Tire load prediction system, tire load prediction program, and tire load prediction method

Abstract

The present invention comprises: a sensor unit (SU) having a strain sensor (SN) for detecting tire strain; a strain data acquisition unit (202) for acquiring tire tangential strain data; a linear transformation unit (251) for performing linear transformation on the strain data; a first estimation unit (252) for estimating tire tangential velocity and angular velocity based on the transformation result; a second estimation unit (253) for estimating tire radial velocity based on the values ​​of tire tangential velocity and angular velocity; a third estimation unit (254) for estimating tire velocity in the θ angular direction based on the values ​​of tire tangential acceleration and angular velocity; a fourth estimation unit (255) for estimating tire deflection based on tire tangential velocity and angular velocity, tire radial velocity, and tire velocity in the θ angular direction; and a load prediction unit (256) for predicting a load applied to the tire based on the tire deflection.

Description

Technical Field

[0001] The present invention relates to a tire load prediction system, a tire load prediction program, and a tire load prediction method for predicting the load of a pneumatic tire. Background Art

[0002] Conventionally, a technology has been proposed that uses the time-series waveform of an acceleration sensor installed in a pneumatic tire (hereinafter referred to as a tire) to calculate the tire's contact time ratio (CTR; a parameter indicating the contact length) and estimate the tire load based on this contact time ratio (Patent Document 1).

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Laid-Open No. 2017-161477 Summary of the Invention

[0006] However, in the conventional technology, the contact length of the tire varies depending on the wear state of the tire, and therefore there is a problem in that the error in load prediction is large.

[0007] Furthermore, acceleration sensors have the following disadvantages: since centrifugal force is small in the low-speed range, it is difficult to make predictions for vehicles that mainly travel at low speeds.

[0008] Therefore, the present invention has been made in view of the above-mentioned problems, and an object thereof is to provide a tire load prediction system, a tire load prediction program, and a tire load prediction method that can improve load prediction accuracy and perform load prediction even for vehicles that mainly travel at low speeds.

[0009] A tire load prediction system according to one embodiment of the present invention is gist of the system, comprising: a sensor unit disposed within a tire and having a strain sensor for detecting tire strain; a strain data acquisition unit for acquiring tire tangential strain data output from the sensor unit; a linear transformation unit for performing a linear transformation on the acquired strain data; a first estimation unit for estimating tire tangential velocity and angular velocity based on the transformation result of the linear transformation unit; a second estimation unit for estimating tire radial velocity based on the estimated tire tangential velocity and angular velocity; a third estimation unit for estimating velocity in an angular direction θ, which corresponds to an angle of the strain sensor relative to a contact patch of the tire, based on the estimated tire tangential acceleration and angular velocity; a fourth estimation unit for estimating tire deflection based on the tire tangential velocity and angular velocity, the tire radial velocity, and the velocity in the angular direction θ; and a load prediction unit for predicting a load applied to the tire based on the estimated tire deflection.

[0010] According to such a configuration, the accuracy of load prediction can be improved.

[0011] Furthermore, the fourth estimating unit may estimate the deformation profile of the tire based on the tire tangential velocity, the tire radial velocity, and the velocity in the θ-angle direction, and extract a feature value corresponding to the tire deflection to estimate the tire deflection.

[0012] This can further improve the accuracy of load prediction.

[0013] In addition, the linear transformation unit may perform linear transformation on the strain data using the following formula:

[0014] [Number 1]

[0015] ω(t)=ω0(a1ε(t)+1)

[0016] Here, ω0 is the average angular velocity, a1 is the angular velocity magnification, and ε is the strain. This allows for more accurate load prediction.

[0017] Alternatively, the first estimating unit may estimate the tangential velocity by performing a linear transformation on the acquired data using the following formula:

[0018] [Number 3]

[0019] v T (t) = v T0 (a2ε(t)+1)

[0020] Among them, v T0is the average tangential velocity, and a2 is the tangential velocity multiplier.

[0021] A tire load prediction program according to another embodiment of the present invention is gist of being executed by a CPU included in a tire load prediction system, the program comprising the following steps: a strain data acquisition step of acquiring tire tangential strain data output from a strain sensor disposed on the inner surface or interior of the tire; a linear transformation step of performing a linear transformation on the acquired strain data; a first estimation step of estimating the tire tangential velocity and angular velocity based on the transformation result; a second estimation step of estimating the tire radial velocity based on the estimated tire tangential velocity and angular velocity; a third estimation step of estimating the velocity in the angular direction θ, which corresponds to the angle of the strain sensor relative to the tire's contact patch, based on the estimated tire tangential acceleration and angular velocity; a fourth estimation step of estimating the tire deflection based on the tire tangential velocity and angular velocity, the tire radial velocity, and the velocity in the angular direction θ; and a load prediction step of predicting the load applied to the tire based on the estimated tire deflection.

[0022] This can improve the accuracy of load prediction.

[0023] Furthermore, in the fourth estimating step, the deformation profile of the tire may be estimated based on the tire tangential velocity, the tire radial velocity, and the velocity in the θ-angle direction, and the tire deflection may be estimated by extracting a feature value corresponding to the deflection of the tire.

[0024] This can further improve the accuracy of load prediction.

[0025] The gist of the tire load prediction method involved in other embodiments of the present invention is that it includes the following processes: a strain data acquisition process, which acquires tire tangential strain data output from a strain sensor arranged on the inner surface or inside of the tire; a linear transformation process, which performs linear transformation on the acquired strain data; a first estimation process, which estimates the tire tangential speed and angular velocity based on the transformation result; a second estimation process, which estimates the tire radial speed based on the estimated tire tangential speed and angular velocity values; a third estimation process, which estimates the speed in the angular direction θ corresponding to the angle of the strain sensor relative to the contact surface of the tire based on the estimated tire tangential acceleration and angular velocity values; a fourth estimation process, which estimates the deflection of the tire based on the tire tangential speed and angular velocity, the tire radial speed, and the speed in the angular direction θ; and a load prediction process, which predicts the load applied to the tire based on the estimated tire deflection.

[0026] This can improve the accuracy of load prediction.

[0027] Furthermore, in the fourth estimation process, the deformation profile of the tire may be estimated based on the tire tangential velocity, the tire radial velocity, and the velocity in the θ-angle direction, and the tire deflection may be estimated by extracting a feature value corresponding to the deflection of the tire.

[0028] This can further improve the accuracy of load prediction.

[0029] According to the present embodiment, it is possible to provide a tire load prediction system, a tire load prediction program, and a tire load prediction method that can improve load prediction accuracy and perform load prediction even for a vehicle that mainly travels at low speeds. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 1 is a schematic configuration diagram showing a schematic configuration of a tire load prediction system according to an embodiment.

[0031] Figure 2 : is a functional block diagram showing the functional configuration of the tire load prediction system according to the embodiment.

[0032] Figure 3 (a) to (d) are explanatory diagrams showing the definition of a coordinate system used in the description of the tire load prediction system according to the embodiment.

[0033] Figure 4 This is a flowchart showing the processing procedure of a tire load prediction process executed in the tire load prediction system according to the embodiment.

[0034] Figure 5 is a graph showing the relationship between tangential strain and time.

[0035] Figure 6 is a graph showing the relationship between angular velocity and time.

[0036] Figure 7 is a graph showing the relationship between tangential velocity and time.

[0037] Figure 8 These are explanatory diagrams (a) to (c) used in explaining the principle of estimating the tangential velocity.

[0038] Figure 9 is a graph showing the relationship between sensor angle and time.

[0039] Figure 10 is a graph showing the relationship between X-coordinate velocity and time.

[0040] Figure 11is a graph showing the relationship between Z-coordinate velocity and time.

[0041] Figure 12 is a graph showing the relationship between X-coordinate displacement and time.

[0042] Figure 13 is a graph showing the relationship between Z-coordinate displacement and time.

[0043] Figure 14 It is a graph showing the state of estimated tire deflection.

[0044] Figure 15 is a graph showing the relationship between the estimated value of the deflection rate of the tire and the load. DETAILED DESCRIPTION

[0045] Reference Figure 1 and Figure 2 A tire load prediction system S1 according to an embodiment of the present invention will be described.

[0046] In the following description of the drawings, the same or similar parts are denoted by the same or similar reference numerals. However, it should be noted that the drawings are schematic and the ratios of the dimensions and the like may differ from the actual ones.

[0047] Therefore, specific dimensions and the like should be determined in consideration of the following description. Furthermore, the drawings may also include portions where the relationship and ratio of dimensions differ from one another.

[0048] (Overview of the Tire Load Prediction System)

[0049] Reference Figure 1 The schematic configuration of the tire load prediction system S1 according to the embodiment will be described with reference to the schematic configuration diagram of FIG.

[0050] Here, the tire load prediction system S1 according to this embodiment uses a strain sensor SN instead of a conventional acceleration sensor and follows the following algorithm (details will be described later): it estimates the tire profile and deflection based on data on one axis (circumferential direction) and predicts the load.

[0051] The tire load prediction system S1 is composed of a sensor unit SU provided on the pneumatic tire (hereinafter simply referred to as tire) 10 and a processing device (vehicle-mounted unit (ECU) etc.) 200 that processes information acquired from the sensor unit SU via a wireless line N1.

[0052] exist Figure 1 , a cross-sectional shape along the tire width direction of the tire 10 assembled on the rim 90 is shown.

[0053] The tread portion 20 is a portion that contacts the road surface when the tire 10 mounted on a vehicle (not shown) rolls on the road surface. A tread pattern corresponding to the type of vehicle and the required performance is formed on the tread portion 20.

[0054] Furthermore, a sensor unit SU including a uniaxial strain sensor SN for detecting strain of the tire 10 is provided on the inner surface 10 a of the tire 10 to which the tire load prediction system S1 is applicable.

[0055] Although not directly related to the present embodiment, the sensor unit SU may be configured to acquire temperature information and the like in addition to strain.

[0056] exist Figure 1 In the illustrated configuration, the sensor unit SU is provided on the inner surface 10a facing the tread portion 20. More specifically, the sensor unit SU is attached to the surface of an inner liner (not shown) that prevents leakage of gas such as air filled in the interior space of the pneumatic tire 10 assembled on the rim 90.

[0057] The sensor unit SU is preferably provided on each tire 10 mounted on the vehicle. This is because it is desirable to monitor the load and the like of each tire 10 to ensure the safety of the vehicle.

[0058] Furthermore, the sensor unit SU does not necessarily need to be attached to the inner surface of the tire 10 . For example, a part or all of the sensor unit SU may be embedded in the tire 10 .

[0059] (Functional Structure of Tire Load Prediction System)

[0060] like Figure 2 As shown in the functional block diagram, the sensor unit SU includes: a uniaxial strain sensor SN for detecting the strain of the tire 10; a transmitter 101 for transmitting detection data to the processing device 200; and a battery 102 for supplying power to the strain sensor SN and the transmitter 101.

[0061] Meanwhile, the processing device 200 includes a strain data acquisition unit 202 that acquires tire tangential strain data output from the sensor units SU via the communication unit 201 .

[0062] Furthermore, a storage unit 203 composed of a nonvolatile memory or the like is provided, and the storage unit 203 stores the acquired strain data.

[0063] Furthermore, a linear transformation unit 251 constituted by the CPU 250 or the like is provided, and the linear transformation unit 251 performs linear transformation on the acquired strain data.

[0064] Furthermore, a first estimating unit 252 is provided for estimating the tire tangential velocity and angular velocity based on the transformation result of the linear transformation unit 251 .

[0065] Furthermore, a second estimating unit 253 is provided for estimating the speed in the tire radial direction based on the estimated values ​​of the speed and angular velocity in the tire tangential direction.

[0066] Furthermore, a third estimating unit 254 is provided for estimating a velocity in the angular direction θ corresponding to the angle of the strain sensor SN relative to the contact patch of the tire 10 based on the estimated values ​​of the tire tangential acceleration and angular velocity.

[0067] Furthermore, a fourth estimating unit 255 is provided for estimating the deflection of the tire 10 based on the velocity and angular velocity in the tire tangential direction, the velocity in the tire radial direction, and the velocity in the θ-angle direction.

[0068] Furthermore, a load prediction unit 256 is provided that predicts the load applied to the tire 10 based on the estimated deflection of the tire 10 .

[0069] The linear transformation unit 251 , the first estimation unit 252 , the second estimation unit 253 , the third estimation unit 254 , the fourth estimation unit 255 , and the load prediction unit 256 can be implemented through collaboration between the CPU 250 , an OS (Operating System) stored in the storage unit 203 , and predetermined application programs.

[0070] Note that details of the processes performed by the linear transformation unit 251 , the first estimation unit 252 , the second estimation unit 253 , the third estimation unit 254 , the fourth estimation unit 255 , and the load prediction unit 256 will be described later.

[0071] (Regarding tire load prediction processing)

[0072] Reference Figures 3 to 15 Next, the processing procedure of the tire load prediction process executed in the tire load prediction system S1 will be described.

[0073] Before explaining the tire load prediction process, Figure 3 (a) to (d) show the definition of the coordinate system used in the tire load prediction system S1 according to the present embodiment.

[0074] Here, R stands for radial direction, and T stands for tangential direction or circumferential direction.

[0075] In addition, the R, T coordinate system is an object coordinate system (local coordinate system) fixed to the strain sensor SN.

[0076] Meanwhile, X and Z are global coordinate systems fixed in space. Furthermore, a represents acceleration, v represents velocity, and u represents displacement. Furthermore, ω represents the angular velocity of the strain sensor SN, and θ represents the angle of the strain sensor SN.

[0077] Figure 4 : is a flowchart showing the processing procedure of the tire load prediction process executed in the tire load prediction system S1 .

[0078] When the process starts, in step S10 , tire tangential strain data is acquired, and the process proceeds to step S11 .

[0079] In step S11 , linear transformation is performed on the acquired strain data, and the process proceeds to step S12 .

[0080] In step S12 , a first estimation process for estimating the tire tangential velocity and angular velocity is performed, and the process proceeds to step S13 .

[0081] In step S13 , a second estimation process is executed for estimating the speed in the tire radial direction based on the speed and angular speed in the tire tangential direction, and the process proceeds to step S14 .

[0082] In step S14 , a third estimation process for estimating the velocity in the θ angle direction is executed, and the process proceeds to step S15 .

[0083] A fourth estimation process is executed for estimating the deflection of the tire 10 based on the tire tangential velocity and angular velocity, the tire radial velocity, and the velocity in the θ-angle direction, and the process proceeds to step S16 .

[0084] In step S16 , the load applied to the tire 10 is estimated based on the deflection of the tire 10 , and the process ends.

[0085] (About the load estimation method using biaxial acceleration)

[0086] Here, a brief description will be given of a method for estimating a load using biaxial acceleration as a comparison target.

[0087] First, physically, tracking the two-dimensional motion of an object (rigid body) and calculating its trajectory requires three degrees of freedom. To estimate tire load using biaxial acceleration, data on the three axes—the "R direction," the "T direction," and the "θ direction"—is required.

[0088] Therefore, assuming that the trajectory within the tire is almost circular motion, the acceleration in the two axis (R, T) directions is measured, and the angular velocity is estimated through calculation, and then the trajectory is obtained.

[0089] As a result of the inventors' intensive research, in order to realize the above-mentioned processing by a single-axis strain sensor SN, a new method (algorithm) on how to estimate the data of three axes ("R direction", "T direction", "θ direction") based on the single-axis measurement data was developed.

[0090] (Regarding the load prediction method in the present invention)

[0091] In the load prediction method of the present invention, first, the measured strain data is linearly transformed to estimate the values ​​of the T-direction velocity and the angular velocity.

[0092] Next, the R-direction acceleration is estimated from these two estimated values. Then, by integrating the R-direction acceleration to obtain the R-direction velocity, data for the three axes of "R-direction velocity," "T-direction velocity," and "θ-direction angular velocity" can be obtained. Using this data, the trajectory can be calculated.

[0093] The following describes the calculation method in detail.

[0094] In addition, for the sake of convenience, it is assumed that Figure 5 The sample data shown is obtained through FEM analysis, and the tire type is "11R22.5M801".

[0095] Note that this data is strain data on the tire inner surface measured by the strain sensor SN, and is hereinafter referred to as ε(t).

[0096] [Estimation of angular velocity]

[0097] First, the process of calculating the angular velocity from the tangential strain will be described.

[0098] The angular velocity is estimated by applying linear transformation to the measured data using the following equation (Equation 1).

[0099] [Number 1]

[0100] ω(t)=ω0(a1ε(t)+1)

[0101] Here, ω0 and a1 are parameters representing the average angular velocity and angular velocity magnification, respectively.

[0102] Furthermore, ω0 is determined by the following equation (Equation 2) using one rotational time (ORT) obtained from the tire rotation cycle.

[0103] [Number 2]

[0104]

[0105] Note that a1 is determined by learning based on experimental values, or by trial and error, etc. Alternatively, nonlinear transformation may be used.

[0106] As Figure 6 , a graph showing the estimated angular velocity.

[0107] [Principle of angular velocity estimation]

[0108] The tire 10 undergoes significant bending deformation in the region near the contact edge, generating significant compressive strain on the tire inner surface.

[0109] Furthermore, it is conceivable that the curvature increases due to the large bending deformation, and the angular velocity of the strain sensor SN itself increases.

[0110] On the contrary, near the axle, the bending deformation is relaxed, the compressive strain becomes smaller (converted to tensile force), and it is also considered that the angular velocity of the strain sensor SN itself also becomes smaller due to the smaller curvature.

[0111] According to this, the compressive strain has a correlation with the angular velocity of the strain sensor SN, which is assumed to be linear here.

[0112] [Estimation of tangential velocity]

[0113] Next, the process of calculating the tangential velocity from the tangential strain will be described.

[0114] The tangential velocity is estimated by applying linear transformation to the measured data using the following equation (Equation 3).

[0115] [Number 3]

[0116] v T (t) = v T0 (a2ε(t)+1)

[0117] Among them, v T0 and a2 are parameters representing the average tangential velocity and the tangential velocity ratio, respectively.

[0118] Furthermore, using the one rotational time (ORT) obtained from the tire rotation cycle and the tire radius R, v is obtained by the following formula (Equation 4): T0 .

[0119] [Number 4]

[0120]

[0121] Note that a2 is determined by learning based on experimental values, or by repeated trials, etc. Alternatively, nonlinear transformation may be used.

[0122] As Figure 7 , showing a graph of the estimated tangential velocity.

[0123] "Principles for Estimating Tangential Velocity"

[0124] Assume that Figure 8 As shown in (a) of FIG. 1 , for the rolling tire 10 , the space is divided at each minute sampling time interval Δt.

[0125] Here, in the case of the tire 10 before deformation (the tire is suspended in the air and rotating), if the radius R0 and the angular velocity ω0 are independent of time, the distance traveled in a short time can be expressed as R0ω0Δt (see Figure 8 (b)).

[0126] On the other hand, when the tire 10 is grounded and deformed, the radius and angular velocity become functions of time, expressed as R(t) and θ'(t), respectively. In this case, the distance traveled in a small time period can be expressed as R(t)θ'(t)Δt (see Figure 8 (c)).

[0127] Strain is defined as the amount of expansion or contraction relative to the original length. Therefore, the circumferential strain of the tire 10 is expressed by the following equation (Equation 5).

[0128] [Number 5]

[0129]

[0130] Here, when it is assumed that the strain sensor SN performs circular motion, the tangential velocity v T (t) can be expressed as the following formula (Equation 6).

[0131] [Number 6]

[0132] v T (t)=R(t)θ'(t)

[0133] Substituting this into the equation of ε(t) in number 5 yields number 7.

[0134] [Number 7]

[0135]

[0136] Here, R0ω0 is a fixed value that does not depend on time, so it can be seen that v T (t) and ε(t) have a linear transformation relationship.

[0137] [Estimation of radial acceleration / velocity]

[0138] When it is assumed that the strain sensor SN performs circular motion, it can be estimated theoretically by calculation using the following equation (Equation 8).

[0139] [Number 8]

[0140] a R (t) = v T (t)ω(t)

[0141] Furthermore, the radial velocity is calculated by time-integrating the estimated value using the following equation (Equation 9).

[0142] [Number 9]

[0143]

[0144] Among them, a R (t) is sometimes accompanied by pre-processing such as centralization. In addition, v R0 This is the initial value and can be set to any value.

[0145] [Coordinate transformation]

[0146] Here, using the estimated angular velocity ω(t), the estimated radial velocity v R (t), tangential velocity v T (t) Transform from the R, T coordinate system to the X, Z coordinate system.

[0147] First, the angular velocity ω(t) is integrated to calculate the angle θ(t) using the following formula (Equation 10).

[0148] [Number 10]

[0149]

[0150] However, ω(t) may be pre-processed such as adjusting so that the average value becomes 2π. The initial value θ0 is set to an appropriate value such as 0 or -π.

[0151] exist Figure 9 An example of the calculation result of the angle θ(t) is shown in the graph of .

[0152] Next, coordinate transformation of the velocity is performed.

[0153] The calculation from the object coordinate system (R, T) of the strain sensor SN to the global coordinate system (X, Z) is performed using the following equation (Equation 11).

[0154] [Number 11]

[0155] v x(t) = v T (t)cosθ(t)-v R (t)sinθ(t)

[0156] v z (t) = v T (t)sinθ(t)+v T (t)cosθ(t)

[0157] exist Figure 10 and Figure 11 An example of the calculated result is shown in the graph of .

[0158] [Estimation of displacement]

[0159] Integrate the velocity and calculate the displacement u according to the following formula (Equation 12): x (t),u z (t).

[0160] [Number 12]

[0161]

[0162]

[0163] Among them, v x 、v z Sometimes it is accompanied by preprocessing such as centralization. Initial value u x0 、u z0 Can be set to any value. Figure 12 and Figure 13 An example of the calculated result is shown in the graph of .

[0164] [Estimation of contour and deflection]

[0165] Moreover, when the time component is removed and the displacement (u x (t),u z (t)) is plotted on a two-dimensional plane, Figure 14 The trajectory shown. A circle is fitted to this trajectory to find the regression radius R fit .

[0166] In addition, the effective radius R when the tire is bent is calculated. eff (e.g. the minimum value from the center of the regression circle).

[0167] Then, the deflection is calculated based on the following equation (Equation 13).

[0168] [Number 13]

[0169] d=R fit -R eff

[0170] In addition, the characteristic quantities used in load prediction may also be deflection d, deflection ratio d / R fit Any of .

[0171] [Load prediction]

[0172] Next, the effectiveness and method of load calculation using deflection will be described.

[0173] First, in Figure 15 The relationship between the estimated deflection value and the load calculated using the algorithm of the present invention is shown in FIG. Note that this data is also an example of analysis using FEM.

[0174] In addition, Figure 15 In FIG. 1 , broken line 10A represents a tire with normal wear, and broken line 10B represents a tire with uneven wear in the center portion.

[0175] In this way, a linear relationship is obtained similarly to the deflection obtained from the height of the axle described above.

[0176] In addition, if Figure 15 As shown, it can be seen that the broken lines 10A and 10B almost converge into one line.

[0177] As described above, wear dependency, which is a disadvantage of CTR, is not observed, and thus load prediction can be made more accurate.

[0178] In addition, when actually predicting the load, the load is calculated using the following formula (Formula 14).

[0179] [Number 14]

[0180] (Load) = f(deflection, temperature, pressure, etc.)

[0181] Furthermore, in addition to deflection information, TPMS information, wear information, etc. can be used as explanatory variables, and machine learning can be performed in advance to determine parameters before operation.

[0182] Alternatively, linear multiple regression is generally sufficient, but nonlinear models can also be used.

[0183] As described above, according to the tire load prediction system S1 according to this embodiment, the accuracy of load prediction can be improved, and load prediction can be performed even for a vehicle that mainly travels at low speeds.

[0184] Furthermore, by using the strain sensor SN, it is possible to predict tire deflection and load regardless of the wear state of the tire.

[0185] While the tire load prediction system and tire load prediction program of the present invention have been described above based on the illustrated embodiments, the present invention is not limited thereto, and the configuration of each component may be replaced with any configuration having the same function.

[0186] For example, as long as the operating conditions of the power source (battery) 102 and the like are satisfied, part of the processing functions of the processing device 200 in this embodiment may be mounted in the sensor unit SU.

[0187] Description of Reference Numerals

[0188] S1: tire load prediction system; SU: sensor unit; SN: strain sensor; 10: pneumatic tire (tire); 200: processing device; 202: strain data acquisition unit; 203: storage unit; 250: CPU; 251: linear transformation unit; 252: first estimation unit; 253: second estimation unit; 254: third estimation unit; 255: fourth estimation unit; 256: load prediction unit.

Claims

1. A tire load prediction system comprising: a sensor unit disposed inside the tire and having a strain sensor for detecting strain of the tire; a strain data acquisition unit that acquires tire tangential strain data output from the sensor unit; a linear transformation unit, which performs linear transformation on the acquired strain data; a first estimating unit for estimating a tangential velocity and an angular velocity of the tire based on a transformation result of the linear transformation unit; a second estimating unit for estimating a radial velocity of the tire based on the estimated values ​​of the tangential velocity and angular velocity of the tire; a third estimating unit for estimating a velocity in an angular direction θ corresponding to an angle of the strain sensor relative to the tire contact patch based on the estimated values ​​of the tire tangential acceleration and angular velocity; a fourth estimating unit configured to estimate the deflection of the tire based on the tire tangential velocity and angular velocity, the tire radial velocity, and the velocity in the θ-angle direction; as well as A load prediction unit predicts a load applied to the tire based on the estimated deflection of the tire.

2. The tire load prediction system according to claim 1, wherein: The fourth estimation unit estimates the deformation profile of the tire based on the tire tangential velocity, the tire radial velocity, and the velocity in the θ-angle direction, and extracts a feature value corresponding to the tire deflection to estimate the tire deflection.

3. The tire load prediction system according to claim 1, wherein: The linear transformation unit performs linear transformation on the strain data using the following formula: [Number 1] ω(t)=ω0(a1ε(t)+1) Where ω0 is the average angular velocity, a1 is the angular velocity magnification, and ε is the strain.

4. The tire load prediction system according to claim 1, wherein: The first estimating unit estimates the tangential velocity by performing a linear transformation on the acquired data using the following formula: [Number 3] v T (t)=v T0 (a2ε(t)+1) Among them, v T0 is the average tangential velocity, a2 is the tangential velocity ratio, and ε is the strain.

5. A tire load prediction program, executed by a CPU of a tire load prediction system, the tire load prediction program comprising the following steps: a strain data acquisition step of acquiring tire tangential strain data outputted from a strain sensor disposed on an inner surface or inside the tire; a linear transformation step, performing a linear transformation on the acquired strain data; A first estimation step estimates the tire tangential velocity and angular velocity based on the transformation result; a second estimating step of estimating the radial speed of the tire based on the estimated values ​​of the tangential speed and angular speed of the tire; a third estimating step of estimating a velocity in an angular direction θ corresponding to an angle of the strain sensor relative to the contact patch of the tire based on the estimated values ​​of the tire tangential acceleration and angular velocity; a fourth estimating step of estimating the tire deflection based on the tire tangential velocity and angular velocity, the tire radial velocity, and the tire velocity in the θ direction; as well as The load prediction step predicts a load applied to the tire based on the estimated deflection of the tire.

6. The tire load prediction program according to claim 5, wherein: In the fourth estimating step, the deformation profile of the tire is estimated based on the tire tangential velocity, the tire radial velocity, and the velocity in the θ-angle direction, and a feature value corresponding to the tire deflection is extracted to estimate the tire deflection.

7. A tire load prediction method comprising the following steps: A strain data acquisition process, which acquires tire tangential strain data output from a strain sensor disposed on the inner surface or interior of the tire; The linear transformation process performs linear transformation on the acquired strain data; A first estimation process estimates the tire tangential velocity and angular velocity based on the transformation result; A second estimation process estimates the tire radial velocity based on the estimated tire tangential velocity and angular velocity; a third estimation process of estimating a velocity in an angular direction θ corresponding to an angle of the strain sensor relative to the contact patch of the tire based on the estimated values ​​of the tire tangential acceleration and angular velocity; a fourth estimation process of estimating the tire deflection based on the tire tangential velocity and angular velocity, the tire radial velocity, and the tire velocity in the θ direction; as well as The load prediction process predicts a load applied to the tire based on the estimated deflection of the tire.

8. The tire load prediction method according to claim 7, wherein: In the fourth estimation process, the deformation profile of the tire is estimated based on the tire tangential velocity, the tire radial velocity, and the velocity in the θ-angle direction, and a feature value corresponding to the tire deflection is extracted to estimate the tire deflection.

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