Information processing device, vehicle equipped with the same, information processing method, and program

Abstract

To estimate the change of state of a tire with high accuracy.SOLUTION: A brake ECU 12 (information processing apparatus 200) is mounted on a vehicle 1 including a steering wheel and a plurality of wheels 400 with respective tires mounted thereon. The brake ECU 12 includes a processor 121, the processor 121 calculating feature quantities on flexibility of the tires when at least one condition is completely satisfied. The at least one condition includes at least one of: a condition that an absolute value of a steering wheel angular velocity ω is smaller than a reference value ωref; and a condition that an absolute value of the vector sum of acceleration of the vehicle is smaller than a reference value Gref.SELECTED DRAWING: Figure 10

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, a vehicle equipped with the same, an information processing method, and a program, and more particularly to information processing in a vehicle. [Background technology]

[0002] Japanese Patent Laid-Open Publication No. 2002-221527 (Patent Document 1) discloses a device for accurately detecting the state of tire wear. This device detects the state of tire wear according to the average value of the linear regression coefficients between the acceleration / deceleration of the vehicle and the slip ratios of the front and rear wheels. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-221527 Summary of the Invention [Problem to be solved by the invention]

[0004] Generally, various sensors are attached to vehicles. It is possible to estimate changes in the condition of vehicle parts based on data acquired from these sensors. In particular, changes in the condition of tires can occur due to deterioration (wear), replacement, etc. Therefore, there is a demand for a system that can estimate changes in the condition of tires with high accuracy (see, for example, Patent Document 1).

[0005] The present disclosure has been made to solve the above-mentioned problems, and one of the objects of the present disclosure is to estimate changes in the state of a tire with high accuracy. [Means for solving the problem]

[0006] (1) An information processing device according to one aspect of the present disclosure is mounted on a vehicle including a steering wheel and a plurality of wheels, each of which has a tire. The information processing device includes a processor. The processor calculates a feature amount related to tire flexibility when at least one condition is met. The at least one condition includes at least one of a first condition that the absolute value of the angular velocity of the steering wheel is smaller than a first reference value and a second condition that the absolute value of the vector sum of the vehicle acceleration is smaller than a second reference value.

[0007] (2) The at least one condition includes both the first and second conditions.

[0008] (3) The at least one condition further includes a third condition that the absolute value of the angle of the steering wheel is smaller than a third reference value.

[0009] (4) The at least one condition further includes a fourth condition that the speed of the vehicle is within a predetermined range.

[0010] According to the above (1) to (4), the feature values are calculated under conditions that guarantee and ensure that the force applied to the tire is within a certain range (that is, the force applied to the tire does not fluctuate), so that changes in the tire condition can be estimated with high accuracy.

[0011] (5) The plurality of wheels includes drive wheels and driven wheels, and the processor calculates, as the feature, a gradient that is a ratio of a rotational speed ratio of the drive wheels to a rotational speed ratio of the driven wheels with respect to an acceleration in a longitudinal direction of the vehicle.

[0012] According to the above (5), changes in the state of the tire, particularly changes in flexibility, can be estimated with high accuracy.

[0013] (6) The processor accumulates the difference from the initial value of the gradient at predetermined intervals, and when the accumulated result exceeds a first threshold, outputs a signal indicating that a gradual change in tire flexibility has occurred.

[0014] (7) The processor outputs a signal indicating that a sudden change in tire flexibility has occurred when the difference between the previous and current gradient values exceeds a second threshold value.

[0015] According to the above (6) and (7), it is possible to identify what kind of change has occurred in the flexibility of the tire (whether it is a gradual change or a sudden change).

[0016] (8) A vehicle according to another aspect of the present disclosure includes the information processing device described in (1) above, a steering wheel, and a plurality of wheels.

[0017] (9) An information processing method according to another aspect of the present disclosure relates to a vehicle including a steering wheel and a plurality of wheels, each of which has a tire. The information processing method includes the steps of determining whether at least one condition is met and calculating a feature amount related to tire flexibility if all of the at least one condition is met. The at least one condition includes at least one of a first condition that the absolute value of the angular velocity of the steering wheel is smaller than a first reference value and a second condition that the absolute value of the vector sum of the vehicle acceleration is smaller than a second reference value.

[0018] (10) A program according to another aspect of the present disclosure, when executed by a processor of a computer, causes the computer to process information about a vehicle including a steering wheel and a plurality of wheels, each with a tire. The program includes a step of determining whether at least one condition is met, and a step of calculating a feature amount related to tire flexibility when all of the at least one condition is met. The at least one condition includes at least one of a first condition that the absolute value of the angular velocity of the steering wheel is smaller than a first reference value and a second condition that the absolute value of the vector sum of the acceleration of the vehicle is smaller than a second reference value.

[0019] According to the configurations or methods of (8) to (10) above, similar to (1) above, it is possible to estimate changes in the state of the tire with high accuracy. [Effects of the Invention]

[0020] According to the present disclosure, changes in the state of a tire can be estimated with high accuracy. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a diagram illustrating an overall configuration of a vehicle management system according to an embodiment of the present disclosure. [Figure 2] FIG. 1 is a diagram illustrating an example of the configuration of a vehicle. [Figure 3] FIG. 1 is a block diagram showing a typical hardware configuration of a brake ECU. [Figure 4] FIG. 1 is a diagram illustrating a system included in a vehicle. [Figure 5] FIG. 1 is a diagram for explaining an outline of processing by an information processing device. [Figure 6] FIG. 2 is a functional block diagram of the information processing device. [Figure 7] FIG. 10 is a diagram for explaining a gradient. [Figure 8] 10A and 10B are diagrams for explaining a method for detecting a gradual change in tire flexibility. [Figure 9] 10A and 10B are diagrams for explaining a method for detecting a sudden change in tire flexibility. [Figure 10] 10 is a flowchart showing a flow of processing by the information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0022] Hereinafter, the present embodiment will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals, and description thereof will not be repeated.

[0023] [Embodiment Mode] <Overall system configuration> 1 is a diagram showing the overall configuration of a vehicle management system according to an embodiment of the present disclosure. The vehicle management system 10 includes a plurality of vehicles 1 and a data center 9.

[0024] The vehicle 1 is, for example, an electric vehicle (BEV: Battery Electric Vehicle). However, the power source of the vehicle 1 is not particularly limited. The vehicle 1 may be a vehicle equipped with an engine (a so-called conventional vehicle), a hybrid vehicle (HEV: Hybrid Electric Vehicle), a plug-in hybrid vehicle (PHEV: Plug-in Hybrid Electric Vehicle), or a fuel cell electric vehicle (FCEV: Fuel Cell Electric Vehicle). The configuration of the vehicle 1 will be described with reference to FIGS. 2 to 4.

[0025] The data center 9 manages data of multiple vehicles 1. The data center 9 is connected to multiple vehicles 1 via a communication network NW so that two-way communication is possible with the vehicles 1. The data center 9 collects data from each vehicle 1. The data center 9 also provides necessary data (such as update programs) to each vehicle 1 and transmits various commands to each vehicle 1. The data center 9 includes a server 91, a vehicle information database 92, and a communication device 93.

[0026] The server 91 is a processing circuitry including a processor 911 and a memory 912. The server 91 collects data from each vehicle 1. The server 91 then processes the collected data and stores the processing results in a vehicle information database 92. Details of the data collected by the server 91 and the processing by the server 91 will be described later. The communication device 93 realizes communication between the server 91 and the communication network NW.

[0027] <Vehicle configuration> 2 is a diagram showing an example configuration of a vehicle 1. The vehicle 1 includes an Advanced Driver-Assistance Systems (ADAS)-ECU (Electronic Control Unit) 11, a brake ECU 12, a central ECU 13, and a DCM (Data Communication Module) 2. The ADAS-ECU 11, the brake ECU 12, and various ECUs (not shown) included in an actuator system 300 (described later) are communicatively connected to the central ECU 13 via a communication bus such as a CAN (Controller Area Network). Alternatively, the central ECU 13 may have a gateway function that relays communication between the ECUs.

[0028] The ADAS-ECU 11 controls an advanced driver assistance system 100 (see FIG. 4). The advanced driver assistance system 100 is configured to realize various functions for assisting the driving of the vehicle 1.

[0029] The brake ECU 12 executes braking control of the vehicle 1. In this embodiment, the brake ECU 12 includes an information processing device 200. The information processing device 200 acquires various information from a motion manager that manages the motion of the vehicle and a vehicle stability control (VSC) system that stabilizes the posture of the vehicle. The information processing device 200 requests the actuator system 300 to move the vehicle 1 in accordance with an action plan set in at least one of a plurality of applications of the advanced driver assistance system 100. A detailed configuration of the information processing device 200 will be described later.

[0030] The information processing device 200 may be implemented in another ECU (such as a steering ECU or a motor generator ECU, not shown) different from the brake ECU 12. Alternatively, the information processing device 200 may be implemented as a stand-alone ECU. The ECU in which the information processing device 200 is implemented (the brake ECU 12 in this embodiment) corresponds to the "information processing device" according to the present disclosure. The "information processing device" according to the present disclosure may be the central ECU 13.

[0031] The central ECU 13 is communicatively connected to the DCM 2. The DCM 2 is a communication module configured to communicate wirelessly with the outside via a communication network NW. This allows two-way communication between the vehicle 1 and a data center 9 (see FIG. 1). In this embodiment, the central ECU 13 transmits data received from ECUs such as the brake ECU 12 to the data center 9 via the DCM 2.

[0032] The central ECU 13 includes a memory (not shown) in which programs are stored. The programs include programs (such as an operating system and application programs) that are read from various ECUs when the system of the vehicle 1 is started. When the central ECU 13 receives an update program from the data center 9, it updates the programs stored in the memory.

[0033] FIG. 3 is a block diagram showing a typical hardware configuration of the brake ECU 12. The brake ECU 12 includes a processor 121, a memory 122, and an input / output interface (I / O) 123. The processor 121 is, for example, a CPU (Central Processing Unit). The processor 121 executes various arithmetic processes according to programs. The memory 122 includes a ROM (Read Only Memory) 122A, a RAM (Random Access Memory) 122B, and a flash memory 122C. The memory 122 stores programs (such as an operating system and application programs) executed by the processor 121. The input / output interface 123 is configured to enable information exchange with other ECUs. Although a description will not be repeated, the hardware configurations of the other ECUs are similar.

[0034] 4 is a diagram illustrating the systems included in the vehicle 1. The vehicle 1 further includes an actuator system 300, a plurality of (four in this example) wheels 400, and a sensor group 500. The information processing device 200 is connected to the advanced driver assistance system 100, the actuator system 300, and the sensor group 500.

[0035] The advanced driver assistance system 100 includes, for example, an adaptive cruise control (ACC) 101, an auto speed limiter (ASL) 102, a lane keeping assist (LKA) 103, a pre-crash safety (PCS) 104, and a lane departure alert (LDA) 105. Although not shown, the advanced driver assistance system 100 may also include an autonomous driving system (ADS).

[0036] The actuator system 300 includes a plurality of actuators and is configured to realize the motion request of the vehicle 1 output from the information processing device 200. The actuator system 300 includes, for example, a steering system 31, a brake system 32, and a powertrain system 33.

[0037] The steering system 31 includes, for example, a rack-and-pinion type electric power steering (EPS) and controls the steering angle (steering wheel angle) of the steering wheel of the vehicle 1.

[0038] The brake system 32 controls a plurality of braking devices (not shown) provided on each wheel 400 of the vehicle 1. The plurality of braking devices include, for example, a disc brake system that operates using hydraulic pressure adjusted by an actuator. The brake system 32 may include an electric parking brake (EPB) (not shown) that locks the wheels 400 by operation of an actuator. The brake system 32 may also include a P lock system (not shown) that controls a parking (P) lock device provided on the transmission of the vehicle 1.

[0039] The powertrain system 33 is configured to switch the shift range using a shift device (not shown), and is configured to control the driving force of the vehicle 1 in the traveling direction using a motor generator (not shown). The powertrain system 33 rotates drive wheels 41, 42 (described later), which applies driving force to the vehicle 1, causing the vehicle 1 to travel.

[0040] The four wheels 400 include, for example, drive wheels 41 and 42 and driven wheels 43 and 44. In this example, the front wheels are drive wheels and the rear wheels are driven wheels. However, the front and rear of the drive wheels and driven wheels are not particularly limited.

[0041] The sensor group 500 detects driving operation amounts of the vehicle 1 and detects running state amounts of the vehicle 1. The sensor group 500 includes, for example, a steering sensor 51, a first wheel speed sensor 521 to a fourth wheel speed sensor 524, and an acceleration sensor 53.

[0042] The steering sensor 51 detects, for example, the rotation angle of a pinion gear connected to a rotary shaft of an actuator as a steering wheel angle θ. The steering sensor 51 outputs the detected steering wheel angle θ to the information processing device 200. The steering sensor 51 also detects a steering wheel angular velocity ω and outputs the detected steering wheel angular velocity ω to the information processing device 200.

[0043] The first wheel speed sensor 521 detects the driving wheel speed VXFL, which is the rotation speed of the left front driving wheel 41. The second wheel speed sensor 522 detects the driving wheel speed VXFR, which is the rotation speed of the right front driving wheel 42. The third wheel speed sensor 523 detects the driven wheel speed VXRL, which is the rotation speed of the left rear driven wheel 43. The fourth wheel speed sensor 524 detects the driven wheel speed VXRR, which is the rotation speed of the right rear driven wheel 44. Each wheel speed sensor outputs the detected wheel speed to the information processing device 200.

[0044] The acceleration sensor 53 includes a longitudinal acceleration sensor and a lateral acceleration sensor (neither of which are shown). The longitudinal acceleration sensor detects the acceleration GX of the vehicle 1 in the longitudinal direction and outputs the detected acceleration GX to the information processing device 200. The lateral acceleration sensor detects the acceleration GY of the vehicle 1 in the lateral direction and outputs the detected acceleration GY to the information processing device 200. The information processing device 200 can calculate the vector sum of both the longitudinal and lateral accelerations GX and GY. Hereinafter, the vector sum of the accelerations will be referred to as the "resultant acceleration G."

[0045] Although not shown, the sensor group 500 may further include other sensors such as a camera, a millimeter wave radar, a LiDAR (Laser Imaging Detection and Ranging), a gyro sensor, and the like.

[0046] In this example, it has been described that all sensors included in the sensor group 500 directly output their detection results to the information processing device 200. However, any one of these sensors may output its detection result to another ECU. The information processing device 200 may acquire the detection result of the sensor via a communication bus or the central ECU 13.

[0047] In the vehicle 1 configured as described above, the information processing device 200 estimates changes in the tire condition using data acquired from various sensors included in the sensor group 500. However, the condition of the vehicle 1 can change significantly depending on various external disturbances, the driving style of the user, etc. Noise caused by external disturbances, the driving style, etc. may reduce the accuracy of estimating changes in the tire condition.

[0048] Therefore, in this embodiment, the information processing device 200 estimates a change in tire condition when at least one predetermined condition (multiple conditions in this embodiment) is met. More specifically, the information processing device 200 calculates a feature quantity related to tire flexibility when all of the multiple conditions are met. These conditions are set assuming a driving situation in which the force applied to the tire is within a certain range. As will be described in detail later, this makes it possible to calculate the feature quantity after removing noise caused by external disturbances, driving style, and the like. As a result, it becomes possible to estimate a change in tire condition with high accuracy.

[0049] <Information processing device> 5 is a diagram for explaining an outline of processing by the information processing device 200. The information processing device 200 includes, for example, a condition determination unit 201, a feature calculation unit 202, and a change detection unit 203.

[0050] The condition determination unit 201 determines whether at least one condition (in this example, multiple conditions) for calculating a feature quantity is satisfied, based on data related to driving operation quantities and data related to vehicle state quantities from the sensor group 500. Details of the multiple conditions will be described with reference to FIG. 6. The condition determination unit 201 outputs the condition determination result to the feature quantity calculation unit 202.

[0051] When multiple conditions for calculating the feature quantities are met, the feature quantity calculation unit 202 calculates feature quantities related to tire flexibility using data related to driving operation quantities and data related to vehicle state quantities. The method for calculating the feature quantities will be described with reference to Figs. 6 and 7. The feature quantity calculation unit 202 outputs the calculated feature quantities to the change detection unit 203.

[0052] The change detection unit 203 detects changes in the tire condition based on feature amounts related to tire flexibility. The method for detecting changes in the tire condition will be described with reference to Figures 6, 8, and 9. The change detection unit 203 outputs data indicating the detected changes in the tire condition to the central ECU 13.

[0053] The central ECU 13 transmits data indicating changes in the tire condition to the data center 9 via the DCM 2. As a result, the data is stored in the vehicle information database 92 in the data center 9.

[0054] FIG. 6 is a functional block diagram of the information processing device 200.

[0055] Condition Judgment The condition determination unit 201 receives, from the sensor group 500, the steering wheel angle θ and the steering wheel angular velocity ω as data related to driving operation quantities, and also receives four wheel speeds (driving wheel rotation speeds VXFL, VXFR, driven wheel rotation speeds VXRL, VXRR) and accelerations GX, GY as data related to vehicle state quantities. Upon receiving a trigger signal (e.g., a signal indicating the passage of a control period), the condition determination unit 201 determines whether multiple conditions for calculating feature quantities are met based on this data. More specifically, in this example, the condition determination unit 201 determines whether the following four conditions are met:

[0056] The condition determination unit 201 determines whether the speed (vehicle speed) V of the vehicle 1 is within a range defined by an upper limit value UL and a lower limit value LL (see equation (1) below). As an example, the lower limit value LL is 30 [km / h], and the upper limit value UL is 70 [km / h]. If this condition is met, the vehicle 1 is traveling at a low or medium speed. LL≦V≦UL (1)

[0057] The condition determination unit 201 may calculate the vehicle speed V using a known method. For example, the condition determination unit 201 may calculate the vehicle speed V from a specific wheel speed among the four wheel speeds. Alternatively, the condition determination unit 201 may calculate the vehicle speed V from the rotation speed of a drive shaft (not shown).

[0058] The condition determination unit 201 determines whether the absolute value of the steering wheel angle θ is equal to or less than a predetermined reference value θref (see the following formula (2)). If this condition is met, the vehicle 1 is traveling straight or making a gentle turn. |θ|≦θref (2)

[0059] The condition determination unit 201 determines whether the absolute value of the steering wheel angular velocity ω is equal to or less than a predetermined reference value ωref (see the following formula (3)). If this condition is met, the vehicle 1 is traveling straight or turning at a substantially constant angular velocity (in uniform circular motion). |ω|≦ωref (3)

[0060] The condition determination unit 201 determines whether the absolute value of the resultant acceleration G is equal to or less than a predetermined reference value Gref (see the following formula (4)). The reference value Gref is, for example, 1 [m / s 2 When this condition is met, the vehicle 1 is accelerating or decelerating slowly. |G|≦Gref (4)

[0061] The above four conditions can be categorized into three attributes. The condition related to vehicle speed V (Equation (1)) is a premise. The condition related to steering wheel angle θ (Equation (2)) and the condition related to steering wheel angular velocity ω (Equation (3)) are inputs (causes). The condition related to resultant acceleration G (Equation (4)) is a response (result). In particular, steering wheel angular velocity ω represents fluctuations in input. When steering wheel angular velocity ω changes, the force applied to the tires fluctuates, and the resultant acceleration G changes in response. Therefore, the condition related to steering wheel angular velocity ω and the condition related to resultant acceleration G are important in determining whether the force applied to the tires is fluctuating or constant.

[0062] If all of formulas (1) to (4) hold, the condition determination unit 201 turns on a permission flag that permits calculation of the feature amount. On the other hand, if at least one of formulas (1) to (4) does not hold, the condition determination unit 201 turns off the permission flag. The condition determination unit 201 outputs a signal indicating whether the permission flag is on or off to the feature amount calculation unit 202.

[0063] <Feature Calculation> When the permission flag is on, the feature calculation unit 202 calculates gradients grdL and grdR as feature quantities based on the driving wheel rotation speeds VXFL and VXFR, the driven wheel rotation speeds VXRL and VXRR, and the longitudinal acceleration GX. The gradient grdL is a feature quantity related to the left tires (the driving wheel 41 and the driven wheel 43). The gradient grdR is a feature quantity related to the right tires (the driving wheel 42 and the driven wheel 44).

[0064] FIG. 7 is a diagram illustrating the gradient grdL. The horizontal axis represents the acceleration GX in the longitudinal direction. The vertical axis represents the left wheel speed ratio SL. The wheel speed ratio SL is the rotational speed ratio VXFL / VXRL between the driving wheels 41 and the driven wheels 43. Note that SL may be set to VXFL / VXRL-1 so that the wheel speed ratio SL becomes 0 when VXFL=VXRL.

[0065] During acceleration, the driving wheel rotation speed VXFL becomes higher than the driven wheel rotation speed VXRL (VXFL / VXRL>1), while during deceleration, the driving wheel rotation speed VXFL becomes lower than the driven wheel rotation speed VXRL (VXFL / VXRL<1). Therefore, the relationship between the longitudinal acceleration GX and the wheel speed ratio SL is a straight line sloping upward to the right, as shown in Figure 7.

[0066] The feature amount calculation unit 202 calculates the ratio of the left wheel speed ratio SL (=VXFL / VXRL) to the longitudinal acceleration GX as the gradient grdL, as shown in the following equation (5). The gradient may also be referred to as the inclination of a straight line. grdL=SL / GX (5)

[0067] Although not shown, the feature calculation unit 202 also calculates the gradient grdR in a similar manner. The gradient grdR is the ratio of the right wheel speed ratio SR (=VXFR / VXRR) to the longitudinal acceleration GX (see equation (6) below). Note that the gradients grdL and grdR correspond to the "ratio" according to the present disclosure. grdR=SR / GX (6)

[0068] If a line representing Hooke's law (F=kx (k: spring constant)) is plotted on a graph with the spring deformation x on the horizontal axis and the spring's elastic force F on the vertical axis, the slope of the line represents the spring constant k. The greater the slope, the greater the spring constant k, i.e., the stiffer the spring. We will use this analogy to conceptually explain the physical meaning of gradient.

[0069] In the equation of motion (F = ma), if the mass m is constant, the acceleration F and the force a are in a proportional relationship, so it is possible to read the acceleration as a force. Therefore, it is considered that the acceleration GX on the horizontal axis in FIG. 7 represents the longitudinal force applied to the tire's contact surface. On the other hand, the difference in rotational speed between the driving wheel and the driven wheel is caused by the slip of the wheel (mainly the driving wheel). The wheel during slip stretches compared to when it is not. From this, it is considered that the wheel speed ratio SR on the vertical axis represents the amount of deformation in the rotational direction of the tire. Therefore, from the above spring analogy, it can be said that the gradient in FIG. 7 is a parameter related to the stiffness (rigidity / elasticity) of the tire like the spring constant. However, the relationship between the vertical axis and the horizontal axis is reversed between FIG. 7 and the graph illustrating Hooke's law. Therefore, a large gradient in FIG. 7 means that the tire has high flexibility. As the deterioration of the tire progresses and the flexibility of the tire decreases, the gradient becomes smaller.

[0070] In addition, when the acceleration GX is in the forward direction and small (for example, when 0.975 < GX < 1.025), when SL > SLPmax, SL may be set to SLPmax, and when SL < SLPmin, SL may be set to SLPmin. When the acceleration GX is in the reverse direction and small (for example, when -1.025 < GX < -0.975), when SL > SLNmax, SL may be set to SLNmax, and when SL < SLNmin, SL may be set to SLNmin. Then, the maximum value of the gradient grdLmax = (SLPmax - SLNmin), and the minimum value of the gradient grdLmin = (SLPmin - SLNmax). The feature quantity calculation unit 202 may calculate the value between the maximum value grdLmax and the minimum value grdLmin of the gradient as the gradient grdL.

[0071] Returning to FIG. 6 , the feature calculation unit 202 stores the calculated feature amounts (gradients grdL, grdR) in the memory 122 in association with the order in which they were calculated. In this example, the number of trips of the vehicle 1 is used as the calculation order. The feature amount is calculated, for example, once per trip. However, the feature calculation unit 202 may calculate a feature amount for one trip multiple times, or may calculate a feature amount for multiple trips once. Alternatively, the feature calculation unit 202 may calculate a feature amount every time a specified time elapses, or may calculate a feature amount every time the vehicle 1 travels a specified distance. The feature calculation unit 202 outputs the calculated gradients grdL, grdR and the number of trips to the change detection unit 203.

[0072] <Change detection> The change detection unit 203 detects changes in tire flexibility based on the gradients grdL and grdR. More specifically, the change detection unit 203 detects changes in the flexibility of the left tire based on the gradient grdL, and detects changes in the flexibility of the right tire based on the gradient grdR. Changes in tire flexibility may include gradual changes (gradual changes) in tire flexibility that are expected to occur due to tire wear, etc., and sudden changes (sudden changes) in tire flexibility that are expected to occur due to tire replacement, etc.

[0073] 8 is a diagram for explaining a method for detecting gradual changes in tire flexibility. The horizontal axis represents the number of trips, and the vertical axis represents the integrated result of the gradient (gradient grdL or gradient grdR).

[0074] The change detection unit 203 separately performs calculation processing for the gradient grdL and calculation processing for the gradient grdR. Although the following description will be given taking the calculation processing for the gradient grdL as an example, the calculation processing for the gradient grdR is similar.

[0075] The change detection unit 203 stores the initial value of the gradient grdL (the gradient for the first trip), grdL(0). For each trip, the change detection unit 203 integrates the difference (grdL(n)-grdL(0)) (usually a negative value) between the current gradient value grdL(n) and the initial gradient value grdL(0) with the integrated result of the gradient up to the previous trip. Then, the change detection unit 203 determines whether the integrated result of the gradient ΣgrdL is equal to or less than a first threshold value TH1 (see equation (7) below). ΣgrdL≦TH1 (7)

[0076] The first threshold TH1 may be a fixed value, or may be set according to the initial value grdL(n) of the gradient. For example, the first threshold TH1 may be set to α times (α<1) the initial value grdL(n).

[0077] If the gradient integration result ΣgrdL is equal to or less than the first threshold value TH1, the change detection unit 203 determines that a gradual change in left tire flexibility has occurred and switches the gradual change detection flag to ON. On the other hand, if the gradient integration result ΣgrdL exceeds the first threshold value TH1, the change detection unit 203 determines that a gradual change in left tire flexibility has not occurred and keeps the gradual change detection flag to OFF. The change detection unit 203 outputs a signal indicating the ON / OFF status of the gradual change detection flag to the central ECU 13.

[0078] 9 is a diagram for explaining a method for detecting a sudden change in tire flexibility. The horizontal axis represents the number of trips. The vertical axis represents the gradient (gradient grdL or gradient grdR). Here, the gradient grdL will be used as an example, but the same applies to the gradient grdR.

[0079] The change detection unit 203 stores, for example, the gradient grdL immediately after the start of each trip. The change detection unit 203 determines whether the difference ΔgrdL between the current gradient value grdL(n) and the previous gradient value grdL(n-1), ΔgrdL=grdL(n)-grdL(n-1), is equal to or greater than a second threshold value TH2 (see equation (8) below). ΔgrdL≧TH2 (8)

[0080] If the difference ΔgrdL is equal to or greater than the second threshold value TH2, the change detection unit 203 determines that a sudden change in left tire flexibility has occurred and switches the sudden change detection flag to ON. On the other hand, if the difference ΔgrdL is less than the second threshold value TH2, the change detection unit 203 determines that a sudden change in left tire flexibility has not occurred and keeps the sudden change detection flag OFF. The change detection unit 203 outputs a signal indicating the ON / OFF status of the sudden change detection flag to the central ECU 13.

[0081] Referring again to FIG. 5, the central ECU 13 transmits the data (the gradual change detection flag and the sudden change detection flag) received from the change detection unit 203 to the data center 9 via the DCM2. The data transmitted from the DCM2 to the data center 9 may further include gradients grdL and grdR, which are feature quantities, or may include an integrated result of the gradients. It is preferable that these data be associated with a processing time. The data center 9 accumulates these data in the vehicle information database 92 as a set of data associated with each other. This allows the data center 9 to obtain statistics regarding changes in the condition of the tires of each of the multiple vehicles 1. Specifically, when the gradual change detection flag is turned on, the data center 9 can determine that a change in the condition (deterioration) of the tires has occurred. Furthermore, when the sudden change detection flag is turned on, the data center 9 can determine that a tire has been replaced. Furthermore, the data center 9 can use these statistics as statistics regarding changes in the driver's driving behavior characteristics.

[0082] <Processing flow> 10 is a flowchart showing the flow of processing by the information processing device 200. In this embodiment, the series of processing steps shown in this flowchart are repeatedly executed by the brake ECU 12 at predetermined control intervals. Each step is realized by software processing by the brake ECU 12, but may also be realized by hardware processing by an electric circuit disposed within the brake ECU 12. Hereinafter, step will also be abbreviated as S.

[0083] In S1, the brake ECU 12 acquires data from the sensor group 500. Specifically, the brake ECU 12 acquires the steering wheel angle θ, the steering wheel angular velocity ω, the driving wheel rotation speeds VXFL and VXFR, the driven wheel rotation speeds VXRL and VXRR, the longitudinal acceleration GX, and the lateral acceleration GY.

[0084] In steps S2 to S5, the brake ECU 12 determines whether four conditions for calculating the feature amount are met. Specifically, in step S2, the brake ECU 12 determines whether the vehicle speed V is within a range between a lower limit value LL and an upper limit value UL (see equation (1), the fourth condition according to the present disclosure). In step S3, the brake ECU 12 determines whether the absolute value of the steering angle θ is equal to or less than a reference value θref (see equation (2), the third condition according to the present disclosure). In step S4, the brake ECU 12 determines whether the absolute value of the steering angular velocity ω is equal to or less than a reference value ωref (see equation (3), the first condition according to the present disclosure). In step S5, the brake ECU 12 determines whether the absolute value of the resultant acceleration G is equal to or less than a reference value Gref (see equation (4), the second condition according to the present disclosure). The order of steps S2 to S5 can be changed.

[0085] If all of the conditions in S2 to S5 are met (YES in S2, YES in S3, YES in S4, and YES in S5), the brake ECU 12 proceeds to S6. On the other hand, if at least one of the conditions in S2 to S5 is not met (NO in S2, or NO in S3, or NO in S4, or NO in S5), the brake ECU 12 ends the process without executing the subsequent steps.

[0086] Not all steps S2 to S5 are required. The brake ECU 12 only needs to execute at least one of steps S4 and S5. However, by executing both steps S4 and S5, it is possible to more reliably ensure that the force applied to the tire is within a certain range (that the force applied to the tire does not fluctuate). Furthermore, by executing one or both of steps S2 and S3 in addition to steps S4 and S5, it is possible to more reliably ensure that the force applied to the tire is within a certain range. As a result, it is possible to improve the accuracy of estimating changes in the state of the tire.

[0087] In S6, the brake ECU 12 calculates the left gradient grdL and the right gradient grdR, which are feature quantities. The method for calculating the gradients grdL and grdR has been described in detail with reference to FIG. 7, so the description will not be repeated here. The brake ECU 12 stores the calculated gradients grdL and grdR in association with the corresponding time in the memory 122. The subsequent steps S7 to S12 are executed separately for the left gradient grdL and the right gradient grdR. The left gradient grdL will be described below as a representative example.

[0088] In S7, the brake ECU 12 calculates the gradient integration result ΣgrdL calculated in S6. Then, the brake ECU 12 determines whether the gradient integration result ΣgrdL is equal to or less than the first threshold value TH1. These processes have been described with reference to FIG. 8, so the description will not be repeated. If the gradient integration result ΣgrdL is equal to or less than the first threshold value TH1 (YES in S7), the brake ECU 12 turns on the gradual change detection flag (S8), and if the gradient integration result ΣgrdL is greater than the first threshold value TH1 (NO in S7), the brake ECU 12 turns off the gradual change detection flag (S9).

[0089] In S10, the brake ECU 12 calculates the gradient difference calculated in S6. Then, the brake ECU 12 determines whether the gradient difference ΔgrdL is equal to or greater than the second threshold value TH2. These processes have been described with reference to FIG. 9, and therefore will not be described again. If the gradient difference ΔgrdL is equal to or greater than the second threshold value TH2 (YES in S10), the brake ECU 12 turns on the sudden change detection flag (S11), and if the gradient difference ΔgrdL is less than the second threshold value TH2 (NO in S10), the brake ECU 12 turns off the sudden change detection flag (S12).

[0090] In S13, the brake ECU 12 outputs the flags (on / off of the gradual change detection flag, on / off of the sudden change detection flag) and the feature amounts (gradients grdL, grdR) together with the calculation order (trip count, timestamp, mileage, etc.) to the central ECU 13. The brake ECU 12 may further output the gradient integration result ΣgrdL and / or the gradient difference ΔgrdL. This completes the series of processes.

[0091] As described above, in this embodiment, four conditions are taken into consideration when calculating the gradients grdL and grdR, which are feature quantities. The four conditions are that the steering wheel angle θ, steering wheel angular velocity ω, vehicle speed V, and vector sum of accelerations (resultant acceleration) G are all smaller than predetermined reference values (or within a predetermined range). When these conditions are met, it is ensured and guaranteed that the forces applied to the tires do not fluctuate (are substantially constant), and therefore the gradients grdL and grdR can be calculated without being affected by noise due to external disturbances, driving style, and the like. Therefore, according to this embodiment, changes in the condition of the tires can be estimated with high accuracy.

[0092] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present disclosure is defined by the claims, not by the description of the above embodiments, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0093] 10 Vehicle management system, 1 Vehicle, 11 ADAS-ECU, 12 Brake ECU, 13 Central ECU, 100 Advanced driver assistance system, 121 Processor, 122 Memory, 122A ROM, 122B RAM, 122C Flash memory, 123 Input / output interface, 200 Information processing device, 201 Condition determination unit, 202 Feature calculation unit, 203 Change detection unit, 300 Actuator system, 31 Steering system, 32 Brake system, 33 Powertrain system, 400 Wheel, 41, 42 Drive wheel, 43, 44 Driven wheel, 500 Sensor group, 51 Steering sensor, 521 First wheel speed sensor, 522 Second wheel speed sensor, 523 Third wheel speed sensor, 524 Fourth wheel speed sensor, 53 Acceleration sensor, 9 Data center, 91 Server, 911 Processor, 912 Memory, 92 Vehicle information database, 93 communication devices, NW communication network.

Claims

1. An information processing device mounted on a vehicle including a steering wheel, and drive wheels and driven wheels each having a tire, a processor that calculates a ratio of a rotational speed ratio between the driving wheels and the driven wheels with respect to a longitudinal acceleration of the vehicle when at least one condition is satisfied; The at least one condition is: a first condition that the absolute value of the angular velocity of the steering wheel is smaller than a first reference value; a second condition that the absolute value of the vector sum of the acceleration of the vehicle is smaller than a second reference value; the ratio decreases as the flexibility of the tire decreases, The processor: a signal indicating that a gradual change in the flexibility of the tire has occurred is output when the result of the integration is below a first threshold value; and and an information processing device that outputs a signal indicating that a sudden change in flexibility of the tire has occurred when a difference between a previous value and a current value of the ratio exceeds a second threshold value.

2. The information processing device according to claim 1 , wherein the at least one condition includes both the first condition and the second condition.

3. The information processing device according to claim 2 , wherein the at least one condition further includes a third condition that the absolute value of the angle of the steering wheel is smaller than a third reference value.

4. The information processing device according to claim 3 , wherein the at least one condition further includes a fourth condition that the speed of the vehicle is within a predetermined range.

5. The information processing device according to claim 1 ; The handle; A vehicle comprising the driving wheels and the driven wheels.

6. 1. A method for processing information relating to a vehicle including a steering wheel, and drive wheels and driven wheels each having a tire, comprising: determining whether at least one condition is met; and calculating a ratio of a rotational speed ratio between the driving wheels and the driven wheels with respect to a longitudinal acceleration of the vehicle when the at least one condition is satisfied, The at least one condition is: a first condition that the absolute value of the angular velocity of the steering wheel is smaller than a first reference value; a second condition that the absolute value of the vector sum of the acceleration of the vehicle is smaller than a second reference value; the ratio decreases as the flexibility of the tire decreases, The information processing method includes: a step of integrating a difference from an initial value of the ratio at a predetermined timing, and outputting a signal indicating that a gradual change in flexibility of the tire has occurred when the integration result falls below a first threshold value; The information processing method further includes a step of outputting a signal indicating that a sudden change in flexibility of the tire has occurred when a difference between a previous value and a current value of the ratio exceeds a second threshold value.

7. A program that, when executed by a processor of a computer, causes the computer to process information about a vehicle including a steering wheel, and drive wheels and driven wheels each having a tire, determining whether at least one condition is met; and calculating a ratio of a rotational speed ratio between the driving wheels and the driven wheels with respect to a longitudinal acceleration of the vehicle when the at least one condition is satisfied, The at least one condition is: a first condition that the absolute value of the angular velocity of the steering wheel is smaller than a first reference value; a second condition that the absolute value of the vector sum of the acceleration of the vehicle is smaller than a second reference value; the ratio decreases as the flexibility of the tire decreases, The program a step of integrating a difference from an initial value of the ratio at a predetermined timing, and outputting a signal indicating that a gradual change in flexibility of the tire has occurred when the integration result falls below a first threshold value; The program further includes a step of outputting a signal indicating that a sudden change in flexibility of the tire has occurred when a difference between a previous value and a current value of the ratio exceeds a second threshold value.

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