Abstract: Aiming at the range anxiety problems of electric vehicles, taking the electric vehicles as the research objects, based on the “vehicle-road-network” intelligent system, the road topology model, impedance evaluation model and vehicle energy consumption model were established, the optimal driving time, optimal energy consumption and comprehensive optimization were as the objectives respectively, and the A* algorithm was used to plan the charging path of electric vehicles. Taking Fuzhou urban cycle as an example, the main driving cycle data was collected, the planned road sections were matched with the driving cycle data to predict the vehicle driving time and energy consumption, and the impedance cost of each objective was calculated by combining the waiting time for charging. The results show that the proposed charging path planning strategy may respectively plan the optimal charging path considering time, energy consumption and comprehensive optimization according to the needs of drivers.

Key words: electric vehicle, charging path planning, energy consumption prediction, impedance cost

摘要： 针对电动汽车续驶里程短的问题，以电动汽车为研究对象，基于“车路网”智能系统建立了道路拓扑模型、阻抗评价模型以及整车能耗模型，分别以电动汽车行驶时间最优、能耗最优和综合最优为目标，运用A*算法对电动汽车进行了充电路径规划。以福州市区交通为实例，采集了各路段主要行驶工况数据，将规划路段与行驶工况数据匹配用于车辆行驶时间和能耗的预测，并结合充电等待时间计算各目标阻抗成本。研究结果表明：所提出的充电路径规划策略能够根据驾驶员的不同需求分别规划出考虑时间、能耗以及综合最优的充电路径。

关键词: 电动汽车, 充电路径规划, 能耗预测, 阻抗成本