Automated solar-focus risk assessment for automotive lighting

Solar focus effects occur when sunlight enters a vehicle’s headlamp at specific orientations, concentrating energy onto sensitive components and causing thermal damage or deformation. These events often arise when vehicles are parked on slopes or exposed to direct sunlight for extended periods. Detecting these solar focus events early in design is challenging. Realistic assessment requires sampling of many sun positions and vehicle attitudes, running high-fidelity optical simulations, and extracting peak irradiance values from large result sets. Manual post-processing of hundreds of simulation runs is time consuming.

This paper describes an automated workflow for solar-focus risk assessment that couples systematic angular sampling with parametric model control and automated result filtering. The approach treats the optical system as a parametric model and executes an angular sweep comparing sunlight position to vehicle orientation to capture the worst-case sunlight incident direction upon the vehicle's headlamp. Results are aggregated using statistical and spatial filtering to isolate persistently high-irradiance regions and to rank configurations by risk.

The method is explicitly designed to be adaptable. It supports different source representations, material models, and result export formats, and it can be coupled to thermal analysis for end-to-end virtual validation. By formalizing the sampling and post-processing steps, this workflow aims to provide designers and verification teams with a repeatable, and scalable process for mitigating solar-induced failure modes during optical system development.