Tire wear diagnosis method, device and equipment and storage medium

Abstract

The invention discloses a tire wear diagnosis method, device and equipment and a storage medium, and the method comprises the steps: generating a tire wear calculation model based on obtained key factors affecting tire wear, wherein the key factors comprise vehicle driving mileage, historical driving road condition information, driving habits, vehicle tire pressure and four-wheel positioning information; and calculating a current tire wear coefficient according to the tire wear calculation model, and diagnosing tire wear by using the current tire wear coefficient. The abnormal condition of tire wear can be effectively identified, a terminal client is reminded of the tire wear state of the vehicle, and the use safety of the vehicle tire is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of tire diagnosis, and in particular to a tire wear diagnosis method, device, equipment and storage medium. Background Art

[0002] Tire wear on new energy vehicles is affected by factors such as mileage, usage time, and driving habits. Frequent strong braking and high-frequency starting and acceleration can cause significant wear on tires. Other issues, such as the vehicle's driving pattern (different front and rear drive torque), improper tire pressure, and out-of-tolerance four-wheel alignment, can also cause abnormal tire wear, significantly reducing tire life. Currently, 4S dealerships and repair shops typically roughly estimate whether a vehicle requires maintenance based on the scheduled maintenance schedule, then have customer service staff call customers based on this rough estimate to remind them to return for maintenance. However, these reminders are inaccurate, leading to premature tire replacements, increasing costs and waste for car owners. Furthermore, abnormal tire wear can occur due to high mileage, excessive brake wear, and undetected abnormal vehicle conditions (such as changes in tire pressure and four-wheel alignment). At these times, even when tire maintenance reminders are needed, they often aren't, creating safety risks.

[0003] Therefore, timely and accurate judgment of the tire wear status of new energy vehicles and reminders to car owners are technical issues that need to be solved urgently. Summary of the Invention

[0004] The main purpose of the present invention is to provide a tire wear diagnosis method, device, equipment and storage medium that can effectively identify abnormal tire wear, remind end customers of the tire wear status of their vehicles, and ensure the safety of vehicle tire use.

[0005] In a first aspect, the present application provides a tire wear diagnosis method, wherein the method comprises the steps of:

[0006] Generate a tire wear calculation model based on the acquired key factors affecting tire wear, wherein the key factors include: vehicle mileage, historical road condition information, driving habits, vehicle tire pressure, and four-wheel alignment information;

[0007] A current tire wear coefficient is calculated according to a tire wear calculation model, and tire wear is diagnosed using the current tire wear coefficient.

[0008] In combination with the first aspect above, as an optional implementation method, key factors affecting tire wear are obtained based on the vehicle cloud platform, and are standardized to form a statistical / regression model;

[0009] Establishing a correlation model between the statistical / regression model and preset calibrated tire standard operating condition wear, and using the correlation model to output a wear coefficient of factors affecting tire wear;

[0010] Based on the wear coefficients of the factors influencing tire wear, a current tire wear coefficient calculation model is calculated.

[0011] In conjunction with the first aspect above, as an optional implementation, driving habit information and road condition information are obtained, wherein the driving habit information includes vehicle speed, number of turns, and rapid acceleration and deceleration, and the road condition information includes different road surface types and road quality;

[0012] Input the driving habit information and the road condition information into the correlation model, and output the influence coefficient λ under different driving habits and road conditions. (m) ;

[0013] Based on the calibration and measured data statistics, the torque distribution coefficient K of the front and rear axles of the vehicle is obtained;

[0014] Based on the measured data of vehicle driving under standard driving conditions, the tire wear observation value S0 is obtained;

[0015] Based on the calculated camber angle change factor α (n) , toe angle variation factor β (n) The coupling factor α between camber and toe (n) β (n) , and the coefficients corresponding to each factor, calculate the control factor ε caused by abnormal tire wear caused by changes in four-wheel alignment parameters (n) ;

[0016] The vehicle speed, lateral acceleration, brake pedal position, drive torque / speed, and four-wheel pulse information are acquired via the CAN bus, and the tire load N is obtained by calibration based on the vibration characteristics of the tire load changes.

[0017] Real-time acquisition of tire pressure P and tire temperature T through the TPMS sensor in the tire;

[0018] The current tire wear coefficient calculation model expression is: M = k(S0 + λ (m) ∫L1 L2 ε (n) N / ((aP+b)(cT+d))dL), where a and b are the wear coefficients related to tire pressure, c and d are the wear coefficients related to temperature, L1 and L2 are the initial and final mileages of the calculation, and L is the total mileage.

[0019] In combination with the first aspect above, as an optional implementation method, the vehicle information obtained in real time is uploaded to the vehicle cloud platform, wherein the vehicle information includes: vehicle driving trajectory, speed, acceleration, tire pressure and four-wheel alignment information;

[0020] The tire wear calculation model deployed on the cloud platform is used to output the current tire wear coefficient.

[0021] In combination with the first aspect above, as an optional implementation method, setting a tire wear calibration value;

[0022] Determining whether the current tire wear coefficient is greater than the tire wear calibration value;

[0023] If so, the vehicle is identified as worn and the vehicle-side information is pushed through the cloud to provide an early warning and suggest that the user check the wear.

[0024] In combination with the first aspect above, as an optional implementation method, the real-time monitored tire pressure is compared with a preset tire pressure standard value;

[0025] If the real-time tire pressure is greater than the preset tire pressure standard value, the vehicle-side information will be pushed through the cloud to suggest the user to adjust the tire pressure value to the preset value.

[0026] In combination with the first aspect above, as an optional implementation method, different levels of tolerance limits are preset;

[0027] If the real-time monitoring of the four-wheel alignment parameter deviation exceeds the first deviation limit, the cloud will push the vehicle-side information to prompt the system to monitor the four-wheel alignment deviation and recommend checking the four-wheel alignment parameters;

[0028] If the real-time monitoring of the four-wheel alignment parameter deviation is greater than the second deviation limit, the cloud will push the vehicle-side information to remind the vehicle that there is a risk of abnormal tire wear and it is recommended to check the tire status in time.

[0029] In a second aspect, the present application provides a tire wear diagnosis device, which includes:

[0030] a processing module configured to generate a tire wear calculation model based on the acquired key factors affecting tire wear, wherein the key factors include: vehicle mileage, historical road condition information, driving habits, vehicle tire pressure, and four-wheel alignment information;

[0031] The diagnosis module is used to calculate the current tire wear coefficient according to the tire wear calculation model, and diagnose the tire wear using the current tire wear coefficient.

[0032] In a third aspect, the present application further provides an electronic device comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method described in any one of the first aspects is implemented.

[0033] In a fourth aspect, the present application further provides a computer-readable storage medium storing computer program instructions, which, when executed by a computer, enables the computer to execute any one of the methods described in the first aspect.

[0034] This application provides a tire wear diagnosis method, apparatus, device, and storage medium. The method includes the following steps: generating a tire wear calculation model based on key factors affecting tire wear, including vehicle mileage, historical road conditions, driving habits, tire pressure, and four-wheel alignment information; calculating the current tire wear coefficient based on the tire wear calculation model, and diagnosing tire wear using the current tire wear coefficient. This application can effectively identify abnormal tire wear, alert end users to the tire wear status of their vehicles, and ensure safe use of vehicle tires.

[0035] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0037] Figure 1 This is a flow chart of a tire wear diagnosis method provided in an embodiment of the present application;

[0038] Figure 2 A schematic diagram of a tire wear diagnosis device provided in an embodiment of the present application;

[0039] Figure 3 This is a tire wear diagnosis diagram provided in an embodiment of the present application;

[0040] Figure 4 A schematic diagram of an electronic device provided in an embodiment of the present application;

[0041] Figure 5 A schematic diagram of a computer-readable program medium provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0043] Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the blocks shown in the drawings are functional entities that do not necessarily correspond to physically or logically separate entities.

[0044] The embodiments of the present application provide a tire wear diagnosis method, device, equipment and storage medium, which can effectively identify abnormal tire wear, remind end customers of the tire wear status of the vehicle, and ensure the safe use of vehicle tires.

[0045] To achieve the above technical effects, the general ideas of this application are as follows:

[0046] A tire wear diagnosis method, the method comprising the steps of:

[0047] S101: Generate a tire wear calculation model based on the acquired key factors affecting tire wear, wherein the key factors include: vehicle mileage, historical driving road condition information, driving habits, vehicle tire pressure, and four-wheel alignment information.

[0048] S102: Calculating a current tire wear coefficient according to a tire wear calculation model, and diagnosing tire wear using the current tire wear coefficient.

[0049] The embodiments of the present application are further described in detail below with reference to the accompanying drawings.

[0050] Reference Figure 1 , Figure 1 The figure shows a flow chart of a tire wear diagnosis method provided by the present invention. Figure 1 As shown, the method includes the steps of:

[0051] Step S101: Generate a tire wear calculation model based on the acquired key factors affecting tire wear, wherein the key factors include: vehicle mileage, historical driving road condition information, driving habits, vehicle tire pressure and four-wheel alignment information.

[0052] Specifically, the key factors affecting tire wear are obtained based on the vehicle cloud platform, and standardized to form a statistical / regression model;

[0053] Establishing a correlation model between the statistical / regression model and preset calibrated tire standard operating condition wear, and using the correlation model to output a wear coefficient of factors affecting tire wear;

[0054] Based on the wear coefficients of the factors influencing tire wear, a current tire wear coefficient calculation model is calculated.

[0055] The calculation model of the current tire wear coefficient is calculated based on the wear coefficient of the factors affecting tire wear, including:

[0056] Acquiring driving habit information and road condition information, wherein the driving habit information includes vehicle speed, number of turns, and sudden acceleration and deceleration, and the road condition information includes different road surface types and road quality;

[0057] Input the driving habit information and the road condition information into the correlation model, and output the influence coefficient λ under different driving habits and road conditions. (m) ;

[0058] Based on the calibration and measured data statistics, the torque distribution coefficient K of the front and rear axles of the vehicle is obtained;

[0059] Based on the measured data of vehicle driving under standard driving conditions, the tire wear observation value S0 is obtained;

[0060] Based on the calculated camber angle change factor α (n) , toe angle variation factor β (n) The coupling factor α between camber and toe (n) β (n) , and the coefficients corresponding to each factor, calculate the control factor ε caused by abnormal tire wear caused by changes in four-wheel alignment parameters (n) ;

[0061] The vehicle speed, lateral acceleration, brake pedal position, drive torque / speed, and four-wheel pulse information are acquired via the CAN bus, and the tire load N is obtained by calibration based on the vibration characteristics of the tire load changes.

[0062] Real-time acquisition of tire pressure P and tire temperature T through the TPMS sensor in the tire;

[0063] The current tire wear coefficient calculation model expression is: M = k(S0 + λ (m) ∫L1 L2 ε (n) N / ((aP+b)(cT+d))dL), where a and b are the wear coefficients related to tire pressure, c and d are the wear coefficients related to temperature, L1 and L2 are the initial and final mileages of the calculation, and L is the total mileage.

[0064] For ease of understanding, the calculation model of the tire wear coefficient M is as follows:

[0065] M=k(S0+λ (m) ∫L1 L2 ε (n) N / ((aP+b)(cT+d))dL)

[0066] Where k is the torque distribution coefficient between the front and rear axles. Tire wear is significantly affected by different driving torques. For example, in a front-wheel drive vehicle, the front wheels are the driving wheels, while the rear wheels are the driven wheels. Under the same conditions, the front wheels will wear faster, while the rear wheels will wear slower. This factor also applies to four-wheel drive vehicles with different torque distribution patterns. This factor can be used to assess the wear difference between the front and rear wheels, thereby guiding the front and rear wheel rotation or replacement of the front or rear tires.

[0067] Among them, S0 is the observed value of tire wear after a certain mileage under standard operating conditions. This data is calibrated in the early development of each vehicle and is obtained from actual measured data under standard operating conditions (standard load / tire pressure / driving mode), as well as standard driving conditions (driving road requirements, lateral and longitudinal acceleration requirements, etc.); at the same time, the specific coefficient value of the k factor also varies according to the torque distribution between the front and rear axles, and different coefficients k1, k2... are obtained from calibration and actual measured data.

[0068] where λ (m) It is the influence coefficient under different driving habits and driving conditions. Driving habits include but are not limited to vehicle speed, number of turns, and sudden acceleration and deceleration; driving conditions mainly include different road types and road quality. Vehicle speed and lateral and longitudinal acceleration will affect the contact between the tire and the ground and the degree of tire deformation, which in turn affects tire wear. By real-time monitoring of vehicle speed and acceleration, as well as vehicle driving trajectory, etc., uploading them to the cloud platform, the cloud analyzes the different road types (such as asphalt roads, cement roads, gravel roads, etc.) passed by the driving trajectory, as well as road conditions such as road flatness and potholes. The above driving habits and driving conditions are standardized, and statistical / regression models are established. A correlation model is established with tire loss data under standard working conditions to obtain the influence coefficient λ. (m) .

[0069] where ε (n) It is the controlling factor of abnormal tire wear caused by changes in four-wheel alignment parameters. During long-term use of the vehicle, changes in driving conditions and the status of various vehicle parts will cause changes in four-wheel alignment parameters. This change includes static parameter deviations of the vehicle itself, as well as dynamic four-wheel alignment parameter changes under conditions such as vehicle steering, load transfer, and bouncing. Since four-wheel alignment parameters are the main cause of abnormal wear such as uneven tire wear, real-time monitoring of four-wheel alignment parameter changes and uploading statistical data to the vehicle cloud platform are crucial for determining abnormal tire wear; here, ε is established (n) =iα(n) +jβ (n) +lα (n) β (n) The four-wheel alignment parameter that affects tire wear is mainly the camber angle change factor Δ (n) and toe angle variation factor β (n) , and the coupling relationship factor lα between camber and toe (n) β (n) Determine, where i, j, and l are the influence coefficients of each factor respectively.

[0070] The four-wheel alignment parameters can be measured by the steering knuckle sensor to monitor the toe angle and camber angle in real time.

[0071] α (n) The influencing factor is calculated based on the tire contact patch change and friction energy change corresponding to different camber angle deviation values. The eccentric wear index relationship is established based on the tire friction energy data. Similarly, the toe angle change factor β (n) , the coupling factor α between camber and toe (n) β (n) , the partial wear index relationship can be established based on the converted tire friction energy data. Finally, ε (n) .

[0072] Where L1 and L2 are the initial and final mileages of the calculation, and L is the total mileage, which refers to the additional increase in tire wear due to non-standard operating conditions;

[0073] Where N represents the tire load, which obtains the vehicle speed, lateral acceleration, brake pedal position information, drive torque / speed information, and extracted four-wheel pulse information through the CAN bus, and calibrates the tire load according to the vibration characteristics of the tire load change; where P represents the tire pressure, T represents the tire temperature, which can be obtained in real time through the TPMS sensor in the tire, a and b are the wear coefficients with tire pressure, and c and d are the wear coefficients with temperature, which are obtained by calibrating the tire wear under standard working conditions.

[0074] In other words, Model M positively introduces key factors that affect tire wear, such as vehicle driving habits, tire pressure, four-wheel alignment, and acceleration and deceleration. Based on the standardized processing of historical vehicle data on the cloud platform, a statistical / regression model is established, and a correlation model is established with the preset calibrated tire standard operating condition wear. The correlation model determines the wear coefficient affecting each factor, and finally forms the current tire wear coefficient calculation model. This tire wear diagnosis model is more accurate and effective.

[0075] Step S102: Calculate the current tire wear coefficient according to the tire wear calculation model, and diagnose tire wear using the current tire wear coefficient.

[0076] Specifically, the real-time vehicle information acquired is uploaded to the vehicle cloud platform. The vehicle information includes: vehicle driving trajectory, speed, acceleration, tire pressure and four-wheel alignment information; the current tire wear coefficient is output using the tire wear calculation model deployed on the cloud platform.

[0077] Set a tire wear calibration value; determine whether the current tire wear coefficient is greater than the tire wear calibration value; if so, identify that the vehicle has been worn, push vehicle-side information through the cloud to provide an early warning prompt, and suggest that the user check the wear condition.

[0078] In one embodiment, the real-time monitored tire pressure is compared with a preset tire pressure standard value;

[0079] If the real-time tire pressure is greater than the preset tire pressure standard value, the vehicle-side information will be pushed through the cloud to suggest the user to adjust the tire pressure value to the preset value.

[0080] Optionally, preset tolerance limits of different levels;

[0081] If the real-time monitoring of the four-wheel alignment parameter deviation exceeds the first deviation limit, the cloud will push the vehicle-side information to prompt the system to monitor the four-wheel alignment deviation and recommend checking the four-wheel alignment parameters;

[0082] If the real-time monitoring of the four-wheel alignment parameter deviation is greater than the second deviation limit, the cloud will push the vehicle-side information to remind the vehicle that there is a risk of abnormal tire wear and it is recommended to check the tire status in time.

[0083] It is understandable that real-time monitoring of the impact of tire pressure, four-wheel alignment parameter changes, and other factors on tire wear can effectively identify abnormal tire wear. This eliminates the need for additional sensors inside the tire while fully considering multiple external factors that affect tire wear. Current mainstream models simply calculate tire wear under normal conditions and are unable to analyze, judge, or provide early warnings for abnormal wear.

[0084] To sum up, the tire wear diagnosis method based on the vehicle cloud platform of this application can effectively remind the end customers of the tire wear status of the vehicle, remind them of low / high tire pressure, front and rear wheel rotation, four-wheel alignment changes, etc., and timely detect tire uneven wear / excessive wear problems to ensure the safe use of vehicle tires.

[0085] Reference Figure 2 , Figure 2 FIG. 1 is a schematic diagram of a tire wear diagnosis device provided by the present invention, as shown in FIG. Figure 2 As shown, the device includes:

[0086] Processing module 201: It is used to generate a tire wear calculation model based on the acquired key factors affecting tire wear, wherein the key factors include: vehicle mileage, historical driving road condition information, driving habits, vehicle tire pressure and four-wheel alignment information.

[0087] Diagnostic module 202: used to calculate the current tire wear coefficient according to the tire wear calculation model, and diagnose tire wear using the current tire wear coefficient.

[0088] Furthermore, in a possible implementation, the processing module is further configured to obtain key factors affecting tire wear based on the vehicle cloud platform, perform standardization processing, and form a statistical / regression model;

[0089] Establishing a correlation model between the statistical / regression model and preset calibrated tire standard operating condition wear, and using the correlation model to output a wear coefficient of factors affecting tire wear;

[0090] Based on the wear coefficients of the factors influencing tire wear, a current tire wear coefficient calculation model is calculated.

[0091] Furthermore, in a possible implementation, the processing module is further configured to obtain driving habit information and road condition information, wherein the driving habit information includes vehicle speed, number of turns, and rapid acceleration and deceleration, and the road condition information includes different road surface types and road quality;

[0092] Input the driving habit information and the road condition information into the correlation model, and output the influence coefficient λ under different driving habits and road conditions. (m) ;

[0093] Based on the calibration and measured data statistics, the torque distribution coefficient K of the front and rear axles of the vehicle is obtained;

[0094] Based on the measured data of vehicle driving under standard driving conditions, the tire wear observation value S0 is obtained;

[0095] Based on the calculated camber angle change factor α (n) , toe angle variation factor β (n) The coupling factor α between camber and toe (n) β (n) , and the coefficients corresponding to each factor, calculate the control factor ε caused by abnormal tire wear caused by changes in four-wheel alignment parameters (n) ;

[0096] The vehicle speed, lateral acceleration, brake pedal position, drive torque / speed, and four-wheel pulse information are acquired via the CAN bus, and the tire load N is obtained by calibration based on the vibration characteristics of the tire load changes.

[0097] Real-time acquisition of tire pressure P and tire temperature T through the TPMS sensor in the tire;

[0098] The current tire wear coefficient calculation model expression is: M = k(S0 + λ (m) ∫L1 L2 ε (n) N / ((aP+b)(cT+d))dL), where a and b are the wear coefficients related to tire pressure, c and d are the wear coefficients related to temperature, L1 and L2 are the initial and final mileages of the calculation, and L is the total mileage.

[0099] Furthermore, in a possible implementation, the diagnostic module is further configured to upload vehicle information acquired in real time to a vehicle cloud platform, wherein the vehicle information includes: vehicle driving trajectory, speed, acceleration, tire pressure, and four-wheel alignment information;

[0100] The tire wear calculation model deployed on the cloud platform is used to output the current tire wear coefficient.

[0101] Furthermore, in a possible implementation, the diagnostic module is further configured to set a tire wear calibration value;

[0102] Determining whether the current tire wear coefficient is greater than the tire wear calibration value;

[0103] If so, the vehicle is identified as worn and the vehicle-side information is pushed through the cloud to provide an early warning and suggest that the user check the wear.

[0104] Furthermore, in a possible implementation manner, the diagnostic module is further configured to compare the real-time monitored tire pressure with a preset tire pressure standard value;

[0105] If the real-time tire pressure is greater than the preset tire pressure standard value, the vehicle-side information will be pushed through the cloud to suggest the user to adjust the tire pressure value to the preset value.

[0106] Furthermore, in a possible implementation, the diagnostic module is further configured to preset different levels of tolerance limits;

[0107] If the real-time monitoring of the four-wheel alignment parameter deviation exceeds the first deviation limit, the cloud will push the vehicle-side information to prompt the system to monitor the four-wheel alignment deviation and recommend checking the four-wheel alignment parameters;

[0108] If the real-time monitoring of the four-wheel alignment parameter deviation is greater than the second deviation limit, the cloud will push the vehicle-side information to remind the vehicle that there is a risk of abnormal tire wear and it is recommended to check the tire status in time.

[0109] Reference Figure 3 , Figure 3 The figure shows a schematic diagram of tire wear diagnosis provided by the present invention, as shown in FIG. Figure 3As shown:

[0110] Real-time vehicle information can be uploaded to the vehicle cloud platform through vehicle interaction modules such as T-BOX. The vehicle cloud platform receives vehicle information from the vehicle-side module and executes the tire wear diagnosis system on the cloud platform, which then transmits the diagnosis results to the vehicle-side module through the interaction module. The tire wear coefficient diagnosis process is based on the tire wear calculation model.

[0111] Specifically, based on the calculated tire wear coefficient M, determine whether M is greater than the set threshold. If so, determine that the tire is worn, push the vehicle computer warning information, and send it to the vehicle end.

[0112] For easier understanding, let's take an example. Scenario 1: The system has a preset tire pressure standard value based on vehicle load calibration. For example, when it is monitored that the customer is driving with a full load for a long time, but the tire pressure is low (the system presets the lower limit of tire pressure under different loads), the cloud diagnosis will push the vehicle-side information: You have been driving with a full load for a long time, and it is recommended to adjust the tire pressure to 290kpa in real time. Or if the vehicle is equipped with a tire pressure adjustment device, the tire pressure can be adaptively adjusted to the standard value through instructions.

[0113] Scenario 2: Tire wear diagnosis can determine the wear of the front and rear axle tires based on a calculation model. The diagnostic system presets the maximum difference in front and rear axle wear (such as when the front and rear wheel wear is greater than 10,000 kilometers). If this limit is triggered, the cloud diagnosis will push a vehicle-side message: It is recommended that you check the wear of the front and rear wheels and perform a cross-wheel rotation operation in time; when the system determines that the tire is worn to the tire limit (calibrated to the preset tire wear limit), the system pushes a vehicle-side message: Please check the tire wear. If the tire is worn to the wear mark line, it is recommended that you replace the tire in time to ensure safe driving.

[0114] Scenario 3: The system presets standard four-wheel alignment parameter values ​​and different levels of deviation limits. When the system diagnoses that the four-wheel alignment parameters have a large deviation, the cloud pushes a vehicle-side information: the system monitors that the four-wheel alignment has a deviation, and it is recommended that you go to the 4S store to check the four-wheel alignment parameters in time; if the four-wheel alignment parameter deviation level is medium, based on the long-term driving of the vehicle and the continuous accumulation of tire wear, when the tire uneven wear limit is triggered, the system will issue an early warning: the tires may have abnormal wear, and it is recommended that you check the tires in time. If there is any abnormality, it is recommended to go to the 4S store for inspection.

[0115] It should be explained that scenarios 1 and 3 can effectively identify abnormal tire wear by real-time monitoring of the impact of tire pressure, four-wheel alignment parameter changes, etc. on tire wear.

[0116] Based on the above scenario, after the client terminal performs the adjustment operation, the relevant operation information is synchronously uploaded to the vehicle cloud platform, so that the prerequisites of the tire wear model are updated in real time and iterated in a cycle.

[0117] In summary, this application can timely and accurately judge the tire wear status of new energy vehicles, thereby reminding the car owner.

[0118] Refer to the following Figure 4 An electronic device 400 according to this embodiment of the present invention will be described. Figure 4 The electronic device 400 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0119] like Figure 4 As shown, electronic device 400 is implemented as a general-purpose computing device. Components of electronic device 400 may include, but are not limited to, at least one processing unit 410, at least one storage unit 420, and a bus 430 connecting various system components (including storage unit 420 and processing unit 410).

[0120] The storage unit stores program codes, which can be executed by the processing unit 410, so that the processing unit 410 performs the steps according to various exemplary embodiments of the present invention described in the above “Example Method” section of this specification.

[0121] The storage unit 420 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit 422 , and may further include a read-only memory unit (ROM) 423 .

[0122] The storage unit 420 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0123] Bus 430 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0124] The electronic device 400 may also communicate with one or more external devices (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 400, and / or any device that enables the electronic device 400 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication may occur via an input / output (I / O) interface 450. Furthermore, the electronic device 400 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 460. As shown, the network adapter 460 communicates with other modules of the electronic device 400 via a bus 430. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 400, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0125] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0126] According to the solution of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above-mentioned method of this specification is stored. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product, which includes program code. When the program product is executed on a terminal device, the program code is used to cause the terminal device to perform the steps according to various exemplary embodiments of the present invention described in the "Exemplary Methods" section of this specification.

[0127] refer to Figure 5 As shown, a program product 500 for implementing the above method according to an embodiment of the present invention is described. The program product 500 may be a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0128] The program product may be implemented in any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0129] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0130] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0131] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0132] Furthermore, the above-described figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes illustrated in the above-described figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0133] The foregoing is merely a list of specific embodiments of the present application, intended to enable those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the broadest scope consistent with the principles and novel features of the present application.

[0134] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

Claims

1. A tire wear diagnosis method, characterized in that: include: Generate a tire wear calculation model based on the acquired key factors affecting tire wear, wherein the key factors include: vehicle mileage, historical road condition information, driving habits, vehicle tire pressure, and four-wheel alignment information; A current tire wear coefficient is calculated according to a tire wear calculation model, and tire wear is diagnosed using the current tire wear coefficient.

2. The method according to claim 1, characterized in that The step of generating a tire wear calculation model based on the acquired key factors affecting tire wear includes: Obtain key factors affecting tire wear based on the vehicle cloud platform, perform standardization, and form a statistical / regression model; Establishing a correlation model between the statistical / regression model and preset calibrated tire standard operating condition wear, and using the correlation model to output a wear coefficient of factors affecting tire wear; Based on the wear coefficients of the factors influencing tire wear, a current tire wear coefficient calculation model is calculated.

3. The method according to claim 2, characterized in that The calculation model of the current tire wear coefficient is calculated based on the wear coefficient of the factors affecting tire wear, including: Acquiring driving habit information and road condition information, wherein the driving habit information includes vehicle speed, number of turns, and sudden acceleration and deceleration, and the road condition information includes different road surface types and road quality; Input the driving habit information and the road condition information into the correlation model, and output the influence coefficient λ under different driving habits and road conditions. (m) ; Based on the calibration and measured data statistics, the torque distribution coefficient K of the front and rear axles of the vehicle is obtained; Based on the measured data of vehicle driving under standard driving conditions, the tire wear observation value S0 is obtained; Based on the calculated camber angle change factor α (n) , toe angle variation factor β (n) The coupling factor α between camber and toe (n) β (n) , and the coefficients corresponding to each factor, calculate the control factor ε caused by abnormal tire wear caused by changes in four-wheel alignment parameters (n) ; The vehicle speed, lateral acceleration, brake pedal position, drive torque / speed, and four-wheel pulse information are acquired via the CAN bus, and the tire load N is obtained by calibration based on the vibration characteristics of the tire load changes. Real-time acquisition of tire pressure P and tire temperature T through the TPMS sensor in the tire; The current tire wear coefficient calculation model expression is: M = k(S0 + λ (m) ∫L1 L2 ε (n) N / ((aP+b)(cT+d))dL), where a and b are the wear coefficients related to tire pressure, c and d are the wear coefficients related to temperature, L1 and L2 are the initial and final mileages of the calculation, and L is the total mileage.

4. The method according to claim 1, wherein Calculating the current tire wear coefficient according to the tire wear calculation model includes: Upload the real-time vehicle information to the vehicle cloud platform, including vehicle trajectory, speed, acceleration, tire pressure and four-wheel alignment information; The tire wear calculation model deployed on the cloud platform is used to output the current tire wear coefficient.

5. The method according to claim 1, characterized in that The diagnosing tire wear by using the current tire wear coefficient includes: Set tire wear calibration value; Determining whether the current tire wear coefficient is greater than the tire wear calibration value; If so, the vehicle is identified as worn and the vehicle-side information is pushed through the cloud to provide an early warning and suggest that the user check the wear.

6. The method according to claim 5, characterized in that Also includes: Compare the real-time monitored tire pressure with the preset tire pressure standard value; If the real-time tire pressure is greater than the preset tire pressure standard value, the vehicle-side information will be pushed through the cloud to suggest the user to adjust the tire pressure value to the preset value.

7. The method according to claim 6, characterized in that Also includes: Preset different levels of tolerance limits; If the real-time monitoring of the four-wheel alignment parameter deviation exceeds the first deviation limit, the cloud will push the vehicle-side information to prompt the system to monitor the four-wheel alignment deviation and recommend checking the four-wheel alignment parameters; If the real-time monitoring of the four-wheel alignment parameter deviation is greater than the second deviation limit, the cloud will push the vehicle-side information to remind the vehicle that there is a risk of abnormal tire wear and it is recommended to check the tire status in time.

8. A tire wear diagnostic device, characterized in that: include: a processing module configured to generate a tire wear calculation model based on the acquired key factors affecting tire wear, wherein the key factors include: vehicle mileage, historical road condition information, driving habits, vehicle tire pressure, and four-wheel alignment information; The diagnosis module is used to calculate the current tire wear coefficient according to the tire wear calculation model, and diagnose the tire wear using the current tire wear coefficient.

9. An electronic device, characterized in that: The electronic device comprises: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer program instructions are stored therein, and when the computer program instructions are executed by a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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