Electric vehicle (EV) adoption in long-distance logistics faces challenges such as range anxiety and uneven distribution of charging stations. Two pivotal questions emerge: How can EVs be efficiently routed in a charging network considering range limits, charging speeds and prices? And, can the existing charging infrastructure sustain the increasing demand for EVs in long-distance logistics? This paper addresses these questions by introducing a novel theoretical and computational framework to study the EV network flow problems. We present an EV network flow model that incorporates range constraints and nonlinear charging rates, and identify conditions under which polynomial-time solutions can be obtained for optimal single EV routing, maximum flow, and minimum-cost flow problems. Our findings provide insights for optimizing EV routing in logistics, ensuring an efficient and sustainable future.

翻译：电动汽车在长途物流中的推广应用面临着续航焦虑与充电站分布不均等挑战。两个关键问题随之产生：如何考虑里程限制、充电速度和价格因素，在充电网络中对电动汽车进行高效路径规划？现有充电基础设施能否支撑长途物流中日益增长的电动汽车需求？本文通过构建新型理论与计算框架研究电动汽车网络流问题，对上述问题作出解答。我们提出了一个融合里程约束与非线性充电速率的电动汽车网络流模型，并确定了在何种条件下可获取最优单辆电动汽车路径规划、最大流及最小费用流问题的多项式时间解。研究结果为物流领域电动汽车路径优化提供了理论依据，有助于推动高效可持续的物流体系建设。