Automobile suspension component model generation method and device, electronic equipment and storage medium

Abstract

The application provides a method and device for generating a model of an automobile suspension component, electronic equipment and a storage medium, relates to the technical field of automobile modeling, and comprises the following steps: in response to a modeling instruction for a target suspension component, obtaining an outer shell grid model of the target suspension component and target attribute parameters, the target attribute parameters at least including target centroid coordinates; establishing a local coordinate system based on the target centroid coordinates, and cutting the outer shell grid model into multiple independent partitions according to the coordinate plane of the local coordinate system; determining the target density of each independent partition based on the target centroid coordinates, and mapping the target density to the corresponding independent partition to generate a model of the automobile suspension component. The application significantly improves the modeling efficiency while ensuring the accuracy of CAE analysis.

Description

Technical Field

[0001] This application relates to the field of automotive modeling technology, and in particular to a method, apparatus, electronic device, and storage medium for generating automotive suspension component models. Background Technology

[0002] In CAE modal and strength analysis of automotive suspension components, simplified modeling methods are often used to balance modeling efficiency and accuracy. Existing technologies mainly include the mass point method and the shell uniformly distributed mass method. While the mass point method can guarantee the model's mass and center of mass, the lack of true stiffness in the connecting elements leads to lower modal analysis results and overly conservative strength analysis. The shell uniformly distributed mass method, while preserving structural stiffness, cannot accurately reproduce the center of mass and inertia, severely impacting simulation accuracy. Therefore, how to quickly construct a suspension component CAE model that guarantees structural stiffness and accurately matches mass and center of mass properties, even in the absence of detailed internal structural data, is a pressing technical problem that needs to be solved. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, electronic device, and storage medium for generating automotive suspension component models, so as to alleviate the aforementioned technical problems existing in the prior art.

[0004] In a first aspect, the present invention provides a method for generating a model of an automobile suspension component, comprising: In response to a modeling instruction for a target suspension component, the shell mesh model and target attribute parameters of the target suspension component are obtained, wherein the target attribute parameters include at least the target centroid coordinates; A local coordinate system is established based on the target centroid coordinates, and the shell mesh model is cut into multiple independent partitions according to the coordinate plane of the local coordinate system; The target density of each independent partition is determined based on the target centroid coordinates, and the target density is mapped to the corresponding independent partition to generate an automotive suspension model.

[0005] In an optional implementation, after obtaining the shell mesh model and target attribute parameters of the target suspension component, the method further includes: Identify geometric defects in the shell mesh model; the geometric defects include free edges or overlapping elements; The geometric defects are repaired by meshing to generate a shell mesh model with a complete topology, and the step of establishing a local coordinate system is performed based on the repaired shell mesh model.

[0006] In an optional implementation, a local coordinate system is established based on the target centroid coordinates, including: Obtain the origin and axial information of the vehicle coordinate system pre-configured for the target suspension component; Using the target centroid coordinates as the origin, the coordinate axis direction is determined based on the axial information, and a local coordinate system parallel to the vehicle coordinate system is established, with the target centroid coordinates as the origin of the local coordinate system.

[0007] In an optional implementation, the shell mesh model is divided into multiple independent partitions according to the coordinate plane of the local coordinate system, including: Traverse the mesh cells in the shell mesh model and determine the geometric center coordinates of each mesh cell; The geometric center coordinates are mapped to the local coordinate system, and the grid cell is divided into multiple independent partitions according to the positive and negative coordinate components of the geometric center coordinates in the local coordinate system.

[0008] In an optional implementation, determining the target density of each of the independent partitions based on the target centroid coordinates includes: Obtain the target total mass of the target suspension component, and calculate the initial average density of each independent partition based on the target total mass and the volume of each independent partition; Based on the target centroid coordinates, an inertial moment balance constraint is constructed, and the initial average density is adjusted according to the inertial moment balance constraint to determine the target density of each independent partition.

[0009] In an optional implementation, adjusting the initial average density according to the moment of inertia balance constraint to determine the target density of each of the independent zones includes: Calculate the moment of inertia contribution value of each independent partition relative to the target centroid coordinates, and construct a density correction coefficient based on the moment of inertia contribution value; The initial average density is weighted and corrected using the density correction coefficient to obtain the target density of each independent partition; the target density is used to calculate the theoretical centroid so that the theoretical centroid of each independent partition coincides with the target centroid coordinates.

[0010] In an optional implementation, mapping the target density to corresponding independent partitions to generate an automotive suspension model includes: Based on the target density of each independent partition, a corresponding material property card is generated; wherein the material property card contains the value of the target density; The material property cards are mapped to the corresponding independent partitions of the grid cells, and the properties of the grid cells are checked. If the attribute check meets the preset attributes, a car suspension model containing density distribution information is generated.

[0011] Secondly, the present invention provides an apparatus for generating a model of an automobile suspension component, comprising: The acquisition module is used to acquire the shell mesh model and target attribute parameters of the target suspension component in response to the modeling command for the target suspension component, wherein the target attribute parameters include at least the target centroid coordinates; The partitioning determination module is used to establish a local coordinate system based on the target centroid coordinates, and to cut the shell mesh model into multiple independent partitions according to the coordinate plane of the local coordinate system; The model generation module is used to determine the target density of each independent partition based on the target centroid coordinates, and map the target density to the corresponding independent partition to generate an automotive suspension model.

[0012] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the method described in any of the foregoing embodiments.

[0013] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the method described in any of the foregoing embodiments.

[0014] The method, apparatus, electronic device, and storage medium for generating automotive suspension models provided in this application acquire the shell mesh model and target centroid coordinates in response to modeling instructions. This provides a fundamental data source for building analysis models when the supplier does not provide the internal structure, solving the problem of the lack of feasibility for detailed modeling in the early stages of development. A local coordinate system is established based on the target centroid coordinates, and the shell is divided into multiple independent partitions according to the coordinate plane. This quantifies the spatial positional relationship of each partition relative to the centroid, providing an operable geometric framework for partition density adjustment. The target density of each independent partition is determined based on the target centroid coordinates and mapped to the corresponding partition, ensuring that the mesh model is consistent with the engineering input in terms of mass and centroid. Simultaneously, the continuity of structural stiffness is ensured through shared node connections between partitions, avoiding the problems of large centroid deviation and Rbe3 connection stiffness distortion in uniform density modeling. Overall, this application significantly improves modeling efficiency while maintaining CAE analysis accuracy. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating a method for generating a car suspension component model provided in an embodiment of this application; Figure 2 A cutting diagram provided for an embodiment of this application; Figure 3 A flowchart illustrating a block-based modeling method for automotive suspension components provided in this application embodiment; Figure 4 A structural diagram of a device for generating an automobile suspension model provided in an embodiment of this application; Figure 5 This is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0018] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0019] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0020] This application provides a method for generating automotive suspension component models. This method is used to quickly generate finite element mesh models of suspension components that meet the accuracy requirements of CAE modal analysis and strength analysis during the vehicle development stage. In vehicle development, the suspension component, as a core load-bearing component, directly affects the vehicle's durability and NVH performance due to its modal and strength properties. Therefore, modal analysis and strength simulation of the suspension component need to be carried out during the development stage. However, in actual engineering, situations often arise where suspension component suppliers have not yet been selected, providing only external styling surfaces without detailed internal structures, making detailed modeling impossible. Existing simplified modeling methods (such as uniform density distribution shell modeling or simple centroid point with Rbe3 connections) suffer from problems such as inability to guarantee centroid and inertia, or underestimating modal analysis results and exhibiting harsh strength conditions.

[0021] This method divides the mesh model of the suspension component's outer shell into multiple independent partitions based on the centroid location, and establishes a system of equations to solve for the material density of each partition. This ensures that the mass and centroid of the mesh model are consistent with the engineering input, while the stiffness of the outer shell structure is guaranteed by a unified elastic modulus of the outer shell material. See also Figure 1 As shown, the method mainly includes the following steps: S110, in response to a modeling instruction for the target suspension component, obtain the shell mesh model and target attribute parameters of the target suspension component, wherein the target attribute parameters include at least the target centroid coordinates.

[0022] Modeling commands are operational instructions initiated by engineers in CAE preprocessing software (such as HyperMesh, ANSA, etc.) to create a finite element mesh model for a target suspension component. The target suspension component refers to automotive suspension parts requiring modal or strength analysis, such as batteries, control arms, and subframes. The shell mesh model refers to the finite element mesh generated after meshing the outer shell geometry of the target suspension component. This mesh consists of multiple elements and nodes, representing the external geometry of the suspension component. When the supplier has not yet been selected and only provides the external styling surface (CAS surface), the engineer performs meshing based on this external styling surface to generate the shell mesh model.

[0023] Target attribute parameters refer to physical attribute parameters such as mass and center of gravity input by the engineering team. The target center of gravity coordinates are the three-dimensional coordinates of the center of gravity in the vehicle coordinate system or a local coordinate system, provided by engineers based on the actual weight distribution of the suspension component. These coordinates guide subsequent density allocation. The target center of gravity coordinates are typically provided by product engineers based on the actual mass distribution of the suspension component, reflecting the position of the center of gravity of the suspension component in its actual installed state.

[0024] In practice, engineers import the external geometry of the target suspension component into CAE preprocessing software, mesh the external geometry according to preset mesh size requirements, and generate a shell mesh model. Simultaneously, engineers obtain the target mass and centroid coordinates of the target suspension component from product engineers as input parameters for subsequent density calculations.

[0025] S120, establish a local coordinate system based on the target centroid coordinates, and cut the shell mesh model into multiple independent partitions according to the coordinate plane of the local coordinate system.

[0026] A local coordinate system refers to a Cartesian coordinate system established with the target centroid coordinates as the origin. This coordinate system is used to map the spatial position of the shell mesh model to a reference system with the centroid as the origin, thereby facilitating the calculation of the positional relationship of each region relative to the centroid. Independent partitions refer to multiple non-overlapping sub-regions formed after the shell mesh model is cut by a coordinate plane.

[0027] In practice, the system establishes a local coordinate system parallel to the vehicle coordinate system, using the target centroid coordinates as the origin and the axial direction of the vehicle coordinate system as the reference direction. Then, the system divides the outer shell mesh model into multiple independent partitions based on the XOY, XOZ, and YOZ coordinate planes. Since the three coordinate planes intersect at the origin, they divide the three-dimensional space into eight octaves, theoretically allowing for a maximum of eight independent partitions. However, due to the varying positional relationships between the suspension component's geometry and its centroid, the actual number of partitions may be less than eight—when the centroid is outside the outer shell geometry, some octave regions may not contain any mesh elements, resulting in empty partitions.

[0028] Figure 2 A schematic diagram of the cutting process is shown. In the CAE preprocessing software, the system establishes a local coordinate system parallel to the vehicle coordinate system, using the centroid coordinates (X, Y, Z) of the suspension component input by the product engineer as the origin. After establishing the coordinate system, the system cuts the outer shell mesh model of the suspension component into multiple independent partitions based on the three coordinate planes (XOY plane, XOZ plane, YOZ plane) of this local coordinate system.

[0029] Due to the varying positional relationship between the suspension component's external geometry and its center of mass, the actual number of partitions created may differ. When the center of mass is located inside the outer shell geometry, the three coordinate planes divide the complete shell into eight octagonal regions. Each octagon's mesh cells constitute an independent partition, resulting in a total of eight partitions. However, when the center of mass is located outside the outer shell geometry or offset to one side, some octagonal regions may not contain any mesh cells, making the corresponding partition an empty partition. Therefore, the actual number of partitions may be less than eight. During the cutting process, mesh nodes on the dividing surface are merged using a common-node technique to ensure complete overlap of mesh cells between adjacent partitions at the dividing surface. This guarantees the continuity of structural stiffness and avoids stiffness loss or stress concentration caused by mesh discontinuities.

[0030] After partitioning, the system traverses all mesh elements and assigns each element to its corresponding partition based on the sign of its coordinate components (X, Y, Z) in the local coordinate system. Subsequently, the system calculates the total volume of the entire suspension shell mesh model, the volume of each of the eight regions, and the centroid coordinates of each region under uniform density conditions, which serve as input parameters for the subsequent density equations.

[0031] During the cutting process, the system traverses all mesh elements in the shell mesh model, determining the coordinate components (X, Y, Z) of the geometric center of each mesh element in the local coordinate system. Based on the sign of the X, Y, and Z coordinate values ​​of the geometric center of the mesh element, it is assigned to the corresponding partition—for example, mesh elements with positive X, positive Y, and positive Z are assigned to the first partition, those with negative X, positive Y, and positive Z are assigned to the second partition, and so on. The meshes on the segmented surface are connected using a common-node technique to ensure that the mesh nodes between adjacent partitions coincide, thereby guaranteeing the continuity of structural stiffness.

[0032] S130, determine the target density of each independent partition based on the target centroid coordinates, and map the target density to the corresponding independent partition to generate an automotive suspension model.

[0033] The target density refers to the material density value assigned to each independent partition. This value ensures that, after assigning the corresponding density to each partition, the centroid of the entire mesh model coincides with the target centroid coordinates, and the total mass equals the target mass. The automotive suspension model, after density assignment, is a finite element model containing complete mesh topology and partition density information, which can be used for subsequent modal and strength analyses.

[0034] In practical implementation, the system first obtains the target total mass of the target suspension component and calculates the volume of each independent partition. Then, based on the target total mass and the volume of each partition, a system of equations is established—with the density of each partition as the unknown and the centroid equation and mass equation as constraints—to obtain the density value of each partition. The centroid equation requires that the sum of the mass moments of each partition be zero (i.e., the centroid is located at the origin of the local coordinate system), and the mass equation requires that the sum of the masses of each partition equals the target total mass. Since the number of partitions is at most eight, while the number of constraint equations is at most four (centroid equation in the X direction, centroid equation in the Y direction, centroid equation in the Z direction, and mass equation), the number of unknowns exceeds the number of equations. Therefore, additional constraints need to be introduced (e.g., specifying some partition densities as preset values) to reduce the non-homogeneous system of equations to a homogeneous system for solution, and all density values ​​must be non-negative. After obtaining the density of each partition, the system maps the density values ​​to the corresponding mesh cells within the partition, generating a car suspension component model containing partition density distribution information.

[0035] The automotive suspension component model generation method provided in this application obtains the shell mesh model and target centroid coordinates, establishes a local coordinate system with the target centroid as the origin, and divides the shell into multiple partitions. Then, based on the target centroid coordinates, the target density of each partition is determined and mapped to the corresponding partition, ensuring that the generated mesh model maintains consistency with the engineering input in terms of mass and centroid. Simultaneously, the continuity of structural stiffness is guaranteed through shared-node meshing. Compared with existing technologies, this method solves the problems of unreliable centroid in uniform-density shell modeling and the underestimation of the Rbe3 connection mode at the centroid point. It can quickly establish a suspension component mesh model that meets the accuracy requirements of CAE analysis.

[0036] For ease of understanding, the method provided in this application will be described in detail below.

[0037] In one specific implementation, after obtaining the shell mesh model of the target suspension component, the system also performs geometric defect identification and repair processing on the mesh model.

[0038] In CAE preprocessing, mesh models generated directly from external modeling surfaces may contain various geometric defects, including free edges and overlapping elements. Free edges refer to boundary edges in the mesh model used by only one element, typically indicating an opening or crack in the mesh at that location. This results in an incomplete mesh, affecting subsequent partitioning and structural stiffness transfer. Overlapping elements refer to two or more elements occupying the same or partially the same spatial location, leading to duplicate volume calculations and abnormal structural stiffness.

[0039] Specifically, the system invokes the built-in mesh inspection tool of the CAE preprocessing software to traverse all elements and edges in the shell mesh model, identifying free edges used by only one element and overlapping elements that are reused repeatedly. For identified free edges, the system repairs them by moving node positions or filling in missing elements, making the free edges internal edges shared by two elements. For identified overlapping elements, the system deletes duplicate elements, retaining only one valid element. After the repair process, the system generates a shell mesh model with a complete topology, ensuring that subsequent partitioning operations can be executed correctly and that the volume and stiffness of the mesh model can be accurately calculated.

[0040] In one specific implementation, the local coordinate system is established based on the target centroid coordinates as follows.

[0041] The system acquires the origin and axial information of the vehicle coordinate system pre-configured for the target suspension component. The vehicle coordinate system is a unified reference coordinate system used in the vehicle design phase. Its origin is usually located at the center of the front axle or the geometric center of the vehicle. The X-axis points to the rear or front of the vehicle, the Y-axis points to the width of the vehicle, and the Z-axis points to the height of the vehicle.

[0042] The system uses the target centroid coordinates as the origin and determines the coordinate axis directions based on the axial information of the vehicle coordinate system, establishing a local coordinate system parallel to the vehicle coordinate system. In other words, the three coordinate axes of the local coordinate system are parallel to the X, Y, and Z axes of the vehicle coordinate system, respectively, but the origin is different—the origin of the local coordinate system is located at the target centroid coordinates, not at the origin of the vehicle coordinate system. This established local coordinate system ensures that the coordinate values ​​of each mesh element directly reflect its spatial position relative to the centroid, facilitating the subsequent establishment and solution of the centroid equations.

[0043] In one specific implementation, the shell mesh model is divided into multiple independent partitions according to the coordinate plane of the local coordinate system as follows.

[0044] The system iterates through all mesh elements in the shell mesh model to determine the geometric center coordinates of each mesh element. The geometric center coordinates of a mesh element are calculated by averaging the coordinates of all nodes in that element. Then, the system maps the geometric center coordinates of each mesh element from the global coordinate system to the local coordinate system, obtaining the coordinate components (X_local, Y_local, Z_local) of that mesh element in the local coordinate system.

[0045] The system assigns a grid cell to a corresponding independent partition based on the sign of its coordinate components in the local coordinate system. Specifically, if the X_local, Y_local, and Z_local coordinate values ​​of a grid cell are all positive, the cell is assigned to the first partition; if X_local is negative, Y_local is positive, and Z_local is positive, the cell is assigned to the second partition; if X_local is positive, Y_local is negative, and Z_local is positive, the cell is assigned to the third partition; if X_local is negative, Y_local is negative, and Z_local is positive, the cell is assigned to the fourth partition; if X_local is positive, Y_local is positive, and Z_local is negative, the cell is assigned to the fifth partition; and so on, for a total of eight partitions corresponding to eight octaves.

[0046] During the partitioning process, the grid cells located on the coordinate plane—that is, the coordinate component of their geometric center is exactly zero—need to be specially processed according to the size and position of the grid cells. They are usually allocated according to the volume ratio of the grid cell on both sides of the coordinate plane or according to the affiliation of adjacent grid cells, so as to ensure that the boundaries between each partition are clear and seamless.

[0047] In one specific implementation, the method for determining the target density of each independent partition based on the target centroid coordinates is as follows.

[0048] The system obtains the target total mass of the suspension component, which is provided by the product engineer based on the actual weight of the suspension component. Simultaneously, the system calculates the volume Vi of each independent zone. Assuming uniform density across all zones, the mass of a zone is equal to its density multiplied by its volume.

[0049] The system calculates the initial average density of each independent partition based on the total target mass and the volume of each partition. The initial average density ρ_avg = m_target / V_total, where m_target is the total target mass and V_total is the sum of the volumes of each partition (i.e., the total volume of the shell mesh model). This initial average density is the density value assumed to be uniform across the entire shell mesh model.

[0050] Then, the system constructs moment of inertia balance constraints based on the target centroid coordinates. In the local coordinate system, the centroid is located at the origin if the sum of the mass moments of each partition is zero, i.e., ∑(Vi·ρi·xi)=0, ∑(Vi·ρi·yi)=0, ∑(Vi·ρi·zi)=0. These equations use the density ρi of each partition as the unknown. Solving the mass equation ∑(Vi·ρi)=m_target simultaneously constitutes a system of equations for solving the density of each partition. Since the number of partitions is at most eight, while the number of equations is at most four (three centroid equations plus one mass equation), the number of unknowns exceeds the number of equations. The system adjusts the initial average density according to the moment of inertia balance constraints to determine the target density of each partition.

[0051] In one specific implementation, the method for adjusting the initial average density according to the moment of inertia balance constraint in step S130 to determine the target density of each partition is as follows.

[0052] The system calculates the moment of inertia contribution of each independent partition relative to the target centroid coordinates. For the i-th partition, its moment of inertia contribution is the volume Vi of that partition multiplied by the coordinate components (xi, yi, zi) of the centroid in the local coordinate system. The system constructs density correction coefficients based on these moment of inertia contributions.

[0053] Specifically, the system treats the density ρi of each partition as an unknown and establishes the following system of equations: The equation of the centroid (taking the X direction as an example): ∑(Vi·ρi·xi)=0, and the same applies to the Y and Z directions.

[0054] Mass equation: ∑(Vi·ρi)=m_target.

[0055] Since the number of unknowns (number of partitions, up to 8) exceeds the number of equations (4), the system sets the density of some partitions to specified values. These specified values ​​can be based on the initial average density or selected according to engineering experience, reducing the non-homogeneous system of equations to a homogeneous system. The system requires all density values ​​ρi ≥ 0 because negative density is physically meaningless.

[0056] After setting the density of some partitions, the system solves the reduced-order system of equations to obtain the density values ​​of the remaining partitions. In the solution results, non-zero solutions are directly set as the density values ​​of the corresponding partitions, while the density of the zero-solution region (the partition with a solution result of zero) is set to a minimum value (e.g., 1e-20) to maintain the existence of grid cells but contribute almost no mass. In this way, the theoretical centroid of each partition coincides with the target centroid coordinates, and the total mass equals the target total mass.

[0057] After the solution is completed, the system will compare and verify the calculated theoretical centroid with the target centroid. If the deviation between the two is within an acceptable range (e.g., the deviation is less than 1 mm), the solution is valid; if the deviation is large, the system will reselect the zone with the set density or reset the density value, and solve the equation system again until the accuracy requirements are met.

[0058] In one specific implementation, the method for mapping the target density to the corresponding independent partition to generate the automotive suspension model is as follows.

[0059] The system generates corresponding material property cards based on the target density of each independent partition. In the CAE preprocessing software, the material property card contains physical parameters such as the material's density, elastic modulus, and Poisson's ratio. The system generates an independent material property card for each partition, with the density field set to the target density value for that partition. The elastic modulus and Poisson's ratio are kept consistent across all partitions—using the standard elastic modulus and Poisson's ratio of the shell material (e.g., steel or aluminum alloy) to ensure uniform structural stiffness.

[0060] The system maps the generated material property cards for each partition to the corresponding mesh cells within that partition. Specifically, the system iterates through all mesh cells in each partition and writes the material property card ID corresponding to that partition into the cell attribute field, enabling the mesh cells to read the correct material property parameters in subsequent CAE calculations.

[0061] After completing the material property mapping, the system performs property checks on the mesh elements. The property checks include: confirming that all mesh elements have been assigned material properties, confirming that the density values ​​in each material property card are positive and reasonable, and confirming that the common node connections between different partitions are normal. If the property checks meet the preset property conditions (i.e., all elements have properties, density values ​​are within a reasonable range, and common node connections are complete), a car suspension component model containing density distribution information is generated. This model can be directly used for subsequent modal analysis and strength analysis.

[0062] In an alternative implementation, for non-homogeneous equation systems, the system directly solves the non-homogeneous equation systems without order reduction. Setting all density values ​​ρi ≥ 0, the system directly solves the non-homogeneous equation system consisting of the centroid equation and the mass equation. Non-zero solutions in the solution are assigned to corresponding partitions, and the density of the zero-solution partition is set to 1e-20. While this method may not achieve precise centroid matching, it can obtain approximate solutions that meet the requirements of CAE software and can be used in the initial analysis stages where high precision is not required.

[0063] In another alternative implementation, the system divides the shell mesh model into more partitions (e.g., more than eight regions) to form a system of optimization equations to solve for the density of each region. Dividing the model into more regions increases the number of unknowns, giving the equations more degrees of freedom. This results in a smoother density distribution while satisfying the centroid and mass constraints, further reducing the deviation between the model and the actual suspension component.

[0064] Figure 3 The flowchart of the CAE model segmentation modeling method for automotive suspension components provided in this application embodiment illustrates the entire process from importing geometry to outputting a verification model. The method includes the following steps: S1: Import the suspension geometry entered by the engineer. The engineer imports the external shape geometry of the target suspension into the CAE preprocessing software. This geometry is usually the external CAS surface provided by the supplier before the supplier has been selected, and does not include the internal detailed structure.

[0065] S2: Using the input centroid as the origin, the system divides the suspension housing geometry into multiple regions. The system establishes a local coordinate system parallel to the vehicle coordinate system, using the centroid coordinates input by the product engineer as the origin. Based on the XOY, XOZ, and YOZ coordinate planes of this local coordinate system, the suspension housing geometry is divided into multiple independent zones. Due to the different positional relationships between the suspension housing shape and the centroid, the number of zones may vary—up to 8 zones can be created when the centroid is inside the housing geometry, and fewer than 8 zones when the centroid is outside or offset from the housing geometry.

[0066] S3: Calculate the centroid and volume of each partitioned region based on its isodense density. Assuming uniform density across all partitions, the system calculates the volume of each partition and the coordinates of its centroid under uniform density, serving as input parameters for solving the subsequent equations.

[0067] S4: Establish coordinate equations with the centroid coinciding with the geometric center, and use the mass equation as the boundary condition. The system establishes a system of equations with the density of each region as unknowns—the centroid equation requires the sum of the mass moments of each region to be zero (i.e., the centroid is located at the origin of the local coordinate system), and the mass equation requires the sum of the masses of each region to equal the total target mass. Since the number of unknowns exceeds the number of equations, the system, based on the positional relationship between the uniform density centroid and the input centroid, sets the density of some regions to the average density, reducing the non-homogeneous system of equations to a homogeneous system, and sets all density values ​​Pi≥0.

[0068] S5: Solve the homogeneous equation system. The system solves the reduced-order homogeneous equation system to obtain the density values ​​of each partition. Non-zero solutions are directly set as the density of the corresponding region, while the density of the zero solution region is set to a minimum value (e.g., 1e-20) to maintain the existence of grid cells but contribute almost no mass.

[0069] S6: Set the solution to the corresponding region density, and compare the overall centroid and mass automatically output by the software with the engineer's input for verification. If the calculated centroid deviates significantly from the input centroid, reset the density of the initial region and solve the above equations again until verification is successful.

[0070] This process achieves consistency between the mesh model's mass and centroid and the engineering input through partitioned density allocation, while ensuring the continuity of structural stiffness through shared-node meshes.

[0071] The technical solution of this application will be fully explained below with reference to a specific implementation example.

[0072] Assuming a vehicle's battery is the target suspension component, modal and strength analyses are required. In the early stages of development, the battery supplier was not yet selected; only the external styling surface (CAS surface) was provided, without detailed internal structure information. The product engineer provided the target battery mass m_input = 12.7 kg, and the target center of mass coordinates in the vehicle coordinate system (X: -155.169 mm, Y: -373.422 mm, Z: 424.579 mm).

[0073] Engineers imported the external shape of the battery into the CAE preprocessing software HyperMesh, and meshed the shape according to the preset mesh size requirements to generate the shell mesh model. The engineers then input the target centroid coordinates and mass provided by the product engineers into the system.

[0074] The system establishes a local coordinate system parallel to the vehicle coordinate system, with the target centroid coordinates (-155.169, -373.422, 424.579) as the origin. Then, based on the XOY, XOZ, and YOZ coordinate planes, the shell mesh model is divided into eight independent partitions, Solid_1 to Solid_8. After division, the system traverses all mesh elements, mapping the geometric center coordinates of each element to the local coordinate system, and assigning the element to the corresponding partition based on the sign of its coordinate components. The meshes on the segmented surfaces are connected using a common-node technique to ensure the continuity of structural stiffness.

[0075] The system calculates the volume of the eight partitions, and the results are as follows: Solid_1 has a volume of 808381.457 mm³, and its centroid coordinates under uniform density are (-56.8, 27.6, 44.0). Solid_2 has a volume of 801478.461 mm³ and a centroid coordinate of (-55.4, -33.9, 45.2). The solid_3 has a volume of 736776.312 mm³ and a centroid coordinate of (58.4, 34.2, 44.0). The solid_4 has a volume of 779284.021 mm³ and a centroid coordinate of (60.7, -27.2, 45.2). Solid_5 has a volume of 609850.820 mm³ and a centroid coordinate of (58.8, 34.5, -54.6). The solid_6 has a volume of 628311.270 mm³ and a centroid coordinate of (60.6, -27.0, -54.6). The Solid_7 has a volume of 646412.085 mm³ and a centroid coordinate of (-55.3, -33.7, -54.6). The Solid_8 has a volume of 668973.186 mm³ and a centroid coordinate of (-57.2, 27.9, -54.6).

[0076] The system establishes the centroid equation and the mass equation. The centroid equation requires: ∑(Vi·ρi·xi)=0, ∑(Vi·ρi·yi)=0, ∑(Vi·ρi·zi)=0. The mass equation requires: ∑(Vi·ρi)=12.7kg. Due to 8 unknowns and 4 equations, the system sets the densities of Solid_1, Solid_3, Solid_5, and Solid_7 to an initial average density value of 2.231e-9 t / mm³ based on the deviation between the initial overall geometrically uniform density centroid and the target centroid, reducing the non-homogeneous equation system to a homogeneous one. After solving the homogeneous equation system, the density values ​​of Solid_2, Solid_4, Solid_6, and Solid_8 are all 2.236125e-9 t / mm³. The system sets each density value to its corresponding partition and generates corresponding material property cards, mapping them to the mesh elements within the corresponding partition. After the attribute check passes, a complete finite element model of the battery is generated.

[0077] Engineers submitted the model to a CAE solver for modal and strength analysis. The analysis results showed that the model's mass and center of mass were consistent with the product engineer's input, and the modal frequencies and stress distribution accurately reflected the battery's structural characteristics, meeting the accuracy requirements for project decision-making. Compared to traditional uniform density modeling methods (where center of mass deviation can reach tens of millimeters), this method's center of mass deviation is less than 1 mm, significantly improving analysis accuracy. Compared to the method of adding Rbe3 connections to the center of mass, this method ensures the accuracy of modal analysis through the stiffness of the outer shell structure. The entire modeling process took approximately 10 minutes, a significant reduction from the hours to days required for detailed modeling.

[0078] In summary, this application obtains the shell mesh model and target centroid coordinates, establishes a local coordinate system with the centroid as the origin, and divides the shell into multiple partitions. Then, by solving the density equations, the theoretical centroid of each partition coincides with the target centroid. The generated mesh model maintains consistency with the engineering input in terms of mass and centroid, while ensuring the continuity of structural stiffness through shared-node meshing. Compared to uniform density shell modeling methods (where the centroid cannot be guaranteed, with deviations reaching tens of millimeters), this method significantly improves centroid accuracy. Compared to the centroid-point-plus-Rbe3 connection method (which results in smaller modes and poorer strength), this method ensures the accuracy of the analysis results through structural stiffness. Compared to detailed modeling methods (which take hours to days), this method can complete modeling within ten minutes. This method significantly improves modeling efficiency while ensuring CAE analysis accuracy, making it particularly suitable for the early stages of development before supplier selection.

[0079] Based on the above method embodiments, this application also provides an apparatus for generating an automobile suspension model, see below. Figure 4 As shown, the device includes the following parts: The acquisition module 410 is used to acquire the shell mesh model and target attribute parameters of the target suspension component in response to the modeling instruction for the target suspension component, wherein the target attribute parameters include at least the target centroid coordinates. The partitioning determination module 420 is used to establish a local coordinate system based on the target centroid coordinates, and to cut the shell mesh model into multiple independent partitions according to the coordinate plane of the local coordinate system; The model generation module 430 is used to determine the target density of each independent partition based on the target centroid coordinates, and map the target density to the corresponding independent partition to generate an automotive suspension model.

[0080] The device provided in this application embodiment has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts of the device embodiment not mentioned can be referred to the corresponding content in the aforementioned method embodiment.

[0081] This application also provides an electronic device, such as... Figure 5 The diagram shows the structure of the electronic device 100, which includes a processor 51 and a memory 50. The memory 50 stores computer-executable instructions that can be executed by the processor 51. The processor 51 executes the computer-executable instructions to implement any of the methods described above.

[0082] exist Figure 5 In the illustrated embodiment, the electronic device further includes a bus 52 and a communication interface 53, wherein the processor 51, the communication interface 53, and the memory 50 are connected via the bus 52.

[0083] The memory 50 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 53 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 52 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 52 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0084] The processor 51 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 51 or by instructions in software form. The processor 51 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. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in the memory, and the processor 51 reads the information in the memory and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiment.

[0085] This application also provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the above-described method. For specific implementation details, please refer to the foregoing method embodiments, which will not be repeated here.

[0086] The computer program product of the method, apparatus, electronic device and storage medium for generating automobile suspension model provided in the embodiments of this application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0087] Unless otherwise specifically stated, the relative steps, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application.

[0088] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0089] In the description of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. In addition, the terms "first," "second," and "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0090] Furthermore, terms such as "horizontal," "vertical," and "sag" do not imply that components must be absolutely horizontal or suspended, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal relative to "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for generating a model of an automotive suspension component, characterized in that, include: In response to a modeling instruction for a target suspension component, the shell mesh model and target attribute parameters of the target suspension component are obtained, wherein the target attribute parameters include at least the target centroid coordinates; A local coordinate system is established based on the target centroid coordinates, and the shell mesh model is cut into multiple independent partitions according to the coordinate plane of the local coordinate system; The target density of each independent partition is determined based on the target centroid coordinates, and the target density is mapped to the corresponding independent partition to generate an automotive suspension model.

2. The method according to claim 1, characterized in that, After obtaining the shell mesh model and target attribute parameters of the target suspension component, the method further includes: Identify geometric defects in the shell mesh model; the geometric defects include free edges or overlapping elements; The geometric defects are repaired by meshing to generate a shell mesh model with a complete topology, and the step of establishing a local coordinate system is performed based on the repaired shell mesh model.

3. The method according to claim 1, characterized in that, Establishing a local coordinate system based on the target centroid coordinates includes: Obtain the origin and axial information of the vehicle coordinate system pre-configured for the target suspension component; Using the target centroid coordinates as the origin, the coordinate axis direction is determined based on the axial information, and a local coordinate system parallel to the vehicle coordinate system is established, with the target centroid coordinates as the origin of the local coordinate system.

4. The method according to claim 1, characterized in that, The shell mesh model is divided into multiple independent partitions according to the coordinate plane of the local coordinate system, including: Traverse the mesh cells in the shell mesh model and determine the geometric center coordinates of each mesh cell; The geometric center coordinates are mapped to the local coordinate system, and the grid cell is divided into multiple independent partitions according to the positive and negative coordinate components of the geometric center coordinates in the local coordinate system.

5. The method according to claim 1, characterized in that, Determining the target density of each independent partition based on the target centroid coordinates includes: Obtain the target total mass of the target suspension component, and calculate the initial average density of each independent partition based on the target total mass and the volume of each independent partition; Based on the target centroid coordinates, an inertial moment balance constraint is constructed, and the initial average density is adjusted according to the inertial moment balance constraint to determine the target density of each independent partition.

6. The method according to claim 5, characterized in that, Adjusting the initial average density according to the inertia moment balance constraint to determine the target density of each of the independent zones includes: Calculate the moment of inertia contribution value of each independent partition relative to the target centroid coordinates, and construct a density correction coefficient based on the moment of inertia contribution value; The initial average density is weighted and corrected using the density correction coefficient to obtain the target density of each independent partition; the target density is used to calculate the theoretical centroid so that the theoretical centroid of each independent partition coincides with the target centroid coordinates.

7. The method according to claim 1, characterized in that, Mapping the target density to corresponding independent partitions to generate an automotive suspension model includes: Based on the target density of each independent partition, a corresponding material property card is generated; wherein, the material property card contains the value of the target density; The material property cards are mapped to the corresponding independent partitions of the grid cells, and the properties of the grid cells are checked. If the attribute check meets the preset attributes, a car suspension model containing density distribution information is generated.

8. A device for generating a model of an automobile suspension component, characterized in that, include: The acquisition module is used to acquire the shell mesh model and target attribute parameters of the target suspension component in response to the modeling command for the target suspension component, wherein the target attribute parameters include at least the target centroid coordinates; The partitioning determination module is used to establish a local coordinate system based on the target centroid coordinates, and to cut the shell mesh model into multiple independent partitions according to the coordinate plane of the local coordinate system; The model generation module is used to determine the target density of each independent partition based on the target centroid coordinates, and map the target density to the corresponding independent partition to generate an automotive suspension model.

9. An electronic device, characterized in that, The method includes a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when invoked and executed by a processor, cause the processor to perform the method according to any one of claims 1 to 7.

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