LAPSE:2023.34055
Published Article
LAPSE:2023.34055
Distributed Nonlinear Model Predictive Control for Connected Autonomous Electric Vehicles Platoon with Distance-Dependent Air Drag Formulation
April 24, 2023
This paper addresses the leader tracking problem for a platoon of heterogeneous autonomous connected fully electric vehicles where the selection of the inter-vehicle distance between adjacent vehicles plays a crucial role in energy consumption reduction. In this framework, we focused on the design of a cooperative driving control strategy able to let electric vehicles move as a convoy while keeping a variable energy-oriented inter-vehicle distance between adjacent vehicles which, depending on the driving situation, was reduced as much as possible to guarantee air-drag reduction, energy saving and collision avoidance. To this aim, by exploiting a distance-dependent air drag coefficient formulation, we propose a novel distributed nonlinear model predictive control (DNMPC) where the cost function was designed to ensure leader tracking performances, as well as to optimise the inter-vehicle distance with the aim of reducing energy consumption. Extensive simulation analyses, involving a comparative analysis with respect to the classical constant time headway (CTH) spacing policy, were performed to confirm the capability of the DNMPC in guaranteeing energy saving.
Keywords
air drag coefficient, distributed nonlinear model predictive control, e-platoon, electric vehicles (EVs), energy consumption
Suggested Citation
Caiazzo B, Coppola A, Petrillo A, Santini S. Distributed Nonlinear Model Predictive Control for Connected Autonomous Electric Vehicles Platoon with Distance-Dependent Air Drag Formulation. (2023). LAPSE:2023.34055
Author Affiliations
Caiazzo B: Department of Information Technology and Electrical Engineering (DIETI), University of Naples Federico II, 80125 Naples, Italy [ORCID]
Coppola A: Department of Information Technology and Electrical Engineering (DIETI), University of Naples Federico II, 80125 Naples, Italy [ORCID]
Petrillo A: Department of Information Technology and Electrical Engineering (DIETI), University of Naples Federico II, 80125 Naples, Italy [ORCID]
Santini S: Department of Information Technology and Electrical Engineering (DIETI), University of Naples Federico II, 80125 Naples, Italy [ORCID]
Journal Name
Energies
Volume
14
Issue
16
First Page
5122
Year
2021
Publication Date
2021-08-19
Published Version
ISSN
1996-1073
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Original Submission
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PII: en14165122, Publication Type: Journal Article
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LAPSE:2023.34055
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doi:10.3390/en14165122
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Apr 24, 2023
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