Tire wear state estimation device

Abstract

To provide an abrasion state estimation device which can estimate the abrasion state of a tire without acquiring a large number of tire data in advance.SOLUTION: A tire abrasion state estimation device comprises: a rotational speed acquisition unit; a driving force acquisition unit; a slip ratio calculation unit; a coefficient calculation unit; and an estimation unit. The rotational speed acquisition unit sequentially acquires the rotational speed of a tire attached to a vehicle. The driving force acquisition unit sequentially acquires the driving force of the vehicle. The slip ratio calculation unit calculates a slip ratio on the basis of the sequentially-acquired rotational speed of the tire. The coefficient calculation unit calculates a regression coefficient expressing the relation between the slip ratio and the driving force on the basis of a plurality of data sets of the slip ratio and the driving force. The estimation unit estimates the abrasion state of the tire in the time of calculation of the regression coefficient on the basis of a previously-specified constant number, the regression coefficient in the reference time of the tire, the abrasion state of the tire and the calculated regression coefficient.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present invention relates to a wear state estimation device, an estimation method, and an estimation program for estimating the wear state of a tire mounted on a vehicle during travel.

Background Art

[0002] Patent Document 1 discloses a device for detecting the wear state of a tire based on the slope of a relational expression between the front-to-rear wheel ratio of the rotational speed of the tire and the vehicle acceleration. According to Patent Document 1, the slope of the relational expression corresponds to the slope of the μ-s characteristic curve of the tire in a range where the slip ratio s is small. The slope of the μ-s characteristic curve has the property that it increases as the rigidity of the tread rubber of the tire increases and decreases conversely, but when the tire wears, the rigidity of the tread rubber increases and the slope of the μ-s characteristic curve increases. In Patent Document 1, the wear of the tire is determined by comparing the slope of the μ-s characteristic curve or the slope of the front-to-rear wheel ratio - acceleration straight line specified in advance for a new or 50% worn tire with the slope calculated during the travel of the vehicle.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the degree to which the above slope changes due to wear varies depending on the type of tire. Therefore, in the device disclosed in Patent Document 1, in order to more accurately determine wear, it is necessary to acquire data on the above slope at the time of wear for each type of tire and determine a threshold value for the slope for determining wear. However, this requires a huge amount of experiments, so a technique that can more simply estimate the wear state is desired.

[0005] This disclosure aims to provide a tire wear state estimation device, estimation method, and estimation system that can estimate the tire wear state without having to acquire data on a large number of tires in advance. [Means for solving the problem]

[0006] A tire wear state estimation device according to the first aspect of this disclosure comprises a rotation speed acquisition unit, a driving force acquisition unit, a slip ratio calculation unit, a coefficient calculation unit, and an estimation unit. The rotation speed acquisition unit sequentially acquires the rotation speed of a tire mounted on a vehicle. The driving force acquisition unit sequentially acquires the driving force of the vehicle. The slip ratio calculation unit calculates the slip ratio based on the sequentially acquired tire rotation speeds. The coefficient calculation unit calculates a regression coefficient representing the relationship between the slip ratio and the driving force based on a plurality of data sets of the slip ratio and the driving force. The estimation unit estimates the tire wear state at the time of calculation of the regression coefficient based on a predetermined constant, the regression coefficient and the tire wear state at a reference time for the tire, and the calculated regression coefficient.

[0007] The determination device relating to the second aspect of this disclosure is a wear state estimation device relating to the first aspect, wherein the constant represents the regression coefficient when it is assumed that the tread grooves of the tire have disappeared or are almost completely gone.

[0008] The wear state estimation device relating to the third aspect of this disclosure is a wear state estimation device relating to the first or second aspect, wherein the constant is independent of the type of tire.

[0009] The wear state estimation device relating to the fourth aspect of this disclosure is a wear state estimation device relating to any of the first or third aspects, wherein the reference time is when the tire is mounted on the vehicle or when the tire is rotated.

[0010] The wear state estimation device according to the fifth aspect of this disclosure is a wear state estimation device according to any of the first or fourth aspects, wherein the coefficient calculation unit calculates the regression coefficient based on a plurality of filtered slip ratio and driving force datasets.

[0011] A wear state estimation device according to the sixth aspect of this disclosure is a wear state estimation device according to any of the first or fifth aspects, further comprising a temperature acquisition unit for acquiring the temperature outside the vehicle, and a coefficient correction unit for correcting the regression coefficient based on the acquired temperature.

[0012] A wear state estimation device according to the seventh aspect of this disclosure is a wear state estimation device according to any of the first or sixth aspects, further comprising: a turning radius acquisition unit that acquires the turning radius of the vehicle; relational information representing the relationship between the turning radius and the slip ratio; and a slip ratio correction unit that corrects the slip ratio based on the acquired turning radius.

[0013] The wear state estimation device relating to the eighth aspect of this disclosure is a wear state estimation device relating to the seventh aspect, wherein the related information is information that expresses the slip ratio as a quadratic function of the reciprocal of the turning radius.

[0014] The wear state estimation method relating to the ninth aspect of this disclosure includes the following. Furthermore, the wear state estimation program relating to the tenth aspect of this disclosure causes a computer to perform the following. - To sequentially acquire the rotation speed of the tires mounted on the vehicle. - To sequentially acquire the driving force of the aforementioned vehicle. • Calculate the slip ratio based on the sequentially acquired tire rotation speeds. Based on multiple datasets of the slip ratio and the driving force, calculate a regression coefficient that represents the relationship between the slip ratio and the driving force. - Estimating the wear state of the tire at the time of calculation of the regression coefficient based on a predetermined constant, the regression coefficient and the wear state of the tire at a reference time, and the calculated regression coefficient. [Effects of the Invention]

[0015] According to this disclosure, it is possible to estimate the wear condition of tires mounted on a vehicle without having to acquire a large amount of data for each type of tire in advance. [Brief explanation of the drawing]

[0016] [Figure 1] A schematic diagram showing how a control unit, as a wear state estimation device according to one embodiment, is mounted on a vehicle. [Figure 2] A block diagram showing the electrical configuration of a control unit according to one embodiment. [Figure 3] A diagram showing the relationship between slip ratio and driving force. [Figure 4] A diagram illustrating the principle of wear state estimation. [Figure 5] A graph from an experiment that supports the principle of estimating wear conditions. [Figure 6] An experimental graph supporting the temperature dependence of the slope. [Figure 7] A flowchart showing the process for estimating the wear condition. [Figure 8] A flowchart showing the process for estimating the wear state (continuation of Figure 7). [Figure 9] A flowchart showing the process for estimating the wear state (continuation of Figure 7). [Figure 10A] A graph showing the accuracy of estimating the remaining groove depth based on the examples. [Figure 10B] A graph showing the accuracy of estimating the remaining groove depth based on the examples. [Figure 10C] A graph showing the accuracy of estimating the remaining groove depth based on the examples. [Modes for carrying out the invention]

[0017] Hereinafter, with reference to the drawings, several embodiments of the wear state estimation apparatus, method, and program of the present invention will be described.

[0018] <1. Overview> FIG. 1 is a schematic diagram showing a state in which a control unit 2 as a wear state estimation device according to the present embodiment is mounted on a vehicle 1. The control unit 2 estimates the wear state of the tires mounted on the vehicle 1, particularly the tires to which driving force is applied, based on sensing data acquired during the running of the vehicle 1. Note that the control unit 2 does not necessarily have to be mounted on the vehicle 1, and at least a part of the functions of the control unit 2 described later may be realized by one or a plurality of computers outside the vehicle 1.

[0019] [Vehicle] The vehicle 1 according to the present embodiment is a four-wheel vehicle and includes a left front wheel FL, a right front wheel FR, a left rear wheel RL, and a right rear wheel RR. Tires T FL , T FR , T RL , T RR are mounted on the wheels FL, FR, RL, RR, respectively. The vehicle 1 is a front-engine front-wheel drive vehicle (FF vehicle), and the front-wheel tires T FL , T FR are drive-wheel tires, and the rear-wheel tires T RL , T RR are driven-wheel tires. Therefore, the control unit 2 according to the present embodiment estimates the wear states of the front-wheel tires T FL , T FR respectively.

[0020] [Wheel speed sensor] Wheel speed sensors 6 are respectively attached to the tires T FL , T FR , T RL , T RR (more precisely, the wheels FL, FR, RL, RR) of the vehicle 1, and the wheel speed sensors 6 detect the rotational speeds (i.e., wheel speeds) V1 to V4 of the tires mounted on the wheels to which they are attached. V1 to V4 are respectively the tires T FL , T FR , T RL , T RRThis is the rotational speed. Any wheel speed sensor 6 can be used as long as it can detect the wheel speeds of the wheels FL, FR, RL, and RR while the vehicle is in motion. For example, a sensor that measures the wheel speed from the output signal of an electromagnetic pickup can be used, or a sensor that generates electricity using rotation, such as a dynamo, and measures the wheel speed from the voltage at that time can be used. The mounting position of the wheel speed sensor 6 is not particularly limited and can be appropriately selected depending on the type of sensor, as long as it is possible to detect the wheel speed. The wheel speed sensor 6 is connected to the control unit 2 via a communication line 5. The rotational speed information V1 to V4 detected by the wheel speed sensor 6 is transmitted to the control unit 2 in real time.

[0021] [Torque sensor] Vehicle 1 is equipped with a torque sensor 7 that detects the wheel torque WT of vehicle 1. The structure and mounting position of the torque sensor 7 are not particularly limited, as long as it can detect the wheel torque WT of vehicle 1. The torque sensor 7 is connected to the control unit 2 via a communication line 5. The wheel torque WT information detected by the torque sensor 7 is transmitted to the control unit 2 in real time, along with the rotation speed information V1 to V4.

[0022] [Lateral acceleration sensor] Furthermore, vehicle 1 is equipped with a lateral acceleration sensor 4 that detects the lateral acceleration γ acting on vehicle 1. Lateral acceleration γ is the centrifugal acceleration acting on vehicle 1 toward the outside of the turn when vehicle 1 is turning. The structure and mounting position of the lateral acceleration sensor 4 are not particularly limited, as long as it can detect the lateral acceleration γ. The lateral acceleration sensor 4 is connected to the control unit 2 via a communication line 5. The information on the lateral acceleration γ detected by the lateral acceleration sensor 4 is transmitted to the control unit 2 in real time, along with the information on the rotational speeds V1 to V4 and wheel torque WT.

[0023] [Yaw rate sensor] Vehicle 1 is also equipped with a yaw rate sensor 8 that detects the yaw rate ω of vehicle 1. The yaw rate ω is the angular velocity of rotation around the vertical axis when vehicle 1 is turning. As the yaw rate sensor 8, for example, a sensor that detects the yaw rate using the Coriolis force can be used, but its structure and mounting position are not particularly limited as long as it can detect the yaw rate ω. The yaw rate sensor 8 is connected to the control unit 2 via a communication line 5. The information of the yaw rate ω detected by the yaw rate sensor 8 is transmitted to the control unit 2 in real time, along with the information of the rotational speeds V1 to V4, wheel torque WT, and lateral acceleration γ.

[0024] [Temperature sensor] Vehicle 1 is also equipped with a temperature sensor 9 that detects the temperature outside of Vehicle 1. Any type of temperature sensor 9 can be used as long as it can detect the temperature outside of Vehicle 1, such as a thermistor, semiconductor, or thermocouple. The mounting location of the temperature sensor 9 is not particularly limited, but it is preferable to place it in a location that is less affected by the heat from the engine or exhaust of Vehicle 1. The temperature sensor 9 is connected to the control unit 2 via a communication line 5. The information of the external temperature t detected by the temperature sensor 9 is transmitted to the control unit 2 in real time, along with the information of the rotational speed V1 to V4, wheel torque WT, lateral acceleration γ, and yaw rate ω.

[0025] [Display] Vehicle 1 is equipped with a display unit 3 connected to a control unit 2. The display unit 3 can output various information, including warnings, to the user (primarily the driver), and can be implemented in any form, such as a liquid crystal display element, liquid crystal monitor, plasma display, or organic EL display. The mounting position of the display unit 3 can be selected as appropriate, but it is preferable to install it in a location easily visible to the driver, such as on the instrument panel. If the control unit 2 is connected to a car navigation system, the monitor for the car navigation system can also be used as the display unit 3. When a monitor is used as the display unit 3, warnings can be displayed as icons or text information on the monitor.

[0026] [Input section] Vehicle 1 is further equipped with an input unit 16 (see Figure 2) connected to the control unit 2. The input unit 16 is not particularly limited, but can be implemented in the form of, for example, buttons, a keyboard, or a touch panel display, and accepts input from the user. If the input unit 16 is configured as a touch panel display, the display unit 3 may also serve as the input unit 16. In this embodiment, the input unit 16 mainly accepts input of information regarding the tire's reference time and initialization instructions. These processes will be described later.

[0027] <2. Control Unit> Figure 2 is a block diagram showing the electrical configuration of the control unit 2. In this embodiment, the control unit 2 is a computer mounted on the vehicle 1, and as shown in Figure 2, it includes an I / O interface 11, a CPU 12, a ROM 13, a RAM 14, and a non-volatile, rewritable storage device 15. The I / O interface 11 is a communication device for communicating with external devices such as a wheel speed sensor 6, a torque sensor 7, a lateral acceleration sensor 4, a yaw rate sensor 8, a temperature sensor 9, a display unit 3, and an input unit 16. The ROM 13 stores a program 10 for controlling the operation of various parts of the vehicle 1. The CPU 12 reads and executes the program 10 from the ROM 13, and operates virtually as a rotation speed acquisition unit 21, a driving force acquisition unit 22, a lateral acceleration acquisition unit 23, a turning radius acquisition unit 24, a temperature acquisition unit 25, a slip ratio calculation unit 26, a relationship identification unit 27, a slip ratio correction unit 28, a coefficient calculation unit 29, a coefficient correction unit 30, an estimation unit 31, and an alarm output unit 32. Details of the operation of each part 21 to 32 will be described later. The storage device 15 consists of a hard disk, flash memory, etc. At least a portion of the program 10 may be stored in the storage device 15 instead of the ROM 13. The RAM 14 and storage device 15 are used as appropriate for calculations by the CPU 12.

[0028] <3. Principles of wear state estimation> The control unit 2 controls the tire T based on the principle described below. FL ,T FR Tire wear condition FL ,T FR The remaining groove depth is estimated. The control unit 2 estimates the tire wear state based on regression coefficients that represent the regression curve between the vehicle's slip ratio S and the vehicle's driving force F. The slip ratio S is calculated as (speed of driving wheels - vehicle speed) / vehicle speed, and in this embodiment, the speed of the driven wheels is used as the vehicle speed. That is, the slip ratio S is calculated according to the following equation (1) based on the rotational speeds V1 to V4 of each wheel. In addition, the regression curve between S and F is a regression line represented by the following equation (2) in this embodiment, and the regression coefficients are the slope f1 and the intercept f2. S={(V1+V2)-(V3+V4)} / (V3+V4) (1) S = f1F + f2 (2)

[0029] Furthermore, it is known that when the road surface condition is constant, the relationship between the slip ratio S and the driving force F is as shown in the graph in Figure 3. Under normal driving conditions for vehicle 1, the slip ratio S generally transitions within the range of 0 to Sc. As can be seen from Figure 3, in the region where the slip ratio S is 0 to Sc, it can be said that an approximate linear relationship holds between the slip ratio S and the driving force F, and one of the dominant factors in this approximate linear relationship is the driving stiffness expressed by the following equation (3). Here, w is the contact width of the tire, and k x Let be the shear stiffness per unit area of ​​block BL of the tire tread rubber, and l be the tire's contact length. We assume that block BL is a rectangular parallelepiped. C=wk x l 2 / twenty three)

[0030] Figure 4 is a model diagram in which the tire block BL on the road surface is considered as a cantilever beam. When a shear force Q acts on block BL, the deformation of block BL is δ, the height of block BL is L, the cross-sectional area of ​​block BL is A, the shear modulus of block BL is G, and the cross-sectional shape modulus of block BL is κ. Then the shear stiffness k per unit area is x It can be expressed by the following formula. k x =Q / δ=(GA) / (κL)

[0031] Here, the height of the block BL when the tire is new is L N The height of block BL when worn is L W Assume that A and G are constant when the tire is new and when it is worn. x to k xN , when the tire wears down x to k xW Therefore, k xW It can be expressed by the following equation (4). k xW =(GA) / (κL W) = (GA) / (κL N )×L N / L W =k xN ×L N / L W (4)

[0032] From equation (3), the slope f1 of the slip ratio S with respect to the driving force F is equal to the shear stiffness k per unit area of ​​block BL. x It is thought that the higher the value, the smaller it becomes. Therefore, the slope f1 is the shear stiffness k per unit area. x Assume that it is inversely proportional to the new tire. N If the slope, which was initially , changes to f1 as the tires wear down, then from equation (4), the following holds true. (f1 N -f1)∝1 / k xN -1 / k xW =(1 / k xN )×(L N -L W ) / L N

[0033] Here, (L N -L W If we consider ) as the amount that block BL has worn down due to wear since it was new, and replace it with the wear amount W, the following equation holds true. (f1 N -f1)∝W / (k xN ×L N )

[0034] This equation means that the amount of wear W is proportional to the change in slope f1. N And, assuming that the road surface conditions are the same when calculating the inclination f1, the inclination f1 when new N The amount of wear W can be estimated from the change in the slope f1. Since the amount of wear W corresponds to the difference between the groove depth of a new tire and the remaining groove depth D at the time of calculating the slope f1, the relationship between the slope f1 and the remaining groove depth D can be linearly regressed.

[0035] Figure 5 is a graph of experimental results supporting this. In the graph of Figure 5, the horizontal axis represents the remaining groove depth D (mm), and the vertical axis represents the slope f1. This graph plots numerous datasets of D and f1 obtained for five types of tires Ta to Te mounted on actual vehicles, and a regression line represented by the following equation (5) was calculated for each. Tires Ta to Te include different sizes and tread patterns. The remaining groove depth D was changed by grinding a predetermined amount off the tread portion of tires Ta to Te. As can be seen from the graph, the relationship between the remaining groove depth D and the slope f1 could be represented by a regression line with slope a4 and intercept b4. Therefore, the slope f1 when the tire is new N If the slope a4 of the D-f1 regression line (hereinafter also referred to as "wear sensitivity") can be determined, it is possible to estimate the remaining groove depth D based on the slope f1 at the time of estimation. f1 = a4D + b4(5)

[0036] However, as can be seen from the graph, the above wear sensitivity a4 differs depending on the type of tire. Therefore, the slope f1 N Furthermore, if we attempt to estimate the remaining groove depth D based on the incline f1, we need to identify the wear sensitivity a4 for each type of tire. However, since there are countless types of tires depending on their application, it is not easy to comprehensively identify the wear sensitivity a4 for all of them.

[0037] The inventors, after further investigation, found that when D=0mm, that is, when the tire tread grooves are assumed to be gone or almost gone, the slope f1 converges to approximately 0.02 regardless of the type of tire (Figure 5, circled). In other words, the intercept b4 of the D-f1 regression line can be considered a constant parameter independent of the type of tire. As a result, once one intercept b4 is identified, the wear sensitivity a4 specific to that tire can be first identified based on the intercept b4 and the data of the remaining tread depth D1 and slope f1 at the reference time. Subsequently, based on the wear sensitivity a4 and the slope f1 calculated by the control unit 2, it becomes possible to estimate the remaining tread depth D of the tire at the time the slope f1 was calculated.

[0038] The above-mentioned reference time is any timing at which the remaining tread depth D and inclination f1 of the tire can be obtained, for example, when the tire is first mounted on vehicle 1, or when the tire is rotated. If the tire is new when mounted on vehicle 1, the specified value of the tread depth can be used as the remaining tread depth D1 at the reference time. If the tire is not new, the remaining tread depth D may be determined at the time the tire is mounted on vehicle 1. The remaining tread depth D may also be determined by actual measurement, and the measurement method is not particularly limited, and can be a method using a depth gauge or a laser measuring instrument. Alternatively, for example, the estimated value of the remaining tread depth based on an image of the tire tread may be used as the remaining tread depth D.

[0039] Based on the above findings, the control unit 2 stores the parameter b4 that has been previously identified through experimentation or simulation. Then, the control unit 2 calculates the wear sensitivity a4 of the tire based on the (D1, f1) data at a reference time for the tire whose wear state is to be estimated and the following equation (6). a4 = (f1 - b4) / D1 (6)

[0040] This allows us to identify the D-f1 regression line specific to each tire. From here on, it becomes possible to estimate the remaining tread depth D of the tire based on the slope f1 obtained while vehicle 1 is running, and the regression coefficients a4 and b4. According to the above principle, the wear state can be easily estimated simply by obtaining the remaining tread depth D1 at the time the tire is mounted on vehicle 1. Similarly, even if the mounted tire is not new and the remaining tread depth D and slope f1 for when it was new cannot be obtained, it is still possible to estimate the remaining tread depth D. Furthermore, according to this principle, the wear state can be estimated for each individual tire. That is, even if the remaining tread depth D1 of each tire at the reference time is different, the wear state can be estimated without any problems.

[0041] <4. Temperature compensation for slope> By the way, the shear stiffness k per unit area included in driving stiffness C x It is known that this is affected by ambient temperature. More specifically, the shear stiffness k per unit area x The slope f1 decreases as the temperature increases and increases as the temperature decreases. Therefore, even if the road surface conditions and tire wear conditions are the same, it is expected that the slope f1 will increase as the temperature increases and decrease as the temperature decreases.

[0042] Figure 6 is a graph showing the results of an experiment confirming the temperature dependence of the slope f1. The graph in Figure 6 plots datasets of external temperature t and slope f1 obtained by mounting new summer tires, studless tires, and all-season tires on vehicles, respectively. The horizontal axis represents temperature t (°C), and the vertical axis represents slope f1. Each dataset was obtained under the same road surface conditions. The results in Figure 6 show that for all types of tires, the slope f1 tends to increase as the temperature t increases and decrease as the temperature t decreases.

[0043] Therefore, in this embodiment, temperature correction of the slope f1 is performed according to the following equation (7). Here, t1 is the reference temperature (°C), and the coefficient a3 is an index representing the degree to which the slope f1 depends on temperature t. The coefficient a3 can be determined by performing regression analysis on a large number of data sets of temperature t and slope f1 acquired while the vehicle 1 is running, provided that the reference temperature t1 is determined. Alternatively, the coefficient a3 may be predetermined by experiment and simulation as a parameter independent of the tire type. Furthermore, even if the reference temperature t1 is not specifically defined, it is possible to cancel the effect of temperature on the slope f1 by performing regression analysis on a large number of data sets of temperature t and slope f1 and identifying the regression line. f1 = f1 - a3 × (t - t1) (7)

[0044] <5. Wear state estimation process> The wear state estimation process performed by the control unit 2 will be described below with reference to Figures 7-9. This estimation process may be performed repeatedly, for example, while power is supplied to the electrical system of vehicle 1, or each time vehicle 1 travels a predetermined distance, or at predetermined time intervals. The parameter b4 for estimating the tire wear state is assumed to be predetermined and stored in the storage device 15 or ROM 13 of the control unit 2.

[0045] [Process for obtaining remaining groove depth] As described above, in this embodiment, the drive wheel tire T FL and T FR The wear condition is estimated for each of these. As preparation for this, the tire T when the tire is mounted on the FL wheel of vehicle 1. FL The remaining groove depth D of the tire T is obtained and input by the user to the control unit 2 via the input unit 16. The control unit 2 controls the tire T FL When the remaining groove depth D is input, this is converted to tire T FLThe remaining tread depth D1 at the reference time is stored in the storage device 15. The remaining tread depth D is obtained, for example, by measuring the depth of the main grooves in the tire tread. Alternatively, for example, when the tire is new, the manufacturing value of the tire's tread depth can be used as the remaining tread depth D. Once the remaining tread depth D1 at the reference time has been stored in the storage device 15, it is not necessary to perform the same preparations again until the tire is replaced or rotated.

[0046] When changing or rotating tires, the user can reset the previously saved remaining tread depth D1, perform the same preparation for the tire to be mounted on the new FL wheel, and overwrite and save the new remaining tread depth D1. This process is called "initialization." The above applies to tire T FL I explained using the tire T as an example, FR The same applies to the remaining tread depth D1 is obtained for each tire whose wear condition is to be estimated and stored in the memory device 15. Then, when vehicle 1 starts driving, the following process begins.

[0047] [Data acquisition process] In step S1, the rotation speed acquisition unit 21 acquires the rotation speed of the tire T during travel. FL ,T FR ,T RL ,T RR The rotational speeds V1 to V4 are acquired. The rotational speed acquisition unit 21 receives the output signal from the wheel speed sensor 6 at a predetermined sampling period and converts it into rotational speeds V1 to V4.

[0048] In step S2, the drive force acquisition unit 22 acquires the wheel torque WT of the vehicle 1. The drive force acquisition unit 22 receives the output signal from the torque sensor 7 at a predetermined sampling period and converts it into wheel torque WT.

[0049] In step S3, the lateral acceleration acquisition unit 23 acquires the lateral acceleration γ applied to the vehicle 1. The lateral acceleration acquisition unit 23 receives the output signal from the lateral acceleration sensor 4 at a predetermined sampling period and converts it into the lateral acceleration γ.

[0050] In step S4, the turning radius acquisition unit 24 acquires the yaw rate ω of the vehicle 1. The turning radius acquisition unit 24 receives the output signal from the yaw rate sensor 8 at a predetermined sampling period and converts it to the yaw rate ω. The turning radius acquisition unit 24 acquires the turning radius R of the vehicle 1 by dividing the vehicle speed by the yaw rate ω. Since the vehicle speed can be approximated by the speed of the driven wheels, in this embodiment, for example, it can also be calculated as R = (V3 + V4) / 2ω.

[0051] In step S5, the temperature acquisition unit 25 acquires the external temperature t of the vehicle 1. The temperature acquisition unit 25 receives the output signal from the temperature sensor 9 at a predetermined sampling period and converts it into a temperature t.

[0052] The rotational speeds V1 to V4, wheel torque WT, lateral acceleration γ, yaw rate ω, turning radius R, and temperature t acquired in the sequentially executed steps S1 to S5 are treated as a dataset acquired at the same or approximately the same time and stored in RAM 14 or storage device 15.

[0053] In step S6, the coefficient calculation unit 29 determines whether the data acquired in steps S1 to S5 is valid. This determination checks, for example, whether the absolute values ​​of the wheel torque WT and turning radius R data exceed a predetermined threshold, whether the data is from when the vehicle 1 was braking, or whether the data is from when the vehicle was driving at low speed. Abnormal values, data from when the vehicle was braking, and data from when the vehicle was driving at low speed can affect the accuracy of the subsequent calculation of the inclination f1, and consequently reduce the accuracy of the wear state estimation. Therefore, if such data exists (in the case of NO), step S22 is executed, and the coefficient calculation unit 29 rejects the data acquired in steps S1 to S5. After that, steps S1 to S5 are executed again, and new data is acquired sequentially. On the other hand, if the data is determined to be valid in step S6 (in the case of YES), this data is stored in the RAM 14 or the storage device 15.

[0054] [Slip ratio and driving force calculation process] In the next step S7, the driving force acquisition unit 22 sequentially calculates the driving force F of the vehicle 1 from the wheel torque WT converted in step S2. The driving force F is calculated, for example, by multiplying the wheel torque WT by the tire torque T FL ,T FR ,T RL ,T RR It can be calculated by dividing by the radius.

[0055] In the next step S8, the slip ratio calculation unit 26 sequentially calculates the slip ratio S according to the above equation (1) based on the sequentially acquired rotational speeds V1 to V4.

[0056] In step S9, the coefficient calculation unit 29 determines whether a predetermined number N or more of data sets of driving force F and slip ratio S based on valid data have been stored in the RAM 14 or storage device 15. N is the number of data sets necessary to effectively perform the regression represented by equation (2) above, and can be determined as appropriate. If it is determined that N or more data sets of (F,S) have been stored (YES), then step S10 is executed. On the other hand, if it is determined that there are fewer than N data sets of (F,S) (NO), then steps S1 to S9 are executed again.

[0057] In step S10, the coefficient calculation unit 29 performs filtering on the data set of the driving force F calculated in step S7 and the slip ratio S calculated in step S8 to remove measurement errors. For this filtering, known methods for removing noise and smoothing can be used.

[0058] In step S11, the slip ratio correction unit 28 determines whether relational information for correcting the slip ratio S has already been identified. More specifically, the relational information includes first relational information for canceling the effect caused by the difference in trajectory between the left and right sides of the vehicle body during a turn, and second relational information for canceling the effect caused by the load transfer between the left and right sides of the vehicle body during a turn. The first relational information consists of the coefficients a1, b1, and c1 in the following equation (8), which expresses the slip ratio S as a quadratic function of the reciprocal of the turning radius R. The second relational information consists of the coefficients a2, b2, c2, and f2 in the following equation (9), which represents the relationship between lateral acceleration γ, driving force F, and slip ratio S. S=a1(1 / R) 2 +b1(1 / R)+c1(8) S = f1F + f2 = (a2γ) 2 (b2γ+c2)F+f2 (9)

[0059] Furthermore, since the correction of the slip ratio S based on the above-mentioned first and second related information is disclosed in the applicant's prior applications, Japanese Patent Publication No. 2021-109540 and Japanese Patent Publication No. 2021-109542, a detailed explanation is omitted here.

[0060] If, in step S11, it is determined that the relational information has already been identified and that the coefficients a1, b1, and c1, as well as a2, b2, c2, and f2, are stored in RAM 14 or storage device 15 (YES), then step S12 in Figure 8 is executed. On the other hand, if it is determined that the relational information has not yet been identified (NO), the relational information identification process in Figure 9 (steps S30 to S31) is executed. Once the relational information is identified, steps S1 to S11 are executed again, followed by step S12.

[0061] [Relevant Information Identification Process] The following describes the relationship information identification process (steps S30 to S31) that follows step S11 in Figure 7. In the relationship information identification process, first relationship information for calculating the slip ratio S in which the effect of the turning radius R is canceled in step S12 and second relationship information for calculating the slip ratio S in which the effect of lateral acceleration is canceled in step S13 are identified.

[0062] In step S30 of Figure 9, the relationship identification unit 27 identifies the coefficients a1, b1, and c1 in equation (8). The coefficients a1, b1, and c1 can be calculated based on a large dataset of the turning radius R calculated in step S4 and the slip ratio S filtered in step S10, for example, by a method such as the least squares method. Alternatively, the relationship identification unit 27 may consider the coefficient b1 in equation (8) to be 0 and identify only the coefficients a1 and c1. The relationship identification unit 27 stores the identified coefficients a1, b1, and c1 as first relationship information in the RAM 14 or storage device 15.

[0063] In the subsequent step S31, the relationship identification unit 27 identifies the coefficients a2, b2, c2, and f2 in equation (9). The coefficients a2, b2, c2, and f2 can be calculated based on a large dataset of the lateral acceleration γ converted in step S3 and the slip ratio S and driving force F filtered in step S10, for example, by a method such as the least squares method. The relationship identification unit 27 stores the identified a2, b2, c2, and f2 as second relationship information in the RAM 14 or storage device 15.

[0064] Once steps S30 and S31 are completed, steps S1 to S11 are executed again. After the relationship information has been identified through the relationship information identification process described above, step S11 is followed by step S12.

[0065] [Slip ratio correction process] In step S12, the slip ratio correction unit 28 corrects the slip ratio S calculated in step S8 based on R obtained in step S4 and the first relationship information already identified. The slip ratio correction unit 28 corrects the slip ratio S by subtracting from the slip ratio S a value obtained by multiplying the square of the reciprocal of the turning radius R at the time of correction by a coefficient a1, according to the following formula. S = S - a1(1 / R) 2 Alternatively, the slip ratio S may be corrected by further subtracting the value obtained by multiplying the reciprocal of the turning radius R during correction by the coefficient b1 from the slip ratio S using the following formula. S = S - a1(1 / R) 2 -b1(1 / R)

[0066] According to the correction formula above, it is possible to calculate the slip ratio S when (1 / R) = 0, that is, when converted to the condition of straight-line driving, and the effects of trajectory differences due to left and right turns are canceled out from the slip ratio S.

[0067] In step S13, the slip ratio correction unit 28 further corrects the slip ratio S corrected in step S12 based on the lateral acceleration γ acquired in step S3, the driving force F calculated in step S7, and the already identified second relationship information. The slip ratio correction unit 28 calculates the sum of the value obtained by multiplying the square of the lateral acceleration γ at the time of correction by the coefficient a2, the value obtained by multiplying the lateral acceleration γ at the time of correction by the coefficient b2, and c2 according to the following formula, calculates the product of this sum and the driving force F at the time of correction, and further corrects the slip ratio S by subtracting this product from the slip ratio S acquired in step S12. S=S-f1F=S-(a2γ 2 (+b2γ+c2)F

[0068] Since b2 is also approximately 0, the slip ratio S may be corrected according to the following formula. S=S-(a2γ 2 +c2)F

[0069] According to the correction formula above, the slip ratio S converted to the straight-line driving state can be calculated, and the effects of lateral load transfer due to left and right turns are canceled out from the slip ratio S.

[0070] [Slope calculation process] In step S14, the coefficient calculation unit 29 calculates the slope f1, which is a regression coefficient representing the linear relationship between the slip ratio S and the driving force F, based on multiple datasets of the slip ratio S corrected in steps S12 and S13 and the driving force F calculated in step S7. The regression coefficient f1 can be calculated by, for example, the least squares method. In this case, the regression coefficient f1 may be calculated sequentially based on a large number of datasets of the slip ratio S and the driving force F, or it may be calculated by batch processing. In this embodiment, the sequential least squares method is used as a preferred example.

[0071] [Tilt correction process] In step S15, the coefficient correction unit 30 corrects the slope f1 calculated in step S14 based on the temperature t obtained in step S5 and the above equation (7). As a result, the effect of temperature t is canceled out from the slope f1 calculated in step S14, and it is converted to the slope f1 obtained under the conditions of a reference temperature t1.

[0072] [Road surface judgment process] In step S16, the coefficient correction unit 30 determines whether the slope f1 corrected in step S15 is based on data acquired while driving on a dry road surface (dry asphalt). The method of determination is not particularly limited, and a known road surface condition determination method can be adopted. Alternatively, the variance of multiple slope f1 corrected in step S15 can be calculated, and if the variance is greater than a predetermined value, it can be determined that the road surface is not dry, and if the variance is less than or equal to the predetermined value, it can be determined that the road surface is dry. This is because the variance of slope f1 is significantly larger on roads that are not dry compared to dry roads. The variance of slope f1 can be calculated, for example, by storing multiple data of slope f1 calculated in step S15 over a certain period of time, or a predetermined number of slope f1 data calculated in step S15, in the RAM 14 or storage device 15. If it is determined in step S16 that the slope f1 was not calculated based on data while driving on a dry road surface (NO), step S22 in Figure 7 is executed. In other words, the coefficient correction unit 30 rejects the previous data, and steps S1 to S16 are executed again. On the other hand, when it is determined that the slope f1 was calculated based on data obtained while driving on a dry road surface (YES), step S17 is executed.

[0073] [Reference Time Data Determination Process] In step S17, the estimation unit 31 determines whether the wear sensitivity a4 for the tire whose wear state is to be estimated has already been identified and stored in the memory device 15. If it is determined that the wear sensitivity a4 has already been stored (YES), the next step S19 is executed for the inclination f1 that was not rejected in the most recent step S16.

[0074] On the other hand, if it is determined that the above wear sensitivity a4 is not stored (NO), step S18 is executed. In step S18, the estimation unit 31 determines that the inclination f1 that was not rejected in the most recent step S16 is the inclination f1 at the reference time. Then, the tire T is stored in the memory device 15. FL and T FRThe remaining groove depth D1 and parameter b4 for each are read from the storage device 15, and the wear sensitivity a4 is calculated according to the above formula (6). The estimation unit 31 stores the wear sensitivity a4 calculated here in the storage device 15. After that, steps S1 to S17 are further executed. In step S18, if there are multiple applicable slopes f1 (for example, if the slopes f1 are calculated sequentially), the average value or weighted average value of these may be used as the slope f1 at the reference time, or the latest slope f1 may be used as the slope f1 at the reference time.

[0075] [Wear State Estimation Process] In step S19, the estimation unit 31 estimates the current (at the time of calculation of the inclination f1) remaining tread depth D of the tire based on the inclination f1 that was not rejected in step S16. The remaining tread depth D is calculated according to the following equation (10). If there are multiple applicable inclinations f1 in step S19, for example, the average value or weighted average value of these values ​​may be substituted into f1 in equation (10), or the latest inclination f1 may be substituted into f1 in equation (10). Alternatively, the average value, weighted average value, maximum value, or minimum value of multiple remaining tread depths D calculated by substituting multiple inclinations f1 into equation (10) may be used as the estimated remaining tread depth D. D=(f1-b4) / a4

[0076] In step S20, the estimation unit 31 determines whether the remaining groove depth D estimated in step S19 is greater than or equal to a threshold for determining that the tire is worn. This threshold can be predetermined as a threshold for prompting the user to replace or rotate the tires, and can be stored in the storage device 15 or ROM 13. If it is determined that the remaining groove depth D estimated in step S19 is greater than or equal to the threshold for all tires (YES), the series of wear estimation processes is terminated. After this, steps S1 to S9 may be executed again. On the other hand, if there is even one tire where the remaining groove depth D estimated in step S19 is determined to be less than the threshold (NO), the next step S21 is executed.

[0077] In step S21, the alarm output unit 32 generates an alarm notifying the driver that a worn tire is present and outputs it via the display unit 3. For example, the alarm output unit 32 displays an alarm on the display unit 3 to the driver indicating that a tire is worn and needs to be replaced or rotated. The alarm may prompt either replacement or rotation, for example, depending on the estimated remaining tread depth D. Alternatively, the alarm may be generated and output in a manner that identifies the tire that is estimated to be worn. In addition to or instead of this, the alarm may be output in the form of an audible message via a speaker or the like mounted on the vehicle 1.

[0078] In addition, the warning output unit 32 may pass information on which tires are worn to various control processes running on the control unit 2. Examples of such controls include brake control and distance control during vehicle operation. This completes the wear estimation process.

[0079] <6. Variation> Although one embodiment of the present invention has been described above, the present invention is not limited to the above embodiment, and various modifications are possible without departing from the spirit of the invention. For example, the following modifications are possible. Furthermore, the gist of the following modifications can be combined as appropriate.

[0080] (1) The wear state estimation process according to the above embodiment can be applied to rear-wheel drive vehicles as well as four-wheel drive vehicles. Furthermore, this function is not limited to four-wheel vehicles, but can be applied as appropriate to three-wheel vehicles, six-wheel vehicles, etc.

[0081] (2) The method for obtaining the lateral acceleration γ of the vehicle 1 is not limited to that described in the above embodiment. For example, the lateral acceleration γ can also be obtained from the yaw rate ω and rotational speeds V1 to V4 information from the yaw rate sensor 8. Furthermore, the method for calculating the vehicle speed used in the calculation of the slip ratio S is not limited to the method for calculating based on the rotational speed of the driven wheel tires. For example, the vehicle speed may be calculated by a method that calculates it by integrating the vehicle acceleration α, or by a method that calculates it based on the positioning signal of a satellite positioning system such as GPS (global positioning system). The vehicle acceleration α can be obtained, for example, by attaching an acceleration sensor to the vehicle 1 and converting its output signal.

[0082] (3) The method for obtaining the driving force F is not limited to those described in the above embodiment. For example, the vehicle acceleration α may be obtained from the signal of the acceleration sensor, and the driving force F may be obtained by multiplying this by the mass of the vehicle 1. Alternatively, the driving force F can be derived from the engine torque and engine speed obtained from the control device of the engine of the vehicle 1, or from the rotational speeds V1 to V4 of the tires.

[0083] (4) At least one of the slip ratio S correction and the temperature correction of the slope f1 may be omitted. That is, any or all of steps S11, S12, S13, S15, S30, and S31 may be omitted. Accordingly, the relational information in the above embodiment may refer to only one of the first relational information and the second relational information. In addition, in the above embodiment, the relational information was specified each time the vehicle was driven, but the relational information may be derived in advance and referred to when correcting the slip ratio S.

[0084] (5) In addition, the slip ratio S can be calculated not by averaging the rotational speeds between the left and right wheels as in the above embodiment, but by using only the rotational speeds V1 and V3 of the left wheel, or only the rotational speeds V2 and V4 of the right wheel, as shown below. Note that the following formula assumes that the vehicle is front-wheel drive, as in the above embodiment. S = (V1 - V3) / V3 S = (V2 - V4) / V4

[0085] (6) In addition to or instead of the method of the above embodiment, the method of Japanese Patent Application Publication No. 2021-109540, already proposed by the applicant, may be used as a method for correcting the slip ratio S in accordance with the lateral acceleration γ.

[0086] (7) At least one of the parameters b4 and coefficient a3, and the groove depth D1 at the reference time may be stored in the storage device of a computer that is communicatively connected to the control unit 2, rather than in the control unit 2, and may be read by the control unit 2 as needed. In other words, these data do not have to be stored in the control unit 2, and the control unit 2 may be configured to access these data via network communication. In this case, the user does not need to input the groove depth D1 at the reference time into the control unit 2.

[0087] (8) In the above embodiment, the control unit 2 calculated the wear sensitivity a4 when it determined that the wear sensitivity a4 had not been specified. In addition to this, or instead, the control unit 2 may be configured to calculate the wear sensitivity a4 when it receives an initialization instruction from the user.

[0088] (9) Although the control unit 2 in the above embodiment was mounted on the vehicle 1, the control unit 2 may be configured to include one or more computers outside the vehicle 1. The one or more external computers may be able to communicate with the control device mounted on the vehicle 1 and at least one of the wheel speed sensor 6, torque sensor 7, yaw rate sensor 8, and temperature sensor 9, and may be configured to implement at least some of the functions of each of the parts 21 to 32. That is, at least some of the steps S1 to S22, and steps S30 and S31 of the above embodiment may be performed by one or more computers outside the vehicle 1. Therefore, the remaining groove depth D1 and parameter b4, etc., may be stored in a computer outside the vehicle 1. Furthermore, the input unit 16 and the display unit 3 are not limited to those installed on the vehicle 1, but may be installed in, for example, one or more external computers as described above. [Examples]

[0089] The following describes an example of the wear state estimation device according to the above embodiment. The example described below is merely one example, and this disclosure is not limited to the following example. <Experiment> This study estimated the tire wear on the front wheel (FL) and rear wheel (FR) of a front-wheel-drive (FF) vehicle and compared it with the actual measured remaining tread depth. The experiment was conducted with 12 different types of tires, including summer tires, studless tires, all-season tires, and tires of different sizes. For each of the 12 types of tires, two samples were prepared in new condition, with 2mm of tread wear (2mm worn), and with 4mm of tread wear (4mm worn). These samples were mounted on both the FL and FR wheels. In other words, the study recreated the conditions of new tires, tires with 2mm of wear, and tires with 4mm of wear. The reference condition was the same for both the FL and FR wheel tires.

[0090] The vehicle was actually driven, and the remaining tread depth of the tires was estimated as they gradually wore down from each reference point using the wear state estimation method according to the above embodiment. In this experiment, the slip ratio S was corrected based on the relationship between the turning radius R and the slip ratio S, and the slope f1 was corrected based on the relationship between the external temperature t and the slope f1. The remaining tread depth was measured using a depth gauge.

[0091] <Result> Figures 10A to 10C show graphs comparing estimated and measured tread depths. Figure 10A is a graph of experimental results with the measured value (mm) of remaining tread depth on the horizontal axis and the estimated value (mm) on the vertical axis when the tire was new. Figure 10B is a graph of experimental results with the measured value (mm) of remaining tread depth on the horizontal axis and the estimated value (mm) on the vertical axis when the tire was worn down to 2mm. Figure 10C is a graph of experimental results with the measured value (mm) of remaining tread depth on the horizontal axis and the estimated value (mm) on the vertical axis when the tire was worn down to 4mm. As can be seen from the graphs in Figures 10A to 10C, it was confirmed that the remaining tread depth can be estimated within the range of -2mm to +2mm regardless of the tire's wear state at the reference point. [Explanation of Symbols]

[0092] 1 vehicle 2. Control Unit (Wear State Estimation Device) 3 Display 4. Lateral acceleration sensor 6. Wheel speed sensor 7 Torque sensor 8. Yaw rate sensor 9. Temperature sensor 21 Rotation speed acquisition unit 22 Driving force acquisition unit 23 Lateral acceleration acquisition section 24. Turning radius acquisition unit 25 Temperature acquisition section 26 Slip Ratio Calculation Unit 27 Related Specific Departments 28 Slip ratio correction section 29 Coefficient Calculation Unit 30 Coefficient Correction Section 31 Estimation part 32 Alarm output section FL left front wheel FR right front wheel RL Left rear wheel RR Right rear wheel V1~V4 Tire rotation speed b4 Constants (parameters) independent of tire type

Claims

1. A rotation speed acquisition unit that sequentially acquires the rotation speed of the tires mounted on the vehicle, A driving force acquisition unit that sequentially acquires the driving force of the aforementioned vehicle, A slip ratio calculation unit calculates the slip ratio based on the sequentially acquired tire rotation speeds, A coefficient calculation unit calculates a regression coefficient representing the relationship between the slip ratio and the driving force based on a plurality of data sets of the slip ratio and the driving force, An estimation unit that estimates the wear state of the tire at the time of calculation of the regression coefficient, based on a predetermined constant, the regression coefficient and the wear state of the tire at a reference time, and the calculated regression coefficient. Equipped with, The aforementioned constant represents the regression coefficient assuming that the tread grooves of the tire have disappeared or are almost completely gone. A device for estimating the wear condition of tires.

2. The aforementioned constant is independent of the type of tire. The wear state estimation device according to claim 1.

3. The aforementioned reference time is when the tire is mounted on the vehicle or when the tire is rotated. The wear state estimation device according to claim 1 or 2.

4. The coefficient calculation unit calculates the regression coefficient based on a plurality of filtered data sets of the slip ratio and the driving force. The wear state estimation device according to claim 1 or 2.

5. A temperature acquisition unit that acquires the temperature outside the vehicle, A coefficient correction unit corrects the regression coefficient based on the acquired temperature. Furthermore, The wear state estimation device according to claim 1 or 2.

6. A turning radius acquisition unit that acquires the turning radius of the vehicle, A slip ratio correction unit that corrects the slip ratio based on relationship information representing the relationship between the turning radius and the slip ratio, and the acquired turning radius. Furthermore, The wear state estimation device according to claim 1 or 2.

7. The aforementioned relationship information is information that expresses the slip ratio as a quadratic function of the reciprocal of the turning radius. The wear state estimation device according to claim 6.

8. The rotational speed of the tires mounted on the vehicle is acquired sequentially, The driving force of the aforementioned vehicle is acquired sequentially, Based on the sequentially acquired tire rotation speeds, the slip ratio is calculated, Based on multiple datasets of the slip ratio and the driving force, a regression coefficient representing the relationship between the slip ratio and the driving force is calculated. Based on a predetermined constant, the regression coefficient and tire wear state at a reference time for the tire, and the calculated regression coefficient, the wear state of the tire at the time of calculation of the regression coefficient is estimated. Includes, The aforementioned constant represents the regression coefficient assuming that the tread grooves of the tire have disappeared or are almost completely gone. A method for estimating the wear condition of tires.

9. The rotational speed of the tires mounted on the vehicle is acquired sequentially, The driving force of the aforementioned vehicle is acquired sequentially, Based on the sequentially acquired tire rotation speeds, the slip ratio is calculated, Based on multiple datasets of the slip ratio and the driving force, a regression coefficient representing the relationship between the slip ratio and the driving force is calculated. Based on a predetermined constant, the regression coefficient and tire wear state at a reference time for the tire, and the calculated regression coefficient, the wear state of the tire at the time of calculation of the regression coefficient is estimated. Have the computer run it, The aforementioned constant represents the regression coefficient assuming that the tread grooves of the tire have disappeared or are almost completely gone. A program for estimating tire wear.

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