Optimal scheduling for electric bus fleets based on dynamic programming approach by considering battery capacity fade

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.