Simulation optimization method, device and system for tire multi-rubber modulus matching

Abstract

The invention discloses a simulation optimization method, device and system for tire multi-rubber modulus matching, and belongs to the technical field of tire simulation optimizing.The method comprises the steps that a tire and a pavement finite element model are built, and the tire and pavement finite element model comprises a three-dimensional tire simulation model and a two-dimensional rigid pavement model; matching a modulus attribute of a rubber material to which each finite element grid of the tire simulation model belongs through an orthogonal test design method, carrying out finite element calculation based on the tire and the pavement finite element model, and calculating multiple groups of stress-strain and strain energy data of target belted layer endpoints of the tire under different modulus attributes; and respectively calculating modulus characteristic values of the tire under different modulus attributes on the basis of the multiple groups of stress-strain and strain energy data of the endpoints of the target belted layer, so as to obtain the optimal modulus ratio of multiple rubber materials of the tire. According to the method, the precision and usability of simulation optimization are improved, the service life of the tire is prolonged, the utilization rate of tire design materials is increased, and the design cost is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of tire simulation optimization. Specifically, it relates to a simulation optimization method, device, and system for the modulus matching of multiple tire rubber compounds. Background Art

[0002] As a complex multi-material coupling system, the modulus matching design of multiple tire rubber compounds directly affects the driving safety and economy of vehicles. Modulus matching is the core of the collaborative work of the tire multi-material system, which will directly affect the stress distribution, energy consumption, wear balance, and structural integrity of the tire. Designing a reasonable modulus matching scheme can ensure that each component of the tire deforms collaboratively when it touches the ground, avoiding local over-stretching or compression.

[0003] Existing multi-rubber-compound modulus design methods analyze the influence degree of the rolling resistance of radial tires, obtain the influence degree of the adjustment of the rubber compound modulus on the rolling resistance, and then clearly indicate how to adjust the material modulus of each part of the tire. Taking the rolling resistance as the optimization goal, they do not consider coupling factors such as contact pressure, adjacent interface shear stress, and fatigue life in a coordinated manner, and it is difficult to effectively predict and optimize the modulus matching under actual working conditions. In addition, there are also optimization schemes for tire structure design only by analyzing the ability of the tire to withstand force and deformation and the influence of the carcass profile, tread profile, and belt structure on the tire durability performance, without realizing the matching optimization of the multi-rubber-compound modulus of the tire. 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 the modulus matching of multiple tire rubber compounds, realizing the multi-objective collaborative design optimization of the multi-rubber-compound modulus of the tire, making the optimization result more suitable for actual applications, improving the accuracy and usability of the simulation optimization. At the same time, while optimizing the tire performance and extending the tire service life, it improves the utilization rate of the tire design materials and reduces the design cost.

[0005] In the first aspect, the present application proposes a simulation optimization method for the modulus matching of multiple tire rubber compounds. The method includes: Constructing a finite element model of the tire and the road surface, where the finite element model of the tire and the road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model; Matching the modulus attributes of the rubber compounds to each finite element mesh of the tire simulation model through the orthogonal experimental design method, and performing finite element calculations based on the finite element model of the tire and the road surface to calculate multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes; Based on the multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes, respectively calculating the modulus characteristic values of the tire under different modulus attributes; Based on the modulus characteristic values of the tire under different modulus properties, obtain the optimal modulus ratio of the multi-compound of the tire.

[0006] Optionally, the matching of the modulus property of the compound to each finite element mesh of the tire simulation model by the orthogonal experimental design method includes: Taking the modulus of the compounds at each part of the tire as the variables of the orthogonal experimental design, and selecting multiple groups of candidate modulus values of the compounds at each part under multiple factor levels; According to the compound type of the corresponding part of each finite element mesh of the tire simulation model, match the corresponding candidate modulus value in each group of candidate modulus values for each finite element mesh.

[0007] Optionally, the finite element calculation is performed based on the tire and road surface finite element model, and multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus properties are calculated, including: For each group of candidate modulus values, calculate the stress-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 respectively; Based on the weights of the stress-strain values of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint in each direction, calculate the stress weighted average value and strain weighted average value of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint in each direction.

[0008] Optionally, the finite element calculation is performed based on the tire and road surface finite element model, and multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus properties are calculated, including: For each group of candidate modulus values, calculate the weighted average value 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 respectively.

[0009] Optionally, based on the multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus properties, calculate the modulus characteristic values of the tire under different modulus properties respectively, including: Based on the weighted summation of the stress weighted average value, strain weighted average value and weighted average value of the strain energy density of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint, 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 summation of multiple groups of weights of the first characteristic values of the first belt layer endpoint, the second belt layer endpoint and the third belt layer endpoint, calculate multiple groups of second characteristic values corresponding to each group of candidate modulus values of the tire; Calculate the average value of multiple sets of second eigenvalue corresponding to each set of candidate modulus values of the tire, and obtain the modulus eigenvalue of the tire under different modulus attributes.

[0010] Optionally, obtaining the optimal modulus matching of the multi-compound of the tire based on the modulus eigenvalue of the tire under different modulus attributes further includes: Select a set of candidate modulus values corresponding to the minimum modulus eigenvalue from the modulus eigenvalues of the tire under different modulus attributes as the optimal modulus ratio of the multi-compound of the tire.

[0011] Optionally, for each set of candidate modulus values, calculating 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 of the tire simulation model in each direction respectively includes: Calculate the stress and strain values of multiple finite element meshes included in the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively in each direction; Calculate the average value of the stress and strain values of multiple finite element meshes included in the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively in each direction as 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.

[0012] Optionally, the compound of each part of the tire includes tread compound, base compound, and shoulder pad compound.

[0013] In a second aspect, the present application also proposes a simulation optimization device for the modulus matching of the multi-compound of a tire. The device includes: A modeling unit for constructing a finite element model of the tire and the road surface. The finite element model of the tire and the road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model; A first calculation unit for matching the modulus attribute of the compound to which each finite element mesh of the tire simulation model belongs by an orthogonal experimental design method, and performing finite element calculation based on the finite element model of the tire and the road surface to calculate multiple sets of stress and strain, strain energy data of the target belt layer end point of the tire under different modulus attributes; A second calculation unit for calculating the modulus eigenvalue of the tire under different modulus attributes respectively based on the multiple sets of stress and strain, strain energy data of the target belt layer end point of the tire under different modulus attributes; An optimization unit for obtaining the optimal modulus ratio of the multi-compound of the tire based on the modulus eigenvalue of the tire under different modulus attributes.

[0014] In a third aspect, the present application also proposes a simulation optimization system for the modulus matching of multi-compound tires, which is used to implement the simulation optimization method for the modulus matching of multi-compound tires described above.

[0015] The present application can at least achieve the following beneficial effects: By calculating the modulus matching of multi-compound tires through a finite element model, the embodiments of the present application realize the collaborative design optimization of multiple objectives, making the optimization results more suitable for practical applications, improving the accuracy and usability of simulation optimization. At the same time, while optimizing tire performance and extending tire service life, the utilization rate of tire design materials is improved, and the design cost is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application and should not be regarded as limiting the scope of the present application.

[0017] Figure 1 is a schematic flowchart of a simulation optimization method for the modulus matching of multi-compound tires according to an embodiment of the present application; Figure 2 is a partial schematic flowchart of a simulation optimization method for the modulus matching of multi-compound tires according to another embodiment of the present application; Figure 3 is a partial schematic flowchart of a simulation optimization method for the modulus matching of multi-compound tires according to another embodiment of the present application; Figure 4 is a partial schematic flowchart of a simulation optimization method for the modulus matching of multi-compound tires according to another embodiment of the present application; Figure 5 is a finite element mesh diagram of the tire belt layer endpoints according to an embodiment of the present application; Figure 6 is a partial schematic flowchart of a simulation optimization method for the modulus matching of multi-compound tires according to another embodiment of the present application; Figure 7 is a finite element calculation result diagram of the tire belt layer endpoints according to an embodiment of the present application; Figure 8 is a schematic structural diagram of a simulation optimization device for the modulus matching of multi-compound tires according to an embodiment of the present application; Figure 9 is a partial schematic structural diagram of a simulation optimization device for the modulus matching of multi-compound tires according to another embodiment of the present application; Figure 10 is a partial schematic structural diagram of a simulation optimization device for the modulus matching of multi-compound tires according to another embodiment of the present application; Figure 11It is a partial structural schematic diagram of a simulation optimization device for tire multi-compound modulus matching according to another embodiment of the present application; Figure 12 It is a partial structural schematic diagram of a simulation optimization device for tire multi-compound modulus matching according to another embodiment of the present application. Specific embodiments

[0018] To make the objectives, 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 with reference to the accompanying 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, rather than all embodiments. Therefore, the following detailed description of the embodiments of the present application is not intended to limit the scope claimed by the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts fall within the scope of protection of the present application.

[0019] It should be noted that the terms "first", "second", etc. in the description and claims of the present application are only used to distinguish and describe similar objects, rather than to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance.

[0020] Figure 1 It is a flow schematic diagram of the simulation optimization of tire multi-compound modulus matching according to an embodiment of the present application. As Figure 1 shown, the method may include the following steps: Step S101, constructing a finite element model of the tire and the road surface, where the finite element model of the tire and the road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model.

[0021] Step S102, matching the modulus attributes of the compound to which each finite element mesh of the tire simulation model belongs through the orthogonal experimental design method, and performing finite element calculations based on the finite element model of the tire and the road surface to calculate multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes.

[0022] Step S103, respectively calculating the modulus eigenvalues of the tire under different modulus attributes based on the multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes.

[0023] Step S104, obtaining the optimal modulus ratio of the multi-compound of the tire based on the modulus eigenvalues of the tire under different modulus attributes.

[0024] 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, a material distribution map is drawn for it and mesh generation is performed, where the mesh is quadrilateral or triangular, and corresponding material properties are assigned to each mesh to establish a tire finite element model corresponding to the real tire. Specifically, when constructing the model, first, the bead is shrunk into the rim, and then a standard air pressure (0.93 MPa) is applied to the inner surface of the tire liner 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. Next, a two-dimensional rigid pavement model is constructed so that the center line of the pavement coincides with the center line of the tire tread surface, the position of the tire is fixed, and a standard load (35500 N) is applied to the pavement, with the direction pointing to the tire, so that the tire contacts the pavement and deforms, thus realizing the construction of the tire and pavement finite element models.

[0025] In this embodiment, in step S102, the modulus property of the rubber compound to which each finite element mesh of the tire simulation model belongs is matched by the orthogonal experimental design method. Among them, the modulus property specifically refers to the elastic modulus, with the unit of Mpa. The orthogonal experimental design designs the experimental variables from multiple levels for the selected multiple factors, and assigns the material properties designed for the selected multiple factors at multiple levels to the corresponding meshes using the TYABAS preprocessing software. At the same time, the reinforcing effect of reinforcing materials such as belts, carcasses, and steel casings is represented by the skeleton material. Among them, all mesh units have axisymmetric properties. The orthogonal experimental design only requires a small number of experiments to cover the global influence weights of multiple factors, accelerating factor convergence while reducing the calculation cost. Subsequently, based on the tire and pavement finite element models, finite element calculations are performed to calculate multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus properties. Since the fatigue failure point of the tire in this embodiment is located at the belt layer endpoints, calculating multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus properties through the finite element model can quantitatively predict the fatigue life of the tire under different modulus combinations.

[0026] In this embodiment, in step S103, based on the multiple groups 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. Among them, the modulus characteristic value reflects the regulation effect of the rubber compound modulus on the key performance of the tire (such as fatigue life, stress concentration, energy dissipation), and is a composite parameter extracted based on stress, strain data, and strain energy data.

[0027] In this embodiment, in step S104, based on the modulus eigenvalue of the tire under different modulus attributes, the magnitudes of the modulus eigenvalues under different modulus attributes are compared to obtain the optimal modulus ratio of the multi-compound of the tire, which optimizes the tire performance, extends the service life of the tire, improves the utilization rate of the tire design materials, and reduces the design cost.

[0028] In the embodiment of the present application, a finite element model of the tire and the road surface is constructed, where the finite element model of the tire and the road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model. The orthogonal experimental design method is used to match the modulus attribute of the compound belonging to each finite element grid of the tire simulation model. By designing experimental variables from multiple levels for multiple factors selected, corresponding material attributes are assigned to each grid, which speeds up the convergence of factors and reduces the calculation cost. Since the fatigue failure point of the tire in this embodiment is located at the end point of the belt layer, based on the finite element model of the tire and the road surface, finite element calculation is performed on multiple groups of stress-strain and strain energy data of the target belt layer end point of the tire under different modulus attributes, and the fatigue life of the tire under different modulus combinations can be quantitatively predicted; based on the multiple groups of stress-strain and strain energy data of the target belt layer end point of the tire under different modulus attributes, the modulus eigenvalues of the tire under different modulus attributes are respectively calculated. Among them, the modulus eigenvalue reflects the regulatory effect of the compound modulus on the key performance of the tire (such as fatigue life, stress concentration, energy dissipation), and is a composite parameter extracted based on stress, strain data and strain energy data, realizing multi-objective collaborative design optimization, making the optimization result more suitable for practical applications, and improving the accuracy and usability of simulation optimization; based on the modulus eigenvalues of the tire under different modulus attributes, the magnitudes of the modulus eigenvalues under different modulus attributes are compared to obtain the optimal modulus ratio of the multi-compound of the tire, which optimizes the tire performance, extends the service life of the tire, improves the utilization rate of the tire design materials, and reduces the design cost. Therefore, in the embodiment of the present application, by calculating the modulus matching of the multi-compound of the tire through the finite element model, multi-objective collaborative design optimization is realized, making the optimization result more suitable for practical applications, improving the accuracy and usability of simulation optimization. At the same time, the tire performance is optimized, the service life of the tire is extended, the utilization rate of the tire design materials is improved, and the design cost is reduced.

[0029] In one embodiment, as Figure 2 shown, in step S102, the method of matching the modulus attribute of the compound belonging to each finite element grid of the tire simulation model by the orthogonal experimental design method includes: Step S201, taking the modulus of the compound of each part of the tire as the orthogonal experimental design variable, and selecting multiple groups of candidate modulus values of the compound of each part at multiple factor levels.

[0030] Step S202: Match the corresponding candidate modulus value in each group of candidate modulus values for each finite element mesh according to the rubber compound type of the corresponding part of the tire simulation model.

[0031] In one embodiment, taking the moduli of the rubber compounds of each part of the tire as the design variables of the orthogonal experiment, for factors the orthogonal experiment design of levels needs to satisfy the form of the orthogonal table, where is the number of experimental groups, is the number of levels, is the number of factors; in this embodiment, the rubber compounds of the tire parts include tread rubber, base rubber, and shoulder pad rubber. The tread rubber is the outermost rubber layer of the tire that directly contacts the ground, undertaking functions such as vehicle-road friction, drainage, and shock absorption. The base rubber is located inside the tread rubber and is the transition layer rubber covering the belt layer (such as a steel belt layer or a fiber belt layer), used to buffer the stress between the belt layer and the carcass. The shoulder pad rubber is the wedge-shaped rubber layer in the shoulder area (the transition area between the tread and the sidewall), connecting the tread rubber and the carcass ply, used to absorb the dynamic stress of the shoulder, reduce the excessive deformation of the tread edge, and delay the shoulder wear. The three are adjacent to each other; in this embodiment, taking the moduli of the tread rubber, base rubber, and shoulder pad rubber as the design variables of the orthogonal experiment, an orthogonal experiment is designed for the above 3 factors. Taking 3 factors and 5 levels as an example, assuming that the modulus of the tread rubber is and the modulus of the base rubber is and the modulus of the shoulder pad rubber is , then the 5-level modulus of the tread rubber is , the 5-level modulus of the base rubber is , the 5-level modulus of the shoulder pad rubber is , and the orthogonal table is adopted, that is, a total of 25 groups of experimental groups are included. Part of the orthogonal experiment design scheme is shown in Table 1 below.

[0032] Table 1

[0033] According to the above orthogonal experiment design scheme of the tire tread rubber, base rubber, and shoulder pad rubber, multiple groups of candidate modulus values of each part of the rubber compound at multiple factor levels are selected.

[0034] Then, match the corresponding candidate modulus value in each group of candidate modulus values for each finite element mesh according to the rubber compound type of the corresponding part of the tire simulation model, where the moduli of the tire tread rubber, base rubber, and shoulder pad rubber are assigned according to the 25 groups of design schemes of the orthogonal experiment.

[0035] In this embodiment, the modulus property of the rubber compound to which each finite element mesh of the tire simulation model belongs is matched through orthogonal experimental design, and the modulus property of the rubber compound to which each finite element mesh of the tire simulation model belongs is matched.

[0036] In one embodiment, as Figure 3 shown, in step S103, the finite element calculation is performed based on the tire and road surface finite element models, and multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus properties are calculated, including: Step S301, for each group of candidate modulus values, calculate the stress-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; Step S302, based on the weights of the stress-strain values of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction, calculate the stress weighted average value and the strain weighted average value of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction.

[0037] In one embodiment, since the fatigue failure point of the tire in this example is located at the belt layer endpoint, multiple cells of the belt layer endpoint are divided into the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint. 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. Among them, the x direction is the tire driving direction, the y direction is the axial direction, and the z direction is the tire loading direction. For the moduli of the tire tread rubber, the base rubber, and the shoulder pad rubber, the stress-strain values of multiple cells of the belt layer endpoint in the above six directions are calculated according to 25 groups of candidate modulus values designed by orthogonal experiment. Among them, stress is the internal force that resists external forces inside the material per unit area, with the unit of Pa (Pascal), and strain is the relative deformation of the material under force. At the belt layer endpoint, stress reflects the local stress intensity in this area caused by geometric transition or load transfer, and strain reflects the elastic or plastic deformation of the material caused by stress.

[0038] Then, based on the weights of the stress-strain values of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction, calculate the stress weighted average value and the strain weighted average value of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction. By assigning weight values to different directions, the mechanical behavior under actual working conditions is more realistically simulated. The weighted average value is used for calculation to comprehensively consider the contributions of stress and strain in different directions and avoid the limitations of single-direction analysis.

[0039] In one embodiment, as Figure 4As shown, for each group of candidate modulus values in step S301, calculating 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 of the tire simulation model in each direction respectively includes: Step S401, calculating the stress and strain values of the multiple finite element meshes included in the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively in each direction.

[0040] Step S402, calculating the average values of the stress and strain values of the multiple finite element meshes included in the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively in each direction, and taking them as 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.

[0041] In this embodiment, each of the first belt layer end point, the second belt layer end point, and the third belt layer end point in the tire simulation model includes multiple finite element cells. Calculate the stress and strain values of the multiple finite element meshes included in the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively in each direction, and calculate the average values of the stress and strain values of the multiple finite element meshes included in the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively in each direction on the basis of the stress and strain values, and take them as 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, which improves the accuracy and authenticity of the finite element calculation.

[0042] Exemplarily, Figure 5 Shown is the finite element mesh diagram of the tire belt layer end point, where the 1-4th cells are marked as the finite element mesh cells covered by the first belt layer end point, and its stress value in the hth direction among the 6 directions is denoted as and the strain value is denoted as where is used to mark 6 directions such as xx, xy, xz, yy, yz, zz, 25 corresponds to solutions P1 - P25, corresponding to cell positions 1 - 4.

[0043] Taking the th solution corresponding to the th group of candidate modulus values as an example, calculating the average stress and average strain of the multiple finite element meshes included in the first belt layer end point in each direction as the stress and strain values of the first belt layer end point in each direction, which can be specifically calculated by the following formulas: ; .

[0044] Among them, Denote the stress value in the h-th direction of the first belt layer end point for the group of candidate modulus values, Denote the strain value in the h-th direction of the first belt layer end point for the group of candidate modulus values.

[0045] Next, denote the sum of the stress values of the first belt layer end point in the h-th direction as , and denote the sum of the strain values in the h-th direction as . Denote the sum of the stresses of the first belt layer end point in 6 directions as , and denote the sum of the strains in 6 directions as .

[0046] Based on the stress and strain values of the first belt layer end point in each direction, calculate the weights of the stress and strain values. Denote the stress weight in the h-th direction as , and denote the strain weight in the h-th direction as , where , which is used to label 6 directions such as xx, xy, xz, yy, yz, zz.

[0047] Based on the weights of the stress and strain values of the first belt layer end point in each direction, calculate the stress weighted average value and the strain weighted average value of the first belt layer end point for the group of candidate modulus values in each direction, where the stress weighted average value , Denote the stress value in the h-th direction of the first belt layer end point for the group of candidate modulus values; the strain weighted average value , Denote the strain value in the h-th direction of the first belt layer end point for the group of candidate modulus values.

[0048] Finally, label the cells 5 - 8 as the second belt layer end points, and label the cells 9 - 13 as the third belt layer end points. The calculation methods of the average values of the stress and strain values of the multiple finite element meshes included in the second belt layer end points and the third belt layer end points in each direction are the same as those of the first belt layer end points. The calculation methods of the weights of the stress and strain values of the second belt layer end points and the third belt layer end points in each direction are the same as those of the first belt layer end points. Denote the stress weighted average values of the second belt layer end points and the third belt layer end points in each direction as 、 respectively, and denote the strain weighted average values as 、 , which is consistent with the calculation method of the first belt layer endpoints and will not be elaborated here one by one.

[0049] Thus, for each group of candidate modulus values in this embodiment, the stress-strain values, weights of stress-strain values, stress weighted average values, and strain weighted average values of the first belt layer endpoints, second belt layer endpoints, and third belt layer endpoints in each direction are obtained through calculation, laying a foundation for the calculation of subsequent characteristic values.

[0050] In one embodiment, in the step S102, the finite element calculation is performed based on the tire and road surface finite element model to calculate multiple groups of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus properties, including: For each group of candidate modulus values, the weighted average of the strain energy density of the first belt layer endpoints, second belt layer endpoints, and third belt layer endpoints of the tire simulation model is calculated respectively. The strain energy density refers to the elastic energy stored per unit volume during the elastic deformation of the material, which is the energy density absorbed and stored when the material is stressed and deformed, and 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 weighted average value of the strain energy density at the corresponding cell positions of each group of orthogonal test design schemes can be obtained by taking the average value, denoted as the weighted average value of this scheme , where the weighted average of the strain energy density of the first belt layer endpoints , where is the strain energy density of the belt layer endpoint cell, 25 corresponds to the schemes P1 - P25, corresponding to the cell positions 1 - 4, and the weighted average of the strain energy density of the second belt layer endpoints and the third belt layer endpoints are denoted as 、 , which is consistent with the calculation method of the first belt layer endpoints and will not be elaborated here one by one.

[0051] In one embodiment, as Figure 6 shown, in the step S103, based on the multiple groups 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, including: Step S601, based on the weighted summation of the stress weighted average value, strain weighted average value, and weighted average value of the strain energy density of the first belt layer endpoints, second belt layer endpoints, and third belt layer endpoints, calculate the first characteristic values of the first belt layer endpoints, second belt layer endpoints, and third belt layer endpoints respectively; Step S602: Based on the first eigenvalues of the first belt layer endpoints, the second belt layer endpoints, and the third belt layer endpoints, perform weighted summation for each group of weights respectively, and calculate multiple groups of second eigenvalues corresponding to each group of candidate modulus values of the tire; Step S603: Calculate the average value of multiple groups of second eigenvalues corresponding to each group of candidate modulus values of the tire, and obtain the modulus eigenvalue of the tire under different modulus attributes.

[0052] In this embodiment, based on the stress weighted average values of the first belt layer endpoints, the second belt layer endpoints, and the third belt layer endpoints obtained by calculating in step S302 、 、 ,the strain weighted average values 、 、 and the subsequent obtained strain energy density weighted average values 、 respectively calculate the first eigenvalues of the first belt layer endpoints, the second belt layer endpoints, and the third belt layer endpoints, and denote the first eigenvalues as where respectively represent the first eigenvalues of the first belt layer endpoints, the second belt layer endpoints, and the third belt layer endpoints. It can be obtained through the following formula:

[0053] where 、 、 are constant coefficients. Exemplarily, they can be obtained according to design experience takes the value of 0.3, takes the value of 0.55, takes the value of 0.15.

[0054] Then, based on the first eigenvalues of the first belt layer endpoints, the second belt layer endpoints, and the third belt layer endpoints, perform weighted summation for each group of weights respectively, and calculate multiple groups of second eigenvalues corresponding to each group of candidate modulus values of the tire, denoted as , which can be obtained through the following formula:

[0055] where represents the first belt layer weight value, represents the second belt layer weight value, represents the third belt layer weight value. The belt layer weight values need to meet the condition. List all weight value schemes that meet the condition, where , , , then 、 、 There are a total of 36 combination methods, that is .

[0056] Next, calculate the average value of multiple groups of second eigenvalue corresponding to each group of candidate modulus values of the tire, and obtain the modulus eigenvalue of the tire under different modulus attributes , where 25 corresponds to solutions P1 - P25 .

[0057] In this embodiment, based on the weighted summation of the stress weighted average value, strain weighted average value, and strain energy density weighted average value of the first belt layer end point, the second belt layer end point, and the third belt layer end point, calculate the first eigenvalue of the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively. The first eigenvalue comprehensively reflects the mechanical response of the belt layer end point under different working conditions. The multi-dimensional quantization index is more accurate than a single parameter. The weighted average calculation makes the eigenvalue closer to the actual usage scenario, reduces the deviation of the design assumption, and lays a foundation for obtaining multiple groups of second eigenvalues corresponding to each group of candidate modulus values of the tire subsequently; then, perform weighted summation on multiple groups of weights of the first eigenvalues of the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively, calculate and obtain multiple groups of second eigenvalues corresponding to each group of candidate modulus values of the tire and calculate the average value, and obtain the modulus eigenvalue of the tire under different modulus attributes, realizing the optimization from a single parameter to multi-objective collaborative design, making the optimization result more suitable for practical applications, and improving the accuracy and usability of the simulation optimization.

[0058] In one embodiment, the obtaining of the optimal modulus matching of multiple rubbers of the tire based on the modulus eigenvalue of the tire under different modulus attributes further includes: Select a group of candidate modulus values corresponding to the smallest modulus eigenvalue from the modulus eigenvalues of the tire under different modulus attributes as the optimal modulus ratio of the multiple rubbers of the tire. The size of the modulus eigenvalue is related to the strain of the belt layer end point. The smaller the modulus eigenvalue, the smaller the stress and strain of the belt layer end point, indicating that its fatigue resistance to damage is better and the fatigue life is longer. Therefore, select a group of candidate modulus values corresponding to the smallest modulus eigenvalue as the optimal modulus ratio of the multiple rubbers of the tire. As Figure 7 shown in the finite element calculation result diagram of the tire belt layer end point, where the minimum value is obtained through solution P10, which is consistent with the calculation result, improving the reliability of the calculation result.

[0059] Figure 8 is a schematic structural diagram of a simulation optimization device for the modulus matching of multiple rubbers of a tire according to an embodiment of the present application. AsFigure 8 As shown, the device includes the following units: A modeling unit 801 for constructing a finite element model of a tire and a road surface, where the finite element model of the tire and the road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model.

[0060] A first calculation unit 802 for matching the modulus property of the rubber compound to which each finite element mesh of the tire simulation model belongs by using the orthogonal experimental design method, and performing finite element calculation based on the finite element model of the tire and the road surface, and calculating multiple groups of stress-strain and strain energy data of the target belt layer end points of the tire under different modulus properties.

[0061] A second calculation unit 803 for respectively calculating the modulus eigenvalue of the tire under different modulus properties based on the multiple groups of stress-strain and strain energy data of the target belt layer end points of the tire under different modulus properties.

[0062] An optimization unit 804 for obtaining the optimal modulus ratio of the multi-rubber compound of the tire based on the modulus eigenvalues of the tire under different modulus properties.

[0063] In one embodiment, as Figure 9 shown, the first calculation unit 802 may further include the following units: A modulus acquisition unit 901 for taking the modulus of the rubber compound of each part of the tire as an orthogonal experimental design variable, and selecting multiple groups of candidate modulus values of the rubber compound of each part at multiple factor levels.

[0064] A modulus matching unit 902 for matching the corresponding candidate modulus value in each group of candidate modulus values to each finite element mesh according to the rubber compound type of the corresponding part of each finite element mesh of the tire simulation model.

[0065] In one embodiment, as Figure 10 shown, the second calculation unit 803 may further include the following units: A third calculation unit 1001 for respectively calculating the stress-strain values of the first belt layer end point, the second belt layer end point and the third belt layer end point of the tire simulation model in each direction for each group of candidate modulus values.

[0066] A fourth calculation unit 1002 for calculating 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 based on the weights of the stress-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.

[0067] In one embodiment, as Figure 11As shown, the second calculation unit 803 may further include the following units: The first feature calculation unit 1101 is configured to calculate the first eigenvalue of the first belt layer end point, the second belt layer end point, and the third belt layer end point 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 end point, the second belt layer end point, and the third belt layer end point.

[0068] The second feature calculation unit 1102 is configured to calculate multiple groups of second eigenvalues corresponding to each group of candidate modulus values of the tire by performing weighted summation on multiple groups of weights of the first eigenvalues of the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively.

[0069] The third feature calculation unit 1103 is configured to calculate the average value of multiple groups of second eigenvalues corresponding to each group of candidate modulus values of the tire to obtain the modulus eigenvalue of the tire under different modulus attributes.

[0070] In one embodiment, as Figure 12 shown, the third calculation unit 1001 may further include: The fifth calculation unit 1201 is configured to calculate the stress and strain values of multiple finite element meshes included in the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively in each direction.

[0071] The sixth calculation unit 1202 is configured to calculate the average value of the stress and strain values of multiple finite element meshes included in the first belt layer end point, the second belt layer end point, and the third belt layer end point respectively in each direction as 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.

[0072] In summary, in the embodiment of the present application, a finite element model of a tire and a road surface is constructed. The finite element model of the tire and the road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model. The 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. By designing experimental variables from multiple levels for multiple selected factors, corresponding material properties are assigned to each mesh, accelerating factor convergence while reducing the calculation cost. Since the fatigue failure point of the tire in this embodiment is located at the belt layer end point, based on the finite element model of the tire and the road surface, finite element calculations are performed on multiple groups of stress-strain and strain energy data of the target belt layer end point of the tire under different modulus properties, and the fatigue life of the tire under different modulus combinations can be quantitatively predicted; based on the multiple groups of stress-strain and strain energy data of the target belt layer end point of the tire under different modulus properties, the modulus eigenvalue of the tire under different modulus properties is calculated respectively. Among them, the modulus eigenvalue reflects the regulation effect of the rubber compound modulus on the key performance of the tire (such as fatigue life, stress concentration, energy dissipation), and is a composite parameter extracted based on stress, strain data and strain energy data, realizing multi-objective collaborative design, making the optimization result more suitable for practical applications, and improving the accuracy and usability of simulation optimization; based on the modulus eigenvalue of the tire under different modulus properties, the magnitudes of the modulus eigenvalues under different modulus properties are compared to obtain the optimal modulus ratio of the multi-rubber compound of the tire, optimizing the tire performance, extending the service life of the tire while improving the material utilization rate of tire design and reducing the design cost. Therefore, in the embodiment of the present application, by calculating the modulus matching of the multi-rubber compound of the tire through the finite element model, multi-objective collaborative design is realized, making the optimization result more suitable for practical applications, improving the accuracy and usability of simulation optimization. At the same time, while optimizing the tire performance and extending the service life of the tire, the material utilization rate of tire design is improved and the design cost is reduced.

[0073] It should be noted that those skilled in the art can understand that the different implementation manners, explanations and achieved technical effects described in the method embodiments of the present application are equally applicable to the device embodiments of the present application, and will not be repeated here.

[0074] The above describes the exemplary embodiments of the present application. It should be understood that the above exemplary embodiments are not restrictive but illustrative, and the protection scope of the present application is not limited thereto. It should be understood that those skilled in the art can modify and vary the embodiments of the present application without departing from the spirit and scope of the present application, and these modifications and variations should be within the protection scope of the present application.

Claims

1. A simulation optimization method for modulus matching of multiple rubber compounds of a tire, characterized in that, The method includes: Constructing a finite element model of a tire and a road surface, where the finite element model of the tire and the road surface includes a three-dimensional tire simulation model and a two-dimensional rigid road surface model; Matching the modulus attributes of the rubber compounds to which each finite element mesh of the tire simulation model belongs by means of an orthogonal experimental design method, and performing finite element calculations based on the finite element model of the tire and the road surface to calculate multiple sets of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes; Respectively calculating the modulus characteristic values of the tire under different modulus attributes based on the multiple sets of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes; Obtaining the optimal modulus ratio of the multi-rubber compounds of the tire based on the modulus characteristic values of the tire under different modulus attributes.

2. The simulation optimization method for modulus matching of multiple rubber compounds of a tire according to claim 1, characterized in that The matching the modulus attributes of the rubber compounds to which each finite element mesh of the tire simulation model belongs by means of an orthogonal experimental design method includes: Taking the moduli of the rubber compounds of each part of the tire as the variables of the orthogonal experimental design, and selecting multiple sets of candidate modulus values of the rubber compounds of each part at multiple factor levels; According to the rubber compound type of the corresponding part of each finite element mesh of the tire simulation model, matching the corresponding candidate modulus value in each set of candidate modulus values to each finite element mesh.

3. The simulation optimization method for modulus matching of multiple rubber compounds of a tire according to claim 2, wherein, The performing finite element calculations based on the finite element model of the tire and the road surface to calculate multiple sets of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes includes: For each set of candidate modulus values, respectively calculating the stress-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; Based on the weights of the stress-strain values of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction, calculating the stress weighted average value and the strain weighted average value of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint in each direction.

4. A simulation optimization method for modulus matching of multiple rubber compounds of a tire according to claim 3, characterized in that, The performing finite element calculations based on the finite element model of the tire and the road surface to calculate multiple sets of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes includes: For each set of candidate modulus values, respectively calculating the weighted average value 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.

5. A simulation optimization method for modulus matching of multiple rubber compounds of a tire, characterized in that The respectively calculating the modulus characteristic values of the tire under different modulus attributes based on the multiple sets of stress-strain and strain energy data of the target belt layer endpoints of the tire under different modulus attributes includes: Based on the weighted summation of the stress weighted average value, the strain weighted average value, and the weighted average value of the strain energy density of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, respectively calculating the first characteristic values of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint; Based on the multiple sets of weights of the first characteristic values of the first belt layer endpoint, the second belt layer endpoint, and the third belt layer endpoint, respectively performing weighted summation to calculate multiple sets of second characteristic values corresponding to each set of candidate modulus values of the tire; Calculate the average value of multiple sets of second eigenvalue corresponding to each set of candidate modulus values of the tire, and obtain the modulus eigenvalue of the tire under different modulus attributes.

6. The simulation optimization method for modulus matching of multiple rubber compounds of a tire according to claim 5, wherein Based on the modulus eigenvalue of the tire under different modulus attributes, obtaining the optimal modulus matching of multiple rubber compounds of the tire further includes: Select a set of candidate modulus values corresponding to the minimum modulus eigenvalue from the modulus eigenvalues of the tire under different modulus attributes as the optimal modulus ratio of the multiple rubber compounds of the tire.

7. The simulation optimization method for modulus matching of multiple rubber compounds of a tire according to claim 6, characterized in that, For each set of candidate modulus values, calculating 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 of the tire simulation model in each direction respectively includes: Calculate the stress and strain values of each of the multiple finite element meshes included in the first belt layer end point, the second belt layer end point and the third belt layer end point in each direction respectively; Calculate the average value of the stress and strain values of each of the multiple finite element meshes included in the first belt layer end point, the second belt layer end point and the third belt layer end point in each direction respectively, and use it as 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.

8. A simulation optimization method for modulus matching of multiple rubber compounds of a tire according to claim 1, characterized in that, The rubber compounds of each part of the tire include tread rubber, base rubber and shoulder pad rubber.

9. A simulation optimization device for modulus matching of multiple rubber compounds of a tire, characterized in that, The device includes: A modeling unit for constructing a finite element model of a tire and a road surface, the finite element model of the tire and the road surface including a three-dimensional tire simulation model and a two-dimensional rigid road surface model; A first calculation unit for matching the modulus attributes of the rubber compounds to which each finite element mesh of the tire simulation model belongs by means of orthogonal experimental design method, and performing finite element calculation based on the finite element model of the tire and the road surface, and calculating multiple sets of stress and strain and strain energy data of the target belt layer end point of the tire under different modulus attributes; A second calculation unit for calculating the modulus eigenvalues of the tire under different modulus attributes respectively based on the multiple sets of stress and strain and strain energy data of the target belt layer end point of the tire under different modulus attributes; An optimization unit for obtaining the optimal modulus ratio of the multiple rubber compounds of the tire based on the modulus eigenvalues of the tire under different modulus attributes.

10. A simulation optimization system for modulus matching of multiple rubber compounds of a tire, characterized in that, Includes: 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 methods for executing any one of claims 1 to 8.

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