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Optimal path planning method of electric vehicles considering power supply
Because of the limitations of electric vehicle (EV) battery technology and relevant supporting facilities, there is a great risk of breakdown of EVs during driving. The resulting driver “range anxiety” greatly affects the travel quality of EVs. These limitations should be overcome to promote the use...
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Published in: | Journal of Central South University 2022, Vol.29 (1), p.331-345 |
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creator | Guo, Dong Li, Chao-chao Yan, Wei Hao, Yu-jiao Xu, Yi Wang, Yu-qiong Zhou, Ying-chao Wen-juan, E. Zhang, Tong-qing Gao, Xing-bang Tan, Xiao-chuan |
description | Because of the limitations of electric vehicle (EV) battery technology and relevant supporting facilities, there is a great risk of breakdown of EVs during driving. The resulting driver “range anxiety” greatly affects the travel quality of EVs. These limitations should be overcome to promote the use of EVs. In this study, a method for travel path planning considering EV power supply was developed. First, based on real-time road conditions, a dynamic energy model of EVs was established considering the driving energy and accessory energy. Second, a multi-objective travel path planning model of EVs was constructed considering the power supply, taking the distance, time, energy, and charging cost as the optimization objectives. Finally, taking the actual traffic network of 15 km×15 km area in a city as the research object, the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm. The simulation results show that compared with the traditional route planning method, the total distance in the proposed optimal route planning method increased by 1.18%, but the energy consumption, charging cost, and driving time decreased by 11.62%, 41.26% and 11.00%, respectively, thus effectively reducing the travel cost of EVs and improving the driving quality of EVs. |
doi_str_mv | 10.1007/s11771-022-4924-x |
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The resulting driver “range anxiety” greatly affects the travel quality of EVs. These limitations should be overcome to promote the use of EVs. In this study, a method for travel path planning considering EV power supply was developed. First, based on real-time road conditions, a dynamic energy model of EVs was established considering the driving energy and accessory energy. Second, a multi-objective travel path planning model of EVs was constructed considering the power supply, taking the distance, time, energy, and charging cost as the optimization objectives. Finally, taking the actual traffic network of 15 km×15 km area in a city as the research object, the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm. The simulation results show that compared with the traditional route planning method, the total distance in the proposed optimal route planning method increased by 1.18%, but the energy consumption, charging cost, and driving time decreased by 11.62%, 41.26% and 11.00%, respectively, thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.</description><identifier>ISSN: 2095-2899</identifier><identifier>EISSN: 2227-5223</identifier><identifier>DOI: 10.1007/s11771-022-4924-x</identifier><language>eng</language><publisher>Changsha: Central South University</publisher><subject>Algorithms ; Charging ; Driving ; Electric vehicles ; Energy consumption ; Engineering ; Metallic Materials ; Multiple objective analysis ; Optimization ; Path planning ; Power supply ; Road conditions ; Route planning ; Shortest-path problems</subject><ispartof>Journal of Central South University, 2022, Vol.29 (1), p.331-345</ispartof><rights>Central South University 2022</rights><rights>Central South University 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-855096fc4fd8b52f50a76a76f096273d26ed5573564f5f4ca3ce1c15bb72b53e3</citedby><cites>FETCH-LOGICAL-c316t-855096fc4fd8b52f50a76a76f096273d26ed5573564f5f4ca3ce1c15bb72b53e3</cites><orcidid>0000-0001-8502-6266 ; 0000-0001-8624-7298</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Guo, Dong</creatorcontrib><creatorcontrib>Li, Chao-chao</creatorcontrib><creatorcontrib>Yan, Wei</creatorcontrib><creatorcontrib>Hao, Yu-jiao</creatorcontrib><creatorcontrib>Xu, Yi</creatorcontrib><creatorcontrib>Wang, Yu-qiong</creatorcontrib><creatorcontrib>Zhou, Ying-chao</creatorcontrib><creatorcontrib>Wen-juan, E.</creatorcontrib><creatorcontrib>Zhang, Tong-qing</creatorcontrib><creatorcontrib>Gao, Xing-bang</creatorcontrib><creatorcontrib>Tan, Xiao-chuan</creatorcontrib><title>Optimal path planning method of electric vehicles considering power supply</title><title>Journal of Central South University</title><addtitle>J. Cent. South Univ</addtitle><description>Because of the limitations of electric vehicle (EV) battery technology and relevant supporting facilities, there is a great risk of breakdown of EVs during driving. The resulting driver “range anxiety” greatly affects the travel quality of EVs. These limitations should be overcome to promote the use of EVs. In this study, a method for travel path planning considering EV power supply was developed. First, based on real-time road conditions, a dynamic energy model of EVs was established considering the driving energy and accessory energy. Second, a multi-objective travel path planning model of EVs was constructed considering the power supply, taking the distance, time, energy, and charging cost as the optimization objectives. Finally, taking the actual traffic network of 15 km×15 km area in a city as the research object, the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm. The simulation results show that compared with the traditional route planning method, the total distance in the proposed optimal route planning method increased by 1.18%, but the energy consumption, charging cost, and driving time decreased by 11.62%, 41.26% and 11.00%, respectively, thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.</description><subject>Algorithms</subject><subject>Charging</subject><subject>Driving</subject><subject>Electric vehicles</subject><subject>Energy consumption</subject><subject>Engineering</subject><subject>Metallic Materials</subject><subject>Multiple objective analysis</subject><subject>Optimization</subject><subject>Path planning</subject><subject>Power supply</subject><subject>Road conditions</subject><subject>Route planning</subject><subject>Shortest-path problems</subject><issn>2095-2899</issn><issn>2227-5223</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kE9LxDAQxYMouOh-AG8Bz9Fk0iTtURb_srAXPYc2TdxKt4lJV3e_vSkVPAkDMwzvvWF-CF0xesMoVbeJMaUYoQCkqKAghxO0AABFBAA_zTOtBIGyqs7RMqWuoZyB5LKSC_SyCWO3q3sc6nGLQ18PQze8450dt77F3mHbWzPGzuAvu-1MbxM2fkhda-OkC_7bRpz2IfTHS3Tm6j7Z5W-_QG8P96-rJ7LePD6v7tbEcCZHUgpBK-lM4dqyEeAErZXM5fIWFG9B2lYIxYUsnHCFqbmxzDDRNAoawS2_QNdzboj-c2_TqD_8Pg75pAYJpSpzDGQVm1Um-pSidTrE_Gg8akb1RE3P1HSmpidq-pA9MHtSmL6z8S_5f9MP7HBwOg</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Guo, Dong</creator><creator>Li, Chao-chao</creator><creator>Yan, Wei</creator><creator>Hao, Yu-jiao</creator><creator>Xu, Yi</creator><creator>Wang, Yu-qiong</creator><creator>Zhou, Ying-chao</creator><creator>Wen-juan, E.</creator><creator>Zhang, Tong-qing</creator><creator>Gao, Xing-bang</creator><creator>Tan, Xiao-chuan</creator><general>Central South University</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0001-8502-6266</orcidid><orcidid>https://orcid.org/0000-0001-8624-7298</orcidid></search><sort><creationdate>2022</creationdate><title>Optimal path planning method of electric vehicles considering power supply</title><author>Guo, Dong ; Li, Chao-chao ; Yan, Wei ; Hao, Yu-jiao ; Xu, Yi ; Wang, Yu-qiong ; Zhou, Ying-chao ; Wen-juan, E. ; Zhang, Tong-qing ; Gao, Xing-bang ; Tan, Xiao-chuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-855096fc4fd8b52f50a76a76f096273d26ed5573564f5f4ca3ce1c15bb72b53e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Charging</topic><topic>Driving</topic><topic>Electric vehicles</topic><topic>Energy consumption</topic><topic>Engineering</topic><topic>Metallic Materials</topic><topic>Multiple objective analysis</topic><topic>Optimization</topic><topic>Path planning</topic><topic>Power supply</topic><topic>Road conditions</topic><topic>Route planning</topic><topic>Shortest-path problems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guo, Dong</creatorcontrib><creatorcontrib>Li, Chao-chao</creatorcontrib><creatorcontrib>Yan, Wei</creatorcontrib><creatorcontrib>Hao, Yu-jiao</creatorcontrib><creatorcontrib>Xu, Yi</creatorcontrib><creatorcontrib>Wang, Yu-qiong</creatorcontrib><creatorcontrib>Zhou, Ying-chao</creatorcontrib><creatorcontrib>Wen-juan, E.</creatorcontrib><creatorcontrib>Zhang, Tong-qing</creatorcontrib><creatorcontrib>Gao, Xing-bang</creatorcontrib><creatorcontrib>Tan, Xiao-chuan</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of Central South University</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guo, Dong</au><au>Li, Chao-chao</au><au>Yan, Wei</au><au>Hao, Yu-jiao</au><au>Xu, Yi</au><au>Wang, Yu-qiong</au><au>Zhou, Ying-chao</au><au>Wen-juan, E.</au><au>Zhang, Tong-qing</au><au>Gao, Xing-bang</au><au>Tan, Xiao-chuan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal path planning method of electric vehicles considering power supply</atitle><jtitle>Journal of Central South University</jtitle><stitle>J. Cent. South Univ</stitle><date>2022</date><risdate>2022</risdate><volume>29</volume><issue>1</issue><spage>331</spage><epage>345</epage><pages>331-345</pages><issn>2095-2899</issn><eissn>2227-5223</eissn><abstract>Because of the limitations of electric vehicle (EV) battery technology and relevant supporting facilities, there is a great risk of breakdown of EVs during driving. The resulting driver “range anxiety” greatly affects the travel quality of EVs. These limitations should be overcome to promote the use of EVs. In this study, a method for travel path planning considering EV power supply was developed. First, based on real-time road conditions, a dynamic energy model of EVs was established considering the driving energy and accessory energy. Second, a multi-objective travel path planning model of EVs was constructed considering the power supply, taking the distance, time, energy, and charging cost as the optimization objectives. Finally, taking the actual traffic network of 15 km×15 km area in a city as the research object, the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm. The simulation results show that compared with the traditional route planning method, the total distance in the proposed optimal route planning method increased by 1.18%, but the energy consumption, charging cost, and driving time decreased by 11.62%, 41.26% and 11.00%, respectively, thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.</abstract><cop>Changsha</cop><pub>Central South University</pub><doi>10.1007/s11771-022-4924-x</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-8502-6266</orcidid><orcidid>https://orcid.org/0000-0001-8624-7298</orcidid></addata></record> |
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subjects | Algorithms Charging Driving Electric vehicles Energy consumption Engineering Metallic Materials Multiple objective analysis Optimization Path planning Power supply Road conditions Route planning Shortest-path problems |
title | Optimal path planning method of electric vehicles considering power supply |
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