Vehicle Simulation-based Planning of Recharging for Battery Electric Bus Fleets

This study focuses on vehicle simulation-based charging planning for battery electric bus (BEB) fleets. As urban transportation shifts towards sustainable energy solutions, the adoption of BEBs is increasing. The driving range of BEBs cannot guarantee that they can complete the specified tasks without charging for a complete day. Effective charging strategies are crucial to maximize vehicle utilization and minimize energy costs. This Master’s Thesis introduces a four-step charging plan optimization model that integrates traffic conditions, driving cycles, SOC of battery, time-of-use tariffs and passenger numbers considerations. MATLAB-SUMO co-simulation was used to create unique driving cycles for each bus line at predefined times, capturing dynamic driver behavior, accounting for traffic flows and traffic lights. Using a backward energy consumption model, cost tables were developed that incorporate electric motor efficiency and braking energy recovery, reflecting trip length, trip duration variability, and energy consumption. An optimization algorithm was designed to minimize the number of BEBs and the overall electricity cost, considering time-of-use (TOU) tariffs, effectively optimizing the charging plan. The influence of passenger numbers on energy consumption was validated, with the maximum SOC difference between validated and optimized values remaining below 3%, confirming the practicality of the optimized charging plan. This study provides a feasible and efficient charging management solution for sustainable urban public transportation.