Investigating Fuel Efficiency of Heavy-Duty Vehicle Platooning Using a CFD Model

Abstract Platooning represents a crucial strategy for mitigating emissions from heavy-duty vehicles (HDVs). This study evaluates the effects of platoon composition on the surrounding airflow utilizing a computational fluid dynamics (CFD) model, and quantifies the resultant fuel efficiency and CO 2 emissions. This study examines fuel consumption data reconstructed from field experiments to validate the CFD model’s ability to accurately simulate drag forces within a homogeneous three-truck platoon. The potential for fuel savings was assessed based on CFD-simulated fuel consumption, taking into account various inter-vehicle distances and driving speeds. The model successfully reproduced the fuel consumption observed in a platooning formation comprising lead, middle, and trailing trucks, with an error margin below 6.2%. Fuel consumption analysis shows that while lead and middle trucks consume more fuel with increased inter-vehicle distances, the trailing truck's consumption decreases at specific distance-to-length ratios (D/L), increasing again beyond a D/L of 1.1. Additionally, a significant decrease in total fuel efficiency was noted for D/L ratios exceeding 1.5. Considering the diverse platooning scenarios analyzed, the study anticipates an annual reduction of up to 7 tons of CO 2 equivalent per vehicle. By optimizing platooning configurations, this research contributes to enhancing fuel efficiency and reducing emissions from HDVs.

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Publication Details

Journal
Asia-Pacific Journal of Atmospheric Sciences
Published
2025-02-04
DOI
https://doi.org/10.1007/s13143-025-00390-y
Citations
2
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
2.43

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article

Investigating Fuel Efficiency of Heavy-Duty Vehicle Platooning Using a CFD Model

Chang‐Keun Song, Yeri Kang, EunRyoung Kim, Ha Jin Hwang et al.
2 citations
Asia-Pacific Journal of Atmospheric Sciences
Traffic control and management
2.43
article

Investigating Fuel Efficiency of Heavy-Duty Vehicle Platooning Using a CFD Model

Chang‐Keun Song, Yeri Kang, EunRyoung Kim, Ha Jin Hwang, Jae‒Jin Kim
article en
2 citations

Abstract

Abstract Platooning represents a crucial strategy for mitigating emissions from heavy-duty vehicles (HDVs). This study evaluates the effects of platoon composition on the surrounding airflow utilizing a computational fluid dynamics (CFD) model, and quantifies the resultant fuel efficiency and CO 2 emissions. This study examines fuel consumption data reconstructed from field experiments to validate the CFD model’s ability to accurately simulate drag forces within a homogeneous three-truck platoon. The potential for fuel savings was assessed based on CFD-simulated fuel consumption, taking into account various inter-vehicle distances and driving speeds. The model successfully reproduced the fuel consumption observed in a platooning formation comprising lead, middle, and trailing trucks, with an error margin below 6.2%. Fuel consumption analysis shows that while lead and middle trucks consume more fuel with increased inter-vehicle distances, the trailing truck's consumption decreases at specific distance-to-length ratios (D/L), increasing again beyond a D/L of 1.1. Additionally, a significant decrease in total fuel efficiency was noted for D/L ratios exceeding 1.5. Considering the diverse platooning scenarios analyzed, the study anticipates an annual reduction of up to 7 tons of CO 2 equivalent per vehicle. By optimizing platooning configurations, this research contributes to enhancing fuel efficiency and reducing emissions from HDVs.

Asia-Pacific Journal of Atmospheric SciencesVol. 61(2)
Ulsan National Institute of Science and Technology (KR), Pukyong National University (KR), The Korea Institute of Public Administration (KR)
Ulsan National Institute of Science and Technology, National Institute of Environmental Research, Korea Environmental Industry and Technology Institute
Openalex Percentile: Top 14%
Traffic control and management
2.43
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