Optimal deployment of charging lanes for electric vehicles in transportation networks
Optimal deployment of charging lanes for electric vehicles in transportation networks
复制标题
交通网络中电动汽车充电车道的优化部署
DOI：
10.1016/j.trb.2016.05.018
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发表时间：
2016-09
期刊：
影响因子：
--
通讯作者：
Yin Yafeng
中科院分区：
文献类型：
--
作者：
Chen Zhibin;He Fang;Yin Yafeng
鉴于边走边充电技术的快速发展，我们设想未来电动汽车充电车道可以部署在区域甚至城市路网中，因此本文尝试对其部署进行优化。我们首先开发一个新的用户均衡模型来描述部署充电车道的路网中的均衡流量分布。电动汽车驾驶员在往返于出发地和目的地之间时，需要选择路线并决定电池充电计划，以最大限度地缩短行程时间，同时确保在不耗尽电量的情况下完成行程。电池充电计划将决定使用哪条充电车道、充电多长时间以及以什么速度运行电动汽车。速度会影响充电量以及行驶时间。根据已建立的用户均衡条件，我们进一步将充电车道的部署制定为具有互补约束的数学程序。网络均衡和设计模型都通过有效的求解算法求解，并通过数值例子进行了论证。
Given the rapid development of charging-while-driving technology, we envision that charging lanes for electric vehicles can be deployed in regional or even urban road networks in the future and thus attempt to optimize their deployment in this paper. We first develop a new user equilibrium model to describe the equilibrium flow distribution across a road network where charging lanes are deployed. Drivers of electric vehicles, when traveling between their origins and destinations, are assumed to select routes and decide battery recharging plans to minimize their trip times while ensuring to complete their trips without running out of charge. The battery recharging plan will dictate which charging lane to use, how long to charge and at what speed to operate an electric vehicle. The speed will affect the amount of energy recharged as well as travel time. With the established user equilibrium conditions, we further formulate the deployment of charging lanes as a mathematical program with complementarity constraints. Both the network equilibrium and design models are solved by effective solution algorithms and demonstrated with numerical examples.
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DOI：
--
发表时间：
2015
期刊：
--
影响因子：
--
作者：
P. Bansal
通讯作者：
P. Bansal
DOI：
10.1109/edpc.2013.6689750
发表时间：
2013-12
期刊：
2013 3rd International Electric Drives Production Conference (EDPC)
影响因子：
--
作者：
N. Shinohara;Y. Kubo;H. Tonomura
通讯作者：
N. Shinohara;Y. Kubo;H. Tonomura
影响因子：
6.8
作者：
Fang He;Di Wu;Yafeng Yin;Yongpei Guan
通讯作者：
Fang He;Di Wu;Yafeng Yin;Yongpei Guan
DOI：
10.1016/j.trc.2014.01.008
发表时间：
2014-03
期刊：
--
影响因子：
--
作者：
Jaeyoung Jung;Joseph Y. J. Chow;R. Jayakrishnan;Ji Young Park
通讯作者：
Jaeyoung Jung;Joseph Y. J. Chow;R. Jayakrishnan;Ji Young Park
影响因子：
2.4
作者：
Jiang, Nan;Xie, Chi;Waller, S. Travis
通讯作者：
Waller, S. Travis