JPH09323515A - Tire air pressure estimating device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To suitably prevent the deterioration of an estimation accuracy of a device which estimates indirectly the air pressure of a tire by a vibration componenent of the tire when a vehicle is running. SOLUTION: A wheel speed sensor 10 is mounted on each wheel of an automobile and a pulse signal output by the sensor 10 is taken by a signal processing device 20, which determines a wheel speed of each wheel by the pulse signal and extracts a resonance frequency with regard to the vibration of a tire by introducing a linear prospect model into the wheel speed signal or performing a FFT calculation. On the other hand, an outside air temperature sensor 40 mounted on the vehicle detects the temperatures of the tire and the road and the extracted resonance frequency is corrected based on the detected temperatures such that the variations caused by the detected temperatures are absorbed. The air pressure of the tire is estimated based on a linear relationship between the corrected resonance frequency and the air pressure of the tire.

Description

Detailed Description of the Invention

[0001]

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

[0002]

2. Description of the Related Art Conventionally, as a tire air pressure estimating device of this type, for example, a device disclosed in Japanese Patent Laid-Open No. 5-133831 or a device described in Japanese Patent Laid-Open No. 6-328920 is known.

In any of these devices, the vibration component of the wheel speed caused by the vibration of the tire is extracted from the wheel speed signal to obtain the vertical or front-rear resonance frequency of the tire, and based on the obtained resonance frequency. The air pressure of those tires is estimated.

According to such a tire air pressure estimating device, it is possible to estimate those air pressures without requiring a means for directly detecting the tire air pressure such as a pressure sensor.

[0005]

As described above, if the vibration component of the wheel speed due to the vibration of the tire can be extracted, the air pressure of the tire can be estimated by obtaining the resonance frequency from the vibration component. Can

In this case, however, the required resonance frequency 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 becomes low, the rubber portion of the tire becomes hard and the resonance frequency becomes high. On the contrary, when the outside air temperature rises, the rubber portion of the tire becomes soft and the resonance frequency becomes low. (B) Affected by wheel speed. That is, the resonance frequency tends to be low in the low vehicle speed range and the high vehicle speed range. (C) It is affected by the magnitude of vibration that the tire receives from the road surface. That is, the greater the magnitude of vibration that the tire receives from the road surface, the lower the resonance frequency tends to be. And so on, it is known that it is affected by external factors and that it also fluctuates due to the effects of these external factors. Further, such fluctuation of the required resonance frequency is also a major cause of lowering the estimation accuracy of the tire air pressure.

The present invention has been made in view of the above circumstances, and even when the tire air pressure is indirectly estimated from the vibration component of the tire when the vehicle is running,
It is an object of the present invention to provide a tire air pressure estimation device capable of suitably suppressing the deterioration of the estimation accuracy.

[0008]

In order to achieve such an object, according to the present invention, as described in claim 1, (a) a vibration component output means for outputting a signal including a tire vibration component when the vehicle is running. . (B) Resonance frequency extracting means for extracting the resonance frequency of the vibration component from the outputted 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 in accordance with the amount of influence of the extracted external factor. A tire air pressure estimation device is configured by including the above.

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

The extracted resonance frequency fluctuates due to the influence of external factors such as the outside air temperature (to be exact, the tire temperature or the road surface temperature), the wheel speed, the magnitude of the vibration that the tire receives from the road surface, and the like. It was also mentioned above that the fluctuation causes the estimation accuracy of the tire pressure to decrease.

Therefore, according to the same configuration of the invention described in claim 1, the influence amounts of the external factors are extracted by the external factor influence amount extraction means, and the influence amounts of the extracted external factors are offset. As described above, if the correction means corrects the resonance frequency or the tire pressure estimated based on the resonance frequency, the estimated or corrected tire pressure is naturally highly reliable. That is, the deterioration of the tire air pressure estimation accuracy due to the influence of external factors can be appropriately suppressed.

Further, at this time, as in the invention according to claim 2, (d1) the external factor influence amount extraction 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 air pressure based on the detected temperature information. With such a configuration, it becomes possible to preferably avoid the influence of the outside air temperature, which is an external factor, and the estimation accuracy of the tire air pressure is improved accordingly.

In this case, for example, as in the invention according to claim 3, (e11) the correction means corrects the extracted resonance frequency, and determines 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
p), the corrected resonance frequency f ′ is calculated based on the equation (1). (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, it becomes possible to easily and accurately avoid the influence of the outside air temperature.

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

On the other hand, according to the invention of claim 4, (d2) the external factor influence amount extraction means is a wheel speed detection means for detecting the 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. With such a configuration, it is possible to preferably avoid the influence of the wheel speed, which is an external factor, and the estimation accuracy of the tire air pressure is improved accordingly.

In this case, for example, according to the invention of claim 5, (e21) the correcting means corrects the extracted resonance frequency, and the resonance frequency to be corrected is f, where 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 equation (2). (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, it becomes possible to easily and accurately avoid the influence of the wheel speed.

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

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

In this case, for example, according to the invention of claim 7, (e31) the correcting means corrects the extracted resonance frequency, and the resonance frequency to be corrected is f, when the magnitude of vibration that the extracted tire receives from the road surface is J, and the correction amount of the resonance frequency f based on the magnitude J of vibration that the tire receives from the road surface is Δf (J), Based on this, the corrected resonance frequency f'is calculated. (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 correction amount Δf of the resonance frequency f based on J is used as the magnitude of the vibration that the tire receives from the road surface.
(J) is: ・ The greater the magnitude of vibration that the tire receives from the road surface,
The resonance frequency tends to be low. In consideration of such characteristics, a value that can offset the influence will be selected. Also for this, for example, a map in which the magnitude of the vibration that the tire receives from the road surface corresponds to J and the correction amount is registered in advance can be used.

Still further, according to the invention of claim 8, (d4) the external factor influence amount extraction means detects a temperature sensor for detecting the temperature of the tire or its surroundings, and a wheel speed of the vehicle. Any two or all of the wheel speed detecting means and the means for extracting the magnitude of the vibration received by the tire from the road surface are provided. (E4) The correction unit is configured to extract the resonance frequency or the extracted resonance frequency based on any two or all of the detected or extracted temperature information, the wheel speed information, and the magnitude of vibration that the tire receives from the road surface. Correct the estimated air pressure. With 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 that the tire receives from the road surface, and the like, and further improve the estimation accuracy of the tire air pressure. Will be done.

On the other hand, in each of the above constructions, according to the invention of claim 9, (b1) the resonance frequency extracting means outputs a time-series signal containing a tire vibration component output from the vibration component output means. On the other hand, a linear prediction model for the same vibration is introduced, a parameter of the introduced linear prediction model is identified, and a resonance frequency of the vibration component is extracted. With such a configuration, the resonance frequency can be extracted from the signal including the vibration component of the tire without using the fast Fourier transform (FFT) or the like unlike the conventional device.

That is, the parameters of the linear prediction model can be estimated by obtaining the correlation coefficient between the time series signals including the tire vibration component.
Further, if the parameters can be estimated in this way, it becomes possible to obtain the above-mentioned vertical resonance direction or front-rear resonance frequency of the tire using these parameters.

In any case, according to the invention as set forth in claim 9, the required calculation amount and memory capacity are significantly reduced as compared with the conventional device using the fast Fourier transform (FFT). Like

In this case, in particular, according to the invention of claim 10, (b11) the linear predicting means sets the sampling frequency to k, and the time series signal including the tire vibration component to y (k), When the disturbance is m (k), a parameter identification means for introducing a quadratic discrete-time model as shown in the equation (4) to identify the respective parameters c1 and c2 as a linear prediction model for the vibration, These identified parameters c
1 and c2, and a resonance frequency calculating means for calculating the resonance frequency. With such a configuration, the required calculation amount and memory capacity can be minimized. Incidentally, considering that each tire has one resonance point depending on its air pressure, the “second order” is sufficient for the order of the linear prediction model.

Further, in this case, as the parameter identifying means, as in the invention according to claim 11, (b111) the parameters c1 and c2 by the least square method.
Is identified. Such a configuration is effective for performing such identification with high efficiency.

Further, compared with the case where these linear prediction models are introduced, there is a disadvantage in terms of the required calculation amount and memory capacity, but the respective configurations described in the above claims 1 to 8 are claimed. Item 12, ie, (b2) the resonance frequency extracting means, and FFT operation means for performing a fast Fourier transform (FFT) operation on the signal including the tire vibration component output from the vibration component output means, and And a center of gravity calculating means for calculating the center of gravity of the frequency spectrum obtained by the FFT calculation. Such a configuration is also effective in suppressing a decrease in tire air pressure estimation accuracy due to the conventional device.

[0028]

BEST MODE FOR CARRYING OUT THE INVENTION

(First Embodiment) FIG. 1 shows a first embodiment of a tire air pressure estimating 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 air 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 unsprung member also affects the rotational movement of the wheels. As a result, the vibration of the unsprung member causes a resonance frequency having the same height as that of the unsprung member even at the wheel speed that is the rotation speed of the wheel. That is, between the tire air pressure and the resonance frequency of the wheel speed, the lower the tire air pressure, the lower the resonance frequency. Such a relationship is established.

Therefore, in the device of this embodiment, the tire air pressure is estimated based on the relationship between the tire air pressure and the resonance frequency of the wheel speed, specifically, as shown in FIG. 16, and the estimated tire air pressure is obtained. Is lower than a lower limit value, that is, a limit value that does not affect the driving of the vehicle.

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

Among them, the wheel speed sensor 10 is a sensor for detecting the rotation speed of each wheel of the vehicle. The sensor 10FR indicates the wheel speed of the "right front wheel" and the sensor 10FL indicates the "left front wheel". The wheel speed is measured by the sensor 10
RR is the wheel speed of the "right rear wheel", and the sensor 10R
L detects the wheel speed of the "left rear wheel". FIG.
In addition, these wheel speed sensors 10 (10FR, 10FL,
10RR, 10RL).

As shown in FIG. 2, these wheel speed sensors 10 include rotors 11 mounted on the corresponding wheels 1 and rotating together, and a plurality of teeth provided on the outer periphery of the rotor 11 at a constant pitch. The (object to be detected) 12 and an electromagnetic pickup 13 that electromagnetically detects passage of these teeth 12 as the rotor 11 rotates are provided. 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 for detecting the temperature around the tire of the vehicle, that is, the outside air temperature. As the sensor 40, it is of course possible to newly install a temperature sensor, but it is also possible to use, for example, an outside air temperature sensor used for air conditioning control (air conditioner control), an intake air temperature sensor used for engine control, or the like. . In any case, the detected temperature information is taken into the signal processing device 20 as an outside air temperature signal.

Further, in the apparatus of the embodiment, the indicator 30 for displaying the judgment result of the tire pressure by the signal processing device 20 is provided in the operation panel of the vehicle in the manner shown in, for example, FIG. This is a device for controlling the lighting of each lamp 31.

That is, the display 30FR is "right front wheel".
When it is determined that the tire air pressure is abnormal, the warning lamp 31FR is turned on, and the indicator 30FL turns on the warning lamp 31FL when it is determined that the tire pressure of the "left front wheel" is abnormal. 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 the determination is made, the warning lamp 31FL is turned on.

Thus, the warning lamp 31 (31FR, 31FR
By controlling the lighting of (FL, 31RR, 31RL), if there is a tire whose air pressure is determined to be abnormal, it is immediately visible to the driver which tire the tire is. You will be informed.

Then, on the basis of 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 air pressure of each wheel is abnormal, and A signal processing device 2 for outputting a drive signal for display control to the display 30.
As shown in FIG. 1, 0 indicates the 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 the tire air pressure based on the detected resonance frequency. The determination unit 22 is configured to include a determination unit.

As shown in FIG. 4, the signal processing apparatus 20 has a microcomputer 200, and by utilizing the arithmetic processing function of the microcomputer 200, the resonance point detecting section 21 and the judgment are performed. 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 is basically configured by including a RAM 203 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 detection unit 21 (21FR, 21F of the signal processing device 20.
L, 21RR, 21RL), the fundamental 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, the 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) contains a resonance component depending on the tire pressure.

In the tire air pressure estimating apparatus according to the embodiment, the tire / suspension system is approximated by a linear prediction model, and the parameters of the model are identified by the least square method. Considering that each tire has only one resonance point depending on its air pressure, the degree of this linear prediction model is sufficient to be "second order". Further, by making the order of the model quadratic, it becomes possible to minimize the amount of calculation and the capacity of the data memory (RAM 203) required for the signal processing device 20.

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

[0046]

(Equation 5) Here, the purpose of parameter identification is to estimate the 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 the equation (5), m (k) is a disturbance and can be regarded as white noise. Therefore, the estimation of the unknown parameter by the method of least squares is performed by using the evaluation function J of the following equation (6). This is to find the minimum c1 and c2.

[0048]

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

[0049]

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

[0050]

(Equation 8)

[0051]

[Equation 9] Therefore, the resonance frequency f and the damping coefficient ζ can be calculated by 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.
The detailed configuration of R, 21RL) is shown. Note that, in FIG. 6, for convenience, only one arbitrary system of the systems corresponding to the wheels shown in FIG. 1 is illustrated.

In the resonance point detecting section 21a shown in FIG. 6, the wheel speed calculating section 211 includes the wheel speed sensor 10a.
The AC signal output from the device is waveform-shaped and converted into a binary pulse signal, for example, 7.8 ms (millisecond)
For example, it is a part for calculating the average value of the pulse intervals for each predetermined sampling cycle and calculating the wheel speed from the reciprocal of the calculated average value. As a result, the wheel speed calculation unit 21
From 1, the calculated wheel speed signal is output for each sampling cycle.

The filter section 212 is a section for filtering (extracting) only the signal component near the resonance frequency depending on the tire air pressure from the output wheel speed signal. That is, the output wheel speed signal has a resonance frequency of the same height as the resonance frequency of the unsprung member of the vehicle, but actually contains other resonance components. Incidentally, in the case of the vehicle (normal passenger vehicle) of interest in the embodiment, it has been found by experiments that the resonance frequency depending on the tire air pressure is between 32 Hz and 40 Hz. Therefore, in the device according to the embodiment, the pass band of the filter unit 212 is 30 Hz.
A Butterworth type filter set at from 45 Hz to 45 Hz is used. Here, the Butterworth type filter is formed of a fourth order. The signal component that has passed through the filter unit 212 becomes the wheel speed signal y (k) defined by the above principle.

Further, the resonance frequency extraction unit 213 uses the wheel speed signal y (k) filtered (extracted) by the filter unit 212 based on the above equation (7) to determine the parameters c1 and c2 of the discrete time model. And the resonance frequency f is calculated from the identified parameters c1 and c2 based on the above equation (10).

On the other hand, the resonance frequency correction unit 214a has 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 influenced by the outside air temperature Temp, and fluctuates in the manner shown in FIG. 7 depending on the outside air temperature Temp even if the tire air pressure is the same.

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

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

To this end, for example, the resonance frequency correction unit 214a has a correction map as shown in FIG.
The resonance frequency f extracted (calculated) may be corrected based on this correction map.

Here, the detected outside air temperature Temp
The correction amount of the resonance frequency f based on
Then, the corrected resonance frequency f ′ is

[0063]

(Equation 12) Will be required as. Further, 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 is high, and conversely, when the tire air pressure is low, the resonance frequency is low. Therefore, this 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 held as a map, and the corrected resonance frequency f ′ value is directly
The value of the corresponding air pressure p is estimated.

Resonance point detector 21a (21FR, 21F
L, 21RR, 21RL), the value of the tire air pressure p thus estimated on the basis of the resonance frequency f ′ which is extracted and further corrected according to the outside air temperature Temp is set to the corresponding determination unit 22 (22FR, 22FL, 22R
R, 22RL).

The judging section 22 makes a corresponding judgment based on a comparison between a judgment value preset as a threshold value for judging an abnormal air pressure and the value of the tire air pressure p output from the resonance point detecting section 21a. The presence or absence of tire pressure abnormality is determined. Then, if the value of the tire air pressure p output from the resonance point detection unit 21a is lower than the determination value, it is determined that the air pressure is abnormal, and the corresponding indicator 30 (30FR, 3FR).
0FL, 30RR, 30RL).

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

That is, when the tire air pressure is abnormally lowered while the vehicle is traveling due to natural leakage, nail depression, etc., the fact is immediately notified to the driver. Also, based on these notifications, the tires are then replenished with air,
When the air pressure is restored to normal, the determination unit 22
The application of the drive signal from the display device to the display device 30 is stopped, and the lit warning lamp 31 is automatically turned off.

As described above, according to the tire air 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. The estimation accuracy of the tire air 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 such as the above equation (5), and the parameters of the model are identified by the least square method to obtain the tire pressure of the wheel speed signal y (k). Since the dependent resonance frequency is estimated, the required calculation amount and memory capacity can be significantly reduced as compared with, for example, the case of using the fast Fourier transform (FFT). And so on, excellent effects can be achieved.

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

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

The apparatus according to the second embodiment has the same basic structure as the apparatus according to the first embodiment shown in FIG. 1, and the outside air temperature sensor 40 is unnecessary. And the resonance point detection unit 21 (21FR, 21FL, 21R that composes the signal processing device 20 accordingly).
R, 21RL) is also partly changed, which is the only difference from the device of the first embodiment. Therefore, this second
The redundant description here of other common elements of the apparatus of the embodiment of will be omitted.

Now, in the device of the second embodiment, the resonance point detecting section 21 which constitutes the signal processing device 20.
As shown in FIG. 10, b represents a wheel speed v obtained through the wheel speed calculator 211, which is separately fetched by the resonance frequency corrector 214b, and the resonance frequency extractor 21
The resonance frequency f extracted (calculated) through 3 is corrected based on the taken-in wheel speed v.

As described above, the extracted resonance frequency f changes in the 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 extracted (calculated) based on the correction map. Correct f.

Here, when the 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 as. In addition, in the resonance point detecting unit 21b shown in FIG. 10, the air pressure estimating unit 215 has a relationship corresponding to that shown in FIG. 16 as a map in advance, and directly corresponds to the corrected resonance frequency f ′ value. Estimate the value of air pressure p. In the determination unit 22, the determination value preset as the threshold value for determining the air pressure abnormality and the resonance point detection unit 21
The presence / absence of air pressure abnormality of each corresponding tire is determined based on the comparison with the value of the tire air pressure p output from b. If the value of the tire air pressure p output from the resonance point detector 21b is lower than the determination value, it is determined that the air pressure is abnormal, and the corresponding indicator 30 (30FR, 30FL,
Drive 30RR, 30RL). In the display unit 30, the drive signal is supplied from the determination unit 22 in this way, so that the corresponding warning lamp 31
Illuminate (FIG. 3) to notify the driver that there are tires for which the air pressure has been 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, (c) the wheel speed is The influence on the estimation accuracy of the air pressure can be suitably avoided, and the estimation accuracy of the tire air pressure can be maintained high by that amount. Such effects can be played together.

(Third Embodiment) This is also the resonance frequency f extracted above, as described in the section of the above-mentioned problem.
Is also affected by the amount of vibration the tire receives from the road surface. That is, the greater the magnitude of vibration that the tire receives from the road surface, the lower the resonance frequency f tends to be.

Therefore, FIG. 13 shows, as a third embodiment of the tire pressure estimating apparatus according to the present invention, the influence of the magnitude of vibration received by the tire from the road surface (the magnitude of road surface input) on the estimation accuracy of the tire pressure. An example of an apparatus that can be preferably avoided will be shown.

The device of the third embodiment has the same basic structure as that of the device of the first embodiment shown in FIG. 1, and the outside air temperature sensor 4 is also used here.
0 is unnecessary, and the signal processing device 2 accordingly
The resonance point detector 21 (21FR, 21FL,
21RR, 21RL) is also partly changed, which is the only difference from the device of the first embodiment. For this reason, the duplicate description of the other common elements of the device of the third embodiment will be omitted here.

Now, in the device of the third embodiment, the resonance point detecting section 21 which constitutes the signal processing device 20.
As shown in FIG. 13, c is a resonance frequency correction unit 21 that calculates a wheel speed v ′ obtained through the wheel speed calculation unit 211 and filtered through the filter unit 212.
4c, and the resonance frequency f extracted (calculated) by the resonance frequency extraction unit 213 is calculated based on the read wheel speed v ′. The magnitude of the road surface input (the magnitude of vibration that the tire receives from the road surface). ) It will be corrected according to J.

Incidentally, the magnitude J of the road surface input can be expressed by the sum of squares of the wheel speed v '(amplitude value) filtered through the filter section 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 device of the third embodiment, the resonance frequency correction unit 214c obtains the magnitude J of the road surface input at each time based on the equation (14), and
For example, the resonance frequency correction unit 214c has a correction map as shown in FIG. 15, and the resonance frequency f extracted (calculated) is corrected based on this correction map.

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

[0087]

(Equation 15) Will be required as. In addition, also in the resonance point detection unit 21c shown in FIG. 13, the air pressure estimation unit 215 has a relationship corresponding to that shown in FIG. 16 as a map in advance, and the corresponding value is directly obtained from the corrected value of the resonance frequency f ′. Estimate the value of the air pressure p to be applied. In the determination unit 22, the determination value preset as the threshold value for determining the air pressure abnormality and the resonance point detection unit 21
The presence / absence of air pressure abnormality of each corresponding tire is determined based on the comparison with the value of the tire air pressure p output from c. If the value of the tire air pressure p output from the resonance point detector 21c is lower than the determination value, it is determined that the air pressure is abnormal, and the corresponding indicator 30 (30FR, 30FL,
Drive 30RR, 30RL). In the display unit 30, the drive signal is supplied from the determination unit 22 in this way, so that the corresponding warning lamp 31
Illuminate (FIG. 3) to notify the driver that there are tires for which the air pressure has been 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 third embodiment, here, in addition to the effect (b) of the apparatus of the first embodiment, (d) It is possible to suitably avoid 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 air pressure, and the estimation accuracy of the tire air pressure can be maintained high by that amount. Such effects can be played together.

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 that the tire receives from the road surface is It is also possible to replace J with the magnitude of the evaluation function J shown in the above equation (6) instead of calculating it with the above equation (14). Then, the expression (6) is obtained by using the relational expression of the above expression (7),

[0090]

(Equation 16) Can be represented as Therefore, as the resonance frequency correction unit 214c, the magnitude of the same road surface input (the magnitude of the vibration that the tire receives from the road surface) J is obtained based on this equation (16), and the obtained value and the example shown in FIG. The resonance frequency f may be corrected based on such a map.

By the way, in the first to third embodiments, the influence of the outside air temperature Temp on the extracted resonance frequency f, the influence of the wheel speed v, and the magnitude of the road surface input (the vibration received by the tire from the road surface). It is decided to consider the influence of each size) J and to make a different correction based on these factors. However, by combining the respective embodiments, the effect of the outside air temperature Temp and the effect of the wheel speed v are considered at the same time, and the resonance frequency f is corrected so as to avoid the effects of these factors at the same time. The effect of the wheel speed v and the effect of the magnitude J of the road surface input 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 influence of the magnitude J of the road surface input and the influence of the outside air temperature Temp are considered at the same time, and the resonance frequency f is corrected so that the influences of these factors are 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 considered at the same time, and the resonance frequency f is corrected so as to avoid the effects of these factors at the same time. And so on. According to the configuration in which these embodiments are combined, the above-described effects of the embodiments are synergized, and the estimation accuracy of the tire air pressure is further improved.

In each of the above embodiments, the batch type least squares 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 as well.

Further, including the case of adopting the recursive least squares method as described above, it is also possible to introduce a model of third or higher order as the linear prediction model. However, as the order increases, the required calculation amount and memory capacity also increase. Considering that each tire has one resonance point depending on its air pressure, the order of this linear prediction model is 2
The following is sufficient.

Further, compared with the case of introducing these linear prediction models, the resonance frequency extracting unit 213 is disadvantageous in terms of the required calculation amount and memory capacity.
In addition, a fast Fourier transform (FFT) operation is performed on the signal including the 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 calculation is calculated. Such a configuration is also effective in suppressing a decrease in tire air pressure estimation accuracy due to the conventional device.

Further, such FFT is used for extracting 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 extracted value may be used as it is to estimate the tire air pressure, and the estimated tire air pressure may be corrected according to the influence amount of the external factor.

Further, in each of the first to third embodiments described above, the device for estimating the tire air pressure and issuing a warning when the tire air pressure drops has been described. However, as shown in FIG. 4 by taking the signal processing device 20 as an example and also showing a broken line arrow, 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 device can also 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 set as the vehicle speed of the vehicle. On the other hand, in those wheels, when the tire air pressure decreases, the wheel radius becomes smaller, and the wheel speed apparently becomes faster. Therefore, if the apparently increased wheel speed is corrected based on the tire pressure signal, brake control and traction control will not be performed based on an incorrect vehicle speed.

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

[Brief description of drawings]

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

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

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

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

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

FIG. 8 is a graph showing how the resonance frequency is corrected by the outside air temperature.

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

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

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

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

FIG. 13 is a block diagram showing a configuration example of a resonance point detection unit according to a 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 the correction amount of the resonance frequency depending on the size of the road surface.

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

[Explanation of symbols]

1 ... Wheels, 10 (10FR, 10FL, 10RR, 10
RL) ... Wheel speed sensor, 11 ... Rotor, 12 ... Tooth (object to be detected), 13 ... Electromagnetic pickup, 20 ... Signal processing device, 200 ... Microcomputer, 201 ... CPU,
202 ... ROM, 203 ... RAM, 21 (21FR, 2
1FL, 21RR, 21RL) ... Resonance point detection unit, 211
... Wheel speed calculation unit, 212 ... Filter unit, 213 ... Resonance frequency extraction unit, 214 (214a, 214b, 214)
c) ... Resonance 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.

Claims (12)

[Claims] 1. A vibration component output means for outputting a signal containing a tire vibration component when a vehicle is running, and a resonance frequency extracting means for extracting a resonance frequency of the vibration component from the outputted signal containing a tire vibration component. An air pressure estimating means for estimating the tire air pressure based on the extracted resonance frequency; and an external factor influence amount extracting means for extracting an influence amount of an external factor affecting the extracted resonance frequency, A tire air pressure estimating device comprising: a correction unit that corrects the extracted resonance frequency or the estimated air pressure according to the amount of influence of an extracted external factor. 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 the resonance frequency or the extracted resonance frequency based on the detected temperature information. The tire air pressure estimation device according to claim 1, wherein the estimated air pressure is corrected. 3. The correcting means corrects the extracted resonance frequency, wherein the resonance frequency to be corrected is f, the detected temperature information is Temp, and the resonance is based on the temperature information Temp. The correction amount of the frequency f is Δf (Te
mp), then 3. The corrected resonance frequency f ′ is calculated as, and the air pressure estimation means estimates the tire air pressure based on the calculated corrected resonance frequency f ′.
The tire pressure estimation device described. 4. The external factor influence amount extraction means is a wheel speed detection means for detecting the wheel speed of the vehicle, and the correction means is the resonance frequency extracted based on the detected wheel speed information. Alternatively, the tire air pressure estimation device according to claim 1, which corrects the estimated air pressure. 5. The correcting means corrects the extracted resonance frequency, wherein the resonance frequency to be corrected is f, the detected wheel speed is v, and the resonance is based on the wheel speed v. When the correction amount of the frequency f is Δf (v), 5. The corrected resonance frequency f ′ is calculated as, and the air pressure estimating means estimates the tire air pressure based on the calculated corrected resonance frequency f ′.
The tire pressure estimation device described. 6. The external factor influence amount extraction means is means for extracting the magnitude of vibration that the tire receives from the road surface, and the correcting means determines the magnitude of vibration that the extracted tire receives from the road surface. The tire air pressure estimating device according to claim 1, wherein the extracted resonance frequency or the estimated air pressure is corrected based on the tire resonance pressure. 7. The correction means corrects the extracted resonance frequency, wherein the correction target resonance frequency is f, and the magnitude of vibration received by the extracted tire from the road surface is J, When the correction amount of the resonance frequency f based on the magnitude J of vibration received from the same road surface is Δf (J), 7. The corrected resonance frequency f ′ is calculated as, and the air pressure estimating means estimates the tire air pressure based on the calculated corrected resonance frequency f ′.
The tire pressure estimation device described. 8. The external factor influence amount extracting means includes a temperature sensor for detecting a temperature of the tire or its surroundings, a wheel speed detecting means for detecting a wheel speed of the vehicle, and a vibration received by the tire from a road surface. It is configured to include any two or all of the means for extracting the size, the correction means, the correction means, the temperature information to be detected or extracted,
The tire air pressure estimating 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 magnitude of the vibration received by the tire from the road surface and the wheel speed information. 9. The resonance frequency extracting means introduces a linear prediction model for the same vibration into a time-series signal containing the tire vibration component output from the vibration component output means,
The tire air pressure estimation device according to any one of claims 1 to 8, which comprises a linear prediction means for identifying a parameter of the introduced linear prediction model and extracting a resonance frequency of the vibration component. 10. The linear predicting means, wherein k is the number of samplings, y (k) is a time-series signal including a tire vibration component, and m (k) is a disturbance, Number 4] And a resonance frequency calculation means for calculating the resonance frequency based on the identified parameters c1 and c2. The tire pressure estimation device described. 11. The tire pressure estimating device according to claim 10, wherein the parameter identifying means identifies the parameters c1 and c2 by a least square method. 12. The resonance frequency extraction means is obtained by FFT calculation means for performing a fast Fourier transform (FFT) calculation on a signal containing the tire vibration component output from the vibration component output means. 9. The tire air pressure estimating device according to claim 1, further comprising: a center of gravity calculating means for calculating a center of gravity of the frequency spectrum.