CDF Analysis and Prediction Model for Air Resistance on Platooned Freight Trucks

She, Ruifeng; Ouyang, Yanfeng; Al-Qadi, Imad L

doi:10.36501/0197-9191/20-011

i

CDF Analysis and Prediction Model for Air Resistance on Platooned Freight Trucks

2018-11-01
By She, Ruifeng ; Ouyang, Yanfeng ; Al-Qadi, Imad L

File Language:

English

Details

Creators:

She, Ruifeng ; Ouyang, Yanfeng ; Al-Qadi, Imad L
Corporate Creators:

Illinois Center for Transportation ; University of Illinois at Urbana-Champaign. Department of Civil and Environmental Engineering
Corporate Contributors:

Center for Connected and Automated Transportation (CCAT) ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Publication/ Report Number:

ICT-20-011
DOI:

https://doi.org/10.36501/0197-9191/20-011
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

University of Michigan. Center for Connected and Automated Transportation
Abstract:

Motivated by autonomous and connected vehicle technology, truck platooning has significant economic benefits on the freight transportation industry. Lower average fuel consumption can be achieved due to the reduced air-drag force experienced by the platoon during operation. This report presents the procedure and results of computational fluid dynamics (CFD) analysis and aims to evaluate the stationary air drag on platooned freight trucks. CFD simulation is performed on paired truck models using the Ansys Fluent software to quantify the effect of positioning on drag force. A prediction model is proposed to evaluate the average air drag on platoons of various sizes and spatial configurations. The results of this study showed the loss of air-drag reduction in platooning when trucks are separated and misaligned and suggested the platoon size needed to achieve maximum drag reduction.
Format:

PDF
Funding:

69A3551747105
Download URL:

https://rosap.ntl.bts.gov/view/dot/60756/dot_60756_DS1.pdf
File Type:

[PDF - 1.19 MB]
Collection(s):

Autonomous Vehicles ; University Transportation Centers
Main Document Checksum:

urn:sha-512:fe0835636c1c6888e7c135d292ed93dab89f27de629fec507a7d3cc95e40bb7ad5c85a691f78d4868e58a1155d95bd2c0daee80ec998d151200247937180c939

File Language:

English

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