Virtual real-time prediction of sensor soiling
Sensors are absolutely crucial for active safety, driver support systems and self-driving vehicles and must be placed so that any contamination is as mild and slow as possible. In order to be able to do this at an early stage, efficient simulation models are needed. In this project, we will use the recurrence computational fluid dynamics (rCFD) technique to construct such models. We will develop an experimentally validated rCFD solver for virtual real-time prediction of sensor soiling for vehicle applications.
The project results can be summarized as: 1) A validated rCFD methodology (solver and associated working methods) for virtual real-time prediction of sensor soiling; 2) Knowledge of differences and similarities between different contaminants in terms of soiling of realistic vehicle bodies; 3) General guidelines for sensor positioning based on rCFD simulations. The developed methodology will be ready to be applied in advanced technical development projects in the near future after the project is finalized.
Henrik Ström (contact)
Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics
China-Euro Vehicle Technology (CEVT) AB
Project ID: 2021-05061
Funding Chalmers participation during 2022–2025