This study investigates the aerodynamic performance of a Formula One rear wing using computational fluid dynamics (CFD), with the primary aim of enhancing downforce generation while strictly maintaining overall aerodynamic efficiency. In high-performance motorsports, the rear wing plays a critical role in determining traction and cornering speeds, making its optimization essential for competitive advantage. A comprehensive three-dimensional rear wing model, encompassing the main plane, flap, and endplates, was meticulously developed and analyzed under steady incompressible turbulent flow conditions using advanced turbulence modeling. Key design parameters—such as the angle of attack, airfoil camber, flap gap dimensions, and endplate geometry—were systematically varied and optimized to identify the most effective aerodynamic configuration. The computational results indicate that the optimized wing configuration achieves a highly significant increase in downforce with only a marginal and moderate rise in aerodynamic drag, ultimately leading to a substantially improved lift-to-drag ratio. Detailed flow-field analysis reveals an enhanced surface pressure distribution, successfully delayed boundary layer flow separation, and significantly reduced tip vortex intensity. These aerodynamic improvements directly contribute to better vehicle stability, enhanced tire grip, and superior high-speed cornering performance on the track. Furthermore, the study demonstrates the profound effectiveness of multi-parameter aerodynamic optimization methodologies in motorsport engineering. The findings provide a robust theoretical and practical foundation for future research initiatives, particularly those involving complex full-vehicle aerodynamic coupling, transient flow simulations, and the application of advanced machine learning-based optimization techniques.
