Fogging (i.e. condensation of water vapor) in headlamps in severe weather conditions present both a performance and potential safety concern for automotive companies. Conventional headlamps are based on incandescent bulbs. In recent times, LED lighting has increasingly become the norm. However, LED based headlamps are prone to higher levels of fogging because they inherently produce less heat than the conventional incandescent or halogen bulbs. A headlamp design must be able to dispose all the formed condensate/fog in a fixed time even under severe thermal conditions. It is of great importance for the car manufacturer to be able to simulate the risk of condensation early in the design stage with an eye on the overall cost reduction. The combined use of experimental studies and numerical modelling is important to optimize headlamp design and to produce high-performance headlamps. Most of the available literature on headlamp defogging simulation is based, primarily, on 2D geometries with simplified physics. However, in reality, the flow and thermal field inside of a headlamp assembly is highly complicated, encompassing conduction, convection, radiation, phase change and varying ambient conditions.
This paper presents an overview of experimental and numerical investigations of the defogging process in an automotive headlamp. In this study, the Eulerian Wall Film (EWF) approach is implemented on a three-dimensional geometry to capture the underlying physics governing the defogging phenomenon inside the headlamp. Lab test observations indicate that the numerical predictions closely agree with the experimental data. Moreover, this study includes simulations on headlamp defogging characterization for different kinds of lens materials. Lenses made of glass and polycarbonate are considered in the analysis to quantify the impact of these materials on defogging performance, thus, enabling the selection of an appropriate lens material in terms of cost and performance with reduced developmental cycle time. The validated numerical prediction method can be used to study the risk of condensation and the required defogging early in the design stage.