Affiliation:
1. National Research Council Canada
Abstract
<div class="section abstract"><div class="htmlview paragraph">Aerodynamic interaction between vehicles on a roadway can modify the fuel use and greenhouse gas emissions of the vehicle relative to their performance under isolated, uniform-wind conditions. A comprehensive wind-tunnel study was undertaken to examine changes to the aerodynamic drag experienced by vehicles in close proximity, in adjacent lanes. Wind-load measurements were conducted for two general configurations: 15%-scale testing with light-duty-vehicle (LDV) models, and 6.7%-scale testing with a heavy-duty vehicle (HDV) model. For the LDV study, a DrivAer model was tested with a proximate AeroSUV model or an Ahmed model at lateral distances representing 75%, 100%, and 125% of a typical highway lane spacing, and for longitudinal distances up to 2 vehicle lengths forward and back. Commensurate measurements were conducted for the AeroSUV model with the proximate DrivAer or Ahmed model. For the HDV study, a tractor-trailer model was tested with a single or combination of adjacent-lane models. Measurements were conducted over a range of yaw angles, permitting wind-averaged-drag evaluations.</div><div class="htmlview paragraph">Changes in drag coefficient on the order of 25% or more were observed, relative to isolated-vehicle conditions. Adjacent-lane proximity-vehicle effects can increase or decrease the drag of a vehicle, with the strongest effects being an increase when vehicle models are side-by-side or when an HDV has its aft end coincident with another vehicle. The LDV-model pairing demonstrated that, for a two-vehicle arrangement, the increased drag on one vehicle can be offset by the decrease in drag on the other, and that proximity-vehicle effects should be examined in the context of the overall vehicle-system performance.</div></div>
Subject
Artificial Intelligence,Mechanical Engineering,Fuel Technology,Automotive Engineering
Cited by
2 articles.
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