GB/T10485 Optimization of Random Vibration Table Test for Automotive Signal Lighting

As exterior and functional safety components, automotive lights are subjected to vibration excitation from various factors during driving, including bumpy roads, uneven road surfaces, and wind. These excitation loads are not variable over time and are unpredictable, but they exhibit statistical patterns, generally referred to as random vibration.

Therefore, random vibration testing is necessary during the design process of automotive lights. This test method is used to assess the integrity of the lights under mechanical vibration loads over their service life. The most common failure mode of lights during testing is fatigue fracture.

Below, we will explore some test optimization methods for random vibration testing of automotive lights.

Test Equipment: Huanyi Instruments GB/T10485 Automotive Signal Lighting Random Vibration Table

Experimental Optimization Method:

1. Establish a finite element model of the lamp and perform modal analysis, then conduct modal tests using the lamp;

a. Simulation analysis includes: removing unnecessary geometric elements, establishing the connection relationships of the assembly structure, setting material properties and boundary conditions, mesh generation, and solution settings. Unnecessary geometric elements include chamfers and fillets. The connection relationships of the assembly structure refer to the connection relationships between each part and the lamp, where contact connections are selected between relatively moving parts, and binding connections are selected between relatively stationary parts.

b. Modal tests include: determining the boundary conditions and global coordinate system of the automotive lamp; the signal source is amplified and transmitted to the excitation device; the external excitation generated by the excitation device is transmitted to the lamp; the accelerometer generates acceleration on the lamp; the measurement degrees of freedom of the lamp and the number and direction of measurement points are determined, and the corresponding measurement point positions are marked; the measurement point signals and acceleration signals are processed by the signal acquisition and processing system, and the calculation results are output and displayed.

2. Compare the modal analysis results with the modal test results. The modal analysis and test results include modal frequencies, mode shape variations, and frequency response functions. Confirm the mode shapes and calibrate the finite element model;

3. Submit modal calculations based on the calibration results, complete the boundary condition settings, and perform random vibration simulation. Boundary condition settings include degree-of-freedom constraints, contact settings, and load application, which are simplified and parameterized according to actual working conditions;

4. Conduct random vibration tests on the luminaire using PSD power spectrum;

5. Compare the simulation results with the random vibration test results to confirm the model's reliability and correct the finite element model;

6. Identify hazardous areas based on vibration test and simulation results, verify risk points, and optimize the data structure; compare whether the hazardous area and the failure area are consistent. If they are consistent, adjust the safety factor and optimize the structure; if they are inconsistent, identify the model differences, adjust the finite element model, and re-simulate.

7. Modify the data based on the optimization results, verify the simulation results of random vibration of the new model, and conduct a vibration test re-test after confirming feasibility.

Method Summary:

This method calibrates the finite element simulation model of automotive lighting fixtures through modal testing, accurately simulating the vibration performance of automotive lighting fixtures under random excitation. It identifies critical stress areas through experiments and the established model, determines prominent influencing factors through sensitivity analysis, and optimizes the structure using a multi-objective optimization algorithm to achieve the optimal solution for both quality and performance. This approach aims to reduce the risk of lighting fixture vibration failure, significantly improve the vibration resistance of automotive lighting fixtures, and enhance simulation reliability.