CN116842637A

CN116842637A - Method and device for determining performance relevance of tire and whole vehicle and storage medium

Info

Publication number: CN116842637A
Application number: CN202310805303.XA
Authority: CN
Inventors: 陈南施; 成健; 禹慧丽; 曾庆强; 张振伟
Original assignee: Chongqing Changan Automobile Co Ltd
Current assignee: Chongqing Changan Automobile Co Ltd
Priority date: 2023-06-30
Filing date: 2023-06-30
Publication date: 2023-10-03

Abstract

The application relates to a method and a device for determining the relevance of performances of a tire and a whole vehicle and a storage medium, and relates to the technical field of automobiles. The method comprises the following steps: and obtaining a tire simulation model and a whole vehicle simulation model. And determining a performance function corresponding to the tire simulation model based on the tire simulation model. And determining a first association relationship based on the tire simulation model and the whole vehicle simulation model. And respectively adjusting the tire simulation model and the whole vehicle simulation model based on each target coefficient and the first association relation, and determining multiple groups of performance change information. A second association is determined based on the plurality of sets of performance change information. Therefore, the whole vehicle factory can put forward the tire requirement based on the influence degree of the tire performance index on the whole vehicle performance index, so that the negative influence of the tire performance index on the whole vehicle performance index is reduced. The method can directly put forward the monomer performance requirement on the tire layer surface for the tire, and has important significance for the vehicle manufacturing of the whole vehicle factory.

Description

Method and device for determining performance relevance of tire and whole vehicle and storage medium

Technical Field

The application relates to the field of automobiles, in particular to the technical field of influence of tire performance on the performance of the whole automobile, and specifically relates to a method and a device for determining the relevance of the tire and the performance of the whole automobile and a storage medium.

Background

In recent years, with the development of automobile technology, there is an increasing demand for running performance of automobiles. The steering stability and steering performance of the automobile are important components of the running performance of the automobile, and the tire is the only part of the automobile which is contacted with the road surface, so that the mechanical property of the tire is critical to the steering stability and steering performance of the whole automobile.

At present, the tire belongs to a multi-performance integrated part, and the performance integration process is completed in a tire factory. Therefore, the whole vehicle factory can only present the performance requirement for the tire from the whole vehicle layer to the tire factory, which can lead to general, unspecific and unfocused requirements. Therefore, how to determine the relation between the performance of the whole vehicle and the performance of the tire becomes a technical problem to be solved.

Disclosure of Invention

The application provides a method, a device and a storage medium for determining the relevance of a tire and the performance of a whole vehicle, which are used for at least solving the technical problem of how to determine the relation between the performance of the whole vehicle and the performance of the tire. The technical scheme of the application is as follows:

according to a first aspect of the present application, a method for determining a performance association between a tire and a whole vehicle is provided, including: obtaining a tire simulation model and a whole vehicle simulation model, wherein the tire simulation model comprises: the whole vehicle simulation model comprises a plurality of tire performance indexes: a plurality of whole car performance indexes. And determining a performance function corresponding to the tire simulation model based on the tire simulation model, wherein the performance function comprises a plurality of coefficients to be adjusted. At least one target coefficient is determined from a plurality of coefficients to be adjusted, wherein the target coefficient is the coefficient to be adjusted, and the influence degree of the coefficient to be adjusted on the tire performance index is larger than a preset influence degree threshold value. And determining a first association relationship based on the tire simulation model and the whole vehicle simulation model, wherein the first association relationship is used for indicating the association between the whole vehicle simulation model and the tire simulation model. Based on each target coefficient and the first association relation, respectively adjusting a tire simulation model and a whole vehicle simulation model, and determining a plurality of groups of performance change information, wherein one group of performance change information comprises: the change amount of each tire performance index and the change amount of each whole vehicle performance index, and one group of performance change information corresponds to one target coefficient. And determining a second association relation based on the plurality of groups of performance change information, wherein the second association relation is used for indicating the influence degree of the tire performance index on the whole vehicle performance index.

Based on the above technical scheme, the server obtains a tire simulation model and a whole vehicle simulation model, and the tire simulation model comprises: the whole vehicle simulation model comprises a plurality of tire performance indexes: a plurality of whole car performance indexes. Then, the server can determine a performance function corresponding to the tire simulation model based on the tire simulation model, wherein the performance function comprises a plurality of coefficients to be adjusted, and at least one target coefficient is determined from the coefficients to be adjusted, and the target coefficient is the coefficient to be adjusted, wherein the influence degree of the coefficient to be adjusted on the tire performance index is greater than a preset influence degree threshold value. In this way, the coefficient of which the degree of correlation between the portion and the tire performance index is low can be reduced. Then, the server determines the relevance between the whole vehicle simulation model and the tire simulation model based on the tire simulation model and the whole vehicle simulation model, adjusts the tire simulation model and the whole vehicle simulation model based on the relevance relation of each target coefficient, and determines a plurality of groups of performance change information, wherein one group of performance change information comprises: the change amount of each tire performance index and the change amount of each whole vehicle performance index, and one group of performance change information corresponds to one target coefficient. Thus, the server can determine the variation of the tire performance index and the variation of the overall vehicle performance index under the condition that the same coefficient is changed. Then, the server can determine the influence degree of the tire performance index on the whole vehicle performance index based on the plurality of groups of performance change information, namely, the influence on the whole vehicle performance index after the tire performance index is changed. Thus, the server can acquire the tire simulation model and the whole vehicle simulation model, and determine the target coefficient based on the tire simulation model. And then, the server establishes the association between the whole vehicle simulation model and the tire simulation model, adjusts the whole vehicle simulation model and the tire simulation model based on each target coefficient and the relation between the whole vehicle simulation model and the tire simulation model, and determines multiple groups of performance change information. And finally, the server determines the influence degree of the tire performance index on the whole vehicle performance index based on the plurality of groups of performance change information. In this way, a relationship between the tire performance index and the overall vehicle performance index can be established. Moreover, by adopting the technical scheme of the application, the whole vehicle factory can put forward the tire requirement based on the influence degree of the tire performance index on the whole vehicle performance index, thereby reducing the negative influence of the tire performance index on the whole vehicle performance index. The method can directly put forward the monomer performance requirement on the tire layer surface for the tire, and has important significance for the vehicle manufacturing of the whole vehicle factory.

In one possible embodiment, the method further comprises: and executing target operation on each coefficient to be adjusted, and determining at least one target coefficient from the plurality of coefficients to be adjusted. The target operation includes: updating the tire simulation model based on the coefficient to be adjusted to obtain an updated tire simulation model, wherein the updated tire simulation model comprises: a plurality of updated tire performance indicators. And if each updated tire performance index is in a preset tire performance interval corresponding to the tire performance index, taking the coefficient to be adjusted as the target coefficient.

In another possible embodiment, the method further comprises: and determining the variation of each tire performance index according to each updated tire performance index and each pre-updated tire performance index. Taking the coefficient to be adjusted as a target coefficient, comprising: if the target variable quantity exists in the variable quantities of the tire performance indexes, taking the coefficient to be adjusted as a target coefficient, wherein the target variable quantity is that the variable quantity of the tire performance indexes is larger than a preset tire performance change threshold value corresponding to the tire performance indexes.

In another possible embodiment, the method further comprises: and performing six-component force test on the tire simulation model to obtain a tire mechanical test curve. And adjusting the coefficient of the magic formula based on the tire mechanical test curve to obtain an adjusted magic formula, wherein the similarity between the function curve of the adjusted magic formula and the tire mechanical test curve is greater than a preset similarity threshold, and the adjusted magic formula is a performance function.

According to a second aspect of the present application, a device for determining a performance association between a tire and a whole vehicle is provided, and the device includes an acquisition unit and a processing unit.

The acquisition unit is used for acquiring a tire simulation model and a whole vehicle simulation model, and the tire simulation model comprises: the whole vehicle simulation model comprises a plurality of tire performance indexes: a plurality of whole car performance indexes. And the processing unit is used for determining a performance function corresponding to the tire simulation model based on the tire simulation model, wherein the performance function comprises a plurality of coefficients to be adjusted. The processing unit is further used for determining at least one target coefficient from the plurality of coefficients to be adjusted, wherein the target coefficient is the coefficient to be adjusted, and the influence degree of the coefficient to be adjusted on the tire performance index is greater than a preset influence degree threshold value. The processing unit is further used for determining a first association relation based on the tire simulation model and the whole vehicle simulation model, and the first association relation is used for indicating association between the whole vehicle simulation model and the tire simulation model. The processing unit is further configured to adjust the tire simulation model and the whole vehicle simulation model based on each target coefficient and the first association relationship, determine a plurality of sets of performance change information, where a set of performance change information includes: the change amount of each tire performance index and the change amount of each whole vehicle performance index, and one group of performance change information corresponds to one target coefficient. The processing unit is further used for determining a second association relation based on the plurality of groups of performance change information, and the second association relation is used for indicating the influence degree of the tire performance index on the whole vehicle performance index.

In one possible design, the processing unit is further configured to perform a target operation on each coefficient to be adjusted, and determine at least one target coefficient from the plurality of coefficients to be adjusted. The target operations include: the processing unit updates the tire simulation model based on the coefficient to be adjusted to obtain an updated tire simulation model, the updated tire simulation model comprising: a plurality of updated tire performance indicators. And if each updated tire performance index is in the preset tire performance interval corresponding to the tire performance index, the processing unit takes the coefficient to be adjusted as the target coefficient.

In another possible design, the processing unit is further configured to determine an amount of change in each tire performance index based on each updated tire performance index and each pre-updated tire performance index. The processing unit takes the coefficient to be adjusted as a target coefficient, and comprises the following steps: if the target variable quantity exists in the variable quantities of the tire performance indexes, the processing unit takes the coefficient to be adjusted as a target coefficient, and the target variable quantity is that the variable quantity of the tire performance indexes is larger than a preset tire performance change threshold value corresponding to the tire performance indexes.

In another possible design, the processing unit is further configured to perform a six-component test on the tire simulation model to obtain a tire mechanical test curve. The processing unit is used for adjusting the coefficient of the magic formula based on the tire mechanical test curve to obtain an adjusted magic formula, the similarity between the function curve of the adjusted magic formula and the tire mechanical test curve is greater than a preset similarity threshold, and the adjusted magic formula is a performance function.

According to a third aspect of the present application, there is provided an electronic apparatus comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement the method of the first aspect and any of its possible embodiments described above.

According to a fourth aspect of the present application there is provided a computer readable storage medium, which when executed by a processor of an electronic device, enables the electronic device to perform the method of the first aspect and any of its possible embodiments.

According to a fifth aspect of the present application there is provided a computer program product comprising computer instructions which, when run on an electronic device, cause the electronic device to perform the method of the first aspect and any of its possible embodiments.

Therefore, the technical characteristics of the application have the following beneficial effects:

the method comprises the steps that a server obtains a tire simulation model and a whole vehicle simulation model, and the tire simulation model comprises: the whole vehicle simulation model comprises a plurality of tire performance indexes: a plurality of whole car performance indexes. Then, the server can determine a performance function corresponding to the tire simulation model based on the tire simulation model, wherein the performance function comprises a plurality of coefficients to be adjusted, and at least one target coefficient is determined from the coefficients to be adjusted, and the target coefficient is the coefficient to be adjusted, wherein the influence degree of the coefficient to be adjusted on the tire performance index is greater than a preset influence degree threshold value. In this way, the coefficient of which the degree of correlation between the portion and the tire performance index is low can be reduced. Then, the server determines the relevance between the whole vehicle simulation model and the tire simulation model based on the tire simulation model and the whole vehicle simulation model, adjusts the tire simulation model and the whole vehicle simulation model based on the relevance relation of each target coefficient, and determines a plurality of groups of performance change information, wherein one group of performance change information comprises: the change amount of each tire performance index and the change amount of each whole vehicle performance index, and one group of performance change information corresponds to one target coefficient. Thus, the server can determine the variation of the tire performance index and the variation of the overall vehicle performance index under the condition that the same coefficient is changed. Then, the server can determine the influence degree of the tire performance index on the whole vehicle performance index based on the plurality of groups of performance change information, namely, the influence on the whole vehicle performance index after the tire performance index is changed. Thus, the server can acquire the tire simulation model and the whole vehicle simulation model, and determine the target coefficient based on the tire simulation model. And then, the server establishes the association between the whole vehicle simulation model and the tire simulation model, adjusts the whole vehicle simulation model and the tire simulation model based on each target coefficient and the relation between the whole vehicle simulation model and the tire simulation model, and determines multiple groups of performance change information. And finally, the server determines the influence degree of the tire performance index on the whole vehicle performance index based on the plurality of groups of performance change information. In this way, a relationship between the tire performance index and the overall vehicle performance index can be established. Moreover, by adopting the technical scheme of the application, the whole vehicle factory can put forward the tire requirement based on the influence degree of the tire performance index on the whole vehicle performance index, thereby reducing the negative influence of the tire performance index on the whole vehicle performance index. The method can directly put forward the monomer performance requirement on the tire layer surface for the tire, and has important significance for the vehicle manufacturing of the whole vehicle factory.

It should be noted that, the technical effects caused by any implementation manner of the second aspect to the fifth aspect may refer to the technical effects caused by the corresponding implementation manner in the first aspect, which are not described herein.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application and do not constitute a undue limitation on the application.

FIG. 1 is a schematic flow chart of a method for determining the performance relevance between a tire and a whole vehicle according to an embodiment of the present application;

FIG. 2 is a schematic diagram of the correlation between a tire simulation model and a whole vehicle simulation model provided by an embodiment of the present application;

FIG. 3 is a flowchart of another method for determining the performance correlation between a tire and a vehicle according to an embodiment of the present application;

FIG. 4 is a schematic structural diagram of a device for determining the performance relevance between a tire and a whole vehicle according to an embodiment of the present application;

FIG. 5 is a schematic structural diagram of a device for determining the performance correlation between a tire and a vehicle according to an embodiment of the present application;

Fig. 6 is a conceptual partial view of a computer program product provided by an embodiment of the application.

Detailed Description

In order to enable a person skilled in the art to better understand the technical solutions of the present application, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.

At present, the tire belongs to a multi-performance integrated part, and the performance integration process is completed in a tire factory. Therefore, the whole vehicle factory can only present the performance requirement for the tire from the whole vehicle layer to the tire factory, which can lead to general, unspecific and unfocused requirements. Therefore, how to determine the relation between the performance of the whole vehicle and the performance of the tire and support the technical development of the tire becomes a technical problem to be solved urgently.

In order to solve the above-mentioned problems, an embodiment of the present application provides a method for determining a performance association between a tire and a whole vehicle, where a determining device obtains a tire simulation model and a whole vehicle simulation model, and the tire simulation model includes: the whole vehicle simulation model comprises a plurality of tire performance indexes: a plurality of whole car performance indexes. The determining device determines a performance function corresponding to the tire simulation model based on the tire simulation model, wherein the performance function comprises a plurality of coefficients to be adjusted. The determining device determines at least one target coefficient from a plurality of coefficients to be adjusted, wherein the target coefficient is the coefficient to be adjusted, and the influence degree of the coefficient to be adjusted on the tire performance index is larger than a preset influence degree threshold value. The determining device determines a first association relation based on the tire simulation model and the whole vehicle simulation model, wherein the first association relation is used for indicating the association between the whole vehicle simulation model and the tire simulation model. The determining device adjusts the tire simulation model and the whole vehicle simulation model based on each target coefficient and the first association relation, and determines a plurality of groups of performance change information, wherein one group of performance change information comprises: the change amount of each tire performance index and the change amount of each whole vehicle performance index, and one group of performance change information corresponds to one target coefficient. The determining device determines a second association relationship based on the plurality of groups of performance change information, wherein the second association relationship is used for indicating the influence degree of the tire performance index on the whole vehicle performance index. In this way, the whole vehicle factory can put forward the tire requirement based on the influence degree of the tire performance index on the whole vehicle performance index, thereby reducing the negative influence of the tire performance index on the whole vehicle performance index. The method can directly put forward the monomer performance requirement on the tire layer surface for the tire, and has important significance for the vehicle manufacturing of the whole vehicle factory.

It should be noted that, the execution subject of the method for determining the relevance between the tire and the whole vehicle performance provided by the application may be a device for determining the relevance between the tire and the whole vehicle performance, and the device may be a server (or an electronic device). Meanwhile, the determining device can also be a central processing unit (Central Processing Unit, CPU) of the server, or a determining module used for determining the relevance of the tire and the whole vehicle performance in the server. In the embodiment of the application, a method for determining the performance relevance of the tire and the whole vehicle, which is provided by the embodiment of the application, is described by taking a method for determining the performance relevance of the tire and the whole vehicle by a server as an example.

The server is one kind of computer and has the features of fast running speed and high load. The server provides computing or application services to other devices in the network. The server has high-speed CPU operation capability, long-time reliable operation, strong input/output external data throughput capability and better expansibility.

The server may be a single physical server, or may be a server cluster including a plurality of servers. Alternatively, the server cluster may also be a distributed cluster. Alternatively, the server may be a cloud server. The embodiment of the application does not limit the specific implementation mode of the server.

For easy understanding, the method for determining the relevance between the tire and the whole vehicle performance provided by the application is specifically described below with reference to the accompanying drawings.

FIG. 1 is a flowchart illustrating a method of determining a tire to vehicle performance relationship, according to an exemplary embodiment, as shown in FIG. 1, comprising the steps of:

s101, a server acquires a tire simulation model and a whole vehicle simulation model.

Wherein, the tire simulation model includes: the whole vehicle simulation model comprises a plurality of tire performance indexes: a plurality of whole car performance indexes.

It should be noted that, the embodiment of the present application is not limited to the type of the tire simulation model. For example, the tire simulation model may be an empirical model (PAC tire model), a magic formula tire model (MF-type tire model), a semi-empirical tire model (MF-Swift tire model), or the like.

In an embodiment of the present application, the tire performance index may include at least one of: cornering stiffness coefficient, aligning stiffness coefficient, tire drag distance, load sensitivity, load transfer sensitivity, and lateral attachment coefficient.

In one possible design, the server may determine the cornering stiffness coefficient based on equation one:

Wherein F is used for representing a lateral force building capacity function, the corresponding performance index of F is a cornering stiffness coefficient, the unit of the cornering stiffness coefficient is dimensionless, alpha is used for representing a cornering angle, fy is used for representing a tire lateral force, and Fz is used for representing a tire vertical load.

In one possible design, the server may determine the correction stiffness coefficient based on equation two:

the method comprises the steps of setting up a capacity function for representing the aligning moment, wherein the performance index corresponding to the AT is an aligning rigidity coefficient, the unit of the aligning rigidity coefficient is mm, and Mz is used for representing the tire aligning moment.

In one possible design, the server may determine the tire drag distance based on equation three:

wherein PT is used for representing a tire trailing distance function, the performance index corresponding to PT is the tire trailing distance, and the unit of the tire trailing distance is mm.

In one possible design, the server may determine the load sensitivity based on equation four:

wherein, H is used for representing a load sensitivity function, the performance index corresponding to H is load sensitivity, and the unit of load sensitivity has no dimension.

In one possible design, the server may determine the load transfer sensitivity based on equation five:

wherein G is used for representing a load transfer sensitivity function, and the performance index corresponding to G is load transfer sensitivity, and the unit of the load transfer sensitivity is dimensionless.

In one possible design, the server may determine the lateral attachment coefficient based on equation six:

wherein MUY is used for representing a lateral adhesion function, and the performance index corresponding to MUY is a lateral adhesion coefficient, and the unit of the lateral adhesion coefficient is dimensionless.

It should be noted that, the embodiment of the application does not limit the type of the whole vehicle simulation model. For example, the whole vehicle simulation model may be a mechanical system dynamics automatic analysis (Automatic Dynamic Analysis of Mechanical System, adams) model, a vehicle model (Carsim model), a whole vehicle model (Simulink model), or the like.

In the embodiment of the application, the performance index of the whole vehicle can comprise at least one of the following: understeer, front axle side compliance, rear axle side compliance, maximum lateral acceleration, body roll gradient, yaw rate gain, yaw rate 45 degree phase lag, yaw rate response time, steering sensitivity, steering wheel angle dead zone, steering torsional stiffness.

S102, the server determines a performance function corresponding to the tire simulation model based on the tire simulation model.

In one possible implementation, the server may perform a six-component test on the tire simulation model to obtain a tire mechanical test curve. And then, the server can adjust the coefficient of the magic formula based on the tire mechanics test curve to obtain the adjusted magic formula. The similarity between the function curve of the regulated magic formula and the tire mechanical test curve is greater than a preset similarity threshold, and the regulated magic formula is a performance function.

It should be noted that, the server adjusts the coefficient of the magic formula based on the tire mechanics test curve, and changes the mathematical curve expressed by the magic formula, where the change of the mathematical curve is represented by a change of the curve shape, and the change of the curve shape includes at least one of the following: linear segment slope, peak point height, curve curvature, etc.

S103, the server determines at least one target coefficient from a plurality of coefficients to be adjusted.

The target coefficient is a coefficient to be adjusted, wherein the influence degree of the coefficient to be adjusted on the tire performance index is larger than a preset influence degree threshold value.

In the embodiment of the application, the influence degree of the coefficient to be adjusted on the tire performance index refers to the influence degree of the coefficient to be adjusted on the variation of the tire performance index after the change.

In one possible implementation, the server performs a target operation on each coefficient to be adjusted, determining at least one target coefficient from a plurality of coefficients to be adjusted. The target operations include: the server updates the tire simulation model based on the coefficient to be adjusted to obtain an updated tire simulation model, wherein the updated tire simulation model comprises: a plurality of updated tire performance indicators. The server may then compare each updated tire performance index to a preset tire performance interval corresponding to the tire performance index. And if each updated tire performance index is in the preset tire performance interval corresponding to the tire performance index, the server takes the coefficient to be adjusted as a target coefficient. If the updated tire performance index is not in the preset tire performance interval corresponding to the tire performance index, the server does not take the coefficient to be adjusted as the target coefficient.

Illustratively, as shown in table 1, the coefficients to be adjusted are shown.

TABLE 1

As can be seen from table 1, the coefficient name "LKY" is the coefficient to be adjusted, the original value of "LKY" is 1.0, and "$ Scale factor of Fy cornering stiffness" is an illustration of "LKY". The coefficient name "LMUY" is a coefficient to be adjusted, the original value of "LMUY" is 1.0, "$ Scale factor of Fy peak friction coefficient" is an explanation of "LMUY". For the description of other coefficients to be adjusted, reference may be made to the descriptions of the coefficients "LKY" and "LMUY", which are not repeated here.

Exemplary, provided that the tire performance indicators include: cornering stiffness coefficient, aligning stiffness coefficient, tire drag distance, load sensitivity, load transfer sensitivity, and lateral attachment coefficient. The preset performance interval of the cornering stiffness coefficient is 0.15-0.50, the preset performance interval of the correcting stiffness coefficient is 2.0-18.0, the preset performance interval of the tire dragging distance is 10.0-60.0, the preset performance interval of the load sensitivity is 0.05-0.40, the preset performance interval of the load transfer sensitivity is 0.05-0.50, and the preset performance interval of the lateral attachment coefficient is 0.8-1.3.

If the server updates the coefficient to be adjusted LKY, and the updated cornering stiffness coefficient has a value of 0.25, the aligning stiffness coefficient has a value of 10.0, the tire dragging distance has a value of 25.0, the load sensitivity has a value of 0.25, the load transfer sensitivity has a value of 0.20, and the lateral adhesion coefficient has a value of 1.0, then each updated tire performance index is within the preset tire performance interval corresponding to the tire performance index, and the server takes the coefficient to be adjusted LKY as the target coefficient.

If the server updates the coefficient to be adjusted LKY, and the updated cornering stiffness coefficient has a value of 0.60, the aligning stiffness coefficient has a value of 20.0, the tire dragging distance has a value of 25.0, the load sensitivity has a value of 0.50, the load transfer sensitivity has a value of 0.25, and the lateral adhesion coefficient has a value of 1.0, then the server does not use the coefficient to be adjusted LKY as the target coefficient if the updated tire performance index is not within the preset tire performance interval corresponding to the tire performance index.

In one possible design, the server determines the amount of change in each tire performance index based on each updated tire performance index and each pre-updated tire performance index before the server takes the coefficient to be adjusted as the target coefficient. Then, the server compares the variation amounts of the plurality of tire performance indexes with preset tire performance variation thresholds corresponding to the tire performance indexes.

If the first target variable quantity exists in the variable quantities of the tire performance indexes, the server takes the coefficient to be adjusted as a target coefficient, and the first target variable quantity is that the variable quantity of the tire performance indexes is larger than a preset tire performance change threshold value corresponding to the tire performance indexes.

If the variation amounts of the tire performance indexes are all second target variation amounts, the server does not take the coefficient to be adjusted as the target coefficient, and the second target variation amounts are the variation amounts of the tire performance indexes which are smaller than the preset tire performance variation threshold value corresponding to the tire performance indexes

Exemplary, provided that the tire performance indicators include: cornering stiffness coefficient, aligning stiffness coefficient, tire drag distance, load sensitivity, load transfer sensitivity, and lateral attachment coefficient. The initial value of the cornering stiffness coefficient was 0.25, the initial value of the aligning stiffness coefficient was 10.0, the preset initial value of the tire drag distance was 25.0, the initial value of the load sensitivity was 0.25, the initial value of the load transfer sensitivity was 0.20, and the initial value of the lateral adhesion coefficient was 1.0. The preset change threshold of the cornering stiffness coefficient is 0.001, the preset change threshold of the aligning stiffness coefficient is 0.1, the preset change threshold of the tire trailing distance is 0.1, the preset change threshold of the load sensitivity is 0.001, the preset change threshold of the load transfer sensitivity is 0.001, and the preset change threshold of the lateral adhesion coefficient is 0.01.

If the server updates the coefficient to be adjusted LKY, the initial value of the updated cornering stiffness coefficient is 0.35, the initial value of the correcting stiffness coefficient is 15.0, the preset initial value of the tire trailing distance is 25.0, the initial value of the load sensitivity is 0.30, the initial value of the load transfer sensitivity is 0.20, and the initial value of the lateral attachment coefficient is 1.0. The variation of the cornering stiffness coefficient is 0.10, the variation of the aligning stiffness coefficient is 5.0, the variation of the tire trailing distance is 0.0, the variation of the load sensitivity is 0.05, the variation of the load transfer sensitivity is 0.0, and the variation of the lateral adhesion coefficient is 0.0. And the variation of the cornering stiffness coefficient is larger than the preset variation threshold of the cornering stiffness coefficient, and the server takes the coefficient LKY to be adjusted as a target coefficient.

If the server updates the coefficient to be adjusted LKY, the initial value of the updated cornering stiffness coefficient is 0.2505, the initial value of the correcting stiffness coefficient is 10.0, the preset initial value of the tire trailing distance is 25.0, the initial value of the load sensitivity is 0.25, the initial value of the load transfer sensitivity is 0.2005, and the initial value of the lateral adhesion coefficient is 1.0. The variation in cornering stiffness coefficient is 0.0, the variation in aligning stiffness coefficient is 0.0, the variation in tire trailing distance is 0.0005, the variation in load sensitivity is 0.0005, the variation in load transfer sensitivity is 0.0, and the variation in lateral adhesion coefficient is 0.0. The variation of the tire performance index is smaller than the preset variation threshold of the cornering stiffness coefficient, and the server does not take the coefficient LKY to be adjusted as the target coefficient.

S104, the server determines a first association relation based on the tire simulation model and the whole vehicle simulation model.

The first association relationship is used for indicating the association between the whole vehicle simulation model and the tire simulation model.

In one possible implementation, the server may establish an association between the complete vehicle simulation model and the tire simulation model based on the tire simulation model and the complete vehicle simulation model.

In the embodiment of the application, after the association relation between the whole vehicle simulation model and the tire simulation model is established, the tire simulation model and the whole vehicle simulation model are updated when the server adjusts the target coefficient.

For example, as shown in fig. 2, the server may perform association mapping on a tire simulation model based on the PAC tire model and a vehicle simulation model based on the PAC tire model, and establish an association between the tire simulation model and the vehicle simulation model.

S105, the server respectively adjusts the tire simulation model and the whole vehicle simulation model based on each target coefficient and the first association relation, and determines multiple groups of performance change information.

Wherein the set of performance change information includes: the change amount of each tire performance index and the change amount of each whole vehicle performance index, and one group of performance change information corresponds to one target coefficient.

Illustratively, if the server updates the target coefficients LKY, a set of performance change information is obtained, including: variation of each tire performance index: the variation of the cornering stiffness coefficient is 0.10, the variation of the aligning stiffness coefficient is 5.0, the variation of the tire trailing distance is 0.0, the variation of the load sensitivity is 0.05, the variation of the load transfer sensitivity is 0.0, and the variation of the lateral adhesion coefficient is 0.0. The variation of each whole vehicle performance index: the amount of change in the understeer degree is-0.05, the amount of change in the front-axle side compliance is-0.15, the amount of change in the rear-axle side compliance is-0.10, the amount of change in the maximum lateral acceleration is 0.0, the amount of change in the vehicle body roll gradient is 0.0, the amount of change in the maximum lateral acceleration is 0.0, the amount of change in the yaw rate gain is 2.5, the amount of change in the yaw rate 45-degree phase lag is 0.15, the amount of change in the yaw rate response time is-0.05, the amount of change in the steering sensitivity is 0.15, the amount of change in the steering wheel angle dead zone is-0.5, and the amount of change in the steering torsional rigidity is 0.008. The above-described change information corresponds to the target coefficient LKY.

Illustratively, if the server updates the target coefficient LMUY, a set of performance change information is obtained, including: variation of each tire performance index: the variation of the cornering stiffness coefficient is 0.0, the variation of the aligning stiffness coefficient is 0.0, the variation of the tire trailing distance is 0.0, the variation of the load sensitivity is 0.0, the variation of the load transfer sensitivity is 0.0, and the variation of the lateral adhesion coefficient is 0.1. The variation of each whole vehicle performance index: the amount of change in the understeer degree is 0.0, the amount of change in the front-axle side compliance is 0.0, the amount of change in the rear-axle side compliance is 0.0, the amount of change in the maximum lateral acceleration is 0.0, the amount of change in the vehicle body roll gradient is 0.0, the amount of change in the maximum lateral acceleration is 0.08, the amount of change in the yaw rate gain is 0.0, the amount of change in the yaw rate 45-degree phase lag is 0.0, the amount of change in the yaw rate response time is 0.0, the amount of change in the steering sensitivity is 0.0, the amount of change in the steering wheel angle dead zone is 0.0, and the amount of change in the steering torsional rigidity is 0.0. The above-mentioned change information corresponds to the target coefficient LMUY.

For the description of the other performance change information, reference may be made to the description of the target coefficient LKY and a corresponding set of performance change information and the target coefficient LMUY and a corresponding set of performance change information, which are not described herein.

S106, the server determines a second association relation based on the plurality of groups of performance change information.

The second association relationship is used for indicating the influence degree of the tire performance index on the whole vehicle performance index.

In one possible design, the degree to which the tire performance index affects the overall vehicle performance index includes: positive correlation, negative correlation, coupled influence, no correlation.

Wherein, the influence degree of the tire performance index on the whole vehicle performance index is positive correlation, which means that the tire performance index is increased and the whole vehicle performance index is increased; the performance index of the tire is reduced, and the performance index of the whole vehicle is reduced. The influence degree of the tire performance index on the whole vehicle performance index is in negative correlation, which means that the tire performance index is increased and the whole vehicle performance index is reduced; the performance index of the tire is reduced, and the performance index of the whole vehicle is increased. The influence degree of the tire performance index on the whole vehicle performance index is influenced by coupling, which means that the influence of the tire performance on the whole vehicle performance is influenced by the relative position between the tire and the whole vehicle, the linking structure between the tire and the whole vehicle, and the like. The fact that the influence degree of the tire performance index on the whole vehicle performance index is irrelevant means that the tire performance index is changed and the whole vehicle performance index is unchanged.

Illustratively, as shown in table 2, it shows the association relationship between the tire performance index and the overall vehicle performance index.

TABLE 2

For example, as shown in table 2, if the correlation value between the cornering stiffness coefficient in the tire performance index and the natural yaw rate frequency in the vehicle performance index is 1, it indicates that the influence degree of the cornering stiffness coefficient on the natural yaw rate frequency is positive correlation.

For example, as shown in table 2, if the correlation value between the cornering stiffness coefficient in the tire performance index and the linear segment understeer degree in the vehicle performance index is 2, it indicates that the influence degree of the cornering stiffness coefficient on the linear segment understeer degree is inversely correlated.

For example, as shown in table 2, if the correlation value between the aligning stiffness coefficient in the tire performance index and the linear segment understeer degree in the vehicle performance index is 3, the influence degree of the aligning stiffness coefficient on the linear segment understeer degree is the coupled influence.

For example, as shown in table 2, if the correlation value between the cornering stiffness coefficient in the tire performance index and the maximum lateral acceleration in the vehicle performance index is 0, it indicates that the influence degree of the cornering stiffness coefficient on the maximum lateral acceleration is irrelevant.

Optionally, the degree of influence of the tire performance index on the overall vehicle performance index further includes: the grade is affected. Wherein the impact level is positively correlated with the degree of impact.

That is, the greater the impact level, the greater the degree to which the tire performance index affects the overall vehicle performance index. The smaller the impact level, the lower the degree to which the tire performance index affects the overall vehicle performance index.

For example, the correlation values of the cornering stiffness coefficient in the tire performance index and the yaw rate natural frequency 45-degree phase lag in the whole vehicle performance index are all 1. If the yaw rate coefficient of stiffness is increased from 0.20 to 0.30, the yaw rate natural frequency is increased from 1.3 to 1.35, and the yaw rate natural frequency 45 degree phase lag is increased from 1.4 to 1.6. It means that the yaw rate coefficient has a greater influence level on the yaw rate natural frequency 45-degree phase lag than on the yaw rate natural frequency.

In another possible design, the degree of influence of the tire performance index on the overall vehicle performance index refers to the influence of the tire performance index on the number of the overall vehicle performance indexes.

In the embodiment of the application, as shown in table 2, the cornering stiffness coefficient in the tire performance index has an effect on the performance indexes such as insufficient steering degree, cornering compliance of front axle, cornering compliance of rear axle, natural frequency of yaw rate, 45-degree phase lag of the natural frequency of yaw rate, maximum lateral acceleration, roll gradient of vehicle body, yaw rate response time, yaw rate overshoot, yaw rate gain of central zone, steering sensitivity, torsional stiffness and the like, and the influence degree of the cornering stiffness coefficient on the overall vehicle performance index is 0-10.

In one possible design, the second association may be represented by a matrix.

It can be understood that the server obtains a tire simulation model and a whole vehicle simulation model, and the tire simulation model comprises: the whole vehicle simulation model comprises a plurality of tire performance indexes: a plurality of whole car performance indexes. Then, the server can determine a performance function corresponding to the tire simulation model based on the tire simulation model, wherein the performance function comprises a plurality of coefficients to be adjusted, and at least one target coefficient is determined from the coefficients to be adjusted, and the target coefficient is the coefficient to be adjusted, wherein the influence degree of the coefficient to be adjusted on the tire performance index is greater than a preset influence degree threshold value. In this way, the coefficient of which the degree of correlation between the portion and the tire performance index is low can be reduced. Then, the server determines the relevance between the whole vehicle simulation model and the tire simulation model based on the tire simulation model and the whole vehicle simulation model, adjusts the tire simulation model and the whole vehicle simulation model based on the relevance relation of each target coefficient, and determines a plurality of groups of performance change information, wherein one group of performance change information comprises: the change amount of each tire performance index and the change amount of each whole vehicle performance index, and one group of performance change information corresponds to one target coefficient. Thus, the server can determine the variation of the tire performance index and the variation of the overall vehicle performance index under the condition that the same coefficient is changed. Then, the server can determine the influence degree of the tire performance index on the whole vehicle performance index based on the plurality of groups of performance change information, namely, the influence on the whole vehicle performance index after the tire performance index is changed. Thus, the server can acquire the tire simulation model and the whole vehicle simulation model, and determine the target coefficient based on the tire simulation model. And then, the server establishes the association between the whole vehicle simulation model and the tire simulation model, adjusts the whole vehicle simulation model and the tire simulation model based on each target coefficient and the relation between the whole vehicle simulation model and the tire simulation model, and determines multiple groups of performance change information. And finally, the server determines the influence degree of the tire performance index on the whole vehicle performance index based on the plurality of groups of performance change information. In this way, a relationship between the tire performance index and the overall vehicle performance index can be established. Moreover, by adopting the technical scheme of the application, the whole vehicle factory can put forward the tire requirement based on the influence degree of the tire performance index on the whole vehicle performance index, thereby reducing the negative influence of the tire performance index on the whole vehicle performance index. The method can directly put forward the monomer performance requirement on the tire layer surface for the tire, and has important significance for the vehicle manufacturing of the whole vehicle factory.

Embodiments of the present application are described below with reference to specific examples. By way of example, as shown in figure 3,

the server acquires performance indexes of the whole vehicle model, the tire model and the tire model. And then the server performs debugging analysis on the coefficient to be adjusted of the tire model to determine a target coefficient. Further, the server establishes an association relationship between the tire model and the whole vehicle model. And finally, the server analyzes the relevance between the whole vehicle performance and the tire performance.

The foregoing description of the solution provided by the embodiments of the present application has been mainly presented in terms of a method. In order to realize the functions, the device or the electronic equipment for determining the relevance of the tire and the whole vehicle performance comprises a hardware structure and/or a software module for executing the functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

According to the method, the functional modules of the device or the electronic device for determining the performance relevance between the tire and the whole vehicle can be divided, for example, the device or the electronic device for determining the performance relevance between the tire and the whole vehicle can comprise each functional module corresponding to each functional division, and two or more functions can be integrated in one processing module. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, in the embodiment of the present application, the division of the modules is schematic, which is merely a logic function division, and other division manners may be implemented in actual implementation.

Fig. 4 is a block diagram illustrating a tire and vehicle performance association determination apparatus according to an exemplary embodiment. Referring to fig. 4, the device for determining the performance relevance between the tire and the whole vehicle comprises: an acquisition unit 401 and a processing unit 402.

An obtaining unit 401, configured to obtain a tire simulation model and a whole vehicle simulation model, where the tire simulation model includes: the whole vehicle simulation model comprises a plurality of tire performance indexes: a plurality of whole car performance indexes. The processing unit 402 is configured to determine, based on the tire simulation model, a performance function corresponding to the tire simulation model, where the performance function includes a plurality of coefficients to be adjusted. The processing unit 402 is further configured to determine at least one target coefficient from a plurality of coefficients to be adjusted, where the target coefficient is a coefficient to be adjusted whose influence degree of the coefficient to be adjusted on the tire performance index is greater than a preset influence degree threshold. The processing unit 402 is further configured to determine a first association relationship based on the tire simulation model and the whole vehicle simulation model, where the first association relationship is used to indicate an association between the whole vehicle simulation model and the tire simulation model. The processing unit 402 is further configured to adjust the tire simulation model and the vehicle simulation model based on each target coefficient and the first association relationship, and determine a plurality of sets of performance change information, where a set of performance change information includes: the change amount of each tire performance index and the change amount of each whole vehicle performance index, and one group of performance change information corresponds to one target coefficient. The processing unit 402 is further configured to determine a second association relationship based on the multiple sets of performance variation information, where the second association relationship is used to indicate a degree of influence of the tire performance index on the overall vehicle performance index.

In one possible design, the processing unit 402 is further configured to perform a target operation on each coefficient to be adjusted, and determine at least one target coefficient from the plurality of coefficients to be adjusted. The target operations include: the processing unit 402 updates the tire simulation model based on the coefficient to be adjusted, to obtain an updated tire simulation model, the updated tire simulation model including: a plurality of updated tire performance indicators. If each updated tire performance index is within the preset tire performance interval corresponding to the tire performance index, the processing unit 402 takes the coefficient to be adjusted as the target coefficient.

In another possible design, the processing unit 402 is further configured to determine an amount of change in each tire performance index based on each updated tire performance index and each pre-updated tire performance index. The processing unit 402 regards the coefficient to be adjusted as a target coefficient, including: if there is a target variation among the variation amounts of the tire performance indexes, the processing unit 402 uses the coefficient to be adjusted as the target coefficient, where the target variation is that the variation amount of the tire performance index is greater than the preset tire performance variation threshold corresponding to the tire performance index.

In another possible design, the processing unit 402 is further configured to perform a six-component test on the tire simulation model to obtain a tire mechanical test curve. The processing unit 402 adjusts the coefficient of the magic formula based on the tire mechanical test curve to obtain an adjusted magic formula, where the similarity between the function curve of the adjusted magic formula and the tire mechanical test curve is greater than a preset similarity threshold, and the adjusted magic formula is a performance function.

According to the above apparatus, the acquisition unit 401 may acquire the tire simulation model and the entire vehicle simulation model, and determine the target coefficient based on the tire simulation model. Thereafter, the processing unit 402 establishes a relationship between the entire vehicle simulation model and the tire simulation model, and adjusts the entire vehicle simulation model and the tire simulation model based on each target coefficient and the relationship between the entire vehicle simulation model and the tire simulation model, to determine a plurality of sets of performance change information. Finally, the processing unit 402 determines the degree of impact of the tire performance index on the overall vehicle performance index based on the sets of performance change information. In this way, a relationship between the tire performance index and the overall vehicle performance index can be established. And, moreover, the method comprises the steps of. The whole automobile factory can directly put forward the monomer performance requirement on the tire layer surface to the tire, and has important significance to the automobile manufacturing of the whole automobile factory.

The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.

Fig. 5 is a schematic hardware configuration diagram of a device for determining the relationship between a tire and the performance of the whole vehicle according to an exemplary embodiment. The device for determining the relevance of the tire and the whole vehicle performance can comprise a processor 502, wherein the processor 502 is used for executing application program codes, so that the method for determining the relevance of the tire and the whole vehicle performance is realized.

The processor 502 may be a CPU, microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of programs in accordance with aspects of the present application.

As shown in fig. 5, the device for determining the association of the tire with the performance of the whole vehicle may further include a memory 503. Wherein the memory 503 is used for storing application codes for executing the inventive arrangements and is controlled by the processor 502 for execution.

The memory 503 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (random access memory, RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (electrically erasable programmable read-only memory, EEPROM), a compact disc (compact disc read-only memory) or other optical disk storage, optical disk storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory 503 may be separate and coupled to the processor 502 via a bus 504. Memory 503 may also be integrated with processor 502.

As shown in fig. 5, the device for determining the association of the tire and the performance of the whole vehicle may further comprise a communication interface 501, wherein the communication interface 501, the processor 502 and the memory 503 may be coupled to each other, for example, via a bus 504. The communication interface 501 is used for performing information interaction with other devices, for example, supporting information interaction between a determining device for the performance association of a tire and a whole vehicle and other devices.

It should be noted that the apparatus structure shown in fig. 5 does not constitute a limitation to the determination means of the tire-to-vehicle performance association, and the determination means of the tire-to-vehicle performance association may include more or less components than those shown in fig. 5, or may combine some components, or may be arranged with different components.

In actual implementation, the functions implemented by processing unit 402 may be implemented by processor 502, shown in fig. 5, invoking program code in memory 503.

The present application also provides a computer readable storage medium having instructions stored thereon, which when executed by a processor of a computer device, enable the computer to perform the method for determining the tire and vehicle performance correlation provided by the above-described embodiments. For example, the computer readable storage medium may be a memory 503 comprising instructions executable by the processor 502 of the computer device to perform the above-described method. Alternatively, the computer readable storage medium may be a non-transitory computer readable storage medium, for example, a ROM, RAM, CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

Fig. 6 schematically illustrates a conceptual partial view of a computer program product provided by an embodiment of the application, the computer program product comprising a computer program for executing a computer process on a computing device.

In one embodiment, a computer program product is provided using signal bearing medium 600. The signal bearing medium 600 may include one or more program instructions that when executed by one or more processors may provide the functionality or portions of the functionality described above with respect to fig. 2, 3. Thus, for example, referring to the embodiment shown in FIG. 2, one or more features of S101-S106 may be carried by one or more instructions associated with signal bearing medium 600. Further, the program instructions in fig. 6 also describe example instructions.

In some examples, signal bearing medium 600 may comprise a computer readable medium 601 such as, but not limited to, a hard disk drive, compact Disk (CD), digital Video Disk (DVD), digital tape, memory, read-only memory (ROM), or random access memory (random access memory, RAM), among others.

In some implementations, the signal bearing medium 600 may comprise a computer recordable medium 602 such as, but not limited to, memory, read/write (R/W) CD, R/W DVD, and the like.

In some implementations, the signal bearing medium 600 may include a communication medium 603 such as, but not limited to, a digital and/or analog communication medium (e.g., fiber optic cable, waveguide, wired communications link, wireless communications link, etc.).

The signal bearing medium 600 may be conveyed by a communication medium 603 in wireless form. The one or more program instructions may be, for example, computer-executable instructions or logic-implemented instructions.

In some examples, a determining device such as the tire and vehicle performance association described with respect to fig. 4 may be configured to provide various operations, functions, or actions in response to program instructions through one or more of the computer readable medium 601, the computer recordable medium 602, and/or the communication medium 603.

It will be apparent to those skilled in the art from this description that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules, so as to perform all the above-described classification or part of the functions.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and the units shown as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. The purpose of the embodiment scheme can be achieved by selecting part or all of the classification part units according to actual needs.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present application, or the portion contributing to the prior art or the whole classification portion or portion of the technical solution, may be embodied in the form of a software product stored in a storage medium, where the software product includes several instructions to cause a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to execute the whole classification portion or part of the steps of the method of the embodiments of the present application. The storage medium includes a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc. which can store the program codes.

The present application is not limited to the above embodiments, and any changes or substitutions within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims

1. A method for determining the performance relevance of a tire to a finished vehicle, the method comprising:

Obtaining a tire simulation model and a whole vehicle simulation model, wherein the tire simulation model comprises: the whole vehicle simulation model comprises a plurality of tire performance indexes, wherein the whole vehicle simulation model comprises: a plurality of overall vehicle performance indicators;

determining a performance function corresponding to the tire simulation model based on the tire simulation model, wherein the performance function comprises a plurality of coefficients to be adjusted;

determining at least one target coefficient from the plurality of coefficients to be adjusted, wherein the target coefficient is the coefficient to be adjusted, and the influence degree of the coefficient to be adjusted on the tire performance index is greater than a preset influence degree threshold value;

determining a first association relationship based on the tire simulation model and the whole vehicle simulation model, wherein the first association relationship is used for indicating the association between the whole vehicle simulation model and the tire simulation model;

based on each target coefficient and the first association relation, respectively adjusting the tire simulation model and the whole vehicle simulation model, and determining multiple groups of performance change information, wherein one group of performance change information comprises: the variation of each tire performance index and the variation of each whole vehicle performance index correspond to one target coefficient in one group of performance variation information;

And determining a second association relation based on the plurality of groups of performance change information, wherein the second association relation is used for indicating the influence degree of the tire performance index on the whole vehicle performance index.

2. The method of claim 1, wherein said determining at least one target coefficient from said plurality of coefficients to be adjusted comprises:

performing target operation on each coefficient to be adjusted, and determining at least one target coefficient from the plurality of coefficients to be adjusted; the target operation includes:

updating the tire simulation model based on the coefficient to be adjusted to obtain an updated tire simulation model, wherein the updated tire simulation model comprises: a plurality of updated tire performance indicators;

and if each updated tire performance index is in a preset tire performance interval corresponding to the tire performance index, taking the coefficient to be adjusted as the target coefficient.

3. The method according to claim 2, characterized in that before taking the coefficient to be adjusted as the target coefficient, the method further comprises:

determining the variation of each tire performance index according to each updated tire performance index and each tire performance index before updating;

Taking the coefficient to be adjusted as the target coefficient comprises the following steps:

and if the target variable quantity exists in the variable quantities of the tire performance indexes, taking the coefficient to be adjusted as the target coefficient, wherein the target variable quantity is that the variable quantity of the tire performance indexes is larger than a preset tire performance change threshold value corresponding to the tire performance indexes.

4. A method according to any one of claims 1-3, wherein said determining a performance function corresponding to said tire simulation model based on said tire simulation model comprises:

performing six-component force test on the tire simulation model to obtain a tire mechanical test curve;

and adjusting the coefficient of the magic formula based on the tire mechanical test curve to obtain an adjusted magic formula, wherein the similarity between the function curve of the adjusted magic formula and the tire mechanical test curve is greater than a preset similarity threshold, and the adjusted magic formula is the performance function.

5. A device for determining the performance relevance of a tyre to a whole vehicle, the device comprising:

the acquisition unit is used for acquiring a tire simulation model and a whole vehicle simulation model, and the tire simulation model comprises: the whole vehicle simulation model comprises a plurality of tire performance indexes, wherein the whole vehicle simulation model comprises: a plurality of overall vehicle performance indicators;

The processing unit is used for determining a performance function corresponding to the tire simulation model based on the tire simulation model, wherein the performance function comprises a plurality of coefficients to be adjusted;

the processing unit is further used for determining at least one target coefficient from the plurality of coefficients to be adjusted, wherein the target coefficient is the coefficient to be adjusted, and the influence degree of the coefficient to be adjusted on the tire performance index is greater than a preset influence degree threshold value;

the processing unit is further used for determining a first association relation based on the tire simulation model and the whole vehicle simulation model, wherein the first association relation is used for indicating the association between the whole vehicle simulation model and the tire simulation model;

the processing unit is further configured to adjust the tire simulation model and the whole vehicle simulation model based on each target coefficient and the first association relationship, and determine multiple sets of performance change information, where a set of performance change information includes: the variation of each tire performance index and the variation of each whole vehicle performance index, and one group of performance variation information corresponds to one target coefficient;

the processing unit is further used for determining a second association relation based on the plurality of groups of performance change information, and the second association relation is used for indicating the influence degree of the tire performance index on the whole vehicle performance index.

6. The apparatus of claim 5, wherein the device comprises a plurality of sensors,

the processing unit is used for executing target operation on each coefficient to be adjusted and determining at least one target coefficient from the coefficients to be adjusted; the target operation includes:

7. The apparatus of claim 5, wherein the device comprises a plurality of sensors,

the processing unit is used for determining the variation of each tire performance index according to each updated tire performance index and each tire performance index before updating;

the processing unit, configured to take the coefficient to be adjusted as the target coefficient, includes:

8. The device according to any one of claims 5 to 7, wherein,

the processing unit is used for carrying out six-component force test on the tire simulation model to obtain a tire mechanical test curve;

the processing unit is used for adjusting the coefficient of the magic formula based on the tire mechanical test curve to obtain an adjusted magic formula, the similarity between the function curve of the adjusted magic formula and the tire mechanical test curve is greater than a preset similarity threshold, and the adjusted magic formula is the performance function.

9. An electronic device, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the method of any one of claims 1 to 4.

10. A computer readable storage medium, characterized in that, when computer-executable instructions stored in the computer readable storage medium are executed by a processor of an electronic device, the electronic device is capable of performing the method of any one of claims 1 to 4.