Li, Bingbing;
Zhuang, Weichao;
Zhang, Hao;
Sun, Hao;
Liu, Haoji;
Zhang, Jianrun;
Yin, Guodong;
(2023)
Traffic-Aware Ecological Cruising Control for Connected Electric Vehicle.
IEEE Transactions on Transportation Electrification
10.1109/tte.2023.3325403.
(In press).
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Abstract
The advent of intelligent connected technology has greatly enriched the capabilities of vehicles in acquiring information. The integration of short-term information from limited sensing range and long-term information from cloud-based systems in vehicle motion planning and control has become a vital means to deeply explore the energy-saving potential of vehicles. In this study, a traffic-aware ecological cruising control (T-ECC) strategy based on a hierarchical framework for connected electric vehicles in uncertain traffic environments is proposed, leveraging the two distinct temporal-dimension information. In the upper layer that is dedicated for speed planning, a sustainable energy consumption strategy (SECS) is introduced for the first time. It finds the optimal economic speed by converting variations in kinetic energy into equivalent battery energy consumption based on long-term road information. In the lower layer, a synthetic rolling-horizon optimization control (SROC) is developed to handle real-time traffic uncertainties. This control approach jointly optimizes energy efficiency, battery life, driving safety, and comfort for vehicles under dynamically changing traffic conditions. Notably, a stochastic preceding vehicle model is presented to effectively capture the uncertainties in traffic during the driving process. Finally, the proposed T-ECC is validated through simulations in both virtual and real-world driving conditions. Results demonstrate that the proposed strategy significantly improves the energy efficiency of the vehicle.
| Type: | Article |
|---|---|
| Title: | Traffic-Aware Ecological Cruising Control for Connected Electric Vehicle |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/tte.2023.3325403 |
| Publisher version: | https://doi.org/10.1109/tte.2023.3325403 |
| Language: | English |
| Keywords: | Batteries , Biological system modeling , Energy efficiency , Energy consumption , Vehicle dynamics , Roads , Traction motors |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10179976 |
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