Typical driving condition establishing method and equipment and readable storage medium

Abstract

The invention relates to a typical driving condition establishing method, establishing equipment and a readable storage medium. The typical driving condition establishment method comprises the following steps: S1, determining a test route and a test procedure, and setting a test evaluation point on the test route; s2, acquiring test working condition data of the test vehicle running on the test route; s3, dividing the test working condition data according to a plurality of segmented driving areas corresponding to the test evaluation points; s4, summarizing test working condition data in each segmented driving area to generate a driving working condition data file, establishing a driving working condition database of the segmented driving areas, and calculating driving working condition characteristics and an average value of the driving working condition data file; and S5, constructing a typical driving condition of the test route based on the driving condition database. According to the invention, the typical driving condition of the test route can be constructed, so that the driving characteristics in the actual test can be accurately reflected.

Description

Technical Field

[0001] The present invention relates to the field of driving test technology, and in particular to a typical driving condition establishment method, establishment equipment and a readable storage medium. Background Art

[0002] There are currently two mainstream technologies in the existing technology field:

[0003] 1. Driving Condition Construction Method Based on Cluster Analysis

[0004] The method first preprocesses the collected vehicle operating condition data, including short trip division and feature parameter extraction. Then, the characteristic parameters are reduced in dimension using principal component analysis (PCA), and clustering analysis methods (such as K-means clustering, improved binary K-means clustering or fuzzy clustering) are used to cluster short trips based on the dimensionality reduction results. Finally, several short trips are selected from each cluster category and combined into representative driving conditions.

[0005] 2. Driving Condition Construction Method Based on Markov Analysis

[0006] This method also extracts short-trip or kinematic segment data from the preprocessed vehicle operating condition data and classifies these data. Then, a state transition probability matrix between different road condition types or kinematic segments is established, and driving conditions are generated based on Markov chain theory.

[0007] Problems with the two mainstream technologies

[0008] Limitations of cluster analysis methods: Clustering results are greatly affected by input feature parameters and clustering algorithm principles. Multiple clustering processes may lead to inconsistent results and randomness. The data classification generated by the clustering algorithm may not be clear enough and deviate from the actual categories of actual road driving conditions.

[0009] Limitations of the Markov analysis method: This method relies on the state transition probability matrix, and the generated driving conditions are highly random, making it difficult to accurately reflect the characteristics of typical driving conditions. Due to the strong randomness, the generated conditions may not fully reflect the typicality and representativeness of actual driving.

[0010] The above two methods are suitable for constructing representative driving conditions from a large amount of random driving condition data, usually based on a large range of diverse actual user driving data, and require the driving route to be highly random and extensive. However, for the road test of passenger car brake comfort evaluation, the test route is usually fixed (such as the mountain road test route in Huangshan City or the specific urban road test route), which makes the traditional cluster analysis and Markov analysis methods no longer applicable. In addition, in actual tests, due to differences in road traffic environment, test time and driver driving style, even on the same route, the driving condition characteristics of each test will be different. Therefore, a method is needed to construct a typical driving condition based on multiple test data. The condition should be closest to the average level of driving conditions that may be encountered during all tests, so as to be more representative.

[0011] Summarize

[0012] Existing methods perform well in scenarios with strong randomness, but are difficult to meet the needs in fixed-route tests. Therefore, a new method that can extract typical driving conditions from multiple test data is urgently needed to more accurately reflect the driving characteristics in actual tests. Summary of the invention

[0013] In view of the above problems in the prior art, the present invention proposes a typical driving condition establishment method, establishment device and readable storage medium to accurately reflect the driving characteristics in actual tests.

[0014] Specifically, the present invention proposes a typical driving condition establishment method, which is applied to the comfort road test and evaluation of the vehicle braking system, comprising the steps of:

[0015] S1, determine the test route and test procedures, and set test evaluation points on the test route;

[0016] S2, collecting test operating condition data of the test vehicle traveling on the test route;

[0017] S3, dividing the test operating condition data according to a plurality of segmented driving areas corresponding to the test evaluation points;

[0018] S4, summarizing the test operating condition data in each segmented driving area to generate a driving condition data file, establishing a driving condition database for the segmented driving area, and calculating driving condition characteristics and average values ​​of the driving condition data file;

[0019] S5: constructing a typical driving condition of the test route based on the driving condition database.

[0020] According to an embodiment of the present invention, in step S1, a plurality of test evaluation points are set to divide the test section into the plurality of segmented driving areas.

[0021] According to one embodiment of the present invention, in step S2, the test vehicle is equipped with sensors and test equipment, and the sensors and test equipment include a pressure sensor, a thermocouple, a GPS, a deceleration sensor, a vibration acceleration sensor, a microphone sensor and an ambient temperature and humidity sensor. The pressure sensor is arranged on the brake pipeline of the test vehicle to record the brake pressure, the thermocouple is arranged in the wheel brake disc of the test vehicle to record the temperature, the GPS is installed on the test vehicle to record the speed, the deceleration sensor is installed in the vehicle to record the braking intensity of the whole vehicle, the vibration acceleration sensor is installed on the brake to record the vibration data when the noise occurs, the microphone sensor is installed at the co-pilot headrest position to record the noise data, and the ambient temperature and humidity sensor is installed on the roof to record the ambient temperature and humidity when the noise occurs.

[0022] According to an embodiment of the present invention, in step S2, the collected test condition data is cleaned.

[0023] According to an embodiment of the present invention, in step S3, based on the plurality of segmented driving areas, the vehicle driving condition data of each segmented driving area is identified and extracted.

[0024] According to one embodiment of the present invention, in step S4, the driving condition characteristics include the average vehicle speed, average deceleration and brake disc temperature ratio of the test vehicle, and a statistical analysis of the driving condition characteristics in each of the segmented driving areas is carried out to determine the average value of each of the driving condition characteristics in each of the segmented driving areas.

[0025] According to an embodiment of the present invention, in step S5, constructing a typical driving condition of the test route specifically includes:

[0026] S51, calculating the deviation of the driving condition characteristics of each segmented driving area based on the driving condition data file corresponding to each segmented driving area in the driving condition database;

[0027] S52, calculating the total deviation of all driving condition characteristics of the segmented driving area;

[0028] S53, identifying the driving condition data file corresponding to the lowest total deviation in each segmented driving area and determining it as the typical driving condition of the segmented driving area;

[0029] S54, splicing the segmented driving areas in sequence.

[0030] According to one embodiment of the present invention, in step S51, the deviation degree b of the driving condition characteristics of the segmented driving area is i The calculation formula is:

[0031]

[0032] Among them, p i is the specific value of the i-th characteristic parameter, d i_median is the median value of the statistical characteristic interval of the ith driving condition characteristic of the segmented driving area, d i_range is the statistical characteristic interval variation range value of the ith driving condition characteristic of the segmented driving area;

[0033] d i_median =(d i_up +d i_down ) / 2;

[0034] d i_range =d i_up -d i_ d own ;

[0035] Among them, d i_down is the lower limit of the statistical characteristic interval of the ith driving condition characteristic of the segmented driving area, d i_up is the upper limit value of the statistical characteristic interval of the i-th driving condition characteristic of the segmented driving area;

[0036] In step S52, the total deviation B j The calculation formula is:

[0037]

[0038] Where n represents the total number of driving condition characteristics studied in the segmented driving area.

[0039] The present invention also provides a typical driving condition establishment device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the aforementioned typical driving condition establishment methods when executing the computer program.

[0040] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the aforementioned methods for establishing a typical driving condition are implemented.

[0041] The present invention provides a typical driving condition establishment method, establishment device and readable storage medium, which set test evaluation points on the test route, divide the collected test condition data according to multiple segmented driving areas corresponding to the test evaluation points, calculate the driving condition characteristics, establish a driving condition database of the segmented driving areas, and construct a typical driving condition of the test route based on the driving condition database, so as to accurately reflect the driving characteristics in the actual test.

[0042] It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are included to provide further explanation of the present invention, and are incorporated into and constitute a part of this application. The accompanying drawings illustrate embodiments of the present invention and together with the description serve to explain the principle of the present invention.

[0044] In the attached figure:

[0045] Figure 1 A flowchart of a method for establishing a typical driving condition according to an embodiment of the present invention is shown.

[0046] Figure 2 A schematic diagram of driving condition data collected on a test route according to an embodiment of the present invention is shown.

[0047] Figure 3 A schematic diagram of a typical driving condition constructed by a test route according to an embodiment of the present invention is shown.

[0048] Figure 4 for Figure 2 Statistical histogram of the average vehicle speed in the segmented driving area from test evaluation points P2 to P3 (Yangzhanling-Guocun).

[0049] Figure 5 for Figure 2 Statistical histogram of the average deceleration in the segmented driving area from test evaluation points P2 to P3 (Yangzhanling-Guocun).

[0050] Figure 6 for Figure 2 Statistical histogram of the front brake disc temperature and the rear brake disc temperature in the segmented driving area of ​​the test evaluation points P2 to P3 (Yangzhanling-Guocun).

[0051] Figure 7 for Figure 2 Statistical histogram of the average vehicle speed in the segmented driving area from test evaluation points P6 to P7 (Huangshan District-Xiuning County).

[0052] Figure 8 for Figure 2 Statistical histogram of the average deceleration in the segmented driving area from the test evaluation points P6 to P7 (Huangshan District-Xiuning County).

[0053] Fig. 9 for Figure 2 Statistical histogram of the front brake disc temperature and the rear brake disc temperature in the segmented driving area of ​​the test evaluation points P6 to P7 (Huangshan District-Xiuning County).

[0054] Fig.10 A schematic diagram showing typical driving condition selection of a test route according to an embodiment of the present invention is shown.

[0055] Fig.11 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P1 to P2 (Xiuning County-Yixian County).

[0056] Fig.12 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P2 to P3 (Yixian-Yangzhanling).

[0057] Fig.13 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P3 to P4 (Yangzhanling-Guocun).

[0058] Fig.14 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P4 to P5 (Guocun-Huangshan District).

[0059] Fig.15 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P5 to P6 (hot state-cold state in Huangshan District).

[0060] Fig.16 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P6 to P7 (Huangshan District-Xiuning County). DETAILED DESCRIPTION

[0061] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other.

[0062] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present application and its application or use. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0063] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0064] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps set forth in these embodiments do not limit the scope of the application. Meanwhile, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to actual proportional relationships. The technology, methods and equipment known to those of ordinary skill in the relevant art may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be considered as a part of the specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0065] In the description of the present application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction, and therefore cannot be understood as limiting the scope of protection of the present application; the directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0066] In addition, it should be noted that the use of words such as "first" and "second" to define components is only for the convenience of distinguishing the corresponding components. If not otherwise stated, the above words have no special meaning and cannot be understood as limiting the scope of protection of this application. In addition, although the terms used in this application are selected from well-known and commonly used terms, some terms mentioned in the specification of this application may be selected by the applicant at his or her discretion, and their detailed meanings are explained in the relevant parts of the description of this article. In addition, it is required to understand this application not only by the actual terms used, but also by the meaning implied by each term.

[0067] Figure 1 A flowchart of a typical driving condition establishment method according to an embodiment of the present invention is shown. As shown in the figure, a typical driving condition establishment method is applied to the comfort road test and evaluation of the vehicle braking system, including the following steps:

[0068] S1, determine the test route and test procedures, and set test evaluation points on the test route. The test route is a fixed route, and the entire test route contains multiple test evaluation points. Figure 2 A schematic diagram of driving condition data collected under a test route of an embodiment of the present invention is shown. As shown in the figure, in this example, 7 test evaluation points P1 to P7 are set on the test route. These test evaluation points divide the entire test route into 6 segmented driving areas, such as "Xiuning County-Yixian County", "Yixian County-Yangzhanling", etc. As an example and not a limitation, more or fewer test evaluation points can be selected for the set test route to conduct road tests. The test procedure is a set of standardized operating procedures and rules formulated to ensure the scientificity, standardization and safety of road tests. The test procedure is used to clarify the test objectives, methods, conditions, data collection methods, and result evaluation standards. At the test evaluation point, the test personnel conduct noise searches and subjective evaluations in accordance with the test procedures.

[0069] S2, collect the test condition data of the test vehicle driving on the test route. During the entire test process, the test data is continuously collected and recorded by the test vehicle, and these test data are collectively referred to as test condition data. Generally, the brake comfort road test requires the test mileage to reach tens of thousands of kilometers, and different drivers carry out the test in turn according to the test schedule. The test route and test procedures followed by each test shift are consistent, so multiple sets of test condition data will be obtained on the same test route.

[0070] S3, divide the test condition data according to the multiple segmented driving areas corresponding to the test evaluation points. Perform data division on all collected test condition data. In this example, the test condition data is divided into 6 segmented driving areas and saved independently as a data file. The purpose of data division is to divide the entire test route into multiple segmented driving areas based on the test evaluation points, and identify and extract the test condition data of each segmented driving area. It should be noted that the test condition data generated when the test vehicle conducts noise search and subjective evaluation at the evaluation point will not be considered.

[0071] S4, summarizing the test operating condition data in each segmented driving area to generate a driving condition data file, establishing a driving condition database for the segmented driving area, and calculating driving condition characteristics and average values ​​of the driving condition data file.

[0072] S5, constructing a typical driving condition of the test route based on the driving condition database.

[0073] In some examples, in step S2, the test vehicle is equipped with sensors and test equipment to obtain test condition data. The sensors and test equipment include pressure sensors, thermocouples, GPS, deceleration sensors, vibration acceleration sensors, microphone sensors, and ambient temperature and humidity sensors. Among them, the pressure sensor is set on the brake line of the test vehicle to record the brake pressure, the thermocouple is set in the wheel brake disc of the test vehicle to record the temperature, the GPS is installed on the test vehicle to record the speed, the deceleration sensor is installed in the vehicle to record the braking intensity of the whole vehicle, the vibration acceleration sensor is installed on the brake to record the vibration data when the noise occurs, the microphone sensor is installed at the co-pilot headrest position to record the noise data, and the ambient temperature and humidity sensor is installed on the roof to record the ambient temperature and humidity when the noise occurs.

[0074] In some examples, in step S2, the collected test condition data is cleaned. The main purpose of data cleaning is to identify abnormal data and remove it. For example, abnormal vehicle speed or abnormal acceleration and deceleration, etc. In addition, it also includes identifying missing data and excluding test conditions with missing data from statistical analysis and condition construction to ensure the development quality of typical driving conditions.

[0075] In some examples, at step S3 , based on the plurality of segmented driving areas, vehicle driving condition data of each segmented driving area is identified and extracted.

[0076] In some examples, in step S4, based on the test procedure, the driving condition characteristics include the average speed, average deceleration and brake disc temperature ratio of the test vehicle. Conduct statistical analysis of the driving condition characteristics in each segmented driving area, and determine the average value of each driving condition characteristic in each segmented driving area. In order to gain a deeper understanding of the performance of the test vehicle in different driving scenarios, it is necessary to conduct statistical analysis of the driving condition characteristics in each segmented driving area. For example, in the segmented driving area of ​​the congested road section, the test vehicle frequently starts and stops, and the average speed is relatively low. At this time, each speed change and deceleration action are recorded, and a large amount of sample data is collected to determine the average value of the average speed in the area. Similarly, for the average deceleration, in various deceleration situations such as the test vehicle following the vehicle slowly, braking suddenly at a traffic light, etc., the deceleration value is recorded in detail, and then the average value is obtained to intuitively reflect the frequency of braking of the test vehicle under congested road conditions. In addition, in the segmented driving area of ​​the continuous downhill section in the mountainous area, the test vehicle brakes for a long time, and the brake disc temperature is very easy to rise. With the help of thermocouples for real-time monitoring, the brake disc temperature data can be collected at fixed intervals, and the brake disc temperature ratio can be calculated based on the mileage of the test vehicle. After measurement and statistics, the average value of each driving condition characteristic in this segmented driving area is finally accurately determined. By determining the average value of each driving condition characteristic in different scenarios such as different segmented driving areas, such as straight roads on highways and curves in urban-rural junctions, it is conducive to establishing typical driving conditions, which can provide solid data support for vehicle performance optimization, safety improvement and many other aspects in the future.

[0077] In some examples, in step S5, a typical driving condition of the test route is constructed, specifically including:

[0078] S51, based on the driving condition data file corresponding to each segmented driving area in the driving condition database, calculate the deviation of the driving condition characteristics of the segmented driving area. For example, if the theoretical reference value of the average vehicle speed is 30km / h, and the average vehicle speed calculated from the actual collected data is 28km / h, the deviation of the driving condition characteristic of the vehicle speed in the segmented driving area can be calculated through a specific mathematical model and algorithm, and other characteristics such as average deceleration and brake disc temperature ratio are calculated in the same way.

[0079] S52, calculating the total deviation of all driving condition characteristics of the segmented driving area to comprehensively reflect the degree of deviation between the segmented driving condition and the ideal state.

[0080] S53, identifying the driving condition data file corresponding to the lowest total deviation in each segmented driving area and determining it as the typical driving condition in the segmented driving area. That is, in each segmented driving area, identifying the driving condition data file corresponding to the data combination with the lowest total deviation and determining it as the typical driving condition in the segmented driving area.

[0081] S54, splicing the segmented driving areas in sequence. After each segmented driving area has determined its own typical driving conditions, these typical driving conditions are spliced ​​together according to the established test route sequence to construct a typical driving condition for a complete test route, which provides a basis for subsequent vehicle testing, performance optimization and many other scientific research and engineering practices. It should be noted that the test evaluation point conditions connecting different segmented driving areas are replaced by idle conditions, and the idle condition time is recommended to be set to at least 3 minutes. Figure 3 A schematic diagram of a typical driving condition constructed by a test route according to an embodiment of the present invention is shown.

[0082] In some examples, in step S51, the deviation b of the driving condition characteristics of the segmented driving area i The calculation formula is:

[0083]

[0084] Among them, p i is the specific value of the i-th characteristic parameter, d i_median is the median value of the statistical characteristic interval of the ith driving condition characteristic of the segmented driving area, d i_range is the statistical characteristic interval variation range value of the ith driving condition characteristic of the segmented driving area;

[0085] d i_median =(d i_up +d i_down ) / 2;

[0086] d i_range =d i_up -d i_down ;

[0087] Among them, d i_down is the lower limit of the statistical characteristic interval of the ith driving condition characteristic of the segmented driving area, d i_up is the upper limit of the statistical characteristic interval of the i-th driving condition characteristic of the segmented driving area;

[0088] In step S52, the total deviation B j The calculation formula is:

[0089]

[0090] Here n represents the total number of driving condition characteristics studied in a specific segmented driving area. In other words, the deviation of each characteristic parameter is accumulated and summed to obtain the total deviation B j It can reflect the deviation between the driving condition of the segmented driving area and the ideal state as a whole.

[0091] The present invention mainly focuses on the test condition characteristics of the road test and evaluation of the brake comfort of passenger cars, proposes to use the test evaluation points as the basis for dividing each segmented driving area in the test route, divides a large amount of test condition data according to different segmented driving areas, and establishes a driving condition database for different segmented driving areas. The driving condition data of different segmented driving areas are taken as the research object, and the main characteristic parameters of the driving condition are counted. The driving condition characteristics at least include the average vehicle speed, the average deceleration and the brake disc temperature ratio. Figure 4 for Figure 2 Statistical histogram of the average vehicle speed in the segmented driving area from test evaluation points P2 to P3 (Yangzhanling-Guocun). Figure 5 for Figure 2 Statistical histogram of the average deceleration in the segmented driving area from test evaluation points P2 to P3 (Yangzhanling-Guocun).

[0092] Figure 6 for Figure 2 The statistical histogram of the front brake disc temperature and rear brake disc temperature in the segmented driving area from P2 to P3 (Yangzhanling-Guocun) in the test evaluation point. As shown in the figure, the average vehicle speed in the segmented driving area from P2 to P3 (Yangzhanling-Guocun) is mainly concentrated in 40-60km / h, the average deceleration in the deceleration section is mainly concentrated in -1.2-0.8m / s2, the front brake disc temperature is mainly concentrated in 50-250℃, and the rear brake disc temperature is mainly concentrated in 50-300℃.

[0093] Figure 7 for Figure 2 Statistical histogram of the average vehicle speed in the segmented driving area from test evaluation points P6 to P7 (Huangshan District-Xiuning County). Figure 8 for Figure 2 Statistical histogram of the average deceleration in the segmented driving area from the test evaluation points P6 to P7 (Huangshan District-Xiuning County). Fig. 9 for Figure 2 The statistical histogram of the front brake disc temperature and rear brake disc temperature in the segmented driving area of ​​the test evaluation point P6 to P7 (Huangshan District-Xiuning County). As shown in the figure, the average vehicle speed in the segmented driving area of ​​P6 to P7 (Huangshan District-Xiuning County) is mainly concentrated in 40-60km / h, the average deceleration in the deceleration section is mainly concentrated in -0.8-0.55m / s2, the front axle brake disc temperature is mainly concentrated in 0-200℃, and the rear axle brake disc temperature is mainly concentrated in 0-250℃.

[0094] Based on the driving condition characteristics of each segmented driving area, the present invention proposes a typical driving condition data file screening method based on multi-driving condition characteristic deviation recognition, which realizes the rapid automatic selection of typical driving conditions for different segmented driving areas. By using this method, the selected typical driving condition is closer to the statistical average value of the driving condition characteristics of the segmented driving area from the multi-parameter characteristic dimension, making the determination process of the typical driving condition more scientific and reasonable. Fig.10 A schematic diagram of typical driving condition selection of a test route of an embodiment of the present invention is shown. As shown in the figure, driving condition data of each segmented driving area is displayed from three driving condition characteristic latitudes (average vehicle speed, average acceleration in acceleration section, and average deceleration in deceleration section).

[0095] Fig.11 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P1 to P2 (Xiuning County-Yixian County). Fig.12 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P2 to P3 (Yixian-Yangzhanling). Fig.13 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P3 to P4 (Yangzhanling-Guocun). Fig.14 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P4 to P5 (Guocun-Huangshan District). Fig.15 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P5 to P6 (hot state-cold state in Huangshan District). Fig.16 for Figure 2 Schematic diagram of the selection results of typical driving conditions in the segmented driving area of ​​the test evaluation points P6 to P7 (Huangshan District-Xiuning County). Figures 11 to 16 The selection results of typical driving conditions from three driving condition characteristic dimensions (average vehicle speed, average acceleration in the acceleration section, and average deceleration in the deceleration section) of each segmented driving area (Xiuning County-Yixian County, Yixian County-Yangzhanling, Yangzhanling-Guocun, Guocun-Huangshan District, Huangshan District hot state-cold state, and Huangshan District-Xiuning County) are shown respectively.

[0096] The present invention also provides a typical driving condition establishment device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of any of the aforementioned typical driving condition establishment methods are implemented.

[0097] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the aforementioned typical driving condition establishment methods are implemented.

[0098] Among them, the specific implementation methods and technical effects of the typical driving condition establishing device and computer-readable storage medium can all be referred to the embodiments of the typical driving condition establishing method provided by the present invention above, and will not be repeated here.

[0099] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or a combination of the two. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps are generally described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. The technician may implement the described functionality in different ways for each specific application, but such implementation decisions should not be interpreted as resulting in a departure from the scope of the present invention.

[0100] The various illustrative logic modules and circuits described in conjunction with the embodiments disclosed herein may be implemented or executed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in cooperation with a DSP core, or any other such configuration.

[0101] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read and write information from / to the storage medium. In an alternative, a storage medium may be integrated into a processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside in a user terminal as discrete components.

[0102] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented as a computer program product in software, each function may be stored on or transmitted by a computer-readable medium as one or more instructions or codes. Computer-readable media include both computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one place to another. Storage media may be any available medium that can be accessed by a computer. As an example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if the software is transmitted from a website, a server, or other remote source using a coaxial cable, a fiber optic cable, a twisted pair, a digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. Disk and disc as used herein include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wherein disk often reproduces data magnetically, while disc reproduces data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0103] It will be apparent to those skilled in the art that various modifications and variations may be made to the above exemplary embodiments of the present invention without departing from the spirit and scope of the present invention. Therefore, it is intended that the present invention covers modifications and variations of the present invention that fall within the scope of the appended claims and their equivalent technical solutions.

Claims

1. A typical driving condition establishment method, which is used for road test and evaluation of vehicle braking system comfort, comprises the following steps: S1, determine the test route and test procedures, and set test evaluation points on the test route; S2, collecting test operating condition data of the test vehicle traveling on the test route; S3, dividing the test operating condition data according to a plurality of segmented driving areas corresponding to the test evaluation points; S4, summarizing the test operating condition data in each segmented driving area to generate a driving condition data file, establishing a driving condition database for the segmented driving area, and calculating driving condition characteristics and average values ​​of the driving condition data file; S5: constructing a typical driving condition of the test route based on the driving condition database.

2. The typical driving condition establishment method according to claim 1, characterized in that: In step S1, a plurality of test evaluation points are set, and the test road section is divided into the plurality of segmented driving areas.

3. The typical driving condition establishment method according to claim 1, characterized in that: In step S2, the test vehicle is equipped with sensors and test equipment, which include a pressure sensor, a thermocouple, a GPS, a deceleration sensor, a vibration acceleration sensor, a microphone sensor and an ambient temperature and humidity sensor. The pressure sensor is arranged on the brake pipe of the test vehicle to record the brake pressure, the thermocouple is arranged in the wheel brake disc of the test vehicle to record the temperature, the GPS is installed on the test vehicle to record the speed, the deceleration sensor is installed in the vehicle to record the braking intensity of the whole vehicle, the vibration acceleration sensor is installed on the brake to record the vibration data when the noise occurs, the microphone sensor is installed at the co-pilot headrest position to record the noise data, and the ambient temperature and humidity sensor is installed on the roof to record the ambient temperature and humidity when the noise occurs.

4. The method for establishing a typical driving condition according to claim 1, characterized in that: In step S2, data cleaning is performed on the collected test condition data.

5. The typical driving condition establishment method according to claim 1, characterized in that: In step S3, based on the plurality of segmented driving areas, vehicle driving condition data of each segmented driving area is identified and extracted.

6. The typical driving condition establishment method according to claim 1, characterized in that: In step S4, the driving condition characteristics include the average vehicle speed, average deceleration and brake disc temperature ratio of the test vehicle, and a statistical analysis of the driving condition characteristics in each segmented driving area is carried out to determine the average value of each driving condition characteristic in each segmented driving area.

7. The typical driving condition establishment method according to claim 1, characterized in that: In step S5, a typical driving condition of the test route is constructed, which specifically includes: S51, calculating the deviation of the driving condition characteristics of each segmented driving area based on the driving condition data file corresponding to each segmented driving area in the driving condition database; S52, calculating the total deviation of all driving condition characteristics of the segmented driving area; S53, identifying the driving condition data file corresponding to the lowest total deviation in each segmented driving area and determining it as the typical driving condition of the segmented driving area; S54, splicing the segmented driving areas in sequence.

8. The method for establishing a typical driving condition according to claim 7, characterized in that: In step S51, the deviation degree b of the driving condition characteristics of the segmented driving area is i The calculation formula is: Among them, p i is the specific value of the i-th characteristic parameter, d i_median is the median value of the statistical characteristic interval of the ith driving condition characteristic of the segmented driving area, d i_range is the statistical characteristic interval variation range value of the ith driving condition characteristic of the segmented driving area; d i_median =(d i_up +d i_down ) / 2; d i_range =d i_up -d i_down ; Among them, d i_down is the lower limit of the statistical characteristic interval of the ith driving condition characteristic of the segmented driving area, d i_up is the upper limit value of the statistical characteristic interval of the i-th driving condition characteristic of the segmented driving area; In step S52, the total deviation B j The calculation formula is: Where n represents the total number of driving condition characteristics studied in the segmented driving area.

9. A typical driving condition establishment device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for establishing a typical driving condition as described in any one of claims 1-8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the typical driving condition establishment method as described in any one of claims 1 to 8 are implemented.

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