Adaptive Freeform Optics Design and Multi-Objective Genetic Optimization for Energy-Efficient Automotive LED Headlights

In addressing the design imperatives of automotive headlight miniaturization and energy conservation, this paper puts forth a design methodology for vehicle lighting systems that is predicated on free surface optics and an intelligent optimization algorithm. The establishment of the energy mapping relationship between the light source surface and the target surface is predicated on relevant performance standards. The numerical calculation is then integrated with MATLAB R2022a to obtain the free-form surface coordinate points and establish a three-dimensional model. To optimize the parameter design, a genetic algorithm is employed to fine-tune the design parameter θmax, thereby attaining the optimal θmax that strikes a balance between volume and luminous efficiency. The experimental results demonstrate that by integrating the optimal incidence angle into the design of the high beam and low beam, the final simulation results show that the optical efficiency of the low beam is 88.89%, and the optical efficiency of the high beam is 89.40%. This enables the automotive headlamp system to achieve a balance between volume and luminous efficiency. The free-form lamp design framework proposed in this study provides a reference for the compact design and intelligent optimization of the lamp system.