A method, system and program product for rapid evaluation of tire braking performance

Abstract

The present invention relates to the technical field of tire simulation design, and particularly to a method, system and program product for rapidly evaluating the braking performance of tires. This method obtains the friction coefficient (μ-s curve) of the tire at different slip ratios through finite element simulation or multi-body dynamics simulation. Then, it is assumed that the slip ratio of the tire during the actual braking process follows a normal distribution, with the mean being the slip ratio corresponding to the maximum μ value in the μ-s curve and the standard deviation being 1. Next, the probability density function of the normal distribution is multiplied by the μ-s curve to obtain a weighted braking coefficient, and the integral is performed on it to calculate the comprehensive braking performance index of the tire μ effective 。 μ effective The larger the value, the better the braking performance of the tire. This method combines simulation technology with a statistical distribution model to achieve rapid and accurate evaluation of the braking performance of tires. The entire calculation process takes about 2 hours, which is significantly better than the more than 48 hours required for traditional explicit dynamics analysis

Description

Technical Field

[0001] The present invention relates to the technical field of tire simulation design, and particularly to a method, a system and a program product for rapidly evaluating the braking performance of a tire. Background Art

[0002] As an important indicator of vehicle safety, the braking performance of a tire has always been the focus of attention in the field of automotive engineering. At present, traditional methods for evaluating the braking performance of a tire mainly rely on on-vehicle tests. In actual tests, by testing the braking process of the tire on a test field, the relationship between the tire slip ratio and the braking force coefficient (μ-s curve) is obtained, and the braking ability of the tire is evaluated accordingly. Although this method can more intuitively reflect the performance of the tire under actual working conditions, due to the influence of various factors such as environmental conditions, test equipment, and road conditions during the test process, its test cost is high, the cycle is long, and the repeatability is poor.

[0003] With the rapid development of computer simulation technology, finite element simulation and multi-body dynamics simulation methods are increasingly widely used in the evaluation of tire performance. By constructing a finite element model or a multi-body dynamics model of the tire, simulation technology can simulate the braking force coefficient of the tire at different slip ratios in a relatively short time, thereby generating a μ-s curve, reducing the requirements for time and cost of on-vehicle tests. However, existing simulation evaluation methods mainly focus on the μ-s curve obtained by direct simulation, and do not fully consider the randomness of the tire slip ratio during the actual braking process.

[0004] In addition, with the increasing demand for high-performance tires, the applicant's previous Chinese patent applications for invention (such as Patent 2021116135564, Patent 2022100923567, and Patent 2022105620611) have also proposed several simulation analysis methods for tire performance. However, during the actual braking process, due to the influence of various factors such as driving operations and road surface conditions, the slip ratio of the tire usually exhibits certain statistical distribution characteristics, often approximately following a normal distribution. Traditional evaluation methods based on a single μ-s curve ignore this statistical characteristic, which may lead to a deviation between the evaluation result and the actual performance. Therefore, how to combine the statistical distribution characteristics of the slip ratio on the basis of simulation technology to achieve a more rapid and accurate evaluation of the braking performance of the tire has become a technical problem to be solved urgently. Summary of the Invention

[0005] In view of the problems of high test cost, long cycle and the evaluation method not fully considering the randomness of the slip rate in the prior art, the present invention proposes a rapid evaluation method for tire braking performance based on simulation and statistical distribution, aiming to combine the μ-s curve obtained by simulation with the normal distribution model of the slip rate, so as to realize the rapid and accurate evaluation of tire braking performance, reduce the test cost, and improve the reliability and practicability of the evaluation.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A rapid evaluation method for tire braking performance, comprising the following steps:

[0008] a) Simulate the braking coefficient of the tire at different slip rates through finite element simulation or multi-body dynamics simulation to obtain the μ-s curve;

[0009] b) Determine the normal distribution parameters of the slip rate according to the μ-s curve, where the normal distribution is set as N(a, σ²) , and the value of a is the slip rate value corresponding to the maximum friction coefficient μ-s on the μ curve, σ and take a preset value;

[0010] c) Multiply the normal distribution probability density function described in step (b) by the μ-s curve to calculate the weighted braking coefficient μ w ( s ), and its calculation formula is:

[0011] ,

[0012] where, μ is the friction coefficient ，s is the slip rate, μ ( s ) is the variation relationship of the friction coefficient with the slip rate;

[0013] d) Integrate or numerically accumulate the weighted braking coefficient μ w ( s ) within the preset integration range [c×a, d×a] to obtain the comprehensive braking performance index μ effective ;

[0014] e) Evaluate the braking performance of the tire according to the μ effective value to evaluate the braking performance of the tire, μ effectiveThe larger the value, the better the braking performance of the tire.

[0015] Preferably, the finite element simulation method used in the simulation in step (a) further includes establishing a finite element model of the tire structure and simulating the force conditions during the contact process between the tire and the road surface.

[0016] Preferably, the simulation in step (a) can also adopt a multi-body dynamics simulation method to obtain the μ-s curve.

[0017] Preferably, the normal distribution parameter σ is fixedly taken as 0.8 - 1.2, preferably 1, and the a value is the slip rate that makes the friction coefficient μ-s reach the maximum value obtained from the μ curve, preferably the a value is 12.0 - 15.0, and more preferably 13.0 - 14.0.

[0018] Preferably, in step (d), the integration of the weighted braking force coefficient μ w (s) adopts a numerical integration algorithm, μ effective and the calculation formula is:

[0019] .

[0020] Preferably, c = 0.6 - 0.9, d = 1.0 - 1.5; more preferably, c = 0.65 - 0.80, d = 1.10 - 1.30.

[0021] Furthermore, the present invention also discloses a system for quickly evaluating the braking performance of a tire, including:

[0022] a) A simulation module for generating the μ-s curve of the tire through finite element or multi-body dynamics simulation;

[0023] b) A statistical module for determining the slip rate normal distribution parameter according to the μ-s curve and generating a normal distribution probability density function;

[0024] c) A calculation module for multiplying the normal distribution probability density function by the μ-s curve to calculate the weighted braking force coefficient and integrating the weighted braking force coefficient within a preset integration range to obtain a comprehensive braking performance index μ effective ;

[0025] d) An evaluation module for evaluating the braking performance of the tire according to the μ effective value pairs.

[0026] Preferably, the simulation module includes a finite element analysis sub-module for establishing a tire finite element model and performing finite element simulation.

[0027] Preferably, the simulation module further includes a multi-body dynamics analysis sub-module for simulating and analyzing the dynamic response of the tire during braking.

[0028] Furthermore, the present invention also discloses a computer-readable storage medium storing a computer program or instruction, which, when executed by a processor, implements the method.

[0029] Furthermore, the present invention also discloses a computer program product including a computer program or instruction, which, when executed by a processor, implements the method.

[0030] Due to the adoption of the above technical solution, the present invention combines the μ-s curve of the tire obtained by finite element or multi-body dynamics simulation with the normal distribution model reflecting the statistical distribution characteristics of the slip rate during the actual braking process, realizing the rapid and accurate evaluation of the tire braking performance, and having the following technical effects:

[0031] 1. Significantly shorten the evaluation time: By using simulation technology to replace traditional real vehicle tests or explicit dynamics analysis, the method of the present invention can complete the evaluation of the tire braking performance within about 2 hours, greatly improving the evaluation efficiency compared with the analysis time of at least 48 hours of traditional methods.

[0032] 2. Reduce the test cost: The present invention uses a simulation platform for data acquisition and performance calculation, effectively avoiding the expensive real vehicle test equipment and site costs, thus reducing the overall test cost and reducing the repeated test overhead caused by changes in the environment and test conditions.

[0033] 3. Improve the evaluation accuracy: In the traditional evaluation method that only relies on the μ-s curve, the randomness and statistical characteristics of the tire slip rate during the actual braking process are not fully considered. However, the present invention introduces a normal distribution model to model the statistical characteristics of the slip rate and calculates the weighted braking force coefficient in combination with the probability density function, thus being closer to the actual working conditions and improving the accuracy and reliability of the braking performance evaluation.

[0034] 4. Enhance the adaptability to engineering applications: The simulation and statistical methods adopted by the present invention are not only applicable to the conventional evaluation of the tire braking performance, but also can be applied to the performance prediction and optimization under different working conditions, providing effective technical support for tire design, road surface adaptability analysis and vehicle safety evaluation.

[0035] 5. Facilitate system integration, promotion, and application: The disclosed technical solution can be implemented through software programs, has good compatibility with existing simulation platforms and vehicle engineering test systems, is convenient for promotion and application in actual engineering, and provides engineers with a simple-to-operate and fast-evaluating tire performance detection tool.

[0036] In summary, while significantly improving the evaluation speed and reducing costs, the present invention realizes a more accurate evaluation of tire braking performance by comprehensively considering the randomness of the slip rate during the actual braking process, and has significant application prospects and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a finite element model for simulation;

[0038] Figure 2 is the μ-s curve obtained by simulation;

[0039] Figure 3 is the a value obtained from the μ-s curve, a = 13.8272;

[0040] Figure 4 is the normal distribution curve with u = a = 13.8272 and σ = 1. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] Next, in combination with the embodiments of the present invention, the technical solutions in the embodiments will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0042] The following will describe in detail the method and system for rapid evaluation of tire braking performance based on simulation and statistical distribution of the present invention with reference to the accompanying drawings.

[0043] 1. Obtain the tire μ-s curve through simulation

[0044] First, obtain the braking coefficient (μ) data of the tire at different slip rates (s) through finite element analysis or multi-body dynamics simulation.

[0045] Step 1.1: Establish a tire finite element model or multi-body dynamics model.

[0046] As Figure 1 shown, by modeling the tire, simulate the internal structure, material properties of the tire, and the contact situation with the road surface. After the model is established, perform simulation calculations according to the preset working conditions (different braking pressures, road surface roughness, etc.).

[0047] Step 1.2: During the simulation process, set test points with different slip ratios, obtain the corresponding braking force coefficient values, and form the μ-s curve of the tire.

[0048] As Figure 2 shown, the simulation results output a series of corresponding relationship data, where the abscissa is the slip ratio s and the ordinate is the corresponding braking force coefficient μ.

[0049] 2. Establish a normal distribution model for the slip ratio

[0050] After obtaining the μ-s curve, establish a normal distribution model according to the statistical characteristics of the tire slip ratio during the actual braking process:

[0051] Step 2.1: Determine the normal distribution parameters.

[0052] Determine the mean a of the normal distribution according to the point where the friction coefficient μ reaches the maximum value in the μ-s curve. As Figure 3 shown, assume that the value of a is 13.8272.

[0053] Step 2.2: Set the standard deviation σ of the normal distribution. In the embodiment, σ is fixedly taken as 1. Thus, construct the normal distribution function:

[0054] ;

[0055] As Figure 4 shown, it shows the normal distribution curve with a = 13.8272 and σ = 1 as parameters.

[0056] 3. Calculate the weighted braking force coefficient

[0057] In order to fully consider the randomness of the slip ratio during the actual braking process, combine the μ-s curve obtained in Step 1 with the normal distribution probability density function established in Step 2 to calculate the weighted braking force coefficient μ w (s) :

[0058] Step 3.1: For each slip ratio s, the calculation formula for the corresponding weighted braking force coefficient is:

[0059] ;

[0060] Step 3.2: Use numerical calculation methods (such as the trapezoidal integration method or the Simpson integration method) to discretize the above formula for calculation, and obtain the weighted value corresponding to each test point.

[0061] 4. Calculate the comprehensive braking performance index

[0062] To obtain an index that can comprehensively reflect the braking performance of the tire, use integration to accumulate and calculate the weighted braking force coefficient:

[0063] Step 4.1: Determine the integration range.

[0064] Set the upper and lower limits of integration as [c×a, d×a] according to the actual working conditions (where c and d are preset constants, for example, c = 0.8, d = 1.2) to ensure that the integration interval covers most of the actual slip rate distribution area.

[0065] Step 4.2: Calculate the comprehensive braking performance index μ effective , and the calculation formula is:

[0066]

[0067] Or discretize it as:

[0068]

[0069] where Δs is the sampling interval during discretization.

[0070] The integration result is the index reflecting the overall braking performance of the tire, μ effective the larger the value, the better the braking performance of the tire.

[0071] 5. Braking performance evaluation and system implementation

[0072] Step 5.1: According to the calculated μ effective value, conduct a comprehensive evaluation of the tire braking performance.

[0073] Of course, one or more thresholds can also be set to divide the tire braking performance into different levels such as excellent, good, medium, and poor, which is convenient for comparison and selection in engineering applications.

[0074] Furthermore, the present invention compares the μ effective value calculated by this method with the results obtained by the traditional explicit dynamics analysis method.

[0075] Test results:

[0076] 1. Efficiency comparison:

[0077] The calculation process of this method takes about 2 hours, while the traditional explicit dynamics analysis method takes at least 48 hours.

[0078] 2. Accuracy comparison:

[0079] The μ effective value calculated by this method differs from the results of the traditional method by within 5%, indicating that this method has high accuracy.

[0080] The foregoing is a description of embodiments of the present invention. Through the above description of the disclosed embodiments, those skilled in the art can implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A tire braking performance rapid evaluation method based on simulation and statistical distribution, characterized in that: The steps include: a) simulating the braking force coefficient of the tire at different slip rates by finite element simulation or multi-body dynamics simulation to obtain the braking force coefficient of the tire; μ-s curve; b) According to the μ-s The normal distribution parameters of the slip rate are determined by the curve, where the normal distribution is set as N ( a,σ² ), and the value of a is μ-s The maximum friction coefficient on the curve μ The slip ratio value, σ Get the preset value; c) according to the normal distribution probability density function described in step b) and μ-s Multiply the curves to calculate the weighted braking force coefficient μ w ( s ), and its calculation formula is: ， in, μ is the friction coefficient ，s is the slip rate, μ ( s ) is the relationship between the friction coefficient and the slip rate; d) In the preset integral range [c×a, d×a], c and d are preset constants; the weighted braking force coefficient μ w ( s ) to integrate or accumulate the values ​​to obtain the comprehensive braking performance index μ effective ; Weighted braking force coefficient μ w (s) The integral of is done using a numerical integration algorithm. μ effective The calculation formula is: Or discretized as: Among them, Δs is the sampling interval during discretization; e) According to the μ effective The braking performance of the tire is evaluated by the value. μ effective The larger the value, the better the braking performance of the tire.

2. The method according to claim 1, characterized in that The finite element simulation method used in the simulation described in step (a) further includes establishing a finite element model of the tire structure and simulating the stress conditions during the contact process between the tire and the road surface.

3. The method according to claim 1, characterized in that The simulation described in step (a) can also use a multi-body dynamics simulation method to obtain the tire during dynamic braking. μ-s curve.

4. The method according to claim 1, characterized in that The normal distribution parameters described in step (b) σ The fixed value is 1. a The value is from μ-s The friction coefficient obtained from the curve μ The slip ratio at the maximum value.

5. A system for rapid evaluation of tire braking performance based on simulation and statistical distribution, characterized in that: The system implements the method described in any one of claims 1 to 4, including: a) Simulation module, used to generate tire dynamics through finite element or multi-body dynamics simulation μ-s curve; b) a statistical module for μ-s The curve determines the normal distribution parameters of slip rate and generates the normal distribution probability density function; c) a calculation module, for calculating the normal distribution probability density function and the μ-s The weighted braking force coefficient is calculated by multiplying the curves, and the weighted braking force coefficient is integrated within the preset integral range to obtain the comprehensive braking performance index. μ effective ; d) an evaluation module for μ effective The braking performance of the tire is evaluated.

6. The system according to claim 5, characterized in that The simulation module includes a finite element analysis submodule, which is used to establish a tire finite element model and perform finite element simulation.

7. The system according to claim 5, characterized in that The simulation module also includes a multi-body dynamics analysis submodule, which is used to simulate and analyze the dynamic response of the tire during braking.

8. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

9. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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