JP3152151B2 - Tire pressure estimation device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a tire pressure estimating apparatus for estimating tire air pressure of an automobile or the like, and more particularly, to estimating the tire air pressure indirectly from a vibration component of a tire when a vehicle is running. It relates to the implementation of an estimation structure that can be higher.

[0002]

2. Description of the Related Art Hitherto, as this kind of tire pressure estimating apparatus, for example, an apparatus described in Japanese Patent Application Laid-Open No. Hei 5-133833 or an apparatus described in Japanese Patent Application Laid-Open No. Hei 6-328920 is known.

[0003] In each of these devices, a vibration component of the wheel speed caused by the vibration of the tire is extracted from the wheel speed signal to determine the resonance frequency in the up-down direction or the front-back direction of the tire, and based on the determined resonance frequency. The tire pressures are estimated.

According to such a tire pressure estimating apparatus, it becomes possible to estimate those tire pressures without a means for directly detecting the tire pressure such as a pressure sensor.

[0005]

As described above, if it is possible to extract the vibration component of the wheel speed due to the vibration of the tire, it is necessary to estimate the tire pressure by obtaining the resonance frequency from the vibration component. Can.

In this case, however, the resonance frequency determined is affected by (A) the outside air temperature (more precisely, the tire temperature or the road surface temperature). That is, even if the tire air pressure is the same, when the outside air temperature decreases, the rubber portion of the tire becomes hard and the resonance frequency increases. Conversely, when the outside air temperature increases, the rubber portion of the tire becomes soft and the resonance frequency decreases. (B) It is affected by the wheel speed. That is, the resonance frequency tends to be lower in the low vehicle speed range and the high vehicle speed range. (C) The tire is affected by the magnitude of vibration received from the road surface. That is, the resonance frequency tends to decrease as the magnitude of the vibration received by the tire from the road surface increases. For example, it has been found that it is affected by external factors and fluctuates due to the influence of such external factors. Such a variation in the resonance frequency is also a major cause of reducing the estimation accuracy of the tire pressure.

[0007] The present invention has been made in view of such circumstances, and is intended for indirectly estimating the tire air pressure from tire vibration components during vehicle travel.
It is an object of the present invention to provide a tire pressure estimating device capable of suitably suppressing a decrease in the estimation accuracy.

[0008]

According to the present invention, there is provided a vibration component output means for outputting a signal including a tire vibration component when a vehicle is running. . (B) resonance frequency extracting means for extracting the resonance frequency of the vibration component from the output signal containing the vibration component of the tire. (C) air pressure estimating means for estimating the air pressure of the tire based on the extracted resonance frequency. (D) external factor influence amount extraction means for extracting the influence amount of the external factor affecting the extracted resonance frequency. (E) correction means for correcting the extracted resonance frequency or the estimated air pressure according to the amount of influence of the extracted external factor. And a tire pressure estimating device is configured.

If the resonance frequency of the vibration component can be extracted from a signal including a tire vibration component during vehicle running, such as a wheel speed signal, the tire pressure can be estimated based on the extracted resonance frequency. Is as described above.

[0010] The extracted resonance frequency fluctuates due to the influence of external factors such as the outside air temperature (to be precise, the tire temperature or the road surface temperature), the wheel speed, the magnitude of vibration applied to the tire from the road surface, and the like. It has also been mentioned above that the fluctuation causes a decrease in the estimation accuracy of the tire pressure.

Therefore, according to the first aspect of the present invention, the influence amounts of the external factors are extracted by the external factor influence amount extracting means, and the influence amounts of the extracted external factors are offset in accordance with the extracted influence amounts. As described above, if the resonance frequency or the tire pressure estimated based on the resonance frequency is corrected through the correction means, the tire pressure estimated or corrected naturally becomes highly reliable. That is, a decrease in the tire pressure estimation accuracy due to the influence of an external factor is appropriately suppressed. In each of the above configurations, the resonance frequency extracting means
The, (b1) the resonant frequency extracting means, the vibration component output
Time series signal containing tire vibration components output from the means
Introduced a linear prediction model for the same vibration
Identify the parameters of the linear prediction model
A linear prediction means for extracting a resonance frequency of the component; When
With such a configuration, a high-speed
Vibration components of tires without using the Rie transform (FFT)
The resonance frequency can be extracted from a signal including
Become like That is, when the vibration component of the tire is included
By determining the correlation coefficient between the sequence signals,
Can estimate the parameters of Dell,
If the parameters can be estimated in this way,
Using these parameters, the tire vertical direction or
Can determine the resonance frequency in the front-rear direction.
You. In any case, use fast Fourier transform (FFT)
Compared with the conventional device, the required computation amount
In addition, the memory capacity is greatly reduced. Also,
The linear prediction unit in the case of a (b11) said linear predicting means, sampling times
k, the time series signal including the tire vibration component is y (k),
When the disturbance is m (k), a linear prediction mode for the vibration
As a Dell, a second-order discrete-time model as shown in the above equation (1)
To identify parameters c1 and c2
Parameter identification means and these identified parameters c
Resonance frequency for calculating the resonance frequency based on 1, c2
Numerical operation means. With such a configuration,
The amount of computation and memory required for
And be able to. By the way, the air pressure for each tire
Considering that there is only one resonance point depending on
The “second order” is sufficient for the order of the shape prediction model.

Further, at this time, according to the second aspect of the present invention, (d1) the external factor influence amount extracting means is a temperature sensor for detecting the temperature of the tire or its surroundings. (E1) The correction means corrects the extracted resonance frequency or the estimated tire pressure based on the detected temperature information. According to such a configuration, it is possible to suitably avoid the influence of the external air temperature as an external factor, and the accuracy of estimating the tire air pressure is improved accordingly.

In this case, for example, according to the third aspect of the present invention, (e11) the correcting means corrects the extracted resonance frequency, and sets the resonance frequency to be corrected. f, the detected temperature information is Temp, and the correction amount of the resonance frequency f based on the temperature information Temp is Δf (Tem
When p), the corrected resonance frequency f ′ is calculated based on the equation ( 2 ). (C11) The air pressure estimating means estimates the air pressure of the tire based on the calculated corrected resonance frequency f '. By adopting such a configuration, the influence of the outside air temperature can be easily and accurately avoided.

At this time, the correction amount Δf (Temp) of the resonance frequency f based on the temperature information Temp is as follows: Even when the tire pressure is the same, the rubber portion of the tire becomes harder when the outside air temperature decreases, and the resonance frequency becomes Get higher. Conversely, when the outside air temperature increases, the rubber portion of the tire becomes soft and the resonance frequency decreases. In consideration of such characteristics, a value that can offset the influence is selected. For example, a map or the like in which the correction amount is registered in advance corresponding to the temperature information Temp can be used.

On the other hand, according to a fourth aspect of the present invention, (d2) the external factor influence amount extracting means is a wheel speed detecting means for detecting a wheel speed of the vehicle. (E2) The correction means corrects the extracted resonance frequency or the estimated air pressure based on the detected wheel speed information. According to such a configuration, the influence of the wheel speed as an external factor, in particular, the wheel speed can be suitably avoided, and the estimation accuracy of the tire air pressure is improved accordingly.

In this case, for example, according to the fifth aspect of the present invention, (e21) the correcting means corrects the extracted resonance frequency, and sets the resonance frequency to be corrected. f, the detected wheel speed is v, and the correction amount of the resonance frequency f based on the wheel speed v is Δf (v), the corrected resonance frequency f ′ is calculated based on the above equation ( 3 ). (C21) The air pressure estimating means estimates the air pressure of the tire based on the calculated corrected resonance frequency f '. By adopting such a configuration, the influence of the wheel speed can be easily and accurately avoided.

At this time, the correction amount Δf (v) of the resonance frequency f based on the wheel speed v tends to be lower in the low vehicle speed range and the high vehicle speed range. In consideration of such characteristics, a value that can offset the influence is selected. For example, a map in which the correction amount is registered in advance in correspondence with the wheel speed v can be used.

On the other hand, according to the invention described in claim 6, (d3) the external factor influence amount extracting means is means for extracting the magnitude of vibration applied to the tire from a road surface. (E3) The correction means corrects the extracted resonance frequency or the estimated air pressure based on the magnitude of the extracted vibration. According to such a configuration, it is possible to appropriately avoid the influence of the magnitude of the vibration that the tire receives from the road surface as an external factor, and the estimation accuracy of the tire pressure is improved accordingly.

In this case, for example, according to the invention of claim 7, (e31) the correction means corrects the extracted resonance frequency, and sets the resonance frequency to be corrected. f, and magnitude of the vibration of the tire to be the extracted received from the road surface J, a correction amount of the resonance frequency f based on the vibration of the size J received from the road surface when a Delta] f (J), the equation (4) Then, the corrected resonance frequency f 'is calculated based on the calculated value. (C31) The air pressure estimating means estimates the air pressure of the tire based on the calculated corrected resonance frequency f '.

At this time, the magnitude of the vibration received by the tire from the road surface is determined by the correction amount Δf of the resonance frequency f based on J.
(J): The larger the magnitude of the vibration that the tire receives from the road surface,
The resonance frequency tends to be lower. In consideration of such characteristics, a value that can offset the influence is selected. For this purpose, for example, a map or the like in which the magnitude of the vibration that the tire receives from the road surface corresponding to J and the correction amount thereof is registered in advance can be used.

According to still another aspect of the present invention, (d4) the external factor influence amount extracting means detects a temperature of the tire or its surroundings, and detects a wheel speed of the vehicle. And two or all of a wheel speed detecting means for extracting the magnitude of vibration received by the tire from the road surface. (E4) The correction means is configured to detect or extract the resonance frequency or the resonance frequency based on any two or all of the detected or extracted temperature information and wheel speed information, and the magnitude of vibration that the tire receives from the road surface. Correct the estimated air pressure. According to such a configuration, it is possible to simultaneously avoid the influence of the temperature information and the wheel speed information as external factors, the magnitude of vibration received by the tire from the road surface, and the like, and further improve the estimation accuracy of the tire pressure. Will be done.

[0022]

[0023]

[0024]

[0025]

[0026] In addition, as the above-mentioned parameter identification means,
According to the ninth aspect of the present invention, (b111) minimum 2
The parameters c1 and c2 are identified by a multiplicative method. Such a configuration is effective in performing such identification with high efficiency.

[0027]

[0028]

BEST MODE FOR CARRYING OUT THE INVENTION

(First Embodiment) FIG. 1 shows a first embodiment of a tire pressure estimation device according to the present invention.

The device of this embodiment is configured as a device that detects the resonance frequency of each wheel speed and determines whether the actual tire pressure is lower than the lower limit value based on the resonance frequency. .

As described above, between the tire air pressure and the unsprung resonance frequency which is the resonance point of the vibration of the vehicle unsprung member: The lower the tire air pressure, the lower the unsprung resonance frequency. Is established.

On the other hand, the vibration of the vehicle unsprung member affects the rotational movement of the wheel. As a result, the vibration of the unsprung member causes a resonance frequency having the same height as that of the unsprung member also at the wheel speed, which is the rotational speed of the wheel. That is, between the tire pressure and the resonance frequency of the wheel speed, the resonance frequency is lower as the tire pressure is lower. Is established.

In the apparatus of this embodiment, the tire pressure is estimated based on the relationship between the tire pressure and the resonance frequency of the wheel speed, specifically, as shown in FIG. Is determined to be lower than a lower limit value, that is, a limit value that does not affect the driving of the vehicle.

First, the outline of the configuration of the apparatus of the embodiment will be described with reference to FIG. As shown in FIG. 1, the device of the embodiment is roughly a wheel speed sensor 10, an outside air temperature sensor 40, and a signal processing device that processes the sensor signals as necessary to execute the above determination on the tire pressure. 20, and a display 30 for displaying the determination result in a predetermined form.

The wheel speed sensor 10 detects the rotational speed of each wheel of the vehicle. The sensor 10FR detects the wheel speed of the "right front wheel" and the sensor 10FL detects the rotation speed of the "left front wheel". The wheel speed is measured by the same sensor 10
RR indicates the wheel speed of the “right rear wheel” and the sensor 10R
L detects the wheel speed of the "left rear wheel". FIG.
The wheel speed sensors 10 (10FR, 10FL,
10RR, 10RL).

As shown in FIG. 2, these wheel speed sensors 10 are provided on a corresponding wheel 1 and rotate together with a rotor 11, and a plurality of teeth provided on the outer periphery of the rotor 11 at a constant pitch. (Detected object) 12 and an electromagnetic pickup 13 that electromagnetically detects the passage of the teeth 12 due to the rotation of the rotor 11. Then, the AC signal induced in the electromagnetic pickup 13 is taken into the signal processing device 20 as an output (wheel speed signal) of the wheel speed sensor 10.

The outside air temperature sensor 40 is a sensor that detects the temperature around the tires of the vehicle, that is, the outside air temperature. The sensor 40 may of course be provided with a new temperature sensor. For example, an outside air temperature sensor used for air-conditioning control (air-conditioning control) or an intake air temperature sensor used for engine control can be used. . In any case, the detected temperature information is taken into the signal processing device 20 as an outside air temperature signal.

In the device of the embodiment, a display 30 for displaying the result of the determination of the tire pressure by the signal processing device 20 is provided in an operation panel of the vehicle, for example, as shown in FIG. This is a device for controlling lighting of the lamps 31.

That is, the display 30FR indicates "the right front wheel".
When it is determined that the tire pressure is abnormal, the warning lamp 31FR is lit, and when the tire pressure of the “left front wheel” is determined to be abnormal, the warning lamp 31FL is lit. Similarly, the indicator 30RR turns on the warning lamp 31RR when it is determined that the tire pressure of the “right rear wheel” is abnormal, and the indicator 30RL indicates that the tire pressure of the “left rear wheel” is abnormal. When it is determined, the warning lamp 31FL is turned on.

Thus, the warning lamp 31 (31FR, 31FR)
FL, 31RR, 31RL) is controlled, so that if there is a tire determined to be abnormal in air pressure, the tire is immediately and highly visible to the driver. Be informed.

Based on the output of the wheel speed sensor 10 (wheel speed signal) and the output of the outside air temperature sensor 40 (outside air temperature signal), it is determined whether or not the tire pressure of each wheel is abnormal. Signal processing device 2 for outputting a drive signal for display control to display 30
0, as shown in FIG. 1, a resonance point detection unit 21 that detects the resonance frequency from each wheel speed signal and the outside air temperature signal, and whether there is an abnormality in tire air pressure based on the detected resonance frequency. The determination unit 22 is provided.

The signal processing device 20 has a microcomputer 200 as shown in FIG. 4, and utilizes the arithmetic processing function of the microcomputer 200 to control the resonance point detecting section 21 and the judgment. Each function as the unit 22 is realized. This microcomputer 2
00, including the CPU 201 which is the arithmetic processing unit,
ROM 202 mainly used as a program memory,
It is well known that it basically comprises a RAM 203 and the like used as a data memory.

Next, the details of the signal processing executed in the signal processing device 20 will be described. First, the resonance point detector 21 (21FR, 21F) of the signal processing device 20
L, 21RR, and 21RL), the basic principle of the resonance frequency estimation based on the wheel speed signal will be described.

The physical model for tire pressure estimation is
It can be represented as in FIG. That is, road surface disturbance m (k), which is white noise, is applied as an input to the tire suspension system, and as a result, the wheel speed signal y (k) is output. At this time, the wheel speed signal y (k) includes a resonance component depending on the tire pressure.

In the tire pressure estimating apparatus according to the embodiment, the tire-suspension system is approximated by a linear prediction model, and parameters of the model are identified using the least squares method. In addition, considering that there is one resonance point depending on the air pressure for each tire, the order of this linear prediction model is “second order”. Further, by setting the order of the model to the second order, the amount of computation and the capacity of the data memory (RAM 203) required for the signal processing device 20 can be minimized.

Now, let k be the number of times of sampling, m (k) be the road surface disturbance and y be the wheel speed signal as described above.
(K), the second-order discrete-time model is expressed by the following (5)
It can be expressed as an equation.

[0046]

(Equation 5) Here, the purpose of parameter identification is to estimate unknown parameters c1 and c2 using a finite number of observation data y (k). Here, the unknown parameters c1 and c2 are identified using the least squares method.

That is, in equation (5), m (k) is a disturbance and can be regarded as white noise. Therefore, the estimation of the unknown parameter by the least square method is performed by evaluating the evaluation function J of the following equation (6). That is, c1 and c2 to be minimized are determined.

[0048]

(Equation 6) Then, the estimated values of c1 and c2 that minimize the evaluation function J can be expressed by the following equation (7) by using the collective least squares method (for example, "Signal Processing", Iwao Morishita et al.) , Japan Society of Instrument and Control Engineers).

[0049]

(Equation 7) Next, from the thus identified c1 and c2, the resonance frequency f
Ask for. Parameters c1 and c of the second-order discrete-time model
2 and the resonance frequency f and the attenuation coefficient ζ are expressed by the following equations (8) and (9), where T is the sampling period.
It becomes an expression.

[0050]

(Equation 8)

[0051]

(Equation 9) Therefore, the resonance frequency f and the attenuation coefficient ζ can be calculated as in the following equations (10) and (11), respectively.

[0052]

(Equation 10)

[0053]

[Equation 11] FIG. 6 shows the resonance point detector 21 (21FR, 21FL, 21R) for estimating the resonance frequency f based on such a principle.
R, 21RL). In FIG. 6, for convenience, only one arbitrary system among the systems corresponding to the wheels shown in FIG. 1 is shown.

In the resonance point detecting section 21a shown in FIG. 6, the wheel speed calculating section 211
The waveform of the AC signal output from is converted to a binary pulse signal, and for example, 7.8 ms (millisecond)
This is a part for calculating an average value of the pulse interval for each predetermined sampling period, and calculating a wheel speed from a reciprocal of the calculated average value. Thereby, the wheel speed calculation unit 21
From 1 the calculated wheel speed signal is output every sampling period.

The filter section 212 is a section for filtering (extracting) only the signal components near the resonance frequency depending on the tire pressure from the output wheel speed signal. That is, the output wheel speed signal has a resonance frequency as high as the resonance frequency of the unsprung member of the vehicle, but actually includes other resonance components. Incidentally, in the case of the target vehicle (normal passenger car) in the embodiment, it has been experimentally found that the resonance frequency depending on the tire pressure is between 32 Hz and 40 Hz. Therefore, in the device according to the embodiment, as the filter unit 212, the pass band is 30 Hz.
And a Butterworth type filter set to 45 Hz. Here, the Butterworth-type filter is configured as a fourth-order filter. The signal component passing through the filter unit 212 becomes the wheel speed signal y (k) defined based on the above principle.

Further, the resonance frequency extraction unit 213 calculates the parameters c1 and c2 of the discrete time model from the wheel speed signal y (k) filtered (extracted) by the filter unit 212 based on the above equation (7). Is a part for calculating the resonance frequency f from the identified parameters c1 and c2 based on the equation (10).

On the other hand, the resonance frequency correction unit 214a outputs the outside air temperature Tem detected by the outside air temperature sensor 40.
This is a part for correcting the extracted (calculated) resonance frequency f based on p.

As described above, the extracted resonance frequency f is affected by the outside air temperature Temp, and fluctuates in the manner shown in FIG. 7 depending on the outside air temperature Temp even when the tire pressure is the same.

That is, as shown in FIG. 7, even at the same tire air pressure, the lower the outside air temperature Temp, the higher the resonance frequency f. This is the outside air temperature Te
It is considered that as the mp becomes lower, the tire rubber part becomes harder and the spring constant of the tire becomes larger.

Therefore, in order to prevent the extraction accuracy of the resonance frequency f from deteriorating due to the outside air temperature Temp, it is necessary to correct the resonance frequency f in the manner shown in FIG. 8 based on the outside air temperature Temp.

For this purpose, for example, a correction map as shown in FIG. 9 is provided in the resonance frequency correction unit 214a.
The extracted (calculated) resonance frequency f may be corrected based on this correction map.

Here, the detected outside air temperature Temp
Δf (Temp)
Then, the corrected resonance frequency f ′ is

[0063]

(Equation 12) Will be required. In the resonance point detecting unit 21a shown in FIG. 6, the air pressure estimating unit 215 is a unit that estimates the air pressure p based on the corrected resonance frequency f ′.

As described above, when the tire air pressure is high, the resonance frequency increases, and when the tire air pressure is low, the resonance frequency also decreases. Therefore, the air pressure estimation unit 21
In FIG. 5, the relationship between the tire air pressure p and the corrected resonance frequency f ′ corresponding to FIG. 16 is previously provided as a map, and the corrected resonance frequency f ′ is directly obtained from the above-described value.
The value of the corresponding air pressure p is estimated.

The resonance point detector 21a (21FR, 21F
L, 21RR, 21RL), the value of the tire pressure p thus estimated based on the resonance frequency f ′ extracted as described above and further corrected according to the outside air temperature Temp is determined by the corresponding determination unit 22 (22FR, 22FR, 21RL). 22FL, 22R
R, 22RL).

The determination unit 22 determines each corresponding value based on a comparison between a determination value preset as a threshold value for determining an air pressure abnormality and the value of the tire pressure p output from the resonance point detection unit 21a. It is determined whether there is a tire pressure abnormality. If the value of the tire pressure p output from the resonance point detection unit 21a is lower than the determination value, the corresponding indicator 30 (30FR, 3FR) is determined to be a pressure abnormality.
0FL, 30RR, 30RL).

In the display 30, as described above, the determination unit 22
Thus, when the drive signal is given in this manner, the corresponding warning lamp 31 (FIG. 3) is turned on to notify the driver that there is a tire whose air pressure is determined to be abnormal.

That is, when the tire air pressure is abnormally reduced while the vehicle is running due to natural leakage, stepping on a nail, or the like, the fact is immediately notified to the driver. The tires will then be re-inflated based on these notifications,
When the air pressure is returned to normal, the determination unit 22
, The application of the drive signal to the display 30 is stopped, and the illuminated warning lamp 31 is naturally turned off.

As described above, according to the tire pressure estimating apparatus of the embodiment, (a) the outside air temperature sensor is provided, and the resonance frequency is corrected according to the detected outside air temperature information. In addition, the estimation accuracy of the tire pressure estimated based on the resonance frequency naturally becomes high. (B) Further, the tire suspension system of the vehicle is approximated by a linear prediction model as shown in the above equation (5), parameters of the model are identified by the least square method, and the tire pressure of the wheel speed signal y (k) is calculated. Since the dependent resonance frequency is estimated, the required amount of computation and memory capacity can be greatly reduced as compared with, for example, the case of using fast Fourier transform (FFT). And so on, and excellent effects can be achieved.

(Second Embodiment) As described above, the extracted resonance frequency f is also affected by the wheel speed. That is, the resonance frequency f tends to be lower in the low vehicle speed range and the high vehicle speed range.

FIG. 10 shows, as a second embodiment of the tire pressure estimation device according to the present invention, an example of a device capable of suitably avoiding the influence of such wheel speed on the estimation accuracy of the tire pressure. .

The basic configuration of the apparatus of the second embodiment is the same as that of the apparatus of the first embodiment shown in FIG. 1, and the outside air temperature sensor 40 is not required. And the resonance point detection unit 21 (21FR, 21FL, 21R) constituting the signal processing device 20 accordingly.
R, 21RL) is different from the device of the first embodiment only in that a part of the configuration is also changed. Therefore, this second
The description of other common elements of the device according to the present embodiment will not be repeated here.

Now, in the apparatus of the second embodiment, the resonance point detecting section 21 constituting the signal processing apparatus 20 will be described.
b, as shown in FIG. 10, the wheel speed v obtained through the wheel speed calculation unit 211 is separately taken into the resonance frequency correction unit 214b, and the resonance frequency extraction unit 21
3, the resonance frequency f extracted (calculated) is corrected based on the taken-in wheel speed v.

As described above, the extracted resonance frequency f varies in a manner shown in FIG. 11 according to the wheel speed v at that time. That is, even when the tire pressures are the same, when the wheel speed v is in the low vehicle speed range and in the high vehicle speed range, the resonance frequency f tends to decrease in the manner shown in FIG. is there.

Therefore, in the apparatus of the second embodiment, for example, a correction map as shown in FIG. 12 is provided in the resonance frequency correction section 214b, and the resonance frequency to be extracted (calculated) based on this correction map. Correct f.

Here, when a correction amount of the resonance frequency f based on the wheel speed v is Δf (v), the correction resonance frequency f ′ is

[0077]

(Equation 13) Will be required. In addition, in the resonance point detecting unit 21b shown in FIG. 10, the air pressure estimating unit 215 has a relationship corresponding to FIG. 16 as a map in advance, and directly corresponds to the corresponding value of the corrected resonance frequency f ′. Estimating the value of the air pressure p. The determination unit 22 determines a predetermined value as a threshold value for determining an air pressure abnormality and the resonance point detection unit 21
determining the presence or absence of abnormal air pressure of each corresponding tire based on comparison with the value of the tire air pressure p output from b. If the value of the tire pressure p output from the resonance point detection unit 21b is lower than the above-described determination value, the corresponding indicator 30 (30FR, 30FL, 30FL,
30RR, 30RL). The display unit 30 receives the drive signal from the determination unit 22 in this manner, and accordingly, the corresponding warning lamp 31
(FIG. 3) is lit to notify the driver that there is a tire whose air pressure is determined to be abnormal. Etc. are the same as in the case of the device of the first embodiment.

As described above, according to the tire air pressure estimating apparatus of the second embodiment, in addition to the effect (b) of the apparatus of the first embodiment, The influence on the estimation accuracy of the air pressure can be suitably avoided, and accordingly, the estimation accuracy of the tire air pressure is kept high. Such effects can also be achieved.

(Third Embodiment) As described in the previous section, the extracted resonance frequency f
Is also affected by the magnitude of vibration the tire receives from the road surface. That is, the resonance frequency f tends to decrease as the magnitude of the vibration received by the tire from the road surface increases.

FIG. 13 shows, as a third embodiment of the tire pressure estimation device according to the present invention, the effect of the magnitude of the vibration received by the tire from the road surface (the magnitude of the road surface input) on the estimation accuracy of the tire pressure. An example of a device that can be suitably avoided will be described.

The basic configuration of the device of the third embodiment is the same as that of the device of the first embodiment shown in FIG.
0 is unnecessary, and the signal processing device 2
The resonance point detector 21 (21FR, 21FL, 21FL,
21RR, 21RL) is also partially different from the device of the first embodiment. For this reason, duplicate descriptions of other common elements of the device of the third embodiment are omitted here.

Now, in the apparatus of the third embodiment, the resonance point detecting section 21 constituting the signal processing apparatus 20 will be described.
As shown in FIG. 13, the wheel speed v ′ obtained by the wheel speed calculation unit 211 and filtered through the filter unit 212 is used as the resonance frequency correction unit 21.
4c, the resonance frequency f extracted (calculated) through the resonance frequency extraction unit 213 is calculated based on the wheel speed v 'obtained by the road surface input magnitude (the magnitude of the vibration the tire receives from the road surface). ) Correction is made according to J.

Incidentally, the magnitude J of the road surface input can be represented by the sum of squares of the wheel speed v ′ (amplitude value) filtered through the filter unit 212.

[0084]

[Equation 14] Is calculated as Then, as described above, the extracted resonance frequency f varies in the manner shown in FIG. 14 according to the magnitude J of the road surface input at that time. That is, even when the tire pressures are the same, when the magnitude J of the road surface input is large, the resonance frequency f tends to decrease in the manner shown in FIG.

Therefore, in the apparatus of the third embodiment, the magnitude J of the road surface input in each case is determined by the resonance frequency correction unit 214c based on the equation (14).
For example, a correction map as shown in FIG. 15 is provided in the resonance frequency correction unit 214c, and the extracted (calculated) resonance frequency f is corrected based on the correction map.

Here, assuming that the correction amount of the resonance frequency f based on the magnitude J of the road surface input is Δf (J), the correction resonance frequency f ′ is

[0087]

(Equation 15) Will be required. In addition, also in the resonance point detecting unit 21c shown in FIG. 13, the air pressure estimating unit 215 has a relationship corresponding to FIG. 16 as a map in advance, and directly obtains the corresponding value from the corrected resonance frequency f ' The value of the air pressure p to be applied. The determination unit 22 determines a predetermined value as a threshold value for determining an air pressure abnormality and the resonance point detection unit 21
determining the presence or absence of an abnormal air pressure of each corresponding tire based on a comparison with the value of the tire air pressure p output from c. If the value of the tire pressure p output from the resonance point detection unit 21c is lower than the above determination value, it is determined that the tire pressure is abnormal, and the corresponding indicator 30 (30FR, 30FL,
30RR, 30RL). The display unit 30 receives the drive signal from the determination unit 22 in this manner, and accordingly, the corresponding warning lamp 31
(FIG. 3) is lit to notify the driver that there is a tire whose air pressure is determined to be abnormal. Etc. are the same as in the case of the device of the first embodiment.

As described above, according to the tire pressure estimating apparatus according to the third embodiment, also in this case, in addition to the effect (b) of the apparatus according to the first embodiment, (d) The influence of the magnitude of the road surface input (the magnitude of the vibration that the tire receives from the road surface) on the estimation accuracy of the tire pressure can be appropriately avoided, and the estimation accuracy of the tire pressure can be maintained high accordingly. Such effects can also be achieved.

In the third embodiment, when the resonance frequency f is extracted (calculated) using the linear prediction as described above, the magnitude of the road surface input (the magnitude of the vibration received by the tire from the road surface) Sa) Instead of calculating J by the above equation (14), the magnitude of the evaluation function J shown in the above equation (6) can be replaced. The expression (6) is obtained by using the relational expression of the expression (7).

[0090]

(Equation 16) Can be expressed as Therefore, the resonance frequency correction unit 214c calculates the magnitude of the road input (magnitude of vibration received by the tire from the road surface) J based on the equation (16), and as shown in FIG. The configuration may be such that the resonance frequency f is corrected based on a simple map.

In the first to third embodiments, the influence of the outside air temperature Temp, the influence of the wheel speed v on the extracted resonance frequency f, and the magnitude of the road surface input (vibration of the tire from the road surface) are described. The effect of J was considered separately, and each correction was performed based on those factors. However, by combining the embodiments, the effects of the outside air temperature Temp and the effects of the wheel speed v are considered at the same time, and the resonance frequency f is corrected so that the effects of these factors are avoided at the same time. The effect of the wheel speed v and the effect of the magnitude J of the road surface input are simultaneously considered, and the resonance frequency f is corrected so that the effects of these factors are avoided at the same time. -The influence of the magnitude J of the road surface input and the influence of the outside air temperature Temp are simultaneously considered, and the resonance frequency f is corrected so that the influence of these factors is avoided at the same time. The effect of the outside air temperature Temp, the effect of the wheel speed v, and the effect of the magnitude J of the road surface input are simultaneously considered, and the resonance frequency f is corrected so that the effects of these factors are avoided at the same time. And so on. According to a configuration in which these embodiments are combined, the above-described effects of the embodiments are synergistically combined, and the estimation accuracy of the tire air pressure is further improved.

In each of the above embodiments, the lump-sum least square method is used to identify the parameters c1 and c2 of the introduced linear prediction model.
It goes without saying that multiplication and the like can be used in the same manner.

In addition to the case where the recursive least squares method is employed, a third-order or higher-order model can be introduced as the linear prediction model. However, as the order increases, the required calculation amount and memory capacity also increase. Considering that one tire has one resonance point depending on the air pressure, the order of this linear prediction model is 2
The following is enough.

Although the required amount of computation and memory capacity are disadvantageous as compared with the case where these linear prediction models are introduced, the resonance frequency extraction unit 213
The following are performed:-Fast Fourier transform (FFT) calculation is performed on a signal including a tire vibration component output from the wheel speed sensor 10 and the wheel speed calculation unit 211, which are vibration component output means.
The center of gravity of the frequency spectrum obtained by this FFT operation is calculated. Such a configuration is also effective in suppressing a decrease in the accuracy of tire pressure estimation by the conventional device.

The FFT is used to extract the resonance frequency.
In the device of each of the above embodiments, including the case where the calculation is adopted, the extracted resonance frequency is corrected by each of the external factors, and the tire air pressure is estimated based on the corrected resonance frequency. As for the resonance frequency, the tire pressure may be estimated using the extracted value as it is, and the estimated tire pressure may be corrected according to the influence of the external factor.

Further, in each of the first to third embodiments, the apparatus for estimating the air pressure of the tire and issuing a warning when the air pressure decreases has been described. However, as shown in FIG. 4 by using the signal processing device 20 as an example and also indicated by the dashed arrows, the estimated air pressure is sent as a tire air pressure signal to, for example, a brake control computer or a traction control computer, and correction in those controls is performed. The same device can be used as the device.

For example, in these brake control and traction control, the maximum value of the wheel speed of each wheel may be used as the vehicle speed of the vehicle. On the other hand, in these wheels, when the tire pressure is reduced, the radius of the wheel is reduced, and the wheel speed is apparently increased. Therefore, if the apparently increased wheel speed is corrected based on the tire pressure signal, brake control and traction control based on an incorrect vehicle speed will not be performed.

In addition, the tire air pressure is deeply related to the road surface friction coefficient and the like. Therefore, the tire pressure signal can be used as a signal for correcting the friction coefficient and the like.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a first embodiment of a tire pressure estimation device.

FIG. 2 is a schematic diagram schematically showing a configuration of a wheel speed sensor of the embodiment.

FIG. 3 is an exemplary plan view showing a schematic configuration of the display device of the embodiment.

FIG. 4 is a block diagram showing a schematic configuration of the signal processing device of the embodiment.

FIG. 5 is a block diagram showing a physical model in tire pressure estimation.

FIG. 6 is a block diagram showing a configuration example of a resonance point detection unit of the embodiment.

FIG. 7 is a graph showing an outside air temperature characteristic of a resonance frequency.

FIG. 8 is a graph showing a manner of correcting the resonance frequency based on the outside air temperature.

FIG. 9 is a graph showing a correction amount of a resonance frequency depending on an outside air temperature.

FIG. 10 is a block diagram illustrating a configuration example of a resonance point detection unit according to the second embodiment.

FIG. 11 is a graph showing a wheel speed characteristic of a resonance frequency.

FIG. 12 is a graph showing a correction amount of a resonance frequency depending on a wheel speed.

FIG. 13 is a block diagram illustrating a configuration example of a resonance point detection unit according to the third embodiment.

FIG. 14 is a graph showing the relationship between the resonance frequency and the magnitude of road surface input.

FIG. 15 is a graph showing a correction amount of a resonance frequency depending on a size of a road surface.

FIG. 16 is a graph showing a relationship between a resonance frequency and a tire pressure.

[Explanation of symbols]

1 ... wheels, 10 (10FR, 10FL, 10RR, 10
RL) wheel speed sensor, 11 rotor, 12 teeth (detected body), 13 electromagnetic pickup, 20 signal processing device, 200 microcomputer, 201 CPU,
202: ROM, 203: RAM, 21 (21FR, 2
1FL, 21RR, 21RL)... Resonance point detector 211
... Wheel speed calculator 212, filter 213, resonance frequency extractor 214 (214a, 214b, 214)
c) Resonant frequency correction unit, 215 Air pressure estimation unit, 22
(22FR, 22FL, 22RR, 22RL) ... Judgment unit, 30 (30FR, 30FL, 30RR, 30RL)
... Display, 31 (31FR, 31FL, 31RR, 31)
RL) ... warning lamp, 40 ... outside air temperature sensor.

────────────────────────────────────────────────── ─── Continuation of front page (56) References JP-A-8-72515 (JP, A) JP-A-8-11085 (JP, A) JP-A-9-104208 (JP, A) JP-A-9-99 309304 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB name) B60C 23/00-23/20 G01L 17/00

Claims (9)

(57) [Claims] 1. A vibration component output means for outputting a signal containing a tire vibration component when the vehicle is running, and a resonance frequency extracting means for extracting a resonance frequency of the vibration component from the output signal containing the tire vibration component. Air pressure estimating means for estimating the air pressure of the tire based on the extracted resonance frequency; external factor influence amount extraction means for extracting an influence amount of an external factor affecting the extracted resonance frequency; Correction means for correcting the extracted resonance frequency or the estimated air pressure in accordance with the amount of influence of the extracted external factor, wherein the resonance frequency extraction means is provided from the vibration component output means.
For time series signals including tire vibration components output
A linear prediction model for the vibration was introduced, and the introduced line
The parameters of the shape prediction model are identified and the
With linear prediction means to extract the vibration frequency
In both cases, the linear prediction means sets the number of samplings to k,
The time series signal including the ear vibration component is represented by y (k), and the disturbance is represented by m.
(K), a linear prediction model for the vibration and
Then, To identify each of the parameters c1 and c2
Meter identification means and these identified parameters c1,
resonance frequency calculation for calculating the resonance frequency based on c2
A tire pressure estimating device comprising: a calculating means . 2. The external factor influence amount extraction means is a temperature sensor for detecting the temperature of the tire or its surroundings, and the correction means is configured to extract the resonance frequency or the extracted resonance frequency based on the detected temperature information. The tire pressure estimation device according to claim 1, wherein the estimated pressure is corrected. 3. The correction means for correcting the resonance frequency to be extracted, wherein f is the resonance frequency to be corrected, Temp is the detected temperature information, and resonance is based on the temperature information Temp. When the correction amount of the frequency f is Δf (Te
mp), The air pressure estimating means estimates the air pressure of the tire based on the calculated corrected resonance frequency f ′.
The tire pressure estimating device according to the above. 4. The external factor influence amount extracting means is a wheel speed detecting means for detecting a wheel speed of the vehicle, and the correcting means is configured to extract the resonance frequency based on the detected wheel speed information. The tire pressure estimation device according to claim 1, wherein the estimated pressure is corrected. 5. The correction means for correcting the resonance frequency to be extracted, wherein f is the resonance frequency to be corrected, v is the detected wheel speed, and resonance is based on the wheel speed v. When the correction amount of the frequency f is Δf (v), The air pressure estimating means estimates the air pressure of the tire based on the calculated corrected resonance frequency f ′.
The tire pressure estimating device according to the above. 6. The external factor influence amount extracting means is means for extracting the magnitude of vibration received by the tire from a road surface, and the correcting means is adapted to extract the magnitude of vibration received by the extracted tire from a road surface. The tire pressure estimating device according to claim 1, wherein the extracted resonance frequency or the estimated air pressure is corrected based on the extracted value. 7. The correction means for correcting the resonance frequency to be extracted, wherein f is the resonance frequency to be corrected, J is the magnitude of the vibration that the extracted tire receives from the road surface, When the amount of correction of the resonance frequency f based on the magnitude J of the vibration received from the road surface is Δf (J), 7. The corrected resonance frequency f 'is calculated as follows, and the air pressure estimating means estimates the tire pressure based on the calculated corrected resonance frequency f'.
The tire pressure estimating device according to the above. 8. The external factor influence amount extracting means includes a temperature sensor for detecting the temperature of the tire or its surroundings, a wheel speed detecting means for detecting a wheel speed of the vehicle, and a vibration of the tire received from a road surface. It comprises any two or all of the means for extracting the size, wherein the correction means is the detected or extracted temperature information,
The tire pressure estimation device according to claim 1, wherein the extracted resonance frequency or the estimated air pressure is corrected based on any two or all of the wheel speed information and the magnitude of the vibration received by the tire from the road surface. 9. The method according to claim 1, wherein the parameter identification means uses a least squares method.
Wherein Te is to identify the parameters c1, c2
Item 7. A tire pressure estimation device according to any one of Items 1 to 8.