Prediction of Aerodynamic Drag in SUVs with Different Specifications by Using Large-Eddy Simulations

Emission regulations are becoming more stringent, as global temperature continues to rise due to the increasing greenhouse gases in the atmosphere. Battery electric vehicles (BEV), which have zero tailpipe emissions, are expected to become widespread to solve this problem. As the powertrain of BEV is more efficient than conventional powered vehicles, the proportion of energy loss during driving due to aerodynamic drag becomes greater. Therefore, reducing aerodynamic drag for improved energy efficiency is important to extend the pure electric range. At Honda, Computational Fluid Dynamics (CFD) and wind tunnel testing are used to optimize vehicle shape and reduce aerodynamic drag. Highly accurate CFD is essential to efficiently guide the development process towards reducing aerodynamic drag. Specifically, the prediction accuracy for the exterior shape, underfloor devices, tires, and wheels must meet development requirements. In this paper, we used the CPU-based moving mesh version of “Fidelity CharLES”, hereafter called “the moving solver”, to calculate aerodynamic drag of SUVs with different shapes and specifications, and compared them with vehicle’s test measurements conducted at Honda’s 5-belt wind tunnel facility. The comparison indicates a good agreement between CFD and test measurements. In particular, the moving solver can predict which configuration yields superior aerodynamic performance given different tire profiles and wheel designs. This was difficult to solve using previous CFD techniques due to the complex flow fields around moving objects and their effects on overall air flow of the vehicle. Furthermore, the moving solver can successfully reproduce the flow field of the test results, such as the wake at the side and behind the vehicle. Calculation times also meet production requirements for the aerodynamic development process.