A method and system for evaluating vehicle motion control performance based on mathematical models

Abstract

This invention provides a method and system for evaluating vehicle motion control performance based on a mathematical model, belonging to the field of vehicle motion control performance evaluation technology. The method includes: collecting operating condition test data and traffic accident data; defining the wheel slip ratio during vehicle driving; calculating the influence score of the wheel slip ratio on the motion data; processing the obtained real-time vehicle performance data, dividing the real-time performance data into multiple intervals, calculating the slip ratio score corresponding to each interval based on the wheel slip ratio, and selecting the slip ratio score with the highest score as the optimal performance score; and weighting the optimal performance score with the influence score to obtain the vehicle's motion control performance score. This invention, by defining the wheel slip ratio and calculating its influence score on the motion data, and by analyzing traffic accident data, determines the weighting coefficients of relevant factor data from the perspective of actual safety issues, making the evaluation of vehicle motion control performance more comprehensive and accurate.

Description

Technical Field

[0001] This invention relates to the field of automotive motion control performance evaluation technology, and in particular to a method and system for evaluating automotive motion control performance based on a mathematical model. Background Technology

[0002] With the rapid development of the automotive industry and the increasing demands for vehicle safety, comfort, and handling, accurately assessing a vehicle's motion control performance has become increasingly important. A vehicle's motion control performance not only affects its stability and safety during driving but also influences the driving experience and energy efficiency.

[0003] On the one hand, in the past, the evaluation of vehicle motion control performance often lacked comprehensive collection and in-depth analysis of real-time data during testing. This resulted in an inability to accurately understand the specific performance of each component under different operating conditions, making it difficult to identify potential performance problems and optimization opportunities. In particular, the inability to collect and analyze component performance data in real time may lead to the discovery of performance defects in some critical components during actual use, thereby affecting the safety and reliability of the vehicle.

[0004] On the other hand, studies on vehicle motion have failed to fully consider the relationship between wheel forces and torques, as well as the impact of wheel slip ratio on vehicle motion data. As a key component directly in contact with the road surface, the wheel's motion significantly affects the vehicle's handling performance. However, previous evaluation methods lacked in-depth research and application of wheel dynamics equations, making it impossible to accurately define and calculate wheel slip ratio. Consequently, it was difficult to assess the impact of wheel slip ratio on vehicle motion data, resulting in inaccurate and incomplete evaluations of vehicle motion control performance.

[0005] To address the aforementioned problems, this invention proposes a method and system for evaluating vehicle motion control performance based on a mathematical model. Summary of the Invention

[0006] This invention provides a method and system for evaluating vehicle motion control performance based on a mathematical model, which addresses the shortcomings of existing technologies in evaluating vehicle motion control performance, such as incomplete evaluation indicators and a lack of basis for determining the weights of various influencing factors.

[0007] On one hand, this invention provides a method for evaluating vehicle motion control performance based on a mathematical model, comprising: real-time acquisition of vehicle data during testing to obtain traffic accident data, component performance data, motion data, and index data; obtaining a dynamic equation for each wheel based on the relationship between wheel forces and torques during longitudinal movement of the vehicle; defining the wheel slip ratio during vehicle driving based on the dynamic equation; calculating the influence score of the wheel slip ratio on the motion data; filtering and analyzing the component performance data and index data to obtain real-time vehicle performance data; dividing the real-time vehicle performance data into multiple intervals; calculating the slip ratio score corresponding to each interval based on the wheel slip ratio; selecting the slip ratio score with the highest score as the optimal performance score; and weighting the optimal performance score with the influence score to obtain the vehicle's motion control performance score.

[0008] According to the present invention, a method for evaluating vehicle motion control performance based on a mathematical model includes the following steps for calculating the influence score: extracting multiple relevant factor data affected by wheel slip rate from motion data; analyzing traffic accident data to determine the weight coefficient of each relevant factor data; calculating the factor score of each relevant factor data corresponding to the current wheel slip rate based on the relationship between each relevant factor data and the wheel slip rate; and integrating the factor scores of all relevant factor data to obtain the influence score.

[0009] According to the present invention, a method and system for evaluating vehicle motion control performance based on a mathematical model includes the following steps for determining weighting coefficients: classifying multiple relevant factor data according to the type, cause, and severity of the accident; analyzing the specific characteristics of the accident occurrence; and statistically analyzing the frequency, value range, and trend of the relevant factor data to obtain analysis results. Correlation analysis is then performed to determine the relationship between each relevant factor data and the severity of the accident, yielding importance coefficients. Based on the analysis results, the proportion of each relevant factor data in different accident categories is determined, and the proportions are adjusted according to the importance coefficients to obtain weighting coefficients.

[0010] According to the present invention, a method and system for evaluating vehicle motion control performance based on a mathematical model, the calculation of the factor scores includes:

[0011] Setting an ideal zero slip ratio Get the current wheel slip ratio. Next The value of each motion data point .calculate With zero slip The difference will be used as a factor score, which is the ratio of the value of the motion data under the ideal zero slip rate.

[0012] According to the present invention, a method and system for evaluating vehicle motion control performance based on a mathematical model includes the following screening and analysis methods: First, component performance data and indicator data are organized, outliers and missing values ​​are removed to obtain numerical data, and then normalized using a min-max normalization method to obtain normalized data. Second, based on vehicle design requirements, industry standards, and analysis results, thresholds are set for component performance data and indicator data, and it is determined whether the normalized data indicators are within the thresholds; if so, they are output as performance data; otherwise, they are output as outlier data. Third, all outlier data are merged to obtain outlier fused data, from which representative performance features are extracted, and the relationship between these representative features and the vehicle's real-time performance is analyzed to obtain key features. Finally, real-time vehicle performance data is obtained based on the performance data and key features.

[0013] According to the present invention, a method and system for evaluating vehicle motion control performance based on a mathematical model includes the following steps: collecting real-time performance data of the vehicle within a preset time period, identifying the maximum and minimum values, determining the number of intervals to be divided according to analysis requirements, using the ratio of the difference between the maximum and minimum values ​​to the number of intervals as the interval interval, and determining the range of each interval based on the interval interval to obtain multiple intervals.

[0014] According to the present invention, a method and system for evaluating vehicle motion control performance based on a mathematical model includes the following steps for calculating multiple slip ratio scores: statistical analysis of real-time vehicle performance data; selection of a linear regression model to fit the relationship between wheel slip ratio and real-time vehicle performance data to obtain a quantitative relationship expression; taking the midpoint value of each interval as a characteristic value representing the performance of that interval, and substituting the obtained characteristic value of each interval into the quantitative relationship expression to obtain the slip ratio corresponding to each interval; setting slip ratio scoring rules based on preset requirements and influence scores, and calculating the slip ratio score corresponding to each slip ratio according to the scoring rules.

[0015] According to the present invention, a method and system for evaluating vehicle motion control performance based on a mathematical model includes the following steps to obtain a quantitative relationship expression: taking real-time vehicle performance data as the dependent variable and wheel slip ratio as the independent variable, and using a linear regression model to fit the relationship between the dependent and independent variables. The parameters of the linear regression model are determined using the least squares method to minimize the sum of squared errors between the predicted and actual values, obtaining the slope and intercept values. The slope and intercept values ​​are then substituted into the linear regression model to obtain the quantitative relationship expression.

[0016] According to the present invention, a method for evaluating vehicle motion control performance based on a mathematical model is provided, wherein the formulas for the slope value and the intercept value are expressed as follows:

[0017]

[0018]

[0019] In the formula, The slope value. This is the intercept value. This represents the sample mean of the wheel slip ratio. This represents the sample mean of real-time vehicle performance data. For the first The dependent variable values ​​for each sample For the first The independent variable values ​​of each sample, This provides data on real-time vehicle performance and wheel slip ratio. For index variables.

[0020] On the other hand, the present invention also provides a vehicle motion control performance evaluation system based on a mathematical model. The vehicle motion control performance evaluation system includes a control device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement a vehicle motion control performance evaluation method based on a mathematical model.

[0021] This invention provides a mathematical model-based method and system for evaluating vehicle motion control performance. By defining wheel slip ratio and calculating its impact score on motion data, it incorporates these factors into the evaluation system. This addresses the problem that existing patented technologies typically focus only on single performance indicators such as vehicle speed and braking distance when evaluating vehicle motion control performance, neglecting the impact of wheel slip ratio on overall vehicle performance. This results in a more comprehensive and accurate evaluation. Furthermore, by analyzing traffic accident data, it determines the weighting coefficients of relevant factors from the perspective of actual safety issues, making the vehicle motion control performance evaluation more comprehensive and accurate. This more realistically reflects the actual performance of vehicles under different operating conditions, providing more valuable references for vehicle research and development, production, improvement, and user selection. A complete mathematical model-based vehicle motion control performance evaluation system is constructed, including multiple stages such as data acquisition, processing, analysis, and performance score calculation. This provides a standardized and regulated process for performance evaluation in the automotive industry, helping to improve the evaluation level and efficiency of the entire industry. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is one of the flowcharts illustrating a method for evaluating vehicle motion control performance based on a mathematical model, provided in an embodiment of the present invention.

[0024] Figure 2 This is the second flowchart of a method for evaluating vehicle motion control performance based on a mathematical model, provided in an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0026] The following is combined with Figures 1-2 This invention describes a method and system for evaluating vehicle motion control performance based on a mathematical model.

[0027] like Figure 1 As shown in the embodiment of the present invention, a method and system for evaluating vehicle motion control performance based on a mathematical model are provided. The executing entity can be a method for evaluating vehicle motion control performance based on a mathematical model, including:

[0028] Real-time data collection of traffic accident data, component performance data, motion data, and indicator data of vehicles during testing.

[0029] Based on the relationship between the wheel forces and torques during the longitudinal movement of the car, the dynamic equations for each wheel are obtained, expressed as follows:

[0030]

[0031] In the formula, For the moment of inertia of the wheel, The angular velocity of the wheel. For wheel drive torque, The rolling resistance torque of the wheel, For the wheel radius, For ground friction, for =1,2,3,4 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel of the vehicle, respectively.

[0032] Based on the dynamic equations, the wheel slip ratio during vehicle driving is defined as follows:

[0033]

[0034] In the formula, For wheel slip ratio, The speed is the vehicle speed.

[0035] The influence score is obtained by calculating the impact score of wheel slip ratio on motion data.

[0036] like Figure 2 As shown, the steps for calculating the impact score include:

[0037] This study extracts data on multiple relevant factors influenced by wheel slip rate from motion data, analyzes traffic accident data, and determines the weight coefficient of each relevant factor from the perspective of actual safety issues. Let the relevant factor data be A(A1, A2, ..., A...). Z (), where A1 is the vehicle speed, A2 is the steering wheel angle, A Z It is braking pressure.

[0038] The steps to determine the weighting coefficients include:

[0039] The data of multiple related factors are classified according to the type, cause and severity of the accident. For each type of accident, the specific characteristics of the accident at the time of occurrence are analyzed, and the frequency of occurrence, value range and trend of the related factor data are statistically analyzed to obtain the analysis results.

[0040] Importance coefficients were obtained by analyzing the relationship between various relevant factors and the severity of accidents. In actual road driving, vehicle speed directly affects the amount of kinetic energy a vehicle possesses. Generally, the higher the speed, the greater the energy released during a collision, potentially leading to more severe consequences, such as greater vehicle damage and more serious injuries or fatalities. Furthermore, excessive speed significantly shortens the driver's reaction time and braking distance, increasing the probability of an accident.

[0041] In emergency maneuvers such as avoidance or turning, improper steering wheel angle control can cause the vehicle to lose stability, potentially leading to collisions, rollovers, or other accidents. For example, suddenly turning the steering wheel sharply at high speeds can easily cause the vehicle to lose control and increase the severity of the accident.

[0042] When braking is required in an emergency, appropriate braking pressure can quickly decelerate and stop the vehicle, effectively avoiding or mitigating the consequences of an accident. However, insufficient braking pressure may prevent the vehicle from stopping within the expected distance, leading to a collision; conversely, excessive braking pressure may cause wheel lock-up, making the vehicle lose control and similarly increasing the risk and severity of an accident.

[0043] For each case, detailed records and analyses were compiled of relevant factor data and specific indicators of accident severity (such as the number of casualties, the amount of property damage, and the extent of vehicle damage). Spearman's rank correlation coefficient analysis was used to analyze the correlation between nonparametric data and obtain coefficient values ​​reflecting the correlation between various relevant factors and accident severity.

[0044] Based on the analysis results, the proportions of each relevant factor in different accident categories were initially determined, and the proportions were adjusted according to the importance coefficients to obtain the weighting coefficients.

[0045] For each relevant factor data, based on its relationship with the wheel slip ratio, the degree of change of each relevant factor data under the current wheel slip ratio is calculated, and the factor score of each relevant factor data is obtained.

[0046] The factor scores are calculated as follows:

[0047] Setting an ideal zero slip ratio ;

[0048] Get the current wheel slip ratio Next The value of each motion data point ;

[0049] calculate With zero slip The difference, when compared to the value of the motion data under ideal zero slip rate, will be used as a factor score. The formula is expressed as:

[0050]

[0051] In the formula, Score the factors. For an ideal zero slip ratio, Current wheel slip ratio Next The value of each motion data point, For reference wheel slip ratio The value of this motion data.

[0052] The influence score is obtained by integrating the factor scores of all relevant factors. The integration method can be summing up the scores of all factors to obtain the influence score.

[0053] The vehicle's real-time performance data is obtained by filtering and analyzing the component performance data and the index data. The vehicle's real-time performance data is divided into multiple intervals. The slip ratio score corresponding to each interval is calculated based on the wheel slip ratio. The slip ratio score with the highest score is selected as the optimal performance score.

[0054] The steps to obtain real-time vehicle performance data include:

[0055] The component performance data and indicator data are organized, outliers and missing values ​​are removed to obtain numerical data, and then normalized using the min-max normalization method to obtain normalized data. The formula is expressed as:

[0056]

[0057] In the formula, To normalize the data, For numerical data, The maximum value of the numerical data. This represents the minimum value of the numerical data.

[0058] Based on the vehicle's design requirements, industry standards, and analysis results, thresholds are set for the component performance data and indicator data. It is then determined whether the normalized data indicators are within the thresholds. If they are, the output is performance data; otherwise, the output is abnormal data.

[0059] All abnormal data are merged together to obtain abnormal fused data. Performance representative features are extracted from the abnormal fused data, and the relationship between performance representative features and real-time vehicle performance is analyzed to identify the key features with the highest correlation to real-time vehicle performance.

[0060] Real-time vehicle performance data is obtained based on performance data and key features.

[0061] The steps to obtain multiple intervals include:

[0062] Collect real-time vehicle performance data within a preset time period, identify the maximum and minimum values, determine the number of intervals to be divided according to the analysis requirements, use the ratio of the difference between the maximum and minimum values ​​to the number of intervals as the interval interval, and determine the range of each interval based on the interval interval to obtain multiple intervals.

[0063] The steps for calculating multiple slip ratio scores include:

[0064] Statistical analysis was performed on real-time vehicle performance data, and a linear regression model was selected to fit the relationship between wheel slip ratio and real-time vehicle performance data, resulting in a quantitative relationship expression.

[0065] The steps to obtain the quantitative relational expression include:

[0066] Using real-time vehicle performance data as the dependent variable and wheel slip ratio as the independent variable, a linear regression model is used to fit the relationship between the dependent and independent variables. The formula is expressed as:

[0067]

[0068] In the formula, As the dependent variable, As the independent variable, The intercept is... The slope This is the error term.

[0069] The parameters of the linear regression model are determined using the least squares method to minimize the sum of squared errors between the predicted and actual values, thereby obtaining the slope and intercept values.

[0070] The formulas for slope and intercept are expressed as follows:

[0071]

[0072]

[0073] In the formula, The slope value. This is the intercept value. This represents the sample mean of the wheel slip ratio. This represents the sample mean of real-time vehicle performance data. For the first The dependent variable values ​​for each sample For the first The independent variable values ​​of each sample, This provides data on real-time vehicle performance and wheel slip ratio. For index variables.

[0074] Substituting the slope and intercept values ​​into the linear regression model yields a quantitative relationship expression.

[0075] The midpoint value of each interval is taken as the characteristic value representing the interval performance, and the obtained characteristic value of each interval is substituted into the quantitative relationship expression to obtain the slip ratio corresponding to each interval.

[0076] Based on preset requirements and influence scores, a scoring rule for slip ratio is set. The slip ratio score corresponding to each slip ratio is calculated according to the scoring rule, expressed by the formula:

[0077]

[0078] In the formula, To score the slip ratio, A coefficient related to slip ratio, For slip ratio, Based on the basic score.

[0079] The optimal performance score and the impact score are weighted together to obtain the vehicle's motion control performance score.

[0080] Example 1: At a certain automotive testing ground, a new energy electric vehicle is undergoing a real-world road test. High-precision sensors are used to collect various data from the vehicle in real time during the test, which lasts for 2 hours, with a data acquisition frequency of 10 times per second.

[0081] Traffic accident data: No traffic accidents occurred during this test, therefore this data is 0 accident records for this test.

[0082] Component performance data: Data were collected on battery pack voltage, current, and temperature; motor speed and torque; and braking system braking pressure. Battery pack voltage ranged from 350V to 400V during the test, with an average voltage of 375V; motor speed fluctuated between 1000r / min and 5000r / min, with an average speed of 3000r / min.

[0083] Motion data: including vehicle speed, acceleration, longitudinal displacement, and lateral displacement. During the test, the vehicle speed varied between 0 km / h and 120 km / h, with an average speed of 60 km / h; the acceleration varied between -5 m / s² and 3 m / s², with an average acceleration of 0.5 m / s².

[0084] Data collected included fuel consumption rate (electricity consumption for new energy vehicles) and emission concentration. The average electricity consumption of this electric vehicle was 15 kWh / 100km.

[0085] Based on the relationship between wheel forces and torques during longitudinal motion of a car, assuming the car's mass is 1500 kg, the wheel radius is 0.3 m, and the wheel moment of inertia is 1.2 kg·m², the dynamic equations for each wheel are obtained using relevant mechanical formulas:

[0086]

[0087] In the formula, For the moment of inertia of the wheel, The angular velocity of the wheel. For wheel drive torque, The rolling resistance torque of the wheel, For the wheel radius, For ground friction, for =1,2,3,4 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel of the vehicle, respectively.

[0088] Based on the above dynamic equations, the wheel slip ratio during vehicle driving is defined as follows:

[0089]

[0090] In the formula, For wheel slip ratio, The speed is the vehicle speed.

[0091] At a certain moment, when the car speed is 30 m / s and the wheel angular velocity is 90 rad / s, the calculated wheel slip ratio is 0.1. A correlation model is established between the wheel slip ratio and motion data (such as velocity and acceleration), and the influence function is fitted using multiple test data. The calculated influence score of this wheel slip ratio on the motion data is 0.4. The influence score ranges from 0 to 1, with a higher score indicating a greater influence.

[0092] The collected component performance and indicator data are screened and analyzed to remove abnormal and interfering data. For battery pack temperature data, data exceeding the normal operating range (-20℃ to 60℃) are considered abnormal and discarded. These data are then processed to obtain the vehicle's real-time performance data.

[0093] The real-time performance data of the vehicle is divided into 5 intervals:

[0094] Range 1: Power consumption less than 13 kWh / 100km, motor torque greater than 200 N·m;

[0095] Range 2: Energy consumption is between 13-14 kWh / 100km, and motor torque is between 150-200 N·m;

[0096] Range 3: Power consumption is between 14-15 kWh / 100km, and motor torque is between 100-150 N·m;

[0097] Range 4: Power consumption is between 15-16 kWh / 100km, and motor torque is between 50-100 N·m;

[0098] Range 5: Power consumption greater than 16 kW·h / 100km, motor torque less than 50 N·m.

[0099] The slip ratio score for each interval is calculated based on the wheel slip ratio. Assuming the scoring rules obtained through experiments and data analysis are as follows: when the wheel slip ratio is between 0 and 0.1, the slip ratio score for interval 1 is 0.8, for interval 2 it is 0.7, for interval 3 it is 0.6, for interval 4 it is 0.5, and for interval 5 it is 0.4. These scores are compared, and the highest score of 0.8 is selected as the optimal performance score.

[0100] The optimal performance score is weighted at 0.6, and the influence score is weighted at 0.4. The optimal performance score of 0.8 and the influence score of 0.4 are weighted to obtain the vehicle's motion control performance score of 0.64.

[0101] The above examples demonstrate the specific application and data processing of the vehicle motion control performance evaluation method based on mathematical models, which can comprehensively and accurately evaluate the motion control performance of a vehicle.

[0102] This embodiment provides a mathematical model-based method for evaluating vehicle motion control performance. By comprehensively considering wheel slip ratio and its impact on multiple related factors, it defines wheel slip ratio and calculates its impact score on motion data, incorporating these factors into the evaluation system. This addresses the problem that existing technologies typically focus only on single performance indicators, such as vehicle speed and braking distance, while neglecting the impact of wheel slip ratio on overall vehicle performance. It enables a more accurate evaluation of vehicle motion control performance. Furthermore, it employs a min-max normalization method to normalize the data and sets thresholds to identify data anomalies. Anomalies are fused and key features are extracted, improving the reliability and stability of the evaluation results and reducing errors in data processing. By identifying the optimal performance score and impact score, it provides clear direction and basis for optimizing vehicle performance.

[0103] Based on the same general inventive concept, this invention also protects a vehicle motion control performance evaluation system based on a mathematical model. The vehicle motion control performance evaluation system includes a control device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement a vehicle motion control performance evaluation method based on a mathematical model.

[0104] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0105] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the performance of vehicle motion control based on a mathematical model, characterized in that, include: Real-time collection of traffic accident data, component performance data, motion data, and indicator data of vehicles during testing; Based on the relationship between wheel forces and torques during longitudinal movement of the vehicle, a dynamic equation for each wheel is obtained. Based on the dynamic equation, the wheel slip ratio during vehicle driving is defined, and the influence score of the wheel slip ratio on the motion data is calculated. The vehicle's real-time performance data is obtained by filtering and analyzing the component performance data and the index data. The vehicle's real-time performance data is divided into multiple intervals. The slip ratio score corresponding to each interval is calculated based on the wheel slip ratio. The slip ratio score with the highest score is selected as the optimal performance score. The calculation steps for the slip ratio score include: Statistical analysis was performed on the real-time vehicle performance data, and a linear regression model was selected to fit the relationship between the wheel slip ratio and the real-time vehicle performance data to obtain a quantitative relationship expression; The steps to obtain the quantitative relational expression include: The real-time vehicle performance data is used as the dependent variable, and the wheel slip ratio is used as the independent variable. The linear regression model is used to fit the relationship between the dependent variable and the independent variable. The parameters of the linear regression model are determined using the least squares method to minimize the sum of squared errors between the predicted and actual values, thereby obtaining the slope and intercept values. Substituting the slope value and the intercept value into the linear regression model, the quantitative relationship expression is obtained; The midpoint value of each interval is taken as the characteristic value representing the performance of the corresponding interval, and the characteristic value of each interval is substituted into the quantitative relationship expression to obtain the slip ratio corresponding to each interval. Based on the preset requirements and the influence score, the scoring rules for the slip ratio are set, and the slip ratio score corresponding to each slip ratio is calculated according to the scoring rules; The optimal performance score and the influence score are weighted together to obtain the vehicle's motion control performance score.

2. The method for evaluating vehicle motion control performance based on a mathematical model according to claim 1, characterized in that, Calculating the influence score includes: Extract multiple relevant factor data affected by the wheel slip rate from the motion data, analyze the traffic accident data, and determine the weight coefficient of each relevant factor data; Based on the relationship between each relevant factor data and the wheel slip ratio, calculate the factor score for each relevant factor data corresponding to the current wheel slip ratio; The factor scores of all relevant factors are integrated to obtain the influence score.

3. The method for evaluating vehicle motion control performance based on a mathematical model according to claim 2, characterized in that, The step of determining the weight coefficient of each relevant factor data includes: The data of multiple related factors are classified according to the type, cause and severity of the accident. The specific characteristics of the accident at the time of occurrence are analyzed. The frequency of occurrence, value range and trend of the related factor data are statistically analyzed to obtain the analysis results. By performing correlation analysis on the relationship between the data of various relevant factors and the severity of the accident, we can obtain... Importance coefficient ; Based on the analysis results, the proportion of each relevant factor data in different accident categories is determined, and the proportion is adjusted according to the importance coefficient to obtain the weight coefficient.

4. The method for evaluating vehicle motion control performance based on a mathematical model according to claim 3, characterized in that, The calculation of the factor scores includes: Setting an ideal zero slip ratio ; Get the current wheel slip ratio Next The value of each motion data point ; calculate With zero slip The difference is calculated, and the ratio of this difference to the value of the motion data under ideal zero slip rate is used as a factor score.

5. The method for evaluating vehicle motion control performance based on a mathematical model according to claim 3, characterized in that, The steps to obtain the real-time performance data of the vehicle include: The component performance data and the index data are sorted out, outliers and missing values ​​are removed to obtain numerical data, and then normalized using the min-max normalization method to obtain normalized data. Based on the vehicle's design requirements, industry standards, and the analysis results, thresholds are set for the component performance data and the indicator data. It is then determined whether the normalized data indicators are within the thresholds. If they are, the output is performance data; otherwise, the output is abnormal data. All abnormal data are merged together to obtain abnormal fused data. Performance representative features are extracted from it, and the relationship between the performance representative features and the real-time performance of the vehicle is analyzed to obtain key features. Real-time vehicle performance data is obtained based on the performance data and the key features.

6. The method for evaluating vehicle motion control performance based on a mathematical model according to claim 1, characterized in that, Divided into multiple intervals, including: Collect real-time performance data of the vehicle within a preset time period, find the maximum and minimum values, determine the number of intervals to be divided according to the analysis requirements, use the ratio of the difference between the maximum and minimum values ​​to the number of intervals as the interval interval, and determine the range of each interval based on the interval interval to obtain multiple intervals.

7. The method for evaluating vehicle motion control performance based on a mathematical model according to claim 1, characterized in that, The formulas for obtaining the slope value and the intercept value are expressed as follows: In the formula, The slope value. This is the intercept value. This represents the sample mean of the wheel slip ratio. This represents the sample mean of real-time vehicle performance data. For the first The dependent variable values ​​for each sample For the first The independent variable values ​​of each sample, This provides data on real-time vehicle performance and wheel slip ratio. For index variables.

8. A vehicle motion control performance evaluation system based on a mathematical model, characterized in that, The vehicle motion control performance evaluation system includes a control device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the vehicle motion control performance evaluation method based on a mathematical model according to any one of claims 1-7.

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