Zhouqiao Zhao, Guoyuan Wu, K. Boriboonsomsin, A. Kailas
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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.