Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
121 tokens/sec
GPT-4o
9 tokens/sec
Gemini 2.5 Pro Pro
47 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Vehicle Platooning Impact on Drag Coefficients and Energy/Fuel Saving Implications (2001.00560v2)

Published 2 Jan 2020 in eess.SY, cs.MA, and cs.SY

Abstract: In this paper, empirical data from the literature are used to develop general power models that capture the impact of a vehicle position, in a platoon of homogeneous vehicles, and the distance gap to its lead (and following) vehicle on its drag coefficient. These models are developed for light duty vehicles, buses, and heavy duty trucks. The models were fit using a constrained optimization framework to fit a general power function using either direct drag force or fuel measurements. The model is then used to extrapolate the empirical measurements to a wide range of vehicle distance gaps within a platoon. Using these models we estimate the potential fuel reduction associated with homogeneous platoons of light duty vehicles, buses, and heavy duty trucks. The results show a significant reduction in the vehicle fuel consumption when compared with those based on a constant drag coefficient assumption. Specifically, considering a minimum time gap between vehicles of $0.5 \; secs$ (which is typical considering state-of-practice communication and mechanical system latencies) running at a speed of $100 \; km/hr$, the optimum fuel reduction that is achieved is $4.5 \%$, $15.5 \%$, and $7.0 \%$ for light duty vehicle, bus, and heavy duty truck platoons, respectively. For longer time gaps, the bus and heavy duty truck platoons still produce fuel reductions in the order of $9.0 \%$ and $4.5 \%$, whereas light duty vehicles produce negligible fuel savings.

Citations (49)

Summary

We haven't generated a summary for this paper yet.