Use of an Eulerian/Lagrangian Framework to Improve the Air Intake System of an Automobile with Respect to Snow Ingress

A simulation approach to predict the amount of snow which is penetrating into the air filter of the vehicle’s engine is important for the automotive industry. The objective of our work was to predict the snow ingress based on an Eulerian/Lagrangian approach within a commercial CFD-software and to compare the simulation results to measurements in order to confirm our simulation approach. An additional objective was to use the simulation approach to improve the air intake system of an automobile. The measurements were performed on two test sites. On the one hand we made measurements on a natural test area in Sweden to reproduce real driving scenarios and thereby confirm our simulation approach. On the other hand the simulation results of the improved air intake system were compared to measurements, which were carried out in a climatic wind tunnel in Stuttgart. An estimation of the snow particle size and the snow mass flux on the two test sites was measured by a Snow Particle Counter (SPC). Our investigation shows that an Eulerian/Lagrangian approach can be used to predict the snow ingress. By using snow properties from the test sites as well as from literature, we observed a good agreement between the simulation results and the experiments. Our results also show that it is possible to improve the air intake system by using an Eulerian/Lagrangian framework. However, there are limitations due to the model applied for the particle-wall interactions and due to the fact that the snow particle density and especially the snow particle shape are not known from the test area.