Path Planning Method for Electric Vehicles Based on Freeway Network
Recently, electric vehicles (EVs) have received more and more attention, but the problem of the insufficient range is still the main reason that hinders electric vehicles to travel long distances. Under the premise of the battery capacity without technological innovation, the path planning method ca...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/3030050 |
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| _version_ | 1849307567717613568 |
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| author | Qichao Liu Wei Wang Xuedong Hua |
| author_facet | Qichao Liu Wei Wang Xuedong Hua |
| author_sort | Qichao Liu |
| collection | DOAJ |
| description | Recently, electric vehicles (EVs) have received more and more attention, but the problem of the insufficient range is still the main reason that hinders electric vehicles to travel long distances. Under the premise of the battery capacity without technological innovation, the path planning method can ensure the safety and efficiency of electric vehicles in long-distance travel. This paper studies the actual freeway network to optimize the vehicle driving path and give the charging strategy based on the shortest travel time of a single vehicle. In this paper, a path and charging strategy planning model is proposed. In this model, the shortest travel time of a single vehicle is taken as the objective function, and the state of charging equipment in the actual road network and the safe electric quantity are considered as constraints. And the genetic algorithm is used to solve the model. Through case analysis, the rationality and optimization efficiency of the model proposed in this paper are verified. Finally, the sensitivity analysis of the three parameters of traffic volume, temperature, and travel speed is carried out with the Shanghai-Nanjing freeway network. The experimental results can get the nodes with the highest service pressure in the network, which can provide a theoretical basis for charging nodes’ expansion in the freeway network in the future. |
| format | Article |
| id | doaj-art-222408a2a7714f49ab5afafad8cf490e |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-222408a2a7714f49ab5afafad8cf490e2025-08-20T03:54:42ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/30300503030050Path Planning Method for Electric Vehicles Based on Freeway NetworkQichao Liu0Wei Wang1Xuedong Hua2Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, ChinaJiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, ChinaJiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, ChinaRecently, electric vehicles (EVs) have received more and more attention, but the problem of the insufficient range is still the main reason that hinders electric vehicles to travel long distances. Under the premise of the battery capacity without technological innovation, the path planning method can ensure the safety and efficiency of electric vehicles in long-distance travel. This paper studies the actual freeway network to optimize the vehicle driving path and give the charging strategy based on the shortest travel time of a single vehicle. In this paper, a path and charging strategy planning model is proposed. In this model, the shortest travel time of a single vehicle is taken as the objective function, and the state of charging equipment in the actual road network and the safe electric quantity are considered as constraints. And the genetic algorithm is used to solve the model. Through case analysis, the rationality and optimization efficiency of the model proposed in this paper are verified. Finally, the sensitivity analysis of the three parameters of traffic volume, temperature, and travel speed is carried out with the Shanghai-Nanjing freeway network. The experimental results can get the nodes with the highest service pressure in the network, which can provide a theoretical basis for charging nodes’ expansion in the freeway network in the future.http://dx.doi.org/10.1155/2021/3030050 |
| spellingShingle | Qichao Liu Wei Wang Xuedong Hua Path Planning Method for Electric Vehicles Based on Freeway Network Journal of Advanced Transportation |
| title | Path Planning Method for Electric Vehicles Based on Freeway Network |
| title_full | Path Planning Method for Electric Vehicles Based on Freeway Network |
| title_fullStr | Path Planning Method for Electric Vehicles Based on Freeway Network |
| title_full_unstemmed | Path Planning Method for Electric Vehicles Based on Freeway Network |
| title_short | Path Planning Method for Electric Vehicles Based on Freeway Network |
| title_sort | path planning method for electric vehicles based on freeway network |
| url | http://dx.doi.org/10.1155/2021/3030050 |
| work_keys_str_mv | AT qichaoliu pathplanningmethodforelectricvehiclesbasedonfreewaynetwork AT weiwang pathplanningmethodforelectricvehiclesbasedonfreewaynetwork AT xuedonghua pathplanningmethodforelectricvehiclesbasedonfreewaynetwork |