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Dynamic charging infrastructure deployment for plug-in hybrid electric trucks

机译:插电式混合动力卡车的动态充电基础设施部署

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Inspired by the rapid development of charging-while-driving (CWD) technology, plans are ongoing in government agencies worldwide for the development of electrified road freight transportation systems through the deployment of dynamic charging lanes. This en route method for the charging of plug-in hybrid electric trucks is expected to supplement the more conventional charging technique, thus enabling significant reduction in fossil fuel consumption and pollutant emission from road freight transportation. In this study, we investigated the optimal deployment of dynamic charging lanes for plug-in hybrid electric trucks. First, we developed a multi-class multi-criteria user equilibrium model of the route choice behaviors of truck and passenger car drivers and the resultant equilibrium flow distributions. Considering that the developed user equilibrium model may have non-unique flow distributions, a robust deployment of dynamic charging lanes that optimizes the system performance under the worst-case flow distributions was targeted. The problem was formulated as a generalized semi-infinite min-max program, and a heuristic algorithm for solving it was proposed. This paper includes numerical examples that were used to demonstrate the application of the developed models and solution algorithms.
机译:受到随车充电(CWD)技术快速发展的启发,全球政府机构正在制定计划,以通过部署动态充电车道来开发电气化道路货运系统。这种用于插电式混合动力卡车充电的途中方法有望补充更传统的充电技术,从而能够显着减少公路货运中化石燃料的消耗和污染物的排放。在这项研究中,我们调查了插电式混合动力卡车的动态充电车道的最佳配置。首先,我们针对卡车和客车驾驶员的路线选择行为以及由此产生的平衡流分布,建立了一个多类,多准则的用户平衡模型。考虑到所开发的用户平衡模型可能具有非唯一的流量分布,因此针对动态充电通道的稳健部署进行了优化,以优化最坏情况下的流量分布。将该问题表述为广义半无限min-max程序,并提出了求解该问题的启发式算法。本文包含一些数值示例,这些示例被用来证明开发的模型和求解算法的应用。

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