Durability prediction method, device and equipment of automobile front wall outer plate and medium

Abstract

The invention discloses a durability prediction method, device and equipment for an automobile front wall outer panel and a medium, and the method comprises the steps: carrying out the finite element modeling and rigid mechanical modeling of a target automobile structure and the front wall outer panel, performing modal calculation and flexibility processing on the front wall outer plate based on a vibration signal of a target automobile structure, and determining a modal participation factor of the front wall outer plate; and determining the durability of the front wall outer plate based on the modal participation factor and the structural damage of the front wall outer plate under at least two operation conditions. According to the technical scheme, the life prediction precision of the front wall outer plate in the whole life cycle is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of simulation analysis, and particularly to a method, device, equipment and medium for predicting the durability of an outer front panel of an automobile. Background Art

[0002] Durability represents the service life of a product and is crucial for an automobile structure. In addition to bearing environmental wind loads, the outer front panel also bears vibration loads transmitted by the road surface during vehicle driving, as well as operating force loads during the opening and closing processes. Therefore, the control of its durability life is relatively complex and difficult.

[0003] The traditional durability control method for the outer front panel mainly involves road or bench tests, which require trial production of sample parts and sample vehicles, consume a long time, and discover problems late. In recent years, with the development of technology, simulation technology has begun to be used for the control of the strength and durability performance of automobile structures, and thus potential structural hazards can be discovered in the middle and early stages of product development, and its durability life can be significantly improved through structural improvement, while reducing development costs and shortening the development cycle.

[0004] Currently, the fatigue simulation analysis of the outer front panel in the industry mainly focuses on frequency-domain simulation with the power spectral density of acceleration signals as the input and life estimation through the Dirlik's method for fatigue life prediction under random loading. However, the driving inputs of the above methods are mostly single-axis inputs, and it is impossible to comprehensively consider various vehicle operating conditions to determine the durability of the outer front panel of an automobile, and thus the durability of the outer front panel of an automobile cannot be accurately determined. Summary of the Invention

[0005] The present invention provides a method, device, equipment and medium for predicting the durability of an outer front panel of an automobile, so as to improve the prediction accuracy of the durability of the outer front panel of an automobile.

[0006] According to one aspect of the present invention, there is provided a method for predicting the durability of an outer front panel of an automobile, the method comprising:

[0007] Performing finite element modeling and rigid body mechanics modeling on the target automobile structure and the outer front panel respectively, and performing modal calculation and flexibility processing on the outer front panel based on the vibration signal of the target automobile structure to determine the modal participation factor of the outer front panel; wherein, the vibration signal is collected through at least two acceleration sensors arranged in the target automobile structure under the test road conditions, and the target automobile structure refers to the automobile system structure to which the fixed end of the outer front panel belongs;

[0008] Based on the modal participation factor and the structural damage of the front outer panel under at least two operating conditions, the durability performance of the front outer panel is determined.

[0009] According to another aspect of the present invention, there is provided a durability prediction device for an automotive front outer panel, the device comprising:

[0010] A simulation module, configured to perform finite element modeling and rigid body mechanics modeling on the target vehicle structure and the front outer panel respectively, and perform modal calculation and flexibility processing on the front outer panel based on the vibration signal of the target vehicle structure to determine the modal participation factor of the front outer panel; wherein, the vibration signal is collected by at least two acceleration sensors arranged in the target vehicle structure under the test road conditions, and the target vehicle structure refers to the vehicle system structure to which the fixed end of the front outer panel belongs;

[0011] A durability determination module, configured to determine the durability performance of the front outer panel based on the modal participation factor and the structural damage of the front outer panel under at least two operating conditions.

[0012] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0013] At least one processor; and

[0014] A memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the durability prediction method of the automotive front outer panel according to any embodiment of the present invention.

[0016] According to another aspect of the present invention, there is provided a computer-readable storage medium, the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the durability prediction method of the automotive front outer panel according to any embodiment of the present invention when executed by a processor.

[0017] According to another aspect of the present invention, there is provided a computer program product, the computer program product comprises a computer program, and the computer program implements the durability prediction method of the automotive front outer panel according to any embodiment of the present invention when executed by a processor.

[0018] In the technical solution of the embodiment of the present invention, by respectively performing finite element modeling and rigid body mechanics modeling on the target vehicle structure and the outer front panel, the modal participation factor of the outer front panel under the test conditions is determined, and the structural damage of the outer front panel under at least two operating conditions is coupled and integrated according to the modal participation factor, improving the life prediction accuracy of the outer front panel in the whole life cycle and solving the problem of durability life control of the automotive outer front panel in the industry.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Brief Description of the Drawings

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0021] Figure 1a is a flowchart of a method for predicting the durability of an automotive outer front panel according to Embodiment 1 of the present invention;

[0022] Figure 1b is a structural schematic diagram of a target vehicle structure according to Embodiment 1 of the present invention;

[0023] Figure 2 is a flowchart of a method for predicting the durability of an automotive outer front panel according to Embodiment 2 of the present invention;

[0024] Figure 3 is a flowchart of a method for predicting the durability of an automotive outer front panel according to Embodiment 3 of the present invention;

[0025] Figure 4 is a structural schematic diagram of a device for predicting the durability of an automotive outer front panel according to Embodiment 4 of the present invention;

[0026] Figure 5 is a structural schematic diagram of an electronic device for implementing the method for predicting the durability of an automotive outer front panel in the embodiment of the present invention. Detailed Embodiments

[0027] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment 1

[0030] Figure 1a A flowchart of a durability prediction method for the outer panel of the front car body is provided for Embodiment 1 of the present invention. This embodiment is applicable to the situation of predicting the durability of the outer panel of the front car body. This method can be executed by a durability prediction device for the outer panel of the front car body. The durability prediction device for the outer panel of the front car body can be implemented in the form of hardware and / or software, and the durability prediction device for the outer panel of the front car body can be configured in various general computing devices. As Figure 1a shown, this method includes:

[0031] S110. Respectively perform finite element modeling and rigid body mechanics modeling on the target vehicle structure and the outer panel of the front car body, and perform modal calculation and flexibility processing on the outer panel of the front car body based on the vibration signal of the target vehicle structure to determine the modal participation factor of the outer panel of the front car body.

[0032] Among them, the vibration signal can be collected through at least two acceleration sensors arranged in the target vehicle structure under the test road conditions. The target vehicle structure can refer to the vehicle system structure to which the fixed end of the outer panel of the front car body belongs. It should be noted that according to different vehicle types, this vehicle system structure can be a vehicle body or a cab assembly.

[0033] In the embodiment of the present invention, the deployment of the acceleration sensor in the target vehicle structure can be as Figure 1b shown, in Figure 1bIn the schematic diagram of the target vehicle structure shown, 1, 2, and 3 can represent triaxial acceleration sensors deployed in the target vehicle structure, and 4 is the area where the outer front panel is located. It should be noted that the deployment positions of the triaxial acceleration sensors are the actual load application positions of the target vehicle structure, which can be adaptively set by those skilled in the art, such as the upper mounting ear of the vehicle body shock absorber or the fixed position of the upper bracket of the cab mount, with the deployment positions being areas with relatively high stiffness.

[0034] The test road conditions can be reliable durability verification roads required by enterprises or specific users, which can include enhanced bad roads and highways, etc. During the process of collecting the vibration signals of the target vehicle structure under the test road conditions, the sampling frequency of the triaxial acceleration sensors is at least set to 10 times the upper limit of the concerned frequency at the deployment positions to avoid aliasing and improve the signal quality of the collected signals. Exemplarily, for vehicle body components, the sampling frequency is at least set to 500 Hz. Optionally, the triaxial acceleration sensors can collect the vibration signals of multiple sampling periods and select the vibration signals within one sampling period with the average standard deviation as the vibration signals to be processed, and the sampling period can be adaptively set by those skilled in the art.

[0035] In an optional embodiment, preprocessing operations such as deburring, detrending, and debiasing can be performed on the vibration signals to be processed, and the vibration signals below the preset range of the signal standard deviation can be deleted to improve the signal quality of the vibration signals.

[0036] Optionally, in the embodiments of the present invention, after the vibration signals are collected, it further includes: screening the acceleration signal channels of the vibration signals collected by the acceleration sensors to determine the target degrees of freedom; performing the first Butterworth high-pass filtering and the first signal integration on the target vibration signals under the target degrees of freedom to convert the target vibration signals into velocity signals; performing the second Butterworth high-pass filtering and the second signal integration on the velocity signals to convert the velocity signals into displacement signals; performing the third Butterworth high-pass filtering and the third signal integration on the displacement signals to output the target displacement signals.

[0037] Specifically, it can be achieved by selecting Figure 1bThe XYZ three-direction signals of the three-direction acceleration sensors deployed at position 1, the Z-direction signal of the three-direction acceleration sensors deployed at position 2, and the YZ-direction signals of the three-direction acceleration sensors deployed at position 3. These six-direction channel signals are used as the target degrees of freedom. It should be noted that the X-axis direction in the target degrees of freedom can be the X-direction signal of any three-direction acceleration sensor. Using signal processing software such as Tecware, etc., perform the first Butterworth high-pass filter on the direction channel signals simultaneously (the starting frequency is recommended to be above 2 Hz), and adopt the zero-phase filtering form of the 8th order to perform the first signal integration, converting the acceleration signal into a velocity signal. Then perform the second Butterworth filter and the second signal integration to convert the velocity signal into a displacement signal. Finally, perform the third Butterworth filter to ensure that the final displacement signal does not drift, modify the signal unit to meters, and output the target displacement signal. Optionally, the format of the target displacement signal can be a binary asc file.

[0038] By screening the target degrees of freedom in six channel directions, that is, 3 Z-directions, two Y-directions, and 1 X-direction drive, the overall vibration characteristics of the target vehicle structure can be truly reproduced. And by directly converting the acceleration signal into a displacement signal, that is, using three high-order Butterworth filters and two integrations, the target displacement signal does not drift, improving the data accuracy of the displacement signal.

[0039] S120. Based on the modal participation factor and the structural damage of the front bulkhead outer panel under at least two operating conditions, determine the durability performance of the front bulkhead outer panel.

[0040] It should be noted that the operating conditions can include enhanced rough road conditions, normal wind load conditions on highways, strong wind conditions, and opening and closing conditions, etc. The structural damage under various operating conditions can be coupled to determine the durability performance of the front bulkhead outer panel. Optionally, the total structural damage after coupling can be the structural damage under enhanced rough road conditions * number of condition cycles + the structural damage under normal wind load conditions on highways * number of condition cycles + the structural damage under strong wind conditions * number of condition cycles + the structural damage under opening and closing conditions * number of condition cycles. Among them, the number of condition cycles is used to represent the number of repeated operations under the corresponding conditions and can be adaptively set by those skilled in the art.

[0041] By establishing a combined condition and coupling the structural damage under different operating conditions, the comprehensive damage of the front bulkhead outer panel is finally obtained, improving the life prediction accuracy of the front bulkhead outer panel in its entire life cycle.

[0042] The technical solution of the embodiment of the present invention determines the modal participation factor of the front outer panel under the test conditions by respectively performing finite element modeling and rigid body mechanics modeling on the target vehicle structure and the front outer panel, and performs coupled integration calculation on the structural damage of the front outer panel under at least two operating conditions according to the modal participation factor, improving the life prediction accuracy of the front outer panel in the whole life cycle and solving the problem of durability life control of the automotive front outer panel in the industry.

[0043] Embodiment 2

[0044] Figure 2 FIG. is a flowchart of a durability prediction method for an automotive front outer panel provided by Embodiment 2 of the present invention. This embodiment is further refined on the basis of the above embodiment, and provides specific steps for respectively performing finite element modeling and rigid body mechanics modeling on the target vehicle structure and the front outer panel, and performing modal calculation and flexibilization processing on the front outer panel based on vibration signals to determine the modal participation factor of the front outer panel. It should be noted that for the parts not detailed in the embodiment of the present invention, reference can be made to the relevant descriptions of other embodiments, which will not be elaborated here. As Figure 2 shown, the method includes:

[0045] S210. Perform finite element modeling and rigid body mechanics modeling on the target vehicle structure to generate a first finite element model and a first rigid body model.

[0046] Optionally, in the embodiment of the present invention, performing finite element modeling and rigid body mechanics modeling on the target vehicle structure to generate a first finite element model and a first rigid body model includes: performing initial modeling according to the body beam structure and skin structure of the target vehicle structure, and classifying and naming the geometric models in the model after initial modeling; and performing geometric cleaning on the model after initial modeling; performing secondary modeling on the model after initial modeling to generate a first finite element model; constructing a first rigid body model of the target vehicle structure according to 3D model tools.

[0047] Among them, geometric cleaning may include mid-surface extraction operation, contour line processing operation, and refinement operation around bolt holes; secondary modeling may include modeling welds and bolt connection units, assembling each connection unit in the model after initial modeling; and assigning corresponding material property information to each connection unit.

[0048] Specifically, during the process of finite element modeling of the target vehicle structure, initial modeling is mainly carried out on the body beam structure and the skin structure of the target vehicle structure to ensure the overall stiffness and mass distribution characteristics of the target vehicle structure. The interior and exterior trim assemblies (including the front outer panel) can be replaced by lumped masses without the need for detailed finite element modeling. After the initial modeling, the geometric models (component models in the target vehicle structure) in the model after the initial modeling can be classified and named. Exemplarily, the naming rule for the geometric models can be part number - material grade - thickness information - version number. Then, geometric cleaning is performed on the model after the initial modeling, including cleaning operations such as extracting the mid-surface, processing the contour lines, and refining around the bolt holes of the model.

[0049] Furthermore, the model after the initial modeling can be re-modeled, and connection units such as welds and bolts are modeled and assembled into the model after the initial modeling to generate the first finite element model. It should be noted that during the process of modeling the connection units, respective material property tag information is assigned to each connection unit, such as Young's modulus, density, Poisson's ratio information, and thickness information, etc. Optionally, the weld connection unit can adopt a seam unit, and the bolt connection unit can be assembled in a mixed modeling form of a rigid unit and a beam unit.

[0050] It should be noted that in the embodiment of the present invention, a rigid body model structure of the target vehicle structure can be established through Simcenter3D software as the first rigid body model.

[0051] Optionally, in the embodiment of the present invention, after the initial modeling of the first finite element model, finite element mesh division can be performed on the model after the initial modeling, and element quality inspection is carried out to ensure the model quality of the model after the initial modeling; and the error percentage between the weight of the completed first finite element model and the actual design value is checked to ensure that the error percentage is less than the preset error value. A trial operation condition can be set, and the output results of the trial operation condition are solved and calculated using Nastran software to observe whether there are abnormal vibration postures in the modal vibration modes of the first finite element model to ensure the effectiveness of the first finite element model, and the first finite element model is output in the form of a finite element file. It should be noted that the preset error value can be adaptively set by those skilled in the art.

[0052] S220. Based on the vibration signal, the first finite element model, and the first rigid body model of the target vehicle structure, perform dynamic solution on the target vehicle structure to determine the displacement data of the front outer panel.

[0053] Among them, the displacement data may include linear displacement data in a preset number of directions and angular displacement data in a preset number of directions. It should be noted that the determined displacement data of the front outer panel conforms to the displacement direction defined by the target degrees of freedom. Optionally, the preset number can be adaptively set by those skilled in the art. Exemplarily, the displacement data can be displacement data that conforms to the target degrees of freedom.

[0054] Optionally, based on the vibration signal, the first finite element model, and the first rigid body model of the target vehicle structure, perform dynamic solution on the target vehicle structure to determine the displacement data of the front outer panel, including: constructing a vehicle coordinate system of the target vehicle structure in the first rigid body model according to the position information of the acceleration sensors arranged in the target vehicle structure; establishing a global coordinate system for the first rigid body model according to the position information of the acceleration sensors arranged in the target vehicle structure; respectively establishing multi-degree-of-freedom drives for the first rigid body model and the global based on the target degrees of freedom specified by the acceleration sensor position information, and using the target displacement signal indicated by the vibration signal as the drive input; performing modal calculation on the first finite element model to determine the modal calculation result, and importing the modal calculation result into the first rigid body model to perform dynamic solution on the first rigid body model to determine the displacement data of the central area of the front outer panel.

[0055] Specifically, a local coordinate system (vehicle coordinate system) of the target vehicle structure can be established in the first rigid body model according to the position information of the acceleration sensors arranged in the target vehicle structure, and at the same time, a global coordinate system is established for the first rigid body model according to the position information of the acceleration sensors arranged in the target vehicle structure; multi-degree-of-freedom drives are established according to the displacement direction defined by the target degrees of freedom, as well as the vehicle coordinate system and the global coordinate system to simulate the dynamic behavior of the target vehicle structure on the ground.

[0056] Furthermore, the target displacement signal can be used as the drive signal input of the multi-degree-of-freedom drive to perform displacement simulation on the target vehicle structure (the signal step of the target displacement signal is consistent with the reciprocal of the sampling frequency of the vibration signal). Import the finite element file represented by the first finite element model into the first rigid body model, and perform modal calculation on the first rigid body model of the target vehicle structure to determine the modal calculation result. Among them, the modal calculation result can include at least 20 vibration modes and 6 static displacement compensation modes; perform flexibilization processing on the first rigid body model of the target vehicle structure according to the modal calculation result to improve the accuracy of displacement simulation; input the modal damping ratio value for each modal calculation result to simulate energy dissipation, where the range of the modal damping ratio value can be 1% - 5%. During this motion simulation process, perform dynamic solution on the first rigid body model and output displacement data in the central area of the front outer panel. Among them, the displacement data is a six-degree-of-freedom displacement, including linear displacement data in 3 directions and angular displacement data in 3 directions.

[0057] It should be noted that the vehicle coordinate system can be used to define and measure the dynamic behavior of the structural units of the target vehicle structure. The earth coordinate system can be used to compare with the vehicle coordinate system of the target vehicle structure to analyze the relative movement of the target vehicle structure.

[0058] By performing the drive decomposition of the front outer panel, the determined displacement data of the front outer panel can lay a foundation for subsequent structural analysis of the front outer panel.

[0059] S230. Perform finite element modeling and rigid body mechanics modeling on the front outer panel of the vehicle to generate a second finite element model and a second rigid body model.

[0060] S240. Based on the displacement data of the front outer panel, the second finite element model, and the second rigid body model, perform modal calculation and flexibility processing on the front outer panel of the vehicle to determine the modal participation factors of the front outer panel of the vehicle.

[0061] Among them, the construction process of the second finite element model is basically the same as that of the first finite element model. The difference is that the second finite element model is mainly used to model the structures such as the front outer panel body, brackets, gas struts, and lock bodies, as well as connection units such as bolts and welding. It should be noted that the second finite element model retains the structural models of the target vehicle structure within 500 mm of the top side and the left and right sides of the front outer panel.

[0062] The second rigid body model is the rigid body unit model of the front baffle. The main point is the central coordinate of the fixed point of the front outer panel, and the slave points are all the nodes of the fixed end structure port of the front baffle.

[0063] Specifically, establish a multi-degree-of-freedom drive to simulate the operation of the front baffle and simulate the motion posture of the front baffle during the movement process. The drive input of this multi-degree-of-freedom drive is the displacement data of the front outer panel. Perform modal calculation and flexibility processing on the second rigid body model, and finally perform multi-body dynamics solution on the first rigid body model to determine the modal participation factors of the front baffle. Optionally, the modal calculation results of the second rigid body model include modal stress, displacement, nodal force, and fulcrum force information. The modal participation factors can be used to evaluate the vibration response of the vehicle structure under operating road conditions. The characteristic modal participation factors can include the modal participation factors of rough roads and highways.

[0064] S250. Based on the modal participation factors and the structural damage of the front outer panel under at least two operating conditions, determine the durability performance of the front outer panel.

[0065] In the technical solution of the embodiment of the present invention, by using the vibration signal obtained from the test of the target vehicle structure under real road conditions as the driving input, kinematic simulation is performed on the target vehicle structure and the outer front panel, the motion posture of the target vehicle structure is simulated, and multi-body dynamics solution is performed on the input of the displacement data of multiple degrees of freedom of the outer front panel. The coupling of the driving input of multiple degrees of freedom is considered in the kinematic simulation, which improves the accuracy of structural damage prediction.

[0066] Embodiment III

[0067] Figure 3 FIG. is a flowchart of a durability prediction method for an outer front panel of an automobile provided in Embodiment III of the present invention. This embodiment is further refined on the basis of the above embodiment, and provides specific steps for determining the durability performance of the outer front panel based on the modal participation factor and the structural damage of the outer front panel under at least two operating conditions. It should be noted that for the parts not detailed in the embodiments of the present invention, reference may be made to the relevant descriptions of other embodiments, which will not be elaborated here. As Figure 3 shown, the method includes:

[0068] S310. Respectively perform finite element modeling and rigid body mechanics modeling on the target vehicle structure and the outer front panel, and perform modal calculation and flexibility processing on the outer front panel based on the vibration signal of the target vehicle structure to determine the modal participation factor of the outer front panel.

[0069] S320. Based on the modal participation factor, determine the structural damage of the outer front panel under the conditions of a reinforced rough road condition, a highway condition, a strong wind condition, and a closing and opening condition.

[0070] S330. Couple the structural damages of the outer front panel under the conditions of a reinforced rough road condition, a normal wind load condition on a highway, a strong wind condition, and a closing and opening condition to determine the durability performance of the outer front panel.

[0071] In the embodiment of the present invention, under the reinforced rough road condition, the modal calculation results (modal stresses) of the second rigid body model can be matched with the loads (modal participation factors of the reinforced rough road) to determine the stress amplitudes and strain amplitudes of each structural point in the second rigid body model. Exemplarily, the modal stresses and load data can be matched according to the linear superposition method to calculate the corresponding strain results (stress amplitudes and strain amplitudes). It should be noted that the modal stresses and modal participation factors are consistent in time and space. Matching their time steps, sampling frequencies, etc. can ensure the synchronization of data.

[0072] Optionally, in the embodiments of the present invention, the structural points in the second rigid body model can be classified by materials, such as metal materials, non-metal materials, and welding materials. For metal materials, the strain method of low-cycle fatigue is selected to obtain the EN (strain-life) fatigue curve of the metal material. For non-metal materials, the stress method of high-cycle fatigue is selected to obtain the SN (stress-life) fatigue curve; for welding materials, the SN fatigue curve of the welding materials based on structural mechanics or notch mechanics is selected, and a welding process correction coefficient is introduced to correct the influence of the welding process on the fatigue performance. Optionally, the EN fatigue curve and the SN fatigue curve can be determined by performing fatigue tests on metal materials.

[0073] For the EN fatigue curve and the SN fatigue curve, mean stress parameter correction can be adopted. For example, correction methods such as Smith-Watson-Topper or Goodman are used to correct the EN fatigue curve and the SN fatigue curve. In a specific embodiment, the structural damage of each material structural point can be determined through the damage accumulation methods of Minor and Haibach, and then the structural damage of the front end outer panel within a test cycle under the enhanced bad road condition can be determined.

[0074] Since the vehicle is driving on the highway, the wind resistance generated by high-speed driving will have a non-negligible impact on the front end outer panel. Therefore, it is necessary to perform a coupled calculation of the vibration condition and the wind load condition on the highway. Under high-speed conditions, for different vehicle speed conditions, according to the CFD (Computational Fluid Dynamics) software, the wind load output to each structural unit of the front end outer panel is determined; in the finite element analysis environment of the second finite element model, target degrees of freedom are applied to the fixed-point rigid unit, and the wind load prestress of the front end outer panel is determined according to the static condition of the wind load of the structural unit; next, the modal calculation results (modal stress) of the second rigid body model are matched with the modal participation factors of the highway to determine the stress amplitude and strain amplitude of each structural point in the second rigid body model. By coupling the wind load prestress with the time-domain stress amplitude under highway conditions, the corrected mean stress and stress amplitude under wind load conditions are obtained. The method of classifying the structural points in the second rigid body model by materials can be adopted to perform the structural damage of the front end outer panel within a test cycle under different wind speed conditions on the highway.

[0075] In the embodiments of the present invention, it is also possible to determine the structural damage of the front end outer panel under strong wind conditions (such as the wind load formed by oncoming vehicles when passing through a tunnel at high speed, or the strong crosswind load on a highway bridge, etc.), and the structural damage under the opening and closing conditions. It should be noted that the opening and closing conditions may refer to the operations of opening or closing the front end outer panel. The structural damage of the front end outer panel under the enhanced rough road conditions, the ordinary wind load conditions on highways, the strong wind conditions, and the opening and closing conditions can be coupled to determine the durability performance of the front end outer panel.

[0076] The technical solution of the embodiments of the present invention determines the durability performance of the front end outer panel throughout its life cycle by coupling and calculating the structural damage of the front end outer panel under different operating conditions. And in the process of determining the structural damage of the front end outer panel under each operating condition, by determining the structural points in the front end outer panel for material classification, determining the structural damage of the structural points under each material classification, and then determining the structural damage of the front end outer panel, covering the durability performance of the load-bearing and non-load-bearing structures of the front end outer panel, and improving the prediction accuracy of structural damage.

[0077] Embodiment 4

[0078] Figure 4 is a schematic structural diagram of a durability prediction device for an automotive front end outer panel provided in Embodiment 4 of the present invention. As Figure 4 shown, the device includes:

[0079] A simulation module 410, configured to perform finite element modeling and rigid body mechanics modeling on the target vehicle structure and the front end outer panel respectively, and perform modal calculation and flexibility processing on the front end outer panel based on the vibration signal of the target vehicle structure to determine the modal participation factor of the front end outer panel; wherein, the vibration signal is collected by at least two acceleration sensors arranged in the target vehicle structure under the test road conditions, and the target vehicle structure refers to the vehicle system structure to which the fixed end of the front end outer panel belongs;

[0080] A durability determination module 420, configured to determine the durability performance of the front end outer panel based on the modal participation factor and the structural damage of the front end outer panel under at least two operating conditions.

[0081] The technical solution of the embodiments of the present invention determines the modal participation factor of the front end outer panel under the test conditions by performing finite element modeling and rigid body mechanics modeling on the target vehicle structure and the front end outer panel respectively, and performs coupled integration calculation on the structural damage of the front end outer panel under at least two operating conditions according to the modal participation factor, improving the life prediction accuracy of the front end outer panel throughout its life cycle and solving the problem of durability life control of automotive front end outer panels in the industry.

[0082] Optionally, the simulation module 410 includes:

[0083] The first modeling unit is used to perform finite element modeling and rigid body mechanics modeling on the target vehicle structure, generating a first finite element model and a first rigid body model;

[0084] The displacement determination unit is used to perform dynamic solution on the target vehicle structure based on the vibration signal of the target vehicle structure, the first finite element model and the first rigid body model, and determine the displacement data of the outer front panel; wherein, the displacement data includes linear displacement data in a preset number of directions and angular displacement data in a preset number of directions;

[0085] The second modeling unit is used to perform finite element modeling and rigid body mechanics modeling on the vehicle outer front panel, generating a second finite element model and a second rigid body model;

[0086] The modal participation factor unit is used to perform modal calculation and flexibility processing on the vehicle outer front panel based on the displacement data of the outer front panel, the second finite element model and the second rigid body model, and determine the modal participation factor of the vehicle outer front panel.

[0087] Optionally, the first modeling unit may specifically be used for:

[0088] Perform initial modeling according to the body beam structure and skin structure of the target vehicle structure, and classify and name the geometric models in the model after initial modeling; and perform geometric cleaning on the model after initial modeling; wherein, the geometric cleaning includes mid-surface extraction operation, contour line processing operation and refinement operation around bolt holes;

[0089] Perform secondary modeling on the model after initial modeling to generate a first finite element model; wherein, the secondary modeling includes modeling of welds and bolt connection units, assembling each connection unit in the model after initial modeling; and assigning corresponding material property information to each connection unit;

[0090] Construct the first rigid body model of the target vehicle structure according to 3D model tools.

[0091] Optionally, the displacement determination unit may specifically be used for:

[0092] Construct the vehicle coordinate system of the target vehicle structure in the first rigid body model according to the position information of the acceleration sensors arranged in the target vehicle structure;

[0093] Establish a geodetic coordinate system for the first rigid body model according to the position information of the acceleration sensors arranged in the target vehicle structure;

[0094] According to the target degrees of freedom specified by the acceleration sensor position information, multi-degree-of-freedom drives are established for the first rigid body model and the ground respectively, and the target displacement signal indicated by the vibration signal is used as the drive input;

[0095] Perform modal calculation on the first finite element model to determine the modal calculation result, and import the modal calculation result into the first rigid body model to perform dynamic solution on the first rigid body model to determine the displacement data of the central region of the front outer panel.

[0096] Optionally, the device further includes:

[0097] A signal processing module, configured to:

[0098] Screen the acceleration signal channels of the vibration signal collected by the acceleration sensor to determine the target degrees of freedom;

[0099] Perform the first Butterworth high-pass filter and the first signal integration on the target vibration signal under the target degrees of freedom to convert the target vibration signal into a velocity signal;

[0100] Perform the second Butterworth high-pass filter and the second signal integration on the velocity signal to convert the velocity signal into a displacement signal;

[0101] Perform the third Butterworth high-pass filter and the third signal integration on the displacement signal to output the target displacement signal.

[0102] Optionally, the durability determination module 420 may specifically be configured to:

[0103] Based on the modal participation factor, determine the structural damage of the front outer panel under the enhanced bad road condition, highway condition, strong wind condition, and closing and opening condition;

[0104] Couple the structural damages of the front outer panel under the enhanced bad road condition, highway ordinary wind load condition, strong wind condition, and closing and opening condition to determine the durability performance of the front outer panel.

[0105] The durability prediction device for the automotive front outer panel provided by the embodiments of the present invention can execute the durability prediction method for the automotive front outer panel provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0106] Embodiment Five

[0107] Figure 5FIG. 510 shows a schematic structural diagram of an electronic device 510 that can be used to implement an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0108] As Figure 5 shown, the electronic device 510 includes at least one processor 511, and a memory communicatively connected to the at least one processor 511, such as a read-only memory (ROM) 512, a random access memory (RAM) 513, etc. The memory stores a computer program executable by the at least one processor. The processor 511 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 512 or the computer program loaded from the storage unit 518 into the random access memory (RAM) 513. In the RAM 513, various programs and data required for the operation of the electronic device 510 can also be stored. The processor 511, the ROM 512, and the RAM 513 are connected to each other via a bus 514. An input / output (I / O) interface 515 is also connected to the bus 514.

[0109] Multiple components in the electronic device 510 are connected to the I / O interface 515, including: an input unit 516, such as a keyboard, a mouse, etc.; an output unit 517, such as various types of displays, speakers, etc.; a storage unit 518, such as a magnetic disk, an optical disk, etc.; and a communication unit 519, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 519 allows the electronic device 510 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0110] The processor 511 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 511 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 511 executes the various methods and processes described above, such as the durability prediction method for the front outer panel of an automobile.

[0111] In some embodiments, a durability prediction method for an outer panel of a vehicle front end can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 518. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 510 via the ROM 512 and / or the communication unit 519. When the computer program is loaded into the RAM 513 and executed by the processor 511, one or more steps of the durability prediction method for the outer panel of the vehicle front end described above can be performed. Alternatively, in other embodiments, the processor 511 can be configured to perform the durability prediction method for the outer panel of the vehicle front end by any other suitable means (e.g., by means of firmware).

[0112] The various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from a storage system, at least one input device, and at least one output device, and transmits the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0113] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer programs are executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0114] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0115] To provide for interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0116] The systems and techniques described herein can be implemented in a computing system that includes backend components (such as, for example, a data server), or a computing system that includes middleware components (such as, for example, an application server), or a computing system that includes frontend components (such as, for example, a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (such as, for example, a communication network). Examples of the communication network include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0117] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The relationship between the client and the server is created by computer programs that run on respective computers and have a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0118] It should be understood that various forms of processes shown above can be used, steps can be reordered, added or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0119] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for predicting the durability of a front outer panel of an automobile, characterized in that: include: The target vehicle structure and the front outer panel are respectively subjected to finite element modeling and rigid body mechanics modeling, and the front outer panel is subjected to modal calculation and flexibility processing based on the vibration signal of the target vehicle structure to determine the modal participation factor of the front outer panel; wherein the vibration signal is acquired under a test road condition by at least two acceleration sensors arranged in the target vehicle structure, and the target vehicle structure refers to the vehicle system structure to which the fixed end of the front outer panel belongs; Based on the modal participation factor and the structural damage of the front outer panel under at least two operating conditions, the durability performance of the front outer panel is determined.

2. The method according to claim 1, characterized in that Finite element modeling and rigid body mechanics modeling are performed on the target vehicle structure and the front outer panel respectively, and modal calculation and flexibility processing are performed on the front outer panel based on the vibration signal of the target vehicle structure to determine the modal participation factor of the front outer panel, including: Performing finite element modeling and rigid body mechanics modeling on the target vehicle structure to generate a first finite element model and a first rigid body model; Based on the vibration signal of the target automobile structure, the first finite element model and the first rigid body model, the target automobile structure is dynamically solved to determine the displacement data of the front outer panel; wherein the displacement data includes linear displacement data in a preset number of directions and angular displacement data in a preset number of directions; Performing finite element modeling and rigid body mechanics modeling on the front outer panel of the automobile to generate a second finite element model and a second rigid body model; Based on the displacement data of the front outer panel, the second finite element model and the second rigid body model, modal calculation and flexibility processing are performed on the front outer panel of the automobile to determine the modal participation factor of the front outer panel of the automobile.

3. The method according to claim 2, characterized in that Performing finite element modeling and rigid body mechanics modeling on the target automobile structure to generate a first finite element model and a first rigid body model includes: Performing initial modeling according to the body beam structure and skin structure of the target automobile structure, and classifying and naming the geometric models in the model after the initial modeling; and performing geometric cleaning on the model after the initial modeling; wherein the geometric cleaning includes extracting mid-surface operations, processing contour lines operations, and thinning operations around bolt holes; Performing secondary modeling on the model after the initial modeling to generate a first finite element model; wherein the secondary modeling includes modeling welds and bolt connection units, assembling each connection unit in the model after the initial modeling; and assigning corresponding material property information to each connection unit; A first rigid body model of the target vehicle structure is constructed according to a 3D modeling tool.

4. The method according to claim 2, characterized in that: Based on the vibration signal, the first finite element model and the first rigid body model, a dynamic solution is performed on the target vehicle structure to determine displacement data of the front outer panel, including: Constructing a vehicle coordinate system of the target vehicle structure in the first rigid body model according to position information of the acceleration sensor arranged in the target vehicle structure; Establishing a geodetic coordinate system for the first rigid body model according to the position information of the acceleration sensor arranged in the target vehicle structure; According to the target degrees of freedom specified by the position information of the acceleration sensor, a multi-degree-of-freedom drive is established for the first rigid body model and the ground respectively, and a target displacement signal indicated by the vibration signal is used as a drive input; Perform modal calculation on the first finite element model to determine the modal calculation result, and import the modal calculation result into the first rigid body model, perform dynamic solution on the first rigid body model to determine the displacement data of the central area of ​​the front outer panel.

5. The method according to claim 1, characterized in that: After the vibration signal is collected, the following steps are also included: Perform acceleration signal channel screening on the vibration signal collected by the acceleration sensor to determine the target degree of freedom; Performing a first Butterworth high-pass filter and a first signal integration on the target vibration signal under the target degree of freedom, and converting the target vibration signal into a velocity signal; Performing a second Butterworth high-pass filtering and a second signal integration on the velocity signal to convert the velocity signal into a displacement signal; The displacement signal is subjected to a third Butterworth high-pass filtering and a third signal integration to output a target displacement signal.

6. The method according to claim 1, characterized in that Based on the modal participation factor and the structural damage of the front outer panel under at least two operating conditions, the durability performance of the front outer panel is determined, including: Based on the modal participation factors, determining the structural damage of the front outer panel under enhanced bad road conditions, highway conditions, strong wind conditions, and closed and open conditions; The structural damage of the front outer panel under the enhanced bad road condition, the ordinary wind load condition on the highway, the strong wind condition and the closed and open condition is coupled to determine the durability performance of the front outer panel.

7. A durability prediction device for a front outer panel of an automobile, characterized in that: include: A simulation module, for performing finite element modeling and rigid body mechanics modeling on the target vehicle structure and the front outer panel, respectively, and performing modal calculation and flexibility processing on the front outer panel based on a vibration signal of the target vehicle structure, and determining a modal participation factor of the front outer panel; wherein the vibration signal is acquired under a test road condition by at least two acceleration sensors arranged in the target vehicle structure, and the target vehicle structure refers to a vehicle system structure to which a fixed end of the front outer panel belongs; The durability determination module is used to determine the durability performance of the front outer panel based on the modal participation factor and the structural damage of the front outer panel under at least two operating conditions.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the durability prediction method for the automobile front outer panel according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the durability prediction method for a front outer panel of an automobile according to any one of claims 1 to 6 when the processor executes the instructions.

10. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the durability prediction method of the automobile front outer panel according to any one of claims 1 to 6.

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