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Connecting the Dots: A Comprehensive Modeling and Evaluation Approach to Assess the Performance and Robustness of Charging Networks for Battery Electric Trucks and Its Application to Germany.

Authors :
Balke, Georg
Zähringer, Maximilian
Schneider, Jakob
Lienkamp, Markus
Source :
World Electric Vehicle Journal; Jan2024, Vol. 15 Issue 1, p32, 18p
Publication Year :
2024

Abstract

The successful introduction of battery electric trucks heavily depends on public charging infrastructure. But even as the first trucks capable of long-haul transportation are being built, no coherent fast-charging networks are yet available. This paper presents a methodology for assessing fast charging networks for electric trucks in Germany from the literature. It aims to establish a quantitative understanding of the networks' performance and robustness to deviations from idealized system parameters and identify crucial charging sites from a transportation planning perspective. Additionally, the study explores the quantification of adaptation effects displayed by agents in response to charging site outages. To achieve these objectives, a comprehensive methodology incorporating infrastructure, vehicle and operational strategy modeling, simulation, and subsequent evaluation is presented. Factors such as charging station locations, C-rates, mandatory rest periods, and vehicle parameters are taken into account, along with the distribution of traffic according to publicly available data. The study aims to offer a comprehensive understanding of charging networks' performance and resilience. This will be applied in a case study on two proposed networks and newly created derivatives. The proposed network offers over 99% coverage for long-haul transport but leads to a time loss of approximately 7% under reference conditions. This study advances the understanding of the performance and resilience of proposed charging networks, providing a solid foundation for the design and implementation of robust and efficient charging infrastructure for electric trucks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20326653
Volume :
15
Issue :
1
Database :
Complementary Index
Journal :
World Electric Vehicle Journal
Publication Type :
Academic Journal
Accession number :
175132420
Full Text :
https://doi.org/10.3390/wevj15010032