Intelligent maintenance method, device and equipment for vehicle braking system and storage medium

Abstract

The embodiment of the invention provides an intelligent maintenance method and device for a vehicle braking system, equipment and a storage medium. The method comprises the steps of collecting multi-dimensional state data of the EMB system, inputting the multi-dimensional state data into a preset dynamic analysis model, determining the health degree of the EMB system, generating a maintenance suggestion according to the health degree and a preset dynamic threshold value, and displaying the maintenance suggestion to a user through a vehicle-mounted terminal. Through the method, the maintenance efficiency and accuracy of the EMB system are improved, the service life of the EMB system is prolonged, the vehicle driving safety is improved, the maintenance cost is reduced, and the user experience is improved.

Description

Technical Field

[0001] This application relates to the technical field of vehicle operation and maintenance, and particularly relates to an intelligent maintenance method, device, equipment and storage medium for a vehicle braking system. Background Art

[0002] The automotive braking system needs to regularly inspect, maintain and service related components, such as regularly inspecting and replacing the wear of the brake friction pads and brake discs, regularly replacing the brake fluid, and regularly replacing the drying tank of the dryer in the pneumatic braking system, etc.

[0003] Under normal circumstances, the regular maintenance of the braking system is carried out according to a certain period or a certain driving mileage, and the setting of the replacement period cannot be combined with the actual use environment of the vehicle. For example, for the replacement of brake friction pads, there are significant differences in the wear rate of friction pads between vehicles used in plain areas and mountainous areas; for brake fluid, there are also significant differences in the water absorption degree of brake fluid when used in areas with high humidity in the south and low humidity in the north; there are also some vehicles that require replacement even though the driving mileage is short but it is time for maintenance, such as the drying tank.

[0004] Therefore, the regular maintenance of the braking system theoretically improves the braking safety of the vehicle, but it cannot be combined with the actual use scenario of the customer, and inevitably brings the situation of over-maintenance or under-maintenance. Summary of the Invention

[0005] Embodiments of this application provide an intelligent maintenance method, device, equipment and storage medium for a vehicle braking system, which are used to solve the problem of how to achieve intelligent maintenance of the vehicle braking system and avoid over-maintenance or under-maintenance.

[0006] In a first aspect, embodiments of this application provide an intelligent maintenance method for a vehicle braking system, which is applied to a controller of an electro-mechanical braking (EMB) system. The method includes:

[0007] Collect multi-dimensional state data of the EMB system;

[0008] Input the multi-dimensional state data into a pre-set dynamic analysis model to determine the health of the EMB system. The dynamic analysis model includes an electrical degradation analysis model, a mechanical wear analysis model and an environmental coupling analysis model;

[0009] Generate a maintenance recommendation according to the health and a pre-set dynamic threshold;

[0010] Display the maintenance recommendation to the user through an in-vehicle terminal.

[0011] In a possible implementation, the multi-dimensional state data includes charge and discharge parameters of the energy storage module, operating parameters of the wheel-end motor, real-time displacement of the brake friction pad and the brake disc, vehicle braking behavior data, and vehicle usage environment data.

[0012] In a possible implementation, the charge and discharge parameters of the energy storage module include voltage, current, and charging time. The operating parameters of the wheel-end motor include voltage, current, deviation value between the expected clamping force and the actual clamping force. The vehicle braking behavior data includes initial braking speed, deceleration, braking duration, and final speed. The vehicle usage environment data includes geographical location, slope of the driving path, load weight, and road surface adhesion coefficient.

[0013] In a possible implementation, the health degree includes electrical health degree, mechanical health degree, and environmental health degree. Determining the health degree of the EMB system by inputting the multi-dimensional state data into a preset dynamic analysis model includes:

[0014] Calculating the electrical health degree according to the charge and discharge parameters of the energy storage module and the electrical degradation analysis model;

[0015] Calculating the mechanical health degree according to the operating parameters of the wheel-end motor, the real-time displacement of the brake friction pad and the brake disc, the vehicle braking behavior data, and the mechanical wear analysis model;

[0016] Calculating the environmental health degree according to the vehicle usage environment data, the vehicle braking behavior data, and the environmental coupling analysis model.

[0017] In a possible implementation, generating a maintenance suggestion according to the health degree and a preset dynamic threshold includes:

[0018] When any health degree in the health degree is lower than the corresponding dynamic threshold, generating a low-level maintenance suggestion, where the low-level maintenance suggestion indicates that it is recommended that the user perform maintenance within a preset period;

[0019] When two or more health degrees in the health degree are lower than the corresponding dynamic thresholds, generating a high-level maintenance suggestion, where the high-level maintenance suggestion indicates that it is recommended that the user perform maintenance immediately.

[0020] In a possible implementation, before generating a maintenance suggestion according to the health degree and a preset dynamic threshold, the method further includes:

[0021] Setting the dynamic threshold based on pre-collected vehicle environment information, historical braking information, and design specifications of each component of the EMB system.

[0022] In a possible implementation, the dynamic thresholds include electrical dynamic thresholds, mechanical dynamic thresholds, and environmental dynamic thresholds. Then, setting the dynamic thresholds based on the pre-collected vehicle environment information, historical braking information, and the design specifications of each component of the EMB system includes:

[0023] Setting initial electrical dynamic thresholds, initial mechanical dynamic thresholds, and initial environmental dynamic thresholds based on the design specifications of each component of the EMB system;

[0024] Calculating the capacitance performance degradation acceleration factor according to the vehicle environment information;

[0025] Exponentially scaling the initial electrical dynamic threshold by the acceleration factor to generate the electrical dynamic threshold;

[0026] Calculating the wear compensation coefficient of the friction plate according to the historical braking information;

[0027] Multiplying and correcting the initial mechanical dynamic threshold by the wear compensation coefficient to generate the mechanical dynamic threshold;

[0028] Calculating the terrain load coefficient according to the vehicle environment information;

[0029] Linearly weighting the initial environmental dynamic threshold by the terrain load coefficient to generate the environmental dynamic threshold.

[0030] In a second aspect, an intelligent maintenance and repair device for a vehicle braking system provided by an embodiment of the present application includes:

[0031] An acquisition module for acquiring multi-dimensional state data of the EMB system;

[0032] An analysis module for inputting the multi-dimensional state data into a pre-set dynamic analysis model to determine the health of the EMB system. The dynamic analysis model includes an electrical degradation analysis model, a mechanical wear analysis model, and an environmental coupling analysis model;

[0033] A generation module for generating maintenance suggestions according to the health and pre-set dynamic thresholds;

[0034] A display module for displaying the maintenance suggestions to the user through an in-vehicle terminal.

[0035] In a possible implementation, the multi-dimensional state data includes charge and discharge parameters of an energy storage module, operating parameters of a wheel-end motor, real-time displacement amounts of a brake friction plate and a brake disc, vehicle braking behavior data, and vehicle usage environment data.

[0036] In a possible implementation, the charge and discharge parameters of the energy storage module include voltage, current, and charging time, the operating parameters of the wheel-end motor include voltage, current, and the deviation value between the expected clamping force and the actual clamping force, the vehicle braking behavior data includes the initial braking speed, deceleration, braking duration, and final speed, and the vehicle usage environment data includes geographical location, driving path gradient, load weight, and road surface adhesion coefficient.

[0037] In a possible implementation, the health includes electrical health, mechanical health, and environmental health. The analysis module is specifically configured to:

[0038] Calculate the electrical health based on the charge and discharge parameters of the energy storage module and the electrical degradation analysis model;

[0039] Calculate the mechanical health based on the operating parameters of the wheel-end motor, the real-time displacement between the brake friction pad and the brake disc, the vehicle braking behavior data, and the mechanical wear analysis model;

[0040] Calculate the environmental health based on the vehicle usage environment data, the vehicle braking behavior data, and the environmental coupling analysis model.

[0041] In a possible implementation, the device further includes:

[0042] A setting module, configured to set the dynamic threshold based on the pre-collected vehicle environment information, historical braking information, and the design specifications of each component of the EMB system.

[0043] In a possible implementation, the dynamic threshold includes an electrical dynamic threshold, a mechanical dynamic threshold, and an environmental dynamic threshold. The setting module is specifically configured to:

[0044] Set an initial electrical dynamic threshold, an initial mechanical dynamic threshold, and an initial environmental dynamic threshold based on the design specifications of each component of the EMB system;

[0045] Calculate the capacitance performance attenuation acceleration factor according to the vehicle environment information;

[0046] Exponentially scale the initial electrical dynamic threshold by the acceleration factor to generate the electrical dynamic threshold;

[0047] Calculate the wear compensation coefficient of the friction pad according to the historical braking information;

[0048] Multiply and correct the initial mechanical dynamic threshold by the wear compensation coefficient to generate the mechanical dynamic threshold;

[0049] Calculate the terrain load coefficient according to the vehicle environment information;

[0050] Linearly weight the initial environmental dynamic threshold and the terrain load factor to generate an environmental dynamic threshold.

[0051] In a third aspect, an embodiment of the present application provides a controller, including: a storage unit and a processing unit;

[0052] The storage unit stores computer execution instructions;

[0053] The processing unit executes the computer execution instructions stored in the storage unit, so that the processing unit executes various possible implementation manners of the first aspect and the second aspect as above.

[0054] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer execution instructions are stored, and when the computer execution instructions are executed by a processing unit, they are used to implement various possible implementation manners of the first aspect and the second aspect as above.

[0055] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, and when the computer program is executed by a processing unit, it implements various possible implementation manners of the first aspect and the second aspect as above.

[0056] The intelligent maintenance method, device, equipment and storage medium for a vehicle braking system provided by the embodiments of the present application collect multi-dimensional state data of the EMB system, input the multi-dimensional state data into a preset dynamic analysis model, determine the health of the EMB system, generate a maintenance suggestion according to the health and a preset dynamic threshold, and display the maintenance suggestion to the user through an in-vehicle terminal. Through the above method, the maintenance efficiency and accuracy of the EMB system are improved, the service life of the EMB system is extended, the driving safety of the vehicle is enhanced, the maintenance cost is reduced, and the user experience is improved. Description of the Drawings

[0057] The drawings here are incorporated into the specification and constitute a part of this specification, showing the embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0058] Figure 1 It is the EMB system architecture diagram provided by the present application;

[0059] Figure 2 It is the flow schematic of the intelligent maintenance method for a vehicle braking system provided by the present application Figure 1 ;

[0060] Figure 3 It is the flow schematic of the intelligent maintenance method for a vehicle braking system provided by the present application Figure 2 ;

[0061] Figure 4 Flow schematic of the intelligent maintenance method for the vehicle braking system provided by this application Figure 3 ;

[0062] Figure 5 Flow schematic of the intelligent maintenance method for the vehicle braking system provided by this application Figure 4 ;

[0063] Figure 6 Structural schematic diagram of the intelligent maintenance device for the vehicle braking system provided by this application;

[0064] Figure 7 Structural schematic diagram of the controller provided by this application.

[0065] Through the above-mentioned drawings, specific embodiments of this application have been shown, and there will be more detailed descriptions hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. Specific embodiments

[0066] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. On the contrary, they are merely examples of devices and methods consistent with some aspects of this application as detailed in the appended claims.

[0067] The automotive braking system needs to regularly inspect, maintain, and service related components, such as regularly inspecting and replacing the wear of the brake friction pads and brake discs, regularly replacing the brake fluid, and regularly replacing the drying tank of the dryer in the pneumatic braking system, etc.

[0068] The regular maintenance of the braking system is generally carried out according to a certain cycle or a certain mileage, and the setting of the replacement cycle cannot be combined with the actual use environment of the vehicle. For example, for the replacement of the brake friction pads, there are significant differences in the wear rate of the friction pads between vehicles used in plain areas and mountainous areas; for the brake fluid, there are also significant differences in the water absorption degree of the brake fluid when used in areas with high humidity in the south and low humidity in the north; there are also some vehicles that require replacement even though the driving mileage is short but it is time for maintenance, such as the drying tank.

[0069] Regular maintenance of the braking system theoretically improves the braking safety of the vehicle, but it cannot be combined with the actual usage scenarios of customers, inevitably resulting in over-maintenance or under-maintenance.

[0070] In view of the above problems, the present application provides an intelligent maintenance method, device, equipment and storage medium for a vehicle braking system, realizing the intelligent maintenance of the vehicle braking system and avoiding the problems of over-maintenance or under-maintenance. Specifically, usually, the regular maintenance of the braking system is carried out according to a certain cycle or a certain driving mileage for replacement, and the setting of the replacement cycle cannot be combined with the actual use environment of the vehicle. For example, when replacing the brake friction pads, there are significant differences in the wear rate of the friction pads between vehicles used in plain areas and mountainous areas; for the brake fluid, there are also significant differences in the water absorption degree of the brake fluid when used in areas with high humidity in the south and low humidity in the north; there are also some vehicles that require replacement when they reach the maintenance time although the driving mileage is short, such as the desiccant tank. Considering these problems, the inventor studied whether it is possible to monitor the functions of each component of the system through the EMB system, and at the same time, based on information such as the vehicle use environment and the customer's vehicle use habits, provide personalized maintenance suggestions for the vehicle based on big data. Based on this, the technical solution of the present application is proposed.

[0071] The execution subject of the intelligent maintenance method for the vehicle braking system provided by the present application is the controller of the EMB system. Figure 1 The EMB system architecture diagram provided by the present application is as Figure 1 shown. The EMB system mainly consists of a pedal simulator, an EPB switch, an EMB controller, an energy storage module, a wheel-end motor, and a wiring harness and a CAN network.

[0072] In the EMB system, the vehicle power supply provides power to the energy storage module of the EMB. The energy storage module is mainly composed of supercapacitors, which store electrical energy after charging and are used to supply power to the wheel-end motor during braking.

[0073] The EMB controller receives a braking demand signal from the pedal simulator or a signal from the EPB switch, controls the operation of the wheel-end motor, and the rotation of the wheel-end motor drives the brake to work and generate braking force. In addition, the EMB controller can also receive a work request signal from the outside and control the operation of the wheel-end motor.

[0074] In the braking system of the EMB, the components that need to be inspected and maintained include the energy storage module. After long-term use of the supercapacitors in the energy storage module, the energy storage function will decline; the wheel-end motor, the insulation, bearing wear, lubrication, etc. of the wheel-end motor involve maintenance; the brake friction pads and brake discs, the wear amount of the brake friction pads and the wear amount of the brake discs need to be detected, and maintenance should be carried out in time after wear.

[0075] Among them, the controller of the EMB system can also monitor its own system, the vehicle braking usage habits, and the vehicle use environment, and then based on the multi-dimensional state data obtained from the monitoring, analyze and obtain maintenance suggestions and push them to the user.

[0076] The technical solution of the present application and how the technical solution of the present application solves the above technical problems will be described in detail below with specific embodiments. The following several specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the drawings.

[0077] Figure 2 Flow schematic of the intelligent maintenance method for the vehicle braking system provided by the present application Figure 1 , such as Figure 2 shown, the method includes:

[0078] S201: Collect multi-dimensional state data of the EMB system.

[0079] In this step, in order to accurately identify whether the relevant components of the braking system need to be repaired, it is necessary to monitor the multi-dimensional state data of the braking system in real time.

[0080] Specifically, when the EMB system is working, it will monitor the component status in real time, such as the performance of the accumulator, the wear of the friction plate and the wear of the brake disc. It can also collect the customer's braking usage habits, such as the usage frequency of the braking system, the braking intensity of the brake, the vehicle speed before and after braking, etc. It can also collect information on the usage scenarios of the customer's vehicle, such as the usage area, road surface slope information, driving route, road adhesion, etc. Furthermore, multi-dimensional state data of the EMB system is collected.

[0081] Optionally, the multi-dimensional state data includes charge and discharge parameters of the energy storage module, operating parameters of the wheel-end motor, real-time displacement of the brake friction plate and the brake disc, vehicle braking behavior data, and vehicle usage environment data. The charge and discharge parameters of the energy storage module include voltage, current, and charging time. The operating parameters of the wheel-end motor include voltage, current, deviation value between the expected clamping force and the actual clamping force. The vehicle braking behavior data includes initial braking speed, deceleration, braking duration, and final speed. The vehicle usage environment data includes geographical location, slope of the driving path, load weight, and road adhesion coefficient.

[0082] Among them, the charge and discharge parameters of the energy storage module:

[0083] Voltage: Record the voltage change of the energy storage module during the charge and discharge process to evaluate its ability to store and release electrical energy.

[0084] Current: Monitor the magnitude of the current during the charge and discharge process to judge the charge and discharge efficiency of the energy storage module.

[0085] Charging time: Record the time required for the energy storage module to charge from low power to full charge to evaluate its charging performance.

[0086] Operating parameters of the wheel-end motor:

[0087] Voltage: Monitor the voltage of the in-wheel motor during operation to ensure it operates within the normal range.

[0088] Current: Record the current of the motor during operation to evaluate its power output and efficiency.

[0089] Deviation value between the expected clamping force and the actual clamping force: By comparing the expected clamping force generated by the motor with the actual clamping force, determine whether the performance of the motor has deteriorated.

[0090] Real-time displacement of the brake friction pad and the brake disc: Through a displacement sensor, monitor the wear of the brake friction pad and the brake disc in real time to predict their remaining service life.

[0091] Vehicle braking behavior data:

[0092] Initial braking speed: Record the speed when the vehicle starts braking to analyze the intensity of the braking behavior.

[0093] Deceleration: Monitor the deceleration of the vehicle during braking to evaluate the response speed and performance of the braking system.

[0094] Braking duration: Record the duration of the braking process to analyze the stability and durability of the braking system.

[0095] Final speed: Record the speed when the vehicle finishes braking to determine whether the braking effect meets the expectation.

[0096] Vehicle usage environment data:

[0097] Geographical location: Record the geographical location where the vehicle travels to analyze the impact of different regions on the braking system.

[0098] Gradient of the driving path: Monitor the gradient of the vehicle's driving path to evaluate the impact of the gradient on braking performance.

[0099] Load weight: Record the weight of the vehicle load to analyze the pressure on the braking system caused by the load.

[0100] Coefficient of road adhesion: By calculating the deceleration and vehicle speed during vehicle braking, estimate the coefficient of road adhesion to evaluate the impact of road conditions on braking performance.

[0101] S202: Input the multi-dimensional state data into a pre-set dynamic analysis model to determine the health status of the EMB system.

[0102] In this step, after collecting the multi-dimensional state data, it is input into the dynamic analysis model, so that the data from multiple dimensions can be comprehensively considered to comprehensively evaluate the health status of the system. Among them, the dynamic analysis model includes an electrical degradation analysis model, a mechanical wear analysis model, and an environmental coupling analysis model.

[0103] Specifically, according to the charge and discharge parameters of the energy storage module and the electrical degradation analysis model, the electrical health degree is calculated. According to the operating parameters of the wheel-end motor, the real-time displacement of the brake friction pad and the brake disc, the vehicle braking behavior data, and the mechanical wear analysis model, the mechanical health degree is calculated. According to the vehicle usage environment data, the vehicle braking behavior data, and the environmental coupling analysis model, the environmental health degree is calculated.

[0104] S203: Generate maintenance suggestions based on the health degree and the preset dynamic threshold.

[0105] In this step, in order to ensure the accuracy and pertinence of the maintenance suggestions, after determining the health degree, maintenance suggestions are generated based on the preset dynamic threshold.

[0106] Specifically, when any one of the health degrees is lower than the corresponding dynamic threshold, a low-level maintenance suggestion is generated. When two or more health degrees are lower than the corresponding dynamic thresholds, a high-level maintenance suggestion is generated.

[0107] S204: Display the maintenance suggestions to the user through the in-vehicle terminal.

[0108] In this step, in order to facilitate the user to understand the vehicle's maintenance requirements, the maintenance suggestions can be displayed for the user to view. Among them, the display can be carried out through the in-vehicle terminal, and the in-vehicle terminal can be a vehicle instrument large screen, a central control display screen, a mobile phone APP, etc., which can intuitively display the content of the maintenance suggestions and the execution time of the suggestions.

[0109] Exemplarily, when the system generates a maintenance suggestion to replace the brake friction pad, the suggestion may be displayed on the vehicle instrument large screen in the form of text or icons, and the user is prompted to arrange maintenance as soon as possible. At the same time, the system may also send a maintenance reminder notification to the user through the mobile phone APP to ensure that the user can receive and process the maintenance suggestion in a timely manner.

[0110] Optionally, a health degree dashboard can be designed for the visualization interface of the in-vehicle terminal. For example, a three-color ring diagram is used to display the health degrees of each component. Furthermore, the user is prompted about the urgency of executing the maintenance suggestion through a warning pop-up window.

[0111] The intelligent maintenance method for the vehicle braking system provided by the embodiment of the present application collects multi-dimensional state data of the EMB system, inputs the multi-dimensional state data into a preset dynamic analysis model to determine the health degree of the EMB system, generates maintenance suggestions according to the health degree and the preset dynamic threshold, and displays the maintenance suggestions to the user through the in-vehicle terminal. Through the above method, the maintenance efficiency and accuracy of the EMB system are improved, the service life of the EMB system is extended, the driving safety of the vehicle is enhanced, the maintenance cost is reduced, and the user experience is improved.

[0112] Figure 3 Flow schematic of the intelligent maintenance method for the vehicle braking system provided by this application Figure 2 , such as Figure 3 shown, based on the above embodiment, the health degree includes electrical health degree, mechanical health degree and environmental health degree. Step S202 specifically includes:

[0113] S301: Calculate the electrical health degree according to the charge and discharge parameters of the energy storage module and the electrical degradation analysis model.

[0114] In this step, in order to accurately analyze the electrical performance of the energy storage module, after collecting the charge and discharge parameters of the energy storage module, the electrical health degree is calculated based on the electrical degradation analysis model.

[0115] Specifically, based on the electrochemical principle and material aging law of the energy storage module, etc., an electrical degradation analysis model is established. That is, the model is the capacity attenuation model of the energy storage module. The electrical performance degradation of the energy storage module under different usage conditions is predicted through the model. The collected charge and discharge parameters are input into the electrical degradation analysis model to calculate the current electrical health degree of the energy storage module. That is, the capacitance capacity attenuation rate is calculated.

[0116] Optionally, the electrical health degree can be expressed as:

[0117]

[0118] Among them, represents the capacitance capacity attenuation rate, and k represents the safety attenuation coefficient, which can be freely adjusted according to the vehicle model.

[0119] For the calculation of the capacitance capacity attenuation rate, it can be expressed as:

[0120]

[0121] Among them, represents the energy efficiency, represents the initial energy efficiency calibrated at the factory, represents the time constant, which is calculated based on the charge and discharge parameters of the energy storage module, represents the factory calibration value.

[0122] Exemplarily, assume that the capacity of the energy storage module in the initial state is 100 Ah. After a certain number of charge and discharge cycles, the current charging voltage is collected as 14.4 V, the discharging voltage is 12.6 V, the discharging current is 50 A, and the discharging time is 2 hours. These parameters are input into the electrical degradation analysis model, and the current capacity retention rate of the energy storage module is calculated to be 85%.

[0123] S302: Calculate the mechanical health degree based on the operating parameters of the wheel-end motor, the real-time displacement of the brake friction pad and the brake disc, the vehicle braking behavior data, and the mechanical wear analysis model.

[0124] In this step, in order to accurately analyze the mechanical performance of the motor, after collecting the operating parameters of the wheel-end motor, the real-time displacement of the brake friction pad and the brake disc, and the vehicle braking behavior data, calculate the mechanical health degree based on the mechanical wear analysis model.

[0125] Specifically, calculating the mechanical health degree is based on the remaining life of the friction pad predicted by the mechanical wear analysis sub-model and the wear grade of the motor bearing.

[0126] Optionally, the mechanical health degree can be expressed as:

[0127]

[0128] Where represents the remaining life of the friction pad, which is calculated based on the operating parameters of the wheel-end motor and the real-time displacement of the brake friction pad and the brake disc. represents the theoretical braking times of a new friction pad. The wear grade is determined by performing a spectrum analysis on the clamping force deviation signal and extracting the proportion of the high-frequency harmonic energy in the range of 50 - 200 Hz.

[0129] Exemplarily, assume the following data is collected:

[0130] The rotational speed of the wheel-end motor is 1500 rpm, the torque is 100 Nm, the temperature is 70 °C, and the vibration level is within the normal range.

[0131] The real-time displacement of the brake friction pad and the brake disc shows that the relative displacement between the friction pad and the brake disc during braking is 1.5 mm, and the contact pressure is stable.

[0132] The vehicle braking behavior data shows that the initial braking speed is 50 km / h, the deceleration is 5 m / s², the braking duration is 2.5 seconds, and the number of braking times per day is about 100 times.

[0133] Input these data into the mechanical wear analysis model, and predict that the friction pad has a remaining life of 5000 braking times or 10000 km based on the braking behavior data, the friction material characteristics, and the contact pressure.

[0134] Evaluate that the bearing is in a slightly worn grade according to the operating parameters of the motor and the material characteristics of the bearing.

[0135] S303: Calculate the environmental health degree based on the vehicle usage environment data, the vehicle braking behavior data, and the environmental coupling analysis model.

[0136] In this step, in order to accurately analyze the performance changes of the vehicle under different usage environments, after collecting the vehicle usage environment data and vehicle braking behavior data, the environmental health is calculated based on the environmental coupling analysis model. That is, the braking load intensity coefficient constructed based on the environmental coupling analysis sub-model.

[0137] Specifically, based on environmental science principles, vehicle dynamics principles, etc., an environmental coupling analysis model is established. The collected usage environment data and braking behavior data are input into the environmental coupling analysis model to calculate the current environmental health of the vehicle.

[0138] Exemplarily, the single-brake load intensity is calculated based on the following formula:

[0139]

[0140] Where, W represents the load weight, represents the slope of the driving path, represents the road surface adhesion coefficient, E represents the single-brake ability, which is calculated based on the vehicle mass, initial braking speed, and final speed, represents the standard braking energy of the vehicle under full load on a flat road.

[0141] The cumulative load intensity coefficient is calculated based on the following formula:

[0142]

[0143] Where, the temperature correction factor is obtained by looking up the table according to the real-time temperature of the brake disc ( ), and N represents the number of brakings per unit time.

[0144] Furthermore, the environmental health can be expressed as:

[0145]

[0146] Where, represents the safety load threshold of the same type of vehicle in the standard environment.

[0147] The intelligent maintenance method for vehicle braking systems provided by the embodiments of the present application calculates the electrical health degree according to the charge and discharge parameters of the energy storage module and the electrical degradation analysis model, calculates the mechanical health degree according to the operating parameters of the wheel-end motor, the real-time displacement between the brake friction pad and the brake disc, the vehicle braking behavior data, and the mechanical wear analysis model, and calculates the environmental health degree according to the vehicle usage environment data, the vehicle braking behavior data, and the environmental coupling analysis model. By integrating a variety of parameters and analysis models, a comprehensive assessment of the electrical, mechanical, and environmental health degrees of the vehicle is achieved, providing strong technical support for vehicle maintenance, operation, and management, and improving the safety, reliability, and economy of the vehicle.

[0148] Figure 4 is the flow schematic of the intelligent maintenance method for vehicle braking systems provided by the present application Figure 3 , as Figure 4 shown, on the basis of the above various embodiments, step S203 specifically includes:

[0149] S401: When any one of the health degrees is lower than the corresponding dynamic threshold, generate a low-level maintenance suggestion.

[0150] S402: When two or more of the health degrees are lower than the corresponding dynamic thresholds, generate a high-level maintenance suggestion.

[0151] In order to provide early warning, reduce the risk of sudden failures, and optimize the allocation of maintenance resources, when it is determined that a single health degree is abnormal, that is, when any one of the health degrees is lower than the corresponding dynamic threshold, a low-level maintenance suggestion is generated to prompt the user to perform preventive maintenance within a preset future time (such as 30 days) to avoid the problem from deteriorating.

[0152] In order to avoid cascading failures caused by multi-factor coupling and ensure driving safety, when two or more health degrees are simultaneously lower than their dynamic thresholds, a high-level maintenance suggestion is generated, requiring the user to immediately disable the relevant functions or perform maintenance nearby to prevent system-level failures.

[0153] Exemplarily, for a single health degree abnormality

[0154] Vehicle status:

[0155] Electrical health degree 0.65, mechanical health degree 0.8, environmental health degree 0.9.

[0156] System response:

[0157] Low-level maintenance suggestion: "It is detected that the performance of the super capacitor has decreased (health degree 65%). It is recommended to go to the authorized service point for capacitor calibration within 30 days (service code: EMB-EC01)."

[0158] Interaction interface:

[0159] The instrument panel displays a yellow warning light;

[0160] Detailed suggestions pop up on the central control screen, and maintenance appointments can be made with one click.

[0161] Multiple health coordination anomalies

[0162] Vehicle status:

[0163] Electrical health is 0.4, mechanical health is 0.3 (remaining thickness of friction plate is 1.2mm, bearing wear level is 4), and environmental health is 0.5 (continuous mountain road driving load exceeds the standard).

[0164] System Response:

[0165] Advanced maintenance advice: "Urgent! Capacitor failure (health 40%) and friction plate wear (health 30%) detected, perform the following operations immediately:

[0166] Switch to backup brake mode;

[0167] Navigate to the nearest service point (XX maintenance center, 2.5km away);

[0168] Replace the supercapacitor pack (model: EMB-CAP-2024) and friction plate (model: EMB-PAD-05). ”

[0169] Interactive interface:

[0170] The red alarm on the instrument panel flashes, accompanied by a buzzer prompt;

[0171] The central control screen locks non-essential functions and forces the display of maintenance navigation;

[0172] The vehicle automatically limits its speed to 40km / h until maintenance is completed.

[0173] The vehicle brake system intelligent maintenance method provided by the embodiment of the present application generates a low-level maintenance suggestion when any health level is lower than the corresponding dynamic threshold, and generates a high-level maintenance suggestion when two or more health levels are lower than the corresponding dynamic threshold. Through the above method, the accuracy of maintenance is improved, excessive maintenance is reduced, systemic failures are prevented, safety is enhanced, resource allocation is optimized, and service efficiency is improved.

[0174] Figure 5 Schematic diagram of the process of the vehicle brake system intelligent maintenance method provided in the embodiment of the present application Figure 4 ,like Figure 5 As shown, on the basis of the above embodiment, based on the pre-collected vehicle environment information, historical braking information and design specifications of each component of the EMB system, a dynamic threshold is set, specifically including:

[0175] S501: Set the initial electrical dynamic threshold, the initial mechanical dynamic threshold, and the initial environmental dynamic threshold based on the design specifications of each component of the EMB system.

[0176] In this step, set the initial threshold as the reference value based on the design specifications of each component of the EMB.

[0177] Specifically, the electrical dynamic threshold sets the capacity decay rate threshold according to the nominal cycle life of the supercapacitor (such as 2000 charge-discharge cycles).

[0178] Example: A warning is triggered when the capacitance decays by 30%, that is, the health degree ≤ 0.7 is abnormal.

[0179] The mechanical dynamic threshold sets the remaining life threshold based on the wear coefficient of the friction plate material (such as 1 mm of wear per 1000 brakings).

[0180] Example: A warning is triggered when the remaining thickness of the friction plate is less than 2 mm, that is, the health degree ≤ 0.5 is abnormal.

[0181] The environmental dynamic threshold sets the safety load threshold according to the vehicle design load and the road surface adhesion coefficient.

[0182] Example: A warning is triggered when the terrain load coefficient exceeds 5.0, that is, the initial environmental dynamic threshold is 0.6.

[0183] S502: Calculate the capacitance performance decay acceleration factor according to the vehicle environmental information.

[0184] In this step, in order to quantify the acceleration effect of environmental factors on capacitor aging, the capacitance performance decay acceleration factor is calculated.

[0185] Specifically, the calculation formula of the capacitance performance decay acceleration factor can be expressed as:

[0186]

[0187] Among them, represents the activation energy of capacitor aging, R represents the gas constant, represents the reference temperature, represents the real-time environmental temperature.

[0188] S503: Exponentially scale the initial electrical dynamic threshold by the acceleration factor to generate the electrical dynamic threshold.

[0189] In this step, adjust the initial threshold according to the environmental acceleration factor.

[0190] Specifically, exponentially scale the initial electrical dynamic threshold by the acceleration factor:

[0191]

[0192] Among them, represents the electrical dynamic threshold, and represents the initial electrical dynamic threshold.

[0193] S504: Calculate the wear compensation coefficient of the friction plate according to the historical braking information.

[0194] In this step, the mechanical wear rate is corrected according to the historical braking data, and then the wear compensation coefficient of the friction plate is calculated.

[0195] Specifically, the calculation formula is expressed as:

[0196]

[0197] S505: Multiply and correct the initial mechanical dynamic threshold by the wear compensation coefficient to generate the mechanical dynamic threshold.

[0198] In this step, the initial threshold is adjusted according to the wear compensation coefficient, that is, multiply and correct.

[0199] Specifically, it is expressed as: , among which, represents the mechanical dynamic threshold, and represents the initial mechanical dynamic threshold.

[0200] S506: Calculate the terrain load coefficient according to the vehicle environment information.

[0201] In this step, in order to quantify the additional load of the terrain on the braking system, the terrain load coefficient is calculated.

[0202] Specifically, the calculation formula is expressed as:

[0203]

[0204] S507: Linearly weight the initial environmental dynamic threshold by the terrain load coefficient to generate the environmental dynamic threshold.

[0205] In this step, the environmental health threshold is adjusted according to the terrain load. Then it can be calculated by linear weighting.

[0206] Specifically, it is expressed as:

[0207]

[0208] Among them, K represents the vehicle type coefficient.

[0209] The intelligent maintenance method for vehicle braking systems provided by the embodiments of this application, based on the design specifications of each component of the EMB system, sets initial electrical dynamic thresholds, initial mechanical dynamic thresholds, and initial environmental dynamic thresholds. According to vehicle environmental information, it calculates the capacitance performance decay acceleration factor, exponentially scales the initial electrical dynamic threshold by the acceleration factor to generate the electrical dynamic threshold. According to historical braking information, it calculates the wear compensation coefficient of the friction plate, multiplies and corrects the initial mechanical dynamic threshold with the wear compensation coefficient to generate the mechanical dynamic threshold. According to vehicle environmental information, it calculates the terrain load coefficient, and linearly weights the initial environmental dynamic threshold with the terrain load coefficient to generate the environmental dynamic threshold. Through the above method, the maintenance accuracy is improved, over-maintenance and under-maintenance are reduced, the adaptability of the system to complex environments is enhanced, collaborative decision-making on multi-dimensional health states is achieved, the lifespan of key components is extended, and the full-life cycle cost is reduced.

[0210] Figure 6 The structural schematic diagram of the intelligent maintenance device for vehicle braking systems provided by this application is as Figure 6 shown. The intelligent maintenance device 600 for vehicle braking systems specifically includes:

[0211] The acquisition module 601 is used to acquire multi-dimensional state data of the EMB system.

[0212] The analysis module 602 is used to input the multi-dimensional state data into a pre-set dynamic analysis model to determine the health of the EMB system. The dynamic analysis model includes an electrical degradation analysis model, a mechanical wear analysis model, and an environmental coupling analysis model.

[0213] The generation module 603 is used to generate maintenance suggestions according to the health and pre-set dynamic thresholds.

[0214] The display module 604 is used to display the maintenance suggestions to the user through the in-vehicle terminal.

[0215] In a possible implementation, the multi-dimensional state data includes charge and discharge parameters of the energy storage module, operating parameters of the wheel-end motor, real-time displacement of the brake friction plate and the brake disc, vehicle braking behavior data, and vehicle usage environment data.

[0216] In a possible implementation, the charge and discharge parameters of the energy storage module include voltage, current, and charging time. The operating parameters of the wheel-end motor include voltage, current, deviation value between the expected clamping force and the actual clamping force. The vehicle braking behavior data includes initial braking speed, deceleration, braking duration, and final speed. The vehicle usage environment data includes geographical location, slope of the driving path, load weight, and road surface adhesion coefficient.

[0217] In a possible implementation, the health degree includes electrical health degree, mechanical health degree and environmental health degree. The analysis module 602 is specifically configured to:

[0218] Calculate the electrical health degree according to the charge and discharge parameters of the energy storage module and the electrical degradation analysis model;

[0219] Calculate the mechanical health degree according to the operating parameters of the wheel-end motor, the real-time displacement of the brake friction plate and the brake disc, the vehicle braking behavior data and the mechanical wear analysis model;

[0220] Calculate the environmental health degree according to the vehicle use environment data, the vehicle braking behavior data and the environmental coupling analysis model.

[0221] In a possible implementation, the intelligent maintenance device 600 for vehicle braking system further includes:

[0222] A setting module 605, configured to set dynamic thresholds based on the pre-collected vehicle environment information, historical braking information and the design specifications of each component of the EMB system.

[0223] In a possible implementation, the dynamic thresholds include electrical dynamic threshold, mechanical dynamic threshold and environmental dynamic threshold. The setting module 605 is specifically configured to:

[0224] Set the initial electrical dynamic threshold, the initial mechanical dynamic threshold and the initial environmental dynamic threshold based on the design specifications of each component of the EMB system;

[0225] Calculate the capacitance performance attenuation acceleration factor according to the vehicle environment information;

[0226] Exponentially scale the initial electrical dynamic threshold by the acceleration factor to generate the electrical dynamic threshold;

[0227] Calculate the wear compensation coefficient of the friction plate according to the historical braking information;

[0228] Multiply and correct the initial mechanical dynamic threshold by the wear compensation coefficient to generate the mechanical dynamic threshold;

[0229] Calculate the terrain load coefficient according to the vehicle environment information;

[0230] Linearly weight the initial environmental dynamic threshold by the terrain load coefficient to generate the environmental dynamic threshold.

[0231] The intelligent maintenance device for vehicle braking system provided in this embodiment can execute the solutions of the intelligent maintenance method for vehicle braking system provided in each of the above method embodiments, and its implementation principle and technical effects are similar. Details are not described herein.

[0232] Figure 7The structural schematic diagram of the controller provided by this application. As Figure 7 shown, the controller 700 provided in this embodiment includes: at least one processing unit 701 and a storage unit 702. Optionally, the controller 700 further includes a communication component 703. Among them, the processing unit 701, the storage unit 702, and the communication component 703 are connected through a bus 704.

[0233] In the specific implementation process, at least one processing unit 701 executes the computer-executable instructions stored in the storage unit 702, so that at least one processing unit 701 executes the above-mentioned method.

[0234] For the specific implementation process of the processing unit 701, reference can be made to the above method embodiment, and its implementation principle and technical effect are similar, so they will not be elaborated here in this embodiment.

[0235] In the above embodiment, it should be understood that the processing unit may be a central processing unit (English: Central Processing Unit, abbreviated as: CPU), or other general-purpose processing units, digital signal processing units (English: Digital Signal Processor, abbreviated as: DSP), application-specific integrated circuits (English: Application Specific Integrated Circuit, abbreviated as: ASIC), etc. The general-purpose processing unit may be a microprocessing unit or the processing unit may also be any conventional processing unit, etc. The steps of the method disclosed in combination with the invention can be directly embodied as being completed by the execution of the hardware processing unit, or completed by the combination of the hardware and software modules in the processing unit.

[0236] The storage unit may include a high-speed storage unit (Random Access Memory, RAM), and may also include a non-volatile storage unit (Non-volatile Memory, NVM), such as at least one disk storage unit.

[0237] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0238] The present application also provides a computer program product, including a computer program which, when executed by a processing unit, implements the above-mentioned method.

[0239] The present application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processing unit, implement the above-mentioned method.

[0240] The above-mentioned readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory unit (SRAM), an electrically erasable programmable read-only memory unit (EEPROM), an erasable programmable read-only memory unit (EPROM), a programmable read-only memory unit (PROM), a read-only memory unit (ROM), a magnetic storage unit, a flash memory unit, a magnetic disk or an optical disk. The readable storage medium may be any available medium accessible by a general-purpose or special-purpose computer.

[0241] An exemplary readable storage medium is coupled to the processing unit, enabling the processing unit to read information from and write information to the readable storage medium. Of course, the readable storage medium may also be a component of the processing unit. The processing unit and the readable storage medium may be located in an application specific integrated circuit (ASIC). Of course, the processing unit and the readable storage medium may also exist as discrete components in a device.

[0242] The division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the couplings, direct couplings or communication connections shown or discussed between each other may be indirect couplings or communication connections through some interfaces, devices or units, and may be in electrical, mechanical or other forms.

[0243] The units described 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 to 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.

[0244] In addition, each functional unit in various embodiments of the present invention may be integrated in a processing unit, may exist separately as individual physical units, or two or more units may be integrated in one unit.

[0245] If a function 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 invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present invention. The foregoing storage medium includes: USB flash drives, mobile hard disks, read-only storage units (ROM, Read-Only Memory), random access storage units (RAM, Random Access Memory), magnetic disks, or optical discs, etc., which can store program codes of various media.

[0246] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps including the above method embodiments; and the foregoing storage medium includes: ROM, RAM, magnetic disks, or optical discs, etc., which can store program codes of various media.

[0247] Finally, it should be noted that: After considering the specification and practicing the invention disclosed herein, those skilled in the art will easily think of other implementation manners of the present invention. The present invention is intended to cover any variations, uses, or adaptations of the present invention, and these variations, uses, or adaptations follow the general principles of the present invention and include common general knowledge or conventional technical means in the technical field not disclosed in the present invention. It is not limited to the exact structures already described and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A vehicle brake system intelligent maintenance method, characterized in that: A controller applied to an electromechanical brake (EMB) system, the method comprising: Collecting multi-dimensional status data of the EMB system; Inputting the multi-dimensional state data into a pre-set dynamic analysis model to determine the health of the EMB system, wherein the dynamic analysis model includes an electrical degradation analysis model, a mechanical wear analysis model, and an environmental coupling analysis model; Generate maintenance suggestions based on the health status and pre-set dynamic thresholds; The maintenance suggestions are presented to the user via the vehicle-mounted terminal.

2. The method according to claim 1, characterized in that The multi-dimensional status data includes charging and discharging parameters of the energy storage module, operating parameters of the wheel-end motor, real-time displacement of the brake friction pad and the brake disc, vehicle braking behavior data, and vehicle use environment data.

3. The method according to claim 2, characterized in that The charging and discharging parameters of the energy storage module include voltage, current, and charging time; the operating parameters of the wheel-end motor include voltage, current, and the deviation value between the expected clamping force and the actual clamping force; the vehicle braking behavior data include initial braking speed, deceleration, braking duration, and final speed; and the vehicle usage environment data include geographic location, driving path slope, load weight, and road adhesion coefficient.

4. The method according to claim 3, characterized in that The health includes electrical health, mechanical health and environmental health. Inputting the multi-dimensional state data into a pre-set dynamic analysis model to determine the health of the EMB system includes: Calculating the electrical health according to the charge and discharge parameters of the energy storage module and the electrical degradation analysis model; The mechanical health is calculated based on the operating parameters of the wheel-end motor, the real-time displacement of the brake friction pad and the brake disc, the vehicle braking behavior data, and the mechanical wear analysis model; The environmental health degree is calculated based on the vehicle usage environment data, the vehicle braking behavior data and the environmental coupling analysis model.

5. The method according to claim 4, characterized in that Generating maintenance suggestions according to the health status and a preset dynamic threshold includes: When any of the health levels is lower than the corresponding dynamic threshold, a low-level maintenance suggestion is generated, wherein the low-level maintenance suggestion indicates that the user is advised to perform maintenance within a preset period of time; When two or more of the health degrees are lower than corresponding dynamic thresholds, an advanced maintenance suggestion is generated, where the advanced maintenance suggestion indicates that the user is advised to perform maintenance immediately.

6. The method according to claim 1, characterized in that Before generating a maintenance suggestion according to the health level and a preset dynamic threshold, the method further includes: The dynamic threshold is set based on pre-collected vehicle environment information, historical braking information, and design specifications of various components of the EMB system.

7. The method according to claim 6, characterized in that The dynamic thresholds include electrical dynamic thresholds, mechanical dynamic thresholds and environmental dynamic thresholds. The dynamic thresholds are set based on the pre-collected vehicle environmental information, historical braking information and design specifications of each component of the EMB system, including: Based on the design specifications of the various components of the EMB system, an initial electrical dynamic threshold, an initial mechanical dynamic threshold, and an initial environmental dynamic threshold are set; Calculating a capacitor performance attenuation acceleration factor according to the vehicle environment information; Exponentially scaling the initial electrical dynamic threshold according to the acceleration factor to generate the electrical dynamic threshold; Calculating the wear compensation coefficient of the friction plate according to the historical braking information; The initial mechanical dynamic threshold is multiplied by the wear compensation coefficient to generate the mechanical dynamic threshold; Calculating a terrain load factor based on the vehicle environment information; The initial environmental dynamic threshold and the terrain load coefficient are linearly weighted to generate an environmental dynamic threshold.

8. An intelligent maintenance device for a vehicle braking system, characterized in that: include: The acquisition module is used to collect multi-dimensional status data of the EMB system; An analysis module, used for inputting the multi-dimensional state data into a preset dynamic analysis model to determine the health of the EMB system, wherein the dynamic analysis model includes an electrical degradation analysis model, a mechanical wear analysis model, and an environmental coupling analysis model; A generation module, used to generate maintenance suggestions according to the health status and a preset dynamic threshold; The display module is used to display the maintenance suggestion to the user through the vehicle terminal.

9. A controller, characterized in that: include: Storage unit, processing unit; The storage unit stores computer-executable instructions; The processing unit executes the computer-executable instructions stored in the storage unit, so that the processing unit executes the vehicle brake system intelligent maintenance method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processing unit, are used to implement the vehicle brake system intelligent maintenance method according to any one of claims 1 to 7.

Images