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作 者:申利民[1,2] 常晓彤 李成宇 赵国瑞 毛鹏皓 Shen Limin;Chang Xiaotong;Li Chengyu;Zhao Guorui;Mao Penghao(School of Information Science&Engineering,Yanshan University,Qinhuangdao Hebei 066004,China;Hebei Key Laboratory of Software Engineering,Qinhuangdao Hebei 066004,China)
机构地区:[1]燕山大学信息科学与工程学院,河北秦皇岛066004 [2]河北省软件工程重点实验室,河北秦皇岛066004
出 处:《计算机应用研究》2025年第3期863-869,共7页Application Research of Computers
基 金:国家自然科学基金资助项目(61772450,60873008)。
摘 要:为了解决目的地导向的电动汽车路径规划和中途充电站选择问题,提出一种以目的地为导向的基于成本优化的电动汽车充电导航策略。首先,构建了基于目的地的电动汽车路径规划和充电导航架构;其次,根据市区道路和高速公路路网的特点,将道路划分为低层道路和高层道路两个层次;考虑到用户充电和行驶成本以及结束充电后继续前往目的地的需求,低层路网内构建决策函数进行充电站选择并进行路径规划,高层路网使用改进的蚁群算法给出全程充电策略;最后,以某市城区和某高速公路为研究范围,对所提方法进行仿真验证,并与其他方法进行了比较。结果表明,在高层和低层路网中,所提出的充电导航策略能降低电动汽车的行驶和充电成本,而且确保低层路网中电动汽车充电完成后更快速地到达目的地。In order to solve the problems of destination oriented electric vehicle route planning and intermediate charging station selection,this paper proposed a cost optimization based electric vehicle charging navigation strategy focused on the destination.Firstly,it developed a destination based architecture for electric vehicle route planning and charging navigation.Next,considering the characteristics of urban roads and highway networks,it divided roads into two levels:lower-level roads and higher-level roads.In the lower-level road network,it established a decision-making function for charging station selection and route planning,taking into account the user’s charging and driving costs,as well as the need to continue towards the destination after charging.In the higher-level road network,it used an improved ant colony algorithm to provide a comprehensive charging strategy.Finally,this paper conducted simulations within the urban area and highway of a certain city to verify the proposed method,and compared it with other methods.The results demonstrate that the proposed charging navigation strategy reduces both driving and charging costs for EVs in both the higher-level and lower-level road networks,while ensuring faster arrival at the destination after charging in the lower-level network.
分 类 号:TP391.9[自动化与计算机技术—计算机应用技术]
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