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The purpose of this paper is to study pressure measurement correlations, as the location of the pressure sensors should enable to capture variation of the drag force depending on the yaw angle and some geometrical modifications.

The present aerodynamical study, performed on a reduced scale mock-up representing a sport utility vehicle, involves both numerical and experimental investigations. Experiments performed in a wind tunnel facility deal with drag and pressure measurements related to the side wind variation. The pressure sensor locations are deduced from wall streamlines computed from large eddy simulation results on the external surfaces of the mock-up.

After validation of the drag coefficient (Cd) values computed with an aerodynamic balance, measurements should only imply pressure tap mounted on the vehicle to perform real driving emission (RDE) tests.

Relation presented in this paper between pressure coefficients measured on a side sensor and the drag coefficient data must enable to better quantify the drag force contribution of a ground vehicle in RDE tests.

The purpose of this paper is to present numerical investigations of the flow dynamic characteristics of a 47° Ahmed Body to identify wake flow control strategy leading to drag coefficient reduction, which could be tested later on sport utility vehicles.

This study begins with a mean flow topology description owing to dynamic and spectral analysis of the aerodynamic tensor. Then, the sparse promoting dynamic modal decomposition method is discussed and compared to other modal approaches. This method is then applied on the wall and wake pressure to determine frequencies of the highest energy pressure modes and their transfers to other frequency modes. This analysis is then used to design appropriated feedback flow control strategies.

This dynamic modal decomposition highlights a reduced number of modes at low frequency which drive the flow dynamics. The authors especially notice that the pressure mode at a Strouhal number of 0.22, based on the width between feet, induces aerodynamic losses close to the rear end. Strategy of the proposed control loop enables to dampen the energy of this mode, but it has been transferred to lower frequency mode outside of the selected region of interest.

This analysis and methodology of feedback control shows potential drag reduction with appropriated modal energy transfer management.

This paper aims to present an experimental investigation of an active flow control solution mounted at rear of a sport utility vehicle (SUV) with the objective of drag reduction, thanks to a selection of flow control parameters leading to a pressure increase on the tailgate.

A flow control design of experiments was conducted with a pulsed jet system mounted on the top and sides of the rear window of the vehicle. The wall pressure, instantaneous velocity and drag were measured with this prototype in a wind tunnel. A dynamic modal decomposition (DMD) analysis of the pressure enables to describe the pressure fluctuations. Fluid dynamic computations show relation between pressure and velocity fields.

Measurements with this prototype in the wind tunnel revealed small improvements in drag for the best flow control configurations. This small benefit is because of the core of the upper span wise vortex further away from the rear window than the lower span wise vortex. These small improvements in drag were confirmed with pressure measurements on the rear window and tailgate. The DMD analysis of the surface pressure showed a low frequency pendulum oscillation on the lower area of the tailgate, linked with low velocity frequencies in the shear layers near the tailgate.

Experimental and numerical results show interest to increase pressure at bottom of the rear end of this SUV prototype. The dynamic description of the wall pressure shows importance of flow control solutions reducing pressure fluctuations at low frequencies in the lower area of the tailgate.

The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.