A method for predicting tire wear conditions based on vehicle acceleration

Abstract

The application relates to the field of tire monitoring technology, in particular to a method for predicting tire wear based on vehicle acceleration, obtaining an acceleration parameter of a driver; establishing a mapping relationship between the acceleration parameter and load distribution; constructing a tire wear database, training a wear model according to the tire wear database; calling corresponding current acceleration parameters in the acceleration database based on driver identity information; and obtaining the predicted wear of each tire of the current driver in the driving process according to the current acceleration parameter, the mapping relationship, the wear model and the vehicle driving route. The total wear is split into the total wear at intersections, the total wear at turns and the total wear in normal driving, so that the total wear at intersections, the total wear at turns and the total wear in normal driving are respectively calculated, the error between the prediction result and the actual wear condition is reduced, and the accuracy of the prediction result is increased.

Description

Technical Field

[0001] This invention relates to the field of tire monitoring technology, and in particular to a method for predicting tire wear based on vehicle acceleration. Background Technology

[0002] As the medium through which a vehicle contacts the ground, the wear and tear of tires is closely related to the safety and comfort of the vehicle during driving. Therefore, it is essential to predict tire wear and avoid safety risks caused by excessive tire wear.

[0003] Existing technologies for predicting tire wear suffer from two main problems. First, while mileage-based predictions provide a rough estimate, they fail to consider the impact of varying driving styles, vehicle load distribution, and driving routes on tire wear. This results in significant discrepancies between predicted and actual wear conditions, leading to low accuracy. Second, while existing technologies attempt to predict tire wear based on acceleration or load, they neglect the fact that acceleration in actual driving causes a redistribution of weight among the vehicle's tires, further contributing to large discrepancies and low accuracy.

[0004] Therefore, the existing technology has defects and urgently needs improvement. Summary of the Invention

[0005] The purpose of this invention is to provide a method for predicting tire wear based on vehicle acceleration, thereby addressing the problems in the prior art. On the one hand, the prior art makes a rough prediction of wear based on mileage without considering the impact of key factors such as different driving styles of different drivers, vehicle load distribution, and driving routes on tire wear. On the other hand, although the prior art attempts to predict tire wear based on acceleration or load, it ignores the fact that acceleration in actual driving causes a redistribution of the load weight of each tire, resulting in a large error between the predicted result and the actual wear condition, and low prediction accuracy.

[0006] This invention provides a method for predicting tire wear based on vehicle acceleration, comprising:

[0007] Acceleration data of each driver is collected during each driving process. The acceleration data is preprocessed to obtain standard acceleration data, which is then stored in an acceleration database. The driver's acceleration parameters are obtained from the acceleration database. The acceleration parameters include: starting acceleration, braking acceleration, and lateral acceleration.

[0008] 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;

[0009] 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.

[0010] 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.

[0011] 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.

[0012] As a preferred technical solution for predicting tire wear based on vehicle acceleration, the steps of obtaining 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 include:

[0013] 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.

[0014] 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.

[0015] The mapping relationship is established based on the quality allocation percentage dataset.

[0016] As a preferred technical solution for a method of predicting tire wear based on vehicle acceleration, the structural parameters include: vehicle curb weight, maximum gross vehicle weight, vehicle wheelbase, vehicle track width, vehicle center of gravity height, center of gravity front axle distance, and center of gravity rear axle distance.

[0017] As a preferred technical solution for predicting tire wear based on vehicle acceleration, the method involves using a bench test to detect tire wear of the same specifications as the vehicle 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, including:

[0018] 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.

[0019] At least three tires of the same specifications as the vehicle tires are selected as test samples. The test samples are tested using a testing bench. The testing conditions include: 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 are selected by traversing the load range through a preset step size.

[0020] The tire wear database is constructed based on several standard tire wear values ​​corresponding to different test loads and different acceleration parameters.

[0021] As a preferred technical solution for predicting tire wear based on vehicle acceleration, the wear model is trained according to the tire wear database. If the tire load and acceleration are input, the model outputs the standard tire wear amount after traveling a unit length.

[0022] As a preferred technical solution for a method of predicting tire wear based on vehicle acceleration, the step of obtaining the predicted wear amount of each tire during the current driving process by the driver, based on the current acceleration parameters, the mapping relationship, the wear model, and the vehicle driving route, includes:

[0023] 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;

[0024] 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.

[0025] 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.

[0026] 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.

[0027] As a preferred technical solution for a method to predict tire wear based on vehicle acceleration, the step of obtaining the predicted wear amount of each tire during the current driving process by the driver, based on the current load of each tire during the starting phase, braking phase, and cornering phase, the wear model, and the vehicle driving route, includes:

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] As a preferred technical solution for a method to predict tire wear based on vehicle acceleration, the step of obtaining the total wear 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:

[0033] 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.

[0034] 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.

[0035] The sum of the first starting wear and the first braking wear is recorded as the first intersection wear.

[0036] 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.

[0037] As a preferred technical solution for a method to predict tire wear based on vehicle acceleration, the step of obtaining the total wear of each tire during cornering based on the current load of each tire during the cornering phase and the wear model includes:

[0038] 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.

[0039] 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.

[0040] 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.

[0041] As a preferred technical solution for a method of predicting tire wear based on vehicle acceleration, the step 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:

[0042] 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.

[0043] Compared with the prior art, the beneficial effect of the present invention is that, during the actual driving process of a vehicle, changes in acceleration lead to a redistribution of the load on each tire. Based on the premise that the vehicle tires are in normal contact with the ground and the tires do not slip, the present invention obtains the driver's personalized starting acceleration, braking acceleration, and lateral acceleration, thereby quantifying the impact of different driving habits on tire wear. The total wear is broken down into total wear at intersections, total wear when turning, and total wear during normal driving. Based on the redistribution of vehicle load during driving based on starting acceleration, braking acceleration, and lateral acceleration, the present invention calculates the total wear at intersections, total wear when turning, and total wear during normal driving, respectively. This incorporates the influence of key factors such as different driving styles of different drivers, vehicle load distribution, and driving routes on tire wear into the wear prediction process, thereby reducing the error between the prediction results and the actual wear, and increasing the accuracy of the prediction results. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating the steps of a method for predicting tire wear based on vehicle acceleration, as described in an embodiment of the present invention. Detailed Implementation

[0045] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0046] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0047] Please see Figure 1 The diagram shows the steps of a method for predicting tire wear based on vehicle acceleration according to an embodiment of the present invention, including:

[0048] Step S1: Collect acceleration data for each driver during each driving process, preprocess the acceleration data to obtain standard acceleration data, store the standard acceleration data in the acceleration database, and obtain the driver's acceleration parameters based on the acceleration database; the acceleration parameters include: starting acceleration, braking acceleration, and lateral acceleration.

[0049] Step S2: Obtain the vehicle's structural parameters and mass distribution; calculate the load distribution 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.

[0050] Step S3: Use bench testing to detect tire wear of the same specifications as the vehicle tires under different loads and acceleration parameters. Build a tire wear database based on the test data and train a wear model based on the tire wear database.

[0051] Step S4: In response to vehicle startup, obtain the current driver's identity information, vehicle driving route and total vehicle mass, retrieve the corresponding acceleration parameters from the acceleration database based on the driver's identity information, and record them as the current acceleration parameters;

[0052] Step S5: Based on the current acceleration parameters, mapping relationship, loss model and vehicle driving route, obtain the predicted wear of each tire during the current driving process.

[0053] In implementation, an onboard inertial measurement unit (IMU) combined with the vehicle's CAN bus is used to collect the driver's acceleration parameters during driving. The preprocessing of the acceleration data includes: based on... The principle is to preprocess the acceleration data, removing values ​​exceeding the average value of the acceleration data. The average value of acceleration data Data within the specified range is identified as outliers and removed. Missing data is supplemented using linear interpolation. Acceleration parameters from states such as vehicle engine shutdown are also removed, and the remaining acceleration data is recorded as standard acceleration data. The acceleration database contains several sub-acceleration datasets configured based on the driver's ID. Each driver's acceleration parameters are stored in their corresponding sub-acceleration dataset. Within the sub-acceleration database, the maximum acceleration value during the starting phase is recorded as the starting acceleration, the minimum acceleration value during the braking phase is recorded as the braking acceleration (the acceleration value is negative during braking), and the maximum lateral acceleration value during cornering is recorded as the lateral acceleration.

[0054] Furthermore, the vehicle's structural parameters and mass distribution are obtained. Based on these parameters and distribution, the load distribution ratio of each tire under different accelerations is calculated, and a mapping relationship between acceleration parameters and load distribution is established, including:

[0055] 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.

[0056] 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.

[0057] Establish a mapping relationship based on the quality allocation percentage dataset.

[0058] In detail, before each vehicle start-up, the vehicle's mass distribution is collected by onboard mass sensors. The vehicle's structural parameters are obtained from the manufacturer's manual. The dynamic load distribution ratio of each tire is calculated using a combination of tire pressure sensors and mass distribution sensors. This invention provides a method for calculating the dynamic load distribution ratio of each tire, treating the vehicle as a rigid body that does not deform. The static load distribution ratio of each tire can be calculated based on the principles of static equilibrium or other physical formulas, according to the mass distribution and structural parameters. For example, in this embodiment, taking the calculation of the static load ratio of the front axle as an example, the front axle static load ratio = (center of gravity / rear axle distance / wheelbase) × total vehicle weight. Then, the load ratio of the left and right front tires is calculated based on the mass distribution of the left and right wheels. In this embodiment, the time-series data of the static load distribution ratio, acceleration parameters, and dynamic load distribution ratio collected during a single driving cycle are stored as a data set in a mass distribution ratio dataset. The principle is to preprocess the data in the weight distribution ratio dataset, remove outliers, and use a multiple linear regression algorithm to establish a mapping relationship. Input the static load distribution ratio and acceleration parameters (i.e., starting acceleration, braking acceleration and lateral acceleration in this embodiment of the invention), and output the dynamic load distribution ratio of each tire. The process of training the model based on known data is existing technology and will not be described in detail here.

[0059] Furthermore, the structural parameters include: vehicle curb weight (i.e., empty vehicle weight), vehicle maximum gross weight (i.e., the total weight of the vehicle when it is under maximum load), vehicle wheelbase, vehicle track width, vehicle center of gravity height (i.e., the vertical distance from the center of gravity to the ground), center of gravity front axle spacing (i.e., the horizontal spacing from the center of gravity to the front axle), and center of gravity rear axle spacing (i.e., the horizontal spacing from the center to the rear axle).

[0060] In detail, the structural parameters cover the core requirements of vehicle dynamics calculation. Based on the structural parameters and existing formulas, the obtained static load distribution ratio and dynamic load distribution ratio can be made to conform to the principles of mechanics. Any of the structural parameters can be selected for calculation according to the vehicle model, avoiding the calculation error of load distribution ratio caused by the fuzzy definition of structural parameters in the prior art, and providing accurate basic data for the establishment of subsequent mapping relationships.

[0061] Furthermore, bench testing was used to detect tire wear of the same specifications as the vehicle tires under different loads and acceleration parameters. A tire wear database was constructed based on the test data, and a wear model was trained using this database, including:

[0062] Obtain the starting acceleration, braking acceleration, and lateral acceleration. Substitute the starting acceleration, braking acceleration, and lateral acceleration into the mapping relationship to obtain the maximum load capacity and minimum load capacity of each tire. Record the interval formed by the maximum load capacity and the minimum load capacity as the load capacity interval.

[0063] At least three tires of the same specifications as the vehicle tires were selected as test samples. The test samples were tested using a test bench. The test conditions during the test process included: applying different test loads to the test tires, applying starting acceleration, braking acceleration, lateral acceleration, and traveling a unit length to the test tires to obtain the corresponding standard tire wear under different test loads and acceleration parameters; the test load was selected by traversing the load range through a preset step size.

[0064] A tire wear database is constructed based on the wear amounts of several standard tires under different test loads and acceleration parameters.

[0065] It should be noted that the starting acceleration, braking acceleration, and lateral acceleration are substituted into the mapping relationship, and each tire corresponds to three load capacities. The interval formed by the maximum and minimum load capacities is recorded as the load capacities interval. Tire specifications include the tire's production batch, rubber compound, tread pattern, and size, etc., to avoid testing errors caused by sample differences. During bench testing, the test temperature and tire pressure are determined according to the actual situation. In this embodiment, the test temperature is the standard operating temperature of 25°C, and the tire pressure is the tire manufacturer's recommended value of 2.5 bar. The unit length is selected according to the actual situation. In this embodiment, the unit length is 10m. The wear amount is the wear thickness of the tire tread, i.e., wear amount = initial thickness - thickness after bench testing. The tread thickness is measured using a laser profilometer. It can be understood that the smaller the preset step size, the more accurate the data in the tire wear database, but the larger the amount of data required for training based on the tire wear database. Therefore, the preset step size is selected according to the actual conditions. Considering the computer's hardware configuration, the preset step size in this embodiment is 10kg.

[0066] In detail, this invention constructs a load range based on a mapping space, thereby ensuring that the load range can include the changes in the load of each tire during vehicle operation. By traversing the load of each tire through a preset step size, several standard tire wear amounts corresponding to starting acceleration, braking acceleration, and lateral acceleration under different test loads are obtained. This provides an accurate data foundation for the subsequent training of the tire wear database, increases the accuracy of predicting tire wear, and after training, other vehicles of the same type equipped with the same tire specifications can directly use this model, thereby reducing implementation costs.

[0067] Furthermore, the wear model is trained based on a tire wear database. If the tire load and acceleration are input, the output is the standard tire wear amount after traveling a unit length.

[0068] In implementation, analysis of data from the tire wear database revealed a linear correlation between test load and standard wear amount. Therefore, a linear regression model was chosen as the wear model. The data in the tire wear database was divided into a training set and a test set. The least squares method was used to fit the data in the training set to obtain the expression for the wear model. The data in the test set was then substituted into the expression for the wear model to calculate the predicted wear amount. The accuracy of the wear model was verified by comparing the predicted wear amount with the standard wear amount in the test set, resulting in the final wear model. The process of training the model based on known data is based on existing technology and will not be elaborated here.

[0069] In detail, based on the current acceleration parameters, mapping relationships, loss models, and vehicle travel routes, the predicted wear of each tire during the current driving process is obtained, including:

[0070] 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;

[0071] Obtain the current static load distribution ratio of each tire of the vehicle, and determine the current dynamic load distribution ratio of each tire during the starting phase, braking phase and cornering phase based on the current static load distribution ratio of each tire, the current acceleration parameters and mapping relationship.

[0072] 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.

[0073] Based on the current load, wear model, and vehicle driving route of each tire during the starting, braking, and turning phases, the predicted wear of each tire during the current driving process is obtained.

[0074] It should be noted that the vehicle's driving route is obtained through the in-vehicle navigation system and other navigation methods. In the driving route, each intersection corresponds to one start and one braking, and each left turn, right turn and U-turn corresponds to one turn, thereby determining the number of starts, braking and turns during the driving process.

[0075] In detail, based on the current load, wear model, and vehicle driving route of each tire during the starting, braking, and cornering phases, the predicted wear of each tire during the current driving process is obtained, including:

[0076] 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.

[0077] The total wear of each tire during the turn is obtained based on the current load and wear model of each tire during the turn.

[0078] The normal driving route is determined based on the vehicle's driving route, starting phase, braking phase, and turning phase. The total wear and tear during normal driving is determined based on the normal driving route, the current static load distribution ratio, and the wear model.

[0079] The sum of the total wear at intersections, the total wear at turns, and the total wear during normal driving is recorded as the predicted wear.

[0080] It should be noted that the route lengths corresponding to the starting, braking, and turning phases are removed from the vehicle's driving route, and the remaining route is the normal driving route.

[0081] In detail, this invention breaks down the total wear amount during the vehicle's driving route into the total wear amount at intersections, the total wear amount when turning, and the total wear amount during normal driving. This conforms to the different patterns of tire wear during the starting, braking, and normal driving stages in actual driving, and achieves refined calculation of wear amount at each stage of the driving process. This avoids deviations when predicting friction amount based on the overall vehicle driving route and increases the accuracy of predicting tire wear.

[0082] In detail, the total wear at 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, including:

[0083] 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.

[0084] The first starting wear is calculated based on the starting acceleration, the current load of each tire during the starting phase, the starting distance, and the wear model. The first braking wear is calculated based on the braking acceleration, the current load of each tire during the braking phase, the braking distance, and the wear model.

[0085] The sum of the first starting wear and the first braking wear is recorded as the first intersection wear.

[0086] 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.

[0087] It should be noted that the process of calculating the first starting wear amount based on the starting acceleration, the current load of each tire during the starting phase, the starting distance, and the wear model is as follows: Substitute the starting acceleration and the load of each tire during the starting phase into the wear model to obtain the standard tire wear amount after traveling 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 phase wear amount should also be n times the standard tire wear amount. The process of obtaining the first braking wear amount is consistent with the process of obtaining the first starting phase wear amount, only the substituted values ​​are different. The preset speed is determined according to the actual situation of the vehicle's driving route. For example, for urban roads, the preset speed is 50 km / h; for highways, the preset speed is 100 km / h. It is understood that those skilled in the art, given the acceleration and the preset speed to be reached, can calculate the distance required to reach the preset speed from a standstill, i.e., the starting distance in this embodiment of the invention. The braking distance is similar, and therefore will not be elaborated further here.

[0088] In detail, the present invention increases the prediction accuracy of the wear amount of each intersection by breaking down the wear amount of the intersection into the wear amount of starting and the wear amount of braking, and calculating the wear amount of starting and braking based on the corresponding dynamic load.

[0089] Furthermore, based on the current load and wear model of each tire during the turning phase, the total wear of each tire during the turning process is obtained, including:

[0090] 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.

[0091] Obtain the turning distance during the turning process, and determine the first turn wear amount during the first turn based on the turning distance, the current load of each tire during the turning process, and the wear model.

[0092] 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.

[0093] It should be noted that the turning distance can be obtained directly from big data or in-vehicle navigation systems, or it can be calculated from the radius of curvature of the route and the turning angle. No specific limit is specified here.

[0094] Furthermore, the normal driving route is determined based on the vehicle's driving path, starting phase, braking phase, and turning phase. The total wear and tear during normal driving is then determined based on the normal driving route, the current static load distribution ratio, and the wear model, including:

[0095] 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 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 of each tire during normal driving, and the wear model.

[0096] It should be noted that the normal driving phase is a phase of approximately uniform straight-line travel with no significant change in acceleration. There is no significant redistribution of the vehicle's load, and the load distribution is basically consistent with the static load distribution ratio. Therefore, the load can be calculated using the current static load distribution ratio.

[0097] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method of predicting a tire wear condition based on vehicle acceleration, the method comprising: The application relates to a method for predicting tire wear, and belongs to the field of tire wear prediction. ​ The method comprises the following steps: 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 comprise starting acceleration, braking acceleration and lateral acceleration; Obtaining structural parameters and mass distribution of the vehicle, calculating load distribution proportions of each tire under different accelerations according to the structural parameters and the mass distribution, and establishing a mapping relationship between the acceleration parameters and the load distribution; Detecting tire wear of a tire with the same specification as a tire of the vehicle under different loads and acceleration parameters by using a bench test method, constructing a tire wear database according to the detection data, and training a wear model according to the tire wear database; In response to starting of the vehicle, obtaining identity information of a current driver, a driving route of the vehicle and a total mass of the vehicle, calling corresponding acceleration parameters of the driver in the acceleration database based on the identity information of the driver, and recording the acceleration parameters as current acceleration parameters; Obtaining predicted wear amounts of each tire of the current driver during driving according to the current acceleration parameters, the mapping relationship, the wear model and the driving route of the vehicle; The method for obtaining the structural parameters and the mass distribution of the vehicle, calculating the load distribution proportions 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 comprises the following steps: For a single driving, before each start of the vehicle, obtaining the mass distribution of the vehicle, and calculating static load distribution proportions of each tire of the vehicle at rest according to the mass distribution and the structural parameters of the vehicle; In response to starting and driving of the vehicle, collecting acceleration parameters of the vehicle and corresponding load distribution proportions of each tire during driving, and storing the static load distribution proportions corresponding to the single driving, the acceleration parameters of the vehicle during driving and the load distribution proportions of each tire as a data group into a mass distribution proportion data set; The mapping relationship is established according to the mass distribution proportion data set; The method for obtaining predicted wear amounts of each tire of the current driver during driving according to the current acceleration parameters, the mapping relationship, the wear model and the driving route of the vehicle comprises the following steps: Obtaining the driving route of the vehicle, determining the number of starting, braking and turning during driving according to the driving route of the vehicle; Obtaining current static load distribution proportions of each tire of the vehicle, respectively determining current dynamic load distribution proportions of each tire in the starting stage, the braking stage and the turning stage according to the current static load distribution proportions of each tire, the current acceleration parameters and the mapping relationship; Respectively determining current load amounts of each tire in the starting stage, the braking stage and the turning stage according to the current dynamic load distribution proportions and the total mass of the vehicle; Obtaining predicted wear amounts of each tire of the current driver during driving according to the current load amounts of each tire in the starting stage, the braking stage and the turning stage, the wear model and the driving route of the vehicle.

2. The method of predicting tire wear condition based on vehicle acceleration according to claim 1, wherein, The structure parameters include: vehicle kerb mass, vehicle maximum gross weight, vehicle wheelbase, vehicle track, vehicle height of gravity center, front axle distance of gravity center, and rear axle distance of gravity center.

3. The method of predicting tire wear condition based on vehicle acceleration according to claim 1, wherein, The tire wear database is constructed according to the detection data, and the wear model is trained according to the tire wear database, including: Obtaining the start-up acceleration, the braking acceleration and the lateral acceleration, and substituting the start-up acceleration, the braking acceleration and the lateral acceleration into the mapping relationship respectively to obtain the maximum load and the minimum load of each tire respectively, and the interval formed by the maximum load and the minimum load is referred to as a load interval; At least three tires with the same specifications as the vehicle tires are selected as test samples, and a detection bench is used to detect the test samples, and 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 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 preset step size; The tire wear database is constructed according to the detection data, and the wear model is trained according to the tire wear database, including:

4. The method of predicting tire wear condition based on vehicle acceleration according to claim 3, wherein, The wear model is trained according to the tire wear database, and if the input tire load and acceleration are input, the standard tire wear amount after driving a unit length is output.

5. The method of predicting tire wear condition based on vehicle acceleration according to claim 1, wherein, The predicted wear amount of each tire during driving by the current driver 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, including: The total wear amount at the intersection when passing through the intersection is obtained 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; The total wear amount of each tire during turning is obtained according to the current load of each tire in the turning stage and the wear model; The normal driving route is determined according to the vehicle driving route, the start-up 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 ratio and the wear model; The sum of the total wear amount at the intersection, the total wear amount during turning and the normal driving total wear amount is referred to as the predicted wear amount.

6. The method of predicting tire wear condition based on vehicle acceleration according to claim 5, wherein, The total wear amount at the intersection when passing through the intersection is obtained 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, including: For the first intersection, the first start-up distance required for the vehicle to reach a preset speed from a static state is calculated according to the start-up 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; According to the starting acceleration, the current load of each tire in the starting stage, the first starting distance, and the wear model, a first starting wear amount is calculated, and according to the braking acceleration, the current load of each tire in the braking stage, the braking distance, and the wear model, a first braking wear amount is calculated; The sum of the first starting wear amount and the first braking wear amount is recorded as a first intersection wear amount; The above steps are repeated to calculate the wear amount corresponding to each intersection and sum to obtain the total wear amount of the intersection.

7. The method of predicting tire wear condition based on vehicle acceleration according to claim 5, wherein, The total wear amount of each tire during the cornering is obtained according to the current load of each tire during the cornering stage and the wear model, including: For the first cornering, the current load of each tire during the cornering is determined according to the load distribution ratio during the cornering stage; The cornering driving distance during the cornering is obtained, and the first cornering wear amount during the first cornering is determined according to the cornering driving distance, the current load of each tire during the cornering, and the wear model; The above steps are repeated to calculate the cornering wear amount corresponding to each cornering and sum to obtain the total cornering wear amount.

8. The method of predicting tire wear condition based on vehicle acceleration according to claim 5, wherein, 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 amount 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 during normal driving is calculated according to the static load distribution ratio, and the total normal driving 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.

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