Sustainable aerodynamic optimization of an SUV: a combined experimental and numerical approach

This study investigates the CFD-based aerodynamic parametric analysis of an SUV by integrating computational fluid dynamics (CFD) simulations with scaled wind–tunnel experiments. Although previous studies have analysed SUV aerodynamics using either numerical or experimental methods, few have systematically validated CFD predictions with experimental data. The present work bridges this gap by correlating CFD and experimental results to assess the effects of windshield angle, diffuser angle, and underbody deflectors on drag and lift performance. Steady-state simulations is conducted in ANSYS Fluent 2023 R1 over a velocity range of 60–110 km/h (Re ≈ 1.1 × 106–2.0 × 106) with a turbulence intensity of 1.5%, validated against 1:12-scale wind–tunnel measurements. The validated CFD model reproduced experimental trends with deviations below 10%. Results show a non-monotonic variation of drag coefficient with velocity, attributed to wake–reattachment phenomena and improved pressure recovery at intermediate speeds. The optimal configuration—featuring a 40° windshield and 13° diffuser—achieved an 18.2% drag reduction relative to the baseline model. The study demonstrates that validated CFD analysis can reliably predict SUV aerodynamic performance, providing a robust foundation for geometry-based drag-reduction strategies and future multivariate optimization.