Eco-driving model for wireless charging scenario of connected and automated electric freight vehicles based on differentiated driving strategies at multi-intersections

Wenbo Wang; Shujing Fang; Fei Hui; Junfei Zhang

doi:10.1117/12.3050791

20 January 2025 Eco-driving model for wireless charging scenario of connected and automated electric freight vehicles based on differentiated driving strategies at multi-intersections

Wenbo Wang, Shujing Fang, Fei Hui, Junfei Zhang

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 134220A (2025) https://doi.org/10.1117/12.3050791
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

Due to their environmentally friendly and energy-saving characteristics, electric freight vehicles (EFVs) have emerged as indispensable and significant modes of urban transportation. However, the limited driving range of vehicles often leads to low transportation efficiency. In this research, an eco-driving model is introduced specifically tailored for connected and autonomous electric freight vehicles (CAEFVs). This model incorporates wireless charging technology by deploying wireless charging lanes at multiple signalized intersections, allowing CAEFVs to replenish energy while moving slowly at traffic lights. At the same time, differentiated passage strategies are designed to meet the charging requirements of different vehicles while ensuring uninterrupted passage through intersections. The traffic benefits of these passage strategies are analyzed considering different initial speeds and wireless charging areas (WCA). The study reveals that the charging-optimum mode (COM) outperforms the time-optimum mode (TOM) in terms of charging efficiency, albeit requiring longer travel times. This study offers valuable insights into the implementation of wireless charging infrastructure for CAEFVs, with the potential to enhance their driving range capabilities.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenbo Wang, Shujing Fang, Fei Hui, and Junfei Zhang "Eco-driving model for wireless charging scenario of connected and automated electric freight vehicles based on differentiated driving strategies at multi-intersections", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 134220A (20 January 2025); https://doi.org/10.1117/12.3050791

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