Motormeter simulation optimization method and device, computer equipment and storage medium

Abstract

The invention discloses an automobile instrument simulation optimization method and device, computer equipment and a storage medium. The method comprises the steps of obtaining an instrument model of a to-be-analyzed automobile instrument; obtaining a damage model of the to-be-optimized automobile instrument, comparing the difference between the instrument model and the damage model so as to determine a to-be-optimized area in the instrument model, obtaining preset parameterization setting of the to-be-optimized area, and then sequentially performing static analysis and modal analysis on the instrument model based on preset optimization parameters and the preset parameterization setting so as to obtain a to-be-optimized automobile instrument model. And obtaining modal solving information of the instrument model, and if the modal solving information meets a preset condition, performing model optimization on the to-be-optimized region according to the modal solving information and a response basis condition to obtain an optimized model, thereby completing optimization. According to the mode, the precision of a simulation result and an optimization result can be improved while the calculation amount is reduced, and the efficiency and the accuracy of simulation optimization are improved. In addition, the weight of the automobile instrument can be reduced under the condition that the overall strength of the automobile instrument is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automotive simulation analysis, and particularly relates to a method, device, computer equipment and storage medium for optimizing automotive instrument simulation. Background Art

[0002] As one of the important components of an automobile, the strength performance of the automotive instrument has always been the focus of attention in the instrument industry. Insufficient strength of the automotive instrument may cause situations such as fracture and detachment during driving. Therefore, simulation analysis can be performed on the automotive instrument to judge its structural strength.

[0003] Currently, when performing simulation analysis on automotive instruments, most are modal analysis of automotive instruments. According to the first-order modal frequencies of each item, the structural strength of the automotive instrument is judged, and then the corresponding deformation degree is obtained, and evaluation and optimization are carried out in the design stage. However, modal analysis is a simulation analysis method under ideal conditions. Due to the differences in the structures of automotive instruments and the models of vehicles they are adapted to, the states of automotive instruments vary during actual installation, resulting in a large error between the simulation results and the actual results. Moreover, currently, when performing simulation analysis and working condition simulation tests, the automotive instrument is often at the end of the production design stage. If it is found at this time that the strength performance of the automotive instrument is unqualified, modifying the structure of these automotive instruments that have already completed mold opening or even have been put into production will also greatly increase the development cost and extend the development cycle.

[0004] Therefore, how to improve the accuracy of the analysis results while simplifying the simulation calculation amount has become an urgent technical problem to be solved. Summary of the Invention

[0005] Based on the above situation, the main purpose of the present invention is to provide a method, device, computer equipment and storage medium for optimizing automotive instrument simulation, so as to improve the accuracy of the analysis results while simplifying the simulation calculation amount.

[0006] To achieve the above purpose, the technical solutions adopted by the present invention are as follows:

[0007] In the first aspect, an embodiment of the present invention discloses a method for optimizing automotive instrument simulation, and the method includes:

[0008] Step S100, obtaining an instrument model of the automotive instrument to be optimized;

[0009] Step S200, obtaining a damage model of the automotive instrument to be optimized, where the damage model is a model obtained by scanning the sample of the automotive instrument to be optimized after a modal test, and the sample of the automotive instrument to be optimized is produced based on the instrument model;

[0010] Step S300, compare the differences between the instrument model and the damaged model to determine the area to be optimized within the instrument model, where the area to be optimized includes the areas where the instrument model and the damaged model are inconsistent;

[0011] Step S400, obtain the preset parametric settings for the area to be optimized in the instrument model, where the preset parametric settings include setting the dimensions of the area to be optimized;

[0012] Step S500, perform static analysis and modal analysis on the instrument model in sequence based on the preset optimization parameters and parametric settings to obtain the modal solution information of the instrument model, where the preset optimization parameters include mesh division parameters, static analysis parameters, and modal analysis parameters;

[0013] Step S600, if the modal solution information meets the preset conditions, perform structural optimization on the area to be optimized according to the modal solution information and response basis conditions to obtain an optimized model, where the response basis conditions include the mass retention percentage of the area to be optimized, and the preset conditions include the instrument strength of the instrument to be optimized.

[0014] Optionally, after step S500, the method further includes:

[0015] Step S510, if the modal solution information does not meet the preset conditions, adjust the parameters set in the parametric settings, and execute step S500.

[0016] Optionally, between step S300 and step S400, the method further includes:

[0017] Step S310, obtain the broken surfaces and / or edge lines in the damaged model;

[0018] Step S320, merge the broken surfaces at the corresponding positions in the instrument model, and / or delete the edge lines at the corresponding positions in the instrument model to simplify the instrument model.

[0019] Optionally, step S500 includes:

[0020] Step S501, perform model mesh division on the instrument model using the mesh division parameters to obtain a mesh model;

[0021] Step S502, perform static solution on the mesh model based on the static analysis parameters to obtain a static solution result, where the static analysis parameters include gravity parameters, connection point degree of freedom constraint parameters, and structural analysis parameters;

[0022] Step S503, perform prestressed modal analysis on the mesh model based on the modal analysis parameters and the static solution result to obtain modal solution information, where the modal analysis parameters include the maximum modal order and frequency range.

[0023] Optionally, step S501 includes:

[0024] Step S5011, performing model mesh division on the instrument model using grid division parameters to obtain a first mesh model;

[0025] Step S5012, obtaining the sheet-like structure in the instrument model and locally encrypting the mesh of the sheet-like structure to obtain a second mesh model.

[0026] Optionally, step S600 includes:

[0027] Step S601, performing structural optimization on the area to be optimized according to modal solution information and structural optimization parameters to obtain a structural model, where the structural optimization parameters include the maximum number of iterations, convergence accuracy, and penalty factor;

[0028] Step S602, performing structural optimization on the structural model according to the response basis condition to obtain an optimized model, where the response basis condition includes the mass retention percentage of the area to be optimized.

[0029] Optionally, after step S600, the method further includes:

[0030] Step S700, performing iterative optimization on the area to be optimized in the optimized model based on a preset optimization index, so that each parameter in the optimized optimized model meets the preset optimization index, where the optimization index includes at least one of an economic index, a demolding index, and a pouring index.

[0031] In a second aspect, an embodiment of the present invention discloses an automotive instrument simulation optimization device, and the device includes:

[0032] A model acquisition module, which acquires the instrument model of the automotive instrument to be optimized;

[0033] A damage acquisition module, which acquires the damage model of the automotive instrument to be optimized, where the damage model is a model obtained by scanning after a modal test on a sample of the automotive instrument to be optimized, and the sample of the automotive instrument to be optimized is produced based on the instrument model;

[0034] A difference comparison module, which compares the differences between the instrument model and the damage model to determine the area to be optimized within the instrument model, and the area to be optimized includes the area where the instrument model is inconsistent with the damage model;

[0035] A parameterization module, which acquires the preset parameterization settings of the area to be optimized in the instrument model, and the preset parameterization settings include setting the size of the area to be optimized;

[0036] A modal solution module performs static analysis and modal analysis on the instrument model in sequence based on preset optimization parameters and the parametric settings to obtain the modal solution information of the instrument model, where the preset optimization parameters include mesh division parameters, static analysis parameters, and modal analysis parameters;

[0037] A structure optimization module, if the modal solution information meets the preset conditions, performs structure optimization on the area to be optimized according to the modal solution information and response basis conditions to obtain an optimized model, where the response basis conditions include the mass retention percentage of the area to be optimized, and the preset conditions include the instrument strength of the automotive instrument to be optimized.

[0038] In a third aspect, an embodiment of the present invention discloses a computer device, including: performing simulation analysis of an automotive instrument by using the method disclosed in the first aspect above, or including the device disclosed in the second aspect above.

[0039] In a fourth aspect, an embodiment of the present invention discloses a computer storage medium, on which a computer program is stored, and the computer program stored in the storage medium is used to be executed to implement the simulation analysis method of the automotive instrument as described in the first aspect above.

[0040] Advantageous effects:

[0041] According to the automotive instrument simulation and optimization method, device, computer device, and storage medium disclosed in the embodiments of the present invention, the method includes obtaining an instrument model of an automotive instrument to be analyzed; obtaining a damaged model of the automotive instrument to be optimized, comparing the differences between the instrument model and the damaged model to determine the area to be optimized within the instrument model, obtaining the preset parametric settings of the area to be optimized, and then performing static analysis and modal analysis on the instrument model in sequence based on the preset optimization parameters and the preset parametric settings to obtain the modal solution information of the instrument model. If the modal solution information meets the preset conditions, model optimization is performed on the area to be optimized according to the modal solution information and response basis conditions to obtain an optimized model, and the optimization is completed. Through the above solution, the structural characteristics of the instrument model are analyzed by combining static analysis and modal analysis, and simulation and optimization of the structural strength of the instrument model are carried out. By directly optimizing the local area to be optimized in the instrument model and then selecting the modal superposition method to optimize the area to be optimized, the accuracy of the simulation results and optimization results is improved while reducing the calculation amount, and the efficiency and accuracy of the simulation and optimization are improved. Moreover, using the response basis conditions for model optimization can also optimize the weight of the automotive instrument, so as to reduce the weight of the automotive instrument while improving the overall strength of the automotive instrument.

[0042] Other beneficial effects of the present invention will be described in the specific implementation manners through the introduction of specific technical features and technical solutions. Those skilled in the art should be able to understand the beneficial technical effects brought by the technical features and technical solutions through the introduction of these technical features and technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. In the drawings:

[0044] Figure 1 is a schematic flow chart of a method for optimizing automotive instrument simulation disclosed in this embodiment;

[0045] Figure 2 is a schematic diagram of an instrument model marked with the area to be optimized disclosed in this embodiment;

[0046] Figure 3 is a schematic diagram of the model of the area to be optimized before optimization disclosed in this embodiment;

[0047] Figure 4 is a schematic diagram of the model of the area to be optimized after structural optimization disclosed in this embodiment;

[0048] Figure 5 is a schematic diagram for comparing the model of the area to be optimized before optimization and after iterative optimization disclosed in this embodiment;

[0049] Figure 6 is a schematic structural diagram of an automotive instrument simulation optimization device disclosed in this embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] The present invention will be described below based on the embodiments, but the present invention is not limited to these embodiments. In the following detailed description of the present invention, some specific details are described in detail. In order to avoid obscuring the essence of the present invention, well-known methods, processes, procedures, and components are not described in detail.

[0051] In addition, those of ordinary skill in the art should understand that the accompanying drawings provided here are for illustrative purposes only, and the drawings are not necessarily drawn to scale.

[0052] Unless the context clearly requires otherwise, the words "including", "comprising", and similar words throughout the specification and claims should be interpreted as including rather than exclusive or exhaustive; that is, the meaning of "including but not limited to".

[0053] In the description of the present invention, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "a plurality" is two or more.

[0054] In order to improve the accuracy of the analysis results while simplifying the simulation computation amount and optimize the product quality, this embodiment discloses an optimization method for automotive instrument simulation. Please refer to Figure 1 , Figure 1 which is a schematic flow chart of an optimization method for automotive instrument simulation disclosed in this embodiment. The optimization method for automotive instrument simulation includes: steps S100 to S600, where:

[0055] Step S100, obtain the instrument model of the automotive instrument to be analyzed. In this embodiment, obtain the instrument model of the automotive instrument that needs to be simulated and analyzed. Among them, the format of the instrument model of the instrument to be analyzed can be the stp format. The instrument model is the original model of the automotive instrument to be analyzed, that is, the design model including the overall view and detailed design of the automotive instrument to be analyzed.

[0056] Step S200, obtain the damaged model of the automotive instrument to be optimized. Among them, the damaged model is the model obtained by scanning after a modal test on the sample of the automotive instrument to be optimized, and the sample of the automotive instrument to be optimized is produced based on the instrument model. In this embodiment, a sample can be made based on the automotive instrument model to be optimized and a modal test is performed on the sample. If the sample is damaged during the modal test, the damaged model can be obtained through reverse engineering. In the specific implementation process, the damaged model corresponding to the sample can be obtained by scanning.

[0057] In the specific implementation process, the process of the modal test can be, for example: First, select a suitable type of test rack according to the shape of the automotive instrument to simulate the installation state of the automotive instrument. Then, perform a modal test on the automotive instrument to simulate whether the connection of the automotive instrument will break or be damaged under the actual installation conditions. For example, if it is found that the automotive instrument is damaged during the modal test, analyze the cause of the damage at the damaged part and draw up a simulation plan for the cause of the damage to determine the simulation direction. Drawing up a simulation plan for the cause of the damage enables the simulation plan to specifically solve the cause of the damage, thereby clarifying the simulation direction and reducing the workload of the simulation. Only the results around the damaged position are optimized, which also enables the cost of modifying the mold to be reduced when the automotive instrument has been put into production. For example, during the modal test, it is found that the connection between the installation point of the instrument rear shell and the main body is weak, and the upper installation point is damaged first when receiving the first excitation, resulting in the number of installation points changing from four to three when receiving the second excitation, affecting the connection and support strength, and the structure around the lower installation point cannot withstand the longitudinal excitation and breaks.

[0058] Step S300: Compare the differences between the instrument model and the damaged model to determine the area to be optimized within the instrument model. The area to be optimized includes the areas where the instrument model and the damaged model are inconsistent. In this embodiment, the instrument model and the damaged model can be overlapped and compared to determine the areas where they are inconsistent, and these inconsistent areas are used as the areas to be optimized. Please refer to Figure 2 , Figure 2 which is a schematic diagram of the instrument model with the area to be optimized marked in this embodiment. Among them, the area boxed by the square is the area to be optimized obtained through comparison. It can be understood that Figure 2 the marking of the area to be optimized on the instrument model in

[0059] is only for the convenience of explaining this solution. In actual application, the area to be optimized may not be marked, or different colors can be used for differentiation marking, etc., which is not limited here. For example, for the automotive instrument housing, its material is usually a plastic material, such as PC + ABS. After comparison, the shapes of the instrument model and the damaged model have not deformed. The difference between the instrument model and the damaged model is that in the damaged model, the automotive instrument housing is broken. Then, the area corresponding to the broken position in the instrument model is determined as the area to be optimized, so as to optimize the local structure of the instrument model.

[0060] Step S310: Obtain the broken surfaces and / or edges in the damaged model. In this embodiment, after scanning the damaged sample, the damaged model can be obtained, and some fragmented surfaces and edges that are difficult to mesh can be determined through the damaged model.

[0061] Step S320, merge the fragmented surfaces at corresponding positions in the instrument model and / or delete the edges at corresponding positions in the instrument model to simplify the instrument model. In this embodiment, for fragmented surfaces, the fragmented surfaces at the corresponding positions in the instrument model can be found corresponding to the fragmented surfaces in the damaged model, and then the fragmented surfaces at the corresponding positions in the instrument model can be directly merged to simplify the model. For edges, the edges at the corresponding positions in the instrument model can be found corresponding to the edges in the damaged model, and then the edges at the corresponding positions in the instrument model can be deleted to simplify the model. It can be understood that in the actual process of model simplification, only fragmented surface merging can be performed, only edge deletion can be performed, or both fragmented surface merging and edge deletion can be performed. These fragmented surfaces and edges have little impact on the structure of the instrument model, and when performing static analysis and modal analysis, it is difficult to draw meshes for some irregular edges, which may affect the accuracy of the simulation analysis. Therefore, in order to reduce the complexity of the model, reduce the computational workload of the simulation analysis while ensuring the accuracy of the simulation analysis, these fragmented surfaces and edges can be simplified.

[0062] In an alternative embodiment, after the model is simplified, the model is modified according to the original dimensions of the sample on the simplified model. For example, rounded corners with the original dimensions can be added to the simplified model, which can avoid the loss of features in the simplified model caused by model simplification, thereby ensuring the accuracy during simulation analysis and structural optimization.

[0063] Step S400, perform parametric setting on the area to be optimized in the instrument model. The parametric setting includes setting the dimensions of the area to be optimized. In this embodiment, when performing parametric setting, either one or more dimension values of the area to be optimized or the dimension range of the area to be optimized can be set. By performing local parametric setting on the area to be optimized, rapid calculation for different parameters of the area to be optimized can be achieved, thereby improving the efficiency of the simulation analysis.

[0064] Step S500, perform static analysis and modal analysis on the instrument model in sequence based on preset optimization parameters to obtain the modal solution information of the instrument model, where the preset optimization parameters include mesh generation parameters, static analysis parameters, and modal analysis parameters. In this embodiment, static analysis and modal analysis are performed on the instrument model in sequence based on the preset optimization parameters to obtain the modal solution information of the instrument model. Static analysis is mainly used to simulate the actual installation position and fixing method of the automotive instrument to obtain the static solution result of the simulated automotive instrument in the actual installation scenario, and then this static solution result is used as one of the parameters for modal analysis of the instrument model. By combining the two analysis methods of static analysis and modal analysis, the accuracy of the simulation analysis result is improved.

[0065] In order to improve the accuracy of the simulation analysis results, in an alternative embodiment, step S500 includes steps S501 to S503, where:

[0066] Step S501, perform model mesh division on the instrument model using the mesh division parameters to obtain a mesh model. In this embodiment, the mesh division parameters include the maximum size of the mesh element, the resolution coefficient, and the feature clearance size. Among them, the maximum size of the mesh element can be, for example, 5 mm, the adaptive resolution coefficient of the mesh division can be, for example, 7, and the minimum feature clearance size can be, for example, 0.1 mm. In the specific implementation process, a simulation software can be used for mesh division. When using the simulation software for mesh division, parameters such as the physical preference of the mesh division, the smooth quality of the mesh connection, and the mesh quality error limit value can be set.

[0067] Step S502, perform a static solution on the mesh model based on the static analysis parameters to obtain a static solution result, where the static analysis parameters include the gravity parameter, the connection point degree-of-freedom constraint parameter, and the structural analysis parameter. In this embodiment, the static analysis is to simulate the position and fixing method of the automotive instrument during actual installation and apply gravity to the automotive instrument. When performing static analysis, it is necessary to preset the material properties of the automotive instrument at the corresponding positions of the instrument model in advance, such as density, elastic modulus, etc. In addition, it is also necessary to establish the connection relationship between each component in the instrument model to simulate the actual state of the instrument model.

[0068] In the specific implementation process, the gravity parameter can be the gravity load of the instrument model. By setting the gravity parameter, the static state of the automotive instrument when affected by the gravity factor after actual installation can be simulated. The connection point degree-of-freedom constraint parameter can be the displacement degree of freedom at the connection of the automotive instrument. For example, remote displacements can be added at the four positions A, B, C, and D of the instrument model respectively to limit the degree of freedom of the connection point. For example, for position A, it can be set to translate in the Y and Z directions and rotate in the X direction; for position B, it can be set to translate in the Z direction and rotate in the X and Y directions; for position C, it can be set to translate in the Y direction and rotate in the X and Z directions; for position D, it has all degrees of freedom. The structural analysis parameter can be the parameter used during static analysis, such as the initial substep, the minimum substep, and the maximum substep, etc.

[0069] Step S503: Perform prestressed modal analysis on the mesh model based on the modal analysis parameters and the static solution results to obtain modal solution information. Here, the modal analysis parameters include the maximum modal order and the frequency range. In this embodiment, prestressed modal analysis means that the static solution results can be applied to the modal analysis in the form of prestress to conduct modal analysis in combination with the results of static analysis, so as to make the results of simulation analysis more accurate. In the specific implementation process, the maximum modal order can be 200, for example, and the frequency range can be 0 - 2000 Hz, for example. Through modal solution, modal solution information can be obtained. For example, the first-order modal vibration modes of the instrument model in the X, Y, and Z directions can be obtained.

[0070] When performing mesh division, in order to improve the accuracy of mesh division and ensure the accuracy of simulation analysis, in an alternative embodiment, step S501 includes step S5011 and step S5012, where:

[0071] Step S5011: Perform model mesh division on the instrument model using the mesh division parameters to obtain a first mesh model. In this embodiment, the instrument model is subjected to model mesh division using the mesh division parameters to obtain a first mesh model. In the first mesh model, the meshes of each component in the instrument model conform to the same mesh division rule.

[0072] Step S5012: Obtain the sheet-like structures in the instrument model and locally refine the meshes of the sheet-like structures to obtain a second mesh model. In this embodiment, the sheet-like structures can be structures such as glass, TFT, circuit boards, film materials, and light guide plates, etc. The meshes of the sheet-like structures are locally refined to ensure the accuracy of the simulation results. That is to say, in the second mesh model, there are two mesh division rules. The meshes of the sheet-like structures are locally refined to increase the mesh density of the divided meshes; while for the non-sheet-like structures, they are divided according to the mesh division parameters.

[0073] In order to improve the accuracy of the simulation results, in an alternative embodiment, step S501 further includes:

[0074] Step S5013: Conduct mesh independence analysis on the second mesh model to determine the optimized mesh density, and adjust the second mesh model according to the optimized mesh density. In this embodiment, after the mesh division is completed, in order to avoid stress singularities caused by poor mesh quality during the mesh division process, mesh independence analysis can be performed to determine an optimized mesh density, and then the second mesh model is adjusted according to the optimized mesh density, so that the finally obtained mesh model can perform accurate simulation analysis and improve the accuracy of the simulation analysis results.

[0075] Step S600: If the modal solution information meets the preset conditions, perform structural optimization on the area to be optimized according to the modal solution information and the response basis conditions to obtain an optimized model. The response basis conditions include the mass retention percentage of the area to be optimized. In this embodiment, when the modal solution information meets the preset conditions, that is, when the instrument strength of the automotive instrument meets the requirements, structural optimization is then carried out. When performing structural optimization, only local structural optimization is performed on the area to be optimized, which can not only reduce the computational workload of structural optimization, but also avoid optimizing the key areas of the instrument model during structural optimization. The key areas can be areas such as connection points that require ensuring connection strength and shape, etc., thereby ensuring the accuracy of the final optimization result. Among them, structural optimization can refer to optimizing the size of the area to be optimized, such as reducing the size and weight of components within the area to be optimized.

[0076] In the specific implementation process, the modal superposition method can be adopted, that is, setting the modal solution information as the initial solution of structural optimization, and then performing structural optimization on the area to be optimized according to the structural optimization parameters and the response basis conditions. Among them, the response basis conditions include the mass retention percentage of the area to be optimized. The mass retention percentage can be the ratio of the mass of the area to be optimized after optimization to the mass before optimization, for example, it can be 85%. The structural optimization parameters can include the maximum number of iterations, the minimum normalized density, the convergence accuracy, and the penalty factor, etc. Among them, the maximum number of iterations can be 500, for example, the minimum normalized density can be 0.001, the convergence accuracy can be 0.001, and the penalty factor can be 3, for example.

[0077] To shorten the design and development process, in an alternative embodiment, after step S500, the automotive instrument simulation optimization method further includes:

[0078] Step S510: If the obtained modal solution information does not meet the preset conditions, adjust the parameters set in the parametric settings, and re-execute step S500. The preset conditions include the instrument strength. In this embodiment, if after modal analysis, the obtained modal solution result does not meet the preset conditions, for example, the overall strength of the instrument model does not meet the preset strength, it is considered that there is still a risk of fracture in the automotive instrument at this time. Then, the parameters set in the parametric settings will be adjusted to re-execute step S500, that is, calling the adjusted parameters to perform static analysis and modal analysis again until the final modal solution information meets the preset conditions. Through static analysis and modal analysis, only when the result of modal analysis meets the preset conditions, further structural optimization is carried out, which can avoid performing structural optimization on the model structure with insufficient strength, thereby reducing the workload of structural optimization, shortening the entire design and development process, and improving the design and development efficiency.

[0079] In an alternative embodiment, after step S600, the automotive instrument simulation optimization method further includes:

[0080] Step S700: Iteratively optimize the area to be optimized in the optimization model based on a preset optimization index, so that each parameter in the optimized optimization model meets the preset optimization index, where the optimization index includes at least one of an economic index, a demolding index, and a pouring index. In this embodiment, please refer to Figure 3 , Figure 4 and Figure 5 , Figure 3 is a schematic diagram of the model of the area to be optimized before optimization disclosed in this embodiment; Figure 4 is a schematic diagram of the model of the area to be optimized after structural optimization in this embodiment, Figure 5 is a schematic diagram of the comparison between the model of the area to be optimized before optimization and after iterative optimization in this embodiment. After obtaining the optimization model, it is also necessary to iteratively optimize the area to be optimized in the optimization model based on a preset optimization index, so that the optimized optimization model can meet the production requirements. For example, the economic index may include mold modification and / or production cost, the demolding index may include whether demolding is convenient, and the pouring index may include whether there is a mold closing line during pouring or high-pressure pouring. Since only the strength and weight of the area to be optimized are considered during structural optimization, that is, structural optimization only considers reducing the weight of the components in the area to be optimized while ensuring the strength of the area to be optimized, but the optimization model obtained based on this condition may not be convenient for production or affect aesthetics (such as Figure 4 shown), so after obtaining the optimization model, iterative optimization can be performed again based on a preset optimization index (such as Figure 5 shown), so that the optimized optimization model can be convenient for production and meet the requirements of aesthetics.

[0081] In an alternative embodiment, the model can be tested and verified again after obtaining the optimized optimization model to determine the matching degree between the test verification result and the simulation result. If the matching degree between the test verification result and the simulation result is within a preset threshold, it is considered that the result of this simulation optimization meets the optimization requirements, and the information such as the optimization direction of this simulation optimization can also be recorded to facilitate the optimization of other objects with the same damage cause.

[0082] This embodiment also discloses an automotive instrument simulation optimization device. Please refer to Figure 6 , Figure 6 is a schematic structural diagram of an automotive instrument simulation optimization device disclosed in this embodiment. The device includes:

[0083] A model acquisition module 100, configured to acquire an instrument model of an automotive instrument to be optimized.

[0084] The damage acquisition module 200 is configured to acquire a damage model of the vehicle instrument to be optimized. The damage model is a model obtained by scanning a sample of the vehicle instrument to be optimized after a modal test. The sample of the vehicle instrument to be optimized is produced based on the instrument model.

[0085] The difference comparison module 300 is configured to compare the differences between the instrument model and the damage model, so as to determine the area to be optimized within the instrument model. The area to be optimized includes the area where the instrument model is inconsistent with the damage model.

[0086] The parameterization module 400 is configured to obtain the preset parameterization settings for the area to be optimized in the instrument model. The preset parameterization settings include setting the size of the area to be optimized.

[0087] The modal solution module 500 is configured to perform static analysis and modal analysis on the instrument model in sequence based on the preset optimization parameters and parameterization settings, so as to obtain the modal solution information of the instrument model. The preset optimization parameters include mesh division parameters, static analysis parameters, and modal analysis parameters.

[0088] The structure optimization module 600 is configured to, if the modal solution information meets the preset conditions, perform structure optimization on the area to be optimized according to the modal solution information and response basis conditions, so as to obtain an optimized model. The response basis conditions include the mass retention percentage of the area to be optimized, and the preset conditions include the instrument strength of the vehicle instrument to be optimized.

[0089] In an alternative embodiment, the device further includes a parameter adjustment module 510. The parameter adjustment module 510 is configured to, if the modal solution information does not meet the preset conditions, adjust the parameters set in the parameterization settings, and execute step S500.

[0090] According to the automotive instrument simulation optimization method, device, computer equipment and storage medium disclosed in the embodiments of the present invention, the method includes obtaining an instrument model of the automotive instrument to be analyzed; obtaining a damage model of the automotive instrument to be optimized, comparing the differences between the instrument model and the damage model to determine the area to be optimized within the instrument model, obtaining the preset parametric settings of the area to be optimized, and then performing static analysis and modal analysis on the instrument model in sequence based on the preset optimization parameters and the preset parametric settings to obtain the modal solution information of the instrument model. If the modal solution information meets the preset conditions, model optimization is performed on the area to be optimized according to the modal solution information and the response basis conditions to obtain an optimized model, thus completing the optimization. Through the above solution, the structural characteristics of the analyzed instrument model are combined with static analysis and modal analysis to perform simulation and optimization on the structural strength of the instrument model. Through local direct optimization design of the area to be optimized in the instrument model, and then selecting the modal superposition method to optimize the area to be optimized, the calculation amount is reduced while the accuracy of the simulation result and the optimization result is improved, and the efficiency and accuracy of the simulation optimization are improved. Moreover, using the response basis conditions for model optimization can also optimize the weight of the automotive instrument, so as to reduce the weight of the automotive instrument while improving the overall strength of the automotive instrument.

[0091] In addition, the present invention also provides a computer-readable storage medium, such as a chip, optical disc, etc. An execution program is stored on the computer-readable storage medium, and when the execution program is executed, it implements the method described in any one of the above.

[0092] It should be noted that the computer-readable storage medium described in the embodiments of the present disclosure is not limited to the above-mentioned given embodiments. For example, it can also be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection with 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the embodiments of the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or component.

[0093] Those skilled in the art can understand that, on the premise of no conflict, the above-mentioned preferred solutions can be freely combined and superimposed. Among them, the flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and this module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions. The numbering of each step in this article is only for convenience of description and reference, and is not used to limit the order before and after. The specific execution order is determined by the technology itself, and those skilled in the art can determine various permitted and reasonable orders according to the technology itself.

[0094] It should be noted that in the present invention, step numbers (letter or number numbers) are used to refer to certain specific method steps only for the purpose of convenient description and brevity, and by no means to limit the order of these method steps by letters or numbers. Those skilled in the art can understand that the order of relevant method steps should be determined by the technology itself and should not be unduly restricted due to the existence of step numbers. Those skilled in the art can determine various permitted and reasonable step orders according to the technology itself.

[0095] Those skilled in the art can understand that, on the premise of no conflict, the above-mentioned preferred solutions can be freely combined and superimposed.

[0096] It should be understood that the above embodiments are merely exemplary and not restrictive. Without departing from the basic principles of the present invention, various obvious or equivalent modifications or substitutions made by those skilled in the art to the above details will be included within the scope of the claims of the present invention.

Claims

1. An automotive instrument simulation optimization method, characterized in that, The method includes: Step S100, obtaining the instrument model of the vehicle instrument to be optimized; Step S200, obtaining the damage model of the vehicle instrument to be optimized, where the damage model is a model obtained by scanning the sample of the vehicle instrument to be optimized after a modal test, and the sample of the vehicle instrument to be optimized is produced based on the instrument model; Step S300, comparing the differences between the instrument model and the damaged model to determine the area to be optimized within the instrument model, and the area to be optimized includes the area where the instrument model is inconsistent with the damaged model; Step S400, obtaining the preset parametric settings for the area to be optimized in the instrument model, and the preset parametric settings include setting the size of the area to be optimized; Step S500, performing static analysis and modal analysis on the instrument model in sequence based on the preset optimization parameters and the parametric settings to obtain the modal solution information of the instrument model, where the preset optimization parameters include mesh division parameters, static analysis parameters, and modal analysis parameters; Step S600, if the modal solution information meets the preset conditions, performing structural optimization on the area to be optimized according to the modal solution information and the response basis conditions to obtain an optimized model, where the response basis conditions include the mass retention percentage of the area to be optimized, and the preset conditions include the instrument strength of the vehicle instrument to be optimized.

2. The automotive instrument simulation optimization method according to claim 1, characterized in that After step S500, the method further includes: Step S510, if the modal solution information does not meet the preset conditions, adjusting the parameters set in the parametric settings, and executing step S500.

3. The automotive instrument simulation optimization method according to claim 1, characterized in that Between step S300 and step S400, the method further includes: Step S310, obtaining the broken surfaces and / or edge lines in the damaged model; Step S320, merging the broken surfaces at the corresponding positions in the instrument model, and / or deleting the edge lines at the corresponding positions in the instrument model to simplify the instrument model.

4. The automotive instrument simulation optimization method according to claim 1, wherein, The step S500 includes: Step S501, performing model mesh division on the instrument model using the mesh division parameters to obtain a mesh model; Step S502, performing static solution on the mesh model based on the static analysis parameters to obtain a static solution result, where the static analysis parameters include gravity parameters, connection point degree of freedom constraint parameters, and structural analysis parameters; Step S503, performing prestressed modal analysis on the mesh model based on the modal analysis parameters and the static solution result to obtain modal solution information, where the modal analysis parameters include the maximum modal order and frequency range.

5. The method for optimizing automotive instrument simulation according to claim 4, wherein The step S501 includes: Step S5011, performing model mesh division on the instrument model using the mesh division parameters to obtain a first mesh model; Step S5012, obtaining the sheet-like structure in the instrument model, and locally encrypting the mesh of the sheet-like structure to obtain a second mesh model.

6. The automotive instrument simulation optimization method according to claim 1, wherein The step S600 includes: Step S601: Optimize the structure of the area to be optimized according to the modal solution information and the structure optimization parameters to obtain a structure model, where the structure optimization parameters include the maximum number of iterations, the convergence accuracy, and the penalty factor; Step S602: Optimize the structure of the structure model according to the response basis condition to obtain an optimized model, where the response basis condition includes the mass retention percentage of the area to be optimized.

7. The method for optimizing the simulation of an automotive instrument according to claim 1, characterized in that, After the step S600, the method further includes: Step S700: Iteratively optimize the area to be optimized in the optimized model based on a preset optimization index, so that each parameter in the optimized optimized model meets the preset optimization index, where the optimization index includes at least one of an economic index, a demolding index, and a pouring index.

8. An automobile instrument simulation optimization device, characterized in that, The device includes: A model acquisition module (100) for acquiring an instrument model of an automobile instrument to be optimized; A damage acquisition module (200) for acquiring a damage model of the automobile instrument to be optimized, where the damage model is a model obtained by scanning after a modal test on a sample of the automobile instrument to be optimized, and the sample of the automobile instrument to be optimized is produced based on the instrument model; A difference comparison module (300) for comparing the differences between the instrument model and the damage model to determine an area to be optimized within the instrument model, where the area to be optimized includes the area where the instrument model and the damage model are inconsistent; A parameterization module (400) for acquiring a preset parameterization setting for the area to be optimized in the instrument model, where the preset parameterization setting includes setting the size of the area to be optimized; A modal solution module (500) for sequentially performing static analysis and modal analysis on the instrument model based on preset optimization parameters and the parameterization setting to obtain modal solution information of the instrument model, where the preset optimization parameters include mesh division parameters, static analysis parameters, and modal analysis parameters; A structure optimization module (600) for, if the modal solution information meets a preset condition, optimizing the structure of the area to be optimized according to the modal solution information and the response basis condition to obtain an optimized model, where the response basis condition includes the mass retention percentage of the area to be optimized, and the preset condition includes the instrument strength of the automobile instrument to be optimized.

9. A computer device, characterized in that, including: Performing simulation optimization of an automobile instrument by using the method according to any one of claims 1-7, or including the device according to claim 8.

10. A computer storage medium, on which a computer program is stored, characterized in that, A computer program stored in a storage medium is used to be executed to implement the method for simulation optimization of an automobile instrument according to any one of claims 1-7.

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