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. • Tackling electrification challenges for electric buses. • Optimization of charging infrastructure and strategies. • Utilization of GTFS and GeoTIFF data. • Detailed battery degradation modeling. • Cost reduction of nearly 35%.

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Publication Details

Journal
Energy
Published
2024-11-29
DOI
https://doi.org/10.1016/j.energy.2024.133974
Citations
4
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.81

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article

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

Fabio Widmer, Mohammad Hossein Moradi, Raymond Claude Turin, Christopher H. Onder
4 citations
Energy
Advanced Battery Technologies Research
0.81
article

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

Fabio Widmer, Mohammad Hossein Moradi, Raymond Claude Turin, Christopher H. Onder
article en
4 citations

Abstract

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. • Tackling electrification challenges for electric buses. • Optimization of charging infrastructure and strategies. • Utilization of GTFS and GeoTIFF data. • Detailed battery degradation modeling. • Cost reduction of nearly 35%.

EnergyVol. 313
ETH Zurich (CH)
Bundesamt für Energie
Industry, innovation and infrastructure
Openalex Percentile: Top 28%
Advanced Battery Technologies Research
0.81
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