Sardana, I Kadek Jimmy (Technical University of Darmstadt), Blat Belmonte, Benjamin Daniel (Technical University of Darmstadt), Heckelmann, Paul (TU Darmstadt), Rinderknecht, Stephan (Technische Universität Darmstadt)

Optimization Technique for Electric Bus Fleet Schedules with a-priori Trip Disaggregation

Scheduled for presentation during the Regular Session "Electric Vehicles - Charging and Scheduling I" (WeAT3), Wednesday, September 25, 2024, 10:30−10:50, Salon 6

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

Electric vehicles represent a great opportunity to electrify the public transportation sector, and thereby mitigate greenhouse gas emissions and noise pollution among others. Due to the limited range of electric buses compared to their internal combustion engine counterparts, the scheduling process has to be rethought. A fleet operator has to decide between different charging strategies such as depot-charging, opportunity-charging, or a combination of both. The existence of different vehicle types, e. g., regarding battery capacity and passenger capacity, further complicates the matter. We introduce a multiple vehicle type scheduling problem with partial charging (MVTSP-PC) that can optimize existing fleet schedules. Our approach is based on the disaggregation of the existing bus schedule. Then, with an exact solution approach using mixed-integer linear programming and route restriction strategies we identify optimal schedules while considering computational resources. With the presented approach bus schedules for whole weeks can be efficiently re-adapted. The approach designs the optimal schedule on a daily basis, and subsequently uses a heuristic approach for the vehicle-to-route assignment when concatenating the days.