As automotive headlamp serves Active Safety functions, it must comply the functional and performance requirements as per regulatory standards across various geographies like AIS (Automotive India Standards), FMVSS (Federal Motor Vehicle Safety Standards), ECE (Economic Commission of Europe) etc. The process of validating headlamp levelling compliance as per regulatory standards involves physical testing with various vehicle loading conditions. This traditional method is labor-intensive, time-consuming, and consumes significant resources. There is a need for a predictive solution that can simulate and validate headlamp levelling tests virtually, thereby reducing dependency on physical trials.
Headlamp levelling compliance is a critical regulatory requirement to ensure optimal visibility and safety under varying vehicle loading conditions. This paper presents an Artificial Intelligence and machine learning-based (AI/ML) solution to simulate headlamp levelling tests virtually/digitally by using historical headlamp designs from past vehicles. By leveraging historical test data and developing regression/machine learning models, the system predicts headlamp height and dipped beam height for both unladen and laden conditions. As these tests need to be complied at full vehicle level, the headlamp levelling outcome is highly influential on key vehicle parameters such as tire load, overhang, deflection, and reflector angle are used as input features. The AI/ML-based approach not only accelerates compliance validation but also enables sensitivity analysis and scalability for other automotive testing scenarios through integration with virtual simulation environments, aiming to reduce no of prototypes and testing time, cost and most importantly, time to market. The algorithm is trained using 80% of test data. The remaining 10% of test data is for validation and testing respectively, using the Bayesian regularization algorithm as a fair amount of correlation established with the physical test data with an accuracy of about 89%. From this work, we can predict the dipped beam height of the vehicle headlamp and finalizing the design specifications for achieving the regulatory requirement in absence of physical prototype vehicle, much ahead of vehicle development gateways.