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Integrated Battery Lifetime and Energy Efficiency Driving Strategy for Electric Vehicles in Urban Environments

Li, Bingbing; Zhuang, Weichao; Zhang, Sunan; Chen, Mingyang; Yin, Guodong; Chen, Boli; (2024) Integrated Battery Lifetime and Energy Efficiency Driving Strategy for Electric Vehicles in Urban Environments. In: 2024 IEEE Conference on Control Technology and Applications (CCTA). (pp. pp. 577-583). IEEE: Newcastle upon Tyne, United Kingdom. Green open access

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Abstract

Continuous traffic signal intersections in urban roads significantly increase vehicle energy consumption and the frequent acceleration and deceleration spur the degradation of electric vehicles (EVs) batteries. This paper proposes an integrated battery lifetime and energy efficiency driving strategy (IBE) based on a hierarchical framework for EVs in urban roads with multi-signalized intersections. In the upper layer, vehicles take into account global information from multiple traffic signals ahead in their travel direction to determine feasible phases time at each intersection. In the lower layer, a spatialdomain-based model predictive control (S-MPC) framework is introduced to achieve optimal control of the vehicle. Simulation results indicate that the proposed IBE strategy avoids stopping at red lights and, compared to two typical constant-speed strategies, can achieve a maximum improvement of 26.6% in battery lifetime and 10.5% in energy savings.

Type: Proceedings paper
Title: Integrated Battery Lifetime and Energy Efficiency Driving Strategy for Electric Vehicles in Urban Environments
Event: The 8th IEEE Conference on Control Technology and Applications (CCTA) 2024
Location: NEWCASTLE UPON TYNE, UK
Dates: 21 Aug 2024 - 23 Aug 2024
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/CCTA60707.2024.10666572
Publisher version: https://doi.org/10.1109/CCTA60707.2024.10666572
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, Model predictive control (MPC), Electric vehicles (EVs), Energy efficiency, Battery lifetime
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/10192821
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