A simulation optimization method, device and system for multi-compound modulus matching of tires

Abstract

The present application discloses a simulation optimization method, device, and system for modulus matching of multiple rubber compounds in a tire, belonging to the technical field of tire simulation optimization. The method constructs a finite element model of the tire and road surface, including a three-dimensional tire simulation model and a two-dimensional rigid road surface model; matches the modulus properties of the rubber compound to each finite element grid of the tire simulation model through an orthogonal experimental design method, and performs finite element calculations based on the tire and road surface finite element models to calculate multiple sets of stress-strain and strain energy data for the target belt layer endpoints of the tire under different modulus properties; based on the multiple sets of stress-strain and strain energy data for the target belt layer endpoints, the modulus characteristic values ​​of the tire under different modulus properties are calculated, thereby obtaining the optimal modulus ratio of the multiple rubber compounds of the tire. The present application improves the accuracy and usability of simulation optimization, extends the service life of the tire, improves the utilization rate of tire design materials, and reduces design costs.

Description

Technical Field

[0001] The present application relates to the technical field of tire simulation optimization, and in particular to a simulation optimization method, device, and system for multi-rubber modulus matching of tires. Background Art

[0002] As a complex multi-material coupling system, the modulus matching design of its multiple rubber compounds directly affects the vehicle's driving safety and economy. Modulus matching is the core of the collaborative work of the tire's multi-material system, which will directly affect the tire's stress distribution, energy consumption, wear balance and structural integrity. A well-designed modulus matching scheme can ensure that all components deform in coordination when the tire contacts the ground, avoiding local excessive stretching or compression.

[0003] Existing multi-compound modulus design methods analyze the impact of radial tire rolling resistance, determine the degree of influence of compound modulus adjustment on rolling resistance, and then clearly indicate how to adjust the material modulus of various parts of the tire. This method uses rolling resistance as the optimization target and does not collaboratively consider coupling factors such as ground pressure, adjacent interface shear stress, and fatigue life, making it difficult to achieve effective prediction and optimization of modulus matching under actual working conditions. In addition, there are also methods that only optimize the tire's structural design by analyzing the tire's ability to withstand force and deformation, as well as the impact of the carcass profile, tread profile, and belt layer structure on the tire's durability performance, without achieving matching optimization of the tire's multi-compound modulus. Therefore, an improved solution is urgently needed to solve these technical problems. Summary of the Invention

[0004] In view of this, the present application proposes a simulation optimization method, device and system for matching the modulus of multiple rubber compounds in tires, which realizes multi-objective collaborative design optimization of the modulus of multiple rubber compounds in tires, makes the optimization results more in line with practical applications, improves the accuracy and usability of simulation optimization, and at the same time, optimizes tire performance, extends tire service life, improves the utilization rate of tire design materials, and reduces design costs.

[0005] In a first aspect, the present application proposes a simulation optimization method for multi-compound modulus matching of tires, the method comprising:

[0006] Constructing a tire and road surface finite element model, wherein the tire and road surface finite element model includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model;

[0007] Matching the modulus properties of the rubber compound to each finite element grid of the tire simulation model using an orthogonal experimental design method, performing finite element calculations based on the tire and road surface finite element models, and calculating multiple sets of stress-strain and strain energy data for target belt end points of the tire under different modulus properties;

[0008] Calculating modulus characteristic values ​​of the tire under different modulus properties based on multiple sets of stress-strain and strain energy data of target belt layer endpoints under different modulus properties;

[0009] Based on the modulus characteristic values ​​of the tire under different modulus properties, an optimal modulus ratio of multiple rubber materials of the tire is obtained.

[0010] Optionally, matching the modulus property of the rubber compound to each finite element mesh of the tire simulation model by an orthogonal experimental design method includes:

[0011] Taking the modulus of the rubber compound of each part of the tire as an orthogonal experimental design variable, multiple groups of candidate modulus values ​​of the rubber compound of each part under multiple factor levels are selected;

[0012] According to the rubber type of the portion corresponding to each finite element mesh of the tire simulation model, a corresponding candidate modulus value in each group of candidate modulus values ​​is matched to each finite element mesh.

[0013] Optionally, performing finite element calculation based on the tire and road surface finite element model to calculate multiple sets of stress-strain and strain energy data of target belt layer endpoints of the tire under different modulus properties includes:

[0014] For each group of candidate modulus values, respectively calculating stress and strain values ​​of a first belt layer endpoint, a second belt layer endpoint, and a third belt layer endpoint of the tire simulation model in various directions;

[0015] Based on the weights of the stress and strain values ​​of the first belt layer end point, the second belt layer end point and the third belt layer end point in each direction, the stress weighted average value and the strain weighted average value of the first belt layer end point, the second belt layer end point and the third belt layer end point in each direction are calculated.

[0016] Optionally, performing finite element calculation based on the tire and road surface finite element model to calculate multiple sets of stress-strain and strain energy data of target belt layer endpoints of the tire under different modulus properties includes:

[0017] For each group of candidate modulus values, a weighted average value of strain energy density of a first belt layer endpoint, a second belt layer endpoint, and a third belt layer endpoint of the tire simulation model is calculated respectively.

[0018] Optionally, the calculating the modulus characteristic values ​​of the tire under different modulus properties based on multiple sets of stress-strain and strain energy data of target belt layer endpoints under different modulus properties of the tire respectively includes:

[0019] Calculating first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint based on weighted sums of the stress weighted average value, the strain weighted average value, and the strain energy density weighted average value of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, respectively;

[0020] Performing weighted summation based on multiple groups of weights of the first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, to calculate multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire;

[0021] An average value of multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire is calculated to obtain modulus eigenvalues ​​of the tire under different modulus properties.

[0022] Optionally, the obtaining of optimal modulus matching of multiple rubber materials of the tire based on modulus characteristic values ​​of the tire under different modulus properties further includes:

[0023] A group of candidate modulus values ​​corresponding to the minimum modulus characteristic value is selected from the modulus characteristic values ​​of the tire under different modulus properties as the optimal modulus ratio of the multiple rubber materials of the tire.

[0024] Optionally, for each group of candidate modulus values, respectively calculating stress and strain values ​​of a first belt layer endpoint, a second belt layer endpoint, and a third belt layer endpoint of the tire simulation model in various directions includes:

[0025] respectively calculating stress and strain values ​​of a plurality of finite element meshes respectively included in the first belt layer end point, the second belt layer end point, and the third belt layer end point in various directions;

[0026] The average values ​​of the stress and strain values ​​in each direction of the multiple finite element meshes contained in each of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint are calculated respectively as the stress and strain values ​​in each direction of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint.

[0027] Optionally, the rubber materials for various parts of the tire include tread rubber, base rubber and shoulder pad rubber.

[0028] In a second aspect, the present application further proposes a simulation optimization device for multi-compound modulus matching of tires, the device comprising:

[0029] A modeling unit, configured to construct a tire and road surface finite element model, wherein the tire and road surface finite element model includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model;

[0030] a first calculation unit, configured to match the modulus property of the rubber compound to each finite element grid of the tire simulation model by an orthogonal experimental design method, and perform finite element calculation based on the tire and road surface finite element models to calculate multiple sets of stress-strain and strain energy data of target belt end points of the tire under different modulus properties;

[0031] a second calculation unit, configured to calculate modulus characteristic values ​​of the tire under different modulus properties based on multiple sets of stress-strain and strain energy data of target belt layer endpoints of the tire under different modulus properties;

[0032] The optimization unit is used to obtain an optimal modulus ratio of multiple rubber materials of the tire based on modulus characteristic values ​​of the tire under different modulus properties.

[0033] Thirdly, the present application also proposes a simulation optimization system for multi-rubber modulus matching of tires, which is used to implement the simulation optimization method for multi-rubber modulus matching of tires described above.

[0034] The present application can at least achieve the following beneficial effects: the embodiment of the present application calculates the modulus matching of multiple rubber compounds of tires through a finite element model, realizes multi-objective collaborative design optimization, makes the optimization results more in line with practical applications, improves the accuracy and usability of simulation optimization, and at the same time, optimizes tire performance, extends tire service life, improves tire design material utilization, and reduces design costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only illustrate certain embodiments of the present application and should not be regarded as limiting the scope of the present application.

[0036] Figure 1 1 is a flow chart of a simulation optimization method for multi-compound modulus matching of tires according to an embodiment of the present application;

[0037] Figure 2 is a partial flow chart of a simulation optimization method for multi-rubber modulus matching of tires according to another embodiment of the present application;

[0038] Figure 3 is a partial flow chart of a simulation optimization method for multi-rubber modulus matching of tires according to another embodiment of the present application;

[0039] Figure 4 is a partial flow chart of a simulation optimization method for multi-rubber modulus matching of tires according to another embodiment of the present application;

[0040] Figure 5is a finite element mesh diagram of tire belt endpoints according to an embodiment of the present application;

[0041] Figure 6 is a partial flow chart of a simulation optimization method for multi-rubber modulus matching of tires according to another embodiment of the present application;

[0042] Figure 7 is a diagram showing the finite element calculation results of the tire belt endpoints according to one embodiment of the present application;

[0043] Figure 8 2 is a schematic structural diagram of a simulation optimization device for multi-compound modulus matching of tires according to an embodiment of the present application;

[0044] Figure 9 is a partial structural diagram of a simulation optimization device for multi-rubber modulus matching of tires according to another embodiment of the present application;

[0045] Figure 10 is a partial structural diagram of a simulation optimization device for multi-rubber modulus matching of tires according to another embodiment of the present application;

[0046] Figure 11 is a partial structural diagram of a simulation optimization device for multi-rubber modulus matching of tires according to another embodiment of the present application;

[0047] Figure 12 It is a partial structural diagram of a simulation optimization device for multi-rubber modulus matching of tires according to another embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings of the embodiments of the present application. However, it should be understood that the described embodiments are only some exemplary embodiments of the present application, not all embodiments, and therefore the following detailed description of the embodiments of the present application is not intended to limit the scope of protection claimed in this application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0049] It should be noted that the terms "first", "second", etc. in the description and claims of this application are only used to distinguish and describe similar objects, rather than to describe a specific order or sequence, and cannot be understood as indicating or implying relative importance.

[0050] Figure 1 FIG. 1 is a flow chart of simulation optimization of tire multi-compound modulus matching according to an embodiment of the present application. Figure 1 As shown, the method may include the following steps:

[0051] Step S101 : constructing a tire and road surface finite element model, wherein the tire and road surface finite element model includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model.

[0052] Step S102, matching the modulus properties of the rubber compound to each finite element grid of the tire simulation model through an orthogonal experimental design method, and performing finite element calculation based on the tire and road surface finite element model to calculate multiple sets of stress, strain, and strain energy data of the target belt layer endpoints of the tire under different modulus properties.

[0053] Step S103 , based on multiple sets of stress-strain and strain energy data of target belt layer endpoints of the tire under different modulus properties, respectively calculating modulus characteristic values ​​of the tire under different modulus properties.

[0054] Step S104 : obtaining an optimal modulus ratio of multiple rubber materials of the tire based on the modulus characteristic values ​​of the tire under different modulus properties.

[0055] In this embodiment, in step S101, the tire finite element model includes a three-dimensional tire simulation model. By constructing a tire geometric structure model, drawing a material distribution map for it and performing meshing, wherein the mesh is a quadrilateral or triangle, and each mesh is assigned corresponding material properties, a tire finite element model corresponding to the real tire is established. Specifically, when constructing the model, the wire ring is first retracted into the rim, and then a standard air pressure (0.93 MPa) is applied to the inner surface of the inner liner of the tire to expand the tire to an equilibrium state. Then, the two-dimensional calculation model is rotated 360 degrees around the central axis of the tire to form a three-dimensional tire simulation model; then, a two-dimensional rigid road surface model is constructed, so that the center line of the road surface coincides with the center line of the tire form surface, the tire position is fixed, and a standard load (35,500 N) is applied to the road surface in a direction pointing to the tire, so that the tire contacts the road surface and thus deforms, thereby realizing the construction of the tire and road surface finite element model.

[0056] In this embodiment, in step S102, an orthogonal experimental design method is used to match the modulus property of the rubber compound to each finite element mesh of the tire simulation model. The modulus property specifically refers to the elastic modulus, measured in MPa. The orthogonal experimental design method designs experimental variables for the selected multiple factors from a multi-level perspective. The material properties designed for the selected multiple factors at the multi-level are assigned to the corresponding meshes using TYABAS pre-processing software. A skeleton material is used to represent the reinforcing effects of reinforcing materials such as the belt, carcass, and ladle. All mesh cells are axisymmetric. The orthogonal experimental design only requires a small number of experiments to cover the global influence weights of the multiple factors, accelerating factor convergence while reducing computational costs. Subsequently, a finite element calculation is performed based on the tire and road finite element model to calculate multiple sets of stress, strain, and strain energy data at the target belt endpoint of the tire under different modulus properties. Since the fatigue failure point of the tire in this embodiment is located at the belt endpoint, the multiple sets of stress, strain, and strain energy data calculated at the target belt endpoint of the tire under different modulus properties using the finite element model can quantitatively predict the fatigue life of the tire under different modulus combinations.

[0057] In this embodiment, in step S103, based on multiple sets of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus properties, the modulus characteristic values ​​of the tire under different modulus properties are calculated respectively, wherein the modulus characteristic value reflects the regulatory effect of the rubber modulus on the key performance of the tire (such as fatigue life, stress concentration, and energy dissipation), and is a composite parameter extracted based on stress, strain data and strain energy data.

[0058] In this embodiment, in step S104, based on the modulus characteristic values ​​of the tire under different modulus properties, the sizes of the modulus characteristic values ​​under different modulus properties are compared to obtain the optimal modulus ratio of multiple rubber materials of the tire, thereby optimizing tire performance, extending tire service life, improving tire design material utilization, and reducing design costs.

[0059] The embodiment of the present application constructs a finite element model of tire and road surface, wherein the finite element model of tire and road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model, and adopts an orthogonal experimental design method to match the modulus properties of the rubber compound to which each finite element grid of the tire simulation model belongs, and assigns corresponding material properties to each grid by designing experimental variables from multiple levels of selected multiple factors, thereby accelerating the convergence of factors and reducing the calculation cost. Since the fatigue failure point of the tire of this embodiment is located at the end point of the belt layer, the finite element calculation of multiple sets of stress-strain and strain energy data of the target belt layer end point of the tire under different modulus properties based on the finite element model of tire and road surface can quantitatively predict the fatigue life of the tire under different modulus combinations; based on the tire under different modulus properties, the fatigue life of the tire under different modulus combinations can be quantitatively predicted. The method uses multiple sets of stress-strain and strain energy data for target belt endpoints under different modulus properties to calculate the modulus characteristic values ​​of the tire under different modulus properties. The modulus characteristic value reflects the regulatory effect of the rubber compound modulus on key tire properties (such as fatigue life, stress concentration, and energy dissipation). It is a composite parameter extracted based on stress, strain, and strain energy data. This method implements multi-objective collaborative design optimization, making the optimization results more suitable for practical applications and improving the accuracy and usability of simulation optimization. Based on the modulus characteristic values ​​of the tire under different modulus properties, the modulus characteristic values ​​under different modulus properties are compared to obtain the optimal modulus ratio of the multiple rubber compounds in the tire. This optimizes tire performance, extends tire service life, improves tire design material utilization, and reduces design costs. Thus, the embodiment of the present application calculates the modulus matching of multiple rubber compounds in the tire through a finite element model, achieving multi-objective collaborative design optimization, making the optimization results more suitable for practical applications, improving the accuracy and usability of simulation optimization, and optimizing tire performance, extending tire service life, while improving tire design material utilization and reducing design costs.

[0060] In one embodiment, Figure 2 As shown, in step S102, the orthogonal experimental design method is used to match the modulus properties of the rubber compound for each finite element mesh of the tire simulation model, including:

[0061] Step S201 : using the modulus of the rubber compound at each part of the tire as an orthogonal experimental design variable, and selecting multiple groups of candidate modulus values ​​of the rubber compound at each part under multiple factor levels.

[0062] Step S202 : matching a corresponding candidate modulus value in each group of candidate modulus values ​​for each finite element mesh according to the rubber type of the corresponding portion of each finite element mesh of the tire simulation model.

[0063] In one embodiment, the modulus of the rubber compound at each part of the tire is used as an orthogonal experimental design variable. factor Horizontal orthogonal experimental design must meet Orthogonal array form, where is the number of experimental groups, is the number of levels, is the number of factors; in this embodiment, the tire's rubber materials include tread rubber, base rubber and shoulder rubber. The tread rubber is the outermost rubber layer of the tire that directly contacts the ground and is responsible for the friction between the vehicle and the road surface, drainage, shock absorption and other functions. The base rubber is located on the inner side of the tread rubber and is a transition layer rubber covering the belt layer (such as a steel belt layer or a fiber belt layer) for buffering the stress between the belt layer and the carcass. The shoulder rubber is a wedge-shaped rubber layer located in the shoulder area (the transition area between the tread and the sidewall) that connects the tread rubber and the carcass cord layer for absorbing dynamic stress of the shoulder, reducing excessive deformation of the tread edge and delaying shoulder wear. The three are in an adjacent relationship; in this embodiment, the moduli of the tread rubber, base rubber and shoulder rubber are used as orthogonal experimental design variables. An orthogonal experiment is designed for the above three factors. Taking 3 factors and 5 levels as an example, it is assumed that the tread rubber modulus is , the base rubber modulus is , the shoulder pad rubber modulus is , then the tread rubber modulus at level 5 is , 5 horizontal base rubber modulus is ,5 horizontal shoulder pad rubber modulus is ,use The orthogonal table contains a total of 25 experimental groups. Some of the orthogonal experimental design schemes are shown in Table 1 below.

[0064] Table 1

[0065]

[0066] According to the above-mentioned orthogonal experimental design scheme of tire tread rubber, base rubber and shoulder pad rubber, multiple groups of candidate modulus values ​​of the rubber materials in each part under multiple factor levels are selected.

[0067] Then, according to the rubber type of the corresponding part of each finite element mesh of the tire simulation model, each finite element mesh is matched with the corresponding candidate modulus value in each group of candidate modulus values, where the moduli of the tire tread rubber, base rubber and shoulder pad rubber are assigned according to 25 design schemes of orthogonal experimental design.

[0068] In this embodiment, each finite element mesh of the tire simulation model is designed to match the modulus property of the rubber compound to which it belongs through orthogonal test.

[0069] In one embodiment, Figure 3As shown, in step S103, the finite element calculation is performed based on the tire and road surface finite element model to calculate multiple sets of stress, strain, and strain energy data of the target belt layer endpoints of the tire under different modulus properties, including:

[0070] Step S301, for each group of candidate modulus values, respectively calculating stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint of the tire simulation model in various directions;

[0071] Step S302: Calculate the weighted average stress and weighted average strain of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction based on the weights of the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction.

[0072] In one embodiment, since the fatigue failure point of the tire in this example is located at the end point of the belt layer, multiple cells at the end point of the belt layer are divided into a first belt layer end point, a second belt layer end point, and a third belt layer end point. In this embodiment, ABAQUS is used for finite element calculation, and its coordinate system is divided into six directions: xx direction, xy direction, xz direction, yy direction, yz direction, and zz direction, wherein the x direction is the tire driving direction, the y direction is the axial direction, and the z direction is the tire loading direction. The stress and strain values ​​of the multiple cells at the end point of the belt layer in the above six directions are calculated according to 25 groups of candidate modulus values ​​designed by orthogonal experiments for the modulus of the tire tread rubber, base rubber, and shoulder pad rubber, wherein stress is the internal force of the material per unit area that resists external force, and the unit is Pa (Pascal). Strain is the relative deformation of the material under stress. At the end point of the belt layer, stress concentration reflects the local stress intensity in the area due to geometric transition or load transfer, and strain reflects the elastic or plastic deformation of the material due to stress.

[0073] Then, based on the weights of the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint in each direction, the weighted average values ​​of the stress and the weighted average values ​​of the strain at the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint in each direction are calculated. By assigning weight values ​​to different directions, the mechanical behavior under actual working conditions is simulated more realistically. The weighted average value is used to calculate the comprehensive contributions of stress and strain in different directions, avoiding the limitations of single-direction analysis.

[0074] In one embodiment, Figure 4 As shown, in step S301, for each group of candidate modulus values, respectively calculating the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint of the tire simulation model in each direction includes:

[0075] Step S401 : calculating stress and strain values ​​in various directions of a plurality of finite element meshes respectively included in the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint.

[0076] Step S402, respectively calculating the average values ​​of stress and strain values ​​of multiple finite element meshes contained in each of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction as the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction.

[0077] In this embodiment, the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint in the tire simulation model each include multiple finite element cells, and the stress and strain values ​​of the multiple finite element grids contained in each of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint in each direction are calculated respectively. Based on the stress and strain values, the average values ​​of the stress and strain values ​​of the multiple finite element grids contained in each of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint in each direction are calculated respectively as the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint in each direction, thereby improving the accuracy and authenticity of the finite element calculation.

[0078] For example, Figure 5 The figure shows the finite element mesh diagram of the tire belt layer endpoint, where cells 1-4 are marked as the finite element mesh cells covered by the first belt layer endpoint, and the stress value in the hth direction among the six directions is recorded as , the strain value is recorded as ,in Used to mark 6 directions such as xx, xy, xz, yy, yz, zz, etc. 25 corresponds to plans P1-P25, Corresponding to cell positions 1-4.

[0079] First The corresponding scheme Taking the candidate modulus values ​​of the group as an example, the stress average value and strain average value of the multiple finite element meshes contained in the first belt layer endpoint in each direction are calculated as the stress and strain values ​​of the first belt layer endpoint in each direction, which can be specifically calculated using the following formula:

[0080] ;

[0081] .

[0082] in, Indicates that the first belt layer endpoint is The stress value in the hth direction of the group candidate modulus value, Indicates that the first belt layer endpoint is The strain values ​​in the h-th direction of the set of candidate modulus values.

[0083] Next, the sum of the stress values ​​of the first belt layer end points in the hth direction is recorded as , the total strain value in the hth direction is recorded as , the sum of stresses in the six directions at the endpoints of the first belt layer is recorded as , the total strain in the six directions is recorded as .

[0084] The weight of the stress and strain value is calculated based on the stress and strain value of the first belt layer end point in each direction, and the stress weight in the hth direction is recorded as , the strain weight in the hth direction is recorded as ,in , used to mark 6 directions: xx, xy, xz, yy, yz, zz.

[0085] Based on the weights of the stress and strain values ​​of the first belt layer end point in each direction, the stress and strain values ​​of the first belt layer end point for the first belt layer are calculated. The stress-weighted average of the candidate modulus values ​​in each direction and the strain-weighted average ,in,

[0086] Stress-weighted average , Indicates that the first belt layer endpoint is The stress value in the hth direction of the group candidate modulus value;

[0087] Strain-weighted average , Indicates that the first belt layer endpoint is The strain values ​​in the h-th direction of the set of candidate modulus values.

[0088] Finally, cells 5-8 are marked as the endpoints of the second belt layer, and cells 9-13 are marked as the endpoints of the third belt layer. The average values ​​of the stress and strain values ​​of the multiple finite element meshes contained in the endpoints of the second belt layer and the third belt layer in each direction are consistent with the calculation method of the endpoints of the first belt layer. The weights of the stress and strain values ​​of the endpoints of the second belt layer and the third belt layer in each direction are consistent with the calculation method of the endpoints of the first belt layer. The weighted average values ​​of the stresses in each direction of the endpoints of the second belt layer and the third belt layer are recorded as 、 , the weighted average values ​​of strain are recorded as 、 , which is consistent with the calculation method of the first belt layer endpoint, and will not be repeated here.

[0089] Therefore, this embodiment obtains the stress and strain values, the weights of the stress and strain values, and the weighted average value of the stress and strain at the end points of the first belt layer, the second belt layer, and the third belt layer in each direction for each group of candidate modulus values, thereby laying the foundation for the subsequent calculation of characteristic values.

[0090] In one embodiment, the step S102 of performing finite element calculation based on the tire and road surface finite element model to calculate multiple sets of stress, strain, and strain energy data at target belt endpoints of the tire under different modulus properties includes:

[0091] For each group of candidate modulus values, the weighted average of the strain energy density of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint of the tire simulation model is calculated respectively. The strain energy density refers to the elastic energy stored per unit volume of the material during elastic deformation. It is the energy density absorbed and stored by the material when deformed by force. It is closely related to the elastic modulus, stress distribution, and strain field of the material. Since the strain energy density does not involve direction, the strain energy density of the corresponding cell position of each group of schemes in the orthogonal experimental design can be averaged and recorded as the weighted average of the scheme. , where the weighted average strain energy density at the endpoint of the first belt layer is ,in is the strain energy density of the unit cell at the end of the belt layer, 25 corresponds to plans P1-P25, Corresponding to cell positions 1-4, the weighted average strain energy density of the second belt layer endpoint and the third belt layer endpoint is recorded as 、 , which is consistent with the calculation method of the first belt layer endpoint, and will not be repeated here.

[0092] In one embodiment, Figure 6 As shown, the step S103 of calculating the modulus characteristic values ​​of the tire under different modulus properties based on multiple sets of stress-strain and strain energy data of the target belt layer endpoints under different modulus properties of the tire includes:

[0093] Step S601, calculating first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint based on a weighted sum of the stress weighted average value, the strain weighted average value, and the strain energy density weighted average value of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint;

[0094] Step S602, performing weighted summation based on multiple groups of weights of the first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, to calculate multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire;

[0095] Step S603 : calculating an average value of multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire, and obtaining modulus eigenvalues ​​of the tire under different modulus properties.

[0096] In this embodiment, the weighted average stress of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint calculated in step S302 is 、 、 , strain-weighted average 、 、 and the subsequently obtained weighted average strain energy density 、 , calculate the first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint respectively, and record the first eigenvalue as ,in , represent the first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint respectively. It can be obtained by the following formula:

[0097]

[0098] in, 、 、 is a constant coefficient, for example, it can be obtained based on design experience The value is 0.3, The value is 0.55, The value is 0.15.

[0099] Then, based on the weighted summation of the multiple groups of first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, the multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire are calculated and recorded as , can be obtained by the following formula:

[0100]

[0101] in, Represents the weight value of the first belt layer, Represents the weight value of the second belt layer, Represents the weight value of the third belt layer. The belt layer weight value must meet Conditions, list all weight value schemes that meet the conditions, where , , ,but 、 、 There are 36 combinations in total, namely .

[0102] Next, the average value of multiple sets of second eigenvalues ​​corresponding to each set of candidate modulus values ​​of the tire is calculated to obtain the modulus eigenvalues ​​of the tire under different modulus properties. ,in, 25 corresponds to plans P1-P25, .

[0103] In this embodiment, based on the weighted sum of the weighted average stress, weighted average strain, and weighted average strain energy density of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, the first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint are respectively calculated. The first eigenvalues ​​comprehensively reflect the mechanical response of the belt layer endpoints under different working conditions. Multi-dimensional quantitative indicators are more accurate than single parameters. The weighted average calculation makes the eigenvalues ​​closer to actual usage scenarios, reduces the deviation of design assumptions, and lays the foundation for subsequent acquisition of multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire. Then, the multiple groups of weights of the first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint are weightedly summed, and multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire are calculated and averaged to obtain the modulus eigenvalues ​​of the tire under different modulus properties. This realizes the transition from single-parameter optimization to multi-objective collaborative design, makes the optimization results more suitable for practical applications, and improves the accuracy and usability of simulation optimization.

[0104] In one embodiment, obtaining optimal modulus matching of multiple rubber materials of the tire based on modulus characteristic values ​​of the tire under different modulus properties further includes:

[0105] A set of candidate modulus values ​​corresponding to the minimum modulus characteristic value is selected from the modulus characteristic values ​​of the tire under different modulus properties as the optimal modulus ratio of the multiple rubber materials of the tire. The magnitude of the modulus characteristic value is related to the strain at the end point of the belt layer. The smaller the modulus characteristic value, the smaller the stress strain at the end point of the belt layer, indicating that its fatigue damage resistance is better and the fatigue life is longer. Therefore, a set of candidate modulus values ​​corresponding to the minimum modulus characteristic value is selected as the optimal modulus ratio of the multiple rubber materials of the tire. Figure 7 The figure shows the finite element calculation results of the tire belt layer endpoints. Among them, the minimum value is obtained by solution P10, which is consistent with the calculation result, improving the reliability of the calculation result.

[0106] Figure 8 FIG. 1 is a schematic diagram of a simulation optimization device for tire multi-compound modulus matching according to an embodiment of the present application. Figure 8 As shown, the device includes the following units:

[0107] The modeling unit 801 is used to construct a tire and road surface finite element model, wherein the tire and road surface finite element model includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model.

[0108] The first calculation unit 802 is used to match the modulus properties of the rubber compound to each finite element grid of the tire simulation model through the orthogonal experimental design method, and perform finite element calculation based on the tire and road surface finite element model to calculate multiple sets of stress, strain, and strain energy data of the target belt layer endpoints of the tire under different modulus properties.

[0109] The second calculation unit 803 is configured to calculate modulus characteristic values ​​of the tire under different modulus properties based on multiple sets of stress-strain and strain energy data of target belt layer endpoints of the tire under different modulus properties.

[0110] The optimization unit 804 is configured to obtain an optimal modulus ratio of multiple rubber materials of the tire based on the modulus characteristic values ​​of the tire under different modulus properties.

[0111] In one embodiment, Figure 9 As shown, the first calculation unit 802 may further include the following units:

[0112] The modulus acquisition unit 901 is configured to use the modulus of the rubber material of each part of the tire as an orthogonal experimental design variable and select multiple groups of candidate modulus values ​​of the rubber material of each part at multiple factor levels.

[0113] The modulus matching unit 902 is configured to match a corresponding candidate modulus value in each group of candidate modulus values ​​for each finite element mesh according to the rubber type of the corresponding portion of each finite element mesh of the tire simulation model.

[0114] In one embodiment, Figure 10 As shown, the second calculation unit 803 may further include the following units:

[0115] The third calculation unit 1001 is configured to calculate the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint of the tire simulation model in various directions for each group of candidate modulus values.

[0116] The fourth calculation unit 1002 is used to calculate the weighted average stress and the weighted average strain of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction based on the weights of the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction.

[0117] In one embodiment, Figure 11 As shown, the second calculation unit 803 may further include the following units:

[0118] The first characteristic calculation unit 1101 is used to calculate the first characteristic values ​​of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint respectively based on the weighted sum of the stress weighted average value, the strain weighted average value and the strain energy density weighted average value of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint.

[0119] The second feature calculation unit 1102 is configured to perform weighted summation based on multiple sets of weights of the first feature values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, to calculate multiple sets of second feature values ​​corresponding to each set of candidate modulus values ​​of the tire.

[0120] The third feature calculation unit 1103 is configured to calculate an average value of multiple groups of second feature values ​​corresponding to each group of candidate modulus values ​​of the tire, to obtain modulus feature values ​​of the tire under different modulus properties.

[0121] In one embodiment, Figure 12 As shown, the third calculation unit 1001 may further include:

[0122] The fifth calculation unit 1201 is configured to calculate stress and strain values ​​in various directions of a plurality of finite element meshes respectively included in the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint.

[0123] The sixth calculation unit 1202 is used to calculate the average stress and strain values ​​of the multiple finite element meshes contained in each of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction as the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction.

[0124] In summary, the embodiment of the present application constructs a finite element model of tire and road surface, wherein the finite element model of tire and road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model, and adopts an orthogonal experimental design method to match the modulus properties of the rubber compound to which each finite element grid of the tire simulation model belongs, and assigns corresponding material properties to each grid by designing experimental variables from multiple levels of selected multiple factors, thereby accelerating the convergence of factors and reducing the calculation cost. Since the fatigue failure point of the tire of this embodiment is located at the end point of the belt layer, finite element calculations are performed based on the finite element model of tire and road surface to obtain multiple sets of stress, strain and strain energy data of the target belt layer end point of the tire under different modulus properties, which can quantitatively predict the fatigue life of the tire under different modulus combinations; based on the tire under different Multiple sets of stress-strain and strain energy data for target belt endpoints under different modulus properties are used to calculate the modulus characteristic values ​​of the tire under different modulus properties. The modulus characteristic value reflects the regulatory effect of the rubber compound modulus on key tire properties (such as fatigue life, stress concentration, and energy dissipation). It is a composite parameter extracted based on stress, strain, and strain energy data. This enables multi-objective collaborative design, making the optimization results more suitable for practical applications and improving the accuracy and usability of simulation optimization. Based on the modulus characteristic values ​​of the tire under different modulus properties, the magnitude of the modulus characteristic values ​​under different modulus properties is compared to obtain the optimal modulus ratio of the multiple rubber compounds in the tire. This optimizes tire performance, extends tire service life, and improves tire design material utilization, thereby reducing design costs. Thus, the embodiments of the present application calculate the modulus matching of multiple rubber compounds in the tire through a finite element model, achieving multi-objective collaborative design, making the optimization results more suitable for practical applications, improving the accuracy and usability of simulation optimization, and optimizing tire performance, extending tire service life, while improving tire design material utilization, thereby reducing design costs.

[0125] It should be noted that those skilled in the art will understand that the different implementation methods described in the method embodiments of the present application and their explanations and technical effects achieved are also applicable to the device embodiments of the present application and will not be repeated here.

[0126] While the exemplary embodiments of the present application have been described above, it should be understood that the exemplary embodiments are illustrative rather than restrictive, and the scope of protection of the present application is not limited thereto. It should be understood that those skilled in the art may modify and alter the embodiments of the present application without departing from the spirit and scope of the present application, and such modifications and alterations are intended to be within the scope of protection of the present application.

Claims

1. A simulation optimization method for multi-compound modulus matching of tires, characterized in that: The method comprises: Constructing a tire and road surface finite element model, wherein the tire and road surface finite element model includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model; Matching the modulus properties of the rubber compound to each finite element grid of the tire simulation model using an orthogonal experimental design method, performing finite element calculations based on the tire and road surface finite element models, and calculating multiple sets of stress-strain and strain energy data for target belt end points of the tire under different modulus properties; Calculating modulus characteristic values ​​of the tire under different modulus properties based on multiple sets of stress-strain and strain energy data of target belt layer endpoints under different modulus properties; Based on the modulus characteristic values ​​of the tire under different modulus properties, an optimal modulus ratio of multiple rubber materials of the tire is obtained.

2. The simulation optimization method for multi-compound modulus matching of tires according to claim 1, characterized in that: The method of matching the modulus properties of the rubber compound to each finite element grid of the tire simulation model by the orthogonal experimental design method includes: Taking the modulus of the rubber compound of each part of the tire as an orthogonal experimental design variable, multiple groups of candidate modulus values ​​of the rubber compound of each part under multiple factor levels are selected; According to the rubber type of the portion corresponding to each finite element mesh of the tire simulation model, a corresponding candidate modulus value in each group of candidate modulus values ​​is matched to each finite element mesh.

3. The simulation optimization method for multi-compound modulus matching of tires according to claim 2, characterized in that: The finite element calculation is performed based on the tire and road surface finite element model to calculate multiple sets of stress, strain, and strain energy data at target belt layer endpoints of the tire under different modulus properties, including: For each group of candidate modulus values, respectively calculating stress and strain values ​​of a first belt layer endpoint, a second belt layer endpoint, and a third belt layer endpoint of the tire simulation model in various directions; Based on the weights of the stress and strain values ​​of the first belt layer end point, the second belt layer end point and the third belt layer end point in each direction, the stress weighted average value and the strain weighted average value of the first belt layer end point, the second belt layer end point and the third belt layer end point in each direction are calculated.

4. The simulation optimization method for multi-compound modulus matching of tires according to claim 3, characterized in that: The finite element calculation is performed based on the tire and road surface finite element model to calculate multiple sets of stress, strain, and strain energy data at target belt layer endpoints of the tire under different modulus properties, including: For each group of candidate modulus values, a weighted average value of strain energy density of a first belt layer endpoint, a second belt layer endpoint, and a third belt layer endpoint of the tire simulation model is calculated respectively.

5. The simulation optimization method for multi-compound modulus matching of tires according to claim 4, characterized in that: The method of calculating the modulus characteristic values ​​of the tire under different modulus properties based on multiple sets of stress-strain and strain energy data of target belt layer endpoints under different modulus properties of the tire comprises: Calculating first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint based on weighted sums of the stress weighted average value, the strain weighted average value, and the strain energy density weighted average value of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, respectively; Performing weighted summation based on multiple groups of weights of the first eigenvalues ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, to calculate multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire; An average value of multiple groups of second eigenvalues ​​corresponding to each group of candidate modulus values ​​of the tire is calculated to obtain modulus eigenvalues ​​of the tire under different modulus properties.

6. The simulation optimization method for multi-compound modulus matching of tires according to claim 5, characterized in that: The step of obtaining optimal modulus matching of multiple rubber materials of the tire based on modulus characteristic values ​​of the tire under different modulus properties further includes: A group of candidate modulus values ​​corresponding to the minimum modulus characteristic value is selected from the modulus characteristic values ​​of the tire under different modulus properties as the optimal modulus ratio of the multiple rubber materials of the tire.

7. The simulation optimization method for multi-compound modulus matching of tires according to claim 6, characterized in that: The step of calculating the stress and strain values ​​of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint of the tire simulation model in each direction for each group of candidate modulus values ​​includes: respectively calculating stress and strain values ​​of a plurality of finite element meshes respectively included in the first belt layer end point, the second belt layer end point, and the third belt layer end point in various directions; The average values ​​of the stress and strain values ​​in each direction of the multiple finite element meshes contained in each of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint are calculated respectively as the stress and strain values ​​in each direction of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint.

8. The simulation optimization method for multi-compound modulus matching of tires according to claim 1, characterized in that: The rubber materials of various parts of the tire include tread rubber, base rubber and shoulder pad rubber.

9. A simulation optimization device for multi-compound modulus matching of tires, characterized in that: The device comprises: A modeling unit, configured to construct a tire and road surface finite element model, wherein the tire and road surface finite element model includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model; a first calculation unit, configured to match the modulus property of the rubber compound to each finite element grid of the tire simulation model by an orthogonal experimental design method, and perform finite element calculation based on the tire and road surface finite element models to calculate multiple sets of stress-strain and strain energy data of target belt end points of the tire under different modulus properties; a second calculation unit, configured to calculate modulus characteristic values ​​of the tire under different modulus properties based on multiple sets of stress-strain and strain energy data of target belt layer endpoints of the tire under different modulus properties; The optimization unit is used to obtain an optimal modulus ratio of multiple rubber materials of the tire based on modulus characteristic values ​​of the tire under different modulus properties.

10. A simulation optimization system for multi-compound modulus matching of tires, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing the method according to any one of claims 1 to 8.

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