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