Improved sliding mode observer-based SOC estimation for lithium battery
In this paper, lithium battery state of charge (SOC) is estimated by using sliding mode observer and H∞ filter. Firstly, through the discharge experiment, parameters of the second-order RC equivalent circuit model of battery are identified. Secondly, by combining sliding mode observer method and H∞...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 1 |
| container_start_page | |
| container_title | |
| container_volume | 2122 |
| creator | Zhang, Hongfei Fu, Zhumu Tao, Fazhan |
| description | In this paper, lithium battery state of charge (SOC) is estimated by using sliding mode observer and H∞ filter. Firstly, through the discharge experiment, parameters of the second-order RC equivalent circuit model of battery are identified. Secondly, by combining sliding mode observer method and H∞ filtering algorithm, the SOC estimation error covariance matrix in real time is updated for adjusting the observation gain matrix. An improved sliding mode observer is designed to estimate the battery’s SOC. Simulation results show that the designed control algorithm has higher estimation accuracy, and the estimation error is lower than 5%, which is 2% higher than H∞ filtering algorithm and 7% higher than that of sliding mode observer. |
| doi_str_mv | 10.1063/1.5116497 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>proquest_scita</sourceid><recordid>TN_cdi_proquest_journals_2257924684</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2257924684</sourcerecordid><originalsourceid>FETCH-LOGICAL-c293t-6be58974b1e72f815cf73de9d2f4dc192a47f37657633d9010bb16ffc636d2673</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMoWKsH_0HAm7CayefmKEVrodCDCt7CZpNoSrdbk7TQf-9qC948zWGed-bhRegayB0Qye7hTgBIrtUJGoEQUCkJ8hSNCNG8opy9n6OLnJeEUK1UPULTWbdJ_c47nFfRxfUH7nrncW-zTzufKtvkYfeymGCfS-yaEvs1Dn3Cq1g-47bDtinFp_0lOgvNKvur4xyjt6fH18lzNV9MZ5OHedVSzUolrRe1VtyCVzTUINqgmPPa0cBdC5o2XAWmpFCSMacJEGtBhtBKJh2Vio3RzeHuYP21HZzMst-m9fDSUCqUplzWfKBuD1RuY_l1Nps02Ke92fXJgDmWZDYu_AcDMT-t_gXYN--faKI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>2257924684</pqid></control><display><type>conference_proceeding</type><title>Improved sliding mode observer-based SOC estimation for lithium battery</title><source>AIP Journals Complete</source><creator>Zhang, Hongfei ; Fu, Zhumu ; Tao, Fazhan</creator><contributor>Liu, Lin ; Zhou, Jun Xiao Yang</contributor><creatorcontrib>Zhang, Hongfei ; Fu, Zhumu ; Tao, Fazhan ; Liu, Lin ; Zhou, Jun Xiao Yang</creatorcontrib><description>In this paper, lithium battery state of charge (SOC) is estimated by using sliding mode observer and H∞ filter. Firstly, through the discharge experiment, parameters of the second-order RC equivalent circuit model of battery are identified. Secondly, by combining sliding mode observer method and H∞ filtering algorithm, the SOC estimation error covariance matrix in real time is updated for adjusting the observation gain matrix. An improved sliding mode observer is designed to estimate the battery’s SOC. Simulation results show that the designed control algorithm has higher estimation accuracy, and the estimation error is lower than 5%, which is 2% higher than H∞ filtering algorithm and 7% higher than that of sliding mode observer.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/1.5116497</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Algorithms ; Batteries ; Computer simulation ; Control algorithms ; Control theory ; Covariance matrix ; Equivalent circuits ; Filtration ; H-infinity control ; Lithium ; Lithium batteries ; Order parameters ; Parameter identification ; Sliding mode control ; State of charge</subject><ispartof>AIP Conference Proceedings, 2019, Vol.2122 (1)</ispartof><rights>Author(s)</rights><rights>2019 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-6be58974b1e72f815cf73de9d2f4dc192a47f37657633d9010bb16ffc636d2673</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubs.aip.org/acp/article-lookup/doi/10.1063/1.5116497$$EHTML$$P50$$Gscitation$$H</linktohtml><link.rule.ids>309,310,314,780,784,789,790,794,4512,23930,23931,25140,27924,27925,76384</link.rule.ids></links><search><contributor>Liu, Lin</contributor><contributor>Zhou, Jun Xiao Yang</contributor><creatorcontrib>Zhang, Hongfei</creatorcontrib><creatorcontrib>Fu, Zhumu</creatorcontrib><creatorcontrib>Tao, Fazhan</creatorcontrib><title>Improved sliding mode observer-based SOC estimation for lithium battery</title><title>AIP Conference Proceedings</title><description>In this paper, lithium battery state of charge (SOC) is estimated by using sliding mode observer and H∞ filter. Firstly, through the discharge experiment, parameters of the second-order RC equivalent circuit model of battery are identified. Secondly, by combining sliding mode observer method and H∞ filtering algorithm, the SOC estimation error covariance matrix in real time is updated for adjusting the observation gain matrix. An improved sliding mode observer is designed to estimate the battery’s SOC. Simulation results show that the designed control algorithm has higher estimation accuracy, and the estimation error is lower than 5%, which is 2% higher than H∞ filtering algorithm and 7% higher than that of sliding mode observer.</description><subject>Algorithms</subject><subject>Batteries</subject><subject>Computer simulation</subject><subject>Control algorithms</subject><subject>Control theory</subject><subject>Covariance matrix</subject><subject>Equivalent circuits</subject><subject>Filtration</subject><subject>H-infinity control</subject><subject>Lithium</subject><subject>Lithium batteries</subject><subject>Order parameters</subject><subject>Parameter identification</subject><subject>Sliding mode control</subject><subject>State of charge</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2019</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNp9kE1LAzEQhoMoWKsH_0HAm7CayefmKEVrodCDCt7CZpNoSrdbk7TQf-9qC948zWGed-bhRegayB0Qye7hTgBIrtUJGoEQUCkJ8hSNCNG8opy9n6OLnJeEUK1UPULTWbdJ_c47nFfRxfUH7nrncW-zTzufKtvkYfeymGCfS-yaEvs1Dn3Cq1g-47bDtinFp_0lOgvNKvur4xyjt6fH18lzNV9MZ5OHedVSzUolrRe1VtyCVzTUINqgmPPa0cBdC5o2XAWmpFCSMacJEGtBhtBKJh2Vio3RzeHuYP21HZzMst-m9fDSUCqUplzWfKBuD1RuY_l1Nps02Ke92fXJgDmWZDYu_AcDMT-t_gXYN--faKI</recordid><startdate>20190715</startdate><enddate>20190715</enddate><creator>Zhang, Hongfei</creator><creator>Fu, Zhumu</creator><creator>Tao, Fazhan</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20190715</creationdate><title>Improved sliding mode observer-based SOC estimation for lithium battery</title><author>Zhang, Hongfei ; Fu, Zhumu ; Tao, Fazhan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-6be58974b1e72f815cf73de9d2f4dc192a47f37657633d9010bb16ffc636d2673</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Batteries</topic><topic>Computer simulation</topic><topic>Control algorithms</topic><topic>Control theory</topic><topic>Covariance matrix</topic><topic>Equivalent circuits</topic><topic>Filtration</topic><topic>H-infinity control</topic><topic>Lithium</topic><topic>Lithium batteries</topic><topic>Order parameters</topic><topic>Parameter identification</topic><topic>Sliding mode control</topic><topic>State of charge</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Hongfei</creatorcontrib><creatorcontrib>Fu, Zhumu</creatorcontrib><creatorcontrib>Tao, Fazhan</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Hongfei</au><au>Fu, Zhumu</au><au>Tao, Fazhan</au><au>Liu, Lin</au><au>Zhou, Jun Xiao Yang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Improved sliding mode observer-based SOC estimation for lithium battery</atitle><btitle>AIP Conference Proceedings</btitle><date>2019-07-15</date><risdate>2019</risdate><volume>2122</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>In this paper, lithium battery state of charge (SOC) is estimated by using sliding mode observer and H∞ filter. Firstly, through the discharge experiment, parameters of the second-order RC equivalent circuit model of battery are identified. Secondly, by combining sliding mode observer method and H∞ filtering algorithm, the SOC estimation error covariance matrix in real time is updated for adjusting the observation gain matrix. An improved sliding mode observer is designed to estimate the battery’s SOC. Simulation results show that the designed control algorithm has higher estimation accuracy, and the estimation error is lower than 5%, which is 2% higher than H∞ filtering algorithm and 7% higher than that of sliding mode observer.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/1.5116497</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0094-243X |
| ispartof | AIP Conference Proceedings, 2019, Vol.2122 (1) |
| issn | 0094-243X 1551-7616 |
| language | eng |
| recordid | cdi_proquest_journals_2257924684 |
| source | AIP Journals Complete |
| subjects | Algorithms Batteries Computer simulation Control algorithms Control theory Covariance matrix Equivalent circuits Filtration H-infinity control Lithium Lithium batteries Order parameters Parameter identification Sliding mode control State of charge |
| title | Improved sliding mode observer-based SOC estimation for lithium battery |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T11%3A03%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_scita&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Improved%20sliding%20mode%20observer-based%20SOC%20estimation%20for%20lithium%20battery&rft.btitle=AIP%20Conference%20Proceedings&rft.au=Zhang,%20Hongfei&rft.date=2019-07-15&rft.volume=2122&rft.issue=1&rft.issn=0094-243X&rft.eissn=1551-7616&rft.coden=APCPCS&rft_id=info:doi/10.1063/1.5116497&rft_dat=%3Cproquest_scita%3E2257924684%3C/proquest_scita%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2257924684&rft_id=info:pmid/&rfr_iscdi=true |