引导电动汽车用户驾驶行为的充电导航策略  

Charging navigation strategy by guiding the driving behavior of electric vehicle users

作　　者：任丽娜[1] 路鹏伟 刘福才[1] REN Li-na;LU Peng-wei;LIU Fu-cai(College of Electrical Engineering,Yanshan University,Qinhuangdao 066004,China)

机构地区：[1]燕山大学电气工程学院

出　　处：《控制与决策》2019年第11期2438-2444,共7页Control and Decision

摘　　要：电动汽车充电导航便于用户合理选择充电站,降低用户自身的时间成本和经济成本,缓解配电网端的负荷压力.在电网分时电价的基础上,考虑电动汽车充电路径的选择与车主的驾驶行为密切相关,通过对电动汽车的负荷设备分类建模,根据不同设备类型的重要程度及用户的电动汽车实际工况和地形因素,利用遗传算法分析最佳出行路径,提出以时间成本与经济成本之和最优为目标,引导用户驾驶行为的充电导航策略.在20 km×10 km含3个充电站的区域内,通过3种不同充电导航策略仿真结果对比,验证所提出的导航策略的可行性和有效性.The charging navigation of electric vehicle is convenient for users to choose charging station reasonably, reduce their own time cost and economic cost, and alleviate the load pressure of distribution network. Based on the time-of-use price of power grid, this paper considers that the choice of charging path of electric vehicle is closely related to the driving behavior of the vehicle owner, and models the load equipment classification of electric vehicle by means of classification.According to the importance of different equipment types and the actual working condition of the electric vehicle and road terrain factors, the optimal travel path is analyzed by using genetic algorithm, and a charging navigation strategy is proposed to guide the user’s driving behavior with the aim of the optimal sum of time cost and economic cost. In the20 km×10 km region with three charging stations, the feasibility and effectiveness of the proposed navigation strategy are verified by comparing the simulation results of three different charging navigation strategies.

关 键 词：充电导航 时间成本 经济成本 分时电价 驾驶行为 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]