JP3362522B2 - Tire pressure detector - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a tire air pressure detecting device which does not make an erroneous judgment.

[0002]

2. Description of the Related Art Japanese Patent Laid-Open No. 63-305011 discloses
Since the wheel speed changes when the load radius of the tire changes according to the air pressure, a tire air pressure detection device that detects the wheel speed of each wheel and indirectly detects the tire air pressure is disclosed.

[0003]

However, the load radius of the tire slightly changes depending on running conditions such as tire wear, cornering, and braking. For this reason, if the tire load radius is used as a parameter for air pressure detection, there is a problem in that sufficient detection accuracy cannot be ensured. In order to solve the above problems, the inventor of the present application extracts the resonance frequency in the up-down direction or the front-rear direction of the unsprung portion, and an air-pressure determination reference value stored in advance in an electronic control unit (hereinafter referred to as an ECU) (the minimum allowable tire pressure is The inventor has applied for a device for detecting the state of the air pressure of a tire by comparing it with the corresponding resonance frequency (Japanese Patent Application No. 3-294622).

The tire air pressure detection and detection device according to the above application is excellent in that the tire air pressure can be surely determined, but it includes the following problems. (1) When the input road surface condition is different between the left and right wheels and the unsprung vibration levels are significantly different, the vibration of the wheel on the higher vibration level vibrates via the drive shaft, steering arm, suspension member, etc. The vibration phenomenon is transmitted to the wheel with the smaller level, and the vibration phenomenon of the wheel with the smaller level cannot be detected. Therefore, it becomes difficult to estimate the resonance frequency of the tire of the wheel or the tire spring constant,
An erroneous determination may occur in the tire pressure determination of the wheel.

(2) When the vehicle makes a turn in which the lateral acceleration is large, the ground load on the inner wheel of the turn is reduced due to the load movement during the turn. For this reason, the vibration level of the wheel decreases, making it difficult to estimate the resonance frequency or the tire spring constant, which may cause an erroneous judgment in the tire air pressure judgment of the wheel.

(3) When the anti-lock brake system (hereinafter referred to as ABS) or the traction control system (hereinafter referred to as TRC) is activated, the unsprung resonance occurs due to the vibration of the control torque fluctuation and the driving torque fluctuation accompanying the control. Vibration phenomenon cannot be detected. For this reason, it becomes difficult to estimate the resonance frequency of the tire or the tire spring constant, and erroneous determination may occur in tire air pressure determination.

(4) In addition to the vibration phenomenon depending on the tire air pressure, the wheel speed fluctuation includes, for example, components of the vibration phenomenon of the suspension member and the suspension arm. For this reason, the above-described vibration phenomenon that does not depend on the tire air pressure may be more prominent than the vibration level that depends on the tire air pressure due to the input of the road surface condition or the like. In this case, it becomes difficult to estimate the resonance frequency of the tire of the wheel or the tire spring constant, and an erroneous determination may occur in determining the tire air pressure.

The present invention has been made in order to solve the above problems, and even if there is a large difference in the vibration levels of the left and right wheels, or when the vehicle makes a turn with a large lateral acceleration, the ABS.
Or even when the TRC is activated, due to the road surface condition input, etc., compared to the tire vibration phenomenon in the unsprung vibration,
It is an object of the present invention to provide a tire air pressure detection device that does not make an erroneous determination even when the resonance phenomenon in other portions is greater.

[0009]

A tire pressure detecting device of the present invention according to claim 1 for solving the above problems, comprises:
Output means for outputting a signal including a vibration frequency component of a tire when the vehicle is running, extraction means for extracting a signal of a resonance frequency component from the signal, and obtaining a difference between left and right wheel vibration levels
Means for comparing the obtained vibration level of the left and right wheels with a preset value to compare the extracted resonance frequency.
A signal sorting unit for sorting signal of the resonance frequency component used in the calculation of the resonant frequency from the component of the signal, and calculating means for calculating a resonant frequency from the signal of the selected resonant frequency component,
And a detection means for detecting a tire air pressure state based on the resonance frequency.

According to a second aspect of the present invention, there is provided a tire air pressure detecting device for solving the above problems .
The ear air pressure detection device further includes a detection unit that detects a turning level, and the signal selection unit further includes the detection unit.
Compare the magnitude of the swivel level with the preset value
It is characterized in that the signals are selected .

[0011] tire pressure detecting device of the present invention described in claim 3 for solving the above problems, according to claim 1 or 2
The tire pressure detection device according to claim 1, further comprising detection means for detecting the operation of the antilock brake system and the traction control system, and the signal selection means.
It is before the further presence or absence of operation of the antilock braking system or traction control system
It is characterized in that the selected signals are selected .

A tire pressure detecting device according to the present invention for solving the above-mentioned problems is provided by the tire pressure detecting device according to any one of claims 1 to 3.
In the tire pressure detection device according to any one of
Te, the extraction means comprises a first extraction means for extracting a signal of a resonance frequency component of the tire from the signal, and the second extracting means for extracting a signal of a frequency component other than the resonance frequency components of the tire from the signal , The signal selection means is further
Further, the selection of the signal is performed by comparing the magnitude of the ratio of the signal extracted by the first extraction means and the ratio of the signal extracted by the second extraction with a preset value.

According to a fifth aspect of the present invention for solving the above-mentioned problems, the tire air pressure detecting device according to the present invention outputs the signal including the vibration frequency component of the tire when the vehicle is running, and the left and right wheels of the signal. Means for obtaining the difference in vibration level
And the difference between the above-obtained left and right wheel vibration levels is preset
The tire spring constant from the signal compared to the
A signal selecting means for selecting a signal used for determination, an estimating means for estimating a tire spring constant from the selected signal, and a detecting means for detecting a tire air pressure state based on the tire spring constant. And

According to a sixth aspect of the present invention, there is provided a tire pressure detecting device according to the present invention for solving the above problems .
In the tire air pressure detection device, a detection means for detecting a turning level is provided, and the signal selecting means further compares the magnitude of the turning level with a preset value to obtain the signal.
It is characterized by performing the selection of .

The tire pressure detecting device of the present invention of claim 7, wherein for solving the above problems, according to claim 5 or 6
The tire pressure detection device according to claim 1, further comprising detection means for detecting the operation of the antilock brake system and the traction control system, and the signal selection means.
It is before the further presence or absence of operation of the antilock braking system or traction control system
It is characterized in that the selected signals are selected .

A tire air pressure detecting device according to the present invention for solving the above-mentioned problems is provided by claim 5 or 7.
In the tire pressure detection device according to any one of
Te, comprising an extraction means for extracting a proportion of the signal level of the resonance frequency component and the other frequency components of the tire from the signal including the vibrational frequency component, the signal selection means, the proportion of further <br/> the signal level Is compared with a preset value to select the signal .

[0017]

According to the tire pressure detecting device of the first aspect, the signal selecting means compares the difference between the vibration levels of the left and right wheels with a preset value from the signal of the resonance frequency component extracted by the extracting means. The signal used for calculating the resonance frequency is selected, and the state of the air pressure is detected from the resonance frequency calculated by the calculation means based on the selected signal. Therefore, since the signal that causes the erroneous detection can be selectively removed, the tire air pressure can be accurately detected.

In the tire air pressure detecting device according to the second aspect of the invention, the resonance frequency is compared by comparing the magnitude of the turning level detected by the signal selecting means with a preset value from the signal of the resonance frequency component extracted by the extracting means. The signal used for the calculation of is selected, and the state of the air pressure is detected from the resonance frequency calculated by the calculation means based on the selected signal. Therefore, since the tire air pressure is not detected during a sharp turn, erroneous detection can be prevented.

In the tire pressure detecting device according to the third aspect of the present invention, the signal selecting means calculates the resonance frequency from the signal of the resonance frequency component extracted by the extracting means depending on whether the ABS or TRC detected by the detecting means is operating. The signal to be used is selected, and the state of air pressure is detected from the resonance frequency calculated by the calculation means based on the selected signal. Therefore, AB
When the S or TRC is operating, the tire pressure is not detected, so erroneous detection can be prevented.

In the tire pressure detecting device according to the fourth aspect, the ratio of the signal of the resonance frequency component of the tire extracted by the first extracting means to the signal of the resonance frequency component of the tire other than the tire extracted by the second extracting means is large. The signal selection means selects the signal used for the calculation of the resonance frequency by the selection means, and detects the air pressure state from the resonance frequency calculated by the calculation means based on the selected signal. To do. Therefore, even if the amount of noise due to other vibration components is larger than that of tire vibration, erroneous detection will not occur.

In the tire pressure detecting device according to the fifth aspect, the difference between the detected vibration levels of the left and right wheels is compared with a preset value, and the signal selecting means determines the tire spring constant from the signal output by the output means. The signal used for estimation is selected, and the state of air pressure is detected based on the tire spring constant estimated by the estimation means from the selected signal. Therefore, since the signal that causes the erroneous detection can be selectively removed, the tire air pressure can be accurately detected.

In the tire pressure detecting device according to the sixth aspect, the detected turning level is compared as a preset value, and the signal used by the signal selecting means for estimating the tire spring constant is calculated from the signal output by the output means. The air pressure is selected based on the tire spring constant estimated by the estimating means from the selected signal. Therefore, since the tire air pressure is not detected during a sharp turn, erroneous detection can be prevented.

In the tire pressure detecting device according to the seventh aspect of the present invention, the signal selecting means selects a signal to be used for estimating the tire spring constant depending on whether the detected ABS or TRC is operated, and the estimating means is selected from the selected signal. The state of air pressure is detected based on the tire spring constant estimated by. Therefore, when the ABS or TRC is operating, the tire air pressure is not detected, so that erroneous detection can be prevented.

In the tire pressure detecting device according to the eighth aspect, the signal selecting means compares the magnitudes of the signal levels of the extracted resonance frequency component of the tire and the other frequency components with a preset value. Selects the signal used for estimating the tire spring constant, and detects the state of air pressure based on the tire spring constant estimated by the estimating means from the selected signal. Therefore, even if the amount of noise due to other vibration components is larger than that of tire vibration, erroneous detection will not occur.

[0025]

Embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a schematic configuration diagram of a tire air pressure detection device. Wheel speed sensors are installed corresponding to the four tires 1a to 1d on the front, rear, left, and right mounted on the vehicle. The wheel speed sensor includes gear-shaped pulsers 2a to 2d made of a magnetic material and pickup coils 3a to 3d. The pulsars 2a to 2d are fixed to the rotating axles (not shown) of the tires 1a to 1d. Pickup coils 3a to 3d
Is mounted at a predetermined distance from the pulsars 2a to 2d, and rotates the pulsars 2a to 2d, that is, the tires 1a to 1a.
An AC signal having a cycle corresponding to the rotation speed of 1d is output.

AC signals output from the pickup coils 3a to 3d are input to the ECU 4. The ECU 4
It is composed of a CPU, a waveform shaping circuit, a ROM, a RAM and the like, and processes various signals input according to a predetermined program. Then, the processing result is input to the display unit 5, and the display unit 5 notifies the driver of the air pressure state of each of the tires 1a to 1d. The notification mode may be such that the state of the air pressure of each tire 1a to 1d is displayed in a special manner, and when the air pressure of any one tire is lower than the reference air pressure by one warning lamp, A warning lamp may be turned on to give a warning.

The principle of tire pressure detection in this embodiment will now be described. When a vehicle travels on a paved asphalt road surface, the tire is vibrated in the vertical and longitudinal directions due to the force in the vertical and longitudinal directions due to the minute irregularities on the road surface. The frequency characteristic of the unsprung acceleration of the vehicle when the tire vibrates has peak values at points a and b as shown in FIG. Point a is the vertical resonance frequency of the vehicle under the spring, and point b is the front-rear resonance frequency of the vehicle under the spring.

When the air pressure of the tire changes, the spring constant of the tire rubber portion also changes, so that the resonance frequencies in the vertical direction and the longitudinal direction both change. For example, as shown in FIG. 3, when the tire air pressure decreases, the spring constant of the tire rubber portion also decreases, so the resonance frequencies in the up-and-down direction and the front-rear direction generally shift to the low frequency side, and the peak value a point is The peak value b point at the a'point shifts to the b'point. Therefore, if at least one of the resonance frequency in the up-down direction and the front-rear direction in the unsprung part of the vehicle is extracted from the vibration frequency of the tire, it is possible to detect the tire air pressure state based on this resonance frequency.

On the other hand, as a result of a detailed study by the present inventors, it was clarified that the detection signal of the wheel speed sensor contains the vibration frequency component of the tire. That is, it is clear that the frequency analysis result of the detection signal of the wheel speed sensor shows peak values at two points as shown in FIG. Became. For this reason, in the present embodiment, the tire air pressure is detected by extracting the vertical and longitudinal resonance frequencies under the spring of the vehicle from the detection signal of the wheel speed sensor.

As described above, according to the present embodiment, since a vehicle equipped with ABS, the number of vehicles of which is increasing in recent years, is already equipped with a wheel speed sensor in each tire, no new sensor is added. It is possible to detect the tire pressure even without it. In the practical range of the vehicle, the amount of change in the resonance frequency is based on the change in the spring constant of the tire rubber portion caused by the change in tire air pressure, and is stable without being affected by other factors such as tire wear. Air pressure can be detected.

The signal processing of the ECU 4 which detects that the tire air pressure has dropped below a predetermined air pressure and issues an alarm will be described below with reference to the flowchart of FIG.
Since the ECU 4 performs the same processing for each wheel,
The flow chart only shows signal processing for one wheel. In addition, the processing content shows an example in which it is detected that the tire air pressure has dropped below a reference value and a warning is given to the driver.

The ECU is turned on by turning on the ignition switch.
When the signal processing by 4 is started, in step 100, the AC signal (FIG. 6) output from the pickup coil 3 is shaped into a pulse signal, and then the pulse interval is divided by a predetermined time. Is calculated. As shown in FIG. 7, the wheel speed v usually contains many high frequency components including the vibration frequency component of the tire. In step 110, a road surface state determination process is performed to determine whether the calculated fluctuation range Δv of the wheel speed v is equal to or greater than the reference value v ₀ . When it is determined that the fluctuation range Δv of the wheel speed v is equal to or greater than the reference value v ₀ , the process proceeds to step 120.

In step 120, a road surface length determination process is performed to determine whether the time ΔT in which the fluctuation width Δv of the wheel speed v is the reference value v ₀ or more is a predetermined time t ₀ or more. Road surface condition determination processing in step 110, and step 1
In the road surface length determination processing of 20, when the road surface on which the vehicle is traveling is
This is performed to determine whether or not the road surface is capable of accurately detecting the tire air pressure by the detection method of this embodiment. That is, in the present embodiment, the tire air pressure is detected based on the change in the resonance frequency included in the tire vibration frequency component. Therefore, unless the wheel speed v fluctuates to some extent and is not continued, sufficient data for accurately calculating the resonance frequency cannot be obtained.
In the determination in step 120, the wheel speed v
The predetermined time period Δt is set when the fluctuation range Δv of Δ becomes equal to or larger than the reference value v ₀ . Further, when the fluctuation width Δv of the wheel speed v becomes v ₀ or more again within the predetermined time Δt, the measurement of the time ΔT is continued.

If a negative determination is made in either step 110 or step 120, step 10
Return to 0. Further, if both step 110 and step 120 are affirmatively determined, the routine proceeds to step 130, where frequency analysis (hereinafter referred to as FFT) calculation is performed on the calculated wheel speed v. In step 140, it is determined whether to adopt the FFT result calculated in step 130.

The conditions under which the FFT result is not adopted are as follows. (1) When there is a large difference between the vibration levels of the left and right wheels. (2) During a turn that generates a large lateral acceleration. (3) ABS or TRC is operating. (4) When the vibration level of the tire (hereinafter referred to as the signal level) depending on the air pressure is higher than a certain level (hereinafter referred to as the noise level).

In the above cases, the tire resonance phenomenon that depends on the air pressure is less likely to appear in the FFT calculation result, and if the result is used to make the air pressure determination, it causes an erroneous determination, so the FFT calculation result is not used. That is, as shown in the flowchart of FIG. 5, the process proceeds to step 150 only when all of the selection conditions (1) to (4) are not satisfied, and (1)
If any one of the selection conditions (4) to (4) is satisfied, the process is not performed and the process returns to step 100.
The details of the data selection process in step 140 will be described later.

In step 150, the gain (magnitude) of the wheel speed signal is adjusted. In this gain adjustment process, the value of each peak value V _P within a predetermined frequency range (f _{1 to} f ₂ ) is set to a preset value V _PK (same value) in the waveform of each FFT calculation result. To be equal, some coefficient K ₁ ,
K _2, multiplied by a ... to each FFT calculation result. By this gain adjustment, it can be prevented that the magnitude of the input of the road surface condition varies and the magnitude of the gain of the FFT result becomes uneven, and the effect of the averaging process of step 180 described later becomes unstable. .

In the following step 160, the number N of FFT calculations is integrated. When the FFT calculation is actually performed on the wheel speed obtained when the vehicle actually travels on a general road, the frequency characteristics are usually very random as shown in FIG. This is because the shape (size and height) of the subtle unevenness existing on the road surface is completely irregular, and the frequency characteristic varies for each wheel speed data. Therefore, in the present embodiment, in order to reduce the variation of the frequency characteristic as much as possible, the average value of the FFT calculation results of a plurality of times is calculated.

Therefore, in step 170, this FF
It is determined whether or not the number of times N of T operations has reached a predetermined number of times n ₀ . If not reached, the processes of steps 100 to 160 are repeated. When the number of calculations N reaches the predetermined number n ₀ , the averaging process is performed in the following step 180. This averaging process is performed by each FF as shown in FIG.
The average value of the T calculation results is obtained, and the average value of the gain of each frequency component is calculated. By this averaging process, it is possible to reduce the fluctuation of the FFT calculation result due to the road surface.

However, with the above averaging process alone, the gain of the resonance frequency in the up-down direction and the front-rear direction of the unsprung part of the vehicle does not always reach the maximum peak value as compared with the gain of the frequencies in the vicinity thereof due to noise or the like. There is a problem that it is not limited. Therefore, following the averaging process described above, the moving average process is performed in step 190. This moving average processing is performed by obtaining the gain Y _n of the _nth frequency by the following arithmetic expression.

[0041]

## EQU1 ## Y _n = (y _{n + 1} + Y _n-1 ) / 2 That is, in the moving average processing, the gain Y of the nth frequency is obtained.
_n is the (n + 1) th gain y in the previous calculation result
_{n + 1} and the gain Y of the n-1th frequency already calculated
_It is an average value with _n-1 . As a result, the FFT calculation result shows a waveform that changes smoothly. The calculation result obtained by this moving average processing is shown in FIG.
The waveform processing here is not limited to the above moving average processing, but the differential calculation of the wheel speed v is performed before the FFT calculation of step 130, and the differential calculation result is FF.
You may implement T calculation.

In the following step 200, the resonance frequency f _K of the unsprung direction of the vehicle in the front-rear direction is calculated based on the FFT calculation result smoothed by the moving average processing. Subsequent step 210 determines an initial resonant frequency f _K0 that is set to correspond to the previously normal tire pressure, decrease the deviation between the resonance frequency f _K is sequentially calculates (f _K0 -f _K), wherein f _K0 And tire pressure drop warning pressure (eg 1.
The resonance frequency f _L corresponding to 4 kg / cm ² ) and the judgment deviation Δf = (f _K0 −f _L ) are compared. If (f _K0 −f _K ) <Δf, the processing from step 100 onward is performed. Also,
If (f _K0 −f _K ) ≧ Δf, the _routine proceeds to step 220, where it is determined that the tire pressure is below the allowable value, and the display unit 5 displays a warning to the driver.

A specific method of the data selection processing of step 140 described above will be described with reference to the flowchart of FIG. First, in step 141, the difference between the vibration levels of the left and right wheels is obtained. FIG. 12 shows an example of data when there is a difference in vibration level between the left and right wheels. FIG. 12 (a),
(B) shows a wheel speed time waveform and its FFT waveform when only the right wheel travels on a rough road surface. As judged from this data, the left-right difference in vibration level can be distinguished by the following three comparisons. (1) The magnitude v (p) between the peaks of the time waveform of the wheel speed signal
-P). (2) Gain peak value Gp in a predetermined frequency range on the FFT waveform. (3) Gain peak integrated amount Gf _{1 to} f _{2 in} a predetermined frequency range on the FFT waveform.

Therefore, the above v (pp), Gp, Gf ₁ ~
If any of the values of f ₂ is used and the difference between the left and right values exceeds a predetermined value, it is determined in step 142 that the vibration level of the left and right wheels is high, and it is determined that the data cannot be adopted.
Return to 00. If the data can be adopted, the process proceeds to step 143 to calculate the lateral acceleration. The magnitude of the lateral acceleration can be calculated by the following formula from the wheel speed values (v) of the left and right wheels calculated in step 100.

[0045]

[Equation 2] G = (v _O ² −v _I ² ) / 2 · T · g (G: lateral acceleration, T: tread amount, v _O : outer wheel speed of turning, g: weight acceleration, v _I : inner wheel of turning Wheel Speed) When the calculated value of the lateral acceleration by the above equation is equal to or larger than a predetermined value, it is determined in step 144 that the data cannot be adopted, and the process returns to step 100. Step 1 if data can be accepted
Proceed to 45.

The above equation is an equation used to calculate the lateral acceleration in the ABS technique. The magnitude of the lateral acceleration can also be estimated from the difference between the resonance levels of the left and right wheels generated by the load movement between the left and right wheels due to the lateral acceleration.
FIG. 13 is an FFT waveform of the wheel speed signal of the inner and outer wheels when turning. The ground load on the turning outer wheel increases as the lateral acceleration increases. Therefore, the exciting force increases inputted to the tire by the road surface irregularities, 13 gain peak value Gp of predetermined frequency range, as shown in _{(a) (0)} or gain integrated amount Gf ₁ ~f 2 _(O) Grows larger. On the contrary, since the ground contact load is reduced in the turning inner wheel, it is the same as the outer wheel in FIG.
As shown in (b), the gain peak value Gp _(I) or the integrated gain amount Gf _{1 to} f _{2 (I)} becomes small. The gain peak value Gp of the inner and outer wheels or the integrated gain amount Gf _{1 to} f ₂ is
Since it changes according to the lateral acceleration as shown in FIG. 14, this value can be used for detecting the lateral acceleration.

In step 145, when the ABS or TRC operation is detected within the predetermined time range of the wheel speed signal which is the basis of the FFT calculation result as shown in FIG. 15, the data is not adopted in step 146. . In this case, the process returns to step 100, and the processes after step 147 are not performed. If data can be adopted, the process proceeds to step 147. The signal indicating whether ABS or TRC is operating is ABS
ECC of TRC and TRC (not shown) and EC of this system
It can be obtained by providing a signal communication line between C.

In step 147, (signal level) /
Calculate (noise level). Here, the "signal" is tire vibration in which the resonance point moves depending on the tire air pressure, and the "noise" is other vibration. In addition to the tire vibration, which is the "signal" component, the wheel speed signal includes "noise" suspension members other than the tire,
It also includes vibration components such as arms. Therefore, both the "signal" component and the "noise" component appear in the FFT calculation result of the wheel speed signal. Normally, there is no problem because the "signal" component is larger, but since the "noise" component of the vibration system such as the bush of the suspension is non-linear, the vibration level of the "noise" component is large depending on the road surface condition. It masks the "signal" component. 16A shows the FFT waveform in the normal state, and FIG. 16B shows the FFT waveform when the "noise" component becomes noticeable. With data having a lot of “noise” components as shown in FIG. 16B, it is difficult to determine the resonance point of the “signal” component, which causes an error in the tire air pressure determination. Therefore, in step 147, if the magnitude of (signal level) / (noise level) is less than or equal to a predetermined value, the data cannot be adopted.

Next, a specific method of discriminating data will be described. Since the "noise" component is mainly a resonance phenomenon of the suspension member, it is generated in a predetermined frequency range. Therefore,
By comparing the gain amount in the frequency range in which "noise" occurs and the gain amount in the frequency range in which "signal" occurs, data having a relatively large "noise" component is determined. As shown in FIG. 17A, a predetermined “noise” is obtained in the FFT calculation result in the normal time.
The ratio N / S of the gain integration amount N in the frequency range and the gain integration amount S in the predetermined “signal” frequency range shows a small value. Also, as shown in FIG. 17B, N / S shows a large value in the FFT calculation result when the “noise” component becomes noticeable. Therefore, in step 147, it is determined whether the ratio of the “noise” component in the data is large by the magnitude of N / S, it is determined that the data having a predetermined value or more cannot be adopted, the process returns to step 100, and the processes in step 150 and the subsequent steps are performed. Does not. If data can be adopted, the process proceeds to step 150.

The ratio of the "noise" component to the "signal" component in the data can also be obtained from the following time waveform of the wheel speed signal without using the FFT calculation result. FIG. 18 (a) shows the wheel speed time waveform with a small amount of "noise" component, and FIG. 18 (b) shows the wheel speed time waveform with a large amount of "noise" component. For each data, the wheel speed at the time waveform after passing through the band pass filter of predetermined "noise" frequency range and the "signal" frequency range, figure _{(a 2), (a 3} ), (b 2), It is shown in (b ₃ ). If the "noise" component is small, the amplitude ratio after the bandpass filter _{f N (PP) / f S} (PP) indicates a smaller value. Conversely, "noise"
When there are many components, the amplitude ratio f after the bandpass filter
_{N (PP)} / fs _(PP) shows a large value. Therefore, this f
_{The value of N (PP)} / fs _(PP) can also be used to determine the high proportion of "noise" components.

As described above, step 14 in FIG.
0 (steps 141 to 148 in FIG. 2), the process returns only when the data is not rejected under all the conditions, and the above-described steps 150 (FIG. 5) and subsequent steps are performed.

In the data selection process of step 140 of FIG. 5 (steps 141 to 148 of FIG. 11), instead of using the FFT calculation result as in the above embodiment, the spring constant is directly calculated to calculate the tire pressure. It can also be used as a detection method. Further, in the above embodiment, based on only the resonance frequency in the front-rear direction of the unsprung part of the vehicle, an example of detecting a decrease in tire air pressure has been shown, but instead, the tire pressure based on only the resonance frequency in the vertical direction is used. Can also be detected. It is also possible to detect based on both the front-rear direction and the vertical resonance frequency.

[Brief description of drawings]

FIG. 1 is a schematic configuration diagram of a tire air pressure detection device according to the present invention.

FIG. 2 is a characteristic diagram showing frequency characteristics of unsprung acceleration of a vehicle.

FIG. 3 is a characteristic diagram showing how the resonance frequencies of the unsprung part of the vehicle change in the up-down direction and the front-rear direction with changes in tire air pressure.

FIG. 4 is an explanatory diagram showing the principle of tire pressure detection.

FIG. 5 is a flowchart showing the processing contents of the ECU.

FIG. 6 is a waveform diagram showing an output voltage waveform of a wheel speed sensor.

FIG. 7 is a waveform diagram showing a variation state of a wheel speed v calculated based on a detection signal of a wheel speed sensor.

FIG. 8 is a characteristic diagram showing an FFT calculation result with respect to a time waveform of a wheel speed v.

FIG. 9 is an explanatory diagram showing an averaging process.

FIG. 10 is a characteristic diagram showing an FFT calculation result after performing a moving average process.

FIG. 11 is a flowchart showing details of the data selection processing in step 140.

FIG. 12 is an explanatory diagram showing a wheel speed signal and an FFT calculation result during actual traveling in which the input levels of the left and right wheels are different.

FIG. 13 is an explanatory diagram showing an FFT calculation result during turning travel.

FIG. 14 is a characteristic diagram showing a ratio of signal levels of left and right wheels to lateral acceleration.

FIG. 15 is an explanatory diagram showing a data selection process at the time of ABS and TRC operation.

FIG. 16 is an FFT when the vibration level of a noise component is high.
It is explanatory drawing which shows a calculation result.

FIG. 17 is an explanatory diagram showing a data selection process based on a signal level / noise level.

FIG. 18 is an explanatory diagram showing data selection processing based on a signal level / noise level from a wheel signal.

[Explanation of symbols]

1a-1d tires 2a-2d pulsar 3a-3d pickup coil 4 EUC

─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Kenji Tomiita, 1-1, Showa-cho, Kariya city, Aichi Prefecture, Nippon Denso Co., Ltd. (56) Reference JP 5-221208 (JP, A) JP JP 6- 183231 (JP, A) JP 5-213019 (JP, A) JP 6-92114 (JP, A) JP 63-305011 (JP, A) Patent 2836652 (JP, B2) (58) Investigation Area (Int.Cl. ⁷ , DB name) B60C 23/00-23/06 G01L 17/00

Claims (8)

(57) [Claims] 1. Output means for outputting a signal including a vibration frequency component of a tire when a vehicle is running, extraction means for extracting a signal of a resonance frequency component from the signal, and vibration levels for the left and right wheels.
Means for obtaining the difference between the bells and the obtained left and right wheel vibrations
The level difference is compared with a preset value, and the extracted
Based on the resonance frequency, the signal selection means for selecting the resonance frequency component signal used for the calculation of the resonance frequency from the selected resonance frequency component signal, the calculation means for calculating the resonance frequency from the selected resonance frequency component signal, A tire air pressure detection device, comprising: a detection unit that detects a tire air pressure state. Wherein a detection means for detecting the swivel level,
Said signal selecting means further selecting said detected turning level of magnitude the signal compared with a preset value
Tire pressure detecting apparatus according to claim 1, wherein the performing. 3. A detecting means for detecting the operation of the Anti-lock braking system and a traction control system
3. The tire pressure detection device according to claim 1 , wherein the signal selection means further selects the signal based on whether or not the antilock brake system or the traction control system is operating. 4. The extracting means includes first extracting means for extracting a signal of a tire resonance frequency component from the signal, and second extracting means for extracting a signal of a frequency component other than the tire resonance frequency component from the signal. Consisting of the signal selector
The stage further selects the signal by comparing the magnitude of the ratio of the signal extracted by the first extraction means and the signal extracted by the second extraction with a preset value. The tire air pressure detection device according to any one of claims 1 to 3 . 5. Output means for outputting a signal including a vibration frequency component of a tire when the vehicle is running, means for obtaining a difference in vibration level between the left and right wheels of the signal, and the obtained left and right wheels.
Compare the difference in the vibration level of
A signal selecting means for selecting a signal used for estimating a tire spring constant from a signal, an estimating means for estimating a tire spring constant from the selected signal, and a detecting means for detecting a tire air pressure state based on the tire spring constant. A tire air pressure detection device comprising: Further comprising: a detection means for detecting the swivel level,
It said signal selecting means further tire air pressure detecting device according to claim 5, in comparison with the preset value the magnitude of the swing level and performing selection of said signals. 7. A detecting means for detecting the operation of the Anti-lock braking system and a traction control system
7. The tire air pressure detection device according to claim 5 , wherein the signal selection means further selects the signal based on whether the antilock brake system or the traction control system is operating. 8. comprising an extraction means for extracting a proportion of the signal level of the resonance frequency component and the other frequency components of the tie <br/> Ya from a signal containing the oscillation frequency component, the signal sorting unit
The tire pressure detecting device according to claim 5 , further comprising: comparing the magnitude of the ratio of the signal level with a preset value to select the signal .