eprintid: 10183141 rev_number: 11 eprint_status: archive userid: 699 dir: disk0/10/18/31/41 datestamp: 2023-12-06 17:21:37 lastmod: 2024-12-23 07:10:04 status_changed: 2023-12-06 17:21:37 type: article metadata_visibility: show sword_depositor: 699 creators_name: Li, Bingbing creators_name: Zhuang, Weichao creators_name: Zhang, Hao creators_name: Zhao, Ruixuan creators_name: Liu, Haoji creators_name: Qu, Linghu creators_name: Zhang, Jianrun creators_name: Chen, Boli title: A comparative study of energy-oriented driving strategy for connected electric vehicles on freeways with varying slopes ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F46 keywords: Eco-driving; Dynamic programming; Model predictive control; Electric vehicles; Energy efficiency note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. 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. date: 2024-02-15 date_type: published publisher: Elsevier official_url: https://doi.org/10.1016/j.energy.2023.129916 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 2114952 doi: 10.1016/j.energy.2023.129916 lyricists_name: Chen, Boli lyricists_id: BCHEB76 actors_name: Chen, Boli actors_id: BCHEB76 actors_role: owner full_text_status: public publication: Energy volume: 289 article_number: 129916 issn: 0360-5442 citation: Li, Bingbing; Zhuang, Weichao; Zhang, Hao; Zhao, Ruixuan; Liu, Haoji; Qu, Linghu; Zhang, Jianrun; Li, Bingbing; Zhuang, Weichao; Zhang, Hao; Zhao, Ruixuan; Liu, Haoji; Qu, Linghu; Zhang, Jianrun; Chen, Boli; - view fewer <#> (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 <https://doi.org/10.1016/j.energy.2023.129916>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10183141/1/Energy_F.pdf