The extension of battery life in electric bus fleets depends intimately on the effective energy management of both internal controls on board and external operations on roads. In this work, an optimal scheduling method based on dynamic programming was proposed to minimize battery replacement costs during the entire service life of electric bus fleets. It highlighted a three-part model. In the first part, the dynamic programming model was proposed to solve the scheduling problem for electric bus fleets. In the second part, a reverse order matching strategy was proposed to simultaneously consider the battery capacity fading processes and the differences in the working loads. In the third part, the battery capacity degradation model was used to determine the amount of battery capacity loss and the number of battery replacements. A case study was used to demonstrate the implementation procedure of the proposed method. The influences of practical factors, such as the differences in the working loads, the number of the electric bus fleets, the duration of the scheduling period, and the working temperature of batteries on the electric bus fleet scheduling were analysed and discussed. Compared with the base case, the proposed method reduces the investment for battery replacements by 20% for the entire electric bus fleet system. The proposed method can readily be applied to a large-scale public transit system to formulate optimal scheduling schemes.

电动公交车队电池寿命的延长，直接取决于车上内部控件和道路外部操作的有效能源管理。在这项工作中，提出了一种基于动态规划的最优调度方法，以在电动公交车队的整个使用寿命期间最大程度地减少电池更换成本。它强调了一个由三部分组成的模型。在第一部分中，提出了动态规划模型来解决电动公交车队的调度问题。在第二部分中，提出了一种逆序匹配策略，以同时考虑电池容量衰减过程和工作负载的差异。在第三部分中，使用电池容量降级模型来确定电池容量损失量和电池更换数量。案例研究证明了该方法的实现过程。分析并讨论了工作负荷的差异，电动公交车队的数量，调度周期的持续时间，电池的工作温度等实际因素对电动公交车队调度的影响。与基本情况相比，该方法将整个电动公交车队系统的电池更换投资减少了20％。所提出的方法可以容易地应用于大规模的公共交通系统以制定最优的调度方案。分析并讨论了电动公交车队调度中电池的工作温度。与基本情况相比，该方法将整个电动公交车队系统的电池更换投资减少了20％。所提出的方法可以容易地应用于大规模的公共交通系统以制定最优的调度方案。分析并讨论了电动公交车队调度中电池的工作温度。与基本情况相比，该方法将整个电动公交车队系统的电池更换投资减少了20％。所提出的方法可以容易地应用于大规模的公共交通系统以制定最优的调度方案。