertheless, the back electromotive force (EMF) model-based position estimation suffers from severe contamination from the fifth and seventh harmonics resulting from inverter nonlinearity and flux spatial harmonics. Therefore, an adaptive training control-based adaptive filter combined with a sliding-mode observer (SMO) is presented for harmonics rejection in the estimated back-EMF, and thus improving the rotor position estimation performance. This method, based on the steepest descent algorithm, is capable of self-adjusting harmonic coefficients to obtain the fundamental component online under various frequency conditions adaptively. Additionally, the proposed method has simpler structure and less calculation burden since its reference signal is self-generated without external injection compared to the conventional method. 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| subjects | Adaptive control Adaptive filters Adaptive training control Algorithms Back electromotive force Digital filters Electromotive forces Estimation Harmonic analysis Harmonics interior permanent magnet synchronous motor (IPMSM) Permanent magnets position estimation Power harmonic filters Reference signals Rotors sensorless sliding mode observer (SMO) Synchronous motors Training |
| title | Improved Position Observer Using Adaptive Training Control-based Filter for Interior Permanent Magnet Synchronous Motor Drives |
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