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Vehicle Dispatching and Scheduling Algorithms for Battery Electric Heavy-Duty Truck Fleets Considering En-route Opportunity Charging

机译:考虑途径机会充电的电池电动重型卡车车队的车辆调度和调度算法

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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.
机译:在现实世界,区域分布应用中,对中型和重型车辆(M-HDV)的电气化的兴趣日益增长。 给出电池电动卡车(BETS)的舰队调度优化给出了有限的板载能量,充电特性和操作考虑。 我们的论文提出了一种双层分层方法,可以在拾取和交付运行期间优化投注调度。 通过任何路线/调度变化,由于货物的重量和实时流量条件,平均速度,旅行时间和从一个位置到另一个位置的能量消耗将相应地改变。 因此,“电动汽车路由问题”扩展为包括拾取和交付,时间窗口和部分充值。 该算法考虑劳动力,能耗和时间窗口惩罚显着降低了投注舰队的运营成本,而不会影响计算效率。

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