Optimization of charging infrastructure and strategy for an electrified public transportation system

Government policies and incentives aimed at reducing the carbon footprint are increasingly focusing on the electrification of public transportation, particularly transit buses. However, electrification faces significant challenges, including optimizing the charging infrastructure, battery size and type, and charging strategies. Addressing these challenges is crucial for the effective deployment and operation of electric bus fleets. This study presents an innovative method for optimizing these aspects of electric bus systems under diverse route conditions. By leveraging general transit feed specification (GTFS) and GeoTIFF data, the developed approach ensures scalability and is grounded in real-world data. A detailed physical model, especially concerning battery degradation, adds a unique dimension to the study, providing more accurate and reliable results. The optimization method employed in this study is dynamic programming (DP), which allows for a comprehensive evaluation of various factors influencing the performance and efficiency of electric buses. The proposed approach has been validated through three distinct case studies. The findings of this study indicate that the optimized solution can lead to a substantial cost reduction of nearly 35% for operators compared to current state-of-the-art practices in Zurich, which underscores the potential of the proposed approach to contribute to more sustainable and cost-effective public transportation systems.