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A CONNECTED VEHICLE SUPPORTED ROUTING STRATEGY FOR ELECTRIC VEHICLES

机译:连接的车辆支持电动车辆的路由策略

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Electric Vehicle (EV) charging problem hinders its wide scale commercial adoption. In this paper, the authors address the problem through an Ant Colony Optimization (ACO) based routing algorithm that is dedicated to accommodate electric vehicle trips. By using Connected Vehicle Technology, connected EVs communicate with other vehicles and infrastructure components to transmit information in real time for finding the best route, and for intelligently recharging on the move. Such connected EVs are capable of adapting each trip with the lowest travel time and/or the lowest recharge cost along with an optimal recharge plan to prevent battery drain. As a case study, a real world roadway network in Charleston, SC was simulated to examine the performance of the routing strategy. Simulation analysis revealed that connected EVs can reduce not only the total travel time and the energy consumption, but also the recharged volume of electricity and corresponding cost, thus significantly relieving the concerns of range anxiety of EV drivers. This routing approach potentially leads to a reduction in the EV battery capacity, which in turn can reduce the cost of energy storage systems to a reasonable level.
机译:电动汽车(EV)充电问题阻碍了其广泛的商业采用。在本文中,作者通过专用于容纳电动车程的基于蚁群优化(ACO)的路由算法来解决问题。通过使用连接的车辆技术,连接的EV与其他车辆和基础设施组件通信,以实时传输信息以找到最佳路线,以及用于在移动上智能充电。这种连接的EV能够使用最低的行程时间和/或最低充电成本以及最佳的充电计划来调整每个行程,以防止电池漏极。作为一个案例研究,模拟了查尔斯顿的现实世界巷道网络,以检查路由策略的性能。仿真分析显示,连接的EV可以不仅可以减少总旅行时间和能量消耗,还可以减少电力的充电量和相应的成本,从而显着缓解了EV驱动程序的范围焦虑的关注。这种路由方法可能导致EV电池容量的降低,这反过来可以将能量存储系统的成本降低到合理的水平。

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