Charging Navigation for Commercial Electric Vehicles in Considering Traffic and Queuing Dynamics

Yantao Sun; Qilin Huang; Mengge Shi; Youwei Jia

10.1109/ISGTAsia54193.2022.10003613

2022

2378-8534

979-8-3503-9967-7

2022 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia)

414-418

1-5 Nov. 2022

Singapore, Singapore

The stochastic nature and time-varying characteristics of traffic networks cast great challenges on real-time navigation and management for commercial electric vehicles (EVs) routing towards fast charging stations (FCS). To address this problem, this paper proposes a FCS navigation strategy by holistically considering traffic flow patterns and the dynamic queuing process. In particular, the optimization objective is to minimize the charging cost and the total time costs of EV users. In formulating the traffic conditions, the correlation among the network flow, traveling speed and energy consumption are collectively considered in our study. To simulate the dynamic queuing process in a specific FCS, a double-layer queuing model is developed to capture the dynamic features. Extensive case studies are carried out to demonstrate the effectiveness of the proposed approach in a genuine operating scenario.

Electric vehicle charging navigation dynamic transportation energy consumption dynamic queue

第一

IEEE

Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China

Yantao Sun,Qilin Huang,Mengge Shi,et al. Charging Navigation for Commercial Electric Vehicles in Considering Traffic and Queuing Dynamics[C],2022:414-418.