JPH11235907A - Tire air pressure estimating device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve estimating accuracy of a tire air pressure, by variably forming a filter characteristic. SOLUTION: This device is provided with an air pressure estimation means estimating an air pressure of a tire, based on a resonance frequency or a tire spring constant extracted by an extraction means by passing through a signal processing filter, and a moving means, while fixedly holding a frequency width, to move a passing frequency band of a signal including a vibration component in the signal processing filter based on the resonance frequency or tire spring constant extracted in the extraction means before the preceding time.

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 pressure of an automobile or the like, and more particularly to an apparatus for indirectly estimating tire pressure from a vibration component of a tire when the vehicle is running.

[0002]

2. Description of the Related Art Conventionally, a tire pressure estimating apparatus of this type is disclosed in Japanese Patent Application Laid-Open No. Hei 5-133831 or Japanese Patent Laid-Open Publication No.
An apparatus described in Japanese Patent No. 28920 is known. 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, and the resonance frequency in the vertical direction of the tire or the torsion direction of the tire or the tire spring constant is determined. Alternatively, the tire pressure is estimated based on the tire spring constant.

[0003] According to such a tire pressure estimation device, it is possible to indirectly estimate the tire pressure without the need for a means for directly detecting the tire pressure such as a pressure sensor.

[0004]

SUMMARY OF THE INVENTION When extracting a resonance frequency or a tire spring constant of a tire vibration pressure-dependent tire vibration component from a signal containing a tire vibration component during running of a vehicle, a signal containing the tire vibration component is extracted. Contains a frequency component that is a noise component that is not related to a change in tire air pressure in addition to the same vibration component. Therefore, only a signal component near a resonance frequency depending on the tire air pressure is filtered (extracted).
To do so, the signal is usually passed through a signal processing filter as preprocessing.

Ideally, the pass frequency band of the signal processing filter sufficiently satisfies a frequency range that includes an air pressure range to be detected among the vibration components depending on the tire air pressure. Here, the frequency range encompassing the air pressure range to be detected does not simply refer to the high pressure to the low pressure of the use range, but due to the properties of the tire rubber,
The frequency also changes depending on the tire temperature. The frequency increases at low temperatures and decreases at high temperatures. For this reason, the frequency range including the air pressure range to be detected from the low-temperature and high-pressure frequency range of the use range to the high-temperature and low-pressure frequency range is set.

However, there are many noise frequency components in this frequency range, and if a filter having filtering characteristics in a frequency range (pass frequency band) including the air pressure range to be detected is adopted, the air pressure detection performance will be reduced. Variations occur. For this reason, conventionally, a filter having a narrower frequency range of the pass frequency band had to be adopted, and there was a problem that the air pressure estimation accuracy could be guaranteed only in a limited temperature range or pressure range.

[0007] In view of such circumstances, in the present invention,
An object of the present invention is to improve the estimation accuracy of the tire air pressure and achieve both system responsiveness by changing a signal processing filter.

[0008]

According to a first aspect of the present invention, there is provided a tire pressure estimating apparatus for detecting a signal containing a vibration component of a tire when a vehicle is running. Extracting means for extracting a resonance frequency or a tire spring constant related to tire air pressure from the vibration component detected by the detection means; and a signal including the vibration component when the resonance frequency or the tire spring constant is extracted by the extraction means. A signal processing filter that passes through a predetermined fixed frequency width, and an air pressure estimation that estimates the air pressure of the tire based on a resonance frequency or a tire spring constant extracted by the extraction means by passing through the signal processing filter. Means and the vibration component in the signal processing filter while keeping the frequency width constant. And a moving means for moving, based on the resonance frequency or Taiyabane constants extracted in the extraction unit before the previous frequency bandpass signal including.

That is, while adopting a filter in which the pass frequency band is narrowed in advance so as to suppress variations in air pressure detection performance, a frequency band in which optimum and high-precision detection is possible is derived, and the filter is adjusted in accordance with the frequency band. The above-mentioned problem is solved by moving the pass frequency band. At this time, the frequency band in which the optimum and highly accurate detection is possible may be derived as described in claims 2 to 6.

According to a second aspect of the present invention, the moving means sets the resonance frequency or the spring constant extracted last time or the average value of the resonance frequency or the spring constant obtained as a result of extracting the reference frequency before the previous time substantially at the center position of the pass frequency band. So that
The pass frequency band is moved. Therefore, since filtering is performed in a narrow band around the resonance frequency representing the tire air pressure or the frequency of the tire spring constant, noise can be efficiently removed without reducing the signal component representing the resonance frequency or the tire spring constant as much as possible.
As a result of a detailed study by the inventors of the present application, a number of frequency components serving as noise exist around the resonance frequency of the vibration component depending on the tire pressure, and as described above, in order to suppress the variation in the air pressure detection performance, It is necessary to employ a filter having a narrow pass frequency band. As shown in FIG. 1A, in the case where the temperature is low and the air pressure is high, even in a predetermined pass frequency band of the filter of about 30 to 50 Hz, noise is outside the pass frequency band. In the frequency characteristics, the peak of the resonance frequency is not cut off, and the detection accuracy is in a sufficiently high state. On the other hand, as shown in FIG.
When the ambient temperature is high and the air pressure is low, a peak of the resonance frequency (near the frequency where the power spectrum of the resonance frequency is the largest) comes near the lower end of the filter. In this case, if a filter whose resonance frequency peak is fixed in a pass frequency band of about 30 to 50 Hz is used, the frequency characteristic after passing through the filter becomes a peak characteristic near the pass frequency band of the filter as shown in the figure. Collapses, and the peak of the resonance frequency itself changes. This is due to the fact that there are many frequencies that are outside the pass band of the filter and must not be cut off. When such a phenomenon occurs, an error occurs in the resonance frequency extracted through the filter with respect to a true change in the resonance frequency due to the tire pressure as shown in FIG. 2, but the present invention can cope with such a problem. That is, as long as the tire pressure does not change suddenly (unless it is a burst or the like), the resonance frequency does not change rapidly. Therefore, the resonance frequency detected last time or the average of the results detected several times in the past is calculated based on the filter pass frequency band. Move the pass frequency band so that it is located in the center,
It is prepared to detect the next resonance frequency. Therefore, a true change of the resonance frequency with respect to the tire air pressure can always be detected, and a time-dependent change and a slight change in the air pressure due to puncture or the like can be accurately detected. In addition,
Extracting the tire spring constant is the same as extracting the resonance frequency. In addition, the moving means as described in claim 3, wherein a resonance frequency or a spring constant extracted last time, or an average value of a resonance frequency or a spring constant obtained as a result of extracting a reference frequency before the previous time, and a center value in the pass frequency band. The pass frequency band may be moved so that the difference from the reference frequency is within a reference. In this case, the moving means determines whether or not the difference from the center value is within a reference to determine whether the extraction result by the extracting means is used for the tire pressure estimating means, and The movement of the pass frequency band may be repeated until the difference from the center value is within the reference. By doing so, although the amount of calculation increases as compared with the invention described in claim 2, even when the resonance frequency suddenly changes due to tire replacement or the like, it can be detected well.

According to a fifth aspect of the present invention, the moving means may move the pass frequency band according to an ambient temperature. This is a frequency range that includes the air pressure range to be detected, that is, a frequency range from a low temperature and a high pressure to a high temperature and a low pressure at an arbitrary temperature. By using a filter with a narrow frequency range up to the frequency of, the variation in air pressure detection performance is suppressed, and the change in frequency due to temperature change is the same as the filter ( (Pass frequency band).

[0012] As described in claim 7, the movement of the pass frequency band may be permitted or prohibited according to the system response time. Further, in the invention according to claim 8, a detecting means for detecting a signal including a vibration component of the tire during running of the vehicle, and a resonance frequency or a tire spring constant related to a tire pressure from the vibration component detected by the detecting means. Extraction means, a signal processing filter that passes the signal containing the vibration component, and the tire pressure based on the resonance frequency or the tire spring constant extracted by the extraction means by passing the signal processing filter. An air pressure estimating means for estimating, and a changing means for changing a width of a pass frequency band of a signal including the vibration component in the signal processing filter are provided.

That is, when a rough value of the resonance frequency or the spring constant of the vibration component depending on the tire pressure is required, the width of the pass frequency band is widened, and the vibration depending on the tire pressure depends on the vibration component depending on the tire pressure. When a highly accurate value of the resonance frequency or the spring constant of the component is required, the width of the pass frequency band is narrowed. As a result, highly accurate tire pressure estimation can be performed.

According to a ninth aspect of the present invention, the changing means changes the width of the pass frequency band passing through the signal processing filter to a signal strength of a signal which has passed through the signal processing filter before the previous time, a vehicle speed, or a speed before the previous time. The change may be made based on at least one of the resonance frequency or the tire spring constant extracted by the extraction means. That is, the width of the pass frequency band of the filter is optimized in accordance with the situation, thereby suppressing variations in the air pressure detection performance. As a means for changing the width of the pass frequency band of the filter, for example, vibrations depending on tire pressure are used. Even if there is some noise at frequencies near the resonance frequency of the component, if the signal intensity of the resonance frequency of the vibration component is sufficiently large, the resonance frequency can be detected well, so the width of the pass frequency band is widened. Then, narrow the opposite case. Also,
The relationship between the signal intensity of the resonance frequency of the vibration component that depends on the tire air pressure and the signal intensity of the noise (SN ratio) depends on the vehicle speed. Therefore, the width of the pass frequency band of the filter is changed depending on the vehicle speed. Further, for example, since the generation frequency of some noises is determined depending on the type of the vehicle, when the frequency band of the resonance frequency of the vibration component depending on the air pressure is close to the generation frequency of the noise, the width of the pass frequency band of the filter is narrowed. However, in the opposite case, it may be made wider.

According to a tenth aspect of the present invention, the changing means may change the width of the pass frequency band in accordance with a required response time of a system in the tire pressure estimation device. This means that if a filter is used that has a pass band that covers the air pressure range to be detected, that is, a wide range of frequencies from any low-temperature and high-pressure frequency to high-temperature and low-pressure frequency. Although it is bad, it can be detected quickly, and conversely, when changing the pass frequency band of the filter as described above, in consideration of the fact that the detection accuracy is high, it takes time to find the optimum state of the width of the pass frequency band, The width of the pass frequency band is varied according to the required time of the system. For example, when the first determination is made from the turning on of the ignition switch of the vehicle, first, from the viewpoint of safety, the pass frequency band of the filter is widened and a rough value of the resonance frequency of the vibration component depending on the tire pressure is detected. . In this way, the calculation time and the response time are prioritized over the detection accuracy. In the subsequent determination, for example, the width of the pass frequency band of the filter is gradually narrowed to obtain an optimum filter pass frequency band, thereby enabling detection with high responsiveness while maintaining accuracy to some extent. in this way,
When responsiveness is more important than accuracy as a system,
By varying the width of the pass frequency band of the filter when the detection accuracy is more important than the responsiveness, it is possible to estimate the tire pressure most suitable for the request.

The moving means may change the width of the passing frequency band only when the vehicle speed or the signal strength passing through the signal processing filter satisfies a predetermined reference value. It may be. This is because if the signal strength of the resonance frequency of the vibration component that depends on the tire pressure is not sufficiently large, the influence of noise at a relatively nearby frequency increases, so that an error is likely to occur in the detection result, and the signal passes through the filter. If the width of the frequency band is changed without considering the signal strength, the frequency band may be moved to the wrong band. Therefore, if the width of the pass frequency band is changed in consideration of the influence of noise due to the vibration intensity, accurate air pressure estimation can be realized.

According to a twelfth aspect of the present invention, there is provided a detecting means for detecting a signal containing a vibration component of a tire when the vehicle is running, and a resonance frequency or a tire frequency related to the tire pressure from the vibration component detected by the detecting means. Extracting means for extracting a tire spring constant, a signal processing filter for passing the signal containing the vibration component through a reference frequency width when the resonance frequency or the tire spring constant is extracted by the extracting means, and passing the signal processing filter. Air pressure estimation means for estimating the tire pressure based on the resonance frequency or tire spring constant extracted by the extraction means; and the signal processing filter based on the resonance frequency or tire spring constant extracted by the extraction means before the previous time. The pass frequency band of the signal containing the vibration component at It is allowed, and a moving changing means for changing the width of the pass frequency band of the signal including the vibrational components, may be provided with a.

That is, both the change and the movement of the width of the pass frequency band are performed. At this time, if the width is changed first and then moved as described in claim 13, the resonance frequency extracted with temporary accuracy by changing the width further improves the accuracy by moving the pass frequency band. I do. By doing so, the accuracy can be further improved, and the response time for tire pressure estimation can be shortened.

[0019]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A first embodiment of a tire pressure estimating apparatus according to the present invention will be described below with reference to FIGS. The device of this embodiment is a device that detects a resonance frequency on a signal of each wheel speed by frequency analysis, and determines whether the actual tire pressure is lower than a lower limit value based on the resonance frequency. It is configured.

There is a relationship between the tire pressure and the tire resonance frequency that the lower the tire pressure, the lower the resonance frequency. On the other hand, the torsional vibration in the tire rotation direction is also included in the wheel speed signal, and is detected as a tire resonance frequency or a tire spring constant. That is, a relationship is established between the tire pressure and the resonance frequency extracted from the wheel speed, such that the lower the tire pressure, the lower the resonance frequency.

Therefore, in the apparatus of this embodiment, the tire pressure is estimated based on the relationship between the tire pressure and the resonance frequency obtained from the wheel speed sensor output, specifically, as shown in FIG. It is determined whether or not the estimated tire pressure is lower than a lower limit value, that is, a limit value that does not affect the operation of the vehicle.

First, the outline of the configuration of the apparatus of the embodiment will be described with reference to FIGS. As shown in FIGS. 4 and 5, the apparatus of the embodiment roughly includes a vehicle speed sensor 10 (FR to RL) and an outside air temperature sensor 40. It comprises a signal processing device 20 for executing the judgment and a display 30 for displaying the judgment result in a predetermined form. Of these, the wheel speed sensor 10 is a sensor that detects the rotational speed of each wheel of the vehicle, the sensor 10FR is the wheel speed of the right front wheel FR, the sensor 10FL is the wheel speed of the left front wheel FL, Sensor 1
0RR indicates the wheel speed of the right rear wheel RR, and
RL detects the wheel speed of the left rear wheel. These wheel speed sensors 10 correspond to the corresponding wheels FR to RL, respectively.
And a rotor 11 mounted on the
A plurality of teeth (objects) are provided at a constant pitch on the outer periphery of the rotor 1 and an electromagnetic pickup 13 that electromagnetically detects the passage of these teeth as the rotor 11 rotates. Then, an AC signal transmitted through 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 conditioner control) or an intake air temperature used for engine control may be used. Further, a microcomputer for estimating tire pressure in the signal processing device 20 for estimating tire pressure and a microcomputer for performing well-known anti-skid control and the like are provided.
It may be provided in the cover of one signal processing device, and the outside air temperature sensor 40 may be incorporated in the cover. 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, a display 30 for displaying the determination result of the tire pressure by the signal processing 20 is provided on an operation panel (instrument panel) of the vehicle as shown in FIG. 6, for example. This is a device for controlling lighting of the warning lamp 31 provided. That is, the display 30 displays the warning lamp 31F when it is determined that the tire pressure of the right front wheel FR is abnormal.
Turn on R. The warning lamp 31FL lights up so as to warn the abnormality of the left front wheel FL, the warning lamp 31RR warns the abnormality of the right rear wheel RR, and the warning lamp 31RL lights up the abnormality of the left rear wheel RL.

By controlling the lighting of the warning lamps 31 (FR to RL) in this way, if there is a tire for which it is determined that the air pressure is abnormal, any of the tires is immediately and visually recognized. It will be easy for the driver to know. The warning lamp 31 may simply notify that at least one of the tires has decreased in air pressure.

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 air pressure of each wheel is abnormal. Signal processing device 20 that outputs a drive signal for display control to display 30
As shown in FIG. 5, based on a resonance point detection unit 21 that detects a resonance frequency corresponding to each wheel from each wheel speed signal and the outside air temperature signal, and a resonance frequency corresponding to each detected wheel. A determination unit 22 that determines whether there is an abnormality in the tire pressure is provided.

As shown in FIG. 7, the signal processing device 20 has a microcomputer 200, 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. Microcomputer 2
00, including the CPU 201 which is the arithmetic processing unit,
ROM20 mainly used as program memory
2. RAM 203 used as a data memory
It is well known that it is basically provided with the above.

Next, the details of the signal processing performed in the signal processing device 20 will be described. First, the basic principle of the resonance frequency estimation based on the wheel speed signal performed in the resonance point detection unit 21 (21FR to RL) of the signal processing device 20 will be described. A physical model in tire pressure estimation can be represented as shown in FIG.

That is, road surface disturbance m which is white noise
(K) is applied as an input to the tire suspension system, and as a result, a 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 the linear prediction model is sufficient to be 2nd order. Further, by setting the order of the model to the second order, the amount of calculation and the capacity of the data memory (RAM 203) required for the signal processing device 20 can be reduced.

Now, let k be the number of samplings, 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 given by the following equation 1.
Can be expressed as

[0031]

Y (k) =-c1y (k-1) -c2y (k-2) + m (k) (Equation 1) Here, the purpose of parameter identification is to obtain a finite number of observation data y (k). Is used to estimate the unknown parameters c1 and c2. Here, the unknown parameters c1 and c2 are identified using the least squares method.

That is, in Equation 1, m (k) is a disturbance and can be regarded as white noise.
The estimation of the unknown parameter by the multiplicative method is to find c1 and c2 that minimize the evaluation function J of Expression 2.

[0033]

(Equation 2)

(Equation 2) The estimated values of c1 and c2 that minimize the evaluation function J can be expressed as shown in Equation 3 by using the general least squares method. (For example, see "Signal Processing" by Iwao Morishita et al., The Society of Instrument and Control Engineers.)

[0035]

(Equation 3)

(Equation 3) Next, the resonance frequency f is obtained from the thus identified c1 and c2.
Ask for. Parameters c1 and c of the second-order discrete-time model
The relationship between 2 and the resonance frequency f and the damping coefficient な る are represented by Expressions 4 and 5, respectively, where T is the sampling period.

[0037]

(Equation 4)

(Equation 4)

[0039]

(Equation 5)

(Equation 5) Accordingly, the resonance frequency f and the attenuation coefficient ζ can be calculated as shown in Equations 6 and 7, respectively.

[0041]

(Equation 6)

(Equation 6)

[0043]

(Equation 7)

(Equation 7) FIG. 9 shows a detailed configuration of the resonance point detecting section 21 for estimating the resonance frequency f based on such a principle. Note that FIG.
1 shows only one arbitrary system among the systems corresponding to the wheels shown in FIG. 4 for convenience. In the resonance point detecting section 21 shown in FIG. 9, the wheel speed calculating section 211 shapes the waveform of the AC signal output from the wheel speed sensor 10 to form a binary pulse signal. The signal is shaped into a waveform and converted into a binary pulse signal, and the average value of the pulse interval is calculated for each reference sampling period, for example, 5.0 ms (milliseconds), and the reciprocal of the calculated average value is calculated. This part calculates the wheel speed. As a result, the calculated wheel speed signal is output from the wheel speed calculating unit 211 at each sampling cycle.

The filter section 212a 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. Then, in the filter adjustment unit 212b, the optimum filter position is obtained based on the resonance frequency obtained through the processing described later, and the filter unit 212a is used for the next calculation.
Adjust the filter position (pass frequency band). Initially, the frequency pass band of the filter unit 212a should be detected in consideration of the possibility that the resonance frequency has changed since the previous run due to tire replacement or the like, of a vibration component that depends on the tire pressure of the tire that can be mounted. A broadband filter capable of covering a frequency range including the air pressure range is obtained, thereby obtaining an approximate resonance frequency f. For example, in the first calculation process of tire pressure estimation after the ignition is turned on, when the filter first passes through the filter unit 212a, the frequency range of the filter pass frequency band is set to 30 to 50 Hz.
Is set to Next, the resonance frequency extracting unit 213 temporarily extracts the resonance frequency, and then the filter adjusting unit 21
In step 2b, the width of the pass frequency band of the filter is changed. At this time, the width is changed by changing the frequency range of 30 to 50 Hz to 32.
Change to ~ 48Hz. It is assumed that after such a change in the width is repeated a predetermined number of times determined by the vehicle speed or the like, the final pass frequency band of the filter becomes 38 to 42 Hz due to the change in the pass frequency band width. Thereafter, the signal passes through the resonance frequency extraction unit 213 from the filter unit 212a again.
When the process proceeds to the filter adjustment unit 212b, the pass frequency band of the filter is moved this time. The shift of the pass frequency band is performed based on the resonance frequency obtained as a result of the previous extraction by the resonance frequency extraction unit 213. For example, if the previously extracted resonance frequency f is f = 40.5 Hz, based on this resonance frequency f, the movement of the pass frequency band of the filter is shifted to the center of the pass frequency band of the filter by 4.
38-42 Hz is adjusted to 38.5 so that it becomes 0.5 Hz.
Move the pass frequency band to 42.5 Hz. Next, if the resonance frequency extracted by the resonance frequency extraction unit 213 based on the signal filtered by the filter unit 212a in this frequency band (38.5 to 42.5 Hz) is 40.2 Hz, the same applies. This 40.2H
The pass frequency band of the filter is set at 38.2-4 around z.
Go to 2.2 Hz. The width of the pass frequency band is changed a predetermined number of times determined by the conditions, and the shift of the pass frequency band is performed during the tire pressure estimation after the change of the width. You may. In the above description, the movement of the pass frequency band is based on the resonance frequency f extracted by the resonance frequency extraction unit 213 last time.
Is moved around this resonance frequency f on the basis of the above, but regardless of this, the movement may be performed as follows.
For example, the pass frequency band of this filter is 38 to 4
2 Hz, and the resonance frequency f extracted this time is 41H
Let z. The center position of this pass frequency band is 40H
Regarding z, a reference range that allows the tire pressure to be determined centering on this 40 Hz is provided. For example, it is assumed that ± 0.1 Hz is allowed as the reference range, and the reference range is variable depending on whether the tire air pressure is being estimated or constant, vehicle speed, signal strength, or the like. Therefore, the resonance frequency 41 Hz extracted this time does not fall within the range obtained by adding the reference range to the center position of the pass frequency band = 40 Hz, that is, 38.9 Hz to 40.1 Hz. Therefore,
Control may be performed to permit movement of the pass frequency band based on the resonance frequency f extracted this time. If the resonance frequency f extracted this time falls within the range obtained by adding the reference range, that is, 38.9 to 40.1 Hz, the pass frequency band is not moved. Note that two reference ranges are provided (for example, ± 0.1 Hz and ± 0.5 H
z) When a resonance frequency f exceeding the larger range is extracted, the air pressure estimation unit 215 to be described later may prohibit the air pressure estimation or the determination unit 22 may prohibit the determination.

Next, at 212b, the filter is moved so that this f becomes the center, and the width is narrower than before to improve the accuracy.
Perform the next process. Further, the same repetition is performed based on the resulting f, and only the movement is performed after the width of the filter pass band at which the detection accuracy is optimized is obtained. As a result, the resonance frequency can be extracted without being affected by noise.

The signal component that has passed through the filter 212a becomes the wheel speed signal y (k) defined according to the above principle. Further, the resonance frequency extraction unit 213 includes the filter unit 2.
Wheel speed signal y filtered (extracted) by 12a
(K) is a part for identifying the parameters c1 and c2 of the discrete-time model based on the above equation 3, and calculating the resonance frequency f based on the above equation 6 from the identified parameters c1 and c2. .

It should be noted that the number of times the filter frequency adjustment section 212b moves and changes the pass frequency band of the filter from the resonance frequency extraction section 213 to the filter adjustment section 212b is determined according to conditions such as the vehicle speed. What should I do? For example, if the vehicle speed is in a low-speed running state, the processing calculation response time of the tire pressure estimation does not need to be so fast, and the number of wheel speed signals (waveforms of the wheel speed signal) as the calculation base input per unit time is not required. Since the number of pulses after shaping) is small, the number of repetitions of the filter movement, that is, the width change of the pass frequency band and the movement are increased. Also, the number of wheel speed signals per unit time during high-speed running, for example, the number of pulses is large, and the danger increases at high-speed running unless the occupant is notified of the decrease in air pressure early. Less. Such a change in the width of the pass frequency band and the change in the number of repetitions of the movement may be equally varied in both the width change and the movement, or the number of width changes may be changed in the number of movements. Alternatively, the number of movements may be constant by changing the number of width changes. As another condition for changing the number of times that the pass frequency band of the filter is moved and the width is changed, there is another condition within a reference time immediately after the ignition switch is turned on or within a reference number of times immediately after the ignition is turned on (for example, once). In the air pressure estimation, a large number of movements and / or width changes of the pass frequency band are performed to perform tire pressure estimation with priority on accuracy, and thereafter, a small number of movements and And / or the width may be changed.

On the other hand, the resonance frequency correcting section 214 is a section for correcting the extracted (calculated) resonance frequency f based on the outside air temperature Temp detected by the outside air temperature line 40. As described above, the extracted resonance frequency f
Is affected by the outside air temperature Temp and fluctuates in the manner shown in FIG. 10 by the outside air temperature Temp even if the tire air pressure is the same.

That is, as shown in FIG. 10, even at the same air pressure, the resonance frequency f increases as the outside air temperature Temp decreases. This is the outside air temperature Te
It is considered that as the mp becomes lower, the tire rubber portion becomes harder and the tire spring constant becomes larger. Therefore, in order to prevent such a decrease in 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 manner shown in FIG. 11 based on the outside air temperature Temp.

For this purpose, for example, a correction map as shown in FIG. 12 may be provided in the resonance frequency correction unit 214, and the resonance frequency f to be extracted (calculated) may be corrected using the correction map. Will be. Here, the resonance frequency f based on the detected outside air temperature Temp
Is the correction amount of Δf (Temp), the corrected resonance frequency f ′ is

[0052]

F '= fΔf (Temp) (Equation 8) In the same resonance point detecting section 21 shown in FIG. 9, the air pressure estimating section 215 is a section for estimating 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, this air pressure estimation unit 2
15, the tire pressure p and the corrected resonance frequency f '
The relationship between the above and FIG. 3 is previously stored as a map, and the value of the corresponding air pressure p is directly estimated from the corrected value of the resonance frequency f ′.

In the resonance point detecting section 21, the value of the tire pressure p estimated in this manner is determined based on the resonance frequency f 'extracted as described above and further corrected in accordance with the outside air temperature Temp. 22 (22FR-R
L). The determination unit 22 determines a determination value preset as a threshold value for determining an air pressure abnormality and a tire pressure p output from the resonance point detection unit 21.
The presence or absence of the corresponding tire air pressure abnormality is determined based on the comparison with the value of. If the value of the tire pressure p output from the resonance point detection unit 21 is lower than the determination value, the corresponding display unit 30 is driven as an air pressure abnormality.

In the display unit 30, as described above, the determination unit 2
When the drive signal is given from Step 2, the corresponding warning lamp 31 (FIG. 6) 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 during running of the vehicle due to natural leakage, stepping on a nail, or the like, the fact is immediately notified to the driver.

Further, based on such notification,
When air is supplied to the tire and the air pressure is restored to normal, the application of the drive signal from the determination unit 22 to the display 30 is stopped, and the warning lamp 31 that has been turned on is turned off naturally. You. As described above, according to the tire pressure estimating apparatus of the embodiment, the following effects are obtained.

Since 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 pressure estimated based on the resonance frequency is high. Further, the tire-suspension system of the vehicle is approximated by a linear prediction model as shown in the above equation 1, the parameters of the model are identified by the least square method, and the resonance frequency of the wheel speed signal y (k) depending on the tire pressure is determined. Since the estimation is performed, the required operation amount and memory capacity can be reduced as compared with, for example, the case of using the fast Fourier transform (FFT).

In the above-described embodiment, the lump-sum least squares method is used to identify the parameters c1 and c2 of the introduced linear prediction model. Can be used. In addition, including 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 the linear prediction model is sufficient to be two orders.

In comparison with the case of introducing these linear prediction models, the resonance frequency extraction unit 213 has a disadvantage in terms of the required operation amount and memory capacity.
In addition, a fast Fourier transform operation is performed on a signal including a tire signal component output from the wheel speed sensor 10 and the wheel speed operation unit 211 as a vibration component output unit, and a frequency spectrum obtained by the FFT operation is obtained. A configuration in which the resonance frequency is calculated from the tire pressure estimation device can also be configured. Similarly, a Fourier transform, which is a known technique for calculating a frequency spectrum,
Needless to say, the configuration can also be made using discrete Fourier transform (DFT), Walsh transform, fast Walsh transform, a method using an autocorrelation function, cepstrum analysis, bispectral analysis, wavelet transform, or the like.

Further, as a method for indirectly estimating the resonance frequency, there is known a system identification method (a model of the present system, and indirectly estimating the resonance frequency by identifying parameters of the model). The methods for identifying the parameters using the method include the lump-square method, the sequential least-squares method, the correlation method, the prediction error method, the canonical variate analysis method, the singular value decomposition method, the applied identification method, and the like. Needless to say, the same configuration can be made.

In the above-described embodiment, both the width change and the movement of the pass frequency band of the filter are performed. However, at least one of the processes, that is, only the change of the pass frequency band width or the pass frequency band is performed. Only the band movement may be performed, and the width change or the number of times the movement is changed may be varied. In addition, the change of the width of the pass frequency band or the execution of the movement is performed based on the strength of the signal input from the wheel speed sensor (signal strength), that is, the portion permitted or prohibited in view of the magnitude of the power spectrum. You may provide between the filter adjustment part 212b. That is, if the signal strength is large in the waveform-shaped wheel speed signal, the signal related to the true resonance frequency can be accurately extracted even if the noise is large to some extent, and the width change or movement of the pass frequency band of the filter is performed. However, the signal related to the true teacher frequency may be turned off, which may adversely affect the accuracy of the tire pressure estimation. Therefore, the width of the passing frequency band may be changed or the movement may be permitted or prohibited according to the signal strength. At this time, the vibration intensity may be compared with a predetermined reference value, and the width of the pass frequency band may be changed or the movement may be permitted or prohibited based on the comparison result.

Next, the second embodiment of the present invention will be described with reference to FIG.
An embodiment will be described. FIG. 13 is a flowchart showing a control flow executed in the signal processing device according to the second embodiment. In addition, since this control flow sequentially performs the same processing for each tire in order, the flowchart described below shows only the processing for one tire.

First, the ignition switch of the vehicle is set to O
If the answer is N, the vehicle starts running. In step 10, the outside air temperature is detected based on the detection signal from the outside air temperature sensor 40. In step 20, the signal of the wheel speed sensor 10 is fetched and the wheel speed calculation Vx is performed. In step 30, the intensity of the tire vibration component included in the wheel speed signal is relatively increased using a narrow band filter (hereinafter referred to as a band pass filter BPF) whose frequency range is fixed in advance, and the tire vibration is increased. Extract the components. In addition,
This filter is an RO built in the ECU 20 in advance.
This is stored in M202, and the number of filters that are prepared internally is limited.

The movement of the filter described below is started from the BPF shown in step 30. In step 40, the resonance frequency f is calculated from the tire vibration component extracted in step 30 by the above-described linear prediction method. Step 50 is a step 40
And the BP used in the calculation
This is a step of determining a deviation of F from the center frequency fbc and determining whether the deviation has not reached within f0.
If a negative determination is made here, the process proceeds to step 60 and the filter is moved. The filter may be moved, for example, by a predetermined process of 0.5 Hz in a pass frequency band to be band-passed in one process.
Then, steps 40 to 60 are repeated, and the filter movement is continued until the absolute value of the deviation between the obtained co-new frequency f and the center frequency fbc of the band-pass filter falls within a predetermined range, that is, until an affirmative determination is made in step 50. I do.

If it is determined in step 50 that the frequency deviation is within the predetermined range, the process proceeds to step 70, where the resonance frequency is corrected. This correction corrects the influence of the outside air temperature on the tire resonance frequency. Next, in step 80, the tire pressure is estimated from the resonance frequency obtained by correction in step 70.

In the next step 90, it is determined whether or not the tire air pressure has fallen below a preset air pressure reduction judgment threshold. And based on this result,
In step 100, it is determined whether or not an alarm is turned on on the display unit 30. Next, a third embodiment will be described with reference to FIG. Steps equivalent to those in the second embodiment described in FIG. 13 are denoted by the same steps in the following embodiments, and description thereof will be omitted.

In the second embodiment, a condition for permitting the execution of the filter movement (vehicle speed) is added. In the present embodiment, the vehicle speed is used as a condition for permitting the filter to move, the pass frequency band of the filter is moved only when the vehicle speed is equal to or less than a preset value, and the filter is moved when the vehicle speed is equal to or greater than the preset value. There is no working example.

In step 110, the vehicle speed VB is obtained from the wheel speed calculation result executed in step 20, and is compared with a preset vehicle speed V0. In step 110, the vehicle speed V
If it is determined that B is smaller than V0, step 5
The process proceeds to 0, and the deviation between the co-new frequency f obtained in step 40 and the center frequency fbc of the BPF used for the calculation is obtained. Here, this deviation is a deviation value f set in advance.
If it is 0 or more, it is determined that it is necessary to move the filter, and the process proceeds to step 60, where the filter is moved. The filter movement is continued until the deviation between the obtained resonance frequency f and the center frequency fbc of the band-pass filter falls within a predetermined range.

When the affirmative determination is made in step 110 and when the affirmative determination is made in step 60, the routine proceeds to step 70, where the resonance frequency f is corrected. As described above, in step 110, when the vehicle speed VB is equal to or higher than the predetermined speed V0, steps 50 and 60 are not executed, and only the resonance frequency related to the outside air temperature is corrected. The control in consideration of the vehicle body speed takes into consideration the system response time. For example, 80 Km / h may be used as the above-mentioned predetermined vehicle body speed V0. That is, when the vehicle speed is re-running on a highway or the like, the input signal from the wheel speed sensor is large, and when the filter is moving, the response time of the tire pressure estimation determination becomes slow. Further, when traveling at high speed, it is not so necessary to detect a gradual decrease in tire air pressure, and it is highly likely that it is required to detect only a sudden change in air pressure such as a burst. Therefore, at the time of high-speed running, it is more useful to reduce the response time of the air pressure estimation determination and cope with the determination of the burst or the like than to perform the accurate air pressure estimation determination by performing the filter movement. In addition, as will be described later, the control in consideration of the vehicle speed increases or decreases the signal intensity according to the vehicle speed, and thus is useful for realizing the tire pressure estimation according to the signal intensity.

Next, a fourth embodiment will be described with reference to FIG. In the present embodiment, the condition (signal strength) for permitting the execution of the filter movement is added to the above-described embodiments. That is, this is an example in which the signal strength is used as the filter movement permission condition. The filter is moved only when the signal strength is equal to or greater than a preset value, and is not moved when the signal strength is equal to or less than the preset value. This is an example.

In step 210, the signal strength GC is obtained from the calculation result of the wheel speed executed in step 20, and the signal strength GC is compared with a preset signal strength GC0. If it is determined in step 210 that the signal strength GC is equal to or greater than GC0, the process proceeds to step 50, in which a deviation between the resonance frequency f obtained in step 213 and the center frequency fbc of the BPF used in the calculation is obtained. If the deviation is equal to or larger than the preset deviation value f0, it is determined that the filter needs to be moved, and the process proceeds to step 212c to move the filter. The filter movement is continued until the deviation between the obtained resonance frequency f and the center frequency fbc of the band-pass filter falls within a predetermined range.

If it is determined in step 210 that the signal strength GC is smaller than the preset value GC0, or if the deviation between the obtained resonance frequency f and the center frequency fbc of the band-pass filter is within a predetermined range, If so, the routine proceeds to step 70, where the resonance frequency is corrected based on the outside air temperature. Here, a specific method of calculating the signal strength will be described with reference to FIGS.

It has already been exemplified in JP-A-6-270618 that the vibration input from the road surface can be extracted from the wheel speed fluctuation (output signal of the wheel speed sensor) by using an appropriate band-pass filter. FIG. 16 illustrates a specific calculation method. FIG. 16 shows the waveform of the wheel speed Vx calculation result after passing through the filter in step 30, where the horizontal axis represents time and the vertical axis represents gain indicating the magnitude of a vibration component from the road surface. Here, assuming that the value of Vx for each calculation cycle (for example, 5 ms) of the wheel speed Vx is Vx (i), the vibration input strength Gc can be expressed by the following equation.

[0074]

(Equation 9) In other words, the square value of Vx (i) calculated for each wheel speed calculation cycle during the Gc calculation cycle that is the signal strength calculation cycle is represented by m
This can be expressed as a sum of the two.

FIG. 17 shows another embodiment of a method for calculating the vibration input intensity from the road surface. That is,
The difference between the maximum gain (maximum Vx (i)) of the vibration component of the wheel speed and the minimum gain (minimum Vx (i)) of the vibration component input during the Gc calculation cycle, which is the signal strength calculation cycle, is used as the signal strength. adopt. Hereinafter, the fifth embodiment will be described with reference to FIG. In the fourth embodiment, conditions for permitting filter movement (system response time) are added to the above-described embodiments. That is, the system response time, that is, the IG-O
This is an example of using the number of extractions n of the resonance frequency f after the start of N vehicles. The filter is moved only when the number of extractions is equal to or greater than a preset number of times n0, and the response time of the system is secured when the number is equal to or less than the preset value. In this embodiment, the filter is not moved in order to perform the operation. Steps equivalent to those in the above-described embodiments are given the same steps, and description thereof is omitted.

In step 310, the resonance frequency f is calculated from the tire vibration component extracted in step 30 by the aforementioned linear prediction method. At the same time, the number of extractions n is counted. In step 320, the number of extractions n counted in step 310 is compared with a preset number of extractions n0. If the number of extractions n is equal to or less than the preset number of extractions n0, the process proceeds to step 70 without moving the filter in order to secure the response time of the system, and the correction using the signal of the outside air temperature sensor 40 is performed. Is carried out.

If the number of extractions n is larger than the predetermined number of extractions n0, the process proceeds to step 50, where the deviation between the center frequency of the filter for which the resonance frequency f has been calculated and the predetermined frequency fbc is obtained. If the difference value is equal to or larger than the preset deviation value f0, it is determined that the filter needs to be moved, and the routine proceeds to step 60, where the filter is moved. In addition, as in the above-described embodiments, the filter movement is continued until the deviation between the obtained resonance frequency f and the center frequency fbc of the band-pass filter falls within a predetermined range.

As described above, if the number of times of extraction of the resonance frequency is equal to or less than the predetermined number, the tire pressure estimation can be performed quickly, although not very accurately, immediately after the ignition switch is turned on unless the pass band of the filter is moved. In the case of departure from a parking lot while the expressway is running or in a region where the expressway is well developed, if the user can get on the expressway immediately from the home parking lot, it is possible to roughly estimate the air pressure before getting on the expressway. Then, if it can be considered that there is enough room to perform the air pressure estimation accurately, such as while the vehicle is running on the highway, by repeating the extraction of a certain number of resonance frequencies, the filter is moved. Since it is permitted to proceed to step 550 for determining whether or not
Accurate tie and air pressure estimation can be performed. However, since it takes time to move the filter, the filter movement is permitted only when the number of times of extraction of the resonance frequency is large as described above.

Hereinafter, a sixth embodiment will be described with reference to FIG. The sixth embodiment relates to changing the filter width when moving the filter, that is, moving the pass band of the filter. The filter that passes the signal in step 30 is a narrow band filter (BPF) whose passing frequency band (df) is fixed in advance, in order to relatively increase the intensity of the tire vibration component included in the wheel speed signal. belongs to.

From step 50, the process proceeds to step 410 as a specific example of step 60. In this step 410, the predetermined frequency width Δf is reduced from the frequency width of the filter used for extracting the resonance frequency f in step 40. Let it. That is, for example, in the first step 40 from the start of calculation, filtering is performed in the pass frequency band df of the filter, and when returning to step 40 through step 410, filtering is performed in the pass frequency band reduced by Δf from the filter width df. . Furthermore, if it is determined in step 50 that the deviation has not yet reached within the preset f0, then in step 410, the pass frequency band is further reduced by Δf from the previously changed width.
Then, in this reduced pass frequency band, step 40
Is used to extract the resonance frequency. Such an operation is repeated.

Next, a seventh embodiment will be described with reference to FIG. The seventh embodiment is an example in which the vehicle speed is used as the execution permission condition when the width of the frequency band of the filter is changed. That is, this is an example in which the vehicle speed is used as a condition for permitting the change of the filter width when the filter is moved, and the pass frequency band is reduced only when the vehicle speed is equal to or less than a preset value. , Does not reduce the pass frequency band of the filter. Steps equivalent to the steps in the above-described embodiments are given the same steps, and description thereof is omitted.

If an affirmative determination is made in step 50, the routine proceeds to step 110, where the vehicle speed VB is determined based on the wheel speed calculation result determined in step 20, and is compared with a preset vehicle speed V0. If it is determined that the vehicle speed VB is lower than V0, the process proceeds to step 410, where the predetermined filter pass frequency band △ f is determined from the filter width df used to extract the resonance frequency f in step 40. Subtract to set the passband of the new filter.

Then, returning to step 40, the above processing is repeated until the deviation between the extracted resonance frequency f and the center frequency fbc of the pass frequency band of the filter used for the extraction becomes equal to or less than the predetermined value f0. If the vehicle speed is equal to or higher than the preset value in step 110, the process returns to step 40 because the change of the pass frequency band is not permitted.

When the frequency deviation falls within the predetermined range in step 50, the effect of the outside air temperature on the tire resonance frequency is corrected in step 70. Next, an eighth embodiment will be described with reference to FIG. The eighth embodiment includes both a step 210 for determining the signal strength and a step 410 for reducing the predetermined frequency width Δf from the pass frequency band of the filter used for extracting the resonance frequency f in the step 40. Is provided. That is,
The pass band of the filter is shifted only when the signal strength is greater than the predetermined value GCO.
If it is smaller than the threshold value, the determination in step 50 is executed, but the frequency band is not shifted in step 410, and the resonance frequency is not substantially extracted.

Note that step 210 shown in FIG. 18 may be applied to step 210 in FIG. In this case, step 40 in FIG. 21 is changed to step 310 in FIG. Next figure
A ninth embodiment will be described based on FIG. Also in the present embodiment, steps that perform the same operations as the above-described embodiments are given the same steps, and description thereof is omitted.

In the ninth embodiment, it is determined in step 110 whether or not the vehicle speed is equal to or higher than the predetermined speed V0.
At 520, a determination is made as to whether the pass frequency band of the filter should be reduced or increased. That is, step 1
If the vehicle speed VB is equal to or higher than the predetermined speed V0 in step 10, the process proceeds to step 510, and the resonance frequency f obtained in step 40 (when the process proceeds to step 510, the resonance frequency obtained in step 40 is replaced by f1
Immediately before proceeding to step 510, an absolute value deviation from the center frequency fbc1 of the band-pass filter used in obtaining the resonance frequency in step 40 is obtained.
It is determined whether this deviation is equal to or smaller than a predetermined deviation f01. If a negative determination is made here, the process proceeds to step 540 and proceeds to step 40.
From the filter width used for obtaining the resonance frequency f1, that is, the frequency range of the filter width Δf set in advance from the pass frequency band of the band-pass filter,
Set a new passband. And step 40
And the resonance frequency f is obtained using the new filter range.

If a negative determination is made in step 110, the process proceeds to step 520. In step 520, the resonance frequency f extracted in step 40 (when proceeding to step 520, the resonance frequency determined in step 40 is expressed as f2), and when the resonance frequency f2 is determined in step 40, It is determined whether or not the absolute value deviation from the center frequency fbc2 of the band-pass filter used for is equal to or smaller than a predetermined deviation f02. Note that the center frequencies fbc1 and fbc2 of the band-pass filter at the time of extracting the resonance frequency in step 40 are updated as needed based on the pass frequency band that becomes the filter width changed when passing through steps 530 and 540, respectively.

The necessity to increase or decrease the filter width based on the vehicle speed depends on the relationship between the intensity of the vibration component included in the wheel speed signal and the vehicle speed. That is, from low vehicle speed to medium vehicle speed (10 km / h to 80 km / h), the tire vibration component is relatively strong, and the vibration component including the resonance frequency included in the wheel speed signal is relatively large. On the other hand, in the high vehicle speed range (80km / h or more), ties and vibration components are relatively weakened. The reason may be that the number of vibration inputs to the tire per unit time due to fine irregularities on the road surface, for example, asphalt, increases, and each vibration input decreases. When the tie or the signal strength is weak, the vibration components including the tire resonance frequency may be dispersed in a wide frequency band. Because of this, the tire signal intensity is sufficient in the low vehicle speed to medium vehicle speed region, so the accuracy is emphasized by gradually narrowing the filter range, and in the high vehicle speed region, tie and air pressure can be estimated. To ensure tire signal strength,
Gradually increase the frequency range of the filter.

Next, a tenth embodiment will be described with reference to FIG. In the tenth embodiment, the pass frequency band of the filter is reduced only when the signal strength determined in step 210, which proceeds from step 40, is equal to or higher than a predetermined signal strength GCO. If it is smaller, the pass frequency band of the filter is increased.

That is, if an affirmative determination is made in step 210, the process proceeds to step 510, where the center frequency fbc1 of the band-pass filter used in extracting the resonance frequency f1 in step 40 and the resonance frequency f1 extracted in step 40
Is determined, and it is determined whether or not the absolute value deviation is within a predetermined deviation f01. If the determination is affirmative, the process proceeds to step 70. If a negative determination is made, step 53
Proceed to 0 to decrease the frequency range of the bandpass filter.

If a negative determination is made in step 210, the process proceeds to step 520, where the center frequency fbc2 of the frequency range of the band-pass filter used when the resonance frequency f2 was extracted in step 40 and the resonance frequency fbc2 are extracted in step 40. It is determined whether or not the absolute value deviation from the resonance frequency f2 is within a predetermined deviation f02. If an affirmative decision is made here, step
Proceeding to 70, if a negative determination is made, the frequency range of the bandpass filter is expanded and increased in step 540. In addition,
Steps 530 and 540 return to step 40 to extract the resonance frequency based on the corrected frequency range of the bandpass filter.

The necessity of increasing or decreasing the filter width, that is, the pass frequency band of the band-pass filter used in step 40, depending on the signal strength is as follows. That is, the relationship between the signal strength of the wheel speed sensor output and the strength of the tire vibration component including the resonance frequency component included in the wheel speed signal is such that when the signal strength is strong, the tire vibration component is relatively large and the tire pressure is estimated. Accuracy can be expected, but when the signal intensity is weak, the magnitude of the tire vibration component is relatively weakened, and the accuracy of tire pressure estimation cannot be expected. Therefore, in the range where the signal strength is strong, the pass frequency band of the band-pass filter is narrowed to improve the accuracy, and in the range where the signal strength is weak, the pass frequency band of the band-pass filter is gradually increased to secure the tie and the signal strength. By increasing the value, it is possible to detect and estimate the tire pressure.

Next, an eleventh embodiment will be described with reference to FIG. In the eleventh embodiment, not only the resonance frequency is corrected based on the outside air temperature, but also the pass frequency band of a preset filter, that is, a band-pass filter is changed in step 30. Here, the band of the pass frequency of the band-pass filter used in step 30 which is stored in the ROM 202 in advance as described above is limited. On the other hand, the resonance frequency f extracted by this filter is affected by the outside air temperature. Therefore, when the outside air temperature is low even at the same tire pressure, the extracted resonance frequency becomes high, and conversely, when the outside air temperature is high. Have a characteristic that the resonance frequency is lowered.

Further, for example, when a sensor for detecting the outside air temperature is arranged in the ECU cover, it is difficult to detect the outside air temperature while the vehicle is running. Therefore, in such a case, the pass frequency band of the filter is initialized based on normal temperature, for example, 20 degrees. In this case, assuming this, when the outside air temperature during traveling of the vehicle is extremely high or low, the difference between the center frequency and the actual resonance frequency in the pass frequency band preset in the filter becomes large. The magnitude of this shift affects the convergence time for bringing the center frequency of the filter closer to the actual resonance frequency.

Therefore, if the pass frequency band of the filter is corrected by the outside air temperature, the start pass frequency band of the filter in the initial stage of the tie or air pressure estimation, that is, immediately after the ignition switch is turned on, can be made regular, and the convergence time of the filter movement can be improved. Can be shortened. Therefore, quick tire pressure estimation can be realized. Hereinafter, after the wheel speed is calculated based on the output of the wheel speed sensor in step 20 which describes the specific flow of the eleventh embodiment, the process proceeds to step 600, and the information of the outside air temperature taken in in step 10 The change correction of the pass frequency band of the filter based on is performed. That is, if the outside air temperature is higher than a reference temperature (for example, 20 degrees) by a predetermined temperature, a correction is made to shift the band of the pass frequency of the filter to a lower side by a certain width. If the outside air temperature is lower than the reference temperature by a predetermined value or more, a correction is made to shift the pass frequency band of the filter to a side higher by a certain width. In step 30, the output of the wheel speed sensor is filtered using the corrected filter.

[Brief description of the drawings]

FIG. 1 is a characteristic diagram showing signal intensity waveforms before and after passing a filter of a frequency component depending on a tire air pressure.

FIG. 2 is a characteristic diagram showing an example of an extracted resonance frequency in the case of a fixed narrow band filter.

FIG. 3 is a characteristic diagram showing a relationship between a resonance frequency and a tire pressure.

FIG. 4 is a block diagram showing a main configuration of the present invention.

FIG. 5 is a block diagram showing a relationship among various sensors, an ECU, and a display unit in the main configuration of the present invention.

FIG. 6 is a configuration diagram illustrating an example of a display device.

FIG. 7 is a configuration diagram showing an ECU.

FIG. 8 is a diagram showing a physical model of a vibration system of a tire suspension.

FIG. 9 is a block diagram showing a control flow of the present invention.

FIG. 10 is a characteristic diagram illustrating a relationship between a resonance frequency and a tire pressure with respect to an outside air temperature.

FIG. 11 is a characteristic diagram showing a specific example of correction of the resonance frequency based on the outside air temperature.

FIG. 12 is a map showing a correction amount of a resonance frequency according to an outside air temperature.

FIG. 13 is a flowchart showing a second embodiment.

FIG. 14 is a flowchart showing a third embodiment.

FIG. 15 is a flowchart showing a fourth embodiment.

FIG. 16 is a reference characteristic diagram when showing a specific calculation method of signal strength.

FIG. 17 is a characteristic diagram showing another example of a method of calculating the vibration input intensity from the road surface.

FIG. 18 is a flowchart showing a fifth embodiment.

FIG. 19 is a flowchart showing a sixth embodiment.

FIG. 20 is a flowchart showing a seventh embodiment.

FIG. 21 is a flowchart showing an eighth embodiment.

FIG. 22 is a flowchart showing a ninth embodiment.

FIG. 23 is a flowchart showing a tenth embodiment.

FIG. 24 is a flowchart showing an eleventh embodiment.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 Wheel speed sensor 20 Electronic control device 30 Indicator 40 Outside air temperature sensor

Claims (13)

[Claims] 1. A detecting means for detecting a signal including a vibration component of a tire when the vehicle is running, and an extracting means for extracting a resonance frequency or a tire spring constant related to a tire pressure from the vibration component detected by the detecting means. When extracting the resonance frequency or the tire spring constant by the extraction means, a signal processing filter that passes the signal containing the vibration component through a predetermined frequency width, and a signal processing filter that passes through the signal processing filter. Air pressure estimating means for estimating the air pressure of the tire based on the resonance frequency or the tire spring constant extracted by the means, the pass frequency of the signal including the vibration component in the signal processing filter while keeping the frequency width constant. The resonance frequency or tire whose band was extracted by the extraction means before the previous time Tire air pressure estimating device characterized by comprising a moving means for moving based on the value constant. 2. The moving means according to claim 1, wherein a resonance frequency or a spring constant extracted last time, or an average value of a resonance frequency or a spring constant obtained as a result of extraction of a reference frequency before the previous time is a substantially center position of the pass frequency band. The tire pressure estimating apparatus according to claim 1, wherein the apparatus moves in the pass frequency band. 3. The method according to claim 1, wherein the moving means is configured to calculate a difference between a center value in the pass frequency band and an average value of a resonance frequency or a spring constant extracted last time or a resonance frequency or a spring constant obtained as a result of extracting a reference frequency before the previous time. The tire pressure estimating device according to claim 1, wherein the pass frequency band is moved so that the value falls within a reference range. 4. The moving means determines whether or not a difference from the center value is within a reference to determine whether to adopt an extraction result by the extracting means to the tire air pressure estimating means, The tire pressure estimating device according to claim 3, wherein the moving unit repeats moving the pass frequency band until the difference from the center value is within a reference. 5. The tire pressure estimating device according to claim 1, wherein the moving unit moves the pass frequency band according to an ambient temperature. 6. The moving means according to claim 1, wherein said moving means moves said pass frequency band only when a vehicle speed or a signal strength passing through said signal processing filter satisfies a predetermined reference value. The tire pressure estimating apparatus according to any one of the above. 7. The moving means according to claim 1, wherein the moving means permits or prohibits moving the pass frequency band according to a required response time of a system in the tire pressure estimating device. The tire pressure estimation device according to any one of claims 1 to 4. 8. A detecting means for detecting a signal including a vibration component of a tire when the vehicle is running, and an extracting means for extracting a resonance frequency or a tire spring constant related to a tire pressure from the vibration component detected by the detecting means. A signal processing filter that passes the signal containing the vibration component, and a pneumatic pressure estimating unit that estimates the air pressure of the tire based on a resonance frequency or a tire spring constant extracted by the extracting unit by passing the signal processing filter. A changing means for changing a width of a pass frequency band of a signal including the vibration component in the signal processing filter. 9. The extracting means may determine the width of the pass frequency band to be passed through the signal processing filter, the signal strength of a signal which has passed through the signal processing filter before the previous time, the vehicle speed, or the extraction means before the previous time. The tire pressure estimation device according to claim 8, wherein the change is performed based on at least one of the extracted resonance frequency or the tire spring constant. 10. The tire pressure according to claim 8, wherein the changing unit changes the width of the pass frequency band in accordance with a required response time of a system in the tire pressure estimation device. Estimation device. 11. The method according to claim 8, wherein the changing unit changes the width of the pass frequency band only when a vehicle speed or a signal intensity passing through the signal processing filter satisfies a predetermined reference value. Item 11. A tire pressure estimation device according to any one of Items 10. 12. A detecting means for detecting a signal including a vibration component of a tire when the vehicle is running, and an extracting means for extracting a resonance frequency or a tire spring constant related to a tire pressure from the vibration component detected by the detecting means. A signal processing filter that passes a signal containing the vibration component through a reference frequency width when the resonance frequency or the tire spring constant is extracted by the extraction means; and a resonance extracted by the extraction means by passing the signal processing filter. Air pressure estimating means for estimating the air pressure of the tire based on a frequency or a tire spring constant; and a signal including the vibration component in the signal processing filter based on a resonance frequency or a tire spring constant extracted by the extracting means before last time. Moving the pass frequency band and the vibration component A moving changing means for changing the width of the pass frequency band of the signal including tire pressure estimating apparatus comprising: a. 13. The movement changing means first changes the width of the pass frequency band from a wide frequency band to a narrow width.
2. The method according to claim 1, wherein the shift of the pass frequency band is performed.
3. The tire pressure estimation device according to 2.