Metamodel-based simulation to assess platooning on battery energy consumption
New technological advances have made possible the recent development of automated and connected vehicles. However, there are still challenges to overcome. For example, maintaining constant values for speed and distance between vehicles when the connection has been interrupted. In this line of research, this paper presents the extension of the 3DCoAutosim simulation platform to integrate platooning by means of a dynamic-flexible model that the authors validate by creating use cases on traffic efficiency. We measured the effects of dynamic-flexible and consistent platooning on battery energy consumption taking into account real-world trips data, collected in Upper Austria. For this purpose we used three electric vans with an autonomous leader, a first semi-autonomous follower with driver and a last autonomous follower. The results showed that the proposed model is able to demonstrate a decrease of the total battery energy consumption when driving in platoon mode.
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- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
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Supplemental Notes:
- © 2022 Aso Validi et al. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
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Authors:
- Validi, Aso
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0000-0002-9335-390X
- Smirnov, Nikita
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0000-0002-6051-9934
- Olaverri-Monreal, Cristina
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0000-0002-5211-3598
- Publication Date: 2022-8
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 103350
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Serial:
- Transportation Research Part D: Transport and Environment
- Volume: 109
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 1361-9209
- Serial URL: http://www.sciencedirect.com/science/journal/13619209
Subject/Index Terms
- TRT Terms: Connected vehicles; Electric batteries; Energy consumption; Simulation; Traffic platooning
- Subject Areas: Energy; Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01852380
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 21 2022 11:42AM