Method for acquiring force acting on tire, method for acquiring tire friction energy, system, and program

Abstract

To provide an acquisition method of force acting on a tire, an acquisition method of friction energy, a system, and a program which can improve accuracy.SOLUTION: An acquisition method of force acting on a tire comprises: acquiring data about the first longitudinal force distribution expressing either brake force distribution or drive force distribution obtained from an ideal formula on the basis of the vehicle specification; acquiring the maximum friction coefficient of a tire; setting the straight line connecting an intersection point of a line expressing the first longitudinal force distribution and a straight line expressing the maximum friction coefficient and an original point of a coordinate system as a second longitudinal force distribution in a coordinate system of a first axis and a second axis, and acquiring a travel mode expressing a travel condition of the vehicle including a front-rear direction acceleration and a left-right direction acceleration of the vehicle; and acquiring tire behavior data calculated on the basis of the second longitudinal force distribution, the vehicle specification, the tire specification, and the front-rear direction and left-right direction accelerations in the travel mode. The tire behavior data includes data about the front-rear direction force, the front-rear direction speed, the left-right direction force, the left-right direction speed, and the slip rate in the tire.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present disclosure relates to a method for acquiring forces acting on a tire, a method for acquiring frictional energy of a tire, a system, and a program. [Background technology]

[0002] For example, it is described that friction energy is calculated in a tire wear life estimation system for predicting the amount of tire wear (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-156295 Summary of the Invention [Problem to be solved by the invention]

[0004] However, Patent Document 1 does not mention braking force distribution, which is the distribution of braking force between the front and rear wheels, and it is believed that there is room for further improvement in accuracy. Braking force distribution is considered important in simulating tire wear and braking distance. The same can be said for driving force distribution in four-wheel drive vehicles. It is desirable to consider front / rear force distribution (braking force distribution or driving force distribution).

[0005] When considering longitudinal force distribution (braking force distribution or driving force distribution), it is possible to use longitudinal force distribution obtained from an ideal equation. However, it has been found that the longitudinal force distribution obtained from the ideal equation deviates from the measured value of an actual vehicle. Therefore, it is believed that there is room for improvement in the calculation accuracy of the force acting on the tires of each wheel.

[0006] The present disclosure provides a method for acquiring forces acting on a tire, a method for acquiring frictional energy, a system, and a program that can improve calculation accuracy. [Means for solving the problem]

[0007] The method for acquiring forces acting on tires of the present disclosure is a method executed by one or more processors, and includes the steps of: acquiring data regarding a first longitudinal force distribution, which represents either a braking force distribution or a driving force distribution obtained from an ideal equation based on vehicle specifications, and which can be expressed by plotting the longitudinal force of the front wheels on a first axis and the longitudinal force of the rear wheels on a second axis perpendicular to the first axis; acquiring a maximum friction coefficient of the tire; defining a second longitudinal force distribution as a line connecting the intersection of a line representing the first longitudinal force distribution and a line representing the maximum friction coefficient with the origin of the coordinate system in a coordinate system of the first axis and the second axis; generating data representing the second longitudinal force distribution; acquiring a driving mode representing vehicle driving conditions including longitudinal acceleration and lateral acceleration of the vehicle; and acquiring tire behavior data calculated based on the data representing the second longitudinal force distribution, the vehicle specifications, tire specifications, and the longitudinal and lateral accelerations in the driving mode, wherein the tire behavior data includes data regarding the longitudinal force, longitudinal speed, lateral force, lateral speed, and slip ratio at the tire. [Brief explanation of the drawings]

[0008] [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 obtaining the force acting on a tire and a method for obtaining the frictional energy of the tire. [Figure 3] 4 is a diagram showing a first braking force distribution (ideal braking force distribution) of vehicle model A. [Figure 4] 4 is a diagram showing a first braking force distribution (ideal braking force distribution) and a second braking force distribution of vehicle type A. [Figure 5] 5 is a diagram showing a first braking force distribution (ideal braking force distribution) and a second braking force distribution of vehicle model A shown in FIGS. 3 and 4, and measured values ​​of braking force distribution of an actual vehicle. FIG. [Figure 6] This diagram shows the actual vehicle braking force (actual measurement value), ideal braking force (first braking force distribution), and estimated braking force (second braking force distribution) using this method for vehicle type A, with the horizontal axis representing vehicle deceleration during braking and the vertical axis representing the braking force on the front wheels. [Figure 7] FIG. 6 is a diagram corresponding to FIG. 5 for vehicle model B. [Figure 8] FIG. 7 is a diagram corresponding to FIG. 6 for vehicle model B. [Figure 9] FIG. 10 is an explanatory diagram of acceleration frequency distribution data having a driving mode. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings.

[0010] [system] The system 1 of this embodiment is configured to be able to acquire the force acting on the tire, and also to be able to calculate the friction energy based on the force acting on the tire.

[0011] As shown in FIG. 1, the system 1 includes a first longitudinal force distribution acquisition unit 10, a maximum friction coefficient acquisition unit 11, a second longitudinal force distribution generation unit 12, a driving mode data acquisition unit 13, a tire behavior data acquisition unit 14, and a friction energy calculation unit 15. These units (10-15) 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, the processor 1a in one device realizes each unit, 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. In other words, one or multiple processors execute the processing. The memory 1b stores data D1 relating to a first longitudinal force distribution, data D2 representing the maximum friction coefficient, data D3 relating to a second longitudinal force distribution, data D4 relating to vehicle specifications, data D5 relating to tire specifications, measurement data D6, acceleration frequency distribution data D7, tire behavior data D8, and data D9 relating to friction energy for each driving mode.

[0012] The first longitudinal force distribution acquisition unit 10 acquires data D1 relating to the first longitudinal force distribution obtained from an ideal equation based on vehicle specifications. The acquired data D1 relating to the first longitudinal force distribution is stored in memory 1b. The first longitudinal force distribution acquisition unit 10 may acquire the data D1 relating to the first longitudinal force distribution from an external source, or may calculate it based on given vehicle specification data D4. The first longitudinal force distribution represents either the braking force distribution or the driving force distribution between the front and rear wheels. In this embodiment, an example will be described in which the first longitudinal force distribution is braking force distribution. FIG. 3 is a diagram showing the first braking force distribution (ideal braking force distribution) of vehicle type A. The horizontal axis represents the braking force per unit load obtained by dividing the braking force [N] of the front wheels by the vehicle load [N] when stationary, and the vertical axis represents the braking force per unit load obtained by dividing the braking force [N] of the rear wheels by the vehicle load [N] when stationary. As shown in Figure 3, the longitudinal force distribution is data that can be expressed by plotting the longitudinal force (braking force) of the front wheels on the first axis (horizontal axis in the figure) and the longitudinal force (braking force) of the rear wheels on the second axis (vertical axis in the figure) perpendicular to the first axis. In other words, the ratio of the longitudinal forces of the front and rear wheels changes depending on the longitudinal forces of the front wheels or the longitudinal forces of the rear wheels. The braking force distribution obtained from the ideal equation is shown as an upwardly convex curve.

[0013] The braking force distribution obtained from the ideal equation (ideal braking force distribution) is the braking force distribution that maximizes the friction coefficient for all four wheels of the vehicle. Generally, it can be obtained using the following equations (1) and (2). B f =α(W f0 +m·α·h / L) …(1) B r =α(W r0 +m·α·h / L) …(2) However, B f indicates the front wheel braking force [N], and B r indicates the rear wheel braking force [N], and α indicates the vehicle acceleration [m / s 2 ] and W f0 indicates the static load on the front wheels when the vehicle is stopped [N], and W r0 indicates the static load [N] on the rear wheels when the vehicle is stopped, m indicates the mass [kg] of the entire vehicle when the vehicle is stopped, h indicates the height of the vehicle's center of gravity [m], and L indicates the wheelbase [m]. Figure 3 shows Bf The horizontal axis is the normalized value obtained by dividing by m·α, and B r The vertical axis shows the normalized value obtained by dividing by m·α, and the vertical axis shows the ideal braking force distribution curve plotted by varying α.

[0014] The maximum friction coefficient acquisition unit 11 acquires the maximum friction coefficient μ of the tire. The maximum friction coefficient μ is obtained by a test using a tire testing machine or a running test using an actual vehicle, and the test results are input into the system, whereby the maximum friction coefficient acquisition unit 11 acquires the maximum friction coefficient μ.

[0015] The second longitudinal force distribution generator 12 generates data D3 representing the second longitudinal force distribution based on data D1 relating to the first longitudinal force distribution and data D2 relating to the maximum friction coefficient μ. The data D3 representing the second longitudinal force distribution is stored in memory 1b. FIG. 4 is a diagram showing the first braking force distribution (ideal braking force distribution) and the second braking force distribution for vehicle model A. Specifically, as shown in FIG. 4, the second longitudinal force distribution generator 12 determines the second longitudinal force distribution as a line connecting the intersection of the line (curve) representing the first longitudinal force distribution and the line representing the maximum friction coefficient μ to the origin of the coordinate system in a coordinate system of the first and second axes. In FIG. 4, the second braking force distribution (second longitudinal force distribution) is shown as a line. In the example of FIG. 4, the line intersects with the maximum friction coefficient [μ=0.98] when the braking force per unit load of the front wheels is 0.8 and the braking force per unit load of the rear wheels is 0.2. The line from this intersection to the origin is the second braking force distribution. In Figure 4, the braking force of the front wheels is denoted as Fx, and the load on the front wheels is denoted as W.

[0016] Next, the reason why the second braking force distribution is superior to the first braking force distribution (ideal braking force distribution) will be explained. Fig. 5 is a diagram showing the first braking force distribution (ideal braking force distribution) of vehicle type A shown in Figs. 3 and 4, the second braking force distribution, and the measured values ​​of braking force distribution of an actual vehicle. In Fig. 5, the measured values ​​are indicated by crosses. It can be seen that the second braking force distribution is closer to the measured values ​​(crosses) than the first braking force distribution. Fig. 6 is a graph in which the horizontal axis represents the acceleration [m / s 26 shows the actual vehicle braking force (measured value), ideal braking force (first braking force distribution), and estimated braking force (second braking force distribution) for vehicle model A, with the vertical axis representing the braking force on the front wheels [N]. The acceleration during braking on the horizontal axis of FIG. 6 is a negative value if the front is considered positive, but in FIG. 6 negative values ​​are shown as positive values. It can be seen from FIG. 6 that the second braking force distribution is closer to the actual measured value than the first braking force distribution. Fig. 7 is a diagram corresponding to Fig. 5 for vehicle model B. In Fig. 7, actual measured values ​​are indicated by triangles. Fig. 8 is a diagram corresponding to Fig. 6 for vehicle model B. It can be seen from Figs. 7 and 8 that the second braking force distribution is closer to the actual measured values ​​than the first braking force distribution. Therefore, the second braking force distribution proposed in this specification is closer to the measured values ​​of an actual vehicle than the ideal braking force distribution (first braking force distribution), and can improve the calculation accuracy of tire behavior data (acting forces and speeds).

[0017] The driving mode data acquisition unit 13 acquires driving modes that represent the driving conditions of the vehicle. The driving modes include the vehicle's longitudinal acceleration and lateral acceleration. In this embodiment, the driving mode data acquisition unit 13 acquires acceleration frequency distribution data D7 that associates multiple driving modes with the frequency at which each driving mode appears on the driving course.

[0018] In this embodiment, the driving mode data acquisition unit 13 generates the acceleration frequency distribution data D7, but is not limited to this and may acquire the data from an external source. Specifically, the driving mode data acquisition unit 13 has a measurement data acquisition unit 13a, a driving mode setting unit 13b, a data classification unit 13c, and a frequency calculation unit 13d in order to generate acceleration frequency distribution data D7.

[0019] The measurement data acquisition unit 13a acquires a plurality of pieces of measurement data D6. The measurement data D6 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.

[0020] The measurement data acquiring unit 13a may acquire the measurement data from the acceleration sensor 20 by any means as long as it can acquire the measurement data D6. 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 13a may receive the measurement data via wireless communication from the computer including the acceleration sensor 20 of the vehicle.

[0021] In this embodiment, the plurality of measurement data D6 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.

[0022] In this embodiment, the measurement data D6 includes a 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.

[0023] In this embodiment, the driving mode data acquisition unit 13 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. 9, a plurality of sections are set by subdividing (dividing) each of the three directions of acceleration. In FIG. 9, one side of one box corresponds to one section. One driving mode can be represented by one box as shown in the figure. 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. 9, 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. 9, the frequency value is expressed as a decimal, so that the sum of the frequency values ​​of all the driving modes becomes 1.0. As shown in FIG. 9, 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.

[0024] 9 shows an example of acceleration frequency distribution data D7 with 11 sections in the forward / backward direction, 11 sections in the left / right direction, and 6 sections in the up / down direction, resulting in 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).

[0025] The driving mode setting unit 13b 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. 9. In this embodiment, the sizes of the plurality of sections are constant, but they do not have to be constant.

[0026] The data classification unit 13c classifies each of the multiple measurement data acquired by the measurement data acquisition unit 13a into one of the multiple driving modes set by the driving mode setting unit 13b. 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.

[0027] The frequency calculation unit 13d 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.

[0028] The tire behavior data acquisition unit 14 acquires tire behavior data D8 calculated based on data D3 representing the second longitudinal force distribution, data D4 related to vehicle specifications, data D5 related to tire specifications, and longitudinal and lateral accelerations in the driving mode. The tire behavior data D8 includes data related to the longitudinal force (Fx), longitudinal velocity (Vx), lateral force (Fy), lateral velocity (Vy), and slip ratio (S) at the tire. The tire behavior data D8 is calculated by a tire behavior simulation system 3. In this embodiment, vehicle motion simulation software "CarSIM (registered trademark)" manufactured by Mechanical Simulation, Inc. of the United States is used as the tire behavior simulation system 3. The tire behavior data acquisition unit 14 acquires the tire behavior data D8 calculated by the tire behavior simulation system 3. CarSIM (registered trademark) runs a virtual vehicle based on the input data so as to obtain specified longitudinal and lateral accelerations. For example, if the vehicle speed is 5 m / s to the right, 2 If you set it to run steadily at , the acceleration to the right will be 5m / s 2 The vehicle continues turning so that the acceleration (deceleration) during braking is 5m / s 2 If so, the vehicle will move at an initial speed of 5 m / s 2 The brake pressure is controlled so that the vehicle decelerates at a specified speed. In this way, the vehicle is driven in a manner that allows the specified driving mode (forward / backward and left / right acceleration) to be realized, and tire behavior data D8 for each of the four wheels at that time can be obtained. The tire behavior data D8 is stored in memory 1b.

[0029] Data D4 relating to vehicle specifications is data that is input to system 1 and stored in memory 1b. Specific examples of data D4 relating to vehicle specifications include the vehicle's overall length [m], overall width [m], overall height [m], front axle load mass [kg], rear axle load mass [kg], wheelbase [m], distance between the ground contact centers of tires mounted on the left and right front wheels [m], distance between the ground contact centers of tires mounted on the left and right rear wheels [m], horizontal distance between the front axle and the center of gravity, front overhang or rear overhang, roll moment of inertia, pitch moment of inertia, yaw moment of inertia, camber angle of the front wheels, camber angle of the rear wheels, toe angle of the front wheels, toe angle of the rear wheels, etc.

[0030] The data D5 relating to the tire specifications is data that is input to the system 1 and stored in the memory 1b. Specific examples of the data D5 relating to the tire specifications include the tire mass, vertical stiffness, rolling radius, radius under no load, rolling resistance, μ-S characteristics, SA-CF characteristics, SA-SAT characteristics, and relaxation length.

[0031] The friction energy calculation unit 15 calculates friction energy based on the tire behavior data D8 for the driving mode into which the measurement data D6 is classified. The calculated friction energy is stored in the memory 1b. 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 friction energy is the friction energy generated when longitudinal acceleration and lateral acceleration occur, assuming that the load is the same as when the vehicle is stationary. The friction energy can be obtained based on computer simulations such as the finite element method (FEM) or experimentally measured values, and is well known, so a detailed description will be omitted. For example, if the longitudinal acceleration, lateral acceleration, and stationary load in each driving mode are input into an existing friction energy simulation system, friction energy may be output. 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. 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 into a tire testing machine, and frictional 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 makes the tire 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 the longitudinal shear force, longitudinal slippage, lateral shear force, and lateral slippage generated at a given point on the tire tread surface. The frictional energy in each direction can be calculated from the longitudinal and lateral shear forces and the amount of slippage.

[0032] The frictional energy calculation unit 15 of this embodiment calculates the accumulated frictional energy based on the frictional energy and frequency of each driving mode. As an example, the frictional energy is weighted according to the frequency of each driving mode and integrated (see, for example, JP 2015-123941 A).

[0033] [Methods for obtaining the force acting on the tire and the frictional energy of the tire] The method for obtaining the force acting on the tire and the method for obtaining the frictional energy of the tire will be explained with reference to FIG.

[0034] First, in step ST1, the first longitudinal force distribution acquisition section 10 acquires data D1 relating to the first longitudinal force distribution. In step ST2, the maximum friction coefficient acquisition unit 11 acquires the maximum friction coefficient μ of the tire. In step ST3, the second longitudinal force distribution generating section 12 generates data D3 representing the second longitudinal force distribution based on the data D1 relating to the first longitudinal force distribution and the maximum friction coefficient μ.

[0035] In step ST4, the driving mode data acquisition unit 13 acquires a driving mode that represents the driving conditions of the vehicle, including the acceleration in the forward / backward direction and the acceleration in the left / right direction of the vehicle. In this embodiment, acceleration frequency distribution data is acquired instead of a single driving mode. The steps will be described in detail. 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). The measurement data acquisition unit 13a acquires a plurality of measurement data having accelerations in three directions, namely, the front-rear direction, the left-right direction, and the up-down direction of the vehicle. The driving mode setting unit 13b 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. The data classification unit 13c classifies each of the acquired multiple pieces of measurement data into one of multiple driving modes. The frequency calculation unit 13d 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, thereby generating acceleration frequency distribution data.

[0036] In step ST5, the tire behavior data acquisition unit 14 acquires tire behavior data D8 calculated based on the second longitudinal force distribution, vehicle specifications, tire specifications, and longitudinal and lateral accelerations in the driving mode. This process is executed the number of times equal to the number of driving modes. In step ST6, the friction energy calculation unit 15 calculates the friction energy based on the tire behavior data.

[0037] As described above, in this embodiment, the method for acquiring forces acting on tires may be a method executed by one or more processors, and may include acquiring data related to a first longitudinal force distribution that represents either a braking force distribution or a driving force distribution obtained from an ideal equation based on vehicle specifications, and that can be expressed by plotting the longitudinal force of the front wheels on a first axis and the longitudinal force of the rear wheels on a second axis perpendicular to the first axis; acquiring a maximum friction coefficient for the tires; defining a second longitudinal force distribution as a line connecting the origin of the coordinate system and the intersection of the line representing the first longitudinal force distribution and the line representing the maximum friction coefficient; generating data representing the second longitudinal force distribution; acquiring a driving mode that represents the driving conditions of the vehicle, including the longitudinal acceleration and lateral acceleration of the vehicle; and acquiring tire behavior data calculated based on the data representing the second longitudinal force distribution, the vehicle specifications, tire specifications, and the longitudinal and lateral acceleration in the driving mode, wherein the tire behavior data includes data related to the longitudinal force, longitudinal speed, lateral force, lateral speed, and slip ratio at the tires. In this way, the second longitudinal force distribution is defined as the line connecting the origin and the intersection of the line (curve) representing the first longitudinal force distribution and the line representing the maximum friction coefficient, and therefore the second longitudinal force distribution is closer to the measured value of the actual vehicle than the first longitudinal force distribution, which is the ideal longitudinal force distribution, and this makes it possible to improve the accuracy of calculating the force acting on the tires.

[0038] Although not particularly limited, as in the present embodiment, a plurality of measurement data having acceleration in three directions, i.e., forward / backward, left / right, and up / down, measured by a triaxial acceleration sensor while the vehicle is traveling may be acquired, a plurality of subdivided sections may be set for each of the three acceleration directions, a plurality of driving modes formed by combinations of the three-directional sections may be set, the plurality of acquired measurement data may each be classified into one of the plurality of driving modes, for each driving mode, the frequency of each driving mode may be calculated based on the number of classified measurement data and the total number of measurement data, and for the driving modes into which the measurement data has been classified, data representing the second longitudinal force distribution, vehicle specifications, tire specifications, and tire behavior data calculated based on the acceleration in the forward / backward and left / right directions in the driving mode may be acquired. In each driving mode, the force can be calculated with high accuracy.

[0039] Although not particularly limited, as in this embodiment, the method for acquiring the frictional energy of the tire may include the method for acquiring the force acting on the tire, and the frictional energy may be calculated based on the tire behavior data. The friction energy can be calculated with high accuracy.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] (1) In the above embodiment, the driving mode data acquisition unit 13 acquires acceleration frequency distribution data having a plurality of driving modes, but this is not limiting. For example, the driving mode data acquisition unit 13 may acquire a single driving mode. In this case, the driving mode may be input to the system or may be generated within the system 1.

[0045] (2) In the above embodiment, the longitudinal force distribution is a braking force distribution, but is not limited to this. The longitudinal force distribution may be a driving force distribution.

[0046] (3) In the above embodiment, the friction energy is calculated based on the tire behavior data, but this is not limiting. For example, the braking distance may be calculated based on the tire behavior data.

[0047] (4) In the above embodiment, a three-axis acceleration sensor is used to detect acceleration in three directions, but data in two directions (front, back, left, and right) is sufficient. Therefore, a two-axis acceleration sensor may be used, and the measurement data D6 may include acceleration in two directions.

[0048] (5) In the above embodiment, as shown in Fig. 9, the acceleration frequency distribution data is subdivided (divided) into multiple sections in each of the three acceleration directions, and one driving mode is set by combining the sections (edges) in the three directions. However, this is not limited to this. For example, the two directions, the forward / backward direction and the left / right direction, may be subdivided (divided) into multiple sections, and one driving mode may be set by combining the sections (edges) in the two directions. In this case, the measurement data may include acceleration in three directions or may include acceleration in two directions.

[0049] 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.

[0050] 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]

[0051] 1...system, 10...first longitudinal force distribution acquisition unit, 11...friction coefficient acquisition unit, 12...second longitudinal force distribution generation unit, 13...driving mode data acquisition unit, 13a...measurement data acquisition unit, 13b...driving mode setting unit, 13c...data classification unit, 13d...frequency calculation unit, 14...tire behavior data acquisition unit, 15...friction energy calculation unit.

Claims

1. 1. A method executed by one or more processors, comprising: acquire data relating to a first longitudinal force distribution that represents either a braking force distribution or a driving force distribution obtained from an ideal equation based on vehicle specifications, and that can be expressed by plotting the longitudinal forces of the front wheels on a first axis and the longitudinal forces of the rear wheels on a second axis perpendicular to the first axis; Get the maximum coefficient of friction of the tire, in a coordinate system of the first axis and the second axis, a line connecting an intersection of a line representing the first longitudinal force distribution and a line representing the maximum friction coefficient and an origin of the coordinate system is defined as a second longitudinal force distribution, and data representing the second longitudinal force distribution is generated; obtaining a driving mode representing a driving condition of the vehicle, including a longitudinal acceleration and a lateral acceleration of the vehicle; acquiring tire behavior data calculated based on the data representing the second longitudinal force distribution, the vehicle specifications, the tire specifications, and the accelerations in the longitudinal direction and the lateral direction in the driving mode; A method for obtaining forces acting on a tire, wherein the tire behavior data includes data relating to longitudinal forces, longitudinal speeds, lateral forces, lateral speeds, and slip ratios on the tire.

2. 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; 2. The method according to claim 1, wherein the tire behavior data calculated based on the data representing the second longitudinal force distribution, the vehicle specifications, the tire specifications, and the longitudinal and lateral accelerations in the driving mode are acquired for the driving mode in which the measurement data has been classified.

3. The method according to claim 1 or 2, A method for obtaining tire frictional energy, which calculates frictional energy based on the tire behavior data.

4. A system comprising one or more processors for carrying out the method according to any one of claims 1 to 3.

5. A program that causes one or more processors to execute the method according to any one of claims 1 to 3.

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