Topology Comparison and Sensitivity Analysis of Fuel Cell Hybrid Systems for Electric Vehicles
The hybrid system containing the fuel cell and energy storage sources contributes to realizing hydrogen energy in road traffic applications. It is meaningful to evaluate the different forms of system topology. In this work, the quantitative comparison of topologies and sensitivity analysis of system...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on transportation electrification 2023-12, Vol.9 (4), p.1-1 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1 |
|---|---|
| container_issue | 4 |
| container_start_page | 1 |
| container_title | IEEE transactions on transportation electrification |
| container_volume | 9 |
| creator | Li, Mince Yu, Pengli Wang, Yujie Sun, Zhendong Chen, Zonghai |
| description | The hybrid system containing the fuel cell and energy storage sources contributes to realizing hydrogen energy in road traffic applications. It is meaningful to evaluate the different forms of system topology. In this work, the quantitative comparison of topologies and sensitivity analysis of system parameters are conducted. Firstly, the output characteristics of the fuel cell, battery, and ultracapacitor are modeled by experimental data. Secondly, the dimensions of four hybrid topologies are determined by an iterative constraint method. An energy management strategy based on dynamic programming is conducted for all topologies. Then the overall economic cost is used as an indicator for quantitative evaluation, considering the initial acquisition, hydrogen consumption, and component aging. The base-case results illustrate that the fuel/cell battery semi-active topology is the least costly one. Finally, seven parameters are analyzed to determine the system cost's key factors. The relationship between costs and driving conditions is further studied. The rankings of the normalized parameter analysis results inspire us on how to further reduce the cost of fuel cell hybrid vehicles. |
| doi_str_mv | 10.1109/TTE.2022.3218341 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_ieee_primary_9933463</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9933463</ieee_id><sourcerecordid>2904460157</sourcerecordid><originalsourceid>FETCH-LOGICAL-c291t-78df9e6e32341501a6fb3ce608e6134efd18c07b11a00859c283b272db3b61563</originalsourceid><addsrcrecordid>eNpNkM9LwzAUx4MoOHR3wUvAc2d-tGlyHGVzwsCD1aOhTV81I2tq0gn97-3YEE_vHT7fx_d9ELqjZEEpUY9luVowwtiCMyp5Si_QjHHOkjyX7PLffo3mMe4IITTjmaJihj5K33vnP0dc-H1fBRt9h6uuwa_QRTvYHzuMeNlVbow2Yt_i9QEcLsA5vBnrYCdwjAPsI259wCsHZgjW4Hf4ssZBvEVXbeUizM_zBr2tV2WxSbYvT8_FcpsYpuiQ5LJpFQjgbCqfEVqJtuYGBJEgKE-hbag0JK8prQiRmTJM8prlrKl5LWgm-A16ON3tg_8-QBz0zh_CVDtqpkiaiunjfKLIiTLBxxig1X2w-yqMmhJ9FKknkfooUp9FTpH7U8QCwB-uFOep4PwX4GZt_g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2904460157</pqid></control><display><type>article</type><title>Topology Comparison and Sensitivity Analysis of Fuel Cell Hybrid Systems for Electric Vehicles</title><source>IEEE Electronic Library (IEL)</source><creator>Li, Mince ; Yu, Pengli ; Wang, Yujie ; Sun, Zhendong ; Chen, Zonghai</creator><creatorcontrib>Li, Mince ; Yu, Pengli ; Wang, Yujie ; Sun, Zhendong ; Chen, Zonghai</creatorcontrib><description>The hybrid system containing the fuel cell and energy storage sources contributes to realizing hydrogen energy in road traffic applications. It is meaningful to evaluate the different forms of system topology. In this work, the quantitative comparison of topologies and sensitivity analysis of system parameters are conducted. Firstly, the output characteristics of the fuel cell, battery, and ultracapacitor are modeled by experimental data. Secondly, the dimensions of four hybrid topologies are determined by an iterative constraint method. An energy management strategy based on dynamic programming is conducted for all topologies. Then the overall economic cost is used as an indicator for quantitative evaluation, considering the initial acquisition, hydrogen consumption, and component aging. The base-case results illustrate that the fuel/cell battery semi-active topology is the least costly one. Finally, seven parameters are analyzed to determine the system cost's key factors. The relationship between costs and driving conditions is further studied. The rankings of the normalized parameter analysis results inspire us on how to further reduce the cost of fuel cell hybrid vehicles.</description><identifier>ISSN: 2332-7782</identifier><identifier>ISSN: 2577-4212</identifier><identifier>EISSN: 2332-7782</identifier><identifier>DOI: 10.1109/TTE.2022.3218341</identifier><identifier>CODEN: ITTEBP</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Batteries ; Battery ; Cost analysis ; Costs ; Driving conditions ; Dynamic programming ; Economic impact ; Electric vehicles ; Energy management ; Energy storage ; Fuel cell ; Fuel cells ; Fuels ; Hybrid systems ; Hybrid topology ; Hybrid vehicles ; Hydrogen ; Iterative methods ; Parameter sensitivity ; Quantitative analysis ; Sensitivity analysis ; Topology</subject><ispartof>IEEE transactions on transportation electrification, 2023-12, Vol.9 (4), p.1-1</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-78df9e6e32341501a6fb3ce608e6134efd18c07b11a00859c283b272db3b61563</citedby><cites>FETCH-LOGICAL-c291t-78df9e6e32341501a6fb3ce608e6134efd18c07b11a00859c283b272db3b61563</cites><orcidid>0000-0003-1341-8599 ; 0000-0001-9312-9089 ; 0000-0001-5722-2673 ; 0000-0001-9742-1351</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9933463$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9933463$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Li, Mince</creatorcontrib><creatorcontrib>Yu, Pengli</creatorcontrib><creatorcontrib>Wang, Yujie</creatorcontrib><creatorcontrib>Sun, Zhendong</creatorcontrib><creatorcontrib>Chen, Zonghai</creatorcontrib><title>Topology Comparison and Sensitivity Analysis of Fuel Cell Hybrid Systems for Electric Vehicles</title><title>IEEE transactions on transportation electrification</title><addtitle>TTE</addtitle><description>The hybrid system containing the fuel cell and energy storage sources contributes to realizing hydrogen energy in road traffic applications. It is meaningful to evaluate the different forms of system topology. In this work, the quantitative comparison of topologies and sensitivity analysis of system parameters are conducted. Firstly, the output characteristics of the fuel cell, battery, and ultracapacitor are modeled by experimental data. Secondly, the dimensions of four hybrid topologies are determined by an iterative constraint method. An energy management strategy based on dynamic programming is conducted for all topologies. Then the overall economic cost is used as an indicator for quantitative evaluation, considering the initial acquisition, hydrogen consumption, and component aging. The base-case results illustrate that the fuel/cell battery semi-active topology is the least costly one. Finally, seven parameters are analyzed to determine the system cost's key factors. The relationship between costs and driving conditions is further studied. The rankings of the normalized parameter analysis results inspire us on how to further reduce the cost of fuel cell hybrid vehicles.</description><subject>Batteries</subject><subject>Battery</subject><subject>Cost analysis</subject><subject>Costs</subject><subject>Driving conditions</subject><subject>Dynamic programming</subject><subject>Economic impact</subject><subject>Electric vehicles</subject><subject>Energy management</subject><subject>Energy storage</subject><subject>Fuel cell</subject><subject>Fuel cells</subject><subject>Fuels</subject><subject>Hybrid systems</subject><subject>Hybrid topology</subject><subject>Hybrid vehicles</subject><subject>Hydrogen</subject><subject>Iterative methods</subject><subject>Parameter sensitivity</subject><subject>Quantitative analysis</subject><subject>Sensitivity analysis</subject><subject>Topology</subject><issn>2332-7782</issn><issn>2577-4212</issn><issn>2332-7782</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkM9LwzAUx4MoOHR3wUvAc2d-tGlyHGVzwsCD1aOhTV81I2tq0gn97-3YEE_vHT7fx_d9ELqjZEEpUY9luVowwtiCMyp5Si_QjHHOkjyX7PLffo3mMe4IITTjmaJihj5K33vnP0dc-H1fBRt9h6uuwa_QRTvYHzuMeNlVbow2Yt_i9QEcLsA5vBnrYCdwjAPsI259wCsHZgjW4Hf4ssZBvEVXbeUizM_zBr2tV2WxSbYvT8_FcpsYpuiQ5LJpFQjgbCqfEVqJtuYGBJEgKE-hbag0JK8prQiRmTJM8prlrKl5LWgm-A16ON3tg_8-QBz0zh_CVDtqpkiaiunjfKLIiTLBxxig1X2w-yqMmhJ9FKknkfooUp9FTpH7U8QCwB-uFOep4PwX4GZt_g</recordid><startdate>20231201</startdate><enddate>20231201</enddate><creator>Li, Mince</creator><creator>Yu, Pengli</creator><creator>Wang, Yujie</creator><creator>Sun, Zhendong</creator><creator>Chen, Zonghai</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>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-1341-8599</orcidid><orcidid>https://orcid.org/0000-0001-9312-9089</orcidid><orcidid>https://orcid.org/0000-0001-5722-2673</orcidid><orcidid>https://orcid.org/0000-0001-9742-1351</orcidid></search><sort><creationdate>20231201</creationdate><title>Topology Comparison and Sensitivity Analysis of Fuel Cell Hybrid Systems for Electric Vehicles</title><author>Li, Mince ; Yu, Pengli ; Wang, Yujie ; Sun, Zhendong ; Chen, Zonghai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-78df9e6e32341501a6fb3ce608e6134efd18c07b11a00859c283b272db3b61563</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Batteries</topic><topic>Battery</topic><topic>Cost analysis</topic><topic>Costs</topic><topic>Driving conditions</topic><topic>Dynamic programming</topic><topic>Economic impact</topic><topic>Electric vehicles</topic><topic>Energy management</topic><topic>Energy storage</topic><topic>Fuel cell</topic><topic>Fuel cells</topic><topic>Fuels</topic><topic>Hybrid systems</topic><topic>Hybrid topology</topic><topic>Hybrid vehicles</topic><topic>Hydrogen</topic><topic>Iterative methods</topic><topic>Parameter sensitivity</topic><topic>Quantitative analysis</topic><topic>Sensitivity analysis</topic><topic>Topology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Mince</creatorcontrib><creatorcontrib>Yu, Pengli</creatorcontrib><creatorcontrib>Wang, Yujie</creatorcontrib><creatorcontrib>Sun, Zhendong</creatorcontrib><creatorcontrib>Chen, Zonghai</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>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on transportation electrification</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Li, Mince</au><au>Yu, Pengli</au><au>Wang, Yujie</au><au>Sun, Zhendong</au><au>Chen, Zonghai</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Topology Comparison and Sensitivity Analysis of Fuel Cell Hybrid Systems for Electric Vehicles</atitle><jtitle>IEEE transactions on transportation electrification</jtitle><stitle>TTE</stitle><date>2023-12-01</date><risdate>2023</risdate><volume>9</volume><issue>4</issue><spage>1</spage><epage>1</epage><pages>1-1</pages><issn>2332-7782</issn><issn>2577-4212</issn><eissn>2332-7782</eissn><coden>ITTEBP</coden><abstract>The hybrid system containing the fuel cell and energy storage sources contributes to realizing hydrogen energy in road traffic applications. It is meaningful to evaluate the different forms of system topology. In this work, the quantitative comparison of topologies and sensitivity analysis of system parameters are conducted. Firstly, the output characteristics of the fuel cell, battery, and ultracapacitor are modeled by experimental data. Secondly, the dimensions of four hybrid topologies are determined by an iterative constraint method. An energy management strategy based on dynamic programming is conducted for all topologies. Then the overall economic cost is used as an indicator for quantitative evaluation, considering the initial acquisition, hydrogen consumption, and component aging. The base-case results illustrate that the fuel/cell battery semi-active topology is the least costly one. Finally, seven parameters are analyzed to determine the system cost's key factors. The relationship between costs and driving conditions is further studied. The rankings of the normalized parameter analysis results inspire us on how to further reduce the cost of fuel cell hybrid vehicles.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/TTE.2022.3218341</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-1341-8599</orcidid><orcidid>https://orcid.org/0000-0001-9312-9089</orcidid><orcidid>https://orcid.org/0000-0001-5722-2673</orcidid><orcidid>https://orcid.org/0000-0001-9742-1351</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2332-7782 |
| ispartof | IEEE transactions on transportation electrification, 2023-12, Vol.9 (4), p.1-1 |
| issn | 2332-7782 2577-4212 2332-7782 |
| language | eng |
| recordid | cdi_ieee_primary_9933463 |
| source | IEEE Electronic Library (IEL) |
| subjects | Batteries Battery Cost analysis Costs Driving conditions Dynamic programming Economic impact Electric vehicles Energy management Energy storage Fuel cell Fuel cells Fuels Hybrid systems Hybrid topology Hybrid vehicles Hydrogen Iterative methods Parameter sensitivity Quantitative analysis Sensitivity analysis Topology |
| title | Topology Comparison and Sensitivity Analysis of Fuel Cell Hybrid Systems for Electric Vehicles |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T03%3A11%3A46IST&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=Topology%20Comparison%20and%20Sensitivity%20Analysis%20of%20Fuel%20Cell%20Hybrid%20Systems%20for%20Electric%20Vehicles&rft.jtitle=IEEE%20transactions%20on%20transportation%20electrification&rft.au=Li,%20Mince&rft.date=2023-12-01&rft.volume=9&rft.issue=4&rft.spage=1&rft.epage=1&rft.pages=1-1&rft.issn=2332-7782&rft.eissn=2332-7782&rft.coden=ITTEBP&rft_id=info:doi/10.1109/TTE.2022.3218341&rft_dat=%3Cproquest_RIE%3E2904460157%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=2904460157&rft_id=info:pmid/&rft_ieee_id=9933463&rfr_iscdi=true |