Browse Topic: Wind tunnel tests
The front wing of a Formula 1 car is one of the most important aerodynamic components in design development. Particularly, as it is the first to interact with the upcoming airflow, the aerodynamic flow structures generated will have a strong interaction with the remainder of the car’s components. In 2026, the Fédération Internationale de l’Automobile will introduce new regulations that incorporate new aerodynamic philosophies for the front wing, including active aerodynamics. This paper presents a design methodology study for the development of a Formula 1 2026 front wing, compliant with Issue 9 of the technical regulations. A computational-based, structured optimisation series was conducted to enhance the aerodynamic performance of a front wing concept with a focus on improving downforce, maximising efficiency, and enhancing trailing flow for the remainder of the car. The final front wing concept at 40%, running at 30 m/s, generated 189 N of downforce and 19 N of drag. Active
MSIL (Maruti Suzuki India Limited), India’s leading automotive manufacturer, offers a diverse range of SUVs (Sports Utility Vehicles) in its portfolio. Traditionally, SUVs are associated with an assertive stance and a commanding road presence; however, this bold design language often compromises aerodynamic drag performance. Over the past decade, demand for this segment has surged, while CAFE (Corporate Average Fuel Economy) regulations have become increasingly stringent. To address this growing market need, MSIL conceptualized a new SUV - Victoris - targeted to deliver best-in-class aerodynamic efficiency in MSIL SUV portfolio. This paper details the aerodynamic development process using CFD (Computational Fluid Dynamics) and full-scale WTT (Wind Tunnel Testing). Initially, the aggressive styling of Victoris negatively impacted drag performance. Strategic exterior surface refinements and integration of aero components enabled recovery of aerodynamic efficiency. Key interventions
Modern aeroacoustic wind tunnels are required to have flat axial static pressure distribution, very low background noise levels, and minimal low-frequency pressure fluctuations. These characteristics enable accurate measurement of aerodynamic forces acting on a vehicle as well as identification of noise sources. The collector of an open-jet or ¾ open-jet wind tunnel plays a critical role in achieving these goals. Collector self-generated noise contributes to the overall background noise level in the test section, and this contribution has become more significant as other noise sources, such as the main fan, have been addressed through improvements to acoustic treatment. Ever-increasing attention to detail is required to manage noise signatures as the overall facility noise floor is lowered. Furthermore, aspects of collector design that may be beneficial to aerodynamics or pressure fluctuation tend to be some of the worst offenders for noise generation. A new collector configuration was
A research team developed a smart strake system that dynamically adapts to flight conditions, showing a promising drag reduction in the wind tunnel with respect to passive strakes. This approach has the potential to save airlines hundreds of kilograms of fuel per flight. University of Washington Department of Aeronautics & Astronautics (A&A), Seattle, WA For decades, aircraft have carried a fundamental compromise between their engines and wing flow interactions by using strakes. These are small fins attached at the sides of engine nacelles that generate helpful vortices during takeoff and landing that boost lift and avoid stall, but create unwanted drag during cruise flight. Now, seven William E. Boeing Department of Aeronautics & Astronautics (A&A) undergraduates have advanced a solution that improves this trade-off, achieving up to 33 percent drag reduction, on the limited tested conditions, during cruise while maintaining critical safety benefits at high angles of attack. The team
The present work demonstrates a transient Fluid-Structure-Interaction (FSI) based numerical methodology for estimation of aerodynamic-induced flutter of the rear bumper of a Sports Utility Vehicle (SUV). Finite Volume Method (FVM) based High-fidelity transient full vehicle aerodynamic simulations were conducted for the estimation of the transient aerodynamic load. Subsequently, by mapping this transient aero load onto the surface of the rear bumper, Finite Element Method (FEM) based dynamic structural simulations were performed to predict its response. The results obtained through simulations were then compared against experimental wind tunnel test data of a prototype car with modified bumper for the specific test-case. The pressure and the time series data of rear bumper deflection were captured at multiple probe locations from wind tunnel experiments at 140 and 200 kmph. The distribution of pressure on the rear surfaces of the car was well captured by the aerodynamic simulation at
The automotive industry is rapidly advancing towards autonomous vehicles, making sensors such as Cameras, LiDAR, and RADAR critical components for ensuring constant information exchange between the vehicle and its surrounding environment. However, these sensors are vulnerable to harsh environmental conditions like rain, dirt, snow, and bird droppings, which can impair their functionality and disrupt accurate vehicle maneuvers. To ensure all sensors operate effectively, dedicated cleaning is implemented, particularly for Level 3 and higher autonomous vehicles. It is important to test sensor cleaning mechanisms across different weather conditions and vehicle operating scenarios to ensure reliability and performance. One crucial aspect of testing is tracking the trajectory of the cleaning fluid to ensure it does not cause self-soiling of vehicles and affects the field of view or visibility zones of other components like the windshield. While wind tunnel tests are valuable, digitalizing
The present work demonstrates a Fluid-Structure Interaction (FSI) based methodology that couples a Finite Volume Method (FVM) and Finite Element Method (FEM) based tools to estimate air guide deformation, thereby predicting accurate aerothermal performance. The method starts with a digital assembly step where the assembly shape and the induced stress due to assembly is predicted. A full vehicle Aerodynamic simulation is performed to extract the surface pressure on the air guide which is then used to estimate the extent of deformation of the air guides. Based on the extent a subsequent Aerodynamic simulation may be carried out to predict thermal efficiency. Comparison against pressure data and deflection data extracted from the wind tunnel experiments of vehicles has shown reasonable match demonstrating the accuracy and usefulness of the method.
Reducing drag forces and minimizing the rear wake region are the main goals of evaluating exterior aerodynamic performance in automobiles. Various literature and experiments shows that the overall fuel computations of the road vehicle improves significantly with the reduction in aerodynamic drag force. In the road vehicle major components of the drag is due the imbalance in pressure between front and rear of the vehicle. At high vehicle speed, aerodynamic drag is responsible for approximately 30 to 40% of the energy consumption of the vehicle. In the recent year, cost of high-performance computing (HPC) has reduced significantly, which helped computational fluid dynamics (CFD) is an affordable tool to the automotive industry for evaluating aerodynamic performance of the vehicle during developing phase. The vehicles aerodynamic performance is greatly impacted by the dynamic environmental conditions it encounters in the real world. Such environmental conditions are difficult to replicate
Wind Tunnels are complex and cost-intensive test facilities. Thus, increasing the test efficiency is an important aspect. At the same time, active aerodynamic elements gain importance for the efficiency of modern cars. For homologation, such active aero-components pose an extra level of test complexity as their control strategies, the relevant drive cycles and their aerodynamics in different positions must be considered for homologation-relevant data. Often, active components have to be manually adjusted between test runs, which is a time-consuming process because the vehicle is not integrated into the test automation. Even if so, designing a test sequence stepping through the individual settings for each component of a vehicle is a tedious task in the test session. Thus, a sophisticated integration of the wind tunnel control system with a test management system, supporting the full homologation process is one aspect of a solution. The other is the integration of the vehicle’s active
Sound source identification based on beamforming is widely used today as a spatial sound field visualization technology in wind tunnel experiments for vehicle development. However, the conventional beamforming technique has its inherent limitation, such as bad spatial resolution at the low frequency range, and limited system dynamic range. To improve the performance, three deconvolution methods CLEAN, CLEAN-SC and DAMAS were investigated and applied to identify wind noise sources on a production car in this paper. After analysis of vehicle exterior wind noise sources distribution, correlation analysis between identified exterior noise sources and interior noise were conducted to study their energy contribution to vehicle interior. The results show that the algorithm CLEAN-SC based on spatial source coherence shows the best capability to remove the sidelobes for the uncorrelated wind noise sources, while CLEAN and DAMAS, which are based on point spread functions have definite
The current Range Rover is the fifth generation of this luxury SUV. With a drag coefficient of 0.30 at launch, it was the most aerodynamically efficient luxury SUV in the world. This aerodynamic efficiency was achieved by applying the latest science. Rear wake control was realised with a large roof spoiler, rear pillar and bodyside shaping, along with an under-floor designed to reduce losses over a wide range of vehicle configurations. This enabled manipulation of the wake structure to reduce drag spread, optimising emissions measured under the WLTP regulations. Along with its low drag coefficient, in an industry first, it was developed explicitly to achieve reduced rear surface contamination with reductions achieved of 70% on the rear screen and 60% over the tailgate when compared against the outgoing product. This supports both perceptions of luxury along with sensor system performance, demonstrating that vehicles can be developed concurrently for low drag and reduced rear soiling
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