Optimization of electric vehicle scheduling with multiple vehicle types in public transport

The effective scheduling of electric buses (EBs) for multiple vehicle types is essential for the sustainable practice of public transport. This paper proposes a new methodology for the electric vehicle scheduling problem with multiple vehicle types (MVT-E-VSP) in public transport based on a given multi-vehicle-type timetable. First, with explicit consideration of differences in driving range, recharging duration and energy consumption of EBs for multiple vehicle types, an optimization model is established to minimize annual total scheduling costs, including the purchase costs of EBs and chargers, the operating costs of deadheading and timetabled trips, etc. Then, a heuristic procedure is developed to find the optimal solution considering recharging trips and the substitution between electric vehicle (EV) types. Finally, the proposed methodology is validated using a real-world transit network in Daxing District, Beijing. The optimization result provides transit agencies with guidance on the purchase and schedule of EBs for multiple vehicle types, as well as the deployment of chargers. Comparative analysis indicates the proposed method considering the substitution between EV types reduces annual total scheduling costs by 15.93% compared with the conventional method. Sensitivity analysis reveals that the current recharging power (240 kW) and discharging depth (80%) are approximately economical.