Search Results (5)

In racing cars, a low ride height is crucial for inverted wings and ground-effect systems to function effectively, significantly enhancing aerodynamic performance but also increasing sensitivity to pitch and roll variations. However, the specific impact of wheel-ground conditions on racing cars under ride-height-related attitude variations has not received attention. This study employed numerical simulations (compared with wind tunnel test data) to investigate these effects on racecar aerodynamic characteristics, analyzing three specific wheel-ground combinations: moving ground with rotating wheels (MR), moving ground with stationary wheels (MS), and stationary ground with stationary wheels (SS). A systematic analysis was conducted on aerodynamic changes associated with wheel-plane total pressure coefficient differences, upper-lower surface pressure coefficient variations, and front-rear axle aerodynamic force distributions, elucidating individual component contributions to overall performance changes induced by wheel-ground alterations. Results indicate that wheel conditions, especially rear wheels and their localized interactions with the diffuser-equipped body predominantly influence drag. In contrast, ground conditions primarily affect the body and front wing to alter downforce, with induced drag variations further amplifying total drag differences. Moreover, ground conditions’ impact on the front wing is modulated by vehicle attitude, resulting in either increased or decreased front wing downforce and thus altering aerodynamic balance. These insights highlight that ride-height related attitudes are critical variables when evaluating combined wheel-ground effects, and while wheel rotation is significant, the aerodynamic force and balance changes induced by ground conditions (as modulated by attitude) warrant greater attention. This understanding provides valuable guidance for racecar aerodynamic design. Full article

One of the key elements in the aerodynamic balance of a race car is the front wing, which is responsible for generating downforce to enhance grip. This article aims to investigate the change in downforce on a Formula Student racecar with a newly mounted front wing and aerodynamic elements at different angles of attack by means of Computational Fluid Dynamics (CFD). In addition, the effect of the front wing on the position of the center of pressure was also investigated, which highly influences the steering stability of the car. The study proved that by applying the front wing, together with additional aerodynamic elements, the downforce increases by 38%, while the center of pressure moves closer to the front axes by approximately 30% (compared to when there is no wing on the car), which results in an understeered but stable controllability. Full article

The Xfinity Racing Series is an American stock car racing series organized by NASCAR. For the 2017 racing season, NASCAR introduced new regulations with the objective of creating a level playing field by reducing aerodynamic influence on vehicle performance. In this context, the primary objective of this work is to explore the differences in the aerodynamic performance between the 2016 and 2017 Toyota Camry Xfinity racecars using only open-source Computational Fluid Dynamics (CFD) and CAE tools. During the CFD validation process, it was observed that none of the standard turbulence models, with default turbulence model closure coefficients, were able to provide racecar aerodynamic characteristics predictions with acceptable accuracy compared to experiments. This necessitated a fine-tuning of the closure coefficient numeric values. This work also demonstrates that it is possible to generate CFD predictions that are highly correlated with experimental measurements by modifying the closure coefficients of the standard $k-\omega$ SST turbulence model. Full article

This study focuses on the development of a body for an electric racecar, utilizing CAD software for the design. A simplified full-vehicle geometric model was constructed. Based on fundamental theories of computational fluid dynamics and using CAE software platforms, the shear stress transport (SST) k-ω physical model was chosen to establish a three-dimensional computational model of the racecar’s external flow field. Simulations were conducted to analyze the pressure, airflow streamlines, and velocity distribution around the body and its surrounding flow field, elucidating the impact of body shape structure on aerodynamic characteristics. Finally, a manufacturing process for the body was designed, and a prototype was produced and integrated into the complete vehicle for road testing. The results indicate that the designed electric racecar body maintained consistent airflow over its surface, meeting the basic requirements of aerodynamics. Full article

Racecar aerodynamic development requires well-correlated simulation data for rapid and incremental development cycles. Computational Fluid Dynamics (CFD) simulations and wind tunnel testing are industry-wide tools to perform such development, and the best use of these tools can define a race team’s ability to compete. With CFD usage being limited by the sanctioning bodies, large-scale mesh and large-time-step CFD simulations based on Reynolds-Averaged Navier–Stokes (RANS) approaches are popular. In order to provide the necessary aerodynamic performance advantages sought by CFD development, increasing confidence in the validity of CFD simulations is required. A previous study on a Scale-Averaged Simulation (SAS) approach using RANS simulations of a Gen-6 NASCAR, validated against moving-ground, open-jet wind tunnel data at multiple configurations, produced a framework with good wind tunnel correlation (within 2%) in aerodynamic coefficients of lift and drag predictions, but significant error in front-to-rear downforce balance (negative lift) predictions. A subsequent author’s publication on a Scale-Resolved Simulation (SRS) approach using Improved Delayed Detached Eddy Simulation (IDDES) for the same geometry showed a good correlation in front-to-rear downforce balance, but lift and drag were overpredicted relative to wind tunnel data. The current study compares the surface pressure distribution collected from a full-scale wind tunnel test on a Gen-6 NASCAR to the SAS and SRS predictions (both utilizing SST $k-\omega$ turbulence models). CFD simulations were performed with a finite-volume commercial CFD code, Star-CCM+ by Siemens, utilizing a high-resolution CAD model of the same vehicle. A direct comparison of the surface pressure distributions from the wind tunnel and CFD data clearly showed regions of high and low correlations. The associated flow features were studied to further explore the strengths and areas of improvement needed in the CFD predictions. While RANS was seen to be more accurate in terms of lift and drag, it was a result of the cancellation of positive and negative errors. Whereas IDDES overpredicted lift and drag and requires an order of magnitude more computational resources, it was able to capture the trend of surface pressure seen in the wind tunnel measurements. Full article