Tire braking performance rapid evaluation method, system and program product

Abstract

The invention relates to the technical field of tire simulation design, in particular to a tire braking performance rapid evaluation method and system and a program product. According to the method, the friction coefficient (mu-s curve) of the tire under different slip rates is obtained through finite element simulation or multi-body dynamics simulation. Then, assuming that the slip rate of the tire obeys normal distribution in the actual braking process, the mean value is the slip rate corresponding to the maximum mu value in the mu-s curve, and the standard deviation is 1; thirdly, multiplying the probability density function of the normal distribution by the mu-s curve to obtain a weighted braking force coefficient, integrating the weighted braking force coefficient, and calculating a comprehensive braking performance index mu effective of the tire; the larger the [mu] effector value is, the better the braking performance of the tire is. According to the method, the simulation technology and the statistical distribution model are combined, the braking performance of the tire is rapidly and accurately evaluated, the whole calculation process is about 2 hours, and the time for calculating the braking performance of the tire is obviously longer than 48 hours required by traditional explicit dynamics analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of tire simulation design, and in particular to a tire braking performance rapid evaluation method, system and program product. Background Art

[0002] As an important indicator of vehicle safety, tire braking performance has always been the focus of attention in the automotive engineering field. At present, the traditional tire braking performance evaluation method mainly relies on real vehicle tests. In actual tests, the relationship between the tire slip rate and the braking force coefficient (μ-s curve) is obtained by testing the tire braking process on the test field, 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, since the test process is affected by many factors such as environmental conditions, test equipment and road conditions, 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 used in tire performance evaluation. By constructing a finite element model or multi-body dynamics model of the tire, simulation technology can simulate the braking force coefficient of the tire at different slip rates in a short time, thereby generating a μ-s curve, reducing the time and cost requirements of actual vehicle testing. However, the 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 rate during actual braking.

[0004] In addition, with the increasing demand for high-performance tires, the applicants' previous applications for Chinese invention patents (such as Patent 2021116135564, Patent 2022100923567, and Patent 2022105620611) also proposed several simulation analysis methods for tire performance. However, in the actual braking process, due to the influence of various factors such as driving operation and road conditions, the slip rate of the tire usually exhibits certain statistical distribution characteristics, and often approximately obeys a normal distribution. The traditional evaluation method based on a single μ-s curve ignores this statistical characteristic, which may lead to a deviation between the evaluation results and the actual performance. Therefore, how to achieve a faster and more accurate evaluation of tire braking performance based on simulation technology and combined with the statistical distribution characteristics of the slip rate has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] In view of the problems in the prior art of high test cost, long test cycle and the evaluation method not fully considering the randomness of slip rate, the present invention proposes a rapid evaluation method for tire braking performance based on simulation and statistical distribution, which aims to achieve rapid and accurate evaluation of tire braking performance by combining the μ-s curve obtained by simulation with the normal distribution model of slip rate, thereby reducing the test cost and improving the reliability and practicability of the evaluation.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions: A tire braking performance rapid evaluation method comprises the following steps: a) Simulate the braking force coefficient of the tire at different slip rates through finite element simulation or multi-body dynamics simulation to obtain the tire's 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 m The slip ratio value, s 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 m w ( s ), and its calculation formula is: , in, m is the friction coefficient ，s is the slip rate, m ( s ) is the relationship between the friction coefficient and the slip rate; d) within the preset integral range [c×a, d×a], the weighted braking force coefficient m w ( s ) to integrate or accumulate the values ​​to obtain the comprehensive braking performance index m effective ; e) According to the m effective The braking performance of the tire is evaluated by the value. m effective The larger the value, the better the braking performance of the tire.

[0007] Preferably, 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.

[0008] Preferably, the simulation in step (a) can also use a multi-body dynamics simulation method to obtain the dynamic braking of the tire. μ-s curve.

[0009] Preferably, the normal distribution parameter in step (b) s The fixed value is 0.8-1.2, preferably 1. a The value is from μ-s The friction coefficient obtained from the curve m The slip ratio at the maximum value is preferably a The value is 12.0-15.0, and more preferably 13.0-14.0.

[0010] Preferably, in step (d), the weighted braking force coefficient m w (s) The integral of is done using a numerical integration algorithm. m effective The calculation formula is: .

[0011] Preferably, c=0.6-0.9, d=1.0-1.5; more preferably, c=0.65-0.80, d=1.10-1.30.

[0012] Furthermore, the present invention also discloses a system for quickly evaluating tire braking performance, comprising: 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. m effective ; d) an evaluation module for m effective The braking performance of the tire is evaluated.

[0013] Preferably, the simulation module includes a finite element analysis submodule for establishing a tire finite element model and performing finite element simulation.

[0014] Preferably, the simulation module further comprises a multi-body dynamics analysis submodule for simulating and analyzing the dynamic response of the tire during braking.

[0015] Furthermore, the present invention also discloses a computer-readable storage medium on which a computer program or instruction is stored. When the computer program or instruction is executed by a processor, the method is implemented.

[0016] Furthermore, the present invention also discloses a computer program product, including a computer program or instructions, which implement the method when executed by a processor.

[0017] The present invention adopts the above technical solution, and realizes a rapid and accurate evaluation of tire braking performance by combining the tire μ-S curve obtained by finite element or multi-body dynamics simulation with a normal distribution model reflecting the statistical distribution characteristics of the slip rate during actual braking, and has the following technical effects: 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 tire braking performance evaluation in about 2 hours, which greatly improves the evaluation efficiency compared to the traditional method of at least 48 hours of analysis time.

[0018] 2. Reduce testing costs: The present invention uses a simulation platform for data acquisition and performance calculation, effectively avoiding expensive real vehicle test equipment and site costs, thereby reducing the overall testing cost and reducing the repeated testing expenses caused by changes in the environment and test conditions.

[0019] 3. Improve 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 in the actual braking process are not fully considered. The present invention introduces a normal distribution model, models the statistical characteristics of the slip rate, and calculates the weighted braking force coefficient in combination with the probability density function, which is closer to the actual working conditions and improves the accuracy and reliability of the braking performance evaluation.

[0020] 4. Enhance adaptability to engineering applications: The simulation and statistical methods used in the present invention are not only applicable to conventional tire braking performance evaluation, but can also be applied to performance prediction and optimization under different working conditions, providing effective technical support for tire design, road adaptability analysis and vehicle safety evaluation.

[0021] 5. Easy system integration and 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 easy to promote and apply in actual projects, and provides engineers with a tire performance testing tool that is simple to operate and quick to evaluate.

[0022] In summary, the present invention greatly improves the evaluation speed and reduces the cost. At the same time, by comprehensively considering the randomness of the slip rate during the actual braking process, a more accurate tire braking performance evaluation is achieved, and it has significant application prospects and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Finite element model for simulation; Figure 2 The µ-s curve obtained by simulation; Figure 3 is the a value obtained from the µ-s curve, a=13.8272; Figure 4 It is the normal distribution curve with u=a=13.8272 and σ=1. DETAILED DESCRIPTION

[0024] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] The tire braking performance rapid evaluation method and system based on simulation and statistical distribution of the present invention are described in detail below with reference to the accompanying drawings.

[0026] 1. Simulate and obtain tire μ-s curve Firstly, the braking force coefficient (μ) data of the tire at different slip rates (s) is obtained through finite element analysis or multi-body dynamics simulation.

[0027] Step 1.1: Establish a tire finite element model or multi-body dynamics model.

[0028] like Figure 1 As shown in the figure, by modeling the tire, the internal structure, material properties and contact between the tire and the road are simulated. After the model is established, simulation calculations are performed according to preset working conditions (different braking pressures, road roughness, etc.).

[0029] Step 1.2: During the simulation, set test points with different slip rates, obtain the corresponding braking force coefficient values, and form the μ-s curve of the tire.

[0030] like Figure 2 As shown, the simulation results output a series of corresponding relationship data, where the horizontal axis is the slip rate s and the vertical axis is the corresponding braking force coefficient μ.

[0031] 2. Establish a normal distribution model for slip rate After obtaining the μ-s curve, a normal distribution model is established based on the statistical characteristics of the tire slip rate during actual braking: Step 2.1: Determine the normal distribution parameters.

[0032] The mean a of the normal distribution is determined based on the point where the friction coefficient μ reaches its maximum value in the μ-s curve. Figure 3 As shown, assume that the value of a is 13.8272.

[0033] Step 2.2: Set the standard deviation σ of the normal distribution. In the embodiment, σ is fixed to 1. Thus, the normal distribution function is constructed: ; like Figure 4 As shown, a normal distribution curve with parameters a=13.8272 and σ=1 is displayed.

[0034] 3. Calculate the weighted braking force coefficient In order to fully consider the randomness of the slip rate in the actual braking process, the μ-s curve obtained in step 1 is combined with the normal distribution probability density function established in step 2 to calculate the weighted braking force coefficient m w (s) : Step 3.1: For each slip ratio s, the corresponding weighted braking force coefficient is calculated as: ; Step 3.2: Use numerical calculation methods (such as trapezoidal integration method or Simpson integration method) to discretize the above formula and obtain the weighted value corresponding to each test point.

[0035] 4. Calculate comprehensive braking performance indicators In order to obtain an index that can fully reflect the tire braking performance, the weighted braking force coefficient is accumulated and calculated using an integral method: Step 4.1: Determine the integration range.

[0036] According to the actual working conditions, the upper and lower limits of the integral are set to [c×a, d×a] (where c and d are preset constants, such as c=0.8 and d=1.2) to ensure that the integral interval covers most of the actual slip rate distribution area.

[0037] Step 4.2: Calculate the comprehensive braking performance index m effective , the calculation formula is:

[0038] Or discretized as:

[0039] Among them, Δs is the sampling interval during discretization.

[0040] The integral result is an indicator reflecting the overall braking performance of the tire. m effective The larger the value, the better the braking performance of the tire.

[0041] 5. Braking performance evaluation and system implementation Step 5.1: Based on the calculated m effective The braking performance of the tire is comprehensively evaluated.

[0042] Of course, one or more thresholds can also be set to classify tire braking performance into different levels such as excellent, good, medium, and poor, which is convenient for comparison and selection in engineering applications.

[0043] Further, the present invention calculates the m effective The values ​​were compared with those obtained by traditional explicit kinetic analysis method.

[0044] Test results: 1. Efficiency comparison: The calculation process of this method takes about 2 hours, while the traditional explicit kinetic analysis method takes at least 48 hours.

[0045] 2. Accuracy comparison: This method calculates m effective The difference between the values ​​and those of the traditional method is within 5%, indicating that the proposed method has high accuracy.

[0046] The above is a description of the embodiments of the present invention. Through the above description of the disclosed embodiments, professionals and technicians in the field can implement or use the present invention. Various modifications to these embodiments will be apparent to professionals and technicians in the field. 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 these embodiments shown in this article, but will conform to the widest range consistent with the principles and novelties disclosed herein.

Claims

1. A method for quickly evaluating tire braking performance, 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) within the preset integral range [c×a, d×a], the weighted braking force coefficient μ w ( s ) to integrate or accumulate the values ​​to obtain the comprehensive braking performance index μ effective ; 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. The method according to claim 1, characterized in that In step (d), the weighted braking force coefficient μ w (s) The integral of is done using a numerical integration algorithm. μ effective The calculation formula is: 。 6. A system for rapid evaluation of tire braking performance, characterized in that: include: 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.

7. The system according to claim 6, 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.

8. The system according to claim 6, 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.

9. 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 5 is implemented.

10. 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 5 is implemented.

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