Passenger vehicle braking performance evaluation system based on automobile big data

Abstract

The invention relates to the technical field of passenger car braking, in particular to a passenger car braking performance evaluation system based on automobile big data. Which comprises a data acquisition module, an acquisition module, a sending module, a computer module, a comparison module, a comprehensive analysis module, an analysis report generation module and an automobile database, and is characterized in that automobile brake data in a sensor and special equipment mounted on a brake test bed or an automobile is acquired, subjected to analog-to-digital conversion and then uploaded to an upper computer; acquiring a test instruction input by a user; according to the test instruction, acquiring corresponding braking data from an upper computer, and performing calculation and evaluation; comparing the calculated and evaluated results with data in an automobile database; and carrying out comprehensive analysis to generate a comprehensive analysis report. According to the method, an automobile database technology is applied to carry out algorithm analysis on the automobile braking performance, so that the evaluation of the automobile braking performance is more convenient and quicker, and the evaluation accuracy is improved. And the user can also compare indexes such as the braking distance and the braking deceleration with other passenger vehicles in the database, so that the advantages and the deficiencies are clear, and reference is provided for the user.

Description

Technical Field

[0001] This application relates to the technical field of passenger vehicle braking, and particularly to a passenger vehicle braking performance evaluation system based on automotive big data. Background Art

[0002] Today's society is an era of big data, and food, clothing, housing, and transportation are the fundamentals of human survival. Therefore, it is crucial to skillfully use big data to evaluate various performances of automobiles. Among various performances of automobiles, braking performance occupies a pivotal position.

[0003] With the rapid development of the automotive industry, the performance requirements for the service braking system are becoming increasingly strict. The braking performance of an automobile refers to the ability of the automobile to decelerate and stop as needed and maintain directional stability, or the ability to maintain a certain speed when going down a long slope. At present, there are mainly two methods for detecting the braking performance of automobiles, namely the road detection method and the bench test method.

[0004] The road detection method refers to detecting the braking performance of an automobile on the road. Usually, instruments are used for measurement. A speedometer (also called a fifth-wheel instrument) is used to measure the change in vehicle speed and the braking distance when the vehicle decelerates from a specified initial speed to a speed of zero. According to current regulations, the performance requirements for the braking system mainly include two aspects: braking efficiency and braking stability. For the road detection method, the evaluation of braking efficiency mainly depends on the measurement of braking distance and the average deceleration dm fully developed, while braking stability is judged by whether the vehicle exceeds the specified road surface width. Therefore, the average braking deceleration fully developed is calculated based on the measurement results of the speedometer, and the braking performance is judged to be qualified based on the length of the braking distance and the average braking deceleration fully developed.

[0005] The bench test method is to detect the braking performance of an automobile on a test bench. The detection items include axle load, maximum braking force, braking rate, imbalance rate, drag rate, etc.

[0006] Based on the above methods for detecting the braking performance of automobiles, a passenger vehicle braking performance evaluation system based on automotive big data is proposed, which is convenient for quickly evaluating the braking performance of passenger vehicles under the condition of automotive big data.

[0007] The currently existing prior art closest to the patented technology and its defects

[0008] Currently, the evaluation system for the braking performance of passenger cars based on big data has gradually become an important direction in vehicle performance testing. In traditional braking evaluation methods, laboratory tests, manual tests, and simplified simulation analyses are often relied upon. For example, many existing technologies use physical measurement indicators such as the braking distance, braking force distribution, and vehicle dynamic characteristics of the vehicle to evaluate braking performance. These methods usually need to be carried out in a fixed test environment, cannot adapt to complex actual driving conditions, and it is also difficult to obtain multi-dimensional data during the driving process in real time.

[0009] 1. Prior Art

[0010] A relatively typical prior art is a real-time data acquisition system based on vehicle sensors. These sensors monitor parameters such as the braking pressure, wheel speed, and road conditions of the vehicle, and analyze and predict the braking performance. For example, some advanced cars are already equipped with intelligent control systems such as ABS (Anti-lock Braking System) and ESP (Electronic Stability Program) based on ECU (Electronic Control Unit), which optimize the braking performance by controlling various components of the vehicle. However, the drawback of these systems is that although they can optimize the braking performance in a single vehicle environment, they are mostly limited to specific physical test parameters and static analysis, and cannot deeply explore and comprehensively consider the complex big data in different driving scenarios.

[0011] In addition, some prior arts attempt to use historical driving data and road condition information of the vehicle for predictive analysis, relying on in-vehicle computers or external cloud platforms to model the driving behavior of the vehicle and optimize algorithms. However, most of these methods ignore the dynamic changes and diverse impacts of real-time data. For example, factors such as individual differences of drivers, driving habits, changes in vehicle load, and the impacts of different climate and road environments are dealt with rather roughly in the prior art. The existing evaluation systems fail to achieve timely responses to these dynamic changes, resulting in certain lag and insufficient accuracy in their evaluation results.

[0012] 2. Defect Analysis

[0013] Although the existing braking evaluation systems can provide certain help in some specific scenarios, they generally have the following defects:

[0014] 1) Insufficient data integration ability: Most existing systems only rely on vehicle sensors or static data, making it difficult to achieve comprehensive data analysis across multiple vehicles and multiple environmental conditions, and unable to fully reflect the braking performance of the vehicle under changing driving conditions.

[0015] 2) Poor real-time performance: Existing technologies often rely on offline data processing, lacking accurate acquisition and immediate analysis of real-time data during the dynamic driving process, resulting in a delay in braking performance evaluation and being unable to quickly provide feedback and adjustment suggestions for drivers.

[0016] 3) Low evaluation accuracy: Existing technologies mostly rely on simplified physical models or historical data for prediction. These methods cannot fully consider complex driving behaviors, environmental factors, and vehicle characteristics, resulting in insufficient accuracy and comprehensiveness in braking performance evaluation.

[0017] 4) Limited applicability: Most existing technologies are only applicable to the braking performance evaluation of specific vehicle models or under specific conditions, and cannot provide a general evaluation standard under different vehicle models, different driving habits, and complex environmental conditions.

[0018] Therefore, a braking performance evaluation system for passenger cars based on automotive big data can collect real-time data from more dimensions, combine big data analysis technology and machine learning algorithms, evaluate the braking performance of vehicles more accurately and comprehensively, and provide personalized braking performance optimization suggestions according to different driving situations and environmental conditions, making up for the deficiencies of existing technologies. Summary of the Invention

[0019] The purpose of the present invention is to provide a braking performance evaluation system for passenger cars based on automotive big data, including:

[0020] Data acquisition module: On the one hand, the data acquisition module includes collecting data such as braking distance and vehicle speed output by special equipment such as a speedometer, that is, the road detection method; collecting data such as axle load and maximum braking force output by a braking test bench, that is, the bench test method. On the other hand, it includes performing analog-to-digital conversion on the collected braking data.

[0021] Acquisition module: The acquisition module is used to acquire the automotive braking performance data after analog-to-digital conversion and save it in the form of a data table; it is also used to acquire the corresponding performance data from the data table according to the type of test instruction given by the user;

[0022] Sending module: Used to upload the automotive braking performance data to the host computer.

[0023] Computer module: The computer module includes two parts, a memory and a processor. The memory stores a computer program; the processor executes the computer program, acquires the corresponding performance data from the host computer according to the type of test instruction, and calculates the braking parameters of the vehicle. The calculation is divided into two aspects. On the one hand, it judges whether the above data meets the national standard; on the other hand, according to the different data sources, it is brought into the corresponding computer program.

[0024] Comparison module: The comparison module is used to compare the results output by the computer module with those of other passenger cars in the automotive big data, locate whether the braking performance of the passenger car being evaluated is upstream, midstream, or downstream in the automotive big data, and can directly see the pros and cons of the braking performance of this passenger car for easy reference;

[0025] Comprehensive analysis module: The comprehensive analysis module comprehensively compares the data information in the positioning module and the automotive big data, and conducts a comprehensive analysis from the aspect of safety;

[0026] Analysis report generation module: The analysis report generation module is used to receive the analysis results of the comprehensive analysis module, generate an analysis report, and judge whether the braking performance of the passenger car meets the standards;

[0027] Automobile database: It internally stores a large amount of passenger car information, including braking data of various models.

[0028] The data acquisition module is connected to the acquisition module. The acquisition module receives the test instructions of the user and is connected to the sending module. The sending module is connected to the computer module. The computer module includes two parts, a memory and a processor, and is connected to the comparison module. The comparison module is respectively connected to the automotive big data and the comprehensive analysis module. The comprehensive analysis module is connected to the analysis report generation module. Brief description of the drawings Figure 1 It is the overall structure diagram of the evaluation system of the present invention. Detailed implementation manners

[0029] The structure diagram of this evaluation system includes various sensors, an automotive CAN bus, a CAN bus data acquisition device, and a host computer. The various sensors, the automotive CAN bus, the CAN bus data acquisition device, and the host computer are connected by wire harnesses. Among them, the sensors and the automotive CAN bus are both installed on the vehicle. The CAN bus data acquisition device is a common electrical device, and the host computer is usually implemented through laptop computer software.

[0030] A passenger car braking performance evaluation system based on automotive big data includes the following steps:

[0031] Step 1: Collect data such as braking distance and vehicle speed output by special equipment such as a speedometer, that is, the road detection method; collect data such as axle load and maximum braking force output by a braking test bench, that is, the bench test method. In the automotive braking performance test, sensors will collect various analog signals, which describe various parameters during the braking process, such as braking pressure, braking time, wheel speed, etc. However, the computer or the host computer processes digital signals. Therefore, these analog signals need to be processed by an analog-to-digital converter (ADC) and converted into digital signals before they can be recognized and processed by the computer. Therefore, the collected braking data is subjected to analog-to-digital conversion;

[0032] Step 2: The acquisition module acquires the vehicle braking performance data after analog-to-digital conversion and saves it in the form of a data table; and according to the type of the test instruction given by the user, acquires the corresponding performance data from the data table; and uploads the vehicle braking performance data to the host computer;

[0033] Step 3: According to the type of the test instruction, acquire the corresponding performance data from the host computer and calculate the braking parameters of the vehicle;

[0034] For the road detection method: In the national standard GB7258—2017 "Motor Vehicle Operating Safety Technical Conditions", the basic requirements and related detection parameters for the braking performance of the road detection method are specified.

[0035] (2) Use the braking distance to test the service braking performance

[0036] The braking distance refers to the distance traveled by a passenger car from the moment the driver's foot starts to contact the

[0037] braking pedal until the passenger car stops when the driver suddenly steps on the braking pedal at the specified initial speed.

[0038] The standard requires that the braking distance of a motor vehicle at the specified initial speed should comply with the provisions of Table 1.

[0039]

[0040]

[0041] Table 1 Vehicle Braking Distance Detection Standard

[0042] (2) Use the average deceleration at full braking to test the service braking performance

[0043] The braking deceleration represents the rate at which the speed of a passenger car decreases during braking. Therefore, the braking deceleration is often used to evaluate the braking effect. In the national standard, the calculation formula for the average deceleration during the braking process of a vehicle is shown in Equation 1:

[0044]

[0045] In the formula:

[0046] a 2 —— The average deceleration at full braking of the test passenger car, unit: m / s 2 ;

[0047] Vo —— The initial braking speed of the test passenger car, unit: km / h;

[0048] Vb —— The vehicle speed at 0.8Vo, unit: km / h;

[0049] Ve —— The vehicle speed at 0.1Vo, with the unit of km / h;

[0050] Sb —— The distance traveled by the test passenger car when the vehicle speed ranges from Vo to Vb, with the unit of meter (m);

[0051] Se —— The distance traveled by the test passenger car when the vehicle speed ranges from Vo to Ve, with the unit of meter (m).

[0052] In the national standard, for a car that suddenly applies the brakes at a specified initial speed, the average deceleration fully developed by the passenger car should comply with the provisions in Table 2.

[0053]

[0054]

[0055] Table 2 Detection Standards for Automobile Braking Deceleration

[0056] (3) Use the braking coordination time to detect the braking performance of a passenger car

[0057] The braking coordination time refers to the time required when suddenly applying the brakes, from the moment the driver's foot starts to touch the brake pedal (or the hand operates the brake lever) until the deceleration of the motor vehicle reaches 75% of the average deceleration fully developed specified in the above table. And for a car with hydraulic braking, the braking coordination time should be less than or equal to 0.35 s; for a car with pneumatic braking, it should be less than or equal to 0.60 s; for a car train, articulated bus, and articulated trolleybus, it should be less than or equal to 0.80 s.

[0058] For the bench test method: In the national standard GB7258—2017 "Technical Conditions for the Safety of Motor Vehicle Operation", the basic requirements and related test parameters for the braking performance of the bench test method are specified.

[0059] (2) Use the braking ratio to test the braking performance of a passenger car

[0060] The braking ratio is an important analysis index of an automobile, which includes multiple types, such as the vehicle braking ratio, axle braking ratio, and parking braking ratio.

[0061]

[0062] The maximum braking force adopted by each of the above braking ratios is the maximum value that can be generated during the emergency braking process.

[0063] In the national standard GB7258—2017 "Technical Conditions for the Safety of Motor Vehicle Operation" newly implemented in China, it is clearly stipulated that for a two-axle vehicle, the braking ratio of one axle ≥ 60%, the braking ratio of the second axle ≥ 50%, the vehicle braking ratio ≥ 60%, and according to the requirements of the standard, the parking braking ratio is not less than 20%.

[0064] (2) Testing the braking performance of passenger cars using the imbalance rate

[0065] The imbalance rate is one of the key indicators of passenger cars. It reflects the consistency of the braking performance between the left and right wheels of a passenger car during braking, which is commonly referred to as "partial braking". The imbalance rate of a passenger car is defined as:

[0066]

[0067] In the latest national standard GB7258—2017 "Technical Conditions for the Safety of Motor Vehicle Operation" implemented in China, it is clearly stipulated that for a two-axle vehicle, the imbalance rate of one axle ≤ 24%, and the imbalance rate of the second axle ≤ 10%.

[0068] (2) Testing the braking performance of passenger cars using the drag rate

[0069] As an indicator to measure the magnitude of the mechanical resistance of a vehicle during normal driving, the drag rate value should not be greater than 10% of the wheel load. Its calculation expression is as follows:

[0070]

[0071] In the process of quantitatively evaluating the braking performance of passenger cars:

[0072] When using the road test method, braking distance, braking deceleration, and braking stability are used as key evaluation indicators. If any one of these indicators fails to meet the established national standard range, the evaluation result of the braking performance of the passenger car is directly judged as failing (i.e., the score is lower than 60 points). In order to more accurately reflect the quality of the braking performance of passenger cars, different weight coefficients are set for these three indicators of braking distance, braking deceleration, and braking stability, and corresponding score standards are formulated accordingly. Specifically, the better the braking performance of a passenger car, the higher its scores on these three indicators will be.

[0073] When using the bench test method, braking rate, imbalance rate, and drag rate are used as key evaluation indicators. If any one of these indicators fails to meet the established national standard range, the evaluation result of the braking performance of the passenger car is directly judged as failing (i.e., the score is lower than 60 points). In order to more accurately reflect the quality of the braking performance of passenger cars, different weight coefficients are set for these three indicators of braking rate, imbalance rate, and drag rate, and corresponding score standards are formulated accordingly. Specifically, the better the braking performance of a passenger car, the higher its scores on these three indicators will be.

[0074] Thus, the objectivity and accuracy of the evaluation results are ensured.

[0075] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0076] (1) The present invention adopts automotive big data technology. While extracting braking data from big data for comparison, it also stores experimental data into big data, gradually improving the accuracy of the system;

[0077] (2) The present invention takes into account special situations in experiments. On the basis of connecting the upload unit, an input upload unit is added, which can manually input evaluation indicators of braking performance, facilitating users;

[0078] (3) The present invention converts a series of complex parameters into an intuitive and short score through an algorithm set in the system, enabling the advantages and disadvantages of passenger cars to be seen intuitively;

[0079] (4) The present invention sets a qualified score according to the real-time data situation of automotive big data, realizing the intuitiveness of the advantages and disadvantages of braking performance.

Claims

1. A passenger car braking performance evaluation system, characterized in that: The system integrates the application of automobile big data, and its specific components include data acquisition module, data acquisition module, data transmission module, calculation and processing module, comparison and verification module, comprehensive analysis module, report generation module and automobile data storage library. The workflow of the system covers: first, the brake-related data is collected from the brake test bench or passenger car sensors and professional equipment, and the data is transmitted to the host computer system after being processed by analog-to-digital conversion technology; then, the system receives the test instructions input by the user; according to the instructions, the corresponding brake performance data is extracted from the host computer for in-depth calculation and performance evaluation; then, the calculation results are compared and analyzed with similar data in the automobile data storage library; through the comprehensive analysis module, all data are comprehensively analyzed, and finally a detailed comprehensive evaluation report is generated.

2. The passenger car braking performance evaluation system according to claim 1, characterized in that: The data collection module is connected to the data acquisition module. This connection not only covers the collection of road test data such as braking distance and vehicle speed from special detection equipment such as speedometers (i.e., road detection methods), and the acquisition of bench test data such as axle load and maximum braking force from the brake test bench, but also involves analog-to-digital conversion of the collected braking data.

3. The passenger car braking performance evaluation system according to claim 1, characterized in that As follows: the data acquisition module establishes a connection with the data transmission module, and its main function is to receive the automobile braking performance data after analog-to-digital conversion and store these data in a data table format; In addition, it can retrieve and extract the corresponding braking performance data from the stored data table according to the type of test instruction input by the user.

4. The passenger car braking performance evaluation system according to claim 1, characterized in that: The sending module is connected to the computer module, and its function is to upload the processed automobile braking performance data to the central control host computer system.

5. The passenger car brake performance evaluation system according to claim 1, wherein the computer module is closely associated with the comparison module, and the computer module is composed of two major components: a memory and a processor. The memory is embedded with a specific computer program; the processor is responsible for executing the program, retrieving and processing the relevant braking performance data from the host computer according to the test instruction type set by the user, and then calculating the braking parameters of the vehicle.

6. The passenger car braking performance evaluation system according to claim 1, characterized in that: The comparison module is not only connected to the automobile big data system, but also to the comprehensive analysis module. Its main function is to compare the calculation results output by the computer module with the braking performance data of other similar passenger cars in the automobile big data, so as to determine the braking performance level of the passenger car in the current big data environment, that is, to determine whether it is in the upstream, midstream or downstream position, so as to intuitively reflect the braking performance of the passenger car and provide valuable reference information for users.

7. The passenger car braking performance evaluation system according to claim 1, characterized in that: The comprehensive analysis module is linked to the analysis report generation module. The comprehensive analysis module not only comprehensively compares the positioning information with the relevant data in the automobile big data, but also conducts a comprehensive and in-depth analysis from a security perspective.

8. The passenger car braking performance evaluation system according to claim 1, characterized in that As follows: The analysis report generation module is responsible for receiving the processing results from the comprehensive analysis module and generating a detailed evaluation report based on it. The report will clearly determine whether the braking performance of the evaluated passenger vehicle meets the established standards.

9. The passenger vehicle braking performance evaluation system according to claim 1, further characterized by The explanation is: The automobile database stores a huge amount of passenger car information, which covers the braking performance data of various types of vehicles, providing rich reference for the evaluation of passenger car braking performance, which not only significantly improves the efficiency of the evaluation, but also greatly enhances the accuracy of the evaluation results. The specific steps of the method for evaluating and analyzing the passenger car braking performance evaluation system based on automobile big data are described as follows: Step 1: Use special testing equipment such as a speedometer to collect key data such as braking distance and vehicle speed through road testing. At the same time, obtain necessary data such as axle load and maximum braking force from the brake test bench through bench testing. In the process of testing the braking performance of automobiles, sensors are responsible for capturing various analog signals during the braking process. These signals record in detail key parameters such as braking pressure, braking duration, and wheel rotation speed. However, since computers or host computers can only process digital signals, the collected analog signals need to be converted into digital signals through an analog-to-digital converter (ADC) for subsequent recognition and processing by the computer. This process is the analog-to-digital conversion of braking data. Step 2: The data acquisition module receives the analog-to-digital converted braking performance data and properly stores it in the form of a data table. Then, according to the type of test instruction entered by the user, the required performance data is accurately extracted from the data table and uploaded to the host computer system for subsequent analysis. Step 3: The host computer retrieves and extracts relevant performance data from the stored data according to the type of test instruction, and then calculates the braking parameters of the car. Subsequently, the comparison and positioning module compares these calculation results with the braking performance scores of all models in the car big data, and sorts them to clarify the braking performance ranking of the passenger car evaluated in this big data environment. This process can clearly reveal the advantages and disadvantages of the braking performance of the evaluated passenger car, and compare it with other passenger cars to highlight its advantages and disadvantages. Finally, based on the scoring and ranking results, combined with the evaluation criteria, a comprehensive judgment is made on whether the braking performance of the passenger car is qualified. Step 4: Input the evaluation results output by the comprehensive analysis module into the report generation module, which will automatically generate a detailed evaluation report for users to review and refer to.

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