Numerical Investigations of the Dust Deposition Behavior at Light
Commercial Vehicles 2023-01-5022
Dry dust testing of vehicles on unpaved dust roads plays a crucial role in the
development process of automotive manufacturers. One of the central aspects of
the test procedure is ensuring the functionality of locking systems in the case
of dust ingress and keeping the dust below a certain concentration level inside
the vehicle. Another aspect is the customer comfort because of dust deposited on
the surface of the car body. This also poses a safety risk to customers when the
dust settles on safety-critical parts such as windshields and obstructs the
driver’s view. Dust deposition on sensors is also safety critical and is
becoming more important because of the increasing amount of sensors for
autonomous driving. Nowadays, dust tests are conducted experimentally at dust
proving grounds. To gain early insights and avoid costly physical testing,
numerical simulations are considered a promising approach.
Simulations of vehicle contamination by dry dust have been studied in the past.
However, they lack detailed tire resuspension models, and none of the
publications focus on the dust deposition at the vehicle in detail, such as door
gaps and locks. Moreover, the emphasis of many authors is the environmental
impact of vehicles resulting from non-exhaust emissions, such as tire and road
wear, brake wear, and dust emissions.
This paper introduces a novel method for simulating the production of dust
resulting from vehicles driving on a dry and dusty, unpaved road, as well as the
subsequent deposition mechanisms that occur within door gaps and locks. To
achieve this, both a basic, generic vehicle model and a more complex, detailed
model of a Volkswagen (VW) Caddy are used in the context of a multiphase
computational fluid dynamics (CFD) simulation with Lagrangian particles.
Citation: Yigci, I., Strohbücker, V., and Schatz, M., "Numerical Investigations of the Dust Deposition Behavior at Light Commercial Vehicles," SAE Technical Paper 2023-01-5022, 2023, https://doi.org/10.4271/2023-01-5022. Download Citation
Author(s):
Ibrahim Yigci, Veith Strohbücker, Markus Schatz