Rigidity evaluation method and device of vehicle braking system, vehicle and storage medium

Abstract

The embodiment of the invention provides a rigidity evaluation method and device of a vehicle braking system, a vehicle and a storage medium, and belongs to the technical field of intelligent vehicles. The method comprises the following steps: acquiring a servo cylinder pressure estimated value, a servo cylinder pressure measured value and a brake fluid flow rate of a target brake system; performing rigidity prediction according to the rigidity correlation parameter and the servo cylinder pressure estimation value to obtain expected rigidity data; performing rigidity prediction according to the pressure measurement value of the servo cylinder and the flow velocity of the brake fluid to obtain actual rigidity data; according to the pressure measurement value of the servo cylinder, the expected rigidity data and the actual rigidity data, performing rigidity abnormity evaluation to obtain initial rigidity abnormity evaluation data; performing anomaly frequency detection according to the initial stiffness anomaly evaluation data to obtain stiffness anomaly frequency; and according to the stiffness anomaly times, the initial stiffness anomaly evaluation data and the data acquisition times, performing stiffness anomaly evaluation to obtain target stiffness anomaly evaluation data. According to the embodiment of the invention, the accuracy of target braking system rigidity evaluation can be improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent automobile technology, and in particular to a stiffness evaluation method and device for a vehicle braking system, a vehicle, and a storage medium. Background Art

[0002] The braking system on the vehicle has been widely used, and the braking system can provide the driver with a variety of braking functions, such as basic braking function, anti-lock function, vehicle stability function, etc. However, the braking function can only be realized under the condition that the hydraulic pipeline of the braking system is normal, and whether the hydraulic pipeline is normal can be judged by the stiffness of the braking system. When the stiffness is detected to be soft, it can be considered that the hydraulic pipeline is abnormal. However, in the related art, the stiffness of the braking system is directly estimated, and the accuracy of the directly estimated stiffness is low. Therefore, how to improve the accuracy of the stiffness evaluation of the braking system has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] The main purpose of the embodiments of the present application is to propose a stiffness evaluation method and device for a vehicle braking system, a vehicle and a storage medium, in order to achieve a more accurate stiffness evaluation.

[0004] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application provides a method for evaluating the stiffness of a vehicle braking system, the method comprising:

[0005] Collecting stiffness influence data of the target brake system; wherein the stiffness influence data includes: servo cylinder pressure estimation value, servo cylinder pressure measurement value, brake fluid flow rate;

[0006] Performing stiffness prediction according to preset stiffness association parameters and the servo cylinder pressure estimation value to obtain expected stiffness data;

[0007] Performing stiffness prediction according to the servo cylinder pressure measurement value and the brake fluid flow rate to obtain actual stiffness data;

[0008] Performing a stiffness abnormality assessment on the target brake system according to the servo cylinder pressure measurement value, the expected stiffness data, and the actual stiffness data to obtain preliminary stiffness abnormality assessment data;

[0009] Performing an abnormality frequency detection according to the preliminary stiffness abnormality assessment data to obtain the stiffness abnormality frequency;

[0010] The target braking system is subjected to a stiffness abnormality assessment according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and a preset data collection times, to obtain target stiffness abnormality assessment data; wherein the target stiffness abnormality assessment data characterizes the stiffness abnormality of the target braking system.

[0011] In some embodiments, performing a stiffness abnormality assessment on the target braking system according to the servo cylinder pressure measurement value, the expected stiffness data, and the actual stiffness data to obtain preliminary stiffness abnormality assessment data includes:

[0012] Performing data conversion on the expected stiffness data to obtain an expected elastic coefficient;

[0013] Performing data conversion on the actual stiffness data to obtain an actual elastic coefficient;

[0014] The target brake system is subjected to a stiffness abnormality assessment according to the servo cylinder pressure measurement value, the expected elastic coefficient, and the actual elastic coefficient to obtain the preliminary stiffness abnormality assessment data.

[0015] In some embodiments, performing a stiffness abnormality assessment on the target brake system according to the servo cylinder pressure measurement value, the expected elastic coefficient, and the actual elastic coefficient to obtain the preliminary stiffness abnormality assessment data includes:

[0016] Calculating a coefficient deviation threshold value according to a preset elastic coefficient associated parameter, the servo cylinder pressure measurement value and the expected elastic coefficient to obtain a first elastic coefficient deviation threshold value;

[0017] Perform deviation calculation according to the first elastic coefficient deviation threshold, the expected elastic coefficient and the actual elastic coefficient to obtain a second elastic coefficient deviation threshold;

[0018] Obtaining a ratio between the second elastic coefficient deviation threshold and the first elastic coefficient deviation threshold to obtain a deviation ratio;

[0019] The target brake system is subjected to a stiffness abnormality assessment based on the deviation ratio to obtain the preliminary stiffness abnormality assessment data.

[0020] In some embodiments, performing stiffness abnormality assessment on the target braking system according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and a preset data collection times to obtain target stiffness abnormality assessment data includes:

[0021] Perform abnormal duration detection according to the number of stiffness abnormalities and the number of data acquisitions, and determine an abnormal duration coefficient;

[0022] Performing stiffness abnormality frequency detection according to the abnormality duration coefficient and the preliminary stiffness abnormality evaluation data to obtain stiffness abnormality frequency data;

[0023] The target brake system is subjected to a stiffness abnormality assessment according to the stiffness abnormality frequency data to obtain the target stiffness abnormality assessment data.

[0024] In some embodiments, performing stiffness prediction according to the servo cylinder pressure measurement value and the brake fluid flow rate to obtain actual stiffness data includes:

[0025] Performing gradient detection on the servo cylinder pressure measurement value to obtain a servo cylinder pressure gradient value;

[0026] The stiffness detection is performed according to the servo cylinder pressure gradient value and the brake fluid flow rate to obtain the actual stiffness data.

[0027] In some embodiments, after performing stiffness abnormality assessment on the target braking system according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and the preset data collection times to obtain target stiffness abnormality assessment data, the method further includes:

[0028] Performing a stiffness abnormality assessment on the target braking system according to the target stiffness abnormality assessment data and a preset stiffness abnormality threshold to obtain a stiffness abnormality assessment result;

[0029] If the stiffness evaluation result indicates that the target braking system has a soft stiffness condition, generating a stiffness abnormality prompt message;

[0030] The first braking adjustment information fed back according to the abnormal stiffness prompt information is received, and the target braking system is brake-adjusted according to the first braking adjustment information.

[0031] In some embodiments, after performing stiffness abnormality assessment on the target braking system according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and the preset data collection times to obtain target stiffness abnormality assessment data, the method further includes:

[0032] Storing the target stiffness abnormality assessment data into a preset database;

[0033] receiving a power-on instruction, reading the target stiffness abnormality assessment data from the preset database according to the power-on instruction, and acquiring the current operating parameters of the target braking system;

[0034] generating second brake adjustment information according to the target stiffness abnormality evaluation data and the current operating parameters;

[0035] The target brake system is brake-adjusted according to the second brake-adjustment information.

[0036] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a stiffness evaluation device for a vehicle braking system, the device comprising:

[0037] A data acquisition module, used for collecting stiffness influence data of a target brake system; wherein the stiffness influence data includes: a servo cylinder pressure estimation value, a servo cylinder pressure measurement value, and a brake fluid flow rate;

[0038] An expected stiffness prediction module, used to perform stiffness prediction according to preset stiffness association parameters and the servo cylinder pressure estimation value to obtain expected stiffness data;

[0039] An actual stiffness prediction module, used to perform stiffness prediction according to the servo cylinder pressure measurement value and the brake fluid flow rate to obtain actual stiffness data;

[0040] a preliminary abnormality assessment module, configured to perform a stiffness abnormality assessment on the target braking system according to the servo cylinder pressure measurement value, the expected stiffness data and the actual stiffness data, to obtain preliminary stiffness abnormality assessment data;

[0041] An abnormal number detection module is used to perform abnormal number detection according to the preliminary stiffness abnormality evaluation data to obtain the stiffness abnormal number;

[0042] A target stiffness abnormality assessment module is used to perform a stiffness abnormality assessment on the target braking system according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and a preset data collection times to obtain target stiffness abnormality assessment data; wherein the target stiffness abnormality assessment data represents the stiffness abnormality of the target braking system.

[0043] To achieve the above-mentioned purpose, a third aspect of an embodiment of the present application proposes a vehicle, comprising a central control system and a target braking system; wherein the central control system is used to execute the stiffness assessment method of the vehicle braking system as described in the first aspect.

[0044] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the stiffness evaluation method of the vehicle braking system described in the first aspect.

[0045] The stiffness evaluation method and device of the vehicle braking system, the vehicle and the storage medium proposed in the present application calculate the expected stiffness data and the actual stiffness data, and make a preliminary stiffness abnormality evaluation on the target braking system according to the expected stiffness data, the actual stiffness data and the servo cylinder pressure measurement value, and then after obtaining the preliminary stiffness abnormality evaluation data after the preliminary stiffness abnormality evaluation, the stiffness abnormality evaluation of the target braking system is performed again based on the stiffness abnormality times of the preliminary stiffness abnormality evaluation data, the preliminary stiffness abnormality evaluation data and the data collection times. Therefore, not only is the stiffness abnormality evaluation of the target braking system performed in combination with various stiffness data, but also two stiffness abnormality evaluations are performed to achieve a more accurate stiffness evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of a vehicle brake system stiffness evaluation method provided in an embodiment of the present application;

[0047] Figure 2 yes Figure 1 Flow chart of step S103 in FIG.

[0048] Figure 3 yes Figure 1 Flow chart of step S104 in FIG.

[0049] Figure 4 yes Figure 3 Flow chart of step S303 in FIG.

[0050] Figure 5 yes Figure 1 Flow chart of step S106 in FIG.

[0051] Figure 6 is a flow chart of a vehicle brake system stiffness evaluation method provided by another embodiment of the present application;

[0052] Figure 7 is a flow chart of a vehicle brake system stiffness evaluation method provided by another embodiment of the present application;

[0053] Figure 8 is a structural schematic diagram of a vehicle brake system stiffness evaluation device provided in an embodiment of the present application;

[0054] Fig. 9 It is a schematic diagram of the hardware structure of the vehicle provided in the embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0056] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0058] First, some nouns involved in this application are analyzed:

[0059] Vehicle braking system: refers to a series of special devices that apply a certain force to certain parts of the vehicle (mainly the wheels) to force braking to a certain extent. The functions of the braking system are: to force the moving car to slow down or even stop according to the driver's requirements; to keep the stopped car stable under various road conditions (including on slopes); and to keep the speed of the car driving downhill stable.

[0060] Hydraulic brake: The brake is the so-called brake, which is a mechanical part that stops or slows down the moving parts in the machine. It is commonly known as brake or brake. The brake is mainly composed of a frame, brake parts and operating devices. Some brakes are also equipped with automatic adjustment devices for the clearance of brake parts.

[0061] Stiffness: refers to the ability of a material or structure to resist elastic deformation when subjected to force, and is a representation of the ease of elastic deformation of a material or structure. The stiffness of a material is usually measured by the elastic coefficient E. Within the macroscopic elastic range, stiffness is the proportional coefficient of the load and displacement of a part, that is, the force required to cause a unit displacement. The reciprocal of this force is called stiffness, that is, the displacement caused by a unit force.

[0062] Servo cylinder: It is a modular product that integrates the servo motor and the lead screw. It converts the rotational motion of the servo motor into linear motion. At the same time, it converts the best advantages of the servo motor - precise speed control, precise rotation speed control, and precise torque control - into precise speed control, precise position control, and precise thrust control.

[0063] With the development of vehicle intelligence, the braking system on the vehicle has been widely used, and the braking system can provide drivers with a variety of braking functions, such as basic braking function, anti-lock function, vehicle stability function, etc. However, the normal use of the braking function can only be achieved under the condition that the hydraulic pipeline is normal, and whether the hydraulic pipeline is normal can be determined by stiffness detection. However, in the related art, the stiffness of the hydraulic pipeline is directly estimated and determined, and the accuracy of the estimated stiffness is insufficient.

[0064] Based on this, the embodiments of the present application provide a stiffness evaluation method and device for a vehicle braking system, a vehicle, and a storage medium, which are intended to first calculate the expected stiffness data and the actual stiffness data, and perform a preliminary stiffness anomaly evaluation on the target braking system based on the expected stiffness data, the actual stiffness data, and the servo cylinder pressure measurement value, and then obtain the preliminary stiffness anomaly evaluation data after the preliminary stiffness anomaly evaluation, and then perform a stiffness anomaly evaluation on the target braking system again based on the stiffness anomaly times of the preliminary stiffness anomaly evaluation data, the preliminary stiffness anomaly evaluation data, and the data acquisition times. Therefore, not only is the stiffness anomaly evaluation of the target braking system performed in combination with various stiffness data, but the stiffness anomaly evaluation is performed twice to achieve a more accurate stiffness evaluation.

[0065] The stiffness evaluation method and device for the vehicle braking system, the vehicle and the storage medium provided in the embodiments of the present application are specifically illustrated through the following embodiments. First, the stiffness evaluation method for the vehicle braking system in the embodiments of the present application is described.

[0066] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0067] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0068] The stiffness evaluation method of the vehicle braking system provided in the embodiment of the present application relates to the field of artificial intelligence technology. The stiffness evaluation method of the vehicle braking system provided in the embodiment of the present application can be applied to the terminal, can also be applied to the server side, and can also be software running in the terminal or the server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the stiffness evaluation method of the vehicle braking system, etc., but is not limited to the above forms.

[0069] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0070] Figure 1 is an optional flow chart of the vehicle brake system stiffness evaluation method provided in the embodiment of the present application, Figure 1 The method may include but is not limited to steps S101 to S106.

[0071] Step S101, collecting stiffness influence data of a target brake system; wherein the stiffness influence data includes: a servo cylinder pressure estimation value, a servo cylinder pressure measurement value, and a brake fluid flow rate;

[0072] Step S102, performing stiffness prediction according to preset stiffness association parameters and servo cylinder pressure estimation values ​​to obtain expected stiffness data;

[0073] Step S103, performing stiffness prediction according to the servo cylinder pressure measurement value and the brake fluid flow rate to obtain actual stiffness data;

[0074] Step S104, performing a stiffness abnormality assessment on the target brake system according to the servo cylinder pressure measurement value, the expected stiffness data and the actual stiffness data, to obtain preliminary stiffness abnormality assessment data;

[0075] Step S105, performing an abnormality frequency detection according to the preliminary stiffness abnormality evaluation data to obtain the stiffness abnormality frequency;

[0076] Step S106, performing a stiffness abnormality assessment on the target braking system according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and the preset data collection times, to obtain target stiffness abnormality assessment data; wherein the target stiffness abnormality assessment data represents the stiffness abnormality of the target braking system.

[0077] Steps S101 to S106 shown in the embodiment of the present application are to collect the stiffness influence data of the target brake system, and the stiffness influence data includes the servo cylinder pressure estimation value, the servo cylinder pressure measurement value and the brake fluid flow rate, so as to predict the expected stiffness data based on the servo cylinder pressure estimation value and the stiffness associated parameters, and then predict the actual stiffness data based on the servo cylinder measurement value and the brake fluid flow rate, so as to make a preliminary stiffness anomaly assessment of the target brake system based on the expected stiffness data and the actual stiffness data, and realize automatic stiffness anomaly detection of the target brake system. In order to improve the accuracy of the stiffness assessment, after obtaining preliminary stiffness anomaly assessment data through preliminary stiffness anomaly assessment, the number of stiffness anomalies is determined through the preliminary stiffness anomaly assessment data, and then the stiffness anomaly assessment of the target brake system is performed again based on the number of stiffness anomalies, the preliminary stiffness anomaly assessment data and the number of data collection, so as to obtain the target stiffness anomaly assessment data as the stiffness assessment result of the target brake system. Therefore, in this embodiment, the actual stiffness data and the expected stiffness data are calculated to perform a preliminary stiffness anomaly assessment on the target braking system, and after the preliminary assessment, the stiffness anomaly assessment is performed again on the target braking system based on the number of stiffness anomalies in the preliminary assessment and the result of the preliminary stiffness anomaly assessment, so as to improve the accuracy of the stiffness assessment.

[0078] In step S101 of some embodiments, the stiffness evaluation of the target braking system is mainly determined by detecting the stiffness of the servo cylinder. It should be noted that the servo cylinder has a soft stiffness condition, which is usually caused by two reasons. The first reason is that the solenoid valve is effective, and the second reason is that the servo cylinder circuit leaks. Among them, the solenoid valve failure situation is: 1. The isolation valve is stuck or leaked. At this time, the valve port of the isolation method is opened. If the brake fluid in the servo cylinder is higher than the pressure of the master cylinder, the brake fluid in the servo cylinder flows into the oil pot, resulting in a soft stiffness condition in the servo cylinder; 2. The fluid replenishment check valve in the servo cylinder is stuck or leaked, and the brake fluid in the servo cylinder flows into the oil pot, resulting in a soft stiffness condition in the servo cylinder; 3. The normally closed valve of the anti-lock braking device (ABS) is opened or leaked, and the brake fluid in the servo cylinder flows back to the oil pot through the normally closed valve, resulting in a soft stiffness condition in the servo cylinder. The leakage of the servo cylinder circuit is specifically a leakage of the wheel cylinder circuit, resulting in a soft stiffness condition in the servo cylinder. Specifically, when the servo cylinder is soft, the braking effect of the target brake system is poor and cannot be judged in time, which leads to safety problems during driving. Therefore, the target brake system is evaluated for stiffness, and the data affecting the stiffness of the target brake system are mainly the pressure of the servo cylinder and the flow rate of the brake fluid. Therefore, the data affecting stiffness include: the estimated value of the servo cylinder pressure, the measured value of the servo cylinder pressure and the flow rate of the brake fluid.

[0079] It should be noted that the servo cylinder pressure estimation value needs to be calculated based on multiple pressure influence items of the servo cylinder. Specifically, the pressure influence items of other functional theories are collected through the servo cylinder estimation module to be calculated through multiple pressure influence items. The servo cylinder pressure measurement value is calculated by collecting multiple servo cylinder pressure pressure influence items through sensors after the servo cylinder is pushed, and the brake fluid flow rate is directly measured by the flow rate sensor. It can be seen that the servo cylinder pressure estimation value is calculated according to the theoretical pressure influence items, and the servo cylinder pressure measurement value is calculated by actually measuring multiple pressure influence items. Therefore, the servo cylinder pressure estimation value reflects the expected stiffness of the servo cylinder, and the servo cylinder pressure measurement value reflects the actual stiffness of the servo cylinder.

[0080] In step S102 of some embodiments, the stiffness-related parameter includes a pressure-to-stiffness coefficient, and the pressure-to-stiffness coefficient is a coefficient for converting the servo cylinder pressure into the servo cylinder stiffness. In this embodiment, a PV function is used for stiffness prediction, and the PV function characterizes the stiffness calculation values ​​corresponding to different pressure estimation values, and different types of stiffness calculations correspond to different PV functions. In this embodiment, the servo cylinder pressure calculation value is obtained by substituting the servo cylinder pressure estimation value into the PV function, and then the pressure-to-stiffness coefficient and the servo cylinder pressure calculation value are combined to perform a product calculation to obtain the expected stiffness data.

[0081] Specifically, the calculation process of the expected stiffness data is shown in formula (1):

[0082] Stifness1=K1*pvcurve(pmodel) (1)

[0083] Where Stifness1 is the expected stiffness data, K1 is the pressure-to-stiffness coefficient, pmodel is the estimated value of the servo cylinder pressure, and pvcurve() is the PV function.

[0084] See also Figure 2 In some embodiments, step S103 may include but is not limited to steps S201 to S202:

[0085] Step S201, performing gradient detection on the servo cylinder pressure measurement value to obtain the servo cylinder pressure gradient value;

[0086] Step S202 , performing stiffness detection according to the servo cylinder pressure gradient value and the brake fluid flow rate to obtain actual stiffness data.

[0087] In step S201 of some embodiments, there are multiple servo cylinder pressure measurement values, and the multiple servo cylinder pressure measurement values ​​are measured according to a preset time period, so the multiple servo cylinder pressure measurement values ​​represent the pressure conditions of the target braking system over a period of time. It should be noted that the servo cylinder pressure gradient value is obtained by performing gradient detection on the servo cylinder pressure measurement value, so as to represent the pressure change of the target braking system over a period of time through the servo cylinder pressure gradient value.

[0088] In step S202 of some embodiments, stiffness detection is performed using the servo cylinder pressure gradient value and the brake fluid flow rate, that is, the ratio between the servo cylinder pressure gradient value and the brake fluid flow rate is obtained as actual stiffness data, making the actual stiffness data easy to calculate and capable of characterizing the actual stiffness of the target braking system.

[0089] Specifically, the actual stiffness data calculation process is shown in formula (2):

[0090] Stifness2=pressuregradient / volumeflow (2)

[0091] Where Stifness2 is the actual stiffness data, pressuregradient is the servo cylinder pressure gradient value, and volumeflow is the brake fluid flow rate.

[0092] In steps S201 to S202 shown in this embodiment, the servo cylinder pressure gradient value is first determined from the difference between the servo cylinder pressure measurement values, and then the ratio between the servo cylinder pressure gradient value and the brake fluid flow rate is used as the actual stiffness data, so that the actual stiffness data can be calculated accurately and easily.

[0093] See also Figure 3 In some embodiments, step S104 may include but is not limited to steps S301 to S303:

[0094] Step S301, performing data conversion on the expected stiffness data to obtain the expected elastic coefficient;

[0095] Step S302, performing data conversion on the actual stiffness data to obtain the actual elastic coefficient;

[0096] Step S303 , performing a stiffness anomaly assessment on the target brake system according to the servo cylinder pressure measurement value, the expected elastic coefficient, and the actual elastic coefficient to obtain preliminary stiffness anomaly assessment data.

[0097] In steps S301 to S302 of some embodiments, the elastic coefficient can more intuitively characterize whether the servo bar is soft in rigidity, so as to determine the rigidity of the target braking system. Therefore, the expected rigidity data is converted into the expected elastic coefficient, and the actual rigidity data is converted into the actual elastic coefficient. The expected elastic coefficient is the elastic coefficient of the theoretical servo cylinder, and the actual elastic coefficient is the elastic coefficient actually measured by the servo cylinder, so as to detect whether the servo cylinder is soft in rigidity by the expected elastic coefficient and the actual elastic coefficient.

[0098] Specifically, the expected elastic coefficient is determined as shown in formula (3), and the actual elastic coefficient is determined as shown in formula (4), so that the operation of determining the expected elastic coefficient and the actual elastic coefficient is simple.

[0099] elase=1 / Stifness1 (3)

[0100] elasa=1 / Stifness2 (4)

[0101] Where elase is the expected elastic coefficient and elasa is the actual elastic coefficient.

[0102] In step S303 of some embodiments, the target brake system is evaluated for stiffness anomaly in combination with the servo cylinder pressure measurement value, the expected elastic coefficient, and the actual elastic coefficient, that is, the probability of the target brake system having a soft stiffness condition is calculated.

[0103] In steps S301 to S303 shown in the present embodiment, by converting the expected stiffness data into the expected elastic coefficient, converting the actual stiffness data into the actual stiffness coefficient, and performing a stiffness abnormality assessment on the target braking system in combination with the expected elastic coefficient, the actual stiffness coefficient and the servo cylinder pressure measurement value, a more accurate stiffness abnormality assessment of the target braking system can be achieved.

[0104] See also Figure 4 In some embodiments, step S303 may include but is not limited to steps S401 to S404:

[0105] Step S401, calculating a coefficient deviation threshold value according to preset elastic coefficient associated parameters, a servo cylinder pressure measurement value and an expected elastic coefficient, to obtain a first elastic coefficient deviation threshold value;

[0106] Step S402, performing deviation calculation according to the first elastic coefficient deviation threshold, the expected elastic coefficient and the actual elastic coefficient to obtain a second elastic coefficient deviation threshold;

[0107] Step S403, obtaining a ratio between the second elastic coefficient deviation threshold and the first elastic coefficient deviation threshold to obtain a deviation ratio;

[0108] Step S404: Perform a stiffness abnormality assessment on the target brake system based on the deviation ratio to obtain preliminary stiffness abnormality assessment data.

[0109] In steps S401 to S402 of some embodiments, the first elastic coefficient deviation threshold is a deviation threshold that characterizes the allowable range of deviation between the actual elastic coefficient of the servo cylinder and the expected elastic coefficient, that is, a theoretically allowable deviation range, and the second elastic coefficient deviation threshold characterizes the deviation threshold between the actual elastic coefficient of the servo cylinder and the expected elastic coefficient, that is, a deviation range that characterizes the actual allowable deviation between the actual elastic coefficient and the expected elastic coefficient. Therefore, whether the deviation between the elastic coefficients is too large can be determined by the second elastic coefficient deviation threshold.

[0110] In this embodiment, the tolerable deviation threshold is calculated by the deviation tolerance function, and then the first elastic coefficient deviation threshold is calculated by combining the deviation threshold, elastic coefficient associated parameter and expected elastic coefficient, that is, the allowable range of the elastic deviation theory is determined. The process of determining the first elastic coefficient deviation threshold is shown in formula (5):

[0111] ElasDeviation=P_ElasDeviation(ActualPressure)+K2*elase (5)

[0112] Where ElasDeviation is the first elastic coefficient deviation threshold, P_ElasDeviation() is the deviation tolerance function, K2 is the elastic coefficient association parameter, and elase is the expected elastic coefficient.

[0113] After the first elastic coefficient deviation threshold is determined, it is necessary to determine the actual allowable range of the deviation between the actual elastic coefficient and the expected elastic coefficient to determine whether the target braking system has a soft stiffness condition. It should be noted that if the actual allowable deviation range is greater than the theoretical allowable deviation range, it indicates that the servo cylinder has a soft stiffness condition. Therefore, the second elastic coefficient deviation threshold is calculated to calculate the allowable range of the actual deviation of the elastic coefficient. Among them, the second elastic coefficient deviation threshold is determined as shown in formula (6):

[0114] Threshold1=ElasDeviation-elasa+elase (6)

[0115] Where Threshold1 is the second elastic coefficient deviation threshold, ElasDeviation is the first elastic coefficient deviation threshold, elasa is the expected elastic coefficient, and elase is the actual elastic coefficient.

[0116] In step S403 of some embodiments, by obtaining the ratio between the first elastic coefficient deviation threshold and the second elastic coefficient deviation threshold, it is determined whether the theoretical elastic coefficient deviation is greater than the actual elastic coefficient deviation. It should be noted that if the theoretical elastic coefficient deviation is less than the actual elastic coefficient deviation, it indicates that the servo cylinder has a soft stiffness condition, and then it is determined that the target braking system has a soft stiffness condition. It should be noted that if the deviation ratio is greater than 1, it indicates that the first elastic coefficient deviation threshold is greater than the second elastic coefficient deviation threshold, and if it is less than 1, it indicates that the first elastic coefficient deviation threshold is less than the second elastic coefficient deviation threshold.

[0117] The deviation ratio is determined as shown in formula (7):

[0118] BufferRatio1=Threshold1 / ElasDeviation (7)

[0119] Wherein, BufferRatio1 is the deviation ratio, Threshold1 is the second elastic coefficient deviation threshold, and ElasDeviation is the first elastic coefficient deviation threshold.

[0120] In step S404 of some embodiments, the target brake system is evaluated for stiffness anomaly through the deviation ratio, that is, the deviation ratio is processed with upper and lower limit values ​​of 0-1 to obtain preliminary stiffness anomaly evaluation data to characterize the stiffness anomaly of the target brake system.

[0121] Specifically, the preliminary stiffness anomaly assessment data is determined as shown in formula (8):

[0122] BufferRatio2=min(max(BufferRatio1,0),1) (8)

[0123] Where BufferRatio2 is the preliminary stiffness abnormality evaluation data. The preliminary stiffness abnormality evaluation data is obtained by first taking the maximum value between the deviation ratio and the zero value, and then taking the minimum value between the maximum value and 1, so as to determine whether the target braking system has a stiffness abnormality, that is, a stiffness soft situation, by whether the minimum value is zero.

[0124] In steps S401 to S404 shown in this embodiment, the theoretical allowable deviation range is first calculated, and then the actual allowable deviation range is calculated. Then, the ratio between the theoretical and actual allowable deviation ranges is used to evaluate the stiffness abnormality of the target braking system, so that the stiffness abnormality evaluation of the target braking system is more accurate.

[0125] In step S105 of some embodiments, if the target brake system is detected to have a stiffness abnormality only once or several times, the stiffness abnormality of the servo cylinder is directly judged to be inaccurate, which may lead to the problem of inaccurate stiffness abnormality judgment. In this regard, the number of abnormalities is evaluated on the preliminary stiffness abnormality evaluation data to determine the number of stiffness abnormalities. When the number of stiffness abnormalities detected continuously is greater than a certain threshold, the servo cylinder is judged to have a stiffness abnormality to determine that the target brake system has a stiffness abnormality, thereby improving the stiffness evaluation accuracy of the target brake system. In this embodiment, it is determined whether the preliminary stiffness abnormality evaluation data is a zero value. If the preliminary stiffness abnormality evaluation data is a zero value, counting is started. Therefore, the number of stiffness abnormalities is the number of times the preliminary stiffness abnormality evaluation data is a zero value.

[0126] For example, the preliminary stiffness abnormality evaluation data is BufferRatio2. If BufferRatio2=0, start counting counter2=counter1+1 to obtain the stiffness abnormality times defined as counter2.

[0127] See also Figure 5 In some embodiments, step S106 may include but is not limited to steps S501 to S503:

[0128] Step S501, performing abnormal duration detection according to the number of stiffness abnormalities and the number of data collection times, and determining the abnormal duration coefficient;

[0129] Step S502, performing stiffness abnormality frequency detection according to the abnormality duration coefficient and the preliminary stiffness abnormality evaluation data to obtain stiffness abnormality frequency data;

[0130] Step S503 , performing a stiffness abnormality assessment on the target brake system according to the stiffness abnormality frequency data to obtain target stiffness abnormality assessment data.

[0131] In step S501 of some embodiments, the abnormal duration coefficient represents the frequency of the abnormal stiffness of the target braking system during the entire stiffness impact data collection process, and can reflect the abnormal stiffness of the target braking system. Specifically, the ratio between the number of abnormal stiffness times and the number of data collection tables is used as the abnormal duration coefficient. For example, the abnormal duration coefficient determination process is: debounceratio = counter / Threshold2; where debounceratio is the abnormal duration coefficient; Threshold2 is the number of data collection times.

[0132] In step S502 of some embodiments, in order to further calculate whether the abnormal stiffness of the servo cylinder in the target brake system is serious, the abnormal stiffness frequency data is calculated to characterize the serious stiffness of the abnormal stiffness of the target brake system through the abnormal stiffness frequency data. It should be noted that the closer the abnormal stiffness frequency data is to 1, the more serious the abnormal stiffness of the target brake system is, and if the abnormal stiffness frequency data is closer to 0, the stiffness of the target brake system is good.

[0133] Specifically, the abnormal duration coefficient and the preliminary abnormal stiffness evaluation data are combined to determine the abnormal stiffness frequency data as shown in formula (9):

[0134] ErrorRatio=0.1875*(1-BufferRatio2)+(0.8125*debounceratio)(9)

[0135] Where ErrorRatio is the stiffness anomaly frequency data, BufferRatio2 is the preliminary stiffness anomaly assessment data, and debounceratio is the anomaly duration coefficient.

[0136] In step S503 of some embodiments, a stiffness abnormality assessment is performed on the target braking system according to the stiffness abnormality frequency data, that is, the stiffness abnormality frequency data is used as target stiffness abnormality assessment data.

[0137] In steps S501 to S503 shown in the present embodiment, the abnormality persistence coefficient is first calculated to determine the duration of the target braking system stiffness abnormality, and then the stiffness abnormality frequency data characterizing the target braking system stiffness abnormality frequency is calculated based on the abnormality persistence coefficient and the preliminary stiffness abnormality evaluation data. The stiffness abnormality frequency data is used as the target stiffness abnormality evaluation data, which can more accurately characterize the target braking system stiffness abnormality and achieve accurate stiffness evaluation of the target braking system.

[0138] See also Figure 6 In some embodiments, after step S106, the vehicle brake system stiffness evaluation method further includes but is not limited to steps S601 to S603:

[0139] Step S601, performing a stiffness abnormality assessment on a target braking system according to the target stiffness abnormality assessment data and a preset stiffness abnormality threshold, and obtaining a stiffness abnormality assessment result;

[0140] Step S602, if the stiffness evaluation result indicates that the target brake system has a soft stiffness condition, generating a stiffness abnormality prompt message;

[0141] Step S603: receiving first braking adjustment information fed back according to the abnormal stiffness prompt information, and performing braking adjustment on the target braking system according to the first braking adjustment information.

[0142] In step S601 of some embodiments, the target stiffness abnormality evaluation data is compared with a preset stiffness abnormality threshold to obtain a stiffness abnormality evaluation result. It should be noted that if the target stiffness abnormality evaluation data is greater than or equal to the stiffness abnormality threshold, the stiffness abnormality evaluation result is determined to be characterized as a soft stiffness condition in the target braking system, that is, it is determined that the target braking system has a stiffness abnormality; if the target stiffness abnormality evaluation data is less than or equal to the stiffness abnormality threshold, the stiffness abnormality evaluation result is determined to be characterized as a normal stiffness condition in the target braking system. Therefore, by comparing the target stiffness abnormality evaluation data with the stiffness abnormality threshold to determine the stiffness abnormality evaluation data of the target braking system, the stiffness abnormality of the target braking system can be more accurately characterized.

[0143] In step S602 of some embodiments, if the stiffness evaluation result indicates that the target braking system has a soft stiffness condition, a stiffness abnormality prompt message is generated. It should be noted that the stiffness abnormality prompt message indicates that the target braking system has a stiffness abnormality, and the stiffness abnormality prompt message will be directly sent to the central control system of the vehicle and displayed on the vehicle terminal on the vehicle, prompting the driver that the target braking system has a stiffness abnormality, so that the driver can perform maintenance on the target braking system in a timely manner.

[0144] In step S603 of some embodiments, when the first brake adjustment information is received, that is, the driver makes an adjustment operation of adjusting the target brake system based on the abnormal stiffness prompt information on the vehicle terminal, so the target brake system is directly braked according to the first brake adjustment information, so that the target brake system can be restored to normal operation in time. It should be noted that the generation of the first brake adjustment information is not only based on the abnormal stiffness prompt information, but also combined with the data of other function feedback to improve the safety of vehicle driving.

[0145] In steps S601 to S603 shown in the present embodiment, when it is determined that the stiffness abnormality evaluation result of the target braking system indicates that the target braking system has a soft stiffness condition, stiffness abnormality prompt information is fed back to the driver, and first braking adjustment information fed back by the driver is received, so that the target braking system is adjusted through the first braking adjustment information, and manual adjustment of the target braking system is achieved, so that the target braking system can be restored to a normal state in a timely manner.

[0146] See also Figure 7 In some embodiments, after step S106, the stiffness evaluation method of the vehicle braking system may also include but is not limited to steps S701 to S704:

[0147] Step S701, storing target stiffness abnormality evaluation data into a preset database;

[0148] Step S702, receiving a power-on instruction, reading target stiffness abnormality assessment data from a preset database according to the power-on instruction, and obtaining current operating parameters of the target braking system;

[0149] Step S703, generating second brake adjustment information according to the target stiffness abnormality evaluation data and the current operating parameters;

[0150] Step S704: performing brake adjustment on the target brake system according to the second brake adjustment information.

[0151] In step S701 of some embodiments, after each output of the target stiffness abnormality evaluation data, the target stiffness abnormality evaluation data is stored in a preset database. It should be noted that the preset database is a read-only memory (EEROM).

[0152] In step S702 of some embodiments, each time the vehicle is powered on, that is, when a power-on command is received, the target stiffness abnormality evaluation data is read from a preset database, so that the stiffness condition of the last evaluation can be determined each time the vehicle is powered on. After the target stiffness abnormality evaluation data is retrieved, the current operating parameters of the target braking system are obtained, and the current operating parameters represent the current operating condition of the target braking system.

[0153] In steps S703 to S704 of some embodiments, the second brake adjustment information is generated in combination with the target stiffness abnormality evaluation data and the current operating parameters, and the target brake system is adjusted according to the second brake adjustment information. Therefore, each time the vehicle is powered on, the target brake system is automatically adjusted so that the target brake system can operate normally, thereby improving the safety of the vehicle during driving.

[0154] In steps S701 to S704 shown in the present embodiment, the target stiffness abnormality assessment data output each time is stored in a preset database, the target stiffness abnormality assessment data stored last time is retrieved after each power-on, and the second braking adjustment information is generated in combination with the current operating parameters of the target braking system. The target braking system is automatically adjusted according to the second braking adjustment information, so that the target braking system is automatically adjusted after each power-on, so that the target braking system can operate normally, thereby improving the safety of the vehicle driving process.

[0155] The embodiment of the present application collects the estimated value of the servo cylinder pressure, the servo cylinder pressure coefficient and the brake fluid flow rate of the target brake system, substitutes the estimated value of the servo cylinder pressure into the PV function to obtain the calculated value of the servo cylinder pressure, and then multiplies the pressure conversion stiffness coefficient and the calculated value of the servo cylinder pressure to obtain the expected stiffness data. The servo cylinder pressure gradient value is obtained by performing gradient detection on the servo cylinder pressure measurement value, and the ratio between the servo cylinder pressure gradient value and the brake fluid flow rate is obtained as the actual stiffness data. Further, the expected stiffness data is converted into the expected elastic coefficient, and the actual stiffness data is converted into the actual elastic coefficient. The first elastic coefficient deviation threshold is obtained by combining the deviation threshold, the elastic coefficient associated parameter and the expected elastic coefficient, that is, the theoretical allowable range of the elastic deviation is determined. The deviation is calculated according to the first elastic coefficient deviation threshold, the expected elastic coefficient and the actual elastic coefficient to obtain the second elastic coefficient deviation threshold to determine the actual allowable range of the elastic coefficient deviation. The ratio between the first elastic coefficient deviation threshold and the second elastic coefficient deviation threshold is obtained to obtain the deviation ratio, and then the deviation ratio is processed with 0-1 upper and lower limit values ​​to obtain preliminary stiffness abnormality evaluation data. By judging whether the preliminary stiffness abnormality assessment data is a zero value, if the preliminary stiffness abnormality assessment data is a zero value, starting to count to obtain the number of stiffness abnormalities, and then taking the ratio between the number of stiffness abnormalities and the number of times in the data collection table as the abnormality duration coefficient, and performing stiffness abnormality frequency detection based on the abnormality duration coefficient and the preliminary stiffness abnormality assessment data to obtain stiffness abnormality frequency data, and taking the stiffness abnormality frequency data as the target stiffness abnormality assessment data, the stiffness abnormality of the target braking system can be more accurately characterized, and accurate stiffness assessment of the target braking system can be achieved.

[0156] After completing the stiffness assessment of the target braking system, if the target braking system is detected to have a soft stiffness condition, a stiffness abnormality prompt message will be fed back to receive the first braking adjustment information generated by the driver's manual adjustment operation, and the target braking system will be adjusted according to the first braking adjustment information. At the same time, the target stiffness abnormality assessment data is stored in a preset database. When powered on, the last stored target stiffness abnormality assessment data is retrieved, and then combined with the current operating parameters of the target braking system to generate the second braking adjustment information. The target braking system is automatically adjusted according to the second braking adjustment information, so that the target braking system is automatically adjusted after each power-on, so that the target braking system can operate normally and the safety of the vehicle driving process is improved.

[0157] See also Figure 8 The present application also provides a vehicle brake system stiffness evaluation device, which can implement the vehicle brake system stiffness evaluation method, and the device includes:

[0158] The data acquisition module 801 is used to collect stiffness influence data of the target brake system; wherein the stiffness influence data includes: servo cylinder pressure estimation value, servo cylinder pressure measurement value, brake fluid flow rate;

[0159] The expected stiffness prediction module 802 is used to perform stiffness prediction according to preset stiffness association parameters and servo cylinder pressure estimation values ​​to obtain expected stiffness data;

[0160] The actual stiffness prediction module 803 is used to perform stiffness prediction according to the servo cylinder pressure measurement value and the brake fluid flow rate to obtain actual stiffness data;

[0161] A preliminary abnormality assessment module 804 is used to perform a stiffness abnormality assessment on the target brake system according to the servo cylinder pressure measurement value, the expected stiffness data and the actual stiffness data to obtain preliminary stiffness abnormality assessment data;

[0162] The abnormal number detection module 805 is used to perform abnormal number detection based on the preliminary stiffness abnormality evaluation data to obtain the stiffness abnormal number;

[0163] The target stiffness abnormality assessment module 806 is used to perform stiffness abnormality assessment on the target braking system according to the stiffness abnormality times, preliminary stiffness abnormality assessment data and the preset data collection times, and obtain target stiffness abnormality assessment data; wherein the target stiffness abnormality assessment data represents the stiffness abnormality of the target braking system.

[0164] The specific implementation of the stiffness evaluation device of the vehicle brake system is substantially the same as the specific implementation of the stiffness evaluation method of the vehicle brake system described above, and will not be described in detail herein.

[0165] Please refer to Fig. 9 , an embodiment of the present application further provides a vehicle, the vehicle comprising a central control system and a target braking system; wherein the central control system is used to execute the stiffness evaluation method of the vehicle braking system as described above.

[0166] It should be noted that the target braking system is communicatively connected with the central control system, and the target braking system is also called an integrated braking control system. The integrated braking control system can provide the driver with a variety of braking functions, including basic braking, anti-lock braking function, vehicle stability system, etc.

[0167] Specifically, the vehicle can be a gasoline vehicle or a new energy vehicle. When the vehicle is a new energy vehicle, it can be a hybrid vehicle or a pure electric vehicle.

[0168] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the stiffness evaluation method of the vehicle braking system is implemented.

[0169] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0170] The stiffness evaluation method and device of the vehicle braking system, the vehicle and the storage medium provided in the embodiments of the present application first calculate the expected stiffness data and the actual stiffness data, and make a preliminary stiffness abnormality evaluation on the target braking system in combination with the expected stiffness data and the actual stiffness data to obtain preliminary stiffness abnormality evaluation data, and calculate the stiffness abnormality number of the preliminary stiffness abnormality evaluation data, so as to perform the stiffness abnormality evaluation on the target braking system again through the stiffness abnormality number and the preliminary stiffness abnormality data, thereby improving the accuracy of the stiffness abnormality evaluation of the target braking system.

[0171] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0172] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0173] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0174] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0175] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0176] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0177] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0178] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0179] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0180] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0181] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for evaluating the stiffness of a vehicle braking system, characterized in that: The method comprises: Collecting stiffness influence data of the target brake system; wherein the stiffness influence data includes: servo cylinder pressure estimation value, servo cylinder pressure measurement value, brake fluid flow rate; Performing stiffness prediction according to preset stiffness association parameters and the servo cylinder pressure estimation value to obtain expected stiffness data; Performing stiffness prediction according to the servo cylinder pressure measurement value and the brake fluid flow rate to obtain actual stiffness data; Performing a stiffness abnormality assessment on the target brake system according to the servo cylinder pressure measurement value, the expected stiffness data, and the actual stiffness data to obtain preliminary stiffness abnormality assessment data; Performing an abnormality frequency detection according to the preliminary stiffness abnormality assessment data to obtain the stiffness abnormality frequency; The target braking system is subjected to a stiffness abnormality assessment according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and a preset data collection times, to obtain target stiffness abnormality assessment data; wherein the target stiffness abnormality assessment data characterizes the stiffness abnormality of the target braking system.

2. The method according to claim 1, characterized in that The step of performing a stiffness abnormality assessment on the target braking system according to the servo cylinder pressure measurement value, the expected stiffness data, and the actual stiffness data to obtain preliminary stiffness abnormality assessment data includes: Performing data conversion on the expected stiffness data to obtain an expected elastic coefficient; Performing data conversion on the actual stiffness data to obtain an actual elastic coefficient; The target brake system is subjected to a stiffness abnormality assessment according to the servo cylinder pressure measurement value, the expected elastic coefficient, and the actual elastic coefficient to obtain the preliminary stiffness abnormality assessment data.

3. The method according to claim 2, characterized in that The step of performing a stiffness abnormality assessment on the target brake system according to the servo cylinder pressure measurement value, the expected elastic coefficient, and the actual elastic coefficient to obtain the preliminary stiffness abnormality assessment data includes: Calculating a coefficient deviation threshold value according to a preset elastic coefficient associated parameter, the servo cylinder pressure measurement value and the expected elastic coefficient to obtain a first elastic coefficient deviation threshold value; Perform deviation calculation according to the first elastic coefficient deviation threshold, the expected elastic coefficient and the actual elastic coefficient to obtain a second elastic coefficient deviation threshold; Obtaining a ratio between the second elastic coefficient deviation threshold and the first elastic coefficient deviation threshold to obtain a deviation ratio; The target brake system is subjected to a stiffness abnormality assessment based on the deviation ratio to obtain the preliminary stiffness abnormality assessment data.

4. The method according to claim 1, characterized in that: The step of performing a stiffness abnormality assessment on the target braking system according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and a preset data collection times to obtain target stiffness abnormality assessment data includes: Perform abnormal duration detection according to the number of stiffness abnormalities and the number of data acquisitions, and determine an abnormal duration coefficient; Performing stiffness abnormality frequency detection according to the abnormality duration coefficient and the preliminary stiffness abnormality evaluation data to obtain stiffness abnormality frequency data; The target brake system is subjected to a stiffness abnormality assessment according to the stiffness abnormality frequency data to obtain the target stiffness abnormality assessment data.

5. The method according to any one of claims 1 to 4, characterized in that: The step of performing stiffness prediction according to the servo cylinder pressure measurement value and the brake fluid flow rate to obtain actual stiffness data includes: Performing gradient detection on the servo cylinder pressure measurement value to obtain a servo cylinder pressure gradient value; The stiffness detection is performed according to the servo cylinder pressure gradient value and the brake fluid flow rate to obtain the actual stiffness data.

6. The method according to any one of claims 1 to 4, characterized in that: After performing stiffness abnormality evaluation on the target brake system according to the stiffness abnormality times, the preliminary stiffness abnormality evaluation data and the preset data collection times to obtain target stiffness abnormality evaluation data, the method further includes: Performing a stiffness abnormality assessment on the target braking system according to the target stiffness abnormality assessment data and a preset stiffness abnormality threshold to obtain a stiffness abnormality assessment result; If the stiffness evaluation result indicates that the target braking system has a soft stiffness condition, generating a stiffness abnormality prompt message; The first braking adjustment information fed back according to the abnormal stiffness prompt information is received, and the target braking system is brake-adjusted according to the first braking adjustment information.

7. The method according to any one of claims 1 to 4, characterized in that: After performing stiffness abnormality evaluation on the target brake system according to the stiffness abnormality times, the preliminary stiffness abnormality evaluation data and the preset data collection times to obtain target stiffness abnormality evaluation data, the method further includes: Storing the target stiffness abnormality assessment data into a preset database; receiving a power-on instruction, reading the target stiffness abnormality assessment data from the preset database according to the power-on instruction, and acquiring the current operating parameters of the target braking system; generating second brake adjustment information according to the target stiffness abnormality evaluation data and the current operating parameters; The target brake system is brake-adjusted according to the second brake-adjustment information.

8. A vehicle braking system stiffness evaluation device, characterized in that: The device comprises: A data acquisition module, used for collecting stiffness influence data of a target brake system; wherein the stiffness influence data includes: a servo cylinder pressure estimation value, a servo cylinder pressure measurement value, and a brake fluid flow rate; An expected stiffness prediction module, used to perform stiffness prediction according to preset stiffness association parameters and the servo cylinder pressure estimation value to obtain expected stiffness data; An actual stiffness prediction module, used to perform stiffness prediction according to the servo cylinder pressure measurement value and the brake fluid flow rate to obtain actual stiffness data; a preliminary abnormality assessment module, configured to perform a stiffness abnormality assessment on the target braking system according to the servo cylinder pressure measurement value, the expected stiffness data and the actual stiffness data, to obtain preliminary stiffness abnormality assessment data; An abnormal number detection module is used to perform abnormal number detection according to the preliminary stiffness abnormality evaluation data to obtain the stiffness abnormal number; A target stiffness abnormality assessment module is used to perform a stiffness abnormality assessment on the target braking system according to the stiffness abnormality times, the preliminary stiffness abnormality assessment data and a preset data collection times to obtain target stiffness abnormality assessment data; wherein the target stiffness abnormality assessment data represents the stiffness abnormality of the target braking system.

9. A vehicle, characterized in that: The vehicle comprises a central control system and a target braking system; wherein the central control system is used to execute the stiffness evaluation method of the vehicle braking system as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the stiffness evaluation method of the vehicle brake system according to any one of claims 1 to 7 is implemented.

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