Electrification of a citywide bus network: A data-driven micro-simulation approach. (March 2023) - Wang, Shiqi; Li, Yuze; Chen, Anthony; Zhuge, Chengxiang
Highlights: A data-driven approach to deploying charging facilities for electric buses (E-buses). A real-world bus trajectory dataset used to quantify charging demand at the micro-scale. Wireless charging lanes can greatly improve level of service with a slightly higher cost. Parameters related to E-buses and charging facilities were influential to model outputs. Abstract: This paper developed a data-driven micro-simulation optimization model to deploy charging infrastructure for a large-scale electric bus network, considering both traditional charging posts and wireless charging lanes (WCLs). The optimization model has two objectives: 1) minimize the total system cost and 2) maximize the level of service. We used New York City as the study area, and one-day GPS trajectories of 3, 133 buses were analyzed to develop the micro-simulation approach, so as to represent the bus operation well. The results showed that the scenario with both charging posts and WCLs deployed had a significantly higher level of service (with its total delay time being 48.11% shorter), more energy saved and fewer emissions than the scenario with only charging posts deployed, though its total cost was 0.76% higher. Moreover, the sensitivity analysis results show that the parameters associated with electric buses and charging facilities could heavily influence the outputs of interest.