Tire rotation speed correction device

Abstract

To early find a change in a regression equation for correcting a rotational speed.SOLUTION: A correction device includes a rotational speed acquisition unit, a comparison value calculation unit, a torque acquisition unit, a regression equation specifying unit, a rotational speed correction unit, and a verification unit. The rotational speed acquisition unit acquires rotational speeds of a first tire and a second tire mounted on a vehicle. The comparison value calculation unit calculates a comparison value for comparing the rotational speed of the first tire and the rotational speed of the second tire. The torque acquisition unit acquires wheel torque. The regression equation specifying unit calculates, based on the comparison value and the wheel torque, a parameter for specifying a regression equation which is obtained by modeling the comparison value. The rotational speed correction unit calculates, based on the rotational speed of the second tire and the parameter, a rotational speed of the first tire in which an influence of a slip is cancelled. The verification unit compares an estimated comparison value based on the wheel torque and the parameter calculated by the regression equation specifying unit, with the comparison value calculated by the comparison value calculation unit.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a correction device, method, and program for correcting the rotational speed of one or more tires mounted on a vehicle. [Background technology]

[0002] Patent Document 1 discloses a correction device for correcting the rotational speed of a tire mounted on a vehicle. More specifically, the correction device cancels out the effects of slip caused by wheel torque, the effect of lateral acceleration on the wheel torque dependence of slip, and the effect of load transfer caused by lateral acceleration from the tire rotational speed obtained from a rotational speed sensor. The tire rotational speed, from which the effects of slip and load transfer have been canceled out, can be used, for example, in a Tire Pressure Monitoring System (TPMS) that automatically detects tire pressure reduction using the Dynamic Loaded Radius (DLR) method. According to Patent Document 1, in the DLR method, tire pressure reduction is detected based on three pressure reduction index values ​​called DEL1 to DEL3, which are calculated based on the rotational speed of the tires mounted on each wheel of the vehicle. As in Patent Document 1, the accuracy of pressure reduction detection is further improved by calculating the pressure reduction index values ​​DEL1 to DEL3 based on the corrected rotational speed. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2020-012766 [Overview of the project] [Problems that the invention aims to solve]

[0004] Patent Document 1 calculates a parameter that identifies a regression equation modeled using wheel torque and lateral acceleration, comparing the rotational speed of the front and rear tires to determine a rotational speed where the effects of wheel torque and lateral acceleration are canceled out. This parameter is calculated sequentially based on data acquired while the vehicle is in motion, but if the tire pressure gradually decreases during driving, it will change gradually in accordance with the change in the dynamic load radius of the tire. Therefore, even if the tire pressure decreases while the vehicle is in motion, as long as the vehicle continues to move, the pressure reduction index value calculated based on the corrected rotational speed will only change slowly, resulting in a time lag between the occurrence of tire pressure reduction and the detection of pressure reduction. However, this is not taken into consideration in Patent Document 1. It should be noted that the above applies not only to cases where tire pressure reduction is detected, but also to cases where the corrected rotational speed is used to estimate the road surface conditions, etc.

[0005] The present invention aims to provide a correction device, method, and program that can detect changes in the regression equation used to correct the rotational speed of a tire, based on a regression equation that models a comparison value between the rotational speed of the front tire and the rotational speed of the rear tire using elements that affect the dynamic load radius of the tire. [Means for solving the problem]

[0006] A correction device according to a first aspect of the present invention is a correction device for correcting the rotational speed of a first tire mounted on a vehicle, and comprises a rotational speed acquisition unit, a comparison value calculation unit, a torque acquisition unit, a regression equation identification unit, a rotational speed correction unit, and a verification unit. The rotational speed acquisition unit acquires the rotational speeds of the first tire and the second tire mounted on the vehicle. The comparison value calculation unit calculates a comparison value comparing the rotational speed of the first tire and the rotational speed of the second tire. The torque acquisition unit acquires the wheel torque. The regression equation identification unit calculates parameters to identify a regression equation that models the comparison value and includes an element dependent on the wheel torque, based on the comparison value and the wheel torque. The rotational speed correction unit calculates the rotational speed of the first tire in which the effect of slip that the wheel torque has on the comparison value is canceled out, based on the rotational speed of the second tire and the parameters. The verification unit compares an estimated comparison value estimated based on the wheel torque acquired by the torque acquisition unit and the parameters calculated by the regression equation identification unit with the comparison value calculated by the comparison value calculation unit. One of the first tire and the second tire is a front tire, and the other is a rear tire, with the first tire being subjected to a greater driving force than the second tire.

[0007] A correction device according to a second aspect of the present invention is a correction device according to a first aspect, wherein the verification unit initializes or modifies the regression equation identified by the regression equation identification unit based on the difference between the estimated comparison value and the comparison value.

[0008] A correction device according to a third aspect of the present invention is a correction device according to a second aspect, wherein the verification unit initializes or modifies the regression equation identified by the regression equation identification unit when the moving average of the difference exceeds a predetermined threshold or falls below a predetermined threshold.

[0009] A correction device according to a fourth aspect of the present invention is a correction device according to any of the first or third aspects, further comprising a lateral acceleration acquisition unit that acquires the lateral acceleration applied to the vehicle. The regression equation further includes elements that synergistically depend on the wheel torque and the lateral acceleration and elements that depend on the lateral acceleration alone. The verification unit compares an estimated comparison value estimated based on the wheel torque acquired by the torque acquisition unit, the lateral acceleration acquired by the lateral acceleration acquisition unit, and the regression equation identified by the regression equation identification unit with the comparison value calculated by the comparison value calculation unit.

[0010] A correction device according to the fifth aspect of the present invention is a correction device according to any of the first or fourth aspects, wherein the comparison value calculation unit calculates a first comparison value as the comparison value, which compares the rotational speed of one front tire with the rotational speed of one rear tire among the two front tires and two rear tires mounted on the vehicle, and calculates a second comparison value which compares the rotational speed of the other front tire with the rotational speed of the other rear tire.

[0011] A correction device according to the sixth aspect of the present invention is a correction device according to any one of the first or fifth aspects, further comprising a pressure reduction index calculation unit that calculates a pressure reduction index value by comparing the rotation speed of any two of the four tires mounted on the vehicle with the rotation speed of the remaining two tires, based on the rotation speed of the second tire and the rotation speed of the first tire calculated by the rotation speed correction unit, and detects pressure reduction of at least one of the tires by comparing the pressure reduction index value with a predetermined pressure reduction threshold.

[0012] A correction device according to the seventh aspect of the present invention is a correction device according to the sixth aspect, further comprising an alarm output unit that outputs a pressure reduction alarm when a pressure reduction state of the tire is detected.

[0013] The correction device according to the eighth aspect of the present invention is a correction device according to any of the first or seventh aspects, wherein the comparative value is the ratio of the rotational speed of the first tire to the rotational speed of the second tire.

[0014] A corrective device according to the ninth aspect of the present invention is a corrective device according to any of the first or eighth aspects, wherein the first tire is a drive wheel tire and the second tire is a driven wheel tire.

[0015] A correction method according to the tenth aspect of the present invention is a correction method for correcting the rotational speed of a first tire mounted on a vehicle, which is executed by a computer, and includes the following. Furthermore, a correction program according to the eleventh aspect of the present invention is a correction program for correcting the rotational speed of a first tire mounted on a vehicle, which causes a computer to execute the following. Note that one of the first tire and the second tire is a front tire, and the other is a rear tire, and the first tire is a tire to which a greater driving force is applied than that of the second tire. (1) To obtain the rotational speed of the first tire and the second tire mounted on the vehicle. (2) Calculate a comparison value that compares the rotational speed of the first tire with the rotational speed of the second tire. (3) Obtain the wheel torque. (4) Based on the comparative value and the wheel torque, calculate parameters to identify a regression equation that models the comparative value and includes an element dependent on the wheel torque. (5) Based on the rotational speed of the second tire and the parameters, calculate the rotational speed of the first tire after the effect of slip on the comparison value by the wheel torque has been canceled out. (6) Compare the wheel torque obtained and the estimated comparison value estimated based on the calculated parameters with the calculated comparison value. [Effects of the Invention]

[0016] From the above perspective, the verification unit compares the estimated comparison value, which is estimated based on a regression equation that models the comparison value, with the comparison value that was used to identify the regression equation. This allows for early detection of cases where the regression equation for correcting the rotation speed of the first tire is estimated to have changed due to factors such as tire pressure reduction. [Brief explanation of the drawing]

[0017] [Figure 1] A schematic diagram showing how a correction device according to one embodiment of the present invention is mounted on a vehicle. [Figure 2] A block diagram showing the electrical configuration of the correction device. [Figure 3] A flowchart showing the flow of the pressure reduction determination process, including rotational speed correction processing. [Figure 4] A graph plotting comparative values ​​against wheel torque. [Figure 5] Graphs showing the moving average of time-series residuals in the examples and comparative examples. [Figure 6] Graphs showing time-series pressure reduction index values ​​in the examples and comparative examples. [Modes for carrying out the invention]

[0018] The correction device, method, and program according to one embodiment of the present invention will be described below with reference to the drawings.

[0019] <1. Configuration of the Correction Device> Figure 1 is a schematic diagram showing how the correction device 2 according to this embodiment is mounted on a vehicle 1. The vehicle 1 is a four-wheeled vehicle and is equipped with a left front wheel FL, a right front wheel FR, a left rear wheel RL, and a right rear wheel RR. The wheels FL, FR, RL, and RR are each equipped with tires T FL ,T FR ,T RL ,T RR The vehicle 1 according to this embodiment is a front-engine, front-wheel-drive (FF) vehicle, and the front wheels are tires T FL ,T FRis a drive wheel tire, and is a rear wheel tire, tire T RL ,T RR is a driven wheel tire. Therefore, tire T FL ,T FR is applied with a driving force greater than that of tire T RL ,T RR . Therefore, in this embodiment, tire T FL ,T FR corresponds to the first tire, and tire T RL ,T RR corresponds to the second tire.

[0020] The correction device 2 cancels the influence of the slip of the drive wheel tire T FL ,T FR and corrects the measured rotational speed of the drive wheel tire T FL ,T FR . Further, the correction device 2 is based on the rotational speed of the drive wheel tire T FL ,T FR corrected in this way, and the measured rotational speed of the driven wheel tire T RL ,T RR to determine the presence or absence of decompression of tire T FL ,T FR ,T RL ,T RR . The correction device 2 calculates a decompression index value based on the dynamic load radius (DLR) method, and based on this, when decompression of tire T FL ,T FR ,T RL ,T RR is detected, an alarm to that effect is output via the indicator 3 mounted on the vehicle 1. Details of the flow of the process of correcting the rotational speed of the drive wheel tire T FL ,T FR (hereinafter sometimes referred to as the rotational speed correction process), and the process of determining the decompression of tire T FL ,T FR ,T RL ,T RR (hereinafter sometimes referred to as the decompression determination process) will be described later.

[0021] In this embodiment, tire T FL,T FR ,T RL ,T RR The pressure reduction state is detected based on these rotational speeds V1~V4. Tire T FL ,T FR ,T RL ,T RR (More precisely, Tire T FL ,T FR ,T RL ,T RR Each wheel (on which the vehicle is mounted) is fitted with a wheel speed sensor 6, which detects the wheel speed information of the wheel it is mounted on (i.e., the rotational speed information of each tire). The wheel speed sensors 6 are connected to the correction device 2 via a communication line 5, and the wheel speed information detected by each wheel speed sensor 6 is transmitted to the correction device 2 in real time.

[0022] Any wheel speed sensor 6 can be used as long as it can detect the wheel speeds of the FL, FR, RL, and RR wheels while the vehicle is in motion. For example, a sensor that measures 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 wheel speed from the voltage generated 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.

[0023] A wheel torque sensor (hereinafter referred to as WT sensor) 7 is attached to the left front wheel, which is one of the drive wheels FL of vehicle 1. The WT sensor 7 detects the wheel torque WT of vehicle 1. The WT sensor 7 is connected to the correction device 2 via a communication line 5, and the wheel torque WT information detected by the WT sensor 7 is transmitted to the correction device 2 in real time.

[0024] The WT sensor 7 is not particularly limited in structure or mounting position, as long as it can detect the wheel torque of the drive wheels of vehicle 1. Various types of wheel torque sensors are commercially available, and their configurations are well known, so a detailed explanation is omitted here. Furthermore, it is possible to detect wheel torque without using the WT sensor 7; for example, wheel torque can be estimated from the engine torque obtained from the engine control device and the tire diameter.

[0025] Vehicle 1 is equipped with a lateral acceleration sensor 4 that detects the lateral acceleration α applied to Vehicle 1. The mounting position of the lateral acceleration sensor 4 is not particularly limited and can be selected as appropriate. The lateral acceleration sensor 4 is connected to the correction device 2 via a communication line 5. The lateral acceleration information detected by the lateral acceleration sensor 4 is transmitted to the correction device 2 in real time, along with the wheel speed information and wheel torque WT information.

[0026] Figure 2 is a block diagram showing the electrical configuration of the correction device 2. As shown in Figure 2, the correction device 2 is a control computer mounted on the vehicle 1 as hardware, and 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 lateral acceleration sensor 4, a wheel speed sensor 6, a WT sensor 7, and a display unit 3. The ROM 13 stores a program 8 for controlling the operation of various parts of the vehicle 1. The program 8 is written to the ROM 13 from a storage medium or writing device such as a CD-ROM. The CPU 12 reads and executes the program 8 from the ROM 13, and thereby virtually operates as a rotational speed acquisition unit 21, a torque acquisition unit 22, a lateral acceleration acquisition unit 23, a comparison value calculation unit 24, a regression equation identification unit 25, a rotational speed correction unit 26, a verification unit 27, a DEL calculation unit (pressure reduction index value calculation unit) 28, and an alarm output unit 29. Details of the operation of each unit 21 to 29 will be described later. The storage device 15 consists of a hard disk, flash memory, etc. Note that the storage location for program 8 may be the storage device 15 instead of ROM 13. RAM 14 and storage device 15 are used as appropriate for calculations by the CPU 12.

[0027] The display unit 3 can be implemented in any form, such as a liquid crystal display element, liquid crystal monitor, plasma display, organic EL display, etc., as long as it can inform the user that a pressure drop is occurring. For example, the display unit 3 is a four-wheel tire T FL ,T FR ,T RL ,T RR Four lamps corresponding to each of the four points can be arranged to match the actual arrangement of the tires. The mounting position of the display unit 3 can also 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. When the correction device 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, the warnings can be displayed as icons or text information on the monitor.

[0028] <2. Pressure Depressure Detection Process> The following refers to the drive wheel tire T, with reference to Figure 3. FL ,T FR Includes a rotation speed correction process to correct the rotation speed of the tire T FL ,T FR ,T RL ,T RR The pressure reduction determination process for determining the pressure reduction will now be explained. The process shown in Figure 3 is executed repeatedly while power is supplied to the electrical system of vehicle 1. For example, step S1 starts when vehicle 1 starts moving, the process up to step S12 is executed repeatedly while vehicle 1 is moving, and then ends when vehicle 1 stops.

[0029] In step S1, the rotation speed acquisition unit 21 acquires V1 to V4. Here, V1 to V4 are the tire T FL ,T FR ,T RL ,T RR The rotational speeds are, in other words, the wheel speeds of wheels FL, FR, RL, and RR. The rotational speed acquisition unit 21 receives the output signal from the wheel speed sensor 6 at a predetermined sampling period ΔT and converts it into rotational speeds V1 to V4.

[0030] In the following step S2, the torque acquisition unit 22 acquires the wheel torque WT of the vehicle 1. The torque acquisition unit 22 receives the output signal from the WT sensor 7 and converts it into the wheel torque WT. The output signal from the WT sensor 7 received at this time is data from the same time or approximately the same time as the output signal from the wheel speed sensor 6 received in the most recent step S1.

[0031] In the following step S3, the lateral acceleration acquisition unit 23 acquires the lateral acceleration α applied to the vehicle 1. The lateral acceleration acquisition unit 23 receives the output signal from the lateral acceleration sensor 4 and converts it into the lateral acceleration α. ​​The output signal from the lateral acceleration sensor 4 received at this time is data from the same time or approximately the same time as the output signal from the wheel speed sensor 6 received in the most recent step S1.

[0032] In the following step S4, the comparison value calculation unit 24 calculates the tire T FL ,T FR ,T RL ,T RR From the rotational speeds V1 to V4, the comparison values ​​H1 and H2 between the rotational speed of the front tires and the rotational speed of the rear tires are calculated, respectively. The comparison values ​​H1 and H2 are values ​​that decrease as the front wheel speed increases and increase as the rear wheel speed increases, or values ​​that increase as the front wheel speed increases and decrease as the rear wheel speed increases.

[0033] The comparative values ​​H1 and H2 can be defined in various ways as long as they have the above characteristics, but in this embodiment, H1 and H2 are calculated according to the following formula. That is, in this embodiment, the comparative value H1 is the left front tire T, which is one of the drive wheels. FL The rotational speed V1 and the drive wheel tire T FL Similarly, the left rear wheel tire T is a driven wheel tire mounted on the left side of vehicle 1. RL This is a comparison value that compares the rotational speed V3 of the other wheel, and is expressed in the form of a ratio of the latter to the former. The comparison value H2 is the right front wheel tire T, which is the other drive wheel tire. FR The rotational speed V2 and the drive wheel tire T FR Similarly, the right rear wheel tire T is a driven wheel tire mounted on the right side of vehicle 1. RR This is a comparison value used to compare the rotational speed V4 with the value of the former, and is expressed in the form of a ratio of the latter to the former. H1 = V3 / V1 H2 = V4 / V2

[0034] H1 and H2 are not limited to the definitions above, but can also be defined as follows. H1=V3 2 / V1 2 H2=V4 2 / V2 2

[0035] Alternatively, H1 and H2 can be defined as follows: H1 = V4 / V1 H2 = V3 / V2

[0036] The comparison value H1 defined above is the same as the two front tires T FL ,T FR and two rear wheel tires T RL ,T RR The first comparison value is a comparison between the rotation speed of one front tire and the rotation speed of the other rear tire. Furthermore, the comparison value H2 defined above is the rotation speed of the two front tires T FL ,T FR and two rear wheel tires T RL ,T RR This is the second comparison value, which compares the rotation speed of the other front tire with the rotation speed of the other rear tire.

[0037] The data sets obtained in steps S1 to S4, consisting of wheel speeds V1 to V4, wheel torque WT, lateral acceleration α, and comparison values ​​H1 and H2 at the same or approximately the same time, are stored in RAM 14 or storage device 15. Steps S1 to S4 are executed repeatedly, and when the number of stored data sets exceeds a preset number N, the process proceeds to step S5.

[0038] In step S5, the regression equation identification unit 25 calculates parameters (x0, x1, x2, x3) and (y0, y1, y2, y3) that identify regression equations L1 and L2, respectively, which model the comparison values ​​H1 and H2, based on the data set of wheel torque WT, lateral acceleration α, and comparison values ​​H1 and H2 stored in RAM 14 or storage device 15, and stores them in RAM 14 or storage device 15. Regression equations L1 and L2 can be defined, for example, as follows. L1:H1=x0WT+x1WTα+x2α+x3 L2:H2=y0WT+y1WTα+y2α+y3

[0039] As disclosed in Patent Document 1, x0WT and y0WT are elements that respectively reflect the ease of tire slip according to the wheel torque WT and depend on the wheel torque WT alone. x1WTα and y1WTα are elements that respectively reflect the change in the ease of slip according to the wheel torque WT during turning and depend synergistically on the wheel torque WT and the lateral acceleration α. x2α and y2α are elements that respectively reflect the asymmetry in the front and rear wheels of the rotational speed change during turning and depend on the lateral acceleration α alone.

[0040] Here, to calculate the parameters (x0, x1, x2, x3) and (y0, y1, y2, y3), a plurality of data sets of (WT, H1, α) and (WT, H2, α) are required. Therefore, in this embodiment, steps S1 to S4 are repeatedly executed until a predetermined amount N (where N ≧ 3) of data sets is accumulated. The predetermined amount N may be determined in advance in light of the reliability of the calculated parameters, the required computing resources, and other factors. And once the number of data sets exceeds N, each time a new data set is obtained, the parameters (x0, x1, x2, x3) and (y0, y1, y2, y3) that specify the regression equations L1 and L2 are calculated using the latest predetermined amount of data sets. In this calculation, in this embodiment, for each of the comparison values H1 and H2, a state space model represented by the following state equation and observation equation is defined. In the formula, X n is a parameter vector that is a 4-dimensional real vector and corresponds to the parameters (x0, x1, x2, x3) and (y0, y1, y2, y3). c n is a 4-dimensional real vector having WT, WTα, α, and 1 as elements. e n is a normal white noise with an average of 0 and a variance of σ 2 .

Equation

Equation

[0041] In this embodiment, the parameter vector X in the above state space model n is sequentially estimated by a Kalman filter. However, the estimation method is not limited to the method using a Kalman filter. For example, the least squares method can be used, and for improving the efficiency of calculation, a recursive least squares method or the like can also be used.

[0042] In step S6, the rotational speed correction unit 26 uses the parameter vector X estimated in step S5 n as a parameter for specifying the regression equations L1 and L2, and calculates the corrected rotational speeds V1′ and V2′ of the tires T FL , T FR . The rotational speeds V1′ and V2′ are calculated based on the rotational speeds V3 and V4 of the rear-wheel tires when the wheel torque WT is 0 (N·m) and the lateral acceleration α is 0 (m / s 2 ). That is, V1′ = V3 / x3 and V2′ = V4 / y3 are calculated respectively.

[0043] In steps S7 to S9, the verification unit 27 verifies the regression equations L1 and L2. More specifically, in steps S7 to S9, it is verified whether the parameters (x0, x1, x2, x3), (y0, y1, y2, y3) calculated based on the latest N data sets and the regression equations L1 and L2 specified thereby are greatly deviated from the latest data sets of (WT, H1, α) and (WT, H2, α). The verification unit 27 substitutes the wheel torque WT n and the lateral acceleration α n which are the bases for calculating this parameter into the following formula (1) represented by the parameter (x0, x1, x2, x3) specified by the regression equation specifying unit 25 and the white Gaussian noise e1 n to calculate an estimated comparison value I1 n (step S7). The estimated comparison value I1 n is an estimated comparison value estimated based on the wheel torque WT n acquired by the torque acquisition unit 22 and the parameter specified by the regression equation specifying unit 25. The verification unit 27 calculates the estimated comparison value I1 nand the comparison value H1 based on the data actually acquired by the correction device 2 n The comparison is performed (step S8). Similarly, the verification unit 27 compares the parameters (y0, y1, y2, y3) with the normal white noise e2 n The following equation (2), which is expressed as the wheel torque WT used to calculate this parameter, is expressed as follows: n and lateral acceleration α n Substitute this into the estimated comparison value I2 n Calculate (Step S7), and estimate the comparative value I2 using the method described later. n Comparison value H2 n Compare with (Step S8). I1 n =x0WT n +x1WT n α n +X2α n +x3+e1 n (1) I2 n =y0WT n +y1WT n α n +y2α n +y³+e² n (2)

[0044] Such verification is performed for the following reasons. The parameters (x0, x1, x2, x3), (y0, y1, y2, y3) and the regression equations L1 and L2 specified by them may change due to factors affecting the dynamic load radius of the tire relative to the wheel torque WT, in addition to the changes in slip susceptibility and load transfer mentioned above—for example, tire pressure reduction, changes in the road surface, etc. For example, consider the case where one of the front and rear tires on the same side of vehicle 1 gradually loses pressure. As the dynamic load radius of the depressurized tire gradually decreases, the comparative value H1 or H2 relative to the wheel torque WT also gradually changes in one direction. The inventor confirmed this experimentally. Figure 4 is a graph plotting the comparative value H1 relative to the wheel torque WT for the case where the tire attached to the FR wheel of the vehicle is at normal pressure and the case where it gradually loses pressure. This graph shows that when the FR wheel tire pressure gradually decreases, the (WT,H1) data set tends to deviate downwards from the (WT,H1) data set for normal pressure as the comparative value H1 decreases.

[0045] As described above, the parameters that determine the regression equations L1 and L2 are sequentially determined based on multiple (WT, H1, α) and (WT, H2, α) datasets, respectively. Therefore, even after tire pressure decompression occurs, the dataset acquired under normal pressure conditions is reflected in the parameters for a certain period, and the fluctuations in the comparison values ​​H1 and H2 are also gradual. As a result, there is a time lag from the actual occurrence of pressure decompression until it becomes possible to distinguish between normal pressure conditions and decompression conditions based on the rotational speed corrected using the above parameters. In the above experiment, we considered the case where the FR wheel tire decompressed, but the same applies when other tires decompress, or when multiple tires decompress, such as the FL wheel and RR wheel tires, decompress. In addition to tire pressure decompression, the relationship between wheel torque WT and comparison values ​​H1 and H2 may also change if, for example, the slipperiness of the road surface on which vehicle 1 is traveling changes. Therefore, fluctuations in the regression equations L1 and L2 can also be caused by changes in the road surface.

[0046] If there is no change in the regression equation L1 described above, the comparison value H1 for N datasets related to the regression equation L1 is n and estimated comparison value I1 n The residual R1 is the difference from the above. n (=H1 n -I1 n ) can be assumed to follow a distribution with a constant variance and a mean of 0. Similarly, if there is no change in the regression equation L2 described above, the comparison value H2 for N datasets related to the regression equation L2 n And the estimated comparative value I2 n The residual R2 is the difference from the above. n (=H2 n -I2 n ) can be assumed to follow a distribution with a constant variance and a mean of 0. In contrast, if there is a change in the regression equations L1 and L2, as mentioned above, the change is unidirectional. For this reason, the residual R1 for N datasets n ,R2 n The average value is expected to deviate from 0. The verification unit 27 uses this to perform the following processing.

[0047] Referring again to Figure 3, in step S8, the verification unit 27 checks the residual R1 n and R2 n The following values ​​are calculated and stored in RAM14 or storage device15. Then, the residual R1 n and R2 n Regarding this, the moving average R1 is calculated using the same method as in step S8 performed so far. a and R2 a These are calculated separately. In addition to the simple moving average, weighted moving averages and exponential moving averages can be used as moving averages.

[0048] In step S9, the verification unit 27 checks the moving average R1 calculated in step S8. a and R2 aThe unit determines whether the values ​​are below the lower threshold or above the upper threshold. The lower and upper thresholds for initialization are predetermined by experiment or simulation and can be stored in the storage device 15 or ROM 13. The verification unit 27 determines the moving average R1 a and R2 a If it is determined that at least one of the values ​​is below the lower threshold for initialization or above the upper threshold (NO), step S10 is executed. The verification unit 27 determines that the moving average R1 a and R2 a If it is determined that both conditions are above the lower threshold and below the upper threshold (YES), step S11 is executed.

[0049] Step S10 is executed when it is estimated that at least one of the parameters that identify regression equations L1 and L2 deviates significantly from the latest (WT,H1,α) and (WT,H2,α) datasets, suggesting the possibility of tire pressure deceleration. In step S10, the verification unit 27 initializes the regression equations by initializing the parameters that identify the regression equations that are estimated to be deviating. That is, the parameters calculated sequentially in step S5 are erased from RAM 14 or storage device 15, step S1 is executed again, and the processing described above is repeated thereafter. As a result, when tire pressure deceleration is suspected, regression equations L1 and L2 can be updated without waiting for all N accumulated (WT,H1,α) and (WT,H2,α) datasets to be replaced with datasets from the suspected pressure deceleration state. In other words, when tire pressure deceleration occurs, the reflection in the pressure deceleration index value calculated below is accelerated, and the time lag between pressure deceleration determination and subsequent alarm output can be shortened.

[0050] On the other hand, the processing from step S11 onwards is a pressure reduction determination process in which the corrected rotational speeds V1' and V2' are used instead of the following rotational speeds V1 and V2, respectively. In step S11, the DEL calculation unit 28 calculates pressure reduction index values ​​DEL1 to DEL3 for determining the pressure reduction state of the tire. DEL1, DEL2, and DEL3 are index values ​​that have the following characteristics, respectively. DEL1: An index value that increases as rotational speeds V1 and V4 increase, and decreases as rotational speeds V2 and V3 increase, or increases as rotational speeds V2 and V3 increase, and decreases as rotational speeds V1 and V4 increase. DEL2: An index value that increases as rotational speeds V1 and V2 increase, and decreases as rotational speeds V3 and V4 increase, or increases as rotational speeds V3 and V4 increase, and decreases as rotational speeds V1 and V2 increase. DEL3: An index value that increases as rotational speeds V1 and V3 increase, and decreases as rotational speeds V2 and V4 increase, or increases as rotational speeds V2 and V4 increase, and decreases as rotational speeds V1 and V3 increase.

[0051] DEL1 to DEL3 can be defined in various ways as long as they have the above characteristics, but in this embodiment, DEL1 to DEL3 are calculated according to the following formula. DEL1=[(V1+V4) / (V2+V3)-1]*100(%) DEL2=[(V1+V2) / (V3+V4)-1]*100(%) DEL3=[(V1+V3) / (V2+V4)-1]*100(%)

[0052] In other embodiments, for example, DEL1 to DEL3 can be defined as follows: DEL1=[[(V1+V4) / 2-(V2+V3) / 2] / (V1+V2+V3+V4)]*100(%) DEL2=[[(V1+V2) / 2-(V3+V4) / 2] / (V1+V2+V3+V4)]*100(%) DEL3=[[(V1+V3) / 2-(V2+V4) / 2] / (V1+V2+V3+V4)]*100(%)

[0053] Alternatively, DEL1 to DEL3 can be defined as follows: DEL1=(V1 2 +V4 2 )-(V2 2 +V3 2 ) DEL2=(V1 2 +V2 2 )-(V3 2 +V4 2 ) DEL3=(V1 2 +V3 2 )-(V2 2 +V4 2 )

[0054] Tire T FL ,T FR ,T RL ,T RR As the pressure decreases, the respective dynamic load radii decrease, causing the respective rotational speeds V1 to V4 to increase and the values ​​of the pressure reduction index values ​​DEL1 to DEL3 to change. In the pressure reduction detection process according to this embodiment, the change from the reference value of the pressure reduction index values ​​DEL1 to DEL3 is detected, and the tire T FL ,T FR ,T RL ,T RR The system determines which of the tires is experiencing pressure loss. More specifically, the pressure loss can be identified using the following 14 patterns. (1)T FL Depressurization only (2)T FR Depressurization only (3)T RL Depressurization only (4)T RR Depressurization only (5)T FL ,T FR Depressurization only (6)T FL ,T RL Depressurization only (7)T FL ,T RR Depressurization only (8)T FR ,T RL Depressurization only (9)T FR ,T RR Depressurization only (10)T RL ,T RR Depressurization only (11)T FL ,T FR ,T RL Depressurization only (12)T FL ,T RL ,T RR Depressurization only (13)T FL ,T FR ,T RR Depressurization only (14)T FR ,T RL ,T RR Depressurization only

[0055] In the following step S12, the DEL calculation unit 28 determines the pressure reduction state. Specifically, the DEL calculation unit 28 first uses DEL1 to DEL3 calculated in step S11 to detect one-wheel pressure reduction (1) to (4), two-wheel pressure reduction (5) to (10), and three-wheel pressure reduction (11) to (14) among the 14 pressure reduction tire patterns described above. More specifically, it determines whether each of DEL1 to DEL3 has increased above a threshold, decreased above a threshold, or the amount of change is below a threshold, and determines which pattern the tire pressure is in based on the combination of these results. The relationship between the change patterns of DEL1 to DEL3 and the pressure reduction tire patterns is shown in Table 1, for example. The upper and lower threshold values ​​used here are determined for each of DEL1 to DEL3 through experiments or simulations using vehicle 1 and are pre-stored in ROM 13 or storage device 15. [Table 1]

[0056] The DEL calculation unit 28 determines whether a pressure reduction has been identified in any of the patterns (1) to (14). If no pressure reduction has been identified in any of the patterns (NO), the process returns to step S1. On the other hand, if a pressure reduction has been identified in any of the patterns (YES), step S13 is executed.

[0057] In step S13, the alarm output unit 29 outputs a pressure reduction alarm via the display unit 3. At this time, the display unit 3 can distinguish which tire is experiencing pressure reduction and issue an alarm, or it can simply indicate that any tire is experiencing pressure reduction. The pressure reduction alarm can also be performed as an audio output.

[0058] <3. Variant> 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.

[0059] <3-1> The method for acquiring data on the lateral acceleration α of vehicle 1 is not limited to that described in the above embodiment. For example, if vehicle 1 is equipped with a yaw rate sensor, the lateral acceleration α can also be obtained from the output value of the yaw rate sensor. In other words, the lateral acceleration sensor 4 can be omitted.

[0060] <3-2> In the above embodiment, the rotational speeds V1' and V2' obtained in step S6 were used for tire pressure reduction detection. However, the processes in steps S1 to S6 are not limited to tire pressure reduction detection; they can also be used in processes such as estimating the slipperiness of the road surface based on the tire rotational speed.

[0061] <3-3> In the above embodiment, H1 and H2 were calculated in step S4, but depending on the vehicle characteristics and as needed, only H1 or only H2 may be calculated. In this case, the tire TFL or T FR One of the rotational speeds will be corrected.

[0062] <3-4> The tire rotation speed correction function according to the present invention can also be applied to rear-wheel drive vehicles. In that case, the rotation speeds V3 and V4 of the rear wheels, which are the drive wheels, can be corrected by the same process as in the above embodiment. Furthermore, this function can also be applied to four-wheel drive vehicles when the torque distribution is constant, and the rotation speed of the tire to which a greater driving force is applied among the front and rear wheels can be corrected. Moreover, this function is not limited to four-wheel vehicles, but can also be applied to three-wheel vehicles or six-wheel vehicles, etc. Also, as mentioned in the above embodiment, this function can be applied not only to front-engine vehicles but also to rear-engine vehicles, etc. In this case, the rear wheels correspond to the first wheels, and the front wheels correspond to the second wheels.

[0063] <3-5> The rotational speeds V1' and V2' are not limited to the case where the wheel torque WT is 0 (N·m), but are also small enough that no or very little tire slip occurs. R The standard wheel torque WT is determined. R It can also be determined from the lateral acceleration α (where α is substituted as 0) and the comparison values ​​H1 and H2.

[0064] <3-6> The comparison values ​​H1 and H2 can also be defined as follows: H1 = V1 / V3 H2 = V2 / V4

[0065] Alternatively, the comparison values ​​H1 and H2 can be defined as follows: H1 = V1 / V4 H2 = V2 / V3

[0066] <3-7> The elements of regression equations L1 and L2 that depend on lateral acceleration α are not limited to forms that include a linear term of α, such as x²α and y²α, but may also include, in addition to or instead of, a linear term of α. 2 The equations may include terms of order of magnitude or higher of α. Furthermore, the elements of the regression equations L1 and L2 that synergistically depend on the wheel torque WT and lateral acceleration α may be expressed in a form in which WT is multiplied by a term of order of magnitude or higher of α, in addition to or instead of the form in which WT is multiplied by a first-order term of α (WTα).

[0067] <3-8> In the above embodiment, the regression equations L1 and L2 included elements that depended on the wheel torque WT as well as elements that depended on the lateral acceleration α, but these may be omitted. That is, the regression equations L1 and L2 may be defined by elements that depend only on the wheel torque WT.

[0068] <3-9> In step S10, as an initialization step, the parameters that identify regression equations L1 and L2 were removed, and then the parameters that identify regression equations L1 and L2 were estimated based on newly acquired datasets. However, the method for updating the parameters that identify regression equations L1 and L2 is not limited to this initialization. For example, regression equations L1 and L2 may be modified by replacing the parameters that identify regression equations L1 and L2, which were estimated based only on the most recent data, with parameters that were calculated sequentially. [Examples]

[0069] The following describes embodiments of the present invention. However, the present invention is not limited to the following embodiments.

[0070] Time-series datasets of rotational speed V1-V4, wheel torque WT, and lateral acceleration α were obtained while a vehicle (FF vehicle) with all tires at normal pressure was in motion. Based on this time-series dataset, a hypothetical time-series dataset was created, assuming that the tire pressure of the front wheel (FL) begins to decrease 1000 seconds after the start of vehicle operation (0 seconds), and then decreases by 5% per minute thereafter. Using this hypothetical dataset, a pressure reduction judgment algorithm including the initialization of the regression equation (L1 only) according to the above embodiment was applied to calculate the time-series pressure reduction index value DEL1 (Example). Moving average R1 for initialization a The lower limit threshold was set to -60. Furthermore, using the same hypothetical dataset, a depressurization determination algorithm without initialization of the regression equation according to the above embodiment was applied to calculate the time-series depressurization index value DEL1 (comparative example). For these cases, the timing at which the depressurization index value DEL1 exceeded a predetermined depressurization threshold was compared.

[0071] Residual R1 in the Examples and Comparative Examples n The moving average R1 of the time series a (t) was calculated based on the following exponential moving average formula. N=200.

number

[0072] For reference, Figure 5 shows R1 in the example. a (t) and R1 relating to the comparative example a The time series graph of (t) is shown. R1 related to the example. a (t) returned to near 0 before 1500 seconds had elapsed due to initialization after reaching the threshold of -60. On the other hand, R1 in the comparative example a (t) once reached the threshold of -60 and never returned to near 0.

[0073] Figure 6 shows time-series graphs of the pressure reduction index value DEL1 in the embodiment and the pressure reduction index value DEL1 in the comparative example. As shown in Figure 6, in the embodiment, immediately after initializing the regression equation L1, DEL1 exceeded the pressure reduction threshold before 1500 seconds had elapsed, confirming that pressure reduction could be detected and an alarm output was possible. On the other hand, in the comparative example, DEL1 did not reach the pressure reduction threshold even after 1500 seconds had elapsed, confirming that the time lag from the occurrence of pressure reduction to the detection of pressure reduction was longer compared to the embodiment. This confirms the effectiveness of the present invention. [Explanation of symbols]

[0074] 1 vehicle 2. Correction device 3 Display 4. Lateral acceleration sensor 6. Wheel speed sensor 7 WT sensor 21 Rotation speed acquisition unit 22 Torque acquisition unit 23 Lateral acceleration acquisition section 24 Comparison Value Calculation Unit 25. Regression Equation Identification Section 26 Rotation speed correction unit 27 Verification Department 28. DEL Calculation Unit (Depressure Index Value Calculation Unit) 29 Alarm output section FL left front wheel FR right front wheel RL Left rear wheel RR Right rear wheel T FL Left front tire T FR Right front tire T RL Left rear tire T RR Right rear tire V1~V4 Wheel speed (rotational speed) α lateral acceleration DEL1-3 Decompression Index Values

Claims

1. A correction device for correcting the rotational speed of a first tire mounted on a vehicle, A rotation speed acquisition unit that acquires the rotation speed of the first tire and the second tire mounted on the vehicle, A comparison value calculation unit calculates a comparison value for comparing the rotational speed of the first tire and the rotational speed of the second tire, A torque acquisition unit that acquires wheel torque, A regression equation identification unit calculates parameters to identify a regression equation that models the comparison value and includes an element dependent on the wheel torque, based on the comparison value and the wheel torque. A rotational speed correction unit calculates the rotational speed of the first tire, in which the effect of slip on the wheel torque on the comparison value is canceled, based on the rotational speed of the second tire and the parameters, A verification unit compares the wheel torque obtained by the torque acquisition unit, the estimated comparison value calculated based on the parameters calculated by the regression equation identification unit, and the comparison value calculated by the comparison value calculation unit. Equipped with, One of the first and second tires is a front tire, and the other is a rear tire, wherein the first tire is subjected to a greater driving force than the second tire. Correction device.

2. The verification unit initializes or modifies the regression equation identified by the regression equation identification unit based on the difference between the estimated comparison value and the comparison value. The correction device according to claim 1.

3. The verification unit initializes or modifies the regression equation identified by the regression equation identification unit if the moving average of the difference exceeds a predetermined threshold or falls below a predetermined threshold. The correction device according to claim 2.

4. Lateral acceleration acquisition unit that acquires the lateral acceleration applied to the vehicle Furthermore, The regression equation further includes elements that synergistically depend on the wheel torque and the lateral acceleration, and elements that depend on the lateral acceleration alone. The verification unit compares the estimated comparison value, which is estimated based on the wheel torque obtained by the torque acquisition unit, the lateral acceleration obtained by the lateral acceleration acquisition unit, and the regression equation identified by the regression equation identification unit, with the comparison value calculated by the comparison value calculation unit. The correction device according to claim 1 or 2.

5. The comparison value calculation unit calculates a first comparison value by comparing the rotational speed of one front tire with the rotational speed of one rear tire among the two front tires and two rear tires mounted on the vehicle, and calculates a second comparison value by comparing the rotational speed of the other front tire with the rotational speed of the other rear tire. The correction device according to claim 1 or 2.

6. A pressure reduction index calculation unit calculates a pressure reduction index value by comparing the rotation speed of any two of the four tires mounted on the vehicle with the rotation speed of the remaining two tires, based on the rotation speed of the second tire and the rotation speed of the first tire calculated by the rotation speed correction unit, and detects pressure reduction in at least one of the tires by comparing the pressure reduction index value with a predetermined pressure reduction threshold. Furthermore, The correction device according to claim 1 or 2.

7. When a depressurized state of the aforementioned tire is detected, the alarm output unit outputs a depressurization alarm. Furthermore, The correction device according to claim 6.

8. The aforementioned comparison value is the ratio of the rotational speed of the first tire to the rotational speed of the second tire. The correction device according to claim 1 or 2.

9. The first tire is a drive wheel tire, and the second tire is a driven wheel tire. The correction device according to claim 1 or 2.

10. A correction method for correcting the rotational speed of a first tire mounted on a vehicle, which is performed by a computer, To obtain the rotational speed of the first tire and the second tire mounted on the vehicle, To calculate a comparison value that compares the rotational speed of the first tire with the rotational speed of the second tire, To obtain wheel torque, Based on the aforementioned comparison value and the wheel torque, calculate parameters to identify a regression equation that models the comparison value and includes an element dependent on the wheel torque. Based on the rotational speed of the second tire and the parameters, the rotational speed of the first tire is calculated such that the effect of slip on the comparison value by the wheel torque is canceled out. The wheel torque obtained and the estimated comparison value estimated based on the calculated parameters are compared with the calculated comparison value. Includes, One of the first and second tires is a front tire, and the other is a rear tire, wherein the first tire is subjected to a greater driving force than the second tire. Correction method.

11. A correction program for correcting the rotational speed of a first tire mounted on a vehicle, To obtain the rotational speed of the first tire and the second tire mounted on the vehicle, To calculate a comparison value that compares the rotational speed of the first tire with the rotational speed of the second tire, To obtain wheel torque, Based on the aforementioned comparison value and the wheel torque, calculate parameters to identify a regression equation that models the comparison value and includes an element dependent on the wheel torque. Based on the rotational speed of the second tire and the parameters, the rotational speed of the first tire is calculated such that the effect of slip on the comparison value by the wheel torque is canceled out. The wheel torque obtained and the estimated comparison value estimated based on the calculated parameters are compared with the calculated comparison value. Have the computer run it, One of the first and second tires is a front tire, and the other is a rear tire, wherein the first tire is subjected to a greater driving force than the second tire. Correction program.

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