In order to achieve the purpose of saving energy and reducing emission, the improvement of aerodynamic performance plays an increasingly crucial role for car manufacturers. Previous studies have confirmed the validity of gradient-based adjoint algorithm for its high efficiency in shape optimization. In this paper, two important aspects of adjoint approach were explored. One is vehicle aerodynamic optimization with multiple objectives, and the other is using time-averaged flow results as the primal solution, both are issues of high interest in recent applications.
First, adjoint shape optimization with steady-state and time-averaged flow simulations were respectively calculated and comparatively discussed based on a production SUV. The shape modifications of the two cases indicated that the impact of primal solution on design change could not be neglected, due to the different intrinsic codes of steady and transient turbulence models. Moreover, multi-objective optimization of reducing both drag and lift was carried out. Given the fact that the objective functions are usually conflicting with each other, it’s quite challenging to find the global optimal solution. But with appropriate parameter setting, a reasonable trade-off was finally achieved that total CD lowered by 8 counts and CL by 11 counts, which is beneficial for fuel economy as well as driving stability. In addition, the current difficulties existed in vehicle aerodynamic optimization were also proposed, serving as a guidance for further researches.
Results in this paper suggest that adjoint approach, with a long application history in a variety of disciplines and fields such as aeronautics, geography and turbomachinery, definitely will get a more promising and extensive utilization in automotive industry in the near future.