Path Planning Method for Electric Vehicles Based on Freeway Network

Author:

Liu Qichao123ORCID,Wang Wei123ORCID,Hua Xuedong123ORCID

Affiliation:

1. Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China

2. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China

3. School of Transportation, Southeast University, Nanjing 211189, China

Abstract

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.

Funder

National Natural Science of China

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Impact of Road Types on the Energy Consumption of Electric Vehicles;Journal of Advanced Transportation;2022-06-29

2. Quantifying the Impact of Traffic on Electric Vehicle Efficiency;World Electric Vehicle Journal;2022-01-01

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