Automotive shape optimization using the radial basis function model based on a parametric surface grid

By optimizing the aerodynamic shape parameters, the aerodynamic performance of the vehicle becomes better as the aerodynamic drag decreases. The driving stability also becomes better as the aerodynamic lift decreases. This research presents aerodynamic shape optimization which employs the multi-variable parametric model and the iterative optimal approach to reduce the aerodynamic drag and the aerodynamic lift. For aerodynamic studies with computational fluid dynamics simulations, a parametric surface grid model was used to morph and enhance the mesh quality by linear deformation of the exterior surfaces. This method employed the radial basis function model, and integrated optimization with multi-software provides excellent morphing ability and reasonable optimal designs. In this paper, the process of aerodynamic optimization for a vehicle body is divided into two phases. The first phase is two-dimensional body optimization aimed at a global search, and the second phase aims at a local approximation by running three-dimensional body optimization. The iterative optimal approach can optimize efficiently the aerodynamic characteristics with a reduction in the aerodynamic drag of 13.23% and a marked improvement in the aerodynamic lift. Sensitivity analysis of the design parameters demonstrated that the hood angle is the major factor in the aerodynamic drag coefficient C-D. For the aerodynamic lift coefficient C-L, the trunk lid angle is the major factor. In addition, the angle of the windshield and the angle of the side window have small influences on C-L. The results obtained are accurate reference values for application in automotive engineering.