Method, system, and program for calculating tire wear performance value

Abstract

To provide tire wear performance value calculation method, system and program that can calculate a tire wear performance value taking load fluctuation acting on a tire into consideration.SOLUTION: A plurality of measurement data having accelerations in three directions comprising a cross direction, a longitudinal direction and a vertical direction of a vehicle is acquired, a plurality of travel modes, which are configured from a combination of sections in three directions, are set, the plurality of measurement data is classified into any travel mode of the plurality of travel modes, a travel mode frequency is calculated on the basis of the number of measurement data classified in each travel mode and the number of all travel modes, first friction energy is acquired for each travel mode from the acceleration in the cross direction, the acceleration in the longitudinal direction and a load during resting, the first friction energy is corrected for each travel mode on the basis of the acceleration in the vertical direction and the first friction energy is converted into the second friction energy, and a tire wear performance value is calculated on the basis of the second friction energy and the frequency of each travel mode.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to a method, system, and program for calculating a tire wear performance value. [Background technology]

[0002] In order to evaluate the wear performance value of a tire, a method is known in which friction energy is calculated based on the acceleration of the vehicle in the front, rear, left and right directions, and the wear performance value of the tire is calculated from the friction energy (see, for example, Patent Documents 1 and 2). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-123941 [Patent Document 2] Japanese Patent Application Laid-Open No. 2011-149879 Summary of the Invention [Problem to be solved by the invention]

[0004] The load acting on the tires fluctuates while the vehicle is running, and the load fluctuations affect the frictional energy, so it is desirable to take the load fluctuations acting on the tires into consideration.

[0005] The present disclosure provides a method, system, and program for calculating a tire wear performance value that can calculate a tire wear performance value taking into account load fluctuations acting on a tire. [Means for solving the problem]

[0006] The tire wear performance value calculation method disclosed herein is a method executed by one or more processors, which acquires multiple pieces of measurement data having acceleration in three directions (forward / backward, left / right, and up / down) of the vehicle measured by a three-axis acceleration sensor while the vehicle is traveling, sets multiple subdivided sections for each of the three acceleration directions, sets multiple driving modes consisting of combinations of the three-directional sections, classifies each of the acquired multiple measurement data into one of the multiple driving modes, calculates the frequency of each driving mode based on the number of classified measurement data and the total number of measurement data, acquires first friction energy from the forward / backward acceleration, left / right acceleration, and stationary load for the driving modes in which the measurement data is classified, corrects the first friction energy based on the up / down acceleration and converts the first friction energy into second friction energy that takes into account load fluctuations in the up / down direction, and calculates a tire wear performance value based on the second friction energy and the frequency for each driving mode. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing a system according to an embodiment of the present invention. [Figure 2] 4 is a flowchart showing a method for calculating a tire wear evaluation value. [Figure 3] FIG. 10 is an explanatory diagram of acceleration frequency distribution data. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings.

[0009] [system] The system 1 of this embodiment calculates frictional energy and calculates the tire wear performance value based on the calculated frictional energy.

[0010] As shown in FIG. 1, the system 1 includes a measurement data acquisition unit 10, an acceleration frequency distribution data generation unit 11, a first frictional energy acquisition unit 15, a conversion unit 16, and a tire wear performance value calculation unit 17. The acceleration frequency distribution data generation unit 11 includes a driving mode setting unit 12, a data classification unit 13, and a frequency calculation unit 14. These units (10-17) are realized by software and hardware working together when the processor 1a executes a processing routine shown in FIG. 2 that is pre-stored in a computer equipped with a processor 1a, a memory 1b, various interfaces, etc. In this embodiment, each unit is realized by the processor 1a in a single device, but this is not limited to this. For example, the units may be distributed using a network, with multiple processors executing the processing of each unit. That is, one or multiple processors execute the processing. The memory 1b stores the measurement data, acceleration frequency distribution data, the first frictional energy for each driving mode, the second frictional energy for each driving mode, the tire wear performance value, etc.

[0011] The measurement data acquisition unit 10 acquires a plurality of pieces of measurement data. The measurement data includes acceleration measured by a three-axis acceleration sensor 20 provided on the vehicle 2 while the vehicle 2 is traveling. The measurement data includes acceleration in three directions of the vehicle 2, that is, acceleration Ax in the front-rear direction of the vehicle 2, acceleration Ay in the left-right direction, and acceleration Az in the up-down direction. The unit of acceleration is [m / s 2 ]. The measurement data includes data that can be converted into distance or is associated with data that can be converted into distance. In this embodiment, the measurement data is measured at a constant sampling time (measurement interval, for example, 0.1 seconds (10 Hz)). The speed and sampling time can be converted into distance. Therefore, the measurement data has speed as data that can be converted into distance. The measurement data is also associated with the sampling time (sampling frequency) as data that can be converted into distance (for example, if the speed is 16 m / s and the sampling time is 0.1 seconds (10 Hz), the distance per measurement data can be calculated as 16 ÷ 10 = 1.6 m). The speed can be calculated based on the position information, obtained based on the wheel rotation speed, or obtained using the ground speed meter 21.

[0012] The measurement data acquiring unit 10 may acquire the measurement data from the acceleration sensor 20 by any means as long as it can acquire the measurement data. For example, the measurement data may be stored in a storage medium of a computer installed in the vehicle, and after the vehicle has completed traveling, the storage medium may be attached to a reading device of the system 1, and the measurement data may be acquired from the reading device. Alternatively, the measurement data acquiring unit 10 may receive the measurement data via wireless communication from the computer including the acceleration sensor 20 of the vehicle.

[0013] In this embodiment, the plurality of measurement data are generated by measuring the acceleration of the acceleration sensor 20 while the vehicle 2 travels along a predetermined travel course. For example, the acceleration sensor 20 measures the acceleration as the vehicle accelerates from a stopped state at the start of the travel course, decelerates before a curve, turns the curve, accelerates again, and then repeats acceleration, deceleration, and turns until the vehicle stops at the finish line of the travel course.

[0014] In this embodiment, the measurement data includes speed measured at regular time intervals, but is not limited to this. For example, the measurement data may include location information as data that can convert location information into distance, or may be associated with location information as data that can convert location information into distance. Location information can be acquired at regular time intervals by various location information acquisition devices, including a GPS receiver that acquires satellite location information based on GPS. Furthermore, the measurement data may be measured each time the vehicle 2 travels a certain distance, rather than at regular time intervals. In this case, the measurement data itself is associated with distance. The measurement data is stored in memory 1b.

[0015] The acceleration frequency distribution data generating unit 11 generates acceleration frequency distribution data. The acceleration distribution data has a plurality of driving modes and the frequency of each driving mode. As shown schematically in FIG. 3, a plurality of sections are set by subdividing (dividing) each of the three directions of acceleration. In FIG. 3, one side of one box corresponds to one section. One driving mode can be represented by one box as shown in FIG. 3. One box (driving mode) is made up of a combination of sections (sides) in three directions. In this embodiment, each of the three directions is divided into 0.05 m / s 2 Therefore, the acceleration range (width of the side) of one driving mode (box) is 0.05 m / s 2 The width of the section is 0.05 m / s 2 Therefore, the representative value for each driving mode is +0.10 [m / s 2 ],+0.05[m / s 2 ],0[m / s 2 ],-0.05[m / s 2 ],-0.10[m / s 2 ]. As shown in FIG. 3, a certain driving mode M1 has a representative value of longitudinal acceleration Ax, a representative value of lateral acceleration Ay, a representative value of vertical acceleration Az, and a frequency (frequency value: 0.1). Similarly, a certain driving mode M2 ​​has a representative value of longitudinal acceleration Ax, a representative value of lateral acceleration Ay, a representative value of vertical acceleration Az, and a frequency (frequency value: 0.01). The frequency value indicates how often that driving mode appears in all the measurement data. In the example of FIG. 3, the frequency value is expressed as a decimal, so that adding up the frequency values ​​of all the driving modes results in 1.0. As shown in FIG. 3, the measured acceleration includes not only positive values ​​(+) but also negative values ​​(-). For example, the longitudinal acceleration Ax of driving mode M1 is 0 [m / s 2], the lateral acceleration Ay is a positive value, and the vertical acceleration Az is a positive value. In driving mode M2, the longitudinal acceleration Ax is a negative value, the lateral acceleration Ay is a negative value, and the vertical acceleration Az is a positive value. In this way, the acceleration values ​​in the three directions in each driving mode are different. Note that the longitudinal acceleration Ax is a positive value at the front of vehicle 2 and a negative value at the rear of vehicle 2. The lateral acceleration Ay is a positive value at the right side of vehicle 2 and a negative value at the left side of vehicle 2. The vertical acceleration Az is a positive value at the bottom of vehicle 2 and a negative value at the top of vehicle 2.

[0016] The acceleration frequency distribution data shown in Fig. 3 has 11 sections in the forward / backward direction, 11 sections in the left / right direction, and 6 sections in the up / down direction, and there are 11 x 11 x 6 = 726 driving modes, but the number of sections is the resolution and can be set arbitrarily. For example, the number of driving modes may be (41 x 41 x 41).

[0017] The driving mode setting unit 12 sets a plurality of subdivided sections for each of the three acceleration directions, and sets a plurality of driving modes formed by combinations of the sections in the three directions, as shown in Fig. 3. In this embodiment, the sizes of the plurality of sections are uniform, but they do not have to be uniform.

[0018] The data classification unit 13 classifies each of the multiple measurement data acquired by the measurement data acquisition unit 10 into one of the multiple driving modes set by the driving mode setting unit 12. The measurement data is classified into a driving mode in which the acceleration in each direction matches. For example, if the longitudinal acceleration Ax is 0.12 m / s 2 In this case, the typical value is 0.10 m / s 2 and the acceleration range is 0.075~0.125m / s 2 As a result, measurement data is always classified into one of the driving modes. There are cases where no measurement data is classified in a driving mode, and the number of measurement data classified also varies.

[0019] The frequency calculation unit 14 calculates the frequency of each driving mode based on the number of classified measurement data and the number of all measurement data for each driving mode. The frequency (frequency value) can be calculated by dividing the number of classified measurement data by the number of all measurement data. If there are N driving modes, the frequency calculation is performed N times. As a result, acceleration frequency distribution data is generated. In this embodiment, measurements are taken at regular intervals, so the measurement data is expressed in units of time, and the frequency calculated simply using the number of measurement data points is the frequency in units of time. Frictional energy is preferably calculated based on distance units corresponding to the number of contacts between the tire and the road surface. Therefore, in this embodiment, a process is performed to convert the data from units of time to units of distance. Specifically, the travel distance in each driving mode is calculated based on the speed and time in that driving mode, and the frequency of the travel distance in each driving mode relative to the total travel distance is calculated. Of course, if the measurement data is measured every time a certain distance is traveled, the data is already in units of distance, so the frequency may be calculated based on the number of measurement data.

[0020] The first friction energy acquisition unit 15 acquires first friction energy from the longitudinal acceleration, lateral acceleration, and stationary load for the driving mode in which the measurement data has been classified. The friction energy can be calculated by multiplying the shear force acting between the tire and the road surface by the amount of slippage. The first friction energy is friction energy generated in a state in which longitudinal acceleration and lateral acceleration occur, assuming that the stationary load is the same as the stationary load. Because the first friction energy is calculated using the stationary load, load fluctuations due to vertical acceleration are not taken into account. The first friction energy can be acquired based on computer simulations such as FEM (finite element method) or experimentally measured values, and is well known, so a detailed description will be omitted. For example, the first friction energy may be output by inputting the longitudinal acceleration, lateral acceleration, and stationary load in each driving mode into an existing friction energy simulation system. The friction energy simulation system, for example, applies a specified load (the input stationary load) to a tire model and brings it into contact with the road surface, rolls the tire model to achieve specified conditions (longitudinal acceleration and lateral acceleration), and simulates the longitudinal shear force, longitudinal slip displacement, lateral shear force, and lateral slip displacement that occur at any node on the tire tread surface. The friction energy can be calculated from the longitudinal and lateral shear forces and the amount of slip displacement. For example, the longitudinal acceleration, lateral acceleration, and stationary load in each driving mode may be input to a tire testing machine, and the first friction energy calculated based on the obtained measurement results may be output. The tire testing machine, for example, applies a specified load (the input stationary load) to a road surface and causes the tire to contact the road surface and roll under specified conditions (longitudinal acceleration and lateral acceleration). At this time, based on a pressure sensor and a motor on the road surface, measures longitudinal shear force, longitudinal slippage, lateral shear force, and lateral slippage generated at a given point on the tire tread surface. The friction energy in each direction can be calculated from the longitudinal and lateral shear force and the amount of slippage.

[0021] For the driving mode in which the first friction energy is acquired, the conversion unit 16 converts the first friction energy into second friction energy that corrects the first friction energy based on the vertical acceleration and takes into account the vertical load fluctuation. This is because shear force is proportional to the load. Specifically, the process of converting the first friction energy into the second friction energy is calculated using the following formula (1). This conversion process is executed for each driving mode, so the number of times the conversion process is executed is the number of driving modes. Second friction energy = First friction energy × {(1G + vertical acceleration) / 1G} … (1) However, G is the gravitational acceleration (1G=9.80665m / s 2) {(1G + vertical acceleration) / 1G} can be considered a correction coefficient, and can be expressed as: second friction energy = first friction energy × correction coefficient. This makes it possible to convert, at the friction energy level, the first friction energy that does not take into account load fluctuations due to acceleration in the vertical direction into the second friction energy that takes into account load fluctuations due to acceleration in the vertical direction.

[0022] The tire wear performance value calculation unit 17 calculates the tire wear performance value based on the second friction energy and frequency of each driving mode. One example is to multiply the second friction energy by a weighting corresponding to the frequency of each driving mode (see, for example, JP 2015-123941 A). Calculating a tire wear performance value from friction energy is well known, so a detailed description will be omitted. The tire wear performance value may be a value that allows tires to be compared as the amount of wear across the entire tire, or may be a value that allows the amount of wear of each part of a tire (for example, a tread block) to be compared using the second friction energy and additional data.

[0023] [Calculation method for tire wear performance value] The method for calculating the tire wear performance value will be explained with reference to FIG.

[0024] First, in step ST1, the acceleration sensor 20 measures the acceleration of the vehicle in three directions (front-rear, left-right, and up-down) multiple times while the vehicle is running. In this embodiment, the measurement is performed once every 0.1 seconds (10 Hz). In step ST2, the measurement data acquisition unit 10 acquires a plurality of measurement data containing accelerations in three directions, namely, the front-rear direction, the left-right direction, and the up-down direction of the vehicle. In step ST3, the driving mode setting unit 12 sets a plurality of subdivided sections for each of the three directions of acceleration, and sets a plurality of driving modes formed by combinations of the sections in the three directions. In step ST4, the data classification unit 13 classifies each of the acquired multiple pieces of measurement data into one of multiple driving modes. In step ST5, the frequency calculation unit 14 calculates the frequency of each driving mode based on the number of classified measurement data and the total number of measurement data for each driving mode. In step ST6, the first frictional energy acquiring unit 15 acquires the first frictional energy from the acceleration in the forward / backward direction, the acceleration in the left / right direction, and the load when stationary for the driving mode in which the measurement data has been classified. In step ST7, the conversion unit 16 corrects the first frictional energy based on the vertical acceleration for the travel mode in which the first frictional energy was acquired, and converts it into second frictional energy that takes into account the vertical load fluctuation. In step ST8, the tire wear performance value calculation unit 17 calculates the tire wear performance value based on the second friction energy and frequency of each driving mode.

[0025] As described above, in this embodiment, the method for calculating a tire wear performance value may be executed by one or more processors, and may include the steps of: acquiring a plurality of measurement data having acceleration in three directions (forward / backward, left / right, and up / down) of the vehicle measured by a three-axis acceleration sensor while the vehicle is traveling; setting a plurality of subdivided sections for each of the three acceleration directions; setting a plurality of driving modes consisting of combinations of the three-directional sections; classifying each of the acquired measurement data into one of the plurality of driving modes; calculating the frequency of each driving mode based on the number of classified measurement data and the total number of measurement data; acquiring first friction energy from the forward / backward acceleration, left / right acceleration, and stationary load for the driving modes in which the measurement data has been classified; correcting the first friction energy based on the up / down acceleration and converting the first friction energy into second friction energy that takes into account load fluctuations in the up / down direction; and calculating a tire wear performance value based on the second friction energy and frequency of each driving mode. In this way, the first friction energy obtained from the longitudinal acceleration, lateral acceleration, and stationary load is converted into second friction energy that takes into account tire load fluctuations due to vertical acceleration.This makes it possible to take into account tire load fluctuations while utilizing the existing configuration that obtains first friction energy from longitudinal and lateral acceleration, thereby improving the accuracy of tire wear evaluation values.

[0026] Although not particularly limited, as in this embodiment, the process of correcting the first friction energy from the vertical acceleration and converting it into the second friction energy that takes into account the vertical load fluctuation may be calculated using the following equation (1). Second friction energy = First friction energy × (1G + vertical acceleration) / 1G … (1) Here, G represents the acceleration due to gravity. In this way, correction can be realized using a simple correction formula.

[0027] The program according to this embodiment is a program that causes one or more computers to execute the above method. By executing these programs, it is possible to obtain the effects of the above-mentioned methods.

[0028] Although the embodiments of the present disclosure have been described above with reference to the drawings, the specific configurations should not be considered to be limited to these embodiments. The scope of the present disclosure is defined not only by the description of the above embodiments but also by the claims, and further includes all modifications within the meaning and scope of the claims.

[0029] The structures employed in the above-described embodiments can be employed in any other embodiment. The specific configurations of the components are not limited to the above-described embodiments, and various modifications are possible within the scope of the present disclosure.

[0030] For example, the order of execution of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings, can be implemented in any order, as long as the output of a previous process is not used in a subsequent process. Even if the flow in the claims, specifications, and drawings is explained using terms such as "first" and "next" for convenience, this does not mean that the processes must be executed in this order.

[0031] 1 are realized by executing a predetermined program on one or more processors, but each unit may also be configured with a dedicated memory or dedicated circuit. In the system 1 of the above embodiment, each unit is implemented in the processor 1a of a single computer, but each unit may be distributed and implemented on multiple computers or in the cloud. In other words, the above method may be executed on one or more processors.

[0032] System 1 includes a processor 1 a. For example, processor 1 a can be a central processing unit (CPU), a microprocessor, or other processing unit capable of executing computer-executable instructions. System 1 also includes memory 1 b for storing data for system 1. In one example, memory 1 b includes computer storage media, such as RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, DVD or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device, or any other medium that can be used to store desired data and that can be accessed by system 1. [Explanation of symbols]

[0033] 1...system, 10...measurement data acquisition unit, 11...acceleration frequency distribution data generation unit, 12...driving mode setting unit, 13...data classification unit, 14...frequency calculation unit, 15...first friction energy acquisition unit, 16...conversion unit, 17...tire wear performance value calculation unit.

Claims

1. 1. A method executed by one or more processors, comprising: Obtaining a plurality of measurement data having acceleration in three directions, i.e., forward / backward, left / right, and up / down directions of the vehicle, measured by a triaxial acceleration sensor while the vehicle is traveling; Multiple sections are set for each of the three acceleration directions, and multiple driving modes are set, each consisting of a combination of the three sections. classifying each of the acquired plurality of measurement data into one of a plurality of driving modes; For each driving mode, calculate the frequency of each driving mode based on the number of classified measurement data and the number of all measurement data; For the driving mode in which the measurement data has been classified, a first friction energy is obtained from the longitudinal acceleration, the lateral acceleration, and the load at a standstill; For the traveling mode in which the first frictional energy is acquired, converting the first frictional energy into second frictional energy using the following equation (1): A method for calculating a tire wear performance value, the method comprising: calculating a tire wear performance value based on the second friction energy and the frequency of each driving mode. Second friction energy = First friction energy × (1 G + vertical acceleration) / 1 G ... (1) Here, G represents the gravitational acceleration.

2. A system comprising one or more processors for executing the method of claim 1.

3. A program causing one or more processors to execute the method of claim 1.

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