A simulation system, method, apparatus, and medium for evaluating the effects of materials on wheels.

Abstract

This invention belongs to the field of automotive parts manufacturing, specifically involving a simulation system, method, equipment, and medium for evaluating the impact of materials on wheels. Based on a target wheel test bench, a corresponding simulation model is established; several sets of material properties, yield strength and tensile strength, are input to generate SN curves; corresponding stress criteria are generated based on the SN curves; the corresponding weight is obtained, optimization results are obtained, and the optimization results are evaluated. This invention converts the wheel bending fatigue life into equivalent fatigue strength through SN curves, and uses high-order mesh deformation technology to quickly and efficiently evaluate the impact of yield strength and tensile strength on wheel weight. It provides a scientific and accurate simulation prediction method for evaluating the impact of material properties on wheel weight, with broad application prospects and market value. This addresses the problem of difficulty in quickly and accurately evaluating the quantitative impact of new materials on wheel weight under bending fatigue conditions.

Description

Technical Field

[0001] This invention belongs to the field of automotive parts manufacturing, and specifically relates to a simulation system, method, equipment, and medium for evaluating the impact of materials on wheels. Background Technology

[0002] For wheels, the three major test benches are essential standard bench tests. Currently, the method for evaluating the impact of material properties on wheel weight mostly involves designing 3D models of different weights and iteratively analyzing them using fatigue software to obtain lifespan values ​​for each weight. This method is inefficient, lacks accuracy, and cannot quickly assess the quantitative impact of material properties on wheel weight. Further investigation reveals that the core cause of this problem lies in the significant limitations of human experience and the long fatigue analysis time. Currently, the automotive industry lacks an effective solution.

[0003] Therefore, there is an urgent need to build a solution based on SN curves and driven by algorithms for automatic iteration. Summary of the Invention

[0004] This invention proposes a system, method, apparatus, and medium for evaluating the impact of materials on wheels, in order to address the lack of a solution for automatic iteration of SN curves driven by algorithms.

[0005] To achieve the above objectives, the present invention proposes the following technical solution: A simulation system for evaluating the impact of materials on wheels includes a simulation model building module, a stress curve generation module, a stress criterion generation module, and a stress-optimization integration module. The simulation model building module establishes a corresponding simulation model based on the bending fatigue test fixture; the SN curve generation module inputs several sets of material properties, yield strength and tensile strength, and generates SN curves based on the simulation model; the stress criterion generation module generates corresponding stress criteria based on the SN curves. The SOM simulation optimization integrated module obtains the corresponding weight based on the stress criterion, and then obtains the optimization results, specifically: It includes the Deform Parameter submodule, Deform submodule, PBS submodule, Post submodule, and Optimization submodule. The Deform Parameter submodule defines variables, and the Deform submodule performs high-order mesh deformation on the wheel solid mesh spoke machining lines in the simulation model based on the variables defined in the Deform Parameter submodule, and outputs the deformed solution file. The PBS submodule calculates the result file based on the solution file. The Post submodule is used to automatically capture the maximum stress value in the analysis result file. The Optimization submodule drives the entire SOM simulation optimization integration module to automatically iterate.

[0006] Preferably, it also includes a 3D modeling verification module, which is used to design a 3D model based on the optimization results to evaluate its weight, bending stress and manufacturing feasibility.

[0007] Preferably, the simulation model building module builds the simulation model in the following ways: Wheels, bolts, and moment bars are modeled using solid meshes. The wheel is meshed with a tetrahedral second-order solid mesh, and the bolt and moment rod are meshed as a whole with a tetrahedral first-order solid mesh, or the bolt and moment rod are meshed with tetrahedral first-order solid meshes respectively. The threaded connection is connected with a tie. Constrain the inner rim portion of the mesh to 1-3 degrees of freedom, and apply a load at the end of the bending moment bar away from the wheel; Contact is established between the contact surfaces of the wheel and the bolt, and between the wheel and the moment rod, and bolt preload is applied.

[0008] Preferably, the SN curve generation module FEMFAT software, enters the Material Data module, selects the cast aluminum alloy, and inputs three sets of yield strength and tensile strength to obtain the corresponding SN curves.

[0009] Preferably, the stress criterion generation module specifically comprises: The software specifies that for cast aluminum alloys, under the premise of a survival rate of 97.5%, the slope k of the SN curve is 11; the formula for the SN curve is y=ax^(-1 / k), where y is the stress criterion, a is the coefficient, and x is the number of cycles; By substituting a cycle life of 200,000 revolutions into their respective SN curves, the stress criteria corresponding to the properties of each material at the same life level can be obtained.

[0010] Preferably, the Optimization submodule specifically comprises: Define and input the initial values ​​and ranges of the design variables, define and input the initial values ​​and ranges of the constraints, define and input the objective function value, and use the Hooke Jeeves optimization algorithm to drive the entire optimization system to iterate automatically.

[0011] A simulation method for evaluating the impact of materials on wheels, applied to a simulation system for evaluating the impact of materials on wheels, includes the following steps: Step 1: Based on the bending fatigue test fixture, establish the corresponding simulation model; Step 2: Generate SN curves based on the simulation model, material properties (yield and tensile strength); Step 3: Generate stress criteria based on the SN curve; Step 4: Obtain the weights corresponding to different stress criteria through SOM simulation optimization integration, and obtain the optimization results. Specifically: Define variables, perform high-order mesh deformation on the wheel solid mesh spokes of the original fatigue strength calculation file based on the defined variables, and output the deformed solution file; calculate the result file based on the solution file; capture the maximum stress value in the analysis result file; iteratively optimize the process; Step 5: Based on the optimization results, design a 3D model to evaluate its weight, bending stress, and manufacturing feasibility.

[0012] An electronic device, comprising a memory and a processor; Memory, used to store computer programs; A processor is configured to execute the computer program, which, when executed by the processor, implements the steps of a simulation method for evaluating the effect of materials on wheels.

[0013] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of a simulation method for evaluating the effect of materials on wheels.

[0014] The advantages of this invention are: This invention generates corresponding SN curves based on material properties such as yield strength and tensile strength. By using these SN curves, the bending fatigue life of a wheel is converted into an equivalent fatigue strength. Utilizing a SOM simulation optimization integration module and high-order mesh deformation technology, the impact of yield strength and tensile strength on wheel weight is rapidly and efficiently evaluated. This provides a scientific and accurate simulation prediction method for assessing the influence of material properties on wheel weight, with broad application prospects and market value. It addresses the problem of the difficulty in quickly and accurately evaluating the quantitative impact of new materials on wheel weight under bending fatigue conditions. Attached Figure Description

[0015] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of a simulation system for evaluating the impact of materials on wheels. Figure 2 This is a schematic diagram of a bending fatigue simulation model; Figure 3 This is a schematic diagram of the SN curve; Figure 4 Schematic diagram of the deformation control body; Figure 5 Optimize the integrated system for SOM simulation; Figure 6 A schematic diagram showing the weight of products with different material properties and lifespans; Figure 7A diagram illustrating the weight reduction ratio for products with different material properties and the same lifespan. Figure 8 3D model designed based on optimization results; Figure 9 The weight and simulation results of the 3D model were designed based on the optimization results; Figure 10 A schematic diagram comparing the optimization results of different materials with their corresponding 3D shapes; Figure 11 This is a schematic diagram of a simulation method for evaluating the impact of materials on wheels; Figure 12 This is a schematic diagram of an electronic device. Detailed Implementation

[0016] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0017] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. Example

[0018] Please see Figure 1 As shown, this invention provides a simulation system for evaluating the influence of materials on wheels, specifically including a simulation model establishment module, an SN curve generation module, a stress criterion generation module, a SOM simulation optimization integration module, and a 3D modeling verification module. Specifically: The simulation model building module is used to build a corresponding simulation model based on the bending fatigue test fixture, such as... Figure 2 As shown, specifically: The wheel, bolt, and moment rod are modeled using solid meshes. The wheel is meshed with a second-order tetrahedral solid mesh, while the bolt and moment rod are meshed as a whole with a first-order tetrahedral solid mesh. Alternatively, the bolt and moment rod can be meshed with first-order tetrahedral solid meshes separately. The threaded connection is connected using tie contact. The inner rim of the wheel is constrained with 1-3 degrees of freedom. A load is applied to the end of the moment rod away from the wheel. Contact is established between the wheel and bolt, and between the wheel and moment rod, and bolt preload is applied.

[0019] The SN curve generation module is used to generate SN curves based on the simulation model, material properties (yield and tensile strength), specifically: like Figure 3As shown, open the FEMFAT software, enter the Material Data module, select the cast aluminum alloy, and input three sets of yield strength and tensile strength to obtain the corresponding SN curves; SN1: Input yield strength 215MPa, tensile strength 275MPa; SN2: Input yield strength 260MPa, tensile strength 320MPa; SN1: Input yield strength 300MPa, tensile strength 375MPa.

[0020] The stress criterion generation module is used to generate stress criteria based on the SN curve, specifically: The formula for the SN curve is y=ax^(-1 / k). The software specifies that for cast aluminum alloys, the slope k of the SN curve is 11, provided that the survival rate is 97.5%. The SN1 formula is obtained as follows: The fatigue limit stress is 82.5 MPa and the number of cycles is 10,000,000 from the FEMFAT software. Therefore, a1 = 357.1. Thus, SN1 is y = 357.12x^(-1 / 11). Similarly, SN2 is obtained as y = 415.56x^(-1 / 11), and SN3 is obtained as y = 486.99x^(-1 / 11). By substituting the 200,000 rpm cycle life commonly used in wheel bending conditions into their respective SN curves, the stress criteria corresponding to the three material properties at the same life level were obtained: σ1=117.7MPa, σ2=137MPa, and σ3=160.5MPa.

[0021] The SOM simulation optimization integration module obtains the weights corresponding to different stress criteria through the SOM simulation optimization integration system, and obtains the optimization results, specifically: like Figure 4 As shown, the creation of the deformation control body is independent of the mesh and element nodes, and can be saved independently. It can be repeatedly imported and used for wheels of the same size and structure. The deformation control body can automatically search for nearby nodes and automatically associate them. By adjusting the deformation control body, the purpose of controlling the mesh nodes can be achieved. The high-order mesh deformation technology supports solid mesh deformation based on the cylindrical coordinate system, which meets the circumferential symmetry characteristics and process requirements of the wheel hub mesh. The high-order mesh deformation technology supports the output of smooth solid mesh models.

[0022] like Figure 5 As shown, the SOM simulation optimization integration module combines the bending fatigue strength simulation model inp file, high-order mesh deformation technology, optimization algorithm, PBS calculation system, and post-processing automation system to automate the entire process and obtain the wheel weight and solid mesh model corresponding to different stress criteria; specifically: The Deform Parameter submodule defines the deformation parameter as the amount of movement of the machining line along the wheel axis. The Deform submodule uses commands to drive high-order mesh deformation of the wheel solid mesh spokes in the original fatigue strength inp calculation file according to the variables defined in the Deform Parameter module. The high-order mesh deformation technology supports solid mesh deformation based on cylindrical coordinate system, satisfies the circumferential symmetry characteristics of the wheel hub mesh. The mesh adjustment is carried out through 1st to 3rd order linear and nonlinear deformation algorithms to ensure that the deformed mesh model has better smoothness and manufacturability, and outputs the deformed inp solution file. PBS submodule: Automatically uploads the inp solution file obtained from the Deform module to the PBS system, and automatically downloads the odb result file to the specified path after the calculation is completed; Post submodule: The post-processing automation module is used to automatically extract the maximum stress value from the analysis results odb file and write it to a csv file; The Optimization submodule defines and inputs the initial values ​​and ranges of design variables, the initial values ​​and ranges of constraints, and the objective function value. It uses the Hooke-Jeves optimization algorithm to drive the entire optimization system in automatic iteration. This algorithm is well-suited for both linear and nonlinear design spaces. It checks points near the current point by perturbing the design variables, one axis at a time, until an improved point is found. Then, it follows a favorable direction until no further design improvements are possible. The magnitude of the variable perturbation is determined by the relative step size, which is gradually reduced by applying a step size reduction factor until convergence is detected. The module obtains the wheel weights corresponding to different stress criteria.

[0023] like Figure 6 As shown, the stress criteria and weights of the three materials at the same lifespan of 200,000 revolutions were obtained. The first material had the following weights: σ1 = 117.7 MPa, m1 = 17.071 kg, σ2 = 137 MPa, m2 = 16.664 kg, and σ3 = 160.5 MPa, m3 = 16.280 kg. For a wheel, the weight of the wheel disc accounts for 44% of the total weight of the wheel, such as Figure 7 As shown, for wheel bending fatigue conditions, improving material properties (yield and tensile strength) is beneficial to wheel lightweighting. Compared with the first material, the second material reduces weight by 5.4%, and the third material reduces weight by 10.5%. Overall, with a tensile strength increase of 100 MPa, the wheel disc can be reduced in weight by about 10.5%.

[0024] The 3D modeling verification module is used to design 3D models based on optimization results and evaluate their weight, bending stress, and manufacturing feasibility. Specifically: like Figure 8 As shown, based on the optimization results, corresponding 3D models were designed, namely the first model, the second model, and the third model, and their weights were measured. A 3D model was used to establish a bending fatigue strength simulation model, and its stress value was analyzed and obtained. Simulation of casting process based on 3D modeling, such as Figure 9 As shown, assess its casting feasibility; like Figure 10 As shown, if the difference between the stress value and weight obtained based on the optimization results and the stress and weight obtained from the corresponding 3D model is less than 1%, the process is complete; otherwise, return to step 2.

[0025] This invention converts wheel bending fatigue life into equivalent fatigue strength using SN curves. With the help of a self-developed SOM simulation optimization integration system and high-order mesh deformation technology, it can quickly and efficiently evaluate the impact of yield and tensile strength on wheel weight, and ultimately quickly evaluate the quantitative impact of material properties on wheel weight. Example

[0026] This invention provides a simulation method for evaluating the impact of materials on wheels. This method is based on a simulation system for evaluating the impact of materials on wheels as described in Example 1, such as... Figure 11 As shown, the specific steps include the following: Step 1: Based on the bending fatigue test bench fixture, a corresponding simulation model is established.

[0027] Step 2: Generate SN curves based on the simulation model, material properties, yield strength, and tensile strength.

[0028] Step 3: Generate stress criteria based on SN curves.

[0029] Step 4: Obtain the weights corresponding to different stress criteria through the SOM simulation optimization integration module, and obtain the optimization results.

[0030] Step 5: Based on the optimization results, design a 3D model to evaluate its weight, bending stress, and manufacturing feasibility. Example

[0031] Please see Figure 12 As shown, the present invention also provides an electronic device 100; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0032] The memory 101 can be used to store the computer program 103. The processor 102 implements the steps of the simulation method for evaluating the influence of materials on wheels as described in Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0033] The at least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor. The processor 102 is the control center of the electronic device 100, connecting various parts of the electronic device 100 via various interfaces and lines.

[0034] The memory 101 in the electronic device 100 stores multiple instructions to implement a simulation method for evaluating the influence of materials on wheels, and the processor 102 can execute the multiple instructions to implement a simulation method for evaluating the influence of materials on wheels. Example

[0035] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0036] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative in all respects and are not the only ones. All modifications within the scope of this invention or its equivalents are included in this invention.

[0037] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0038] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0039] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0040] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A simulation system for evaluating the influence of materials on wheels, characterized in that, It includes a simulation model building module, an SN curve generation module, a stress criterion generation module, and a SOM simulation optimization integration module. The simulation model building module establishes a corresponding simulation model based on the bending fatigue test fixture; the SN curve generation module takes into account several sets of material properties, yield strength and tensile strength, and generates SN curves based on the simulation model. The stress criterion generation module generates corresponding stress criteria based on the SN curve; The SOM simulation optimization integrated module obtains the corresponding weight based on the stress criterion, and then obtains the optimization results, specifically: It includes the Deform Parameter submodule, Deform submodule, PBS submodule, Post submodule, and Optimization submodule. The Deform Parameter submodule defines variables, and the Deform submodule performs high-order mesh deformation on the wheel solid mesh spoke machining lines in the simulation model based on the variables defined in the Deform Parameter submodule, and outputs the deformed solution file. The PBS submodule calculates the result file based on the solution file. The Post submodule is used to automatically capture the maximum stress value in the analysis result file. The Optimization submodule drives the entire SOM simulation optimization integration module to automatically iterate.

2. The simulation system for evaluating the influence of materials on wheels as described in claim 1, characterized in that, It also includes a 3D modeling verification module, which is used to design 3D models based on optimization results to evaluate their weight, bending stress and manufacturing feasibility.

3. The simulation system for evaluating the influence of materials on wheels as described in claim 1, characterized in that, The simulation model building module builds the simulation model in the following ways: Wheels, bolts, and moment bars are modeled using solid meshes. The wheel is meshed with a tetrahedral second-order solid mesh, and the bolt and moment rod are meshed as a whole with a tetrahedral first-order solid mesh, or the bolt and moment rod are meshed with tetrahedral first-order solid meshes respectively. The threaded connection is connected with a tie. Constrain the inner rim portion of the mesh to 1-3 degrees of freedom, and apply a load at the end of the bending moment bar away from the wheel; Contact is established between the contact surfaces of the wheel and the bolt, and between the wheel and the moment rod, and bolt preload is applied.

4. The simulation system for evaluating the influence of materials on wheels as described in claim 1, characterized in that, The SN curve generation module, FEMFAT software, allows you to enter the Material Data module, select the cast aluminum alloy, and input three sets of yield strength and tensile strength to obtain the corresponding SN curves.

5. The simulation system for evaluating the influence of materials on wheels as described in claim 1, characterized in that, The stress criterion generation module specifically comprises: The software specifies that for cast aluminum alloys, under the premise of a survival rate of 97.5%, the slope k of the SN curve is 11; the formula for the SN curve is y=ax^(-1 / k), where y is the stress criterion, a is the coefficient, and x is the number of cycles; By substituting a cycle life of 200,000 revolutions into their respective SN curves, the stress criteria corresponding to the properties of each material at the same life level can be obtained.

6. The simulation system for evaluating the influence of materials on wheels as described in claim 1, characterized in that, The Optimization submodule is specifically as follows: Define and input the initial values ​​and ranges of the design variables, define and input the initial values ​​and ranges of the constraints, define and input the objective function value, and use the Hooke Jeeves optimization algorithm to drive the entire optimization system to iterate automatically.

7. A simulation method for evaluating the influence of materials on wheels, characterized in that, The simulation system for evaluating the influence of materials on wheels, as described in any one of claims 1-6, includes the following steps: Step 1: Based on the bending fatigue test fixture, establish the corresponding simulation model; Step 2: Generate SN curves based on the simulation model, material properties (yield and tensile strength); Step 3: Generate stress criteria based on the SN curve; Step 4: Obtain the weights corresponding to different stress criteria through SOM simulation optimization integration, and obtain the optimization results. Specifically: Define variables, and perform high-order mesh deformation on the wheel solid mesh spoke machining lines in the original fatigue strength calculation file according to the defined variables, and output the deformed solution file. The result file is obtained by calculating based on the solution file; Extract the maximum stress value from the analysis results file; iterative optimization process; Step 5: Based on the optimization results, design a 3D model to evaluate its weight, bending stress, and manufacturing feasibility.

8. An electronic device, characterized in that, Including memory and processor; Memory, used to store computer programs; A processor for executing the computer program, which, when executed by the processor, implements the steps of a simulation method for evaluating the effect of materials on wheels as described in claim 7.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of a simulation method for evaluating the influence of materials on wheels as described in claim 7.

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