Aerodynamic Optimization of Vehicle Configuration Based on Adjoint Method 2020-01-0915
Due to the increasingly stringent environmental regulations all around the world confronted by exhaust emission and energy consumption, improving fuel economy has been the top priority for most automotive manufacturers. In this context, the basic process for vehicle shape development has evolved into optimizing the design to achieve better aerodynamic characteristics, especially drag reduction. Of all the optimization approaches, the gradient-based adjoint method has currently received extensive attention for its high efficiency in calculating the objective sensitivity with respect to geometry parameters, which is the first and foremost step for subsequent shape modification.
In this work, the main goal is to explore the adjoint method through optimizing the vehicle shape for a lower drag based on a production SUV. Firstly, the influence of different mesh schemes was discussed on sensitivity prediction of aerodynamic drag. Secondly, according to the sensitivity distribution, several key areas, like the side mirrors, A pillars, air dam, and rear lamps, were respectively altered through mesh morphing process. Furthermore, the optimized effect was validated by steady as well as transient simulation. Steady Reynolds Averaged Navier Stokes (RANS) approach was used for the primal flow solution of adjoint calculations, while transient simulation with Stress Blended Eddy Simulation (SBES) was also performed on the baseline and the optimized vehicle for more detailed flow field structure. The overall drag reduction is approximately 8counts for steady result, and 10counts for unsteady solution. Finally, the drag reduction effect of the optimized side mirrors and air dam was correlated with full-scale wind tunnel test.
This paper evaluates the effectiveness of adjoint method for aerodynamic optimization of a production vehicle, which indicates more extensive and promising application of this approach in the early stage of vehicle development for its high efficiency as well as strong robustness.