考虑途中机会充电的纯电动重卡车队车辆调度算法

Zhouqiao Zhao, Guoyuan Wu, K. Boriboonsomsin, A. Kailas
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引用次数: 4

摘要

在现实世界的区域分销应用中,人们对中型和重型车辆(m- hdv)的电气化越来越感兴趣。考虑到有限的车载能量、充电特性和操作考虑,电池电动卡车(BETs)的车队调度优化至关重要。本文提出了一种双层分层方法来优化取货和交付过程中的BET调度。随着路线/调度的变化,由于货物的重量和实时交通状况,从一个地点到另一个地点的平均速度、旅行时间和能耗都会发生相应的变化。因此,将“电动汽车路线问题”扩展到包括取货、送货、时间窗口和部分充电。该算法在不影响计算效率的情况下,显著降低了BET车队在人工、能耗和时间窗惩罚方面的运营成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicle Dispatching and Scheduling Algorithms for Battery Electric Heavy-Duty Truck Fleets Considering En-route Opportunity Charging
There has been growing interest in the electrification of medium- and heavy-duty vehicles (M-HDVs) in real-world, regional distribution applications. Fleet dispatch optimization of battery-electric trucks (BETs) is critical given the limited onboard energy, charging characteristics, and operational considerations. Our paper proposes a bi-level hierarchical method to optimize BET dispatch during pickup and delivery runs. With any route/scheduling change, the average speed, travel time, and energy consumption from one location to another will change accordingly because of the weight of the goods and the real-time traffic condition. So, the "electric vehicle routing problem" was extended to include pickup and delivery, time windows, and partial recharge. The proposed algorithm significantly reduces the operation cost of the BET fleet considering labor, energy consumption, and time window penalties without compromising computational efficiency.
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