New CO2 targets require innovative solutions to achieve safety and comfort at low emission rates. This poses new engineering challenges such as detecting and resolving potential hazards. For conventional cars, water is a hazard as it can hinder an engine’s combustion process by impeding airflow. For electric cars, safety is impacted by pressure forces exceeded on the underbody, endangering battery packs of an electric car when driving through deep water.
With PreonLab, you can simulate wading through arbitrary depths of water in a controlled virtual environment. You don’t need to have the physical prototype and a wading channel. You don’t need to mount dozens of cameras to get minimal information. You don’t need to rely on a complicated and sensitive sensor setup for measurements. PreonLab accounts for all parts of the car; even the suspension. You can gain loads of insight by doing a full wetting analysis, measuring the flooding height, predicting underbody forces, measuring flow rates and understanding the flow path. PreonLab gives you the tools to quickly learn how your designs perform in whatever metric you’re interested in.
In wading simulations, the precise modelling of the car movement becomes increasingly important the faster the car moves or with increasing water level in the wading channel. The position, orientation and velocity of the car when hitting the water pool determine the wave pattern in front of the car and whether or not water flows across the engine hood or not. Considering the latter, the profiles of springs and dampers play an important role. In PreonLab you can easily define a model for the car suspension and get higher accuracy and reliability.
For Volvo Cars, Johann Idoffsson had worked on an evaluation of PreonLab for the simulation of water wading scenarios. The comparison has been made not only between PreonLab and the previous toolchain based on a grid-based CFD method but also between the virtual water wading results from PreonLab with the real-world test bed.
Even though only having the limited time of a Master Thesis, the ease-of-use of PreonLab enabled them to set up a sophisticated model even including a model of the car suspension in many different variants taking a GPS velocity profile as a boundary condition.