Method for optimizing vibration performance of automobile lamp

Abstract

The invention discloses an optimization method for vibration performance of an automobile lamp. The optimization method comprises the following steps: S101, establishing a finite element model of the lamp and performing modal analysis; and S102, carrying out a modal test by using the lamp. And S103, comparing a modal analysis result in the step S101 with a modal test result in the step S102, confirming a vibration mode and calibrating the finite element model. And S104, submitting modal calculation according to a calibration result, completing boundary condition setting, and performing random vibration simulation. And S105, carrying out a random vibration test on the lamp by using the PSD power spectrum. And S106, comparing a random vibration simulation result in the step S104 with a random vibration test result in the step S105, confirming the reliability of the model and correcting the finite element model. And S107, determining a dangerous area according to a vibration test result and a vibration simulation result, and checking a risk point optimization data structure. And S108, modifying data according to an optimization result, verifying a random vibration simulation result of the new model, and performing vibration test retest after confirming feasibility.

Description

Technical Field

[0001] This invention relates to the field of automotive lighting design, and more particularly to a method for optimizing the vibration performance of automotive lighting. Background Technology

[0002] Automotive lighting fixtures typically require random vibration testing during the design process. This testing method is used to evaluate the integrity of the fixtures under mechanical vibration loads over their service life. The most common failure mode of lighting fixtures during testing is fatigue fracture. After failure, the injection mold needs to be modified and optimized, which results in an expensive and time-consuming design cycle.

[0003] As exterior and functional safety components, automotive lights are typically subjected to vibration excitation from various factors such as bumpy roads, uneven road surfaces, and wind during driving. These excitation loads do not change over time and cannot be determined, but they exhibit statistical regularity and are generally referred to as random vibration.

[0004] To address the impact of complex environments on the mechanical properties of structures, random vibration simulations are conducted during the design phase to reduce stress concentration and deformation of the luminaires, preventing damage. For prototypes after mold opening, broadband random vibration tests at various frequencies are typically used to simulate the random vibration of the parts. The stress concentration range is determined by the performance after vibration, ensuring that the parts will not suffer damage or failure during subsequent use. However, since the vibration simulation model is based on an ideal design, assembly errors of the luminaire itself, fastener preload, etc., will all affect the actual model. If the influence of these errors is not considered, the numerical simulation results will deviate from the actual vibration test results.

[0005] The design of automotive lighting fixtures precedes the manufacturing of parts. Numerical simulation can effectively verify the performance and design of products, but some problems still need to be solved for the prototype lighting fixtures after physical prototyping:

[0006] First, there are assembly differences between the 3D model and the actual sample.

[0007] Second, the simulation model is based on an ideal structure, has not been verified, and the assembly relationship is defined too simply, making it unable to accurately simulate the performance of the parts.

[0008] Third, actual random vibration tests simulate the service life of automotive lights, and failures are mostly fatigue fractures or frictional powdering, which are difficult for simulation models to simulate in real failure modes.

[0009] Fourth, after the vibration test fails, the weak points of the structure cannot be accurately identified, resulting in low effectiveness and long cycle of rectification.

[0010] The aforementioned technical issues can lead to significant structural changes and low simulation reliability during the development of automotive lighting systems. Ultimately, the results need to be verified and optimized through rounds of testing, which not only fails to demonstrate the value of simulation but also results in resource consumption and waste. Summary of the Invention

[0011] This invention aims to provide a method for optimizing the vibration performance of automotive lighting fixtures, which involves three aspects: random vibration, finite element analysis, and optimization design.

[0012] Vibration analysis can be divided into two dimensions: the time domain and the frequency domain. The relationship between the time domain and the frequency domain can be derived through Fourier transform. The amplitude and phase of random vibration change with time and are unpredictable. The amplitude, frequency, and phase parameters commonly used in the time domain analysis of vibration measurements cannot fully describe the characteristics of random vibration. Random vibration is defined and characterized by the spectrum of the power spectral density (PSD) or acceleration spectral density (ASD) and power spectral density within the relevant frequency range.

[0013] The finite element method (FEM) can decompose complex structures into a finite number of small elements, and then calculate the stress and strain distribution of the structure numerically. Structural design and optimization are common problems in engineering applications, involving multiple interrelated factors, including material parameters, external loads, and environmental conditions. Identifying key factors and optimizing the structure is crucial for balancing performance and cost.

[0014] Numerical simulation is an effective method for verifying structural designs. Improving the accuracy of numerical simulation models can not only save a lot of time and resources, but also ensure the overall performance and reliability of automotive lighting.

[0015] Optimization design is based on reliable simulation and experimental results. By identifying key influencing factors and determining input variables, various optimization algorithms are used to improve the structure, while more accurately predicting structural performance and improving efficiency.

[0016] To overcome the above-mentioned technical problems, the present invention provides a method for optimizing the vibration performance of automotive lighting fixtures, comprising the following steps:

[0017] Step S101: Establish a finite element model of the lamp and perform modal analysis;

[0018] Step S102: Conduct modal testing using lamps;

[0019] Step S103: Compare the modal analysis results of step S101 with the modal test results of step S102 to confirm the mode shape and calibrate the finite element model;

[0020] Step S104: Submit modal calculations based on the calibration results, complete the boundary condition settings, and perform random vibration simulation;

[0021] Step S105: Conduct random vibration tests on the luminaire using PSD power spectrum;

[0022] Step S106: Compare the simulation results of random vibration in step S104 with the results of random vibration test in step S105 to confirm the reliability of the model and correct the finite element model.

[0023] Step S107: Based on the vibration test results and vibration simulation results, identify the hazardous area, verify the risk points, and optimize the data structure;

[0024] Step S108: Modify the data based on the optimization results, verify the simulation results of random vibration of the new model, and conduct a vibration test after confirming the feasibility.

[0025] Furthermore, the simulation analysis in step S101 includes: cleaning up unnecessary geometric elements, establishing the connection relationship of the assembly structure, setting material properties and boundary conditions, and mesh generation and solution settings.

[0026] Furthermore, non-essential geometric elements include chamfers and fillets. The connection relationship of the assembly structure is the connection relationship between each part and the lamp, wherein relatively moving parts are selected for contact connection, and relatively stationary parts are selected for binding connection.

[0027] Furthermore, before step S102, the modal testing environment is set up and the data acquisition equipment is calibrated.

[0028] Furthermore, the modal test in step S102 includes: determining the boundary conditions and global coordinate system of the automotive lamp; the signal source is transmitted to the excitation device after passing through the power amplifier; the external excitation generated by the excitation device is transmitted to the lamp; the accelerometer generates acceleration on the lamp; determining the measurement degrees of freedom of the lamp and the number and direction of the measurement points, and marking the corresponding measurement point positions; after the measurement point signals and acceleration signals are processed by the signal acquisition and processing system, the calculation results are output and displayed.

[0029] Furthermore, the modal analysis results and experimental results in step S103 include modal frequencies, modal shape changes, and frequency response functions.

[0030] Furthermore, the boundary condition setting in step S104 includes degree of freedom limitation, contact setting, and load application, which are simplified and parameterized according to the actual working conditions.

[0031] Furthermore, step S105 completes the random vibration test through the entire life cycle.

[0032] Furthermore, step S106 includes comparing whether the dangerous area and the failure area are consistent. If they are consistent, the safety factor is adjusted and the structure is optimized. If they are inconsistent, the model difference points need to be identified and the finite element model is adjusted before resimulating.

[0033] Furthermore, step S107 includes identifying key factors through sensitivity analysis, identifying design variables and objective functions, using the critical boundary size as the design variable, setting mass and maximum stress as objective functions while ensuring lightweight and reliability, and using a multi-objective optimization algorithm to obtain the Pareto optimal solution.

[0034] Furthermore, after step S108, the simulation results of random vibration are compared with the results of the vibration test. If failure exists, vibration optimization is performed again according to the failure mode and region. If the test results are qualified, the optimization method ends.

[0035] The main beneficial effects of this invention are: by calibrating the finite element simulation model of the lamp through modal testing, the vibration performance of the automotive lamp under random excitation is accurately simulated; the dangerous stress area is determined through experiments and the established model; the prominent influencing factors are identified through sensitivity analysis; and the structure is optimized by using a multi-objective optimization algorithm to achieve the optimal solution for quality and performance. This ensures cost savings while reducing the risk of lamp vibration failure, significantly improves the vibration resistance of automotive lamps, and enhances simulation reliability. Attached Figure Description

[0036] Figure 1 This is a flowchart of the first part of the method for optimizing the vibration performance of automotive lighting fixtures in this invention;

[0037] Figure 2 This is a flowchart of the second part of the method for optimizing the vibration performance of automotive lighting fixtures in this invention;

[0038] Figure 3 This is a flowchart of the modal analysis in step S101 of the present invention;

[0039] Figure 4 This is a schematic diagram of the modal testing system in step S102 of the present invention;

[0040] Figure 5 This is a flowchart of the random vibration optimization process in this invention. Detailed Implementation

[0041] The measurement method based on finite element technology described in this invention will be further explained and described below with reference to the accompanying drawings and specific embodiments. However, this explanation and description do not constitute an undue limitation on the technical solution of this invention.

[0042] refer to Figure 1 and combined Figure 2 , Figure 1 and Figure 2 The method for optimizing the vibration performance of automotive lamps in this invention includes the following steps: Step S101, establishing a finite element model of the lamp and then performing simulation analysis;

[0043] Step S102: Conduct modal testing using lamps;

[0044] Step S103: Compare the simulation results of step S101 with the modal test results of step S102 to confirm the mode shape and calibrate the finite element model.

[0045] Step S104: Submit simulation calculations based on calibration results, complete boundary condition settings, and perform random vibration simulation;

[0046] Step S105: Conduct random vibration tests on the luminaire using PSD power spectrum;

[0047] Step S106: Compare the simulation results of step S104 with the experimental results of step S105 to confirm the reliability of the model and correct the finite element model.

[0048] Step S107: Based on the vibration test results and vibration simulation results, identify the hazardous area, verify the risk points, and optimize the data structure;

[0049] Step S108: Verify the results of the random vibration simulation of the new model based on the optimization results, and conduct a vibration test retest.

[0050] Continue to refer to Figure 3 , Figure 3 This is a flowchart of the modal analysis in step S101 of the present invention;

[0051] Importing the 3D model: First, import the 3D model into the finite element software. Finite element analysis software includes, but is not limited to, ANSYS, Abaqus, Nastran, Hyperworks, etc., to create the finite element model and perform modal analysis.

[0052] Geometry cleanup: This includes removing unnecessary chamfers, fillets, etc. After saving the 3D model as a STEP format, import it into preprocessing software (such as Hypermesh, ANSA, etc.) to check the structure and perform geometry cleanup.

[0053] Establish assembly structure connection relationships: In 3D design software, confirm the overall assembly relationship of the lamp, analyze the relative motion relationship of the parts, establish the connection relationship between each part and the structure, select contact connection between parts with relative motion, and use binding connection between relatively stationary parts (such as welding, hot riveting, hot stamping and other process structures).

[0054] Material properties and boundary conditions settings: Set the material properties for different parts, including elastic modulus, shear modulus, density, Poisson's ratio, and damping ratio. Note that non-elastic parts require the selection of the appropriate material model. Set boundary conditions (constrained boundaries and free boundaries) according to the actual operating conditions of the lighting fixture.

[0055] Mesh generation and solution settings: The established model is meshed. The quality and quantity of the mesh are key to the accuracy and efficiency of numerical simulation. To reduce mesh iteration error, the Jacobian Ratio is checked after meshing. The closer the value is to 1, the better the mesh quality. The fully configured model is then submitted for calculation to solve for the first 10 modal frequencies.

[0056] refer to Figure 4 , Figure 4 This is a schematic diagram of the modal testing system in step S102 of the present invention;

[0057] The modal test in step S102 includes: determining the boundary conditions and global coordinate system of the automotive lighting fixture, using the determined parameters as a signal source, and transmitting the signal source to the excitation device after passing through a power amplifier. Figure 4 The hammer or vibrator is one of the excitation devices to be selected. The external excitation generated by the excitation device is transmitted to the automotive lamps, and the accelerometer generates acceleration on the automotive lamps. The measurement degrees of freedom of the automotive lamps and the number and direction of the measurement points are determined, and the corresponding measurement point positions are marked. After the measurement point signals and acceleration signals are processed by the signal acquisition and processing system, the calculation results are displayed.

[0058] During modal testing, the signal is filtered by the system to determine a reasonable sampling frequency and sampling duration. The required data is collected and checked. Modal analysis is then performed on the measured data. For a structurally damped vibration system, the differential equation of motion for an n-degree-of-freedom vibration system can be expressed as:

[0059]

[0060] Where [M], [C], and [K] are the mass, damping, and stiffness matrices, respectively, and the transfer function is defined as the ratio of the Laplace transform of the output to the Laplace transform of the input. The initial conditions are all 0.

[0061]

[0062] In the formula, S = σ + jω. For a steady-state linear system, S = jω

[0063]

[0064] When the phase σ = 0, the transfer function is called the frequency response function. The frequency response function H(S) is obtained through modal testing. Modal identification extracts modal parameters, including the modal frequencies {ω}. d}、Modal modes and damping{C}.

[0065] refer to Figure 5 , Figure 5 This is a schematic diagram of the vibration optimization method in this invention. The critical boundary is identified based on the results calculated from random vibration tests and simulations. Then, sensitivity analysis is used to identify key factors, thereby determining the design variables and objective function. Structural optimization design is then performed. The structural design typically uses the critical boundary dimensions as the design variable. Under the premise of ensuring lightweight and reliability, mass and maximum stress are set as objective functions, and a multi-objective optimization algorithm is used to obtain the Pareto optimal solution.

[0066] When the objective function of a multi-objective optimization is to minimize the objective function and the constraint functions are inequalities, the mathematical form of the standard multi-objective optimization model is min F(X)=[f1(x),f2(x)]. T

[0067] stg i (x)≤0,i=1,2,…,p

[0068] In the formula, f1(x) and f2(x) are the objective functions of the lamp mass and the maximum stress, and x = [x1, x2, ..., x]. n T represents an n-dimensional design variable, namely the structural dimensions of the lighting fixture components, and g i (x) is the constraint function, that is, the design requirements that the objective function needs to meet. In this invention, it is set to ensure that there is no interference in the matching of parts and that the first-order modal frequency of the lamp is greater than 32Hz.

[0069] The optimization method described in step S106 of this invention involves a multi-objective optimization problem, whose solutions are typically a set of non-dominated solutions, called the Pareto solution set. When multiple Pareto optimal solutions exist, the goal of multi-objective optimization is to find a set of solutions that are closest to the true Pareto optimal solution. The main algorithms for solving Pareto front solutions fall into two categories: mathematical programming methods and genetic algorithms. Among these, the NSGA-II (Elitist Non-Dominated Sorting Genetic Algorithm) algorithm is the most widely used multi-objective genetic algorithm.

[0070] This invention uses a genetic algorithm to converge the objective function to an optimal solution that yields the best quality and performance. The optimization process in step S106 is performed using the multi-parameter, multi-disciplinary optimization tool software Isight. By modifying the dimensions of the 3D model created in the 3D software, and calling finite element software for calculation, a multi-platform optimization system is constructed.

[0071] The errors in the finite element modal analysis results in step S101 include model errors, mesh errors, and assembly errors. Specifically, the model errors for automotive lighting fixtures include both structural and material parameter errors. Structural errors mainly stem from simplified features such as bolt holes, fillets, and chamfers. Material parameters are related to the injection molding process and surface treatment of the parts. Mesh errors include mesh accuracy, mesh quantity, and stress singularities caused by sharp-cornered meshes. Assembly errors include assembly relationships in the structure that cannot be reproduced through a numerical model, such as sealant, welding, and riveting. Furthermore, the simulation results need to be evaluated to determine whether the errors are caused by software calculations.

[0072] The purpose of step S103 is to cross-validate the experimental results of step S102 with the simulation analysis results of step S101. Since there are errors in finite element calculations, in order to obtain a more accurate numerical model, the material parameters, structural simplification methods, mesh accuracy, etc. are adjusted based on the experimental results to establish a more accurate model, providing a reliable simulation basis for structural optimization and applying it to the prediction of system dynamic characteristics.

[0073] Step S104 involves comparing and adjusting the model according to step S103, performing finite element calculations, setting boundary conditions based on the modal calculation results, defining the input random vibration acceleration power spectral density, conducting random vibration simulations, determining whether the natural frequencies of the lamps meet the requirements, and verifying the maximum stress in the hazardous area based on the allowable stress of the material. The spectrum of a random signal is random, but the power spectrum remains constant. By definition, the power spectrum is the statistical average of the squared function of the amplitude spectrum.

[0074] In the formula, X T (ω) is the Fourier transform of the signal x(t) in the time interval [T, -T]. Therefore, random vibrations are usually loaded in the form of power spectral density, which results in randomness when converted into a time-domain signal. The 3σ criterion is usually used for verification.

[0075] When examining the vibration life performance of automotive lighting under applied loads using random vibration processes, fatigue strength should be considered when checking hazardous areas. Fatigue strength is determined by local stress state and material properties. However, fatigue defects are difficult to reproduce in finite element simulations. Stress concentration areas are often predicted using the finite element method. In areas with stress concentration, the safety factor should be appropriately increased to avoid stress accumulation that could lead to component failure.

[0076] The purpose of step S105 is to verify the vibration reliability of the prototype part. By simulating the complete life cycle of the lamp through random vibration test, it is ensured that the mechanical structure of the automotive lamp will not be affected by vibration excitation such as bumpy roads, uneven road surface vibration, and wind force during driving. If the test fails, it is necessary to analyze and optimize the failure area and test form.

[0077] If the random vibration test fails in step S106, the failure mode is confirmed, such as powder discharge, fracture, interference, etc., and compared with the random vibration simulation results. The dangerous area and the failure area are compared. If they are consistent, the safety factor needs to be adjusted and the structure optimized. If they are inconsistent, the model difference points need to be confirmed and the finite element model needs to be adjusted and re-simulated.

[0078] Step S108: Modify the three-dimensional data according to the optimization results, verify the random vibration simulation results of the new model, and conduct a vibration test after confirming the feasibility of the mold. Continue to compare the test and simulation results. If there is still breakage or powder discharge, the vibration optimization process needs to be carried out again according to the failure mode and area. If the test results are qualified, the complete vibration optimization process is completed.

[0079] In summary, this invention optimizes the performance of automotive lighting fixtures based on modal theory, finite element method, and multi-objective optimization algorithm, aiming to ensure that the mechanical structure of automotive lighting fixture parts will not suffer damage during their life cycle.

[0080] It should be noted that the prior art portion of the protection scope of this invention is not limited to the embodiments given in this application. All prior art that does not contradict the solution of this invention, including but not limited to prior patent documents, prior publications, prior public uses, etc., can be included in the protection scope of this invention.

[0081] Furthermore, the combination of the technical features in this case is not limited to the combination methods described in the claims of this case or the combination methods described in the specific embodiments. All technical features described in this case can be freely combined or combined in any way, unless they contradict each other.

[0082] It should also be noted that the embodiments listed above are merely specific embodiments of the present invention. Obviously, the present invention is not limited to the above embodiments, and similar changes or modifications made thereto are those that can be directly derived or easily conceived by those skilled in the art from the content disclosed in the present invention, and should all fall within the protection scope of the present invention.

Claims

1. A method for optimizing the vibration performance of automotive lighting fixtures, characterized in that, Includes the following steps: Step S101: Establish a finite element model of the lamp and perform modal analysis; Step S102: Conduct modal testing using lamps; Step S103: Compare the modal analysis results of step S101 with the modal test results of step S102 to confirm the mode shape and calibrate the finite element model; Step S104: Submit modal calculations based on the calibration results, complete the boundary condition settings, and perform random vibration simulation; Step S105: Conduct random vibration tests on the luminaire using PSD power spectrum; Step S106: Compare the simulation results of random vibration in step S104 with the results of random vibration test in step S105 to confirm the reliability of the model and correct the finite element model. Step S107: Based on the vibration test results and vibration simulation results, identify the hazardous area, verify the risk points, and optimize the data structure; Step S108: Modify the data based on the optimization results, verify the simulation results of random vibration of the new model, and conduct a vibration test after confirming the feasibility.

2. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 1, characterized in that, The simulation analysis in step S101 includes: cleaning up unnecessary geometric elements, establishing the connection relationship of the assembly structure, setting material properties and boundary conditions, and mesh generation and solution settings.

3. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 2, characterized in that, The non-essential geometric elements include chamfers and fillets. The connection relationship of the assembly structure is the connection relationship between each part and the lamp, wherein relatively moving parts are selected for contact connection, and relatively stationary parts are selected for binding connection.

4. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 1, characterized in that, Before step S102, the modal test environment is set up and the data acquisition equipment is calibrated.

5. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 4, characterized in that, The modal test in step S102 includes: determining the boundary conditions and global coordinate system of the automotive lamp; the signal source is transmitted to the excitation device after passing through the power amplifier; the external excitation generated by the excitation device is transmitted to the lamp; the accelerometer generates acceleration on the lamp; determining the measurement degrees of freedom of the lamp and the number and direction of the measurement points, and marking the corresponding measurement point positions; after the measurement point signals and acceleration signals are processed by the signal acquisition and processing system, the calculation results are output and displayed.

6. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 1, characterized in that, The modal analysis results and experimental results in step S103 include modal frequencies, modal shape changes, and frequency response functions.

7. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 1, characterized in that, The boundary condition setting in step S104 includes degree of freedom limitation, contact setting, and load application, which are simplified and parameterized according to the actual working conditions.

8. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 1, characterized in that, Step S105 involves completing the random vibration test over the entire life cycle.

9. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 1, characterized in that, Step S106 includes comparing whether the dangerous area and the failure area are consistent. If they are consistent, the safety factor is adjusted and the structure is optimized. If they are inconsistent, the model difference points need to be identified and the finite element model is adjusted before resimulating.

10. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 1, characterized in that, Step S107 includes identifying key factors through sensitivity analysis, identifying design variables and objective functions, using the critical boundary size as the design variable, setting mass and maximum stress as objective functions while ensuring lightweight and reliability, and using a multi-objective optimization algorithm to obtain the Pareto optimal solution.

11. The method for optimizing the vibration performance of automotive lighting fixtures as described in claim 1, characterized in that, After step S108, continue to compare the simulation results of random vibration with the results of vibration test retest. If failure exists, re-optimize the vibration according to the failure mode and region; if the test results are qualified, the optimization method ends.

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