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Ecological Electric Vehicle Platooning: An Adaptive Tube-based Distributed Model Predictive Control Approach

Sun, Hao; Li, Bingbing; Zhang, Hao; Dai, Li; Fedele, Giuseppe; Zhuang, Weichao; Chen, Boli; (2024) Ecological Electric Vehicle Platooning: An Adaptive Tube-based Distributed Model Predictive Control Approach. IEEE Transactions on Transportation Electrification 10.1109/TTE.2024.3400461. (In press). Green open access

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Abstract

The advent connected and autonomous vehicle technologies have greatly improved traffic in terms of energy efficiency and road safety. This paper addresses an ecological control problem of electric vehicle platoons subject to various system uncertainties, including but not limited to modeling uncertainties and measurement noise from different sources. Based on a spatial domain modeling approach with appropriate coordination change and nonconvex constraints relaxation, the traditional nonlinear optimal control problem is convexified. Reformulation in spatial domain can incorporate accurate road information, and convexification substantially improves computational efficiency. Then, aforementioned models are employed within an adaptive tube-based distributed model predictive control (AT-DMPC) framework, taking into account platoon formation consensus, road safety, energy consumption and driver comfort under the predecessor-following communication topology. Finally, numerical simulations and hardware-in-the-loop experiments are conducted to assess the performance of the proposed method relative to several state-of-the-art algorithms.

Type: Article
Title: Ecological Electric Vehicle Platooning: An Adaptive Tube-based Distributed Model Predictive Control Approach
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TTE.2024.3400461
Publisher version: https://doi.org/10.1109/TTE.2024.3400461
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: Biological system modeling, Uncertainty, Adaptation models, Topology, Mathematical models, Electric vehicles, Computational modeling
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/10192092
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