Drag reduction via separation control using plasma actuators on a truck cabin side

TL;DR

This study demonstrates active flow control of a heavy-duty truck model using dielectric-barrier discharge plasma actuators mounted on the A-pillars to mitigate lateral separation bubbles and reduce drag. Through wind-tunnel experiments on the GTS at $Re=4.2\times 10^4$ and yaw angles up to $7.5^\circ$, the authors compare leeward, windward, and symmetric actuation modes, revealing that leeward actuation generally provides stronger drag reduction across yaw, while windward actuation loses effectiveness at larger yaws. PIV analyses show the actuators shrink the lateral separation bubbles, decreasing the apparent frontal area and correlating bubble size with drag reductions (linear relation, $R^2\approx0.82$). The authors also propose an adaptive control strategy that switches off the windward actuator beyond a threshold yaw to maintain drag benefits while reducing energy use, highlighting practical implications for tractor-trailer aerodynamics and energy efficiency.

Abstract

We investigate the drag reduction on a heavy-duty vehicle using dielectric-barrier discharge plasma actuators located on the A-pillars. An experimental campaign is carried out on a generalized truck model, the Ground Transportation System (GTS), which is known for its lateral separation bubbles on both sides of the truck's cabin. Measurements are performed for several yaw angles up to $7.5\degree$. Actuation is applied individually on the leeward and windward sides as well as simultaneously. Load cell measurements show that the plasma actuators effectively reduce the axial force on the GTS, with symmetric actuation achieving the highest reduction. Leeward actuation demonstrates greater control authority than the windward one; at large yaw angles the latter has a negligible effect on the axial force. Regarding side force, the leeward actuation produces a drop in its magnitude while windward actuation produces an increase. Interestingly, actuating symmetrically also augments the side force. Particle image velocimetry reveals that the plasma actuator causes a reduction in the length and width of the separation bubble on the cabin side, reducing the apparent frontal area of the truck and thus its drag. Under crosswind conditions, the stronger authority of the leeward actuator is explained by the larger separation bubble. The side force variation is driven by the net lateral suction force, which correlates with the size of the lateral recirculation regions controlled by the actuators.

Figures (9)

• Figure 1: Setup of the experiment. The reference axes are in red, and the laser sheet is in green. The plasma actuator indicated in violet is also present on the other side.
• Figure 2: Functioning principle of a DBD plasma actuator. Reproduced from castellanos_convective_2022.
• Figure 3: Influence of the yaw angle on the axial force coefficient $C_x$. The experimental datapoints without actuation as well as the regression are shown in Figure \ref{['fig:Cx_NA_alphacorr']}. Figure \ref{['fig:Delta_Cx_alphacorr']} shows only the difference between the linear fit of the baseline case and the ones of the actuated cases. The area where drag is reduced is marked in green, while red indicates a drag increase.
• Figure 4: Influence of the yaw angle on the absolute lateral force coefficient $|C_y|$. The experimental datapoints without actuation as well as the regression are shown in Figure \ref{['fig:Cy_NA_alphacorr']}. Figure \ref{['fig:Delta_Cy_alphacorr']} shows only the difference between the linear fit of the baseline case and the ones of the actuated cases. The area where the absolute lateral force is reduced is marked in green, while the area where it increases appears in red.
• Figure 5: Visualization of the separation bubble on the GTS left side, based on PIV measurements. First, second, and third columns show $\alpha=0\degree$, $\alpha=5\degree$, and $\alpha=-5\degree$, respectively. The top row shows the velocity field without actuation, and the bottom row with actuation. Flow is from left to right. The fields are averaged over 1500 samples. The color indicates the normalized velocity magnitude, while the orientation is rendered using a LIC visualization. Ticks indicate the spatial coordinates as fractions of the truck width $W$.