Method for predicting tire wear condition based on vehicle acceleration

Abstract

The invention relates to the technical field of tire monitoring, in particular to a method for predicting a tire wear condition based on vehicle acceleration, and the method comprises the steps: obtaining an acceleration parameter of a driver; establishing a mapping relation between acceleration parameters and load distribution; building a tire loss database, and training a loss model according to the tire loss database; calling a corresponding current acceleration parameter in the acceleration database based on driver identity information; according to the current acceleration parameter, the mapping relation, the loss model and the vehicle driving route, the predicted abrasion loss of each tire of the current driver in the driving process is obtained. According to the method, the total abrasion loss is divided into the intersection total abrasion loss, the turning total abrasion loss and the normal driving total abrasion loss, so that the intersection total abrasion loss, the turning total abrasion loss and the normal driving total abrasion loss are calculated respectively, the error between the prediction result and the actual abrasion condition is reduced, and the accuracy of the prediction result is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of tire monitoring, in particular to a method for predicting tire wear based on vehicle acceleration. BACKGROUND

[0002] As the medium of vehicle and ground, the wear of tire is closely related to the safety and comfort of vehicle during driving, therefore, it is necessary to predict the wear of tire to avoid the safety risk caused by excessive wear of tire.

[0003] In the prior art, on the one hand, the rough prediction of wear based on driving mileage does not consider the influence of key factors such as different driving styles of different drivers, vehicle load distribution and driving route on tire wear, resulting in large error between the prediction result and the actual wear condition and low prediction accuracy. On the other hand, although the prior art attempts to predict the wear of tire from acceleration or load, it ignores the redistribution of load weight of each tire of vehicle caused by acceleration in actual driving, resulting in large error between the prediction result and the actual wear condition and low prediction accuracy.

[0004] Therefore, the prior art has defects and needs to be improved. SUMMARY

[0005] The present application aims to provide a method for predicting tire wear based on vehicle acceleration to solve the problems in the prior art that, on the one hand, the rough prediction of wear based on driving mileage does not consider the influence of key factors such as different driving styles of different drivers, vehicle load distribution and driving route on tire wear, and on the other hand, although the prior art attempts to predict the wear of tire from acceleration or load, it ignores the redistribution of load weight of each tire of vehicle caused by acceleration in actual driving, resulting in large error between the prediction result and the actual wear condition and low prediction accuracy.

[0006] The present application provides a method for predicting tire wear based on vehicle acceleration, comprising: collecting acceleration data of each driver during each driving process, preprocessing the acceleration data to obtain standard acceleration data, storing the standard acceleration data into an acceleration database, and obtaining acceleration parameters of the driver according to the acceleration database; the acceleration parameters include start-up acceleration, braking acceleration and lateral acceleration; obtaining the structural parameters and mass distribution of the vehicle, calculating the load distribution proportion of each tire under different accelerations according to the structural parameters and mass distribution, and establishing a mapping relationship between the acceleration parameters and the load distribution; The tire loss under different loads and acceleration parameters of the tire with the same specification as the vehicle tire is detected by using a bench detection method, a tire loss database is constructed according to the detection data, and a loss model is trained according to the tire loss database; In response to the start of the vehicle, identity information of the current driver, a vehicle driving route and a total mass of the vehicle are obtained, the corresponding acceleration parameter is called in the acceleration database based on the identity information of the driver and is recorded as the current acceleration parameter; According to the current acceleration parameter, the mapping relationship, the loss model and the vehicle driving route, the predicted wear of each tire of the current driver in the driving process is obtained.

[0007] As a preferred technical solution of the method for predicting the tire wear condition based on the vehicle acceleration, the structure parameters and the mass distribution of the vehicle are obtained, the load distribution proportion of each tire under different accelerations is calculated according to the structure parameters and the mass distribution, and a mapping relationship between the acceleration parameter and the load distribution is established, including: For a single driving, before each start of the vehicle, the mass distribution of the vehicle is obtained, and the static load distribution proportion of each tire of the vehicle at rest is calculated according to the mass distribution and the structure parameters of the vehicle; In response to the start and driving of the vehicle, the acceleration parameter of the vehicle and the load distribution proportion of each tire corresponding to the driving process are collected, and the static load distribution proportion corresponding to a single driving, the acceleration parameter of the vehicle and the load distribution proportion of each tire in the driving process are stored as a data group in the mass distribution proportion data set; The mapping relationship is established according to the mass distribution proportion data set.

[0008] As a preferred technical solution of the method for predicting the tire wear condition based on the vehicle acceleration, the structure parameters include: the vehicle kerb mass, the maximum gross vehicle weight, the wheelbase of the vehicle, the track of the vehicle, the height of the center of gravity of the vehicle, the front axle distance of the center of gravity and the rear axle distance of the center of gravity.

[0009] As a preferred technical solution of the method for predicting the tire wear condition based on the vehicle acceleration, the tire loss under different loads and acceleration parameters of the tire with the same specification as the vehicle tire is detected by using a bench detection method, a tire loss database is constructed according to the detection data, and a loss model is trained according to the tire loss database, including: The start-up acceleration, the braking acceleration and the lateral acceleration are obtained, the start-up acceleration, the braking acceleration and the lateral acceleration are substituted into the mapping relationship respectively, the maximum load of each tire and the minimum load of each tire are obtained respectively, and the interval formed by the maximum load and the minimum load is recorded as the load interval; Select at least 3 tires with the same specifications as the vehicle tires as test samples, and use the test bench to detect the test samples. The detection conditions during the detection process include: applying different test loads to the test tires, respectively applying the start-up acceleration, the braking acceleration and the lateral acceleration to the test tires, and driving a unit length, so as to obtain a plurality of standard tire wear amounts corresponding to different test loads and different acceleration parameter conditions; the test load is selected by traversing the load interval by a preset step size; According to the plurality of standard tire wear amounts corresponding to different test loads and different acceleration parameter conditions, the tire wear database is constructed.

[0010] As a preferred technical solution of the method for predicting tire wear based on vehicle acceleration, the wear model is trained according to the tire wear database. If the input tire load and acceleration are input, the standard tire wear amount after driving a unit length is output.

[0011] As a preferred technical solution of the method for predicting tire wear based on vehicle acceleration, the current driver's predicted wear amount of each tire during driving is obtained according to the current acceleration parameter, the mapping relationship, the wear model and the vehicle driving route, which includes: Obtain the vehicle driving route, and determine the start-up times, braking times and turning times during driving according to the vehicle driving route; Obtain the current static load distribution proportion of each tire of the vehicle, and determine the current dynamic load distribution proportion of each tire in the start-up stage, the braking stage and the turning stage according to the current static load distribution proportion of each tire, the current acceleration parameter and the mapping relationship; Determine the current load of each tire in the start-up stage, the braking stage and the turning stage according to the current dynamic load distribution proportion and the total mass of the vehicle; Obtain the current driver's predicted wear amount of each tire during driving according to the current load of each tire in the start-up stage, the braking stage and the turning stage, the wear model and the vehicle driving route.

[0012] As a preferred technical solution of the method for predicting tire wear based on vehicle acceleration, the current driver's predicted wear amount of each tire during driving is obtained according to the current load of each tire in the start-up stage, the braking stage and the turning stage, the wear model and the vehicle driving route, which includes: Obtain the total wear amount at the intersection when passing through the intersection according to the current load of each tire in the start-up stage, the current load of each tire in the braking stage and the wear model; According to the current load of each tire in the turning stage, the total wear of each tire in the turning stage is obtained according to the wear model; According to the driving route of the vehicle, the starting stage, the braking stage and the turning stage, the normal driving route is determined, and the total normal driving wear is determined according to the normal driving route, the current static load distribution ratio and the wear model; The sum of the total wear of the intersection, the total wear of the turning and the total wear of the normal driving is recorded as the predicted wear.

[0013] As a preferred technical solution of the method for predicting the tire wear condition based on the vehicle acceleration, the total wear of the intersection is obtained according to the current load of each tire in the starting stage, the current load of each tire in the braking stage and the wear model, which comprises: For the first intersection, the first starting distance required for the vehicle to reach a preset speed from a static state is calculated according to the starting acceleration, and the first braking distance required for the vehicle to reach a static state from the preset speed is calculated according to the braking acceleration; The first starting wear is calculated according to the starting acceleration, the current load of each tire in the starting stage, the first starting distance and the wear model, and the first braking wear is calculated according to the braking acceleration, the current load of each tire in the braking stage, the braking distance and the wear model; The sum of the first starting wear and the first braking wear is recorded as the first intersection wear; The above steps are repeated to calculate the wear corresponding to each intersection and to sum up the total wear of the intersection.

[0014] As a preferred technical solution of the method for predicting the tire wear condition based on the vehicle acceleration, the total wear of each tire in the turning stage is obtained according to the current load of each tire in the turning stage and the wear model, which comprises: For the first turning, the current load of each tire in the turning process is determined according to the load distribution ratio of each tire in the turning stage; The turning driving distance in the turning process is obtained, and the first turning wear in the first turning process is determined according to the turning driving distance, the current load of each tire in the turning process and the wear model; The above steps are repeated to calculate the turning wear corresponding to each turning process and to sum up the total wear of the turning.

[0015] As a preferred technical solution of the method for predicting the tire wear condition based on the vehicle acceleration, the normal driving route is determined according to the vehicle driving route, the starting stage, the braking stage and the turning stage, and the normal driving total wear amount is determined according to the normal driving route, the current static load distribution proportion and the wear model, which comprises: The route corresponding to the starting stage, the braking stage and the turning stage in the vehicle driving route is excluded, and the remaining route is recorded as the normal driving route, the load of each tire during normal driving is calculated according to the static load distribution proportion, and the normal driving total wear amount is calculated according to the length of the normal driving route, the load of each tire during normal driving and the wear model.

[0016] Compared with the prior art, the beneficial effects of the present application are that, in the actual driving process of the vehicle, the change of the acceleration will cause the redistribution of the load of each tire, based on the premise that the vehicle tire is in normal contact with the ground and the tire does not slip, the personalized starting acceleration, braking acceleration and lateral acceleration of the driver are obtained, so as to quantify the influence of different driving habits on the tire wear, split the total wear amount into the total wear amount at the intersection, the total wear amount during turning and the normal driving total wear amount, calculate the redistribution result of the vehicle load during driving based on the starting acceleration, the braking acceleration and the lateral acceleration, so as to calculate the total wear amount at the intersection, the total wear amount during turning and the normal driving total wear amount respectively, so as to add the influence of the key factors such as different driving styles of different drivers, vehicle load distribution and driving route on the tire wear into the prediction process of the wear, so as to reduce the error between the prediction result and the actual wear condition, and increase the accuracy of the prediction result. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 The step flow chart of the method for predicting the tire wear condition based on the vehicle acceleration of the embodiment of the present application. DETAILED DESCRIPTION

[0018] The features and exemplary embodiments of various aspects of the present application will be described in detail below, in order to make the purposes, technical solutions and advantages of the present application more clear and apparent, the present application will be further described in detail below in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, but not to limit the present application. The present application can be implemented without some of these specific details by those skilled in the art. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0019] It is to be noted that the relative terms such as first and second and the like are used herein solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any such actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element preceded by "comprises... " does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the stated elements.

[0020] Referring to Figure 1 The method for predicting the tire wear condition based on the vehicle acceleration according to the embodiment of the application is shown in the flowchart, which comprises the following steps: Step S1, collecting the acceleration data of each driver during each driving process, pre-processing the acceleration data to obtain standard acceleration data, storing the standard acceleration data into an acceleration database, and obtaining the acceleration parameters of the driver according to the acceleration database; the acceleration parameters include the starting acceleration, the braking acceleration, and the lateral acceleration; Step S2, obtaining the structural parameters and the mass distribution of the vehicle, calculating the load distribution of each tire under different accelerations according to the structural parameters and the mass distribution, and establishing the mapping relationship between the acceleration parameters and the load distribution; Step S3, detecting the tire wear of the tires with the same specifications as the vehicle tires under different loads and acceleration parameters using the bench test method, constructing a tire wear database according to the detection data, and training a wear model according to the tire wear database; Step S4, in response to the start of the vehicle, obtaining the identity information of the current driver, the driving route of the vehicle, and the total mass of the vehicle, calling the corresponding acceleration parameters in the acceleration database based on the identity information of the driver, and recording them as the current acceleration parameters; Step S5, obtaining the predicted wear amount of each tire of the current driver during the driving process according to the current acceleration parameters, the mapping relationship, the wear model, and the driving route of the vehicle.

[0021] In the implementation, the acceleration parameters of the driver during the driving process are collected by using the vehicle-mounted inertial measurement unit combined with the vehicle CAN bus. The pre-processing process of the acceleration data comprises the following steps: The acceleration data is pre-processed according to the principle that the acceleration data exceeding the average value of the acceleration data The average value of the acceleration data The data in the range is determined as an abnormal value and is eliminated, and the missing data is supplemented by using a linear interpolation method. The acceleration parameters in the state of vehicle engine off and the like are eliminated, and the remaining acceleration data is recorded as standard acceleration data. The acceleration database is configured with a plurality of sub-acceleration data sets according to the identity ID of the driver. The acceleration parameters of each driver are stored in the corresponding sub-acceleration data set. In the sub-acceleration database, the maximum value of the acceleration in the starting stage is recorded as the starting acceleration, the minimum value of the acceleration in the braking stage is recorded as the braking acceleration (in the braking stage, the value of the acceleration is negative), and the maximum value of the lateral acceleration in the turning stage is recorded as the lateral acceleration.

[0022] Further, the structural parameters and the mass distribution of the vehicle are obtained, the load distribution ratios of the tires under different accelerations are calculated according to the structural parameters and the mass distribution, and a mapping relationship between the acceleration parameters and the load distribution is established, including: For a single driving, before each start of the vehicle, the mass distribution of the vehicle is obtained, and the static load distribution ratios of the tires of the vehicle at rest are calculated according to the mass distribution and the structural parameters of the vehicle; In response to the start and driving of the vehicle, the acceleration parameters of the vehicle and the load distribution ratios of the tires corresponding to the vehicle during driving are collected, the static load distribution ratios corresponding to a single driving, the acceleration parameters of the vehicle during driving and the load distribution ratios of the tires are stored in the mass distribution ratio data set as a data group; The mapping relationship is established according to the mass distribution ratio data set.

[0023] In detail, before each start of the vehicle, the mass distribution on the vehicle is collected by the vehicle-mounted mass sensor arranged on the vehicle. The structural parameters of the vehicle are obtained through the vehicle manual. The dynamic load distribution ratios of the tires are calculated by the tire pressure sensor and the mass distribution sensor. The present embodiment provides a calculation method of the dynamic load distribution ratios of the tires. The vehicle is regarded as a rigid body without deformation. The static load distribution ratios of the tires are calculated according to the mass distribution and the structural parameters. The calculation can be performed according to the statics balance principle or other physical formula. For example, in the present embodiment, the static load ratio of the front axle is calculated as an example. The static load ratio of the front axle = (distance between the rear axle and the center of gravity / axle distance) x total weight of the vehicle. Then, the load ratios of the front left tire and the front right tire are calculated according to the mass distribution of the left and right wheels. In the present embodiment, the static load distribution ratios, the time sequence data of the acceleration parameters and the time sequence data of the dynamic load distribution ratios collected during a single driving are stored in the mass distribution ratio data set as a data group, and the mapping relationship between the acceleration parameters and the load distribution is established according to the mass distribution ratio data set. The principle pre-processes the data in the quality distribution ratio data set, eliminates abnormal data, and uses a multiple linear regression algorithm to establish a mapping relationship. By inputting the static load distribution ratio and acceleration parameters (i.e., the starting acceleration, braking acceleration, and lateral acceleration in the embodiment of the application), the dynamic load distribution ratio of each tire is output. The process of training the model based on known data is a prior art and will not be described here.

[0024] Further, the structure parameters include: vehicle kerb mass (i.e., empty vehicle mass), vehicle maximum gross weight (i.e., the mass of the entire vehicle when the vehicle is at maximum load), vehicle wheelbase, vehicle track, vehicle center of gravity height (i.e., the vertical distance from the center of gravity to the ground), front axle distance of the center of gravity (i.e., the horizontal distance from the center of gravity to the front axle), and rear axle distance of the center of gravity (i.e., the horizontal distance from the center to the rear axle).

[0025] In detail, the structure parameters cover the core requirements of vehicle dynamics calculation. According to the structure parameters and existing formulas, the obtained static load distribution ratio and dynamic load distribution ratio can meet the mechanical principles. The structure parameters can be selected from any of the vehicle types for calculation, avoiding the calculation error of the load distribution ratio caused by the fuzzy definition of the structure parameters in the prior art, and providing accurate basic data for the establishment of the subsequent mapping relationship.

[0026] Further, the same tires as the vehicle tires are detected by a bench test method under different loads and acceleration parameters, a tire wear database is constructed according to the detection data, and a wear model is trained according to the tire wear database, including: The starting acceleration, braking acceleration, and lateral acceleration are obtained, and the starting acceleration, braking acceleration, and lateral acceleration are substituted into the mapping relationship to obtain the maximum load and minimum load of each tire, respectively. The interval formed by the maximum load and the minimum load is referred to as the load interval; At least three tires with the same specifications as the vehicle tires are selected as test samples, and the test samples are detected by a detection bench. The detection conditions during the detection process include: applying different test loads to the test tires, respectively applying starting acceleration, braking acceleration, and lateral acceleration to the test tires, and driving a unit length to obtain a plurality of standard tire wear amounts corresponding to different test loads and different acceleration parameters. The test load is selected by traversing the load interval by a predetermined step size; A tire wear database is constructed according to a plurality of standard tire wear amounts corresponding to different test loads and different acceleration parameters.

[0027] It should be noted that the starting acceleration, braking acceleration and lateral acceleration are substituted into the mapping relationship respectively, and each tire corresponds to 3 load weights, and the interval formed by the maximum load weight and the minimum load weight is referred to as a load weight interval. Tire specifications include tire production batch, rubber formula, pattern, size, etc., which can avoid test errors caused by sample differences. During the bench test, the test temperature and tire air pressure are determined according to the actual situation. In this embodiment, the test temperature is the standard working condition temperature 25℃, and the tire air pressure is the recommended value of the tire manufacturer 2.5bar. The unit length is selected according to the actual situation. In this embodiment, the unit length is 10m. The loss amount is the wear thickness of the tire tread, that is, the loss amount = initial thickness - thickness after bench test. The tread thickness is measured and detected using a laser profiler. It can be understood that the smaller the preset step value, the more accurate the data in the tire loss database. However, the amount of data required for training based on the tire loss database is also larger, therefore, the value of the preset step is selected according to the actual conditions. Considering the hardware configuration of the computer, the value of the preset step in this embodiment is 10kg.

[0028] In detail, the present application constructs a load weight interval based on a mapping space, thereby ensuring that the load weight interval can include the change of the load weight of each tire during vehicle driving. By traversing the load weight of each tire by a preset step, a number of standard tire loss amounts corresponding to the starting acceleration, braking acceleration and lateral acceleration under different test loads are obtained, thereby providing an accurate data basis for subsequent training of the tire loss database, increasing the accuracy of predicting tire wear, and after training, other vehicles of the same type with the same tire specifications can directly use this model, thereby reducing the implementation cost.

[0029] Further, the loss model is trained according to the tire loss database. If the tire load and acceleration are input, the standard tire wear amount after driving a unit length is output.

[0030] In implementation, by analyzing the data in the tire loss database, it is found that the test load and the standard loss amount present a linear correlation characteristic, therefore a linear regression model is selected as the loss model. The data in the tire loss database is divided into a training set and a test set, the least squares method is used to fit the data in the training set, the expression of the loss model is obtained, the data in the test set is substituted into the expression of the loss model to calculate the predicted wear amount, the accuracy of the loss model is verified according to the comparison result of the predicted wear amount and the standard wear amount in the test set, and the final loss model is obtained. The process of training the model according to the known data is a prior art, which will not be described here.

[0031] In detail, the predicted wear and tear of each tire in the driving process of the current driver is obtained according to the current acceleration parameter, the mapping relationship, the wear and tear model and the vehicle driving route, including: The vehicle driving route is obtained, and the number of starts, the number of brakes and the number of turns in the driving process are determined according to the vehicle driving route; The current static load distribution proportion of each tire of the vehicle is obtained, and the current dynamic load distribution proportion of each tire in the start stage, the brake stage and the turn stage is respectively determined according to the current static load distribution proportion of each tire, the current acceleration parameter and the mapping relationship; The current load of each tire in the start stage, the brake stage and the turn stage is respectively determined according to the current dynamic load distribution proportion and the total mass of the vehicle; The predicted wear and tear of each tire in the driving process of the current driver is obtained according to the current load of each tire in the start stage, the brake stage and the turn stage, the wear and tear model and the vehicle driving route.

[0032] It should be noted that the vehicle driving route is obtained through the vehicle navigation system and other navigation methods. In the vehicle driving route, each intersection corresponds to a start and a brake, and each left turn, right turn and U-turn corresponds to a turn, so as to determine the number of starts, the number of brakes and the number of turns in the driving process.

[0033] In detail, the predicted wear and tear of each tire in the driving process of the current driver is obtained according to the current load of each tire in the start stage, the brake stage and the turn stage, the wear and tear model and the vehicle driving route, including: The total wear and tear at the intersection is obtained according to the current load of each tire in the start stage, the current load of each tire in the brake stage and the wear and tear model; The total wear and tear of each tire in the turn is obtained according to the current load of each tire in the turn stage and the wear and tear model; The normal driving route is determined according to the vehicle driving route, the start stage, the brake stage and the turn stage, and the total wear and tear of normal driving is determined according to the normal driving route, the current static load distribution proportion and the wear and tear model; The sum of the total wear and tear at the intersection, the total wear and tear of the turn and the total wear and tear of normal driving is recorded as the predicted wear and tear.

[0034] It should be noted that the route length corresponding to the start stage, the brake stage and the turn stage is removed from the vehicle driving route, and the remaining vehicle driving route is the normal driving route.

[0035] In detail, the total wear amount in the vehicle driving route driving process is split into the total wear amount at the intersection, the total wear amount at the corner and the total wear amount in normal driving, which conforms to the different rules of tire wear amount in the starting stage, the braking stage and the normal driving in the actual driving, realizes the fine calculation of the wear amount in each stage in the driving process, avoids the deviation when predicting the friction amount according to the whole of the vehicle driving route, and increases the prediction precision of the tire wear condition.

[0036] In detail, the total wear amount at the intersection is obtained according to the current load of each tire in the starting stage, the current load of each tire in the braking stage and the loss model, which includes: For the first intersection, the first starting distance required for the vehicle to reach the preset speed from the static state is calculated according to the starting acceleration, and the first braking distance required for the vehicle to reach the static state from the preset speed is calculated according to the braking acceleration; The first starting wear amount is calculated according to the starting acceleration, the current load of each tire in the starting stage, the starting distance and the loss model, and the first braking wear amount is calculated according to the braking acceleration, the current load of each tire in the braking stage, the braking distance and the loss model; The sum of the first starting wear amount and the first braking wear amount is recorded as the first intersection wear amount; The above steps are repeated to calculate the wear amount corresponding to each intersection and sum up to obtain the total wear amount at the intersection.

[0037] It should be noted that the process of calculating the first starting wear amount according to the starting acceleration, the current load of each tire in the starting stage, the starting distance and the loss model is that the starting acceleration and the load of each tire in the starting stage are substituted into the loss model to obtain the standard tire wear amount after driving a unit length, if the first starting distance corresponding to the first intersection is n times the unit length, then the wear amount corresponding to the first starting stage wear amount should also be n times the standard tire wear amount, and the process of obtaining the first braking wear amount is consistent with the process of obtaining the first starting stage wear amount, only the substituted values are different. The value of the preset speed is determined according to the actual situation of the vehicle driving route, for example: for urban roads, the value of the preset speed is 50km / h; for highways, the value of the preset speed is 100km / h. It can be understood that those skilled in the art can calculate the distance required to reach the preset speed from the static state, i.e. the starting distance in the embodiment of the present application, given the acceleration and the preset speed to be reached, and the braking distance is the same, so it is not repeated here.

[0038] In detail, the total wear amount at the intersection is obtained according to the current load of each tire in the starting stage, the current load of each tire in the braking stage and the loss model, which includes: The starting wear amount and the braking wear amount are calculated based on the corresponding dynamic load, which increases the prediction accuracy of the wear amount of each intersection.

[0039] Further, the total cornering wear is obtained according to the current load of each tire in the cornering stage and a wear model, including: For the first cornering, the current load of each tire in the cornering process is determined according to the load distribution ratio of each tire in the cornering stage; The cornering driving distance in the cornering process is obtained, and the first cornering wear in the first cornering process is determined according to the cornering driving distance, the current load of each tire in the cornering process and the wear model; The above steps are repeated to calculate the cornering wear corresponding to each cornering process and sum up to obtain the total cornering wear.

[0040] It should be noted that the cornering driving distance is directly obtained according to big data or a vehicle navigation system, or is calculated according to the curvature radius of the route and the cornering angle, which is not limited here.

[0041] Further, the normal driving route is determined according to the vehicle driving route, the starting stage, the braking stage and the cornering stage, and the total normal driving wear is determined according to the normal driving route, the current static load distribution ratio and the wear model, including: The remaining route is recorded as the normal driving route by excluding the routes corresponding to the starting stage, the braking stage and the cornering stage in the vehicle driving route, the load of each tire in the normal driving is calculated according to the static load distribution ratio, and the total normal driving wear is calculated according to the length of the normal driving route, the load of each tire in the normal driving and the wear model.

[0042] It should be noted that the normal driving stage is a stage of approximate constant speed straight line driving without obvious acceleration change, and the vehicle load has no obvious redistribution, so the current static load distribution ratio is used to calculate the load.

[0043] Obviously, the above embodiments of the present application are only examples for clearly illustrating the present application, and are not intended to limit the embodiments of the present application. For those skilled in the art, other different forms of changes or variations can be made on the basis of the above description. Here, all the embodiments are not required to be exhausted. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the claims of the present application.

Claims

1. A method for predicting tire wear based on vehicle acceleration, characterized in that, include: Acceleration data of each driver is collected during each driving process. The acceleration data is preprocessed to obtain standard acceleration data. The standard acceleration data is stored in the acceleration database. The driver's acceleration parameters are obtained from the acceleration database. The acceleration parameters include: starting acceleration, braking acceleration, and lateral acceleration; Obtain the vehicle's structural parameters and mass distribution, calculate the load distribution ratio of each tire under different accelerations based on the structural parameters and mass distribution, and establish a mapping relationship between acceleration parameters and load distribution; The bench test method was used to detect tire wear of the same tire specifications as the vehicle under different load and acceleration parameters. A tire wear database was constructed based on the test data, and a wear model was trained based on the tire wear database. In response to vehicle startup, the system obtains the current driver's identity information, the vehicle's driving route, and the vehicle's total mass. Based on the driver's identity information, the system retrieves the corresponding acceleration parameters from the acceleration database and records them as the current acceleration parameters. The predicted wear of each tire during the current driving process is obtained based on the current acceleration parameters, the mapping relationship, the loss model, and the vehicle driving route.

2. The method for predicting tire wear based on vehicle acceleration according to claim 1, characterized in that, The process of acquiring the vehicle's structural parameters and mass distribution, calculating the load distribution ratio of each tire under different accelerations based on the structural parameters and mass distribution, and establishing a mapping relationship between acceleration parameters and load distribution includes: For a single trip, before each vehicle starts, the vehicle's mass distribution is obtained, and the static load distribution ratio of each tire is calculated based on the mass distribution and the vehicle's structural parameters when the vehicle is stationary. In response to vehicle startup and driving, the acceleration parameters of the vehicle during driving and the corresponding load distribution ratio of each tire are collected. The static load distribution ratio corresponding to a single driving cycle, the acceleration parameters of the vehicle during driving, and the load distribution ratio of each tire are stored as a data group in the mass distribution ratio dataset. The mapping relationship is established based on the quality allocation percentage dataset.

3. The method for predicting tire wear based on vehicle acceleration according to claim 2, characterized in that, The structural parameters include: vehicle curb weight, vehicle maximum gross weight, vehicle wheelbase, vehicle track width, vehicle center of gravity height, center of gravity front axle distance, and center of gravity rear axle distance.

4. The method for predicting tire wear based on vehicle acceleration according to claim 2, characterized in that, The method of using bench testing to detect tire wear of the same specifications as vehicle tires under different loads and acceleration parameters, constructing a tire wear database based on the test data, and training a wear model based on the tire wear database includes: The starting acceleration, braking acceleration, and lateral acceleration are obtained. The starting acceleration, braking acceleration, and lateral acceleration are substituted into the mapping relationship respectively to obtain the maximum load capacity and minimum load capacity of each tire. The interval formed by the maximum load capacity and the minimum load capacity is recorded as the load capacity interval. At least three tires of the same specifications as the vehicle tires were selected as test samples. The test samples were tested using a testing bench. The testing conditions included: applying different test loads to the test tires, applying the starting acceleration, the braking acceleration, the lateral acceleration, and the distance traveled per unit length to the test tires, in order to obtain several standard tire wear amounts under different test loads and different acceleration parameters; the test loads were selected by traversing the load range through a preset step size. The tire wear database is constructed based on several standard tire wear values ​​corresponding to different test loads and different acceleration parameters.

5. The method for predicting tire wear based on vehicle acceleration according to claim 4, characterized in that, The wear model is trained based on the tire wear database. If the tire load and acceleration are input, it outputs the standard tire wear amount after traveling a unit length.

6. The method for predicting tire wear based on vehicle acceleration according to claim 5, characterized in that, The step of obtaining the predicted wear of each tire during the current driving process based on the current acceleration parameters, the mapping relationship, the loss model, and the vehicle driving route includes: Obtain the vehicle's driving route and determine the number of starts, braking, and turns during the driving process based on the vehicle's driving route; The current static load distribution ratio of each tire of the vehicle is obtained. Based on the current static load distribution ratio of each tire, the current acceleration parameters, and the mapping relationship, the current dynamic load distribution ratio of each tire is determined for the starting phase, braking phase, and cornering phase, respectively. The current load capacity of each tire is determined based on the current dynamic load distribution ratio and the total vehicle mass during the starting, braking, and turning phases, respectively. The predicted wear of each tire during the current driving process is obtained based on the current load of each tire during the starting, braking, and turning phases, the wear model, and the vehicle's driving route.

7. The method for predicting tire wear based on vehicle acceleration according to claim 6, characterized in that, The method of obtaining the predicted wear of each tire during the current driving process based on the current load of each tire during the starting, braking, and turning phases, the wear model, and the vehicle's driving route includes: The total wear of the intersection when passing through the intersection is obtained based on the current load of each tire during the starting phase, the current load of each tire during the braking phase, and the wear model. The total wear of each tire during the turn is obtained based on the current load of each tire during the turn and the wear model. The normal driving route is determined based on the vehicle's driving route, starting phase, braking phase, and turning phase. The total wear amount during normal driving is determined based on the normal driving route, the current static load distribution ratio, and the wear model. The sum of the total wear at the intersection, the total wear at the bend, and the total wear during normal driving is recorded as the predicted wear.

8. The method for predicting tire wear based on vehicle acceleration according to claim 7, characterized in that, The step of obtaining the total wear amount at the intersection when passing through the intersection based on the current load of each tire during the starting phase, the current load of each tire during the braking phase, and the wear model includes: For the first intersection, the first starting distance required for the vehicle to go from a standstill to a preset speed is calculated based on the starting acceleration, and the first braking distance required for the vehicle to go from a preset speed to a standstill is calculated based on the braking acceleration. The first starting wear amount is calculated based on the starting acceleration, the current load of each tire during the starting phase, the first starting distance, and the wear model; the first braking wear amount is calculated based on the braking acceleration, the current load of each tire during the braking phase, the braking distance, and the wear model. The sum of the first starting wear and the first braking wear is recorded as the first intersection wear. Repeat the above steps to calculate the wear amount for each intersection and sum them up to obtain the total wear amount for the intersection.

9. The method for predicting tire wear based on vehicle acceleration according to claim 7, characterized in that, The step of obtaining the total wear of each tire during a turn based on the current load of each tire during the turn and the wear model includes: For the first turn, the current load of each tire during the turn is determined based on the load distribution ratio of each tire during the turn. The turning distance during the turning process is obtained, and the first turning wear amount during the first turning process is determined based on the turning distance, the current load of each tire during the turning process, and the wear model. Repeat the above steps to calculate the turning wear amount corresponding to each turning process and sum them to obtain the total turning wear amount.

10. The method for predicting tire wear based on vehicle acceleration according to claim 7, characterized in that, The process of determining the normal driving route based on the vehicle's driving path, starting phase, braking phase, and turning phase, and determining the total wear amount during normal driving based on the normal driving route, the current static load distribution ratio, and the wear model, includes: Excluding the starting, braking, and turning phases of the vehicle's driving route, the remaining route is recorded as the normal driving route. The load capacity of each tire during normal driving is calculated based on the static load distribution ratio. The total wear during normal driving is calculated based on the length of the normal driving route, the load capacity of each tire during normal driving, and the wear model.

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