Rim optimization design method and device, computer equipment and storage medium

Abstract

The invention discloses a rim optimization design method and device, computer equipment and a storage medium. The method comprises the steps that structural parameter identification is conducted on an original rim model, key structural parameters are determined, and rim parameterized data are obtained; finite element analysis is conducted on the rim parameterized data, and target rim performance corresponding to the original rim model is determined; if the target rim performance does not meet the preset performance requirement, updating rim structure parameters of the original rim model, and repeatedly performing structure parameter identification on the original rim model to obtain rim parameterization data corresponding to the original rim model; and if the target rim performance meets the preset performance requirement, determining the original rim model as a target rim model. According to the method, a better rim model is obtained in an automatic adjustment mode, the human participation degree is reduced, the working efficiency of rim performance analysis and the model accuracy are improved, resources can be saved, the cost can be reduced, and economic benefits can be maximized.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a rim optimization design method, device, computer equipment and storage medium. Background Art

[0002] The wheel rim assembly directly bears the impact load from the road surface, and the performance of the wheel rim has a significant impact on the road noise performance and fatigue durability of the vehicle. In the early stages of vehicle development, simulation methods are usually used to analyze the wheel rim performance, and the analyzed wheel rim performance is compared and optimized with the target value to avoid the huge cost caused by repeated design verification in the later stage.

[0003] In the prior art, when analyzing the performance of a rim, the 3D model of the rim is imported into the finite element pre-processing software, the finite element modeling and analysis are manually performed, the finite element model is exported, the exported finite element model is submitted to the solver, the key parameters are identified by the finite element post-processing software, and then the target rim performance of interest, such as the mode, rim lateral stiffness and strength, is obtained through relevant calculations; when the target rim performance does not meet the performance requirements, the finite element model is manually modified and the calculation is submitted until the target rim performance meets the performance requirements and a roughly qualified calculation model is obtained; finally, the 3D model of the rim is manually modified according to the roughly qualified calculation model. In the prior art, the entire analysis process involves multiple software, the process is complicated, and manual modification operations are required at each stage, and usually multiple rounds of analysis, comparison and iteration are required, and the efficiency and standardization are extremely low. That is to say, in the process of rim performance analysis, manual operation not only reduces the work efficiency of the analysis, but also reduces the accuracy of the analysis. Therefore, how to improve the work efficiency and accuracy of rim performance analysis is a problem that needs to be solved in the process of rim optimization design. Summary of the invention

[0004] The embodiments of the present invention provide a rim optimization design method, device, computer equipment and storage medium to solve the problem of how to improve the work efficiency and accuracy of rim performance analysis.

[0005] A rim optimization design method, comprising:

[0006] Performing structural parameter identification on the original rim model, determining key structural parameters, deleting rim structural parameters other than the key structural parameters, and acquiring rim parameterized data corresponding to the original rim model;

[0007] Performing finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model;

[0008] If the target rim performance does not meet the preset performance requirements, the rim structural parameters of the original rim model are updated, the structural parameter identification of the original rim model is repeatedly performed, the key structural parameters are determined, the rim structural parameters other than the key structural parameters are deleted, and the rim parameterized data corresponding to the original rim model is obtained;

[0009] If the target rim performance meets the preset performance requirement, the original rim model is determined as the target rim model.

[0010] Preferably, performing finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model includes:

[0011] Performing finite element analysis on the rim parameterized data corresponding to the original rim model to generate a rim finite element calculation file;

[0012] The rim finite element calculation file is automatically solved to obtain target rim performance.

[0013] Preferably, the performing finite element analysis on the rim parameterized data to generate a rim finite element calculation file comprises:

[0014] Performing geometric cleaning on the rim parameterized data to obtain a first rim model;

[0015] Meshing the first wheel rim model to obtain at least two target mesh models corresponding to the first wheel rim model;

[0016] Connecting at least two of the target mesh models and assigning material properties to obtain a second wheel rim model;

[0017] Perform finite element analysis on the second wheel rim model to generate a wheel rim finite element calculation file.

[0018] Preferably, said meshing the first rim model to obtain at least two target mesh models corresponding to the first rim model includes:

[0019] Performing two-dimensional mesh division on the first wheel rim model to obtain at least two two-dimensional mesh models corresponding to the first wheel rim model;

[0020] If the two-dimensional mesh model meets the preset mesh quality requirement, a three-dimensional mesh model is generated based on the two-dimensional mesh model, and the three-dimensional mesh model is determined as the target mesh model corresponding to the first rim model.

[0021] Preferably, automatically solving the rim finite element calculation file to obtain target rim performance includes:

[0022] Automatically solving the wheel rim finite element calculation file to obtain a calculation result file;

[0023] Extracting parameters from the calculation result file to obtain target design parameters;

[0024] The target design parameters are processed to obtain target rim performance.

[0025] Preferably, the processing of the target design parameters to obtain the target rim performance further includes:

[0026] Extract parameters from the calculation result file to obtain the model weight, response point frequency, and Y-axis acceleration response corresponding to the response point frequency;

[0027] Based on the response point frequency and the Y-direction acceleration response corresponding to the response point frequency, a target two-dimensional array is formed;

[0028] Based on the target two-dimensional array, selecting the resonance peak frequency and the anti-resonance peak frequency;

[0029] The lateral stiffness of the rim is obtained based on the model weight, the resonance peak frequency and the anti-resonance peak frequency.

[0030] Preferably, after determining the target rim performance corresponding to the original rim model, the rim optimization design method further comprises:

[0031] If the target rim performance does not meet the preset performance requirements, obtaining the current iteration number;

[0032] If the current number of iterations is less than the preset number of iterations, the rim structural parameters of the original rim model are updated, the structural parameter identification of the original rim model is repeatedly performed, key structural parameters are determined, rim structural parameters other than the key structural parameters are deleted, and rim parameterized data corresponding to the original rim model is obtained;

[0033] If the current number of iterations is not less than a preset number of iterations, the original wheel rim model is determined as the target wheel rim model.

[0034] A rim optimization design device, comprising:

[0035] A rim parameterized data acquisition module is used to identify structural parameters of the original rim model, determine key structural parameters, delete rim structural parameters other than the key structural parameters, and acquire rim parameterized data corresponding to the original rim model;

[0036] A target rim performance acquisition module is used to perform finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model;

[0037] A first judgment module is used for updating the rim structural parameters of the original rim model if the target rim performance does not meet the preset performance requirements, repeatedly performing the structural parameter identification of the original rim model, determining the key structural parameters, deleting the rim structural parameters other than the key structural parameters, and obtaining the rim parameterized data corresponding to the original rim model;

[0038] The second judgment module is used to determine the original rim model as the target rim model if the target rim performance meets the preset performance requirement.

[0039] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned wheel rim optimization design method when executing the computer program.

[0040] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned wheel rim optimization design method is implemented.

[0041] The above-mentioned rim optimization design method, device, computer equipment and storage medium identify the structural parameters of the original rim model, determine the key structural parameters, and obtain the rim parameterized data corresponding to the original rim model with only the key structural parameters marked by deleting the rim structural parameters other than the key structural parameters, and delete the rim structural parameters that are not related to the rim performance, so as to facilitate the subsequent improvement of the efficiency of finite element analysis of the rim parameterized data corresponding to the original rim model; perform finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model, without the need for manual finite element analysis, reduce human operation, not only improve the efficiency of obtaining the target rim performance, but also reduce the error of the target rim performance, so that the determined target rim performance has a higher accuracy. When the target rim model does not meet the preset performance requirements, the rim structural parameters in the original rim model are automatically optimized and updated, the optimization is highly targeted, and unrealistic optimization updates and redundant work are avoided, which can improve work efficiency and model accuracy, save resources and reduce costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0043] Figure 1 is a flow chart of a rim optimization design method according to an embodiment of the present invention;

[0044] Figure 2 is another flow chart of the rim optimization design method in one embodiment of the present invention;

[0045] Figure 3 is another flow chart of the rim optimization design method in one embodiment of the present invention;

[0046] Figure 4 is another flow chart of the rim optimization design method in one embodiment of the present invention;

[0047] Figure 5 is another flow chart of the rim optimization design method in one embodiment of the present invention;

[0048] Figure 6 is another flow chart of the rim optimization design method in one embodiment of the present invention;

[0049] Figure 7 is another flow chart of the rim optimization design method in one embodiment of the present invention;

[0050] Figure 8 is a schematic diagram of a rim optimization design device in one embodiment of the present invention;

[0051] Fig. 9 is a schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] The rim optimization design method provided by the embodiment of the present invention can be applied in a computer device to achieve the purpose of improving the working efficiency and accuracy of rim performance analysis.

[0054] In one embodiment, if Figure 1As shown, a rim optimization design method is provided, which is applied in Fig. 9 The computer device in the example is used as an example to illustrate, including the following steps:

[0055] S101: performing structural parameter identification on the original rim model, determining key structural parameters, deleting rim structural parameters other than the key structural parameters, and obtaining rim parameterized data corresponding to the original rim model;

[0056] S102: performing finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model;

[0057] S103: if the target rim performance does not meet the preset performance requirements, the rim structural parameters of the original rim model are updated, the structural parameter identification of the original rim model is repeatedly performed, the key structural parameters are determined, the rim structural parameters other than the key structural parameters are deleted, and the rim parameterized data corresponding to the original rim model is obtained;

[0058] S104: If the target rim performance meets the preset performance requirement, the original rim model is determined as the target rim model.

[0059] The original rim model refers to the rim model before the rim structural parameters are updated. Structural parameter identification refers to the process of identifying all rim structural parameters in the original rim model to obtain key structural parameters that affect the rim performance. The rim structural parameters refer to the parameters that constitute the original rim model. Key structural parameters refer to the parameters in the rim structural parameters that can affect the rim performance. Rim parameterized data refers to the original rim model with only key structural parameters marked.

[0060] As an example, in step S101, the computer device performs structural parameter identification on the acquired original rim model to obtain key structural parameters affecting the rim performance, deletes the rim structural parameters other than the key structural parameters in the original rim model, annotates the obtained key structural parameters in the original rim model from which the rim structural parameters other than the key structural parameters are deleted, and obtains rim parameterized data corresponding to the original rim model. In this example, the computer device obtains the original rim model established in the three-dimensional software, imports the original rim model into the corresponding recognition model, performs structural parameter identification on the rim structural parameters in the original rim model, and obtains the key structural parameters affecting the rim performance. Subsequently, the rim structural parameters other than the key structural parameters in the original rim model are cleared to obtain the original rim model annotated with only the key structural parameters, and the original rim model annotated with only the key structural parameters is determined as the rim parameterized data corresponding to the original rim model. Among them, the three-dimensional software includes but is not limited to CAD software and CATIA software. The recognition model includes but is not limited to a rim structure-performance big database training model and / or a big data neural network prediction model.

[0061] For example, the computer device controls the CATIA software to generate an original wheel rim model with a file identifier of *.CATPart, runs the wheel rim structure-performance database training model, identifies the structural parameters of the original wheel rim model with a file identifier of *.CATPart, and obtains the key structural parameters that affect the wheel rim performance. Subsequently, the wheel rim structural parameters other than all the key structural parameters in the original wheel rim model with a file identifier of *.CATPart are cleared, and only the key structural parameters are marked in the original wheel rim model with a file identifier of *.CATPart, and the wheel rim parameterized data corresponding to the original wheel rim model is obtained.

[0062] In this example, the key structural parameters are determined, and the rim structural parameters other than the key structural parameters are deleted to obtain the rim parametric data corresponding to the original rim model with only the key structural parameters marked. The rim structural parameters that are not related to obtaining the rim performance are deleted to facilitate the subsequent improvement of the efficiency of finite element analysis of the rim parametric data corresponding to the original rim model.

[0063] The finite element analysis refers to the process of creating and analyzing finite element working conditions based on the rim parametric data. The target rim performance refers to the rim performance obtained by performing finite element analysis on the rim parametric data.

[0064] As an example, in step S102, after obtaining the rim parametric data that only marks the key structural parameters that affect the rim performance, the computer device performs finite element analysis on the rim parametric data to obtain the rim performance corresponding to the rim parametric data, and uses the rim performance as the target rim performance. In this example, the computer device processes the rim parametric data to obtain a model corresponding to the rim parametric data, creates a finite element working condition for the obtained model and performs finite element analysis to obtain the target rim performance. In this example, the rim parametric data is subjected to finite element analysis to determine the target rim performance corresponding to the original rim model. This method does not require manual finite element analysis, reduces manual operation, and not only improves the efficiency of obtaining the target rim performance, but also can reduce the error of the target rim performance, so that the determined target rim performance has a higher accuracy.

[0065] The preset performance requirement refers to the preset conditions used to determine whether the target rim performance meets the design requirements. Understandably, when performing rim optimization design, the target rim performance obtained may have large errors, and it is necessary to determine whether the target rim performance obtained meets the preset performance requirements to determine whether the original rim model corresponding to the target rim performance can be used as the target rim model for rim optimization design. The target rim model refers to a rim model that can be used for rim optimization design.

[0066] As an example, in step S103, the computer device determines whether the target rim performance meets the preset performance requirements. When it is determined that the target rim performance does not meet the preset performance requirements, a set of optimized rim structural parameters are re-acquired, and based on the optimized rim structural parameters, the original rim model is updated, so that the rim structural parameters in the original rim model are updated to the optimized rim structural parameters, and the structural parameter identification of the original rim model is repeatedly performed to obtain the rim parameterized data corresponding to the original rim model, and the finite element analysis is performed on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model, that is, steps S101 and S102 are repeated until the target rim performance meets the preset performance requirements. In this example, when the computer device determines that the error between the target rim performance and the preset performance requirement is large, it determines that the target rim performance does not meet the preset performance requirement. At this time, the optimized rim structure parameters are obtained, and the parameters of the original rim model are updated based on the optimized rim structure parameters. For example, the optimized rim structure parameters are added to the original rim model to achieve parameter updating of the original rim model based on the optimized rim structure parameters. After the parameters of the original rim model are updated, step S101 and step S102 are continued until the target rim performance meets the preset performance requirement.

[0067] For example, when the computer device determines that the target rim performance is the rim lateral stiffness, it queries the system database, obtains the preset lateral stiffness, and determines the error value between the rim lateral stiffness corresponding to the target rim performance and the preset lateral stiffness. When the error value is within an unpredictable range, it is determined that the rim lateral stiffness corresponding to the target rim performance does not meet the preset performance requirements. At this time, the optimized rim structure parameters are obtained, and the parameters of the original rim model are updated based on the optimized rim structure parameters. Steps S101 and S102 are continued until the rim lateral stiffness corresponding to the target rim performance meets the preset performance requirements.

[0068] In this example, it is determined whether the target rim performance meets the preset performance requirements. When the target rim model does not meet the preset performance requirements, the rim structure parameters in the original rim model are automatically optimized and updated. The optimization is highly targeted, avoids unrealistic optimization updates and redundant work, and can improve work efficiency.

[0069] As an example, in step S104, the computer device determines whether the target rim performance meets the preset performance requirements. When it is determined that the target rim performance meets the preset performance requirements, the original rim model corresponding to the target rim performance is determined as the target rim performance. In this example, when the computer device determines that the error between the target rim performance and the preset performance requirements is small, it determines that the target rim performance meets the preset performance requirements. At this time, the original rim model corresponding to the target rim performance is determined as the target rim model. The target rim performance and the target rim model are correspondingly stored in the system database.

[0070] For example, when the computer device determines that the target rim performance is the rim lateral stiffness, it queries the system database, obtains the preset lateral stiffness, and determines the error value between the rim lateral stiffness corresponding to the target rim performance and the preset lateral stiffness. When the error value is within a preset range, it is determined that the rim lateral stiffness corresponding to the target rim performance meets the preset performance requirements, and the original rim model corresponding to the rim lateral stiffness is used as the target rim model. The rim lateral stiffness that meets the preset conditions is stored in the system's rim structure-performance database corresponding to the target rim model for easy access and viewing at any time.

[0071] In this example, when it is determined that the target rim performance meets the preset performance requirements, the original rim model is determined as the target rim model, and a better rim model is obtained through automated judgment, reducing human participation. This not only improves work efficiency and model accuracy, but also saves resources, reduces costs, and maximizes economic benefits.

[0072] The rim optimization design method provided in this embodiment determines the key structural parameters, obtains the rim parameterized data corresponding to the original rim model with only the key structural parameters marked by deleting the rim structural parameters other than the key structural parameters, and deletes the rim structural parameters that are irrelevant to the rim performance, so as to facilitate the subsequent improvement of the efficiency of the finite element analysis of the rim parameterized data corresponding to the original rim model; the finite element analysis is performed on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model, without the need for manual finite element analysis, reducing human operations, not only improving the efficiency of obtaining the target rim performance, but also reducing the error of the target rim performance, so that the determined target rim performance has a higher accuracy. When the target rim model does not meet the preset performance requirements, the rim structural parameters in the original rim model are automatically optimized and updated, the optimization is highly targeted, and unrealistic optimization updates and redundant work are avoided, which can improve work efficiency and model accuracy, save resources, reduce costs, and maximize economic benefits.

[0073] In one embodiment, if Figure 2 As shown, step S102, i.e., performing finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model, includes:

[0074] S201: Perform finite element analysis on the rim parameterized data corresponding to the original rim model to generate a rim finite element calculation file;

[0075] S202: Automatically solving the wheel rim finite element calculation file to obtain target wheel rim performance.

[0076] The rim finite element calculation file refers to the file exported after the finite element analysis of the rim parametric data.

[0077] As an example, in step S201, the computer device performs finite element analysis on the rim parametric data corresponding to the original rim model, and generates a corresponding rim finite element calculation file after completing the finite element analysis. In this example, the computer device uses Tcl code to control the operation of the Hypermesh software, reads the rim parametric data generated in the three-dimensional software, processes the read rim parametric data, generates a corresponding model, performs finite element analysis on the model, and generates a rim finite element calculation file after completing the finite element analysis. In this example, the rim parametric data is subjected to finite element analysis to generate a rim finite element calculation file, and this process does not require manual participation, which can improve the accuracy and analysis efficiency of the finite element analysis.

[0078] As an example, in step S202, after determining to obtain the rim finite element calculation file, the computer device automatically solves the rim finite element calculation file to obtain the target rim performance. In this example, the computer device obtains the rim finite element calculation file, inputs the rim finite element calculation file into the solver for automatic solution, and obtains the automatic solution result. Among them, the solver can use the Nastran solver. The automatic solution result is analyzed and calculated to obtain the target rim performance. In this example, the rim finite element calculation file is automatically solved to obtain the target rim performance. This method does not require manual participation and can improve the accuracy and solution efficiency of the target rim performance. This method effectively connects the acquisition of the rim finite element calculation file and the automatic solution of the rim finite element calculation file in series, realizes the automatic solution of the rim finite element calculation file, and obtains the target rim performance without manual operation, which is convenient for improving work efficiency.

[0079] In this embodiment, finite element analysis is performed on the rim parameterized data to generate a rim finite element calculation file. This process does not require manual intervention, which can improve the accuracy and efficiency of the finite element analysis. The rim finite element calculation file is automatically solved to obtain the target rim performance. This process does not require manual intervention, which can improve the accuracy and efficiency of the target rim performance.

[0080] In one embodiment, if Figure 3 As shown, step S201, i.e., performing finite element analysis on the rim parameterized data to generate a rim finite element calculation file, includes:

[0081] S301: performing geometric cleaning on the rim parameterized data to obtain a first rim model;

[0082] S302: Meshing the first rim model to obtain at least two target mesh models corresponding to the first rim model;

[0083] S303: Connect at least two target mesh models and assign material properties to obtain a second rim model;

[0084] S304: Perform finite element analysis on the second rim model to generate a rim finite element calculation file.

[0085] Among them, geometric cleaning refers to the process of regularizing the original rim model in the rim parameterized data to facilitate subsequent meshing. Understandably, the rim parameterized data refers to the original rim model with only key structural parameters annotated, and the geometric cleaning of the original rim model makes the geometric shape of the original rim model more regular, so that the subsequent meshing is more regular. The first rim model refers to the rim model annotated with key structural parameters after geometric cleaning.

[0086] As an example, in step S301, the computer device performs geometric cleaning on the rim parametric data according to the preset geometric cleaning requirements to obtain the first rim model after geometric cleaning. In this example, the computer device automatically deletes the repeated faces of the original rim model in the rim parametric data, compresses the redundant lines and boundaries, and performs curvature recognition, performs geometric cleaning according to the curvature recognition result, so that the rim model after geometric cleaning meets the subsequent meshing requirements, which is convenient for subsequent meshing, and then uses the rim model after geometric cleaning as the first rim model.

[0087] The meshing refers to the process of dividing the first wheel rim model according to a certain mesh shape and mesh density. The target mesh model refers to the mesh model obtained after meshing the first wheel rim model.

[0088] As an example, in step S302, the computer device meshes the first rim model according to the preset meshing requirements to obtain at least two mesh models after meshing, performs quality inspection on the at least two mesh models after meshing, and determines the target mesh model. In this example, the computer device meshes the first rim model according to the preset meshing requirements to obtain at least two mesh models, performs mesh quality inspection on the mesh models obtained after meshing based on the preset mesh quality requirements, and when all mesh models meet the mesh quality requirements, the mesh model is used as the target mesh model. In this example, the first rim model is meshed to obtain the target mesh model, so that the subsequent finite element analysis is feasible.

[0089] The second wheel rim model refers to the wheel rim model obtained by processing the target mesh model.

[0090] As an example, in step S303, after obtaining at least two target mesh models, the computer device connects the target mesh models according to the connection rules of the actual hardware corresponding to the target mesh models, and assigns the preset material properties to the connected target mesh models to generate a second rim model. For example, when the computer device determines that the connection method between the target mesh models is bolt connection, it automatically identifies the bolt holes of the target mesh model, establishes rbe2 units at the bolt hole positions, forms a main node at the center point of the bolt hole based on the rbe2 units, and connects each target mesh model. After completing the automatic connection of the target mesh models, the computer device automatically establishes aluminum alloy materials and Psolid properties, and assigns aluminum alloy materials and Psolid properties to the connected target mesh models. Subsequently, the computer device establishes a whole vehicle coordinate system, automatically identifies the rim axis and adjusts the rim axis to be parallel to the Y direction of the whole vehicle coordinate system, automatically identifies the center nodes of the rbe2 units and standardizes the numbers, and generates a second rim model. In this example, at least two target mesh models are connected and assigned material properties to obtain a second rim model. In this example, at least two target mesh models are connected and assigned material properties to obtain a second rim model, which reduces manual participation and can improve work efficiency.

[0091] As an example, in step S304, the computer device performs finite element analysis on the second rim model and generates a rim finite element calculation file. In this example, the computer device automatically adds loads and analysis steps to the second rim model, implements finite element analysis of the second rim model, and generates a rim finite element calculation file. Wherein, the load refers to the excitation applied to the second rim model during the finite element analysis of the second rim model. The analysis step refers to the step of applying excitation to the second rim model according to a certain frequency increment. For example, after the computer device determines that the excitation point of the second rim model is the center point of the rbe2 unit, it automatically applies loads in the Y-axis direction of the excitation point multiple times according to the preset analysis steps with a certain frequency increment. The load can be a sinusoidal excitation with a frequency range of 1 to 1000 Hz and an amplitude of 1N, obtains the corresponding response, implements the finite element analysis of the second rim model, and generates the corresponding rim finite element calculation file according to the relationship between the applied load and the corresponding response obtained. In this example, finite element analysis is performed on the second rim model to obtain the rim finite element calculation file. This process does not require manual participation, which can improve the accuracy and efficiency of the finite element analysis and facilitate more accurate target rim performance obtained based on the rim finite element calculation file.

[0092] In this implementation, the rim parameterized data is geometrically cleaned to obtain a first rim model; the first rim model is meshed to obtain at least two target mesh models corresponding to the first rim model; the at least two target mesh models are model-connected and assigned material properties to obtain a second rim model; the second rim model is subjected to finite element analysis to generate a rim finite element calculation file. This process does not require manual participation, can improve the accuracy and efficiency of the finite element analysis, and facilitates more accurate target rim performance subsequently obtained based on the rim finite element calculation file.

[0093] In one embodiment, if Figure 4 As shown, step S302, i.e., meshing the first rim model to obtain at least two target mesh models corresponding to the first rim model, includes:

[0094] S401: performing two-dimensional mesh division on the first rim model to obtain at least two two-dimensional mesh models corresponding to the first rim model;

[0095] S402: If the two-dimensional mesh model meets the preset mesh quality requirement, a three-dimensional mesh model is generated based on the two-dimensional mesh model, and the three-dimensional mesh model is determined as a target mesh model corresponding to the first rim model.

[0096] The two-dimensional meshing refers to mapping the surface of the first wheel rim model into a two-dimensional parameter space for meshing. The two-dimensional mesh model refers to a model obtained by performing two-dimensional meshing on the first wheel rim model.

[0097] As an example, in step S401, the computer device maps the first rim model into a two-dimensional parameter space, meshes the first rim model mapped into the two-dimensional parameter space, implements two-dimensional meshing of the first rim model, and obtains at least two two-dimensional mesh models. For example, after obtaining the first rim model, the computer device sets the mesh type to triangle and the mesh size to 5 mm, and automatically performs two-dimensional meshing of the first rim model according to the mesh type and mesh size, to obtain at least two two-dimensional mesh models. In this example, the first rim model is meshed in two dimensions to obtain at least two two-dimensional mesh models corresponding to the first rim model, so as to facilitate the subsequent determination of whether the meshing meets the mesh quality requirements based on the two-dimensional mesh model.

[0098] The mesh quality requirement refers to the pre-set requirement for judging whether the two-dimensional mesh division is qualified. The three-dimensional mesh model refers to the mesh model generated by mapping the two-dimensional mesh model that meets the mesh quality requirement into the three-dimensional space.

[0099] As an example, in step S402, the computer device performs a mesh quality test on the two-dimensional mesh model to determine whether all the two-dimensional mesh models meet the mesh quality requirements. When it is determined that all the two-dimensional mesh models meet the mesh quality requirements, the two-dimensional mesh model is mapped to the three-dimensional space to generate a three-dimensional mesh model, and the three-dimensional mesh model is determined as the target mesh model corresponding to the first rim model. For example, when the computer device determines that all the two-dimensional mesh models meet the mesh quality requirements, the two-dimensional mesh model is automatically mapped to the three-dimensional space, a second-order tetrahedral unit is generated, the second-order tetrahedral unit is used as the three-dimensional mesh model, and the two-dimensional mesh model is automatically deleted. In this example, a three-dimensional mesh model is generated based on the two-dimensional mesh model that meets the mesh quality requirements, and the three-dimensional mesh model is determined as the target mesh model corresponding to the first rim model, thereby reducing manual participation and improving the efficiency of obtaining the target mesh model and the calculation accuracy.

[0100] In this embodiment, if the two-dimensional mesh model meets the mesh quality requirements, a three-dimensional mesh model is generated based on the two-dimensional mesh model, and the three-dimensional mesh model is determined as the target mesh model corresponding to the first rim model. This method reduces manual participation and improves the efficiency of obtaining the target mesh model and the calculation accuracy.

[0101] In another embodiment, after step S401, the rim optimization design method further includes:

[0102] If the two-dimensional mesh model does not meet the mesh quality requirements, the geometric cleaning of the rim parameterized data is continued to obtain the first rim model.

[0103] As an example, the computer device performs mesh quality detection on the two-dimensional mesh model to determine whether all the two-dimensional mesh models meet the mesh quality requirements. When it is determined that there are two-dimensional mesh models that do not meet the mesh quality requirements, the computer device continues to perform geometric cleaning on the rim parameterized data, obtains the first rim model, and meshes the first rim model until all the two-dimensional mesh models meet the mesh quality requirements, and obtains at least two target mesh models corresponding to the first rim model. In this example, when there are two-dimensional mesh models that do not meet the mesh quality requirements, the first rim model is re-acquired and the re-acquired first rim model is meshed until all the two-dimensional mesh models meet the mesh quality requirements, and at least two target mesh models corresponding to the first rim model are obtained. This process can be automatically implemented without manual participation, thereby improving the efficiency of obtaining the target mesh model and the calculation accuracy.

[0104] In one embodiment, if Figure 5 As shown, step S202, i.e. automatically solving the rim finite element calculation file to obtain the target rim performance, includes:

[0105] S501: Automatically solve the rim finite element calculation file to obtain a calculation result file;

[0106] S502: extracting parameters from the calculation result file to obtain target design parameters;

[0107] S503: Process the target design parameters to obtain target rim performance.

[0108] The calculation result file is a solution result file of the rim finite element calculation file, including target design parameters. The target design parameters refer to parameters used to calculate the target rim performance.

[0109] As an example, in step S501, after obtaining the rim finite element calculation file, the computer device inputs the rim finite element calculation file into the automatic solver, and automatically solves to obtain the calculation result file. The automatic solver includes but is not limited to the Nastran solver software. In this example, the rim finite element calculation file is automatically solved to obtain the calculation result file. This process can be solved automatically without manual participation, which can improve the solution efficiency and facilitate the subsequent acquisition of target design parameters based on the calculation result file.

[0110] As an example, in step S502, the computer device extracts parameters from the calculation result file to obtain the target design parameters for calculating the target rim performance. In this example, after the computer device obtains the calculation result file, it starts the result post-processing script file, reads the calculation result file according to the processing order of the result post-processing script file, and obtains the target design parameters for calculating the target rim performance, so that the target rim performance can be determined according to the target design parameters in the subsequent process to ensure the feasibility of the solution. Among them, the result post-processing script file is a script file for reading the calculation result file in a certain order. It can be understood that when reading the calculation result file, the result post-processing script file reads it in a certain order, so as to improve the efficiency of file reading and make the reading process organized. In this example, the target design parameters are obtained to make it feasible to obtain the target rim performance in the subsequent process.

[0111] As an example, in step S503, after obtaining the target design parameters for calculating the target rim performance, the computer device calculates and processes the target design parameters according to the calculation logic corresponding to the target rim performance to obtain the target rim performance. In this example, the target design parameters are processed to obtain the target rim performance. This method reduces manual operations, which can not only improve work efficiency but also reduce work costs.

[0112] In this implementation, the rim finite element calculation file is automatically solved to obtain a calculation result file; parameters are extracted from the calculation result file to obtain target design parameters; the target design parameters are processed to obtain target rim performance. The automatic solution of the rim finite element calculation file, the parameter extraction of the calculation result file, and the acquisition of the target rim performance based on the target design parameters are effectively connected in series to reduce manual operations, achieve unified standard output, have good consistency, and facilitate improving work efficiency.

[0113] In one embodiment, if Figure 6 As shown, step S503, i.e., processing the target design parameters to obtain the target rim performance, also includes:

[0114] S601: extracting parameters from the calculation result file to obtain the model weight, response point frequency, and Y-axis acceleration response corresponding to the response point frequency;

[0115] S602: forming a target two-dimensional array based on the response point frequency and the Y-direction acceleration response corresponding to the response point frequency;

[0116] S603: Screening out the resonance peak frequency and the anti-resonance peak frequency based on the target two-dimensional array;

[0117] S604: Obtain the lateral stiffness of the wheel rim based on the model weight, the resonance peak frequency, and the anti-resonance peak frequency.

[0118] Among them, the model weight refers to the mass of the hardware corresponding to the original rim model. The response point frequency refers to the frequency corresponding to the response point after the excitation is applied to the excitation point during the finite element analysis of the rim parameterized data. Among them, the excitation point refers to the position point where the original rim model corresponding to the rim parameterized data is excited during the finite element analysis of the rim parameterized data. The response point refers to the position point where the original rim model corresponding to the rim parameterized data generates a response corresponding to the excitation after being excited during the finite element analysis of the rim parameterized data. The Y-direction acceleration response refers to the acceleration generated by the response point in the Y-axis direction in the coordinate system after the excitation is applied to the excitation point during the finite element analysis of the rim parameterized data. It can be understood that in the process of finite element analysis of the rim parameterized data, after the excitation is applied to the excitation point, the corresponding response point frequency and the acceleration response corresponding to the response point frequency will be generated at the response point. Among them, the acceleration response refers to the acceleration generated at the response point after the original rim model corresponding to the rim parameterized data is excited. Since the lateral stiffness of the rim is the dynamic stiffness in the Y-axis direction in the three-dimensional coordinate system, if the target rim performance is the lateral stiffness of the rim, it is necessary to obtain the acceleration response corresponding to the response point frequency, specifically the acceleration response in the Y-axis direction of the coordinate system, that is, the Y-direction acceleration response. Among them, the lateral stiffness of the rim refers to the dynamic stiffness of the original rim model in the Y-axis direction in the three-dimensional coordinate system.

[0119] As an example, in step S601, the computer device extracts parameters from the calculation result file to obtain the model weight, response point frequency, and Y-axis acceleration response corresponding to the original rim model in the rim parameterization data. In this example, the computer device automatically runs the result post-processing script, automatically identifies the calculation result file, reads the model weight marked in the file name of the calculation result file, and extracts the response point frequency and the Y-axis acceleration response of the response point in the calculation result file according to the processing order of the result post-processing script. In this example, the calculation result file is parameter extracted without manual parameter extraction, so that the obtained model weight, response point frequency, and Y-axis acceleration response corresponding to the response point frequency are more accurate and have a higher extraction efficiency.

[0120] Among them, the target two-dimensional array refers to the array formed by the correspondence between the response point frequency and the Y-direction acceleration response corresponding to the response point frequency. It can be understood that for each response point frequency of the response point, there is a Y-direction acceleration response corresponding to it. This correspondence is formed into an array to form a target two-dimensional array. The target two-dimensional array is convenient for querying the correspondence between the response point frequency and the Y-direction acceleration response of the response point.

[0121] As an example, in step S602, the computer device forms an array by one-to-one correspondence between the response point frequency and the Y-axis acceleration response of the response point, and uses the array as the target two-dimensional array. For example, when the target rim performance is the rim lateral stiffness, the computer device determines that the excitation point is the wheel center point of the original rim model, and the response point includes the excitation point. In this example, the wheel center point of the original rim model is also used as the response point, the wheel center point frequency corresponding to the wheel center point is used as the response point frequency, the Y-axis acceleration of the coordinate system corresponding to the wheel center point frequency is used as the Y-axis acceleration response of the response point, and the wheel center point frequency is one-to-one correspondence with the Y-axis acceleration of the coordinate system corresponding to the wheel center point frequency to form a target two-dimensional array. In this example, based on the response point frequency and the Y-axis acceleration response corresponding to the response point frequency, a target two-dimensional array is formed to facilitate the acquisition of the resonance peak frequency and the anti-resonance peak frequency to calculate the rim lateral stiffness.

[0122] The resonance peak frequency refers to the response point frequency corresponding to the maximum Y-direction acceleration response in the target two-dimensional array, and the anti-resonance peak frequency refers to the response point frequency corresponding to the minimum Y-direction acceleration response in the target two-dimensional array.

[0123] As an example, in step S603, the computer device selects the response point frequency corresponding to the maximum Y-axis acceleration response in the target two-dimensional array as the resonance peak frequency; and selects the response point frequency corresponding to the minimum Y-axis acceleration response as the anti-resonance peak frequency. In this example, the wheel center point frequency and the Y-axis acceleration of the coordinate system corresponding to the wheel center point frequency correspond to each other to form a target two-dimensional array. The computer device uses the wheel center point frequency corresponding to the maximum Y-axis acceleration of the coordinate system in the target two-dimensional array as the resonance peak frequency, and uses the wheel center point frequency corresponding to the minimum Y-axis acceleration of the coordinate system as the anti-resonance peak frequency. In this example, the resonance peak frequency and the anti-resonance peak frequency are selected to facilitate the acquisition of the rim lateral stiffness based on the resonance peak frequency and the anti-resonance peak frequency.

[0124] As an example, in step S604, the computer device calculates the rim lateral stiffness based on the acquired model weight, resonance peak frequency, and anti-resonance peak frequency. In this example, the computer device substitutes the model weight, resonance peak frequency, and anti-resonance peak frequency into the rim lateral stiffness calculation formula, and calculates the rim lateral stiffness according to the rim lateral stiffness calculation formula:

[0125]

[0126] Among them, K wheeel represents the lateral stiffness of the rim, M represents the model weight, and f 1 represents the resonance peak frequency, f 2 represents the antiresonance peak frequency.

[0127] In this implementation, parameters are extracted from the calculation result file to obtain the model weight, response point frequency and the Y-axis acceleration response corresponding to the response point frequency; a target two-dimensional array is formed based on the response point frequency and the Y-axis acceleration response corresponding to the response point frequency; based on the target two-dimensional array, the resonance peak frequency and the anti-resonance peak frequency are screened out; based on the model weight, the resonance peak frequency and the anti-resonance peak frequency, the rim lateral stiffness is obtained. This process does not require manual operation, and the parameter extraction of the calculation result file, the acquisition of the target two-dimensional array, the screening of the resonance peak frequency and the anti-resonance peak frequency, and the acquisition of the rim lateral stiffness are organically connected in series to achieve automation of a series of operations, have good consistency, and can improve work efficiency.

[0128] In another embodiment, if Figure 7 As shown, after step S102, that is, after determining the target rim performance corresponding to the original rim model, the rim optimization design method further includes:

[0129] S701: If the target rim performance does not meet the preset performance requirement, obtain the current iteration number;

[0130] S702: if the current number of iterations is less than the preset number of iterations, the rim structural parameters of the original rim model are updated, structural parameter identification of the original rim model is repeatedly performed, key structural parameters are determined, rim structural parameters other than the key structural parameters are deleted, and rim parameterized data corresponding to the original rim model is obtained;

[0131] S703: If the current number of iterations is not less than the preset number of iterations, the original wheel rim model is determined as the target wheel rim model.

[0132] The current number of iterations refers to the number of times the rim structural parameters of the original rim model are updated and structural parameter identification of the original rim model is repeatedly performed when the target rim performance does not meet the preset performance requirements.

[0133] As an example, in step S701, when the computer device determines that the target rim performance does not meet the preset performance requirements, it obtains the current number of iterations, that is, obtains the rim structural parameters of the updated original rim model and repeatedly performs structural parameter identification on the original rim model, and obtains the number of rim parameterized data corresponding to the original rim model, so as to facilitate subsequent judgment on whether the current number of iterations exceeds the preset number of iterations.

[0134] The preset number of iterations refers to the preset maximum number of iterations. Understandably, in the process of obtaining the target rim model, the maximum number of iterations needs to be set to avoid repeated iterations. Therefore, the maximum number of iterations needs to be set as the preset number of iterations to end the iteration and obtain the target rim model.

[0135] As an example, in step S702, when the computer device determines that the current number of iterations is less than the preset number of iterations, the rim structural parameters of the original rim model are updated, the structural parameter identification of the original rim model is repeatedly performed, the key structural parameters are determined, the rim structural parameters other than the key structural parameters in the original rim model are deleted, the rim parameterization data corresponding to the original rim model is obtained, and the rim parameterization data corresponding to the original rim model is analyzed by finite element analysis to determine the target rim performance corresponding to the original rim model, that is, step S101 and step S102 are repeatedly performed until it is determined that the target rim performance meets the preset performance requirements or reaches the preset number of iterations. In this example, when the current number of iterations is less than the preset number of iterations, the rim structural parameters of the original rim model are updated, the structural parameter identification of the original rim model is repeatedly performed to obtain the rim parameterization data corresponding to the original rim model, and the target rim model is obtained. This process does not require manual participation, has a high degree of automation, can improve work efficiency, and reduce work costs.

[0136] As an example, in step S703, when the computer device determines that the target rim performance does not meet the preset performance requirements and the current iteration number is not less than the preset iteration number, the original rim model determined by the most recent update of the rim structure parameters is determined as the target rim model. In this example, if the current iteration number is not less than the preset iteration number, the original rim model is determined as the target rim model, avoiding the problem of repeated iterations and improving the work efficiency of obtaining the target rim model.

[0137] In this implementation, when the target rim performance does not meet the preset performance requirements, the current iteration number is obtained; when the current iteration number is less than the preset iteration number, the rim structure parameters of the original rim model are updated to obtain the rim parameterized data corresponding to the original rim model, without manual participation, with a high degree of automation, which can improve work efficiency and reduce work costs. When the current iteration number is not less than the preset iteration number, the original rim model is determined as the target rim model, which can avoid the problem of repeated iterations and improve the work efficiency of obtaining the target rim model.

[0138] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0139] In one embodiment, a rim optimization design device is provided, and the rim optimization design device corresponds one-to-one to the rim optimization design method in the above embodiment. Figure 8 As shown, the rim optimization design device includes a rim parameterization data acquisition module 801, a target rim performance acquisition module 802, a first judgment module 803 and a second judgment module 804. The detailed description of each functional module is as follows:

[0140] The rim parameterized data acquisition module 801 is used to identify the structural parameters of the original rim model, determine the key structural parameters, delete the rim structural parameters other than the key structural parameters, and acquire the rim parameterized data corresponding to the original rim model;

[0141] The target rim performance acquisition module 802 is used to perform finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model;

[0142] The first judgment module 803 is used to update the rim structural parameters of the original rim model if the target rim performance does not meet the preset performance requirements, repeatedly perform structural parameter identification on the original rim model, determine key structural parameters, delete rim structural parameters other than the key structural parameters, and obtain rim parameterized data corresponding to the original rim model;

[0143] The second judgment module 804 is configured to determine the original rim model as the target rim model if the target rim performance meets the preset performance requirement.

[0144] In one embodiment, the target rim performance acquisition module 802 includes:

[0145] A rim finite element calculation file generation submodule is used to perform finite element analysis on the rim parameterized data corresponding to the original rim model and generate a rim finite element calculation file;

[0146] The target rim performance acquisition submodule is used to automatically solve the rim finite element calculation file to obtain the target rim performance.

[0147] In one embodiment, the rim finite element calculation file generation submodule includes:

[0148] A first rim model acquisition unit, used for geometrically cleaning the rim parameterized data to acquire a first rim model;

[0149] A target grid model acquisition unit, used to perform grid division on the first wheel rim model to acquire at least two target grid models corresponding to the first wheel rim model;

[0150] A second wheel rim model acquisition unit is used to connect at least two target mesh models and assign material properties to obtain a second wheel rim model;

[0151] The rim finite element calculation file generating unit is used for performing finite element analysis on the second rim model and generating a rim finite element calculation file.

[0152] In one embodiment, the target grid model acquisition unit includes:

[0153] A two-dimensional grid model acquisition subunit is used to perform two-dimensional grid division on the first wheel rim model to obtain at least two two-dimensional grid models corresponding to the first wheel rim model;

[0154] The target mesh model determination subunit is used to generate a three-dimensional mesh model based on the two-dimensional mesh model if the two-dimensional mesh model meets the preset mesh quality requirements, and determine the three-dimensional mesh model as the target mesh model corresponding to the first rim model.

[0155] In one embodiment, the target rim performance acquisition submodule includes:

[0156] A calculation result file acquisition unit is used to automatically solve the rim finite element calculation file and acquire the calculation result file;

[0157] A target design parameter acquisition unit is used to extract parameters from the calculation result file to obtain target design parameters;

[0158] The target rim performance acquisition unit is used to process the target design parameters to obtain the target rim performance.

[0159] In one embodiment, the target rim performance acquisition unit further includes:

[0160] The parameter extraction subunit is used to extract parameters from the calculation result file to obtain the model weight, response point frequency and Y-axis acceleration response corresponding to the response point frequency;

[0161] The target two-dimensional array forming subunit forms a target two-dimensional array based on the response point frequency and the Y-direction acceleration response corresponding to the response point frequency;

[0162] The frequency screening subunit screens out the resonance peak frequency and anti-resonance peak frequency based on the target two-dimensional array;

[0163] The rim lateral stiffness acquisition subunit acquires the rim lateral stiffness based on the model weight, the resonance peak frequency and the anti-resonance peak frequency.

[0164] In another embodiment, the rim optimization design device further comprises:

[0165] A current iteration number acquisition module is used to obtain the current iteration number if the target rim performance does not meet the preset performance requirements;

[0166] A first iteration number judgment module is used for updating the rim structural parameters of the original rim model if the current iteration number is less than the preset iteration number, repeatedly performing structural parameter identification on the original rim model, determining key structural parameters, deleting rim structural parameters other than the key structural parameters, and obtaining rim parameterized data corresponding to the original rim model;

[0167] The second iteration number judgment module is used to determine the original wheel rim model as the target wheel rim model if the current iteration number is not less than the preset iteration number.

[0168] The specific definition of the rim optimization design device can be found in the definition of the rim optimization design method above, which will not be repeated here. Each module in the above-mentioned rim optimization design device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0169] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data used or generated during the execution of the rim optimization design method. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a rim optimization design method is implemented.

[0170] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the wheel rim optimization design method in the above embodiment is implemented, for example Figure 1 S101-S104 as shown, or Figures 2 to 7 As shown in, to avoid repetition, it will not be repeated here. Alternatively, when the processor executes the computer program, the functions of each module / unit in this embodiment of the rim optimization design device are realized, for example Figure 8 The functions of the rim parameterized data acquisition module 801 , the target rim performance acquisition module 802 , the first judgment module 803 and the second judgment module 804 are not described here in detail to avoid repetition.

[0171] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the wheel rim optimization design method in the above embodiment is implemented. For example, Figure 1 S101-S104 as shown, or Figures 2 to 7Alternatively, when the computer program is executed by the processor, the functions of each module / unit in the above-mentioned rim optimization design device are realized, for example, Figure 8 The functions of the rim parameterized data acquisition module 801, the target rim performance acquisition module 802, the first judgment module 803 and the second judgment module 804 are not described here in detail to avoid repetition. The computer-readable storage medium may be non-volatile or volatile.

[0172] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0173] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0174] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A rim optimization design method, characterized in that: include: Performing structural parameter identification on the original rim model, determining key structural parameters, deleting rim structural parameters other than the key structural parameters, and acquiring rim parameterized data corresponding to the original rim model; Performing finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model; If the target rim performance does not meet the preset performance requirements, the rim structural parameters of the original rim model are updated, the structural parameter identification of the original rim model is repeatedly performed to determine the key structural parameters, and the rim structural parameters other than the key structural parameters are deleted to obtain the rim parameterized data corresponding to the original rim model; If the target rim performance meets the preset performance requirement, the original rim model is determined as the target rim model.

2. The rim optimization design method according to claim 1, characterized in that: The performing finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model includes: Performing finite element analysis on the rim parameterized data corresponding to the original rim model to generate a rim finite element calculation file; The rim finite element calculation file is automatically solved to obtain target rim performance.

3. The rim optimization design method according to claim 2, characterized in that: The step of performing finite element analysis on the rim parameterized data to generate a rim finite element calculation file comprises: Performing geometric cleaning on the rim parameterized data to obtain a first rim model; Meshing the first wheel rim model to obtain at least two target mesh models corresponding to the first wheel rim model; Connecting at least two of the target mesh models and assigning material properties to obtain a second wheel rim model; Perform finite element analysis on the second wheel rim model to generate a wheel rim finite element calculation file.

4. The rim optimization design method according to claim 3, characterized in that: The step of meshing the first rim model to obtain at least two target mesh models corresponding to the first rim model includes: Performing two-dimensional mesh division on the first wheel rim model to obtain at least two two-dimensional mesh models corresponding to the first wheel rim model; If the two-dimensional mesh model meets the preset mesh quality requirement, a three-dimensional mesh model is generated based on the two-dimensional mesh model, and the three-dimensional mesh model is determined as the target mesh model corresponding to the first rim model.

5. The rim optimization design method according to claim 2, characterized in that: The automatically solving the rim finite element calculation file to obtain the target rim performance includes: Automatically solving the wheel rim finite element calculation file to obtain a calculation result file; Extracting parameters from the calculation result file to obtain target design parameters; The target design parameters are processed to obtain target rim performance.

6. The rim optimization design method according to claim 5, characterized in that: The processing of the target design parameters to obtain the target rim performance also includes: Extract parameters from the calculation result file to obtain the model weight, response point frequency, and Y-axis acceleration response corresponding to the response point frequency; Based on the response point frequency and the Y-direction acceleration response corresponding to the response point frequency, a target two-dimensional array is formed; Based on the target two-dimensional array, selecting the resonance peak frequency and the anti-resonance peak frequency; The lateral stiffness of the rim is obtained based on the model weight, the resonance peak frequency and the anti-resonance peak frequency.

7. The rim optimization design method according to claim 1, characterized in that: After determining the target rim performance corresponding to the original rim model, the rim optimization design method further includes: If the target rim performance does not meet the preset performance requirements, obtaining the current iteration number; If the current number of iterations is less than the preset number of iterations, the rim structural parameters of the original rim model are updated, the structural parameter identification of the original rim model is repeatedly performed, key structural parameters are determined, rim structural parameters other than the key structural parameters are deleted, and rim parameterized data corresponding to the original rim model is obtained; If the current number of iterations is not less than a preset number of iterations, the original wheel rim model is determined as the target wheel rim model.

8. A rim optimization design device, characterized in that: include: A rim parameterized data acquisition module is used to identify structural parameters of the original rim model, determine key structural parameters, delete rim structural parameters other than the key structural parameters, and acquire rim parameterized data corresponding to the original rim model; A target rim performance acquisition module is used to perform finite element analysis on the rim parameterized data corresponding to the original rim model to determine the target rim performance corresponding to the original rim model; A first judgment module is used for updating the rim structural parameters of the original rim model if the target rim performance does not meet the preset performance requirements, repeatedly performing the structural parameter identification of the original rim model, determining the key structural parameters, deleting the rim structural parameters other than the key structural parameters, and obtaining the rim parameterized data corresponding to the original rim model; The second judgment module is used to determine the original rim model as the target rim model if the target rim performance meets the preset performance requirement.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the rim optimization design method as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the rim optimization design method according to any one of claims 1 to 7 is implemented.

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