Li, Bingbing;
Zhuang, Weichao;
Zhang, Hao;
Zhao, Ruixuan;
Liu, Haoji;
Qu, Linghu;
Zhang, Jianrun;
(2024)
A comparative study of energy-oriented driving strategy for connected electric vehicles on freeways with varying slopes.
Energy
, 289
, Article 129916. 10.1016/j.energy.2023.129916.
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Abstract
This paper proposes two real-time energy-oriented driving strategies to minimize the energy consumption for electric vehicles on highways with varying slopes. First, a novel strategy, called normalized-energy consumption minimization strategy (NCMS), adopts a designed kinetic energy conversion factor to convert the vehicle kinetic energy change into the equivalent battery energy consumption. By minimizing the total normalized energy consumption, the energy-orientated vehicle control sequence is calculated. In addition, a logic car-following algorithm is developed to enhance NCMS for avoiding collisions with the potential preceding vehicle on the journey. Second, an improved model predictive control (MPC) is developed with a hierarchical framework, which achieves a balance between optimization and computational efficiency. In the upper level, a global, coarse-grained, iterative dynamic programming is employed to penalize the MPC terminal state, while the lower level performs online rolling optimization of the vehicle within a moderate time step. Thirdly, the performance of the proposed driving strategies is verified through a traffic simulation to evaluate the energy efficiency improvement and processor computation time compared to dynamic programming and constant speed strategy. Finally, a vehicle-in-the-loop test is carried out to validate the feasibility of the proposed two novel driving strategies.
| Type: | Article |
|---|---|
| Title: | A comparative study of energy-oriented driving strategy for connected electric vehicles on freeways with varying slopes |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.energy.2023.129916 |
| Publisher version: | https://doi.org/10.1016/j.energy.2023.129916 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Eco-driving; Dynamic programming; Model predictive control; Electric vehicles; Energy efficiency |
| 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.ucl.ac.uk/id/eprint/10183141 |
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