Aerodynamic simulation on roof-mounted intelligent awareness system of intelligent vehicle

With the rapid development of intelligent driving technology, it is urgent to conduct research on the distribution and motion characteristics of snow particles in the area of the intelligent vehicle awareness system under harsh snow and wind conditions. In this paper, the Unsteady Reynolds-Averaged Navier-Stokes (URANS) was first used to conduct 1:12 scaled aerodynamic simulation of the intelligent vehicle. It is found that the error of aerodynamic drag coefficient between simulation and test is 5.6%, indicating that the current numerical simulation model can predict the aerodynamic characteristics of intelligent vehicle accurately. Based on this, URANS was used coupled with Lagrangian Multiphase Model (LMP) to investigate the snow accumulation near the roof-mounted intelligent awareness system under different vehicle speeds and snowfall intensities. The study found that with the increase of snowfall intensity from moderate to heavy and vehicle speed at 40 km/h, the incidence of snow particles on various components significantly increases, and the number of adhered particles also increased accordingly. The particle adhesion rate of the awareness system has decreased by 1.24%, while the number of adhered snow particles increased significantly at the back of the roof-mounted intelligent awareness system and the wake window. Under moderate snow condition, as the vehicle speed increased from 40 to 60 km/h, the number of incident particles and adhered particles in the awareness system have significantly decreased by 24,592 and 317,019, respectively, but the particle adhesion rate has increased by a significant 2.88%. Compared to the same snowfall intensity but low speed, the range of particle distribution is significantly reduced and more scattered.