Wheel hub digital R&D method, device and server based on low-code development platform

Abstract

The present invention provides a wheel hub digital R&D method, device, and server based on a low-code development platform, relating to the technical field of universal development of simulation applications. The method comprises: performing material property mapping processing on an initial wheel hub model based on interactive information from a user end to determine a target wheel hub model; performing feature selection processing on the target wheel hub model to determine a target feature surface, and determining a load arm coordinate system and a target simulated load arm based on the target feature surface; simulating the fixed state of the wheel hub to determine a target detection state of the target wheel hub model based on the load arm coordinate system, the target simulated load arm, and the surface feature information of the rim in the target wheel hub model; assigning a load to the target wheel hub model in the target detection state, and utilizing a preset life assessment component and a preset impact assessment component to perform an assessment and analysis process on the target wheel hub model to determine a target assessment result. The present invention can significantly reduce the R&D cost of the wheel hub and improve R&D efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of universal development of simulation applications, and in particular to a wheel hub digital R&D method, device and server based on a low-code development platform. Background Art

[0002] At present, the research and development and production of wheels rely on a large number of physical tests to meet the use standards. This process is not only time-consuming and labor-intensive, but also increases the cost and time of research and development. Relevant technologies have proposed that structural strength analysis can be performed through commercial simulation tools. However, when using existing structural simulation tools for wheel hub development, users are required to complete complex processes such as model building, load definition, boundary condition setting, and evaluation standard matching. The operation is highly professional, prone to errors, and inefficient. Especially for small and medium-sized enterprises, the lack of professional simulation teams and experience accumulation makes it difficult to build a complete simulation system covering multiple test requirements for wheels. This makes it difficult for existing simulation tools to replace physical tests. Simulation tools still need to be combined with physical experiments, and effective auxiliary verification cannot be performed in the early stages of design. Therefore, the problems of high R&D costs and long R&D cycles in the process of wheel hub development have not yet been solved. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a wheel hub digital R&D method, device and server based on a low-code development platform, which can significantly reduce the wheel hub R&D cost and improve R&D efficiency.

[0004] In the first aspect, an embodiment of the present invention provides a digital research and development method for a wheel hub based on a low-code development platform, the method comprising: obtaining an initial wheel hub model, and performing material property mapping processing on the initial wheel hub model according to interactive information from a user terminal, so as to simulate the actual material properties of the wheel hub body and the wheel hub research and development auxiliary equipment to obtain a target wheel hub model; performing feature selection processing on the inner wall surface of the wheel hub center hole of the target wheel hub model to determine the target feature surface, and based on the target feature surface, determining the load arm coordinate system and the target simulation load arm in the wheel hub research and development auxiliary equipment; simulating the fixed state of the wheel rim according to the load arm coordinate system, the target simulation load arm and the surface feature information of the rim in the target wheel hub model to determine the target detection state of the target wheel hub model; assigning a load to the target wheel hub model in the target detection state, and using a preset life assessment component and a preset impact assessment component to perform evaluation and analysis processing on the target wheel hub model to determine the target evaluation result, wherein the target evaluation result includes: the wheel hub bending fatigue life assessment result and the impact numerical assessment result.

[0005] In one embodiment, the initial hub model is subjected to material property mapping processing based on the interactive information of the user end to simulate the actual material properties of the hub body and the hub R&D auxiliary equipment to obtain the target hub model, including: dividing the components in the initial hub model based on body features, and determining the hub body features based on the interactive information of the user end; mapping the material properties of the hub body based on the hub body features, and assigning basic material properties to the hub R&D auxiliary equipment to determine the target hub model.

[0006] In one embodiment, the steps of determining the load arm coordinate system and the target simulated load arm in the hub R&D auxiliary equipment based on the target characteristic surface include: calculating the center of mass coordinates of the target characteristic surface, determining the standard center of mass coordinates of the inner wall surface of the hub center hole, and constructing the load arm coordinate system with the standard center of mass coordinates as the origin; simulating the extended part of the load arm according to the hub width information, the radius information of the inner wall surface of the hub center hole and the load arm coordinate system to determine the target simulated load arm.

[0007] In one embodiment, the fixed state of the rim is simulated based on the surface feature information of the rim in the load arm coordinate system, the target simulation load arm and the target hub model, and the step of determining the target detection state of the target hub model includes: assigning the surface feature information to the load arm coordinate system, constraining the translational degree of freedom of the X-axis, Y-axis and Z-axis in the load arm coordinate system after the surface feature information is assigned, and constraining the rotational degree of freedom of the X-axis and Y-axis to simulate the fixed state of the rim and the rotational state of the target hub model along the Z axis, and determining the rotational state as the target detection state.

[0008] In one embodiment, a preset life assessment component and a preset impact assessment component are used to evaluate and analyze the target hub model, and the steps of determining the target assessment results include: based on the preset life assessment component and the equivalent stress, through stress cycle analysis and fatigue life prediction model, mapping each stress point in the finite element analysis result to the corresponding number of fatigue life cycles; rotating and adjusting the target hub model through the preset model pre-processing component to determine the adjusted target hub model, and using the preset impact assessment component to perform an impact assessment on the adjusted target hub model to determine the target assessment result based on the number of fatigue life cycles and the impact assessment results.

[0009] In one embodiment, based on a preset life assessment component and equivalent stress, each stress point in the finite element analysis result is mapped to a corresponding number of fatigue life cycles through stress cycle analysis and a fatigue life prediction model, including: performing finite element calculation on the target hub model to determine the finite element calculation result, and extracting the equivalent stress corresponding to each node from the finite element calculation result; using a preset stress analysis model, performing stress analysis processing on the equivalent stress to determine the stress amplitude and average stress, and performing material fatigue limit analysis processing based on the average stress and stress amplitude through a fatigue life prediction model to determine the influence relationship of the average stress on the material fatigue limit, so as to correct the average stress and determine the effective stress amplitude; using a target stress-life curve corresponding to the material properties of the target hub model, based on the effective stress amplitude, establishing a functional relationship between stress amplitude and life, and solving the functional relationship according to the equivalent stress to determine the number of fatigue life cycles.

[0010] In one embodiment, the step of performing an impact evaluation on the adjusted target hub model using a preset impact evaluation component includes: using the preset impact evaluation component to construct an impact plate based on the adjusted target hub model, and converting the impact distance of the impact plate into a corresponding initial impact velocity; obtaining friction parameters corresponding to the test scenario, and performing a dynamic analysis on the target hub model based on the friction parameters and the initial impact velocity by fixing the target hub model to determine the impact evaluation result.

[0011] In a second aspect, an embodiment of the present invention further provides a wheel hub digital R&D device based on a low-code development platform, the device comprising: an information acquisition module, which acquires an initial wheel hub model, and performs material property mapping processing on the initial wheel hub model according to the interactive information of the user end, so as to simulate the actual material properties of the wheel hub body and the wheel hub R&D auxiliary equipment to obtain a target wheel hub model; a feature extraction module, which performs feature selection processing on the inner wall surface of the wheel hub center hole of the target wheel hub model, determines the target feature surface, and determines the load arm coordinate system and the target simulation load arm in the wheel hub R&D auxiliary equipment based on the target feature surface; a state simulation module, which simulates the fixed state of the wheel rim according to the surface feature information of the load arm coordinate system, the target simulation load arm and the rim in the target wheel hub model, and determines the target detection state of the target wheel hub model; an evaluation and analysis module, which assigns a load to the target wheel hub model in the target detection state, and uses a preset life evaluation component and a preset impact evaluation component to evaluate and analyze the target wheel hub model to determine the target evaluation result, wherein the target evaluation result includes: the wheel hub bending fatigue life evaluation result and the impact numerical evaluation result.

[0012] In a third aspect, an embodiment of the present invention further provides a server, comprising a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement any one of the methods provided in the first aspect.

[0013] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement any one of the methods provided in the first aspect.

[0014] The embodiments of the present invention bring the following beneficial effects:

[0015] An embodiment of the present invention provides a digital R&D method, device and server for a wheel hub based on a low-code development platform. After obtaining an initial wheel hub model, the method performs material property mapping processing on the initial wheel hub model according to the interactive information of the user end to simulate the actual material properties of the wheel hub body and the wheel hub R&D auxiliary equipment to obtain a target wheel hub model. Thereafter, feature selection processing is performed on the inner wall surface of the wheel hub center hole of the target wheel hub model to determine the target feature surface, and based on the target feature surface, the load arm coordinate system and the target simulation load arm in the wheel hub R&D auxiliary equipment are determined. Further, according to the load arm coordinate system, the target simulation load arm and the surface feature information of the rim in the target wheel hub model, the fixed state of the wheel rim is simulated to determine the target detection state of the target wheel hub model. Finally, the load is assigned to the target wheel hub model in the target detection state, and the preset life assessment component and the preset impact assessment component are used to evaluate and analyze the target wheel hub model to determine the target assessment result.

[0016] The embodiment of the present invention proposes a complete set of simulation modeling, load simulation, constraint setting and evaluation and judgment schemes around physical test contents such as hub single-axis and circumferential radial strength evaluation, hub axial strength evaluation, hub bending fatigue life evaluation and hub impact strength evaluation, which realizes the effective alignment between the wheel design stage and standard test requirements and the design of industrial simulation application system, so that users can quickly complete wheel simulation verification, thereby significantly reducing hub R&D costs and improving R&D efficiency.

[0017] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A schematic diagram of an existing physical test of a wheel hub provided by an embodiment of the present invention;

[0021] Figure 2 A schematic diagram of a process flow of a wheel hub digital development method based on a low-code development platform provided in an embodiment of the present invention;

[0022] Figure 3 A schematic diagram of a hub bending fatigue life assessment provided by an embodiment of the present invention;

[0023] Figure 4 A schematic diagram of another hub bending fatigue life assessment method provided by an embodiment of the present invention;

[0024] Figure 5 A schematic diagram of the structure of a wheel hub digital R&D device based on a low-code development platform provided in an embodiment of the present invention;

[0025] Figure 6 A schematic diagram of the structure of a server provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] Currently, the research and development and production of wheels rely on a large number of physical tests to meet usage standards. This process is not only time-consuming and labor-intensive, but also increases R&D costs and time. However, with the automotive industry's transition to large-scale customized production, the traditional "trial production-testing-correction" R&D model can no longer meet the needs of efficient and high-quality development. In this context, some small and medium-sized wheel manufacturing companies are facing many challenges. In particular, for many small and medium-sized wheel manufacturing companies, due to limited R&D resources and simulation capabilities, the transformation to positive R&D faces challenges such as long cycles, high barriers to entry, and high costs.

[0028] During the wheel development process, physical testing is a key step in evaluating its performance. Figure 1 The schematic diagram of a conventional physical test for a wheel hub is shown. The standard physical testing process for evaluating the bending fatigue life of a wheel hub is as follows: the wheel hub's rim is fixed in place using a rotating disc clamp, a load arm is fixed to the hub's center hole, and a weight is used to apply pressure to the load arm. Repeated testing is performed to evaluate the lifespan. However, this testing process has significant issues: the materials used in the fixture and load arm assembly are much harder than the wheel hub, which can lead to deviations between test results and actual usage. In current motorcycle wheel product development practices, physical prototyping and testing remain the primary verification methods. Manufacturers typically produce samples after each round of design changes and complete multiple physical tests in accordance with standards. Due to the irreversible and destructive nature of these tests, multiple samples must be prepared for different tests to prevent structural damage from previous tests from interfering with subsequent test results. This serial, sample-by-sample testing method not only leads to long R&D cycles and high costs, but also struggles to meet the demands of rapid design iteration.

[0029] On the other hand, although there are a variety of commercial simulation tools available for structural strength analysis, most of them are general-purpose platforms and lack built-in support for special wheel working conditions and industry standards. Users need to complete complex processes such as model building, load definition, boundary condition setting, and evaluation standard matching on their own. The operation is highly professional, prone to errors, and inefficient. Especially for small and medium-sized enterprises, the lack of professional simulation teams and accumulated experience makes it difficult to build a complete simulation system that covers multiple wheel testing requirements. Existing solutions are difficult to replace physical tests in actual applications, and cannot achieve effective auxiliary verification in the early stages of design, which limits the overall digital transformation process of the industry. Based on this, the present invention implements a digital R&D method, device, and server for wheel hubs based on a low-code development platform. Focusing on physical test contents such as wheel hub uniaxial and circumferential radial strength assessment, wheel hub axial strength assessment, wheel hub bending fatigue life assessment, and wheel hub impact strength assessment, a complete set of simulation modeling, load simulation, constraint setting, and evaluation and judgment schemes are proposed. This achieves effective alignment between the wheel design stage and standard test requirements and the design of an industrial simulation application system, thereby allowing users to quickly complete wheel simulation verification, thereby significantly reducing wheel hub R&D costs and improving R&D efficiency.

[0030] See also Figure 2 The flowchart of a wheel hub digital development method based on a low-code development platform is shown, and the method mainly includes the following steps S202 to S208:

[0031] Step S202, obtain the initial wheel hub model, and perform material property mapping processing on the initial wheel hub model based on the interactive information of the user end, so as to simulate the actual material properties of the wheel hub body and the wheel hub R&D auxiliary equipment to obtain the target wheel hub model. In one embodiment, the various components in the initial wheel hub model can be divided based on body features, and the wheel hub body features are determined based on the interactive information of the user end. Then, based on the wheel hub body features, the material properties of the wheel hub body are mapped, and the wheel hub R&D auxiliary equipment is assigned basic material properties to determine the target wheel hub model.

[0032] Specifically, in the initial state of the simulation model, the system automatically assigns a vector mapping relationship of the base material to all body features. The base material is based on the material of the auxiliary device. For example, in the hub bending fatigue life assessment test, assuming that the load arm and fastener materials are cast iron, the system will automatically set the default material of all body features to cast iron. This initial assignment method ensures that the simulation model has uniform material properties in the initial state, which facilitates subsequent material replacement and simulation calculations. The components are distinguished based on the body features. For the material assignment of the hub body, the hub body features are obtained through user interaction, and the material properties are replaced separately. For example, the hub body feature can be selected and assigned an aluminum alloy material. At this time, the system will replace the original default cast iron material with the aluminum alloy material and map it to the hub body feature. This material replacement method can accurately simulate the actual material properties of the hub body while retaining the material characteristics of the auxiliary devices.

[0033] In the subsequent meshing process, the body features are converted into mesh cells. At this point, the system will assign corresponding material property parameters to the mesh cells of each component based on the results of material replacement. For example, the mesh cells of the wheel hub body will have the material properties of aluminum alloy, while the mesh cells of the auxiliary device will retain the material properties of cast iron. This precise material property mapping can ensure the accuracy of the simulation calculation and make the simulation results closer to the effects of actual physical testing. This method provides an efficient and accurate solution for the industrial simulation application of the wheel hub, which can effectively support the digital research and development process of the wheel hub.

[0034] In step S204, feature selection processing is performed on the inner wall surface of the hub center hole of the target hub model to determine the target feature surface, and based on the target feature surface, the load arm coordinate system and the target simulated load arm in the hub research and development auxiliary equipment are determined. In one embodiment, the center of mass coordinates of the target feature surface can be calculated to determine the standard center of mass coordinates of the inner wall surface of the hub center hole, and the standard center of mass coordinates are used as the origin to construct the load arm coordinate system. Then, according to the hub width information, the radius information of the inner wall surface of the hub center hole and the load arm coordinate system, the load arm extension part is simulated to determine the target simulated load arm.

[0035] For details, see Figure 3 A schematic diagram of a hub bending fatigue life assessment is shown. During the digital verification process of the hub bending fatigue life assessment, in order to improve the convenience of industrial simulation applications, the present invention proposes a digital verification method that does not require additional physical testing auxiliary equipment. The user only needs to provide a model of the hub product to complete the simulation analysis of related tests through the digital verification system. In the interactive stage of digital verification, the system first guides the user to select the inner wall surface of the hub center hole (the surface is a cylindrical surface). By accurately selecting the target feature surface and calculating the center of mass coordinates, the system can obtain the standard center of mass coordinates of the inner wall surface of the hub center hole.

[0036] According to the characteristics of the selected cylindrical surface, the value of the cylindrical surface radius and the direction of the cylindrical surface center axis are obtained. These parameters are the key basic data for the subsequent generation of the load arm device. The system sets the center of mass coordinates as the origin of the load arm generation coordinate system, and sets the direction of the cylindrical surface center axis as the Z axis of the generated coordinate system. Based on the orthogonality theorem, the system automatically generates the X axis and Y axis of the coordinate system, thereby constructing a load arm generation coordinate system that is closely related to the geometric characteristics of the inner wall of the hub center hole.

[0037] For the wheel hub model, the system obtains the wheel width data in the wheel hub size through the interactive interface, generates the origin of the coordinate system and the cylindrical radius value based on the load arm, and performs a stretching operation along the Z-axis direction of the coordinate system to form a cylinder with a length equal to the wheel width, simulating the contact part between the load arm and the center hole of the hub in the actual test. Subsequently, the system continues to generate the origin of the coordinate system and the cylindrical radius value based on the load arm, and performs a stretching operation along the -Z-axis direction of the coordinate system to form a cylinder with a length of five times the wheel width, simulating the extended part of the load arm for applying load. Through this series of automated operations, the system can automatically generate a load arm device to assist in digital verification, and its geometric features and positional relationships are highly consistent with the load arm device in the actual physical test.

[0038] This solution not only simplifies the user workflow, eliminating the tedious steps of manually creating complex auxiliary equipment models, but also ensures the accuracy and consistency of the load arm assembly during the digital verification process. Through automated feature selection and geometry generation, the system can quickly construct a load arm assembly that meets test requirements, effectively completing the digital verification of the wheel hub bending fatigue life assessment.

[0039] Step S206, based on the surface feature information of the rim in the load arm coordinate system, the target simulated load arm and the target hub model, simulate the fixed state of the rim and determine the target detection state of the target hub model. In one embodiment, the surface feature information can be assigned to the load arm coordinate system, and the X-axis, Y-axis and Z-axis in the load arm coordinate system after the surface feature information is assigned are constrained by translational freedom, and the X-axis and Y-axis are constrained by rotational freedom to simulate the fixed state of the rim and the rotation state of the target hub model along the Z axis, and the rotation state is determined as the target detection state. That is to say, in In the industrial simulation application of hub bending fatigue life assessment, in order to accurately simulate the state of the hub rim fixed by the rotating disk fastener, the system adopts an open interactive interface. The user inputs interactive information of the hub rim surface to obtain the corresponding surface feature information. Based on the previously generated load arm coordinate system, these surface features are given translational freedom restrictions on the X, Y, and Z axes, as well as rotational freedom restrictions on the X and Y axes, with only the rotational freedom of the Z axis open. This setting simulates the fixed state of the rim in actual physical testing, while allowing rotation in the Z axis direction to reflect real operating conditions.

[0040] Step S208, assigning a load to the target hub model in the target detection state, and using a preset life assessment component and a preset impact assessment component to evaluate and analyze the target hub model to determine the target assessment result, wherein the target assessment result includes: the hub bending fatigue life assessment result and the impact numerical assessment result. In one embodiment, during the load assignment process, the system opens an interactive interface of the load arm force surface, through which the user can obtain the characteristic information of the load arm end face. Based on these characteristics, the system generates the center of mass coordinate information of the end face and couples all nodes of the end face to the center of mass point position. This coupling method ensures that the load force can be transmitted to the entire end face through the center of mass position, and accurately controls the force direction. Through this method, the user can assign any force direction based on the global coordinate system of the model, thereby achieving accurate simulation of the stress state of the hub under different working conditions. The industrial simulation application of hub bending fatigue life assessment is to assess the number of fatigue life. The core logic of the algorithm for converting stress cloud map results into fatigue life number cloud map is based on equivalent stress. Through stress cycle analysis and Goodman criterion correction, combined with the SN curve model of the material, each stress point in the finite element analysis result is mapped to the corresponding number of fatigue life cycles. The embodiment of the present invention also provides an implementation method for evaluating the digital development of the hub. For details, see (1) to (3) below:

[0041] (1) Based on the preset life assessment components and equivalent stress, each stress point in the finite element analysis results is mapped to the corresponding number of fatigue life cycles through stress cycle analysis and fatigue life prediction model. For details, see (A) to (C) below:

[0042] (A) By performing finite element calculation on the target hub model, the finite element calculation results are determined, and the equivalent stress corresponding to each node is extracted from the finite element calculation results. Specifically, the equivalent stress of each node or unit is extracted from the finite element calculation results. It is a scalar value that comprehensively describes the material strength under multi-axial stress state. The calculation formula is:

[0043]

[0044] in, is the first principal stress; is the second principal stress; is the third principal stress; It is the equivalent stress, representing the comprehensive strength actually borne by the point and is used as the basis for fatigue analysis.

[0045] (B) Using the preset stress analysis model, perform stress analysis on the equivalent stress to determine the stress amplitude and mean stress. Using the fatigue life prediction model, perform material fatigue limit analysis based on the mean stress and stress amplitude to determine the influence of the mean stress on the material fatigue limit. This will correct the mean stress and determine the effective stress amplitude. Specifically, determine whether the stress is part of the cyclic loading process. At this time, two key parameters of the stress cycle need to be calculated: stress amplitude ( ) and mean stress ( ). The stress amplitude is defined as half the difference between the maximum and minimum stresses:

[0046] =

[0047] The mean stress is the average of the maximum and minimum stresses:

[0048] =

[0049] These two values ​​have a significant impact on fatigue life under asymmetric cyclic loading. In order to correct the influence of mean stress on fatigue life, the Goodman criterion (i.e., fatigue life prediction model) is introduced. The Goodman correction is a widely used fatigue life prediction method that considers the influence of mean stress on the fatigue limit of the material. Its expression is:

[0050]

[0051] in, is the corrected effective stress amplitude, The ultimate tensile strength of the material is the maximum tensile stress at which the material fails. After applying the Goodman correction, it can more accurately estimate the true fatigue damage. After completing the stress correction, the fatigue life calculation phase begins.

[0052] (C) Based on the target stress-life curve corresponding to the material properties of the target hub model, a functional relationship between stress amplitude and life is established based on the effective stress amplitude, and the functional relationship is solved according to the equivalent stress to determine the number of fatigue life cycles. Specifically, the material's SN curve, that is, the stress-life curve, can be used to establish a functional relationship between stress amplitude and life. This relationship is usually in logarithmic form:

[0053]

[0054] Among them, N is the fatigue life (that is, the number of cycles that the point can withstand under this stress amplitude), a and b are material constants obtained by fitting experimental data. The formula is reversible and the life can be calculated given the stress. Finally, the fatigue life N result of each node or unit is visualized and drawn as a fatigue life cloud map. This step generates the simulation post-processing file through VTK's visualization format file and transmits it to the Web for rendering. The life cloud map is similar to the stress cloud map. The color distribution shows the fatigue life of various parts of the structure. The colder the color (gray is the background color here), the longer the life, and the hotter the color (red) indicates the shorter the life, thereby intuitively identifying the fatigue weak areas of the structure. This result can be used for subsequent structural optimization, material selection or safety factor adjustment.

[0055] (2) See Figure 4 The schematic diagram of another hub bending fatigue life assessment is shown. The circle on the left represents the wheel of the test auxiliary device in the physical test, and the hub on the right is the test model itself. It is necessary to apply a load to its radial surface while driving the hub to rotate to evaluate its fatigue life times. Specifically, in the industrial simulation application of hub bending fatigue life assessment, in order to ensure the accuracy of the model and the reliability of the simulation results, the system strictly restricts the coordinate conditions of the model import. When importing the model, the axis of the hub is required to be along the Z axis of the global coordinate system, and the radial surface of the hub must coincide with the XY plane of the global coordinate system. This coordinate setting method can directly simulate the existence of the auxiliary device wheel in the actual test, which provides convenience for subsequent simulation analysis.

[0056] In the simulation application's interactive interface, users need to input interactive information about the wheel hub and rim surfaces so that the system can obtain the corresponding surface feature data. Based on this data and the load arm, a coordinate system is generated. The system then restricts the model's translational degrees of freedom in the X, Y, and Z axes, while also limiting rotational freedom in the X and Y axes, leaving only rotational freedom in the Z axis. This setup effectively simulates the fixed state of the wheel hub during actual testing.

[0057] To further refine the simulation model, the system uses the interactive interface to obtain the wheel hub outer diameter, thereby determining the radius of the auxiliary wheel and target wheel hub models. The system also obtains the user-selected inner wall surface characteristics of the hub center hole and calculates the center of mass based on this data. Combined with the X and Y axes of the global coordinate system, the system forms a reference surface for auxiliary wheel model generation.

[0058] Based on the center of mass of the inner wall of the hub center hole, the system determines the auxiliary wheel's origin along the global coordinate system's X-axis, with the sum of the radii of the auxiliary wheel and the target hub model as the distance. The system then uses the auxiliary wheel's radius to generate a corresponding planar circle and stretches it along the Z-axis by 100 mm in both the positive and negative directions, forming a circular auxiliary wheel surface. To reduce the number of meshes and improve simulation efficiency, the auxiliary wheel surface is represented using shell elements, and surface meshing is performed during pre-processing.

[0059] During the digital verification process, the system imposed boundary conditions on the auxiliary wheel surface, restricting its translational freedom along the X, Y, and Z axes in the global coordinate system. It also restricted its rotational freedom around the X and Y axes, leaving only the rotational freedom around the Z axis. For the target hub model, the system restricted its translational freedom along the Y and Z axes, and its rotational freedom around the X and Y axes, while leaving the X-axis translational freedom and the Z-axis rotational freedom open.

[0060] The system also offers a flexible load application method. Users can enter the wheel hub center hole inner wall surface characteristics through an interactive interface and apply a load value in the X-axis direction based on this data. To better reflect actual test conditions, the system introduces two input values: an enhanced test coefficient and a rated load parameter. Users can enter these two parameters based on their actual needs, and the system multiplies them to obtain the final load value.

[0061] The system also features a universal formula editing feature for the load application process. Users are no longer limited to a single input-output match. Instead, they can freely construct mathematical logic between input content and actual applied load values ​​through formula editing. This flexible load application method can meet the simulation needs of different users under different working conditions, improving simulation accuracy and applicability.

[0062] The above is the case of radial life assessment in the uniaxial direction of the hub. By synchronously setting the time step and applying a constant speed rotational displacement to the hub model based on the Z axis of the global coordinate system, radial life assessment in the circumferential direction can be achieved.

[0063] (3) The target hub model is rotationally adjusted by a preset model pre-processing component to determine the adjusted target hub model, and the preset impact evaluation component is used to perform an impact evaluation on the adjusted target hub model to determine the target evaluation result according to the number of fatigue life cycles and the impact evaluation result. In one embodiment, the preset impact evaluation component can be used to construct an impact plate based on the adjusted target hub model, and the impact distance of the impact plate is converted into a corresponding initial impact velocity. Finally, the friction parameters corresponding to the test scenario are obtained, and the target hub model is fixed to perform a dynamic analysis on the target hub model based on the friction parameters and the initial impact velocity to determine the impact evaluation result.

[0064] Specifically, in the industrial simulation application of wheel hub impact assessment, a model pre-processing component is specially designed to ensure that the model can accurately simulate the real physical test conditions of the automobile wheel hub. The core function of this component is to process and transform the state of the wheel hub model so that it fully meets the requirements of the testing process. Among them, the automated adjustment process is encapsulated as a model adjustment component, and its primary task is to adjust the rotational shape of the model.

[0065] Specifically, through the interactive interface, users can operate and select the inner wall surface of the hub center hole. The system obtains the characteristic information of the surface and further calculates the center of mass coordinates of the selected surface based on this characteristic information. This center of mass coordinate is then determined as the origin of the rotating coordinate system, and the directions of each axis of the coordinate system are strictly based on the X, Y, and Z axis directions of the global coordinate system. On this basis, the system can use the center of mass coordinate system as a reference to perform precise rotation operations on the model around each coordinate axis, thereby generating a rotated model file, providing an accurate initial state for subsequent impact assessment simulations.

[0066] In industrial simulation applications for wheel impact assessment, a specialized model pre-processing component was designed to accurately simulate the test conditions of automotive wheels. After the model's rotation is adjusted, a "BoundaryBox" operation is performed on the model based on the global coordinate system to obtain the axial maximum point. This maximum point will serve as a reference point for subsequent impact plate creation. The "Boundary Box" defines the minimum enclosing rectangle or cube of a geometric object and is used to quickly determine the model's size range, locate key points, or perform geometric operations. Its calculation principle is primarily based on the model's geometric features and coordinate information. To determine the model's extreme points, the system traverses all vertices or geometric feature points of the model and calculates their coordinate values ​​in the global coordinate system. For 3D models, it is typically necessary to find the maximum and minimum points of the model in the X, Y, and Z directions. These extreme points define the extent of the bounding box.

[0067] Furthermore, the creation of the impact plate is centered on the extreme point, a rectangle is constructed based on the global coordinate system, and stretching is performed to form a solid structure. The length, width, and height parameters of the impact plate can be flexibly adjusted according to actual working conditions to adapt to different test requirements. This impact plate creation method based on extreme points and the global coordinate system can ensure that the relative position and size relationship between the impact plate and the wheel hub model meet the actual test requirements, thereby improving the accuracy and reliability of the simulation.

[0068] In the industrial simulation application of wheel hub impact, the impact distance is converted into the corresponding initial impact velocity. By fixing the wheel hub and assigning friction parameters to the corresponding scenario, dynamic analysis can be performed to obtain the corresponding numerical calculation results.

[0069] In summary, the present invention can develop general components for various physical testing conditions of the wheel hub, including material models, geometric modeling, load application and simulation algorithm modules. Through the rapid development and packaging capabilities of the low-code platform, the complex digital verification process can be simplified into an easy-to-operate digital application, realizing the digital transformation of the wheel hub physical testing process, meeting standard requirements, and helping enterprises to efficiently complete the virtual design and verification of the wheel hub, thereby reducing R&D costs and cycles.

[0070] Regarding the wheel hub digital development method based on the low-code development platform provided in the above embodiment, the embodiment of the present invention provides a wheel hub digital development device based on the low-code development platform, see Figure 5 The following is a schematic diagram of the structure of a wheel hub digital R&D device based on a low-code development platform. The device includes the following parts:

[0071] The information acquisition module 502 acquires an initial wheel hub model and performs material property mapping processing on the initial wheel hub model based on the interactive information of the user terminal to simulate the actual material properties of the wheel hub body and wheel hub R&D auxiliary equipment to obtain a target wheel hub model;

[0072] The feature extraction module 504 performs feature extraction processing on the inner wall surface of the hub center hole of the target hub model to determine the target characteristic surface, and based on the target characteristic surface, determines the load arm coordinate system and the target simulated load arm in the hub R&D auxiliary equipment;

[0073] The state simulation module 506 simulates the fixed state of the rim according to the load arm coordinate system, the target simulated load arm and the surface feature information of the rim in the target hub model to determine the target detection state of the target hub model;

[0074] The evaluation and analysis module 508 assigns a load to the target hub model in the target detection state, and uses a preset life evaluation component and a preset impact evaluation component to evaluate and analyze the target hub model to determine the target evaluation results, wherein the target evaluation results include: hub bending fatigue life evaluation results and impact numerical evaluation results.

[0075] The above-mentioned wheel hub digital R&D device based on the low-code development platform provided in the embodiment of the present application can significantly reduce the wheel hub R&D cost and improve R&D efficiency.

[0076] In one embodiment, when performing material property mapping processing on the initial hub model based on the interactive information of the user end to simulate the actual material properties of the hub body and the hub R&D auxiliary equipment to obtain the target hub model, the above-mentioned information acquisition module 502 is also used to: divide the various components in the initial hub model based on body features, and determine the hub body features based on the interactive information of the user end; map the material properties of the hub body based on the hub body features, and assign basic material properties to the hub R&D auxiliary equipment to determine the target hub model.

[0077] In one embodiment, when performing the steps of determining the load arm coordinate system and the target simulated load arm in the hub R&D auxiliary equipment based on the target feature surface, the feature extraction module 504 is also used to: calculate the center of mass coordinates of the target feature surface, determine the standard center of mass coordinates of the inner wall surface of the hub center hole, and use the standard center of mass coordinates as the origin to construct the load arm coordinate system; simulate the extended part of the load arm according to the hub width information, the radius information of the inner wall surface of the hub center hole and the load arm coordinate system to determine the target simulated load arm.

[0078] In one embodiment, when performing the step of simulating the fixed state of the rim based on the surface feature information of the rim in the load arm coordinate system, the target simulation load arm and the target hub model, and determining the target detection state of the target hub model, the above-mentioned state simulation module 506 is also used to: assign the surface feature information to the load arm coordinate system, perform translational freedom constraints on the X-axis, Y-axis and Z-axis in the load arm coordinate system after the surface feature information is assigned, and perform rotational freedom constraints on the X-axis and Y-axis to simulate the fixed state of the rim and the rotation state of the target hub model along the Z-axis, and determine the rotation state as the target detection state.

[0079] In one embodiment, when performing the step of evaluating and analyzing the target hub model using a preset life assessment component and a preset impact assessment component to determine the target assessment result, the above-mentioned evaluation and analysis module 508 is also used to: based on the preset life assessment component and equivalent stress, through stress cycle analysis and fatigue life prediction model, map each stress point in the finite element analysis result to the corresponding number of fatigue life cycles; rotate and adjust the target hub model through the preset model pre-processing component to determine the adjusted target hub model, and use the preset impact assessment component to perform impact assessment on the adjusted target hub model to determine the target assessment result based on the number of fatigue life cycles and the impact assessment result.

[0080] In one embodiment, when performing the step of mapping each stress point in the finite element analysis result to the corresponding number of fatigue life cycles through stress cycle analysis and fatigue life prediction model based on the preset life assessment component and equivalent stress, the above-mentioned assessment analysis module 508 is also used to: determine the finite element calculation result by performing finite element calculation on the target hub model, and extract the equivalent stress corresponding to each node from the finite element calculation result; use the preset stress analysis model to perform stress analysis processing on the equivalent stress to determine the stress amplitude and average stress, and use the fatigue life prediction model to perform material fatigue limit analysis processing based on the average stress and stress amplitude to determine the influence relationship of the average stress on the material fatigue limit, so as to correct the average stress and determine the effective stress amplitude; establish a functional relationship between stress amplitude and life based on the effective stress amplitude through the target stress-life curve corresponding to the material properties of the target hub model, and solve the functional relationship according to the equivalent stress to determine the number of fatigue life cycles.

[0081] In one embodiment, when performing the step of performing an impact evaluation on the adjusted target hub model using a preset impact evaluation component, the above-mentioned evaluation and analysis module 508 is also used to: construct an impact plate based on the adjusted target hub model using the preset impact evaluation component, and convert the impact distance of the impact plate into a corresponding initial impact velocity; obtain friction parameters corresponding to the test scenario, and perform a dynamic analysis on the target hub model based on the friction parameters and the initial impact velocity by fixing the target hub model to determine the impact evaluation result.

[0082] The device provided in the embodiment of the present invention has the same implementation principle and technical effects as those in the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference can be made to the corresponding content in the aforementioned method embodiment.

[0083] An embodiment of the present invention provides a server. Specifically, the server includes a processor and a storage device. The storage device stores a computer program, and when the computer program is executed by the processor, it executes the method described in any one of the above-mentioned embodiments.

[0084] Figure 6 A structural diagram of a server provided in an embodiment of the present invention, wherein the server 100 includes: a processor 60, a memory 61, a bus 62 and a communication interface 63, wherein the processor 60, the communication interface 63 and the memory 61 are connected via the bus 62; the processor 60 is used to execute an executable module stored in the memory 61, such as a computer program.

[0085] Memory 61 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage. Communication between the system network element and at least one other network element is achieved through at least one communication interface 63 (which may be wired or wireless), and may utilize the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0086] The bus 62 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 6 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0087] Among them, the memory 61 is used to store programs, and the processor 60 executes the program after receiving the execution instruction. The method executed by the device for flow process definition disclosed in any embodiment of the above-mentioned embodiment of the present invention can be applied to the processor 60 or implemented by the processor 60.

[0088] The processor 60 may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above method may be performed by hardware integrated logic circuits or software instructions within the processor 60. The processor 60 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in conjunction with the embodiments of the present invention may be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules within the decoding processor. The software modules may be located in storage media well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or the like. The storage medium is located in the memory 61 , and the processor 60 reads the information in the memory 61 and completes the steps of the above method in combination with its hardware.

[0089] The computer program product of the readable storage medium provided in the embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiment. The specific implementation can be referred to the previous method embodiment and will not be repeated here.

[0090] If the functions 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, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0091] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A wheel hub digital development method based on a low-code development platform, characterized in that: The method comprises: Obtaining an initial wheel hub model and, based on the interactive information from the user, performing material property mapping on the initial wheel hub model to simulate the actual material properties of the wheel hub body and wheel hub R&D auxiliary equipment to obtain a target wheel hub model; Performing feature selection processing on the inner wall surface of the hub center hole of the target hub model to determine a target feature surface, and determining a load arm coordinate system and a target simulation load arm in the hub R&D auxiliary equipment based on the target feature surface; Simulating a fixed state of the rim according to the load arm coordinate system, the target simulated load arm, and surface feature information of the rim in the target hub model to determine a target detection state of the target hub model; Applying a load to the target hub model in the target detection state, and using a preset life assessment component and a preset impact assessment component to perform an assessment and analysis on the target hub model to determine a target assessment result, wherein the target assessment result includes: a hub bending fatigue life assessment result and an impact numerical assessment result; The step of determining the load arm coordinate system and the target simulated load arm in the wheel hub R&D auxiliary equipment based on the target characteristic surface includes: calculating the center of mass coordinates of the target characteristic surface, determining the standard center of mass coordinates of the inner wall surface of the wheel hub center hole, and constructing the load arm coordinate system using the standard center of mass coordinates as the origin; simulating the extended portion of the load arm according to the wheel hub width information, the radius information of the inner wall surface of the wheel hub center hole and the load arm coordinate system to determine the target simulated load arm; Among them, the step of simulating the fixed state of the rim according to the load arm coordinate system, the target simulation load arm and the surface feature information of the rim in the target hub model to determine the target detection state of the target hub model includes: assigning the surface feature information to the load arm coordinate system, constraining the translational degree of freedom of the X-axis, Y-axis and Z-axis in the load arm coordinate system after the surface feature information is assigned, and constraining the rotational degree of freedom of the X-axis and Y-axis to simulate the fixed state of the rim and the rotation state of the target hub model along the Z axis, and determining the rotation state as the target detection state.

2. The wheel hub digital development method based on the low-code development platform according to claim 1 is characterized in that: The step of performing material property mapping processing on the initial hub model based on the interactive information of the user terminal to simulate the actual material properties of the hub body and the hub R&D auxiliary equipment to obtain the target hub model includes: Dividing the components in the initial hub model based on body features, and determining hub body features based on user-side interactive information; According to the hub body characteristics, the material properties of the hub body are mapped, and the hub R&D auxiliary equipment is assigned basic material properties to determine the target hub model.

3. The wheel hub digital development method based on the low-code development platform according to claim 1 is characterized in that: The step of evaluating and analyzing the target hub model using a preset life evaluation component and a preset impact evaluation component to determine a target evaluation result includes: Based on the preset life assessment components and equivalent stress, each stress point in the finite element analysis results is mapped to the corresponding number of fatigue life cycles through stress cycle analysis and fatigue life prediction model; The target hub model is rotationally adjusted by a preset model pre-processing component to determine the adjusted target hub model, and a preset impact assessment component is used to perform an impact assessment on the adjusted target hub model to determine the target assessment result based on the fatigue life cycle number and the impact assessment result.

4. The wheel hub digital development method based on the low-code development platform according to claim 3 is characterized in that: The step of mapping each stress point in the finite element analysis result to a corresponding number of fatigue life cycles through stress cycle analysis and fatigue life prediction model based on the preset life assessment component and equivalent stress includes: Performing finite element calculation on the target hub model to determine finite element calculation results, and extracting equivalent stress corresponding to each node from the finite element calculation results; Using a preset stress analysis model, performing stress analysis on the equivalent stress to determine a stress amplitude and an average stress; using a fatigue life prediction model, performing material fatigue limit analysis based on the average stress and the stress amplitude to determine an influence relationship between the average stress and the material fatigue limit, thereby correcting the average stress and determining an effective stress amplitude; A target stress-life curve corresponding to the material properties of the target hub model is used to establish a functional relationship between the stress amplitude and the life based on the effective stress amplitude. The functional relationship is solved according to the equivalent stress to determine the number of fatigue life cycles.

5. The wheel hub digital development method based on the low-code development platform according to claim 3 is characterized in that: The step of performing impact assessment on the adjusted target wheel hub model using a preset impact assessment component includes: Using a preset impact assessment component, constructing an impact plate based on the adjusted target hub model, and converting the impact distance of the impact plate into a corresponding initial impact velocity; The friction parameters corresponding to the test scenario are obtained, and by fixing the target wheel hub model, a dynamic analysis is performed on the target wheel hub model based on the friction parameters and the initial impact velocity to determine the impact assessment result.

6. A wheel hub digital R&D device based on a low-code development platform, characterized in that: The device comprises: An information acquisition module acquires an initial wheel hub model and, based on the interactive information from the user, performs material property mapping on the initial wheel hub model to simulate the actual material properties of the wheel hub body and wheel hub R&D auxiliary equipment to obtain a target wheel hub model. a feature extraction module, performing feature selection processing on the inner wall surface of the hub center hole of the target hub model, determining a target feature surface, and determining a load arm coordinate system and a target simulated load arm in the hub R&D auxiliary equipment based on the target feature surface; a state simulation module, simulating the fixed state of the rim according to the load arm coordinate system, the target simulated load arm and the surface feature information of the rim in the target hub model, and determining the target detection state of the target hub model; an evaluation and analysis module, which applies a load to the target hub model in the target detection state, and uses a preset life evaluation component and a preset impact evaluation component to perform evaluation and analysis on the target hub model to determine a target evaluation result, wherein the target evaluation result includes: a hub bending fatigue life evaluation result and an impact numerical evaluation result; The step of determining the load arm coordinate system and the target simulated load arm in the wheel hub R&D auxiliary equipment based on the target characteristic surface includes: calculating the center of mass coordinates of the target characteristic surface, determining the standard center of mass coordinates of the inner wall surface of the wheel hub center hole, and constructing the load arm coordinate system using the standard center of mass coordinates as the origin; simulating the extended portion of the load arm according to the wheel hub width information, the radius information of the inner wall surface of the wheel hub center hole and the load arm coordinate system to determine the target simulated load arm; Among them, the step of simulating the fixed state of the rim according to the load arm coordinate system, the target simulation load arm and the surface feature information of the rim in the target hub model to determine the target detection state of the target hub model includes: assigning the surface feature information to the load arm coordinate system, constraining the translational degree of freedom of the X-axis, Y-axis and Z-axis in the load arm coordinate system after the surface feature information is assigned, and constraining the rotational degree of freedom of the X-axis and Y-axis to simulate the fixed state of the rim and the rotation state of the target hub model along the Z axis, and determining the rotation state as the target detection state.

7. A server, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method according to any one of claims 1 to 5.

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