Supercapacitor Modeling: A System Identification Approach
Recently a great deal of attention has been given to supercapacitors (SC) due to their outstanding power densities and long cycling life. Their behavior has been extensively analyzed and tested through several modeling approaches. One common technique for modeling the dynamic operation of SCs is thr...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on energy conversion 2023-03, Vol.38 (1), p.1-11 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 11 |
|---|---|
| container_issue | 1 |
| container_start_page | 1 |
| container_title | IEEE transactions on energy conversion |
| container_volume | 38 |
| creator | Slaifstein, Dario Ibanez, Federico Martin Siwek, Katarzyna |
| description | Recently a great deal of attention has been given to supercapacitors (SC) due to their outstanding power densities and long cycling life. Their behavior has been extensively analyzed and tested through several modeling approaches. One common technique for modeling the dynamic operation of SCs is through an electrical circuit model (ECM). This article presents a new approach to identifying ECM parameters by applying subspace system identification (SSID) algorithms and incorporating coulombic efficiency. This novel application of SSID improves model accuracy by almost 50% in some cases compared to the literature procedures. This was done without manual tuning of the parameters, risk of non-convergence or any prior knowledge. The approach was validated at three different temperatures and with experimental data from an electric motorcycle. The resulting models are ready to be used as building blocks in a wide range of applications such as energy management systems, renewable power generation, electric vehicles, and microgrids. |
| doi_str_mv | 10.1109/TEC.2022.3212617 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_ieee_primary_9913712</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9913712</ieee_id><sourcerecordid>2778699638</sourcerecordid><originalsourceid>FETCH-LOGICAL-c221t-32a13f493eb1e8ab05d44734f8791f4b2102d428565008e0ce19c1b9b57a248f3</originalsourceid><addsrcrecordid>eNo9kDFPwzAUhC0EEqWwI7FEYk5579lObLaqaqFSEUPLbDmOA6naJNjp0H9PqlZMt3x3J32MPSJMEEG_bOazCQHRhBNShvkVG6GUKgWQ-pqNQCmZKp3pW3YX4xYAhSQcMb0-dD4421lX921IPtrS7-rm-zWZJutj7P0-WZa-6euqdrav2yaZdl1orfu5ZzeV3UX_cMkx-1rMN7P3dPX5tpxNV6kjwj7lZJFXQnNfoFe2AFkKkXNRqVxjJQpCoFKQkpkEUB6cR-2w0IXMLQlV8TF7Pu8Ot78HH3uzbQ-hGS4N5bnKtM64Gig4Uy60MQZfmS7UexuOBsGcBJlBkDkJMhdBQ-XpXKm99_-41shzJP4H-fJfeQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2778699638</pqid></control><display><type>article</type><title>Supercapacitor Modeling: A System Identification Approach</title><source>IEEE Electronic Library (IEL)</source><creator>Slaifstein, Dario ; Ibanez, Federico Martin ; Siwek, Katarzyna</creator><creatorcontrib>Slaifstein, Dario ; Ibanez, Federico Martin ; Siwek, Katarzyna</creatorcontrib><description>Recently a great deal of attention has been given to supercapacitors (SC) due to their outstanding power densities and long cycling life. Their behavior has been extensively analyzed and tested through several modeling approaches. One common technique for modeling the dynamic operation of SCs is through an electrical circuit model (ECM). This article presents a new approach to identifying ECM parameters by applying subspace system identification (SSID) algorithms and incorporating coulombic efficiency. This novel application of SSID improves model accuracy by almost 50% in some cases compared to the literature procedures. This was done without manual tuning of the parameters, risk of non-convergence or any prior knowledge. The approach was validated at three different temperatures and with experimental data from an electric motorcycle. The resulting models are ready to be used as building blocks in a wide range of applications such as energy management systems, renewable power generation, electric vehicles, and microgrids.</description><identifier>ISSN: 0885-8969</identifier><identifier>EISSN: 1558-0059</identifier><identifier>DOI: 10.1109/TEC.2022.3212617</identifier><identifier>CODEN: ITCNE4</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Capacitors ; Circuits ; Distributed generation ; Electric motorcycles ; Electric vehicles ; Electrodes ; Energy management systems ; Equivalent circuits ; Integrated circuit modeling ; Mathematical models ; Model accuracy ; modeling ; Modelling ; Motorcycles ; Parameter identification ; power electronics ; storage ; subspace system identification ; supercapacitor ; Supercapacitors ; System identification ; Time-domain analysis ; Tuning</subject><ispartof>IEEE transactions on energy conversion, 2023-03, Vol.38 (1), p.1-11</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c221t-32a13f493eb1e8ab05d44734f8791f4b2102d428565008e0ce19c1b9b57a248f3</citedby><cites>FETCH-LOGICAL-c221t-32a13f493eb1e8ab05d44734f8791f4b2102d428565008e0ce19c1b9b57a248f3</cites><orcidid>0000-0003-1560-4942 ; 0000-0001-8654-2131</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9913712$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9913712$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Slaifstein, Dario</creatorcontrib><creatorcontrib>Ibanez, Federico Martin</creatorcontrib><creatorcontrib>Siwek, Katarzyna</creatorcontrib><title>Supercapacitor Modeling: A System Identification Approach</title><title>IEEE transactions on energy conversion</title><addtitle>TEC</addtitle><description>Recently a great deal of attention has been given to supercapacitors (SC) due to their outstanding power densities and long cycling life. Their behavior has been extensively analyzed and tested through several modeling approaches. One common technique for modeling the dynamic operation of SCs is through an electrical circuit model (ECM). This article presents a new approach to identifying ECM parameters by applying subspace system identification (SSID) algorithms and incorporating coulombic efficiency. This novel application of SSID improves model accuracy by almost 50% in some cases compared to the literature procedures. This was done without manual tuning of the parameters, risk of non-convergence or any prior knowledge. The approach was validated at three different temperatures and with experimental data from an electric motorcycle. The resulting models are ready to be used as building blocks in a wide range of applications such as energy management systems, renewable power generation, electric vehicles, and microgrids.</description><subject>Algorithms</subject><subject>Capacitors</subject><subject>Circuits</subject><subject>Distributed generation</subject><subject>Electric motorcycles</subject><subject>Electric vehicles</subject><subject>Electrodes</subject><subject>Energy management systems</subject><subject>Equivalent circuits</subject><subject>Integrated circuit modeling</subject><subject>Mathematical models</subject><subject>Model accuracy</subject><subject>modeling</subject><subject>Modelling</subject><subject>Motorcycles</subject><subject>Parameter identification</subject><subject>power electronics</subject><subject>storage</subject><subject>subspace system identification</subject><subject>supercapacitor</subject><subject>Supercapacitors</subject><subject>System identification</subject><subject>Time-domain analysis</subject><subject>Tuning</subject><issn>0885-8969</issn><issn>1558-0059</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kDFPwzAUhC0EEqWwI7FEYk5579lObLaqaqFSEUPLbDmOA6naJNjp0H9PqlZMt3x3J32MPSJMEEG_bOazCQHRhBNShvkVG6GUKgWQ-pqNQCmZKp3pW3YX4xYAhSQcMb0-dD4421lX921IPtrS7-rm-zWZJutj7P0-WZa-6euqdrav2yaZdl1orfu5ZzeV3UX_cMkx-1rMN7P3dPX5tpxNV6kjwj7lZJFXQnNfoFe2AFkKkXNRqVxjJQpCoFKQkpkEUB6cR-2w0IXMLQlV8TF7Pu8Ot78HH3uzbQ-hGS4N5bnKtM64Gig4Uy60MQZfmS7UexuOBsGcBJlBkDkJMhdBQ-XpXKm99_-41shzJP4H-fJfeQ</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Slaifstein, Dario</creator><creator>Ibanez, Federico Martin</creator><creator>Siwek, Katarzyna</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-1560-4942</orcidid><orcidid>https://orcid.org/0000-0001-8654-2131</orcidid></search><sort><creationdate>20230301</creationdate><title>Supercapacitor Modeling: A System Identification Approach</title><author>Slaifstein, Dario ; Ibanez, Federico Martin ; Siwek, Katarzyna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c221t-32a13f493eb1e8ab05d44734f8791f4b2102d428565008e0ce19c1b9b57a248f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Capacitors</topic><topic>Circuits</topic><topic>Distributed generation</topic><topic>Electric motorcycles</topic><topic>Electric vehicles</topic><topic>Electrodes</topic><topic>Energy management systems</topic><topic>Equivalent circuits</topic><topic>Integrated circuit modeling</topic><topic>Mathematical models</topic><topic>Model accuracy</topic><topic>modeling</topic><topic>Modelling</topic><topic>Motorcycles</topic><topic>Parameter identification</topic><topic>power electronics</topic><topic>storage</topic><topic>subspace system identification</topic><topic>supercapacitor</topic><topic>Supercapacitors</topic><topic>System identification</topic><topic>Time-domain analysis</topic><topic>Tuning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Slaifstein, Dario</creatorcontrib><creatorcontrib>Ibanez, Federico Martin</creatorcontrib><creatorcontrib>Siwek, Katarzyna</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on energy conversion</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Slaifstein, Dario</au><au>Ibanez, Federico Martin</au><au>Siwek, Katarzyna</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Supercapacitor Modeling: A System Identification Approach</atitle><jtitle>IEEE transactions on energy conversion</jtitle><stitle>TEC</stitle><date>2023-03-01</date><risdate>2023</risdate><volume>38</volume><issue>1</issue><spage>1</spage><epage>11</epage><pages>1-11</pages><issn>0885-8969</issn><eissn>1558-0059</eissn><coden>ITCNE4</coden><abstract>Recently a great deal of attention has been given to supercapacitors (SC) due to their outstanding power densities and long cycling life. Their behavior has been extensively analyzed and tested through several modeling approaches. One common technique for modeling the dynamic operation of SCs is through an electrical circuit model (ECM). This article presents a new approach to identifying ECM parameters by applying subspace system identification (SSID) algorithms and incorporating coulombic efficiency. This novel application of SSID improves model accuracy by almost 50% in some cases compared to the literature procedures. This was done without manual tuning of the parameters, risk of non-convergence or any prior knowledge. The approach was validated at three different temperatures and with experimental data from an electric motorcycle. The resulting models are ready to be used as building blocks in a wide range of applications such as energy management systems, renewable power generation, electric vehicles, and microgrids.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TEC.2022.3212617</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-1560-4942</orcidid><orcidid>https://orcid.org/0000-0001-8654-2131</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0885-8969 |
| ispartof | IEEE transactions on energy conversion, 2023-03, Vol.38 (1), p.1-11 |
| issn | 0885-8969 1558-0059 |
| language | eng |
| recordid | cdi_ieee_primary_9913712 |
| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Capacitors Circuits Distributed generation Electric motorcycles Electric vehicles Electrodes Energy management systems Equivalent circuits Integrated circuit modeling Mathematical models Model accuracy modeling Modelling Motorcycles Parameter identification power electronics storage subspace system identification supercapacitor Supercapacitors System identification Time-domain analysis Tuning |
| title | Supercapacitor Modeling: A System Identification Approach |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T07%3A13%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Supercapacitor%20Modeling:%20A%20System%20Identification%20Approach&rft.jtitle=IEEE%20transactions%20on%20energy%20conversion&rft.au=Slaifstein,%20Dario&rft.date=2023-03-01&rft.volume=38&rft.issue=1&rft.spage=1&rft.epage=11&rft.pages=1-11&rft.issn=0885-8969&rft.eissn=1558-0059&rft.coden=ITCNE4&rft_id=info:doi/10.1109/TEC.2022.3212617&rft_dat=%3Cproquest_RIE%3E2778699638%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2778699638&rft_id=info:pmid/&rft_ieee_id=9913712&rfr_iscdi=true |