Bibliographic Details
| Title: |
Influence of Inter-Vehicle Distance on the Aerodynamics of a Two-Truck Platoon. |
| Authors: |
Törnell, Johannes1 (AUTHOR) johannes.tornell@chalmers.se, Sebben, Simone1 (AUTHOR), Söderblom, David2 (AUTHOR) |
| Source: |
International Journal of Automotive Technology. Jun2021, Vol. 22 Issue 3, p747-760. 14p. |
| Subjects: |
Aerodynamics, Computational fluid dynamics, Motor vehicle driving, Truck driving, Model trucks, Aerodynamic load, Transonic flow |
| Abstract: |
The increasing importance of fuel and energy efficiency in transport combined with recent improvements in vehicle automation has renewed interest in the concept of platooning. Many studies so far have used very simplified models, thus, creating a need for understanding the flow behavior and the aerodynamic gains in more complex scenarios. This paper proposes a method of examining the aerodynamics of vehicles driving in close proximity using detailed European truck models and Computational Fluid Dynamics. The study was conducted using two trucks driving at inter-vehicle distances of 2.5 m to 20 m. A thorough numerical investigation was carried out and showed that the combined drag of the platoon had a continuous improvement with decreased distance between the vehicles. This was due to a significant drag improvement of the leading truck. This behavior originated from the increased base pressure induced by the presence of a close blockage behind it. The drag of the trailing truck showed an opposite behavior, that is, a moderate increase in drag with decreased inter-vehicle distance. This was a result of a decreased acceleration of the flow around the front edges and an increase in pressure in the tractor-trailer gap. [ABSTRACT FROM AUTHOR] |
|
Copyright of International Journal of Automotive Technology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |