JP2001074579A - Method and device for detecting pneumatic pressure of tire - Google Patents

Abstract

PROBLEM TO BE SOLVED: To properly distinguish resonance frequencies of a tire from frequencies other than these, to enhance estimation precision for pneumatic pressure of the tire. SOLUTION: A wheel speed sensor 2 is arranged in each tire TR of a vehicle 1. Vibration components of a wheel speed caused by vibration of the tire are extracted from a wheel speed signal of the speed sensor 2 to find the resonance frequencies of the tire, and pneumatic pressure of the tire is detected based on the found resonance frequencies. A distribution of the resonance frequencies of the tire is calculated therein. A distribution condition in the resonance frequencies of the tire is determined, based on the calculated distribution, and detection for the pneumatic pressure of the tire based on the estimated resonance frequencies of the tire is inhibited, when the distribution condition is determined to be not uniform.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention estimates a tire resonance frequency based on a vibration electric signal including a vibration frequency component of a vehicle tire, and detects a tire pressure of the vehicle based on the estimated tire resonance frequency. The present invention relates to a tire pressure detection method and a tire pressure detection device.

[0002]

2. Description of the Related Art Hitherto, various tire pressure detecting methods and tire pressure detecting devices for detecting tire pressure of a vehicle have been proposed. In the tire pressure detection method and the tire pressure detection device, a vibration electric signal including a vibration frequency component of a tire of a vehicle, for example, a vibration component of a wheel speed caused by a tire vibration is extracted from a wheel speed signal of a wheel speed sensor. The resonance frequency of the tire is determined, and the tire pressure is detected based on the determined resonance frequency.

[0003]

In detecting the tire air pressure, white noise-like vibration, that is, vibration uniformly distributed in each frequency band, is input from the road surface to excite the tire. On this assumption, the resonance frequency of the tire is determined.

However, in practice, vibrations distributed uniformly in each frequency band like white noise from a road surface are not always input, and vibrations concentratedly distributed in a specific frequency band are input. There is. Such vibration concentratedly distributed in a specific frequency band is input, for example, when the vehicle is traveling on a road surface having periodic undulations in a sine curve shape or on a road surface cut off by a shovel.

When such vibrations distributed in a specific frequency band are inputted, the specific frequency is set as the tire resonance frequency, and the tire pressure is erroneously detected based on the specific frequency. is there.

In order to avoid such erroneous detection of the tire air pressure, various methods have been proposed for distinguishing between the resonance frequency of the tire and other frequencies, for example, as described in Japanese Patent Application Laid-Open No. 9-104208. What was done is known. In the method described in the publication, the magnitude of the road surface input or the magnitude of the damping coefficient of the vibration component is estimated based on the wheel speed signal from the wheel speed sensor, and the magnitude of the road surface input or the magnitude of the damping coefficient is determined in accordance with the magnitude of the road surface input or the magnitude of the damping coefficient. To distinguish the tire resonance frequency from other frequencies. If the frequency is recognized as a frequency other than the resonance frequency of the tire, the air pressure of the tire is not detected, and an attempt is made to improve the accuracy of estimating the air pressure.

However, the vibration input from the road surface changes from moment to moment. Therefore, the magnitude of the road surface input and the magnitude of the damping coefficient can sufficiently distinguish the resonance frequency of the tire from other frequencies. The reality is that you can't. In other words, the distinction between the tire resonance frequency and the other frequencies is a frequency-related problem, and a sufficient causal relationship is not recognized between the magnitude of the road surface input and the magnitude of the damping coefficient.

SUMMARY OF THE INVENTION An object of the present invention is to provide a tire pressure detecting method and a tire pressure detecting device capable of suitably distinguishing a tire resonance frequency from other frequencies and improving the estimation accuracy of the tire pressure. It is in.

[0009]

SUMMARY OF THE INVENTION In order to solve the above problems, the invention according to claim 1 estimates a resonance frequency of a tire based on a vibration electric signal including a vibration frequency component of a tire of a vehicle. In the tire air pressure detection method of detecting the tire air pressure based on the estimated tire resonance frequency, a distribution of the tire resonance frequency is calculated, and a distribution state of the tire resonance frequency is calculated based on the calculated distribution. If it is determined that the distribution of the resonance frequency of the tire is not uniform, the gist of the present invention is to prohibit the detection of the air pressure of the tire based on the estimated resonance frequency of the tire.

According to a second aspect of the present invention, in the tire pressure detecting method according to the first aspect, the distribution of the resonance frequency of the tire is calculated by at least one statistical method of variance, standard deviation, and frequency. The point is that

According to a third aspect of the present invention, a tire resonance frequency is estimated based on a vibration electric signal including a vibration frequency component of a tire of a vehicle, and an air pressure of the tire is detected based on the estimated tire resonance frequency. In the tire air pressure detecting device to perform, the distribution calculating means for calculating the distribution of the resonance frequency of the tire, the determination means for determining the distribution state of the resonance frequency of the tire based on the calculated distribution, and the determination means The gist of the present invention is to provide a prohibition unit for prohibiting the detection of the tire air pressure based on the estimated tire resonance frequency when it is determined that the distribution of the tire resonance frequency is not uniform.

According to a fourth aspect of the present invention, in the tire pressure detecting device according to the third aspect, the distribution calculating means calculates the resonance frequency of the tire by at least one statistical method of variance, standard deviation and frequency. The point is to calculate the distribution of.

(Operation) In general, when a tire resonance frequency is estimated based on a vibration electric signal including a vibration frequency component of a vehicle tire, and the tire pressure is detected based on the estimated tire resonance frequency, It is assumed that vibrations like white noise, that is, vibrations uniformly distributed in each frequency band, are input from the road surface to excite the tire. Therefore, when vibrations that are concentrated and distributed in a specific frequency band from the road surface are input, the specific frequency is set as the tire resonance frequency, and the tire pressure may be erroneously detected based on the specific frequency.

[0014] Here, when vibrations that are concentrated and distributed in a specific frequency band from the road surface are input and this specific frequency is estimated as a tire resonance frequency, the resonance frequency varies with time in the distribution. Have been confirmed by the present inventors to be small and concentrated at a specific frequency (the distribution is not uniform).

According to the first and third aspects of the present invention, when it is determined that the estimated distribution of the resonance frequency of the tire is not uniform, the tire based on the estimated tire resonance frequency is determined. Air pressure detection is prohibited. Therefore,
When the input from the road surface is not uniform in each frequency band, erroneous detection of the tire air pressure can be avoided, and the estimation accuracy of the tire air pressure is improved.

According to the second and fourth aspects of the present invention, the distribution of the resonance frequency of the tire can be calculated very easily by at least one statistical method of variance, standard deviation and frequency.

[0017]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS (First Embodiment) A tire pressure alarm device using a tire pressure detection device according to a first embodiment of the present invention will be described below with reference to the drawings. In FIG. 1, each tire TR of the vehicle 1 includes:
As a wheel speed detector for detecting the rotation speed, a wheel speed sensor (represented by 2) is provided. The wheel speed sensor 2 is, for example, a well-known electromagnetic induction type sensor including a toothed rotor that rotates with the rotation of each wheel and a pickup provided to face the tooth portion of the rotor. Although a device configured to output a digital signal corresponding to the rotation speed is used, another system may be used. FIG. 2 shows an example of a change in wheel speed. When a vibration component is extracted, the state shown in FIG. 3 is obtained. Each wheel speed sensor 2 is connected to an electronic control unit 3, and an output signal of the wheel speed sensor 2 is
The microcomputer 20 is configured to determine a decrease in the air pressure of the tire TR, which will be described later, and to drive the alarm device 4 according to the determination result.

The microcomputer 20 has a general configuration including an input port 21, a CPU 22, a ROM 23, and a RAM.
24, an output port 25, and the like are connected to each other via a common bus, and an output signal of the wheel speed sensor 2 is input from the input port 21 and processed by the CPU 22,
The output port 25 is configured to output to the alarm device 4. In addition, a wavelet function (for example, Gabor function) 11 is set for the microcomputer 20. In the microcomputer 20, RO
M23 stores a program corresponding to the flowchart shown in FIG. 4, and the CPU 22 executes the program while an ignition switch (not shown) is closed,
The RAM 24 temporarily stores variable data necessary for executing the program.

Here, the definition of the wavelet transform as a premise of the invention of this application and the terms used in this application will be clarified. First, a function serving as a basis of the wavelet transform is called a basic wavelet function h (t), whose norm is normalized by a square integrable function, and is localized at least in the time domain. This basic wavelet function h (t) is represented by the following equation 1 called an admissible condition.
It can be expressed that the equation holds. Equation 1 indicates that the DC component (average value) of the signal is zero.

[0020]

(Equation 1) Then, as shown in the following equation 2, the basic wavelet function is scale-converted by a times, and the origin is shifted by b to set the wavelet function.

[0021]

(Equation 2) When the function to be analyzed is f (t), the wavelet function is defined as shown in the following equation (3).
In this equation, F (a, b) represents a wavelet coefficient, <> represents an inner product, and * represents a complex conjugate.

[0022]

(Equation 3) The wavelet function used for analysis is called an analyzing wavelet (basic wavelet function).
Various functions such as a Gabor function are used. For example,
Morle which is a kind of Gabor function shown in the following equation (4)
The t wavelet is known as an analyzing wavelet suitable for analyzing a signal having a singular point whose derivative is discontinuous.

[0023]

(Equation 4) In the microcomputer 20, a decrease in the air pressure of the tire TR is determined as described later, and the determination result is output to the alarm device 4. The alarm device 4 is configured so that, for example, a lamp (not shown) is turned on when it is determined that the air pressure of the tire TR has decreased. Or,
The decrease in air pressure may be reported by a display and / or sound.

In the tire pressure warning device of the present embodiment configured as described above, the electronic control unit 3 performs a series of processes relating to the detection of the pressure of the tire TR. That is, when an ignition switch (not shown) is closed, execution of a program corresponding to the flowchart of FIG. 4 starts, and a predetermined cycle time (for example, 5 milliseconds)
Is repeated.

As shown in FIG. 4, when the processing shifts to this routine, first in step 101, the CPU 2
2 sets the period count value j in the RAM 24 to “1”. This period count value j is a predetermined time (for example, 1
This is a count value set corresponding to a certain period Tj divided for each second), and in the present embodiment, “1” to “12”.
It counts up to "0".

CP in which the period count value j is set to "1"
U22 proceeds to step 102, and stores various data in RA
After reading from M24, the process proceeds to step 103.
The CPU 22 that has proceeded to step 103 calculates the wheel speed based on the output signal of the wheel speed sensor 2. The wheel speed is used for estimating the air pressure as a vibration electric signal including a vibration frequency component of the tire TR.

After calculating the wheel speed, the CPU 22 proceeds to step 104 to calculate the filter output. In the calculation of the filter output, the oscillating electric signal output from the wheel speed sensor 2 is converted into, for example, the above-described function f (t) to be analyzed.
Is input to the microcomputer 20, and the microcomputer 20 converts the frequency scale parameter a (scale (a)) into the shift parameter b.
Wavelet transform is performed according to (time position (b)), and wavelet coefficients F (a, b) are calculated. That is, the convolution of the basic wavelet function with respect to the function f (t) is performed.

FIG. 5 shows an aspect of the wavelet coefficient F (a, b) by the wavelet analysis. The magnitude of the wavelet coefficient F (a, b) is distinguished by a contour pattern as shown in FIG. Note that, when this is three-dimensionally displayed, it is as illustrated in FIG. 6 (in each of the figures, the scale parameter a is displayed in a logarithmic manner, but FIGS. 5 and 6 do not directly correspond to each other). Examples of the wavelet function include a Gabor function, a Mexican hat function, a French function, and a Haar function.

The filter output calculation in step 104 is performed at five predetermined frequencies in the frequency band near the original tire resonance frequency where the tire resonance frequency is considered to vary, for example, 35 Hz, 37.5 Hz, 40 Hz, 42.
It is performed at 5 Hz and 45 Hz, and has a wavelet coefficient F (a, b) _{35 at} a frequency of 35 Hz and a frequency of 37.5.
Wavelet coefficient F (a, b) _37.5 at Hz, wavelet coefficient F (a, b) ₄₀ at frequency ₄₀ Hz, wavelet coefficient F (a, b) at frequency 42.5 Hz
_42.5 and the wavelet coefficient F at a frequency of 45 Hz
(A, b) ₄₅ is required. The predetermined frequency at which the filter output operation is performed is not limited to five, and may be performed at least three or more predetermined frequencies. Further, the wavelet coefficient corresponding to the selected frequency may be combined in addition to the above.

After calculating the filter output, the CPU 22
The process proceeds to step 105 to perform an addition value calculation. This addition
In the arithmetic operation, the weight calculated in step 104 is calculated.
Bullet coefficient F (a, b)₃₅, F (a, b)_37.5, F
(A, b)₄₀, F (a, b) _42.5, And F (a, b)₄₅
, 200 pieces (1 second / 5 mm) in the period Tj
Second) addition value (wavelet coefficient addition value) SFj
(A, b)₃₅, SFj (a, b)_37.5, SFj (a,
b)₄₀, SFj (a, b)_42.5, And SFj (a, b)
₄₅Is calculated.

After calculating the added value, the CPU 22 proceeds to step 106 to execute a maximum value process. In this maximum value processing, these wavelet coefficient added values SFj
(A, b) ₃₅ , SFj (a, b) _37.5 , SFj (a,
b) ₄₀ , SFj (a, b) _42.5 and SFj (a, b)
Of _45, the frequency fj _i and frequency fj that is adjacent to the back and forth corresponding to the wavelet coefficients addition value becomes the maximum value
_i-1 and fj _{i + 1} and three frequencies fj _i-1 and f
wavelet coefficient addition value SF corresponding to j _i , fj _{i + 1}
j (a, b) _i-1 , SFj (a, b) _i , and SFj
(A, b) Extract _{i + 1} . For example, in the example shown in FIG. 7, since the wavelet coefficient addition value SFj (a, b) _{40 at} the frequency of 40 Hz is the maximum value, the frequencies 37.5 Hz, 40 Hz, and 42.5 Hz
Each frequency _{fj i-1, fj i,} fj i + 1 and then, wavelet coefficients addition value SFj corresponding to the same frequency (a,
b) _37.5 , SFj (a, b) ₄₀ and SFj (a, b)
_42.5 is calculated by adding the wavelet coefficient sum SFj (a,
b) _i-1 , SFj (a, b) _i and SFj (a, b)
_{i + 1} .

After executing the maximum value processing, the CPU 22 proceeds to step 107 to execute the second approximation processing. This 2
In the next approximation processing, the wavelet coefficient added value SF
j (a, b) _i-1 , SFj (a, b) _i , and SFj
(A, b) Waveform approximation processing for obtaining a quadratic approximation curve passing through _{i + 1} is performed. That is, the wavelet coefficient sum SF
j (a, b) _i-1 , SFj (a, b) _i , and SFj
(A, b) Using _{i + 1} , a constant k1 in the following equation
j, k2j, and k3j are calculated by the least square method. SFj (a, b) _n = k1j × fj _n ＾ 2 + k2j × fj
_n + k3j (n = i-1, i, i + 1) These constants k1j, k2j, and k3j are calculated by the following equation (5).

[0033]

(Equation 5) The value of the inverse matrix in the above equation (5) is a constant calculated based on a preselected frequency.
It is a value stored in advance in M23.

After executing the quadratic approximation processing, the CPU 22 proceeds to step 108, where the calculated constants k1j, k1
The road surface feature amounts K1j, K2j, and K3j are calculated using 2j and k3j.
Ask for. These road surface features K1j, K2j, K3j
Is the constant k1j, k2j, an expression based on k3j, SFj (a, b) n = K1j (fj n -K2j) ^ 2 + K
3j (n = i-1, i, i + 1), which is the value when deformed, and K1j = k1j K2j = -k2j / (2k1j) K3j = k3j-k2j２2 / (4k1j).

Here, the road surface feature K3j represents the maximum value (peak) of the wavelet coefficient addition value SFj (a, b) during the period Tj. The road surface feature K2j represents the frequency at the maximum value of the wavelet coefficient addition value SFj (a, b), and corresponds to the resonance frequency. Further, the road surface feature K1j represents a feature corresponding to a Q factor indicating the sharpness of resonance of the vibration system, and the reciprocal thereof (1 / −K1j) represents a feature of a frequency width.

The CPU 22 sets the calculated road surface feature values K1j, K2j, and K3j and proceeds to step 109 to determine whether or not the period count value j is "120". Here, if it is determined that the period count value j is not “120”, the CPU 22 proceeds to step 110,
After incrementing the count value j for the same period by “1”,
Steps 102 to 109 are repeated. Such processing is performed in each case in which the period Tj becomes the period T1 to T120, respectively, where the road surface feature amounts K1j, K2j, and K3
This is a process for calculating j (j = 1 to 120).

If it is determined in step 109 that the period count value j is "120", the CPU 22 proceeds to step 111. CPU2 shifted to step 111
2 tests the resonance frequency. This resonance frequency test is
As shown in the flowchart of FIG.
1, the road surface characteristic amount (resonance frequency) K2j (j
= 1 to 120), the average value M (K2) and the variance V (K2) are calculated based on the following equations (6) and (7).

[0038]

(Equation 6)

[0039]

(Equation 7) After calculating the average value M (K2) and the variance V (K2), the CPU 22 proceeds to step 202 and determines whether or not the variance V (K2) is equal to or greater than a predetermined value V0. The predetermined value V0 is a suitable value for determining whether or not the input from the road surface is uniformly distributed in each frequency band.
The value is stored in advance in M23, but may be a value calculated as a learning value, for example.

Here, the variance V (K2) is equal to a predetermined value V0.
If it is determined that the above, since there is a predetermined variation in the road surface characteristic amount K2j, it is assumed that the input from the road surface is uniformly distributed in each frequency band, and the routine proceeds to step 203, where the resonance frequency setting flag XK2 Is set to “1”. Then, the process goes to step 204 to set the resonance frequency K2 to the above average value M (K2), and then goes to step 112 in FIG.

On the other hand, if the variance V (K2) is determined to be less than the predetermined value V0, it is assumed that the road surface characteristic amount K2j has little variation, and that a specific frequency band is being subjected to the force from the road surface. The process proceeds to 205, where the resonance frequency setting flag XK2 is set to “0”. Then, the process proceeds to step 112 of FIG.

In step 112, the CPU 22 determines whether or not the resonance frequency setting flag XK2 is "1". Here, when the resonance frequency setting flag XK2 is “0”, since the resonance frequency K2 is not set,
The CPU 22 once ends the subsequent processing.

On the other hand, when the resonance frequency setting flag XK2 is "1", the CPU 22 proceeds to step 113 on the assumption that the calculated resonance frequency K2 indicates a resonance frequency corresponding to the tire pressure. And
The CPU 22 determines whether the resonance frequency K2 is smaller than a predetermined value K. Note that the predetermined value K is a value stored in advance in the ROM 23 as a suitable value for determining whether or not the tire pressure has decreased.

In step 112, the resonance frequency K2
Is determined to be smaller than the predetermined value K, the CPU 22
Assuming that the resonance frequency of the tire has significantly decreased, that is, the tire pressure has decreased, step 1
Proceed to 14 to output an air pressure alarm signal to the alarm device 4,
In the alarm device 4, for example, an alarm is issued by turning on a lamp (not shown).

On the other hand, if it is determined in step 113 that the resonance frequency K2 is equal to or higher than the predetermined value K, the CPU 22 determines that the decrease in the tire resonance frequency is small and the tire pressure is sufficient, and temporarily terminates the subsequent processing. .

As described in detail above, according to the present embodiment, the following effects can be obtained. (1) In the present embodiment, if the variance V (K2) of the road surface feature amount K2j (j = 1 to 120) corresponding to the resonance frequency is equal to or more than the predetermined value V0, the input from the road surface is uniform in each frequency band. , And the average value M (K2) of the road surface feature amounts K2j (j = 1 to 120) obtained during this period is set as the resonance frequency K2. Then, based on the resonance frequency K2, the tire pressure was detected.

On the other hand, the road surface characteristic amount K2j (j = 1 to 1)
If the variance V (K2) in 20) is less than the predetermined value V0, it is assumed that a force from the road surface is being received in a specific frequency band, and the tire air pressure is not detected. Therefore, erroneous detection of the tire pressure when the input from the road surface is not uniform in each frequency band can be avoided, and the estimation accuracy of the tire pressure can be improved.

(2) In the present embodiment, the road surface characteristic amount K2j
The distribution of (j = 1 to 120) can be calculated very easily from the variance V (K2). (3) In the present embodiment, the constant k1 in the second approximation processing
j, k2j, k3j, that is, road surface feature amounts K1j, k2
j and K3j can be easily calculated by multiplying the values of the inverse matrix stored in advance in the ROM 23 and calculated based on the frequency selected in advance.

(Second Embodiment) A tire pressure alarm device using a tire pressure detection device according to a second embodiment of the present invention will be described below with reference to the drawings. Note that the second embodiment differs from the first embodiment only in that a standard deviation is used instead of the variance V (K2) used in the resonance frequency test in step 111 (FIG. 4) of the first embodiment. Detailed description of the parts will be omitted.

In the present embodiment, as shown in the flowchart of FIG. 9, the CPU 22 proceeds to step 111, and in step 301, based on the road surface characteristic amount (resonance frequency) K2j (j = 1 to 120), 6
The average value M (K2) and the standard deviation σ (K2) are calculated based on the equation and the following equation (8).

[0051]

(Equation 8) Then, the average value M (K2) and the standard deviation σ (K
The CPU 22 having calculated 2) proceeds to step 302, and determines whether or not the standard deviation σ (K2) is equal to or larger than a predetermined value σ0. The predetermined value σ0 is a value previously stored in the ROM 23 as a suitable value for determining whether or not the input from the road surface is uniformly distributed in each frequency band. Value.

Here, if the standard deviation σ (K2) is determined to be equal to or greater than the predetermined value σ0, the road surface characteristic amount K2j has a predetermined variation, and the input from the road surface is uniformly distributed in each frequency band. In step 303, the resonance frequency setting flag XK2 is set to "1". Then, the process proceeds to step 304, where the resonance frequency K2 is set to the average value M (K2).
Move to

On the other hand, the standard deviation σ (K2) is equal to a predetermined value σ
If it is determined to be less than 0, it is assumed that the road surface characteristic amount K2j has little variation, so that it is assumed that a force from the road surface is received in a specific frequency band, and the process proceeds to step 305 to set the resonance frequency setting flag XK2 to “0”. Set to. Then, the process proceeds to step 112 of FIG.

In the step 112, the CPU 22 selectively executes the judgment of the calculated resonance frequency K2 (step 113) according to the value of the resonance frequency setting flag XK2 as in the first embodiment. is there.

As described in detail above, according to the present embodiment, the same effects as (1) to (3) in the first embodiment can be obtained. (Third Embodiment) Hereinafter, a tire pressure alarm device using a tire pressure detection device according to a third embodiment of the present invention will be described with reference to the drawings. The third
In the embodiment, step 111 of the first embodiment is used.
The variance V adopted in the resonance frequency test of FIG. 4
The only difference is that the frequency is used instead of (K2), and a detailed description of similar parts will be omitted.

In the present embodiment, the CPU 22 that has proceeded to step 111, as shown in the flowchart of FIG. 10, in step 401, based on the road surface characteristic amount (resonant frequency) K2j (j = 1 to 120), The average value M (K2) is calculated based on Equation 6.

Then, the CP for which the average value M (K2) was calculated
U22 proceeds to step 402 and calculates the K2 frequency. The K2 frequency belongs to each of the divided frequencies (hereinafter, referred to as “frequency group”) when a frequency band in which the tire resonance frequency is considered to fluctuate is divided into a plurality at predetermined frequency intervals (for example, 1 Hz). This is the number of road surface feature values K2j. Figure As shown in 12, the frequency groups in the present embodiment, the road surface feature quantity value of K2j respectively less than the frequency fr _1, the frequency fr ₁ or more · fr
Less than ₂ ,..., Frequency fr _p-1 or more and less than fr _p (fr ₁ <f
p pieces of r ₂ <... <fr _p ) are formed.

Then, the CPU proceeds to step 402.
Reference numeral 22 denotes frequency counters cfr ₁ , cf in step 501 as shown in the flowchart of FIG.
Initialize r ₂ ,..., cfr _p (set to zero). These frequency counter cfr _1, cfr _2, ..., cfr _p is the corresponding frequency group (less than the frequency fr _1, the frequency fr ₁ or more · fr less than _2, ..., the frequency fr _p-1 or more · fr less than _p) road belonging to Each time the feature K2j is confirmed, “1” is set,
The K2 frequency is counted as being incremented.

After the initialization, the CPU 22 proceeds to step 502 and sets the count value m to "1". The count value m is determined by the road surface characteristic amount K2j (j =
1 to 120) are count values for performing the above grouping.

The CPU 22 having set the count value m proceeds to step 503, where the road surface characteristic amount K2m is set to the frequency fr.
Judge whether it is less than ₁ . Here, CPU 22 when the road characteristic amount K2m is determined to be less than the frequency fr _1, the process proceeds to step 505, "1" and the frequency counter cfr _1, increments the process proceeds to step 507. On the other hand, CPU 22 when the road characteristic amount K2m is determined that the frequency fr ₁ or more, the process proceeds to step 504, the road feature amount K2m determines whether less than the frequency fr _2. Here, CPU 22 when the road characteristic amount K2m is determined to be less than the frequency fr _2, the process proceeds to step 506, "1" and the frequency counter cfr _2, increments the process proceeds to step 507.

The CPU 22 executes the same processing for the frequency counter corresponding to each frequency group, and determines in step 507 whether or not the count value m is “120”. Here, when it is determined that the count value m is not “120”, the CPU 22 proceeds to step 508,
The count value m is incremented by “1”, and the processing of steps 503 to 507 is repeatedly executed.

On the other hand, if it is determined in step 507 that the count value m is “120”, the CPU 22 determines that the counting according to the frequency group has been completed for all the road surface feature amounts K2m, and proceeds to step 403 in FIG. I do.

The CPU 22 that has proceeded to step 403
The counted frequency counters cfr ₁ , cfr ₂ ,
.., Cfr _p maximum value MAX (cfr ₁ , cfr ₂ ,.
It is determined whether or not cfr _p ) is less than a predetermined value C. The predetermined value C is a value stored in advance in the ROM 23 as a suitable value for determining whether or not the input from the road surface is uniformly distributed in each frequency band. Value.

Here, the maximum value MAX (cfr ₁ , cfr
fr ₂ ,..., cfr _p ) are determined to be less than the predetermined value C.
Since there is a predetermined variation in the road surface characteristic amount K2j, it is assumed that the input from the road surface is uniformly distributed in each frequency band, and the process proceeds to step 404 to set the resonance frequency setting flag X
Set K2 to "1". And furthermore, step 405
Then, the resonance frequency K2 is set to the average value M (K2), and the flow shifts to step 112 in FIG.

On the other hand, the maximum value MAX (cfr ₁ , cf
If r ₂ ,..., cfr _p ) is determined to be equal to or greater than the predetermined value C, it is determined that the road surface feature amount K2j has little variation, and it is assumed that a force from the road surface has been received in a specific frequency band. To set the resonance frequency setting flag XK2 to "0"
Set to. Then, the process proceeds to step 112 of FIG.

In step 112, the CPU 22 selectively executes the determination of the calculated resonance frequency K2 (step 113) in accordance with the value of the resonance frequency setting flag XK2, as in the first embodiment. is there.

As described in detail above, according to the present embodiment, effects similar to the effects (1) to (3) of the first embodiment can be obtained. Note that the embodiment of the present invention is not limited to the above-described embodiment, and may be modified as follows.

In the above embodiments, the output signal (wheel speed) of the wheel speed sensor 2 is used as the vibration electric signal including the vibration frequency component of the tire of the vehicle. The speed of change or acceleration of a vehicle height sensor or the like may be used.

In the above embodiments, a wavelet filter composed of an FIR (finite impulse response) filter is generally used for the wavelet operation. However, in order to reduce the load on the microcomputer, the same impulse as the wavelet transform is used. An IIR (infinite impulse response) type filter having a response or a frequency response can be used in combination. Regarding the combination of IIR filters, for example, when a Gabor function is used as a mother function, it is divided into a real part and an imaginary part. Therefore, in practice, √ ((real part) ＾ 2 + (imaginary part) ＾ 2) Although it is necessary to obtain it, any one of | real part | + | imaginary part |, max (| real part |, | imaginary part |), low-pass | real part |, and low-pass | imaginary part | Therefore, the burden on the microcomputer can be further reduced.

In each of the above embodiments, a wavelet filter is used as a frequency filter. However, this may be a general-purpose band-pass filter having a predetermined pass band.

In the second-order approximation processing in each of the above-described embodiments, it may be difficult to calculate the constant k2j (road surface characteristic amount K2j) by the least squares method due to road surface input and disturbances such as tires. The road surface feature K2j is set only when the absolute value of the road surface feature K1j) is equal to or larger than a predetermined value, that is, when the predetermined resonance sharpness is confirmed in the wavelet coefficient addition value SFj (a, b). Is also good. In this case, since the constant k2j (the road surface characteristic amount K2j) having low reliability is excluded, the estimation accuracy of the tire pressure can be further improved.

In the above embodiments, the maximum value processing or the like is performed based on the added value (wavelet coefficient added value) in the period Tj. For example, this is the average value (wavelet coefficient average value) in the period Tj. May be performed based on the maximum value processing.

In the above embodiments, the average value (arithmetic mean) M (K2) of the road surface feature values K2j (j = 1 to 120) is adopted as the resonance frequency K2. A geometric mean or harmonic mean of (j = 1 to 120) may be adopted.

As the resonance frequency K2, the road surface feature K2j (j = 120) calculated immediately before may be employed. In the above embodiments, the resonance frequency is calculated using the wavelet filter. However, the resonance frequency may be calculated using, for example, FFT (Fast Fourier Transform).

In each of the above embodiments, the resonance frequency is calculated by the second-order approximation processing. However, for example, a peak may be directly detected from a frequency characteristic to detect a corresponding resonance frequency.

Next, technical ideas other than the claims that can be grasped from the above embodiments will be described below together with their effects. (A) In the tire pressure detection method according to claim 1 or 2, the Q factor of the tire is estimated based on the detected wheel speed, and the magnitude of the estimated Q factor of the tire is small. Is a step of prohibiting the detection of the tire air pressure based on the estimated tire resonance frequency.

According to this method, when the estimated Q factor of the tire is small, the detection of the tire air pressure based on the estimated tire resonance frequency is prohibited. In general, when the estimated Q factor of the tire is small, the reliability of the estimated resonance frequency of the tire is low. Therefore, by prohibiting the detection of the tire air pressure based on such a low-reliability tire resonance frequency, the estimation accuracy of the tire air pressure is improved.

(B) The tire pressure detecting device according to claim 3 or 4, wherein a Q factor estimating means for estimating the Q factor of the tire based on the detected wheel speed, and a Q factor of the estimated tire. A tire pressure detecting device, comprising: a Q factor prohibiting unit that prohibits detection of the tire pressure based on the estimated tire resonance frequency when the factor is small.

According to this configuration, when the estimated Q factor of the tire is small, the detection of the tire air pressure based on the estimated tire resonance frequency is prohibited by the Q factor prohibiting means. . Therefore, by prohibiting the detection of the tire air pressure based on the low-reliability tire resonance frequency, the estimation accuracy of the tire air pressure is improved.

(C) The vibration electric signal containing the vibration frequency component of the tire of the vehicle is converted into a wavelet function which is enlarged / reduced by a scale parameter with respect to at least three predetermined frequencies based on a temporally localized basic wavelet function. A wavelet transform is performed according to a shift parameter indicating a time position, a wavelet coefficient is calculated by the wavelet transform, and an approximate curve is obtained by a least square method using the wavelet coefficient at each predetermined frequency by a least-square method to obtain a tire resonance frequency. In the tire air pressure detection method of detecting the tire air pressure based on the estimated tire resonance frequency, a tire resonance frequency distribution is calculated, and the tire resonance is calculated based on the calculated distribution. Judging the frequency distribution situation, the resonance frequency of the tire If the distribution is determined not to be uniform, the air pressure detection method of the tire and inhibits the detection of the air pressure of the tire based on the resonance frequency of the estimated tire.

According to the method, when it is determined that the distribution of the estimated resonance frequency of the tire is not uniform,
Detection of the tire pressure based on the estimated tire resonance frequency is prohibited. Therefore, erroneous detection of the tire pressure when the input from the road surface is not uniform in each frequency band can be avoided, and the estimation accuracy of the tire pressure can be improved.

(D) A vibration electric signal including a vibration frequency component of a tire of a vehicle is converted into a wavelet function enlarged / reduced by a scale parameter with respect to at least three predetermined frequencies based on a basic wavelet function localized in time. A wavelet transform is performed according to a shift parameter indicating a time position, a wavelet coefficient is calculated by the wavelet transform, and an approximate curve is obtained by a least square method using the wavelet coefficient at each predetermined frequency by a least-square method to obtain a tire resonance frequency. In the tire air pressure detecting device for detecting the tire air pressure based on the estimated tire resonance frequency, distribution calculation means for calculating the distribution of the tire resonance frequency, based on the calculated distribution A judgment tool for judging the distribution status of the resonance frequency of the tire And prohibiting means for prohibiting detection of the tire air pressure based on the estimated tire resonance frequency when the determining means determines that the distribution of the resonance frequency of the tire is not uniform. A tire pressure detection device characterized by the above-mentioned.

According to the above configuration, when it is determined that the distribution of the estimated resonance frequency of the tire is not uniform,
Detection of the tire pressure based on the estimated tire resonance frequency is prohibited. Therefore, erroneous detection of the tire pressure when the input from the road surface is not uniform in each frequency band can be avoided, and the estimation accuracy of the tire pressure can be improved.

[0084]

As described in detail above, according to the first and third aspects of the present invention, it is possible to avoid erroneous detection of the tire air pressure when the input from the road surface is not uniform in each frequency band. Thus, the estimation accuracy of the tire pressure can be improved.

According to the second and fourth aspects of the present invention, the distribution of the resonance frequency of the tire can be calculated very easily by at least one statistical method of variance, standard deviation and frequency.

[Brief description of the drawings]

FIG. 1 is a schematic diagram showing a tire pressure warning device to which a first embodiment of the present invention is applied.

FIG. 2 is a graph showing an example of a change state of a wheel speed.

FIG. 3 is a graph showing an example of a vibration state of a wheel speed.

FIG. 4 is a flowchart showing the embodiment.

FIG. 5 is a graph showing an example of a mode of a wavelet coefficient.

FIG. 6 is a three-dimensional graph showing an example of a mode of a wavelet coefficient.

FIG. 7 is a graph for explaining how to obtain constants k1, k2, and k3.

FIG. 8 is a flowchart showing the embodiment.

FIG. 9 is a flowchart showing a second embodiment of the present invention.

FIG. 10 is a flowchart illustrating a third embodiment of the present invention.

FIG. 11 is a flowchart showing the embodiment.

FIG. 12 is a graph illustrating frequency calculation.

[Explanation of symbols]

 Reference Signs List 1 vehicle 2 wheel speed sensor 3 electronic control unit 20 microcomputer TR tire

Claims (4)

[Claims] 1. A tire air pressure detection method for estimating a tire resonance frequency based on a vibration electric signal including a vibration frequency component of a vehicle tire and detecting the tire air pressure based on the estimated tire resonance frequency. Calculating the distribution of the resonance frequency of the tire; determining the distribution of the resonance frequency of the tire based on the calculated distribution; if it is determined that the distribution of the resonance frequency of the tire is not uniform, Detecting a tire air pressure based on the estimated tire resonance frequency; 2. The tire pressure detection method according to claim 1, wherein the distribution of the resonance frequency of the tire is calculated by at least one statistical method of variance, standard deviation, and frequency. Air pressure detection method. 3. A tire air pressure detecting device for estimating a tire resonance frequency based on a vibration electric signal including a vibration frequency component of a vehicle tire and detecting an air pressure of the tire based on the estimated tire resonance frequency. Distribution calculation means for calculating the distribution of the resonance frequency of the tire; determination means for determining the distribution state of the resonance frequency of the tire based on the calculated distribution; distribution state of the resonance frequency of the tire by the determination means And a prohibition unit for prohibiting the detection of the air pressure of the tire based on the estimated resonance frequency of the tire when it is determined that the tire pressure is not uniform. 4. The tire air pressure detection device according to claim 3, wherein the distribution calculating means calculates the distribution of the resonance frequency of the tire by at least one statistical method of variance, standard deviation, and frequency. Characteristic tire pressure detector.