WO2021244677A1 - 一种轮胎模型的优化方法及设备 - Google Patents

一种轮胎模型的优化方法及设备 Download PDF

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WO2021244677A1
WO2021244677A1 PCT/CN2021/110132 CN2021110132W WO2021244677A1 WO 2021244677 A1 WO2021244677 A1 WO 2021244677A1 CN 2021110132 W CN2021110132 W CN 2021110132W WO 2021244677 A1 WO2021244677 A1 WO 2021244677A1
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modal
optimized
tire model
cross
coordinates
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PCT/CN2021/110132
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English (en)
French (fr)
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王�锋
WuZhengqi
刘畅
宋明亮
渠春玲
魏胜
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山东玲珑轮胎股份有限公司
北京玲珑轮胎有限公司
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Publication of WO2021244677A1 publication Critical patent/WO2021244677A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • G06F30/23Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]

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  • This application relates to the field of tire technology, and more specifically, to a tire model optimization method and equipment.
  • the present invention provides a tire model optimization method to solve the technical problem of low efficiency of tire model optimization in the prior art.
  • the method includes:
  • An optimized tire model is generated based on a plurality of the cross-sectional models.
  • the generation of multiple cross-sectional models based on the modal coordinates and multiple preset coefficients of the positions of the cross-sections is specifically realized through a cross-sectional contour generation equation, and the cross-sectional contour generation equation is specifically:
  • is the cross-sectional model coordinates
  • ⁇ 1, ⁇ 2... ⁇ n are the modal coordinate coordinates of the first to nth order modes
  • K1, K2...Kn are the multiple preset coefficients
  • K1+K2+...Kn 1.
  • the modal coordinates of each modal order are saved in an ODB file.
  • the method further includes:
  • the present invention also provides a tire model optimization device, which includes:
  • the processing module is configured to perform finite element analysis processing on the tire model to be optimized to obtain the modal coordinates of each cross-sectional position of the tire to be optimized, and the modal coordinates corresponding to one or more modal orders;
  • the first generating module is configured to generate multiple cross-sectional models based on the modal coordinates and multiple preset coefficients, and the sum of the multiple preset coefficients is 1;
  • the second generating module is used to generate an optimized tire model based on a plurality of the cross-sectional models.
  • the generation of multiple cross-sectional models based on the modal coordinates and multiple preset coefficients of the positions of the cross-sections is specifically realized through a cross-sectional contour generation equation, and the cross-sectional contour generation equation is specifically:
  • is the cross-sectional model coordinates
  • ⁇ 1, ⁇ 2... ⁇ n are the modal coordinate coordinates of the first to nth order modes
  • K1, K2...Kn are the multiple preset coefficients
  • K1+K2+...Kn 1.
  • the processing module is specifically used for:
  • the modal coordinates of each modal order are determined based on the modalities of the multiple modal orders, and the modal coordinates of each modal order are used as the modal coordinates of each section position.
  • the modal coordinates of each modal order are saved in an ODB file.
  • the processing module is further used for:
  • the present invention has the following beneficial effects:
  • the invention discloses a tire model optimization method and equipment.
  • the method includes: performing finite element analysis processing on the tire model to be optimized to obtain the modal coordinates of each section position of the tire to be optimized, and the modal coordinates correspond to
  • the modal order of is one or more; multiple section models are generated based on the modal coordinates and multiple preset coefficients, and the sum of the multiple preset coefficients is 1; the optimization is generated based on the multiple section models
  • a large number of cross-sectional models can be generated through the above-mentioned method, and then a tire model is generated based on the cross-sectional model, thereby improving the optimization efficiency of the tire model.
  • FIG. 1 shows a schematic flowchart of a tire model optimization method proposed by an embodiment of the present invention
  • FIG. 2 shows a schematic flowchart of a tire model optimization method proposed by another embodiment of the present invention
  • Fig. 3 shows a schematic structural diagram of a tire model optimization device proposed by an embodiment of the present invention
  • Fig. 4 shows a schematic diagram of a tire model to be optimized proposed by an embodiment of the present invention
  • FIG. 5 shows a schematic diagram of various modes of a tire model to be optimized proposed by an embodiment of the present invention
  • FIG. 6 shows a schematic diagram of the tire outer diameter and cross-sectional width of a tire model with a preset coefficient within a preset range proposed by an embodiment of the present invention
  • FIG. 7 shows a schematic diagram of the comparison of the tire model to be optimized before and after optimization proposed in the embodiment of the present invention.
  • the embodiment of the present application proposes a tire model optimization method and equipment.
  • the method includes: performing finite element analysis processing on the tire model to be optimized to obtain the modal coordinates of each section position of the tire to be optimized ,
  • the modal order corresponding to the modal coordinate is one or more; generating multiple section models based on the modal coordinate and multiple preset coefficients, and the sum of the multiple preset coefficients is 1;
  • Each of the cross-section models generates an optimized tire model.
  • a schematic flowchart of a tire model optimization method proposed in an embodiment of the present invention includes the following steps:
  • S101 Perform a finite element analysis process on the tire model to be optimized to obtain modal coordinates of each cross-sectional position of the tire model to be optimized, and the modal coordinates correspond to one or more modal orders.
  • the model to be optimized is selected in advance. From a large number of tire model libraries, a regular and representative tire model is selected, that is, a tire model with better performance is selected and used as the model to be optimized.
  • the optimized tire model the performance refers to the rolling resistance, that is to say, generally an existing tire model with better rolling resistance is selected as the tire model to be optimized, and a tire model with better performance can be generated based on the tire model to be optimized.
  • the modal order corresponding to the modal coordinate is one or more, for example, the modal coordinate of the seventh-order modal.
  • Finite element analysis can use mathematical approximation methods to simulate real physical systems. Using simple and interacting elements, a finite number of unknowns can be used to approximate the real system of infinite unknowns.
  • Finite element analysis is to replace complex problems with simpler problems before solving. It regards the solution domain as consisting of many small interconnected subdomains called finite elements, and assumes a suitable approximate solution for each element. Let’s say that this approximate solution is simpler, and then we derive and solve the total satisfying conditions of the domain, such as the equilibrium condition of the structure, so as to obtain the solution of the problem. Because the actual problem is replaced by a simpler problem, this solution is not an accurate solution. It is an approximate solution. Because most practical problems are difficult to obtain accurate solutions, finite element not only has high calculation accuracy, but also can adapt to various complex shapes, so it has become an effective engineering analysis method.
  • any simulation software can be used to perform finite element analysis on the model to be optimized, such as ABAQUS, ANSYS, etc., and generate corresponding analytical data File, read the modal coordinates of each section position by reading the parsed data file.
  • the tire model to be optimized is subjected to finite element analysis processing to obtain the modality of each section position of the tire model to be optimized Coordinates, specifically:
  • the modal coordinates of each modal order are determined based on the modalities of the multiple modal orders, and the modal coordinates of each modal order are used as the modal coordinates of each section position.
  • the order of the modes can be adjusted according to actual needs, for example, If the order is selected as the seventh order, then the 1-7 order modals of the tire model to be optimized are obtained.
  • the modal coordinates of the modals of each order that is, the modal coordinates of the cross-sections, are sequentially acquired.
  • the method further includes:
  • the number of nodes of the tire model to be optimized before performing finite element analysis on the tire model to be optimized, it is also necessary to receive the number of nodes of the tire model to be optimized, the number of nodes on the symmetry axis of the tire model to be optimized, and The node number of the highest point of the tire crown of the to-be-optimized tire model is subjected to finite element analysis on the to-be-optimized tire model according to the above-mentioned input data, the number of nodes of the to-be-optimized tire model input by the user, and the The number of nodes on the symmetry axis of the tire model to be optimized and the node number of the highest point of the crown of the tire model to be optimized are specifically shown in FIG. 4.
  • S102 Generate multiple cross-sectional models based on the modal coordinates and multiple preset coefficients, where the sum of the multiple preset coefficients is 1.
  • a corresponding number of preset coefficients are determined according to the modal order of the modal coordinates, and the sum of the plurality of preset coefficients is 1, based on the modal
  • multiple cross-section models can be determined.
  • the generation of multiple cross-sectional models based on the modal coordinates of each cross-section and a plurality of preset coefficients is specifically realized by generating equations for the external contour of the cross-section.
  • the generating equation of the outer contour of the section is specifically:
  • is the cross-sectional model coordinates
  • ⁇ 1, ⁇ 2... ⁇ n are the modal coordinates of the first to nth order modes
  • K1, K2...Kn are the multiple preset coefficients
  • K1+K2+...Kn 1 .
  • a cross-sectional contour generation equation is constructed.
  • multiple preset coefficients and modal coordinates of multi-order modes can be different.
  • Combining to generate the coordinates of multiple cross-sectional models, and multiple different cross-sectional models can be obtained through the coordinates of the cross-sectional model, realizing batch generation of cross-sectional models.
  • the value of K is determined according to the value range of the tire outer diameter in the tire industry standard, and the outer diameter of the standard range minus the outer diameter of the reference model is the value of K.
  • the modal coordinates of each modal order are stored in an ODB file.
  • the modal coordinates of each modal order are generated, the modal coordinates are saved in an ODB file, and when the cross-sectional contour generation equation is used to generate the cross-sectional model, it is directly read from the ODB file Just take the modal coordinates, which improves the generation efficiency of the section model.
  • the optimized tire model is generated by combining the plurality of the cross-sectional models.
  • the tire model to be optimized is subjected to finite element analysis processing to obtain the modal coordinates of each section position of the tire to be optimized, and the modal coordinates corresponding to the modal coordinates are one or more; based on The modal coordinates and multiple preset coefficients generate multiple cross-sectional models, and the sum of the multiple preset coefficients is 1.
  • An optimized tire model is generated based on the multiple cross-sectional models.
  • the embodiment of the present invention proposes a tire model optimization method, by performing finite element analysis processing on the tire model to be optimized, to obtain the modal coordinates of each section position of the tire to be optimized, and the modal coordinates corresponding to the modal coordinates
  • the order is one or more; multiple cross-sectional models are generated based on the modal coordinates and multiple preset coefficients, and the sum of the multiple preset coefficients is 1; an optimized tire is generated based on the multiple cross-sectional models Model, through the above method, a large number of cross-sectional models can be generated, and then tire models are generated based on the cross-sectional models, thereby improving the optimization efficiency of tire models
  • S201 Receive data of a tire model to be optimized input by a user.
  • the data of the tire model to be optimized is specifically the number of nodes of the tire model to be optimized, the number of nodes on the symmetry axis of the tire model to be optimized, and the highest point of the crown of the tire model to be optimized The sequence number of the node.
  • the plane grid is first divided, and then the tire model is established by rotating 360° along the axis of symmetry, and then based on the data of the tire model to be optimized, the tire model to be optimized can be limited Meta calculation processing, as shown in Figure 4.
  • S202 Perform finite element calculation processing on the tire model to be optimized, and obtain multiple modes of the tire model to be optimized, where the order of the multiple modes is 1 order or more.
  • the selection of the modal order can be reasonably selected according to the actual situation to achieve the optimal effect, and the difference in the modal order does not affect the protection scope of the present application.
  • S203 Determine modal coordinates according to the multiple modalities.
  • the modal coordinates corresponding to the multiple modalities are obtained, and the modal coordinates are stored in an OBD file to facilitate subsequent extraction at any time.
  • the generating equation of the outer contour of the cross-section is specifically as follows:
  • is the cross-sectional model coordinates
  • ⁇ 1, ⁇ 2... ⁇ n are the modal coordinates of the first to nth order modes
  • K1, K2...Kn are multiple preset coefficients
  • K1+K2+...Kn 1.
  • modal coordinates and preset coefficients are required.
  • the modal coordinates have been obtained through the above steps, so only multiple preset coefficients need to be obtained.
  • the coefficient is determined according to the node number of the highest point of the crown of the tire model to be optimized input by the user.
  • the mode order is 7, which means that it is necessary to obtain the mode coordinates of the 1-7 modes
  • ⁇ 1, ⁇ 2... ⁇ 7 are the coordinates of the first to seventh-order modes
  • k1, k2...k7 are the preset coefficients
  • K1+K2+...K7 1.
  • the value ranges of the preset coefficients k1, k2...k7 are as follows:
  • S205 Generate an optimized tire model based on the multiple cross-sectional models.
  • An optimized tire model is generated by combining a plurality of the cross-sectional models.
  • Fig. 7 is a comparison diagram of the tire model to be optimized before and after optimization.
  • the tire model to be optimized is subjected to finite element analysis processing to obtain the modal coordinates of each section position of the tire to be optimized, and the modal coordinates corresponding to the modal coordinates are one or more; based on The modal coordinates and multiple preset coefficients generate multiple cross-sectional models, and the sum of the multiple preset coefficients is 1.
  • An optimized tire model is generated based on the multiple cross-sectional models.
  • the embodiment of the present application also proposes a tire model optimization device. As shown in FIG. 3, the device includes:
  • the processing module 301 performs finite element analysis processing on the tire model to be optimized to obtain the modal coordinates of each section position of the tire to be optimized, and the modal coordinates corresponding to one or more modal orders;
  • the first generating module 302 generates multiple cross-sectional models based on the modal coordinates and multiple preset coefficients, and the sum of the multiple preset coefficients is 1;
  • the second generating module 303 generates an optimized tire model based on a plurality of the cross-sectional models.
  • the generation of multiple cross-sectional models based on the modal coordinates and multiple preset coefficients of the positions of the cross-sections is specifically realized by the cross-sectional contour generation equations, and the cross-sectional contour generation equations are specifically for:
  • is the coordinate of the cross-section model
  • ⁇ 1, ⁇ 2... ⁇ n are the modal coordinate coordinates of the first to nth order modes
  • K1, K2...Kn are the multiple preset coefficients
  • K1+K2+...Kn 1.
  • the processing module is specifically used for:
  • the modal coordinates of each modal order are determined based on the modalities of the multiple modal orders, and the modal coordinates of each modal order are used as the modal coordinates of each section position.
  • the modal coordinates of each modal order are stored in an ODB file.
  • the processing module is also used for:
  • the present invention can be implemented by hardware, or can be implemented by means of software plus a necessary general hardware platform.
  • the technical solution of the present invention can be embodied in the form of a software product.
  • the software product can be stored in a non-volatile storage medium (which can be a CD-ROM, U disk, mobile hard disk, etc.), including:
  • a computer device which may be a personal computer, a server, or a network device, etc. executes the methods described in each implementation scenario of the present invention.
  • modules in the device can be distributed in the device in the implementation scenario according to the description of the implementation scenario, or can be changed to be located in one or more devices different from the implementation scenario.
  • the modules of the above implementation scenarios can be combined into one module or further divided into multiple sub-modules.

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Abstract

一种轮胎模型的优化方法及设备,方法包括:对待优化轮胎模型进行有限元解析处理,以获取待优化轮胎的各断面位置的模态坐标,模态坐标对应的模态阶数为一个或多个(S101),基于模态坐标及多个预设系数生成多个断面模型,多个预设系数之和为1(S102),基于多个断面模型生成优化后的轮胎模型(S103),通过方法,可以生成大量的断面模型,进而基于断面模型生成轮胎模型,从而提高了轮胎模型的优化效率。

Description

一种轮胎模型的优化方法及设备 技术领域
本申请涉及轮胎技术领域,更具体地,涉及一种轮胎模型的优化方法及设备。
背景技术
汽车对轮胎性能的不断提高,为了满足需求,在采用石墨烯增强复合材料实现材料最优外,轮胎结构的优化设计是不可缺少的技术,轮胎结构的优化设计需要很多样本模型来构筑设计空间函数,因此在原有轮胎结构基础上,需要进一步优化设计生成大量的样本模型。
在现有技术的条件下,由于轮胎结构非常复杂,在保持相同轮胎模型体积下,生成大量的横断面结构模型需要花费大量时间和人力,传统方法进行轮胎结构优化生成断面形状模型非常困难,需要大量的时间。
因此,提出一种轮胎模型的优化方法,通过生成大量的轮胎模型的断面结构,提高轮胎模型的优化效率,是本领域技术人员亟待解决的技术问题。
发明内容
本发明提供一种轮胎模型的优化方法,用以解决现有技术中对轮胎模型的优化效率低的技术问题,该方法包括:
对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;
基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;
基于多个所述断面模型生成优化后的轮胎模型。
优选的,所述基于所述各断面的位置的模态坐标及多个预设系数生成多个断面模型具体是通过断面外轮廓生成方程实现的,所述断面外轮廓生成方程具体为:
φ=K 1φ 1+K 2φ 2+…+K nφ n
其中,φ是所述断面模型坐标,φ1、φ2…φn是1阶到n阶模态的模态坐标坐标,K1、K2…Kn是所述多个预设系数,且K1+K2+…Kn=1。
优选的,所述各模态阶数的模态坐标保存在ODB文件中。
优选的,在对待优化轮胎模型进行有限元解析处理之前,还包括:
接收用户输入的所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号。
相应地,本发明还提出了一种轮胎模型的优化设备,所述设备包括:
处理模块,用于对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;
第一生成模块,用于基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;
第二生成模块,用于基于多个所述断面模型生成优化后的轮胎模型。
优选的,所述基于所述各断面的位置的模态坐标及多个预设系数生成多个断面模型具体是通过断面外轮廓生成方程实现的,所述断面外轮廓生成方程具体为:
φ=K 1φ 1+K 2φ 2+…+K nφ n
其中,φ是所述断面模型坐标,φ1、φ2…φn是1阶到n阶模态的模态坐标坐标,K1、K2…Kn是所述多个预设系数,且K1+K2+…Kn=1。
优选的,所述处理模块具体用于:
对所述待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎模型的多个模态阶数的模态;
基于所述多个模态阶数的模态确定各模态阶数的模态坐标,并将所述各模态阶数的模态坐标作为所述各断面位置的模态坐标。
优选的,所述各模态阶数的模态坐标保存在ODB文件中。
优选的,所述处理模块,还用于:
接收用户输入的所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号。
与现有技术对比,本发明具备以下有益效果:
本发明公开了一种轮胎模型的优化方法及设备,该方法包括:对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;基于多个所述断面模型生成优化后的轮胎模型,通过上述方法,可以生成大量的断面模型,进而基于所述断面模型生成轮胎模型,从而提高了轮胎模型的优化效率。
附图说明
为了更清楚地说明本申请实施例中的技术方案,下面将对实施例描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本申请的一些实施例,对于本领域技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。
图1示出了本发明实施例提出的一种轮胎模型的优化方法的流程示意图;
图2示出了本发明另一实施例提出的一种轮胎模型的优化方法的流程示意图;
图3示出了本发明实施例提出的一种轮胎模型的优化设备的结构示意图;
图4示出了本发明实施例提出的待优化轮胎模型的示意图;
图5示出了本发明实施例提出的待优化轮胎模型的各阶模态示意图;
图6示出了本发明实施例提出的预设系数在预设范围内的轮胎模型的轮胎外直径和断面宽的示意图;
图7示出了本发明实施例提出的待优化轮胎模型优化前后的对比示意图。
具体实施方式
下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进 行清楚、完整地描述,显然,所描述的实施例仅仅是本申请一部分实施例,而不是全部的实施例。基于本申请中的实施例,本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例,都属于本申请保护的范围。
如背景技术所述,传统方法进行轮胎结构优化生成断面形状模型非常困难,需要大量的时间,优化效率低。
为解决上述问题,本申请实施例提出了一种轮胎模型的优化方法及设备,该方法包括:对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;基于多个所述断面模型生成优化后的轮胎模型,通过上述方法,可以生成大量的断面模型,进而基于所述断面模型生成轮胎模型,从而提高了轮胎模型的优化效率。
如图1所示本发明实施例提出的一种轮胎模型的优化方法的流程示意图,该方法包括以下步骤:
S101,对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎模型的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个。
具体的,所述待优化模型是预先选定的,在众多的轮胎模型库中,挑选出具有规律性、代表性的轮胎模型,也就是说挑选出性能较好的轮胎模型,将其作为待优化轮胎模型,所述性能是指滚阻,也就是说一般选取滚阻更好的现有轮胎模型作为待优化轮胎模型,基于所述待优化轮胎模型就可以生成性能更为优良的轮胎模型。
需要说明的是,以上选取标准仅是本申请的一个优选实施方案,本领域技术人员可以根据实际情况确定不同的选取标准,以获取需要的待优化轮胎模型,所述待优化轮胎模型的选取标准的不同并不影响本申请的保护范围。
在确定好待优化轮胎模型后,对所述待优化轮胎模型做有限元解析处理,通过有限元解析处理后,可以得到所述待优化轮胎模型的各断面位置的模态坐标,为了达到更好的优化效果,所述模态坐标对应的模态阶数为一个或多个,例如七阶模态的模态坐标。
有限元分析可以利用数学近似的方法对真实物理系统进行模拟,利用简单而又相互作用的单元,就可以用有限数量的未知量去逼近无限未知量的真实系统。
有限元分析是用较简单的问题代替复杂问题后再求解,它将求解域看成是由许多称为有限元的小的互连子域组成,对每一单元假定一个合适的近似解,一般来说这个近似解选取较为简单的,然后推导求解这个域总的满足条件,如结构的平衡条件,从而得到问题的解,因为实际问题被较简单的问题所代替,所以这个解不是准确解,而是近似解,由于大多数实际问题难以得到准确解,而有限元不仅计算精度高,而且能适应各种复杂形状,因而成为行之有效的工程分析手段。
在本申请的优选实施例中,在获取到所述待优化模型后,可以通过任一仿真软件对所述待优化模型进行有限元解析,例如ABAQUS,ANSYS等,并生成对应的解析后的数据文件,通过对所述解析后的数据文件读取出各断面位置的模态坐标。
需要说明的是,通过仿真软件获取模态坐标只是本申请的一个优选实施方式,其他通过有限元解析获取模态坐标的方式同样属于本申请的保护范围。
需要说明的是,本领域的技术人员可以根据实际需要对所述模态坐标对应的模态阶数进行选取,所述模态阶数的不同,并不影响本申请的保护范围。
为了准确的对所述待优化轮胎模型进行有限元解析处理,在本申请的 优选实施例中,对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎模型的各断面位置的模态坐标,具体为:
对所述待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎模型的多个模态阶数的模态;
基于所述多个模态阶数的模态确定各模态阶数的模态坐标,并将所述各模态阶数的模态坐标作为所述各断面位置的模态坐标。
具体的,在对所述待优化的轮胎模型进行有限元解析处理后,可以获取到所述待优化轮胎模型的多个模态,所述模态的阶数可根据实际需要进行调整,例如所述阶数选定为七阶,则获取所述待优化轮胎模型的1-7阶的模态。
在获取到所述模态后,依次获取所述各阶模态的模态坐标,也就是所述各断面的模态坐标。
为了对所述待优化轮胎模型进行有限元解析处理,在本申请的优选实施例中,在对待优化轮胎模型进行有限元解析处理之前,还包括:
接收用户输入的所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号。
具体的,在对所述待优化轮胎模型进行有限元解析处理之前,还需要接收用户输入的所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号,根据上述输入的数据对所述待优化轮胎模型进行有限元解析,所述用户输入的所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号具体如附图4所示。
S102,基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1。
具体的,当确定好所述模态坐标后,根据所述模态坐标的模态阶数确 定对应数量的预设系数,并且所述多个预设系数之和为1,基于所述模态坐标与预设系数的不同组合,就可以确定多个断面模型。
为了生成多个断面模型,在本申请的优选实施例中,所述基于所述各断面的模态坐标及多个预设系数生成多个断面模型具体是通过断面外轮廓生成方程实现的,所述断面外轮廓生成方程具体为:
φ=K 1φ 1+K 2φ 2+…+K nφ n
其中,φ是所述断面模型坐标,φ1、φ2…φn是1阶到n阶模态的模态坐标,K1、K2…Kn是所述多个预设系数,且K1+K2+…Kn=1。
具体的,为了可以生成多个断面模型,在本申请的优选实施例中,构建了断面外轮廓生成方程,通过上述方程,使得多个预设系数与多阶模态的模态坐标可以进行不同组合,进而生成多个断面模型的坐标,通过所述断面模型的坐标可以获得多个不同的断面模型,实现了断面模型的批量生成。
其中,所述K的取值根据轮胎行业标准中轮胎外直径取值范围确定,标准范围外直径减去基准模型外直径即为K的取值。
为了实现所述各模态阶数的模态坐标的调用,在本申请的优选实施例中,所述各模态阶数的模态坐标保存在ODB文件中。
具体的,在生成所述各模态阶数的模态坐标后,将所述模态坐标保存在ODB文件中,当采用断面外轮廓生成方程生成所述断面模型时,直接从ODB文件中读取所述模态坐标即可,提高了所述断面模型的生成效率。
S103,基于多个所述断面模型生成优化后的轮胎模型。
具体的,在通过上述断面外轮廓生成方程获取到多个所述断面模型后,通过多个所述断面模型的结合,从而生成优化后的轮胎模型。
通过应用以上技术方案,对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;基于多个所述断面模型生成优化后的轮胎模型,通过上述方法,可以生成大量的断面模型,进而基于所述断面模型生成轮胎模型,从而提高了轮胎模型的优化效率。
为了进一步阐述本发明的技术思想,如图2所示,现结合具体的应用场景,对本发明的技术方案进行说明。
本发明实施例提出了一种轮胎模型的优化方法,通过对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;基于多个所述断面模型生成优化后的轮胎模型,通过上述方法,可以生成大量的断面模型,进而基于所述断面模型生成轮胎模型,从而提高了轮胎模型的优化效率
上述方法具体步骤如下:
S201,接收用户输入的待优化轮胎模型的数据。
具体的,所述待优化轮胎模型的数据具体为所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号。
由于轮胎为轴对称结构,所以先进行平面网格划分,然后沿着对称轴周向旋转360°建立轮胎模型,进而根据上述待优化的轮胎模型的数据即可对所述待优化轮胎模型进行有限元计算处理,如图4所示。
S202,对待优化轮胎模型进行有限元计算处理,并获取所述待优化轮胎模型的多个模态,所述多个模态的阶数为1阶或多阶。
根据实际需要选取轮胎模型,并将其作为待优化轮胎模型,对所述待优化轮胎模型进行有限元计算处理,得到所述待优化轮胎模型的多阶模态,例如所述阶数为七阶,如图5所示为所述待优化轮胎模型的各阶模态图。
所述模态阶数的选取可以根据实际情况进行合理选取,以达到最优效果为准,所述模态阶数的不同并不影响本申请的保护范围。
S203,根据所述多个模态确定模态坐标。
当通过有限元计算处理后,得到所述多个模态对应的模态坐标,并将所述模态坐标存储到OBD文件中,方便后续随时进行提取。
需要说明的是,将所述模态坐标存储到OBD文件中仅是本申请的一个优选实施方式,存储位置的不同并不影响本申请的保护范围。
S204,根据断面外轮廓生成方程生成多个断面模型。
具体的,所述断面外轮廓生成方程具体为:
φ=K 1φ 1+K 2φ 2+…+K nφ n
其中,φ是所述断面模型坐标,φ1、φ2…φn是1阶到n阶模态的模态坐标,K1、K2…Kn是多个预设系数,且K1+K2+…Kn=1。
由上述方程可知,通过断面外轮廓方程生成断面模型,需要模态坐标以及预设系数,模态坐标通过上述的步骤已经获取,所以只需要获取多个预设系数即可,多个所述预设系数是根据所述用户输入的所述待优化轮胎模型的胎冠最高点的节点序号确定的。
例如,在本申请的优选实施例中,模态阶数为7,也就是说需要获取1-7阶模态的模态坐标,那么此时的断面外轮廓生成方程为φ=K 1φ 1+K 2φ 2+…+K 7φ 7,φ1,φ2…φ7是一到七阶模态的坐标,k1,k2…k7是所述预设系数,并且K1+K2+…K7=1。
为了生成的断面模型变动范围合理可用,预设系数k1,k2…k7的取值范围如下:
-5≤k1≤5
-5≤k2≤5
.
.
.
-5≤k7≤5
需要说明的是,上述预设系数的取值范围仅是本申请的一个优选实施例,本领域技术人员可以根据实际需要对所述取值范围进行调整,取值范围的不同并不影响本申请的保护范围。
通过上述模态坐标以及预设系数的不同组合,可以生成多个不同的断面模型,实现了断面模型的批量生成。
S205,基于多个所述断面模型生成优化后的轮胎模型。
通过对多个所述断面模型的结合生成优化后的轮胎模型。
如图6所示为在预设系数k取值为(-5,5)时生成不同的轮胎外直径和断面宽,在待优化的轮胎外轮廓基础上,进行外轮廓调整,满足轮胎结构优化设计对断面形状的需求。
如图7为所述待优化轮胎模型优化前后的对比图。
通过应用以上技术方案,对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;基于多个所述断面模型生成优化后的轮胎模型,通过上述方法,可以生成大量的断面模型,进而基于所述断面模型生成轮胎模型,从而提高了轮胎模型的优化效率。
为了达到以上技术目的,本申请实施例还提出了一种轮胎模型的优化设备,如图3所示,所述设备包括:
处理模块301,对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;
第一生成模块302,基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;
第二生成模块303,基于多个所述断面模型生成优化后的轮胎模型。
在具体的应用场景中,所述基于所述各断面的位置的模态坐标及多个预设系数生成多个断面模型具体是通过断面外轮廓生成方程实现的,所述断面外轮廓生成方程具体为:
φ=K 1φ 1+K 2φ 2+…+K nφ n
其中,φ是所述断面模型坐标,φ1、φ2…φn是1阶到n阶模态的模态坐标坐标,K1、K2…Kn是所述多个预设系数,且K1+K2+…Kn=1。
在具体的应用场景中,所述处理模块具体用于:
对所述待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎模型的多个模态阶数的模态;
基于所述多个模态阶数的模态确定各模态阶数的模态坐标,并将所述各模态阶数的模态坐标作为所述各断面位置的模态坐标。
在具体的应用场景中,所述各模态阶数的模态坐标保存在ODB文件中。
在具体的应用场景中,所述处理模块,还用于:
接收用户输入的所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号。
通过以上的实施方式的描述,本领域的技术人员可以清楚地了解到本发明可以通过硬件实现,也可以借助软件加必要的通用硬件平台的方式来实现。基于这样的理解,本发明的技术方案可以以软件产品的形式体现出来,该软件产品可以存储在一个非易失性存储介质(可以是CD-ROM,U盘,移动硬盘等)中,包括以若干指令的形式使一台计算机设备(可以是个人计算机,服务器,或者网络设备等)执行本发明各个实施场景所述的方法。
本领域技术人员可以理解附图只是一个优选实施场景的示意图,附图中的模块或流程并不一定是实施本发明所必须的。
本领域技术人员可以理解装置中的模块可以按照实施场景描述分布于实施场景的装置中,也可以进行相应变化位于不同于本实施场景的一个或多个装置中。上述实施场景的模块可以合并为一个模块,也可以进一步拆分成多个子模块。
上述本发明序号仅仅为了描述,不代表实施场景的优劣。
以上公开的仅为本发明的几个具体实施场景,但是,本发明并非局限于此,任何本领域的技术人员能思之的变化都应落入本发明的保护范围。

Claims (10)

  1. 一种轮胎模型的优化方法,其特征在于,所述方法包括:
    对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;
    基于所述模态坐标及多个预设系数生成多个断面模型,所述多个预设系数之和为1;
    基于多个所述断面模型生成优化后的轮胎模型。
  2. 如权利要求1所述的方法,其特征在于,所述基于所述各断面的位置的模态坐标及多个预设系数生成多个断面模型具体是通过断面外轮廓生成方程实现的,所述断面外轮廓生成方程具体为:
    φ=K 1φ 1+K 2φ 2+…+K nφ n
    其中,φ是所述断面模型坐标,φ1、φ2…φn是1阶到n阶模态的模态坐标坐标,K1、K2…Kn是所述多个预设系数,且K1+K2+…Kn=1。
  3. 如权利要求1所述的方法,其特征在于,对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎模型的各断面位置的模态坐标,具体为:
    对所述待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎模型的多个模态阶数的模态;
    基于所述多个模态阶数的模态确定各模态阶数的模态坐标,并将所述各模态阶数的模态坐标作为所述各断面位置的模态坐标。
  4. 如权利要求3所述的方法,其特征在于,所述各模态阶数的模态坐标保存在ODB文件中。
  5. 如权利要求1所述的方法,其特征在于,在对待优化轮胎模型进行有限元解析处理之前,还包括:
    接收用户输入的所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号。
  6. 一种轮胎模型的优化设备,其特征在于,所述设备包括:
    处理模块,对待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎的各断面位置的模态坐标,所述模态坐标对应的模态阶数为一个或多个;
    第一生成模块,基于所述模态坐标及多个预设系数生成多个断面模型, 所述多个预设系数之和为1;
    第二生成模块,基于多个所述断面模型生成优化后的轮胎模型。
  7. 如权利要求6所述的设备,其特征在于,所述基于所述各断面的位置的模态坐标及多个预设系数生成多个断面模型具体是通过断面外轮廓生成方程实现的,所述断面外轮廓生成方程具体为:
    φ=K 1φ 1+K 2φ 2+…+K nφ n
    其中,φ是所述断面模型坐标,φ1、φ2…φn是1阶到n阶模态的模态坐标坐标,K1、K2…Kn是所述多个预设系数,且K1+K2+…Kn=1。
  8. 如权利要求6所述的设备,其特征在于,所述处理模块具体用于:
    对所述待优化轮胎模型进行有限元解析处理,以获取所述待优化轮胎模型的多个模态阶数的模态;
    基于所述多个模态阶数的模态确定各模态阶数的模态坐标,并将所述各模态阶数的模态坐标作为所述各断面位置的模态坐标。
  9. 如权利要求8所述的设备,其特征在于,所述各模态阶数的模态坐标保存在ODB文件中。
  10. 如权利要求6所述的设备,其特征在于,所述处理模块,还用于:
    接收用户输入的所述待优化轮胎模型的节点个数、所述待优化轮胎模型的对称轴上的节点个数以及所述待优化轮胎模型的胎冠最高点的节点序号。
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Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111914441B (zh) * 2020-06-02 2022-11-29 山东玲珑轮胎股份有限公司 一种轮胎模型的优化方法及设备
CN113392549B (zh) * 2021-06-02 2022-08-30 中策橡胶集团股份有限公司 一种轮胎外轮廓快速提取方法、设备和可读载体介质
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020014294A1 (en) * 2000-06-29 2002-02-07 The Yokohama Rubber Co., Ltd. Shape design process of engineering products and pneumatic tire designed using the present design process
JP2002099579A (ja) * 2000-09-22 2002-04-05 Bridgestone Corp シミュレーション方法及び設計方法
CN103065021A (zh) * 2013-01-23 2013-04-24 鲁东大学 有限元模型修正的多步有效法
CN105631090A (zh) * 2015-12-02 2016-06-01 中国商用飞机有限责任公司北京民用飞机技术研究中心 一种有限元模型优化装置及方法
CN107145663A (zh) * 2017-05-04 2017-09-08 吉林大学 车轮多目标优化设计方法
JP2018079789A (ja) * 2016-11-16 2018-05-24 東洋ゴム工業株式会社 タイヤ接地シミュレーション方法、装置、及びプログラム
CN111914441A (zh) * 2020-06-02 2020-11-10 山东玲珑轮胎股份有限公司 一种轮胎模型的优化方法及设备

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101510230A (zh) * 2009-03-11 2009-08-19 同济大学 车辆道路载荷的仿真方法
JP2012088834A (ja) * 2010-10-18 2012-05-10 Bridgestone Corp 振動モード算出方法及び振動モード算出装置
CN108470086B (zh) * 2018-02-09 2020-06-16 中国汽车工程研究院股份有限公司 轮胎不平衡量的动力学模拟方法
CN109885864B (zh) * 2019-01-07 2023-03-17 长沙理工大学 一种三维钢桥塔涡激振动计算方法
CN109977460B (zh) * 2019-02-14 2023-03-24 中国第一汽车股份有限公司 一种基于车身断面参数化的多目标优化设计方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020014294A1 (en) * 2000-06-29 2002-02-07 The Yokohama Rubber Co., Ltd. Shape design process of engineering products and pneumatic tire designed using the present design process
JP2002099579A (ja) * 2000-09-22 2002-04-05 Bridgestone Corp シミュレーション方法及び設計方法
CN103065021A (zh) * 2013-01-23 2013-04-24 鲁东大学 有限元模型修正的多步有效法
CN105631090A (zh) * 2015-12-02 2016-06-01 中国商用飞机有限责任公司北京民用飞机技术研究中心 一种有限元模型优化装置及方法
JP2018079789A (ja) * 2016-11-16 2018-05-24 東洋ゴム工業株式会社 タイヤ接地シミュレーション方法、装置、及びプログラム
CN107145663A (zh) * 2017-05-04 2017-09-08 吉林大学 车轮多目标优化设计方法
CN111914441A (zh) * 2020-06-02 2020-11-10 山东玲珑轮胎股份有限公司 一种轮胎模型的优化方法及设备

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
LIU, WEI: "Study on Linear Material Modeling & Influencing Factors of Modal Tire", JOURNAL OF CHONGQING UNIVERSITY OF TECHNOLOGY(NATURAL SCIENCE), vol. 34, no. 5, 31 May 2020 (2020-05-31), pages 121 - 129, XP055876849 *

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