Parameter matching and optimization for power system of range-extended electric vehicle based on requirements
For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle powe...
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| Veröffentlicht in: | Proceedings of the Institution of Mechanical Engineers. Part D, Journal of automobile engineering Journal of automobile engineering, 2020-12, Vol.234 (14), p.3316-3328 |
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| container_title | Proceedings of the Institution of Mechanical Engineers. Part D, Journal of automobile engineering |
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| creator | Liu, Hanwu Lei, Yulong Fu, Yao Li, Xingzhong |
| description | For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle. |
| doi_str_mv | 10.1177/0954407020936781 |
| format | Article |
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Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle.</description><identifier>ISSN: 0954-4070</identifier><identifier>EISSN: 2041-2991</identifier><identifier>DOI: 10.1177/0954407020936781</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Algorithms ; Auxiliary power units ; Business metrics ; Coupling ; Design optimization ; Design parameters ; Electric power systems ; Electric vehicles ; Energy consumption ; Indicators ; Matching ; Mathematical models ; Multiple objective analysis ; Optimization ; Parameter sensitivity ; Particle swarm optimization ; Sensitivity analysis ; Simulation ; Variance analysis</subject><ispartof>Proceedings of the Institution of Mechanical Engineers. Part D, Journal of automobile engineering, 2020-12, Vol.234 (14), p.3316-3328</ispartof><rights>IMechE 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c309t-b48e7936355025c6a95297e0fcccf6942b755934f577ae701ca7e2e2b1c035cb3</citedby><cites>FETCH-LOGICAL-c309t-b48e7936355025c6a95297e0fcccf6942b755934f577ae701ca7e2e2b1c035cb3</cites><orcidid>0000-0002-0382-0552</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0954407020936781$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0954407020936781$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21798,27901,27902,43597,43598</link.rule.ids></links><search><creatorcontrib>Liu, Hanwu</creatorcontrib><creatorcontrib>Lei, Yulong</creatorcontrib><creatorcontrib>Fu, Yao</creatorcontrib><creatorcontrib>Li, Xingzhong</creatorcontrib><title>Parameter matching and optimization for power system of range-extended electric vehicle based on requirements</title><title>Proceedings of the Institution of Mechanical Engineers. Part D, Journal of automobile engineering</title><description>For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle.</description><subject>Algorithms</subject><subject>Auxiliary power units</subject><subject>Business metrics</subject><subject>Coupling</subject><subject>Design optimization</subject><subject>Design parameters</subject><subject>Electric power systems</subject><subject>Electric vehicles</subject><subject>Energy consumption</subject><subject>Indicators</subject><subject>Matching</subject><subject>Mathematical models</subject><subject>Multiple objective analysis</subject><subject>Optimization</subject><subject>Parameter sensitivity</subject><subject>Particle swarm optimization</subject><subject>Sensitivity analysis</subject><subject>Simulation</subject><subject>Variance analysis</subject><issn>0954-4070</issn><issn>2041-2991</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kM1LAzEQxYMoWKt3jwHP0SSbbJqjFL-goAc9L9l0tk1pNtskVetfb0oFQXAuA_N-b4Z5CF0yes2YUjdUSyGoopzqqlYTdoRGnApGuNbsGI32Mtnrp-gspRUtpYQcIf9iovGQIWJvsl26foFNP8dhyM67L5Nd6HEXIh7CR2HSLmXwOHQ4mn4BBD4z9HOYY1iDzdFZ_A5LZ9eAW5PKuJgjbLYugoc-p3N00pl1goufPkZv93ev00cye354mt7OiK2ozqQVE1DljUpKyqWtjZZcK6CdtbarteCtklJXopNKGVCUWaOAA2-ZpZW0bTVGV4e9QwybLaTcrMI29uVkw4UUVa0ntS4UPVA2hpQidM0QnTdx1zDa7ENt_oZaLORgSWYBv0v_5b8ByTV3yg</recordid><startdate>202012</startdate><enddate>202012</enddate><creator>Liu, Hanwu</creator><creator>Lei, Yulong</creator><creator>Fu, Yao</creator><creator>Li, Xingzhong</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><orcidid>https://orcid.org/0000-0002-0382-0552</orcidid></search><sort><creationdate>202012</creationdate><title>Parameter matching and optimization for power system of range-extended electric vehicle based on requirements</title><author>Liu, Hanwu ; Lei, Yulong ; Fu, Yao ; Li, Xingzhong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c309t-b48e7936355025c6a95297e0fcccf6942b755934f577ae701ca7e2e2b1c035cb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Auxiliary power units</topic><topic>Business metrics</topic><topic>Coupling</topic><topic>Design optimization</topic><topic>Design parameters</topic><topic>Electric power systems</topic><topic>Electric vehicles</topic><topic>Energy consumption</topic><topic>Indicators</topic><topic>Matching</topic><topic>Mathematical models</topic><topic>Multiple objective analysis</topic><topic>Optimization</topic><topic>Parameter sensitivity</topic><topic>Particle swarm optimization</topic><topic>Sensitivity analysis</topic><topic>Simulation</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Hanwu</creatorcontrib><creatorcontrib>Lei, Yulong</creatorcontrib><creatorcontrib>Fu, Yao</creatorcontrib><creatorcontrib>Li, Xingzhong</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>Proceedings of the Institution of Mechanical Engineers. Part D, Journal of automobile engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Hanwu</au><au>Lei, Yulong</au><au>Fu, Yao</au><au>Li, Xingzhong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Parameter matching and optimization for power system of range-extended electric vehicle based on requirements</atitle><jtitle>Proceedings of the Institution of Mechanical Engineers. Part D, Journal of automobile engineering</jtitle><date>2020-12</date><risdate>2020</risdate><volume>234</volume><issue>14</issue><spage>3316</spage><epage>3328</epage><pages>3316-3328</pages><issn>0954-4070</issn><eissn>2041-2991</eissn><abstract>For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><doi>10.1177/0954407020936781</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-0382-0552</orcidid></addata></record> |
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| subjects | Algorithms Auxiliary power units Business metrics Coupling Design optimization Design parameters Electric power systems Electric vehicles Energy consumption Indicators Matching Mathematical models Multiple objective analysis Optimization Parameter sensitivity Particle swarm optimization Sensitivity analysis Simulation Variance analysis |
| title | Parameter matching and optimization for power system of range-extended electric vehicle based on requirements |
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