JPH04254259A - Yawrate detecting device for vehicle - Google Patents

Abstract

PURPOSE:To properly detect a yawrate by discriminating abnormality of a yawrate sensor without wrong decision. CONSTITUTION:A yawrate sensor is provided to perform its abnormality decision process for whether the yaw rate sensor is abnormal or not by comparing an actual yaw rate Wa* detected by this yawrate sensor, with an estimated yawrate rx* calculated from a speed difference between right/left wheels of a vehicle. Here in the case of detecting a slip condition of the right/left wheels from respective wheel speeds thereof, the above-mentioned abnormality decision process is suspended.

Description

[Detailed description of the invention]

0001

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a device for detecting the yaw rate of a vehicle.

0002

2. Description of the Related Art Conventionally, devices have been proposed that perform various types of vehicle control based on the yaw rate of the vehicle. For example, in the device disclosed in Japanese Patent Application Laid-Open No. 60-124572, a target yaw rate during a turn is determined from the steering amount of the front wheels and the vehicle speed. Then, the amount of steering of the rear wheels is controlled according to the difference between the two yaw rates so that the actual yaw rate detected by the yaw rate sensor matches the target yaw rate.

[0003] In the above-mentioned apparatus, there is a problem in that if the yaw rate sensor fails or there is an error in the detected yaw rate, not only will the intended control not be performed, but it will also have a large effect on vehicle behavior. Therefore, conventionally, a failure of the yaw rate sensor has been diagnosed by monitoring whether the output value of the yaw rate sensor is within the specification range or whether there is a sudden change.

However, this method has a problem in that an abnormality is not detected if the output value of the yaw rate sensor does not change or changes with an excessive offset. Therefore, the estimated yaw rate is calculated from the wheel speed difference between the left and right wheels, and the actual yaw rate detected by the yaw rate sensor and the estimated yaw rate calculated from the wheel speed difference are compared to determine whether the actual yaw rate is abnormal, that is, the yaw rate sensor. There are possible ways.

[0005]

[Problem to be solved by the invention] However, even with this method, when the steering angle is large or the steering speed is high,
There is a problem in that it is not possible to calculate the speed difference and accurate yaw rate. Another problem is that if the wheels slip during acceleration or braking, a large error will occur if the yaw rate is calculated from the wheel speed detected at that time.

SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and it is an object of the present invention to provide a yaw rate detection device for a vehicle that can correctly detect the yaw rate without erroneously determining that the yaw rate sensor is abnormal. shall be.

[0007]

[Means for Solving the Problems] The present invention provides a yaw rate sensor that detects the yaw rate that occurs when a vehicle turns;
A left wheel speed detecting means for detecting the left wheel speed of the vehicle, a right wheel speed detecting means for detecting the right wheel speed of the vehicle, and a speed difference between the left and right wheel speeds by the left wheel speed detecting means and the right wheel speed detecting means. estimated yaw rate calculation means for calculating an estimated yaw rate based on the yaw rate; slip detection means for detecting wheel slip based on the left wheel speed by the left wheel speed detection means and the right wheel speed by the right wheel speed detection means; abnormality determining means for determining an abnormality in the yaw rate sensor by comparing an actual yaw rate determined by the sensor with an estimated yaw rate by the estimated yaw rate calculating means; and a canceling means for suspending abnormality determination by the abnormality determining means based on the slip detecting means; The gist of the present invention is a vehicle yaw rate detection device comprising:

[0008]

[Operation] In the vehicle yaw rate detection device of the present invention, the yaw rate sensor M1 detects the actual yaw rate of the vehicle. Further, the estimated yaw rate calculation means M4 calculates the estimated yaw rate from the speed difference between the left and right wheels. and abnormality determination means M
6 compares the actual yaw rate and the estimated yaw rate to determine whether the yaw rate sensor M1 is abnormal.

[0009] If slip occurs in the wheels, there is a risk that an error will occur in the estimated yaw rate and an incorrect yaw rate will be calculated, so the slip detection means M5 detects the slip state of the vehicle and The aborting means M7 aborts the abnormality determination based on the slip state.

0010

DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment in which the present invention is applied to a rear wheel steering system for a vehicle will be described below with reference to the drawings. FIG. 2 is a block diagram of the first embodiment of the present invention. In Figure 2,
DC servo motor 2 installed in rear wheel steering mechanism 1
rotates in forward and reverse directions in response to a command signal from an electrical control unit (hereinafter referred to as "ECU") 3, and is connected to the input shaft of a rack and pinion mechanism with hydraulic power assist, that is, the steering mechanism 1, through a reduction gear 4. (Torsion bar not shown)
is connected to one end of the A pinion gear 5 is attached to the other end of the torsion bar, and meshes with a rack 7 formed at one end of the power piston 6. That is, one end of the torsion bar is rotated by the motor 2, the torsion bar is twisted, the throttle area of the hydraulic valve 8 is changed, and hydraulic pressure is supplied in a direction that corrects the torsion of the torsion bar to move the power piston 6. ing. Both ends of the power piston 6 are connected to a knuckle arm 10 via tie rods 9, respectively. The rear wheel 11 is supported by a knuckle arm 10 so as to be swingable in the left-right direction.

Therefore, the power piston 6 is moved in the direction A in the head.
By moving, the rear wheels 11 are steered left and right. and,
When the torsion bar is no longer twisted, the throttle area of the hydraulic valve 8 becomes "0", the oil pressure for moving the power piston 6 becomes "0", and the power piston 6 stops. Here, the rear wheel steering angle sensor 12 detects the position of the power piston 6 and outputs a signal. Based on this signal, the ECU 3 determines the actual rear wheel steering angle from the relationship between the position of the power piston 6 and the actual rear wheel steering angle, and also determines the steering angular velocity from the rate of change of the actual rear wheel steering angle. The steering mechanism 1 including the servo motor 2 and the ECU 3 constitute a positioning servo system that positions and controls the rear wheels 11 so that the actual rear wheel steering angle matches the rear wheel steering angle command position. Note that 13 indicates a hydraulic pump that supplies hydraulic pressure to the power piston 6 via a hydraulic valve 8, and 14 an oil tank.

Vehicle speed sensor 15 detects the rotational speed of the axle or wheel and outputs a vehicle speed signal corresponding to vehicle speed V to ECU 3. The front wheel steering angle sensor 16 is composed of an incremental type rotary encoder, and is provided on a steering shaft 17 as a rotated body. Then, the rotation of the steering shaft 17 accompanying the operation of the steering wheel 18 is detected, and the steering angle θS of the front wheels 19 is determined.
A front wheel steering angle signal corresponding to the front wheel steering angle signal is output to the ECU 3. The yaw rate sensor 20 is composed of a gyro or the like, and outputs a yaw rate signal to the ECU 3 according to the rotational angular velocity (yaw rate Wa) of the vehicle around the center of gravity of the vehicle. The left wheel speed sensor 21 detects the rotational speed of the left wheel of the front wheel 19 (left wheel speed ωL).
The right wheel speed sensor 22 detects the rotational speed of the right wheel of the front wheel 19 (left wheel speed ωR). The brake switch 23 is turned on during ABS (anti-lock brake system) control or when the brake pedal is operated.

The ECU 3 will be explained based on FIG.
The CU 3 includes a microcomputer (hereinafter referred to as "microcomputer") 24, waveform shaping circuits 25 to 28, an analog buffer 29, an A/D converter 30, a digital buffer 31, and a drive circuit 32. The waveform shaping circuits 25 to 28 shape the waveforms of signals from the vehicle speed sensor 15, the left wheel speed sensor 21, the right wheel speed sensor 22, and the front wheel steering angle sensor 16, and input them into the microcomputer 24. Further, the analog buffer 29 reads each signal from the rear wheel steering angle sensor 12 and the yaw rate sensor 20, and the A/D converter 30 performs analog-to-digital conversion. Digital buffer 31 latches the signal from brake switch 23. Further, the drive circuit 32 supplies the DC servo motor 2 with a current according to the current command value signal If from the microcomputer 24.

Next, the operation of the rear wheel steering system constructed as described above will be explained. 4 shows the main processing routine of the microcomputer 24, FIG. 5 shows the vehicle speed pulse processing using pulse signals from the vehicle speed sensor 15 and the left and right wheel speed sensors 21, 22, and FIG. 6 shows the main processing routine of the microcomputer 24. This shows the interrupt handling routine that is executed every time.

As shown in FIG. 4, the microcomputer 24 is initialized in step A10 when started, and performs various processes in step A20. On the other hand, as shown in FIG. 5, the microcomputer 24 calculates and stores the vehicle speed pulse width from the time when the previous pulse interrupt occurred and the time when the current interrupt occurred in step B10.

Then, as shown in FIG. 6, the microcomputer 24
In step C10, the vehicle speed V is calculated from the vehicle speed pulse width stored in the vehicle speed pulse interrupt process. Similarly, for the left wheel speed sensor 21 and the right wheel speed sensor 22, the left wheel speed ωL and right wheel speed ωR of the front wheels 19 are calculated based on the wheel speed pulse widths. That is, step C10 corresponds to the left wheel speed detection means M2 and the right wheel speed detection means M3. In this embodiment, the vehicle speed V was determined by the vehicle speed sensor 15, but the vehicle speed V was calculated from the left and right wheel speeds ωL and ωR (ωL +
It may be determined as ωR )/2.

Then, in step C20, the microcomputer 24 receives A/A from the rear wheel steering angle sensor 12 and the yaw rate sensor 20.
The A/D conversion data is taken in via the D converter 30, and the rear wheel actual steering angle θr and the actual yaw rate W are obtained in step C30.
Calculate a. Next, in step C35, the signal from the brake switch 23 is taken in via the digital buffer 31.

In step C40, the microcomputer 24 counts the pulses from the front wheel steering angle sensor 16 to calculate the front wheel steering angle (steering wheel angle) θS. Thereafter, in step C50, a routine for determining abnormality of the yaw rate sensor 20 is executed. In other words, step C50 corresponds to the abnormality determining means M6. The contents of the abnormality determination processing routine are shown in FIG.

In FIG. 7, first, in step D10, in order to extract only the frequency component including the yaw rate information, the following equation is used for the left wheel speed ωL detected by the left wheel speed sensor 21 and the right wheel speed ωR detected by the right wheel speed sensor 22. Performs the low-pass filter processing shown in .

[0020]

[Equation 1] ωLi* = (1-a)・ωLi-1* +a
・ωLi

[0021]

[Formula 2] ωRi* = (1-a)・ωRi-1*+a・
ωRi, where a is the filter constant, i is the current value, i-1
is the previous value. As a result, the estimated yaw rate rx * obtained later will be delayed with respect to the actual yaw rate Wa, so in order to eliminate the influence of the delay, the actual yaw rate W
Perform the low-pass filter processing of a.

[0022]

[Math. 3] Wai* = (1-a)・Wai-1* +a
・Wait Then, in step D20, the estimated yaw rate rx* is calculated from the left and right wheel speeds ωL*, ωR* that have been subjected to the low-pass filter processing using the following equation. In other words, step D20 corresponds to the estimated yaw rate calculation means M4.

[0023]

[Math 4] However, T is the tread of the vehicle.

Next, in step D30, wheel slip detection (slip detection will be described later) is performed. In other words,
Step D30 corresponds to slip detection means M5. In step D40, the difference e between the actual yaw rate Wa* filtered in step D10 and the estimated yaw rate rx* calculated in step D20 is calculated.

[0025]

e=Wa*-rx* Then, in step D50, it is determined whether the driving state is such that the above yaw rate estimation calculation is valid, that is, whether the vehicle driving characteristics are in a linear region. in particular,
Whether the vehicle speed V is within the range from the lower limit value VL to the upper limit value VH, the brake operation is not performed by the signal from the brake switch 23, or the absolute value |rx*| of the estimated yaw rate rx* is less than or equal to the predetermined value rT. It is determined whether the absolute value |θS | of the steering wheel angle θS is less than or equal to a predetermined value θT.

If all of these conditions are met, the process advances to step D60 and the difference e calculated in step D40 is calculated.
is cumulatively added for a predetermined time Tave. If the above-mentioned conditions are not satisfied, this cumulative addition is not performed and the flowchart is ended. In other words, step D50 corresponds to the canceling means M7. Let E be the cumulative addition value of data for a predetermined time Tave based only on the data when the condition is satisfied.

[0027]

[Formula 6] Ei = Ei-1 +ei where i is the current value and i-1 is the previous value. And T
When the data for the ave time has been accumulated, the cumulative addition value E is compared with a predetermined value eH in step D70, and if it is greater than or equal to the predetermined value eH, it is determined that the output of the yaw rate sensor 20 is different from the estimated value, After turning on the abnormality detection flag in step D80, the flowchart is ended. If it is less than the predetermined value eH, step D80 is jumped and the flowchart is ended.

The slip detection in step D30 is performed by paying attention to the rate of change in wheel speed, as shown in FIG. First, in step E10, the left and right wheel speeds ωL *, ωR *
The absolute value of the rate of change |dωL * |, |dωR *
It is determined whether any of | is less than or equal to a predetermined value C1. Next, in step E20, the left and right wheel speed ωL *
, ωR * absolute value of the difference in rate of change | dωL * −d
It is determined whether ωR*| is less than or equal to a predetermined value C2. When it is determined NO in step E10 or step E20, the process proceeds to step E70, where the flag is turned on, and thereafter, the process proceeds to step E80, where it is set that the vehicle is slipping, and the flowchart is temporarily terminated. Step E1
0 and YES in step E20, the process proceeds to step E30, where it is determined whether or not the flag is on. If it is on, step E40
If it is not on, the process jumps to step E60. In step E40, it is determined whether a certain period of time tD has elapsed since the flag was turned on. If NO is determined in step E40, step E
Proceed to 80. If it is determined to be YES, the process proceeds to step E50, where the flag is turned off, and thereafter, the process proceeds to step E60, where it is set that there is no slippage, and the flowchart is temporarily terminated. In this flowchart, once the flag is turned on, even if the above two conditions are satisfied (that is, less than the predetermined values C1 and C2, respectively), a certain period of time tD has elapsed since the flag was turned on in steps E30 and E40. If not, the settings during the slip will be retained. This suppresses the flapping (chattering) of the flag and allows accurate detection of slippage.

This slip detection is not limited to this, and the judgments in steps E10 and E20 may include those regarding the rear wheels. Furthermore, the above slip detection may be performed as shown in the block diagram shown in FIG. First, in block F1, the front wheel left and right wheel speeds ωFL*,
ωFR* is determined, and an estimated front wheel yaw rate rFX* is calculated from the left and right front wheel speeds in block F2. Similarly, in block F3, rear wheel left and right wheel speeds are determined from a rear wheel vehicle speed sensor (not shown), and in block F4, rear wheel left and right wheel speeds ωRL*
, ωRR*, the estimated rear wheel yaw rate rRX* is calculated. Then, in block F5, it is determined whether the absolute value |rFX*-rRX*| of the difference between the front wheel estimated yaw rate rFX* and the rear wheel estimated yaw rate rRX* is greater than a threshold value rT. Depending on this judgment, the flag is turned on or off. Regarding the processing of this flag, as shown in steps E30 to E50 in FIG. 8, once the ON condition is met, there is a block F6 that maintains the ON state of the flag for a time TD.

If it is determined in step C50 of FIG. 6 that the yaw rate sensor 20 is normal (the abnormality detection flag is off), the process proceeds to step C60. In step C60, the microcomputer 24 performs processing to calculate the rear wheel steering angle command value θr*. First, the target yaw rate WS is calculated from the vehicle speed V and the final steering angle θ of the front wheels using the following equation. (Margin below)

[0031]

[Equation 7] Here, K represents the stability factor, L represents the wheel base of the vehicle, and N represents the steering ratio.

Then, the difference ΔW (=Wa*-WS) between the actual yaw rate Wa* and the target yaw rate WS is calculated, and the rear wheel steering angle command value θr* is calculated using the following equation.

[0033]

[Equation 8] θr*=F(ΔW, V) Here, F(ΔW, V) represents a function using the yaw rate difference ΔW and the vehicle speed V as variables. The microcomputer 24 performs step C70
Based on the rear wheel steering angle command value θr* and the rear wheel actual steering angle θr, generally known rear wheel steering positioning servo calculation is performed in order to eliminate the difference between the two, and based on the calculation result, a current command value signal is set in step C80. If is calculated and output to the drive circuit 32 to drive the servo motor 2.

In step C50 of FIG. 6, the yaw rate sensor 2
0 is determined to be abnormal (abnormality detection flag on), in the next step C60, the above-mentioned rear wheel control is stopped and the rear wheels are gradually brought to the neutral position (rear wheel steering angle 0 degrees). The rear wheel steering angle change speed at this time varies depending on the vehicle speed, and is slowed down as the vehicle speed increases. As described above, in this embodiment, the microcomputer 24 (yaw rate estimating means, slip detecting means, and abnormality determining means) controls the left and right wheel speed sensors 21 and 2.
2, the estimated yaw rate rx * is calculated from the left and right wheel speeds ωL *, ωR *, and the wheel speeds ωL, ωR * are calculated.
Slip detection using the rate of change of ωR or slip detection that compares the front wheel estimated yaw rate rFX* from the front wheels and the rear wheel estimated yaw rate rRX* from the rear wheels, so that the estimated yaw rate at the time of slip is not used for abnormality determination. did.

Next, a second embodiment of the present invention will be explained. The yaw rate detection device of the second embodiment has a brake pressure sensor for detecting brake pressure added to the configuration of the first embodiment shown in FIG. Furthermore, step C shown in FIG.
The flowchart regarding the yaw rate sensor abnormality determination process in No. 60 is different from the first embodiment. That is, regarding the flowchart, the flowchart shown in FIG. 10 is executed instead of FIG. 8.

First, in G10, the left and right wheel speeds ωL,
ωR and the yaw rate sensor output Wa are low-pass filtered and calculated using equations 1, 2, and 3. Next, in step G20, the left and right wheel speed ω processed in the previous step
Estimated yaw rate rx* using L*, ωR*
is calculated using equation 4. Then, in step G30, the difference e between the actual yaw rate Wa* filtered in step G10 and the estimated yaw rate rx* calculated in step G20 is calculated using Equation 5. Thereafter, the process proceeds to step G40, where the accuracy k is calculated, which indicates how much the actual yaw rate and the estimated yaw rate match or are likely.

The content of the arithmetic processing in step G40 is shown in the flowchart of FIG. First, in step H10, the accuracy k1 corresponding to the current vehicle speed V is determined from the function map FIG. 13 of the vehicle speed V and k1, which is one factor of accuracy. In step H20, the absolute value of the steering angle θS is calculated, and in step H3
0, from the function map in Figure 14, the absolute value of the steering angle |θ
Determine the accuracy k2 corresponding to S |. Step H40
Then, the accuracy k3 corresponding to the current brake pressure Pb is determined from the function map shown in FIG. This means that k3 can be set to 1 or 0 by the brake switch, even if it is not the brake pressure.
You may switch to Alternatively, k3 may be switched to 1 or 0 using a symbol representing the ABS operating state (ABS control signal). Estimated yaw rate r in step H50
The absolute value of x* |rx*| is calculated and step H
At 60, the accuracy k4 corresponding to the absolute value |rx*| of the estimated yaw rate is determined from the function map shown in FIG.

Then, in step H70, the wheel speed change rate (
Differential values) dωL *, dωR * are calculated, and in step H80, their absolute values |dωL * |, |dωR
* | is calculated, and in step H90 |dωL *
The higher absolute value of the wheel speed change rate |dω*| of | and |dωR*| is selected. Next, in step H95, a low-pass filter process is performed on the absolute value |dω*| of the wheel speed change rate selected in step H90. This is the absolute value of the wheel speed change rate due to wheel speed vibration |dω
* This is done to prevent | from changing. In step H100, the absolute value of the wheel speed change rate |dω* is low-pass filtered based on the function map in FIG.
The accuracy k5 corresponding to |* is determined. Here, the low-pass filter processing is calculated using the following equation, and the filter constant b is selected so that the time constant is several hundred ms.

[0039]

[Formula 9] |dω* |i * = (1-b)・|dω* |i−
1*+b·|dω* |i By this low-pass filter processing, the absolute value |dω* | of the wheel speed change rate can be smoothed, and the accuracy can be uniformly lowered during a period in which the error in the estimated yaw rate is large. Instead of this low-pass filter processing, as shown in the flowchart of Fig. 12, when the absolute value of the wheel speed change rate |dω*| increases, k5 quickly approaches 0, and when it decreases, k5 slowly returns to 1. You can also do this.

The flowchart shown in FIG. 12 will now be explained. First, in step I10, a map similar to the function map in FIG. 17 (however, the horizontal axis is |dω*|) is
Determine the value of k5 corresponding to dω* |. Next, in step I20, it is determined whether this determined value of k5 is smaller than the previous k5. If this determined value of k5 is smaller than the previous k5, that is, if it is close to 0, step I
Proceeding to step 70, the determined value of k5 is set as a new k5. On the other hand, if it is larger than the previous k5, the difference k5' between the determined value of k5 and the previous k5 is compared with the predetermined value Δk in step I30 in order to limit the increase by more than the predetermined value Δk. If the difference k5' between this determined value of k5 and the previous k5 is smaller than the predetermined value Δk, this determined value of k5 becomes the new k5 in step I70. Otherwise (if greater than the predetermined value Δk), the new k5 is obtained by adding the predetermined value Δk to the previous k5 in step I40. after that,
In step I50, it is determined whether or not k5 exceeds 1. If k5 > 1, the process advances to step I60.
5 is 1, if k5 ≦1, keep the previous k5
The sum of Δk and Δk becomes the new k5.

[0041] Thereafter, in step H110, the absolute value |ωR*-ωL*| of the left-right difference in wheel speed change rate is calculated, and in step H115, the absolute value |ωR*−ωL*|

[0042]

[Formula 10] |dωR * −dωL * |i * = (1-b)
・｜dωR * −dωL * |i−1 * +b・
|dωR*−dωL*|i is performed, and in step H120, the corresponding accuracy k6 is determined from the function map in FIG.
is determined. Similarly to the above, instead of filter processing, the accuracy k6 may be quickly brought closer to 0 when the absolute value of the wheel speed change rate becomes high, and slowly brought closer to 1 when it becomes low, as shown in Fig. 12. .

Each accuracy factor k1 obtained through the above process
~k6 is the product k1 ・k2 in step H130
...k6 is calculated and becomes the final accuracy k. This may result in driving conditions where the estimated yaw rate does not match the actual vehicle yaw rate, in other words, the accuracy of the wheel speed is insufficient, or the approximation of the estimation calculation formula does not hold.
When the wheel speed is disturbed due to slipping or the like, the accuracy k approaches 0.

Once the accuracy k is determined, step G5 in FIG.
0, the deviation ε is calculated by multiplying the difference e between the actual yaw rate Wa* filtered in the previous step G10 and the estimated yaw rate rx* calculated in the step G20 by the accuracy k. Then, in step G60, the deviation ε is cumulatively added for a predetermined time Tave. Instead of cumulative addition, low-pass filter processing according to the following equation may be performed.

[0045]

[Formula 11] Ei = (1-c)·Ei-1 +εi where c is a filter constant. In step G70, the cumulative addition value E and the predetermined value eH are compared, and if the cumulative addition value E exceeds the predetermined value, it is assumed that the yaw rate sensor is abnormal, and the abnormality detection flag is turned on in step G80, and the flowchart is temporarily terminated. . When the abnormality detection flag is turned on, control shifts to processing when a sensor abnormality occurs. On the other hand, if the cumulative addition value E is less than or equal to the predetermined value eH, the yaw rate sensor is considered to be normal, and step G80 is jumped to, and the flowchart is temporarily ended.

[0046]

As described in detail above, according to the vehicular yaw rate detection device of the present invention, an abnormality in the yaw rate sensor can be detected. Furthermore, with the introduction of slip detection, even if an error occurs in the estimated yaw rate, the aborting means cancels the abnormality determination, which has the excellent effect of correctly detecting the yaw rate without erroneously determining that the yaw rate sensor is abnormal. be.

[0047]

[Brief explanation of the drawing]

FIG. 1 is a complaint correspondence diagram.

FIG. 2 is a diagram showing the configuration of a rear wheel steering control device according to an embodiment.

FIG. 3 is an electrical configuration diagram.

FIG. 4 is a flowchart.

FIG. 5 is a flowchart.

FIG. 6 is a flowchart.

FIG. 7 is a flowchart.

FIG. 8 is a flowchart.

FIG. 9 is a block diagram.

FIG. 10 is a flowchart.

FIG. 11 is a flowchart.

FIG. 12 is a flowchart.

FIG. 13 is a function map.

FIG. 14 is a function map.

FIG. 15 is a function map.

FIG. 16 is a function map.

FIG. 17 is a function map.

FIG. 18 is a function map.

[Explanation of symbols]

M1 Yaw rate sensor M2 Left wheel speed detection means M3 Right wheel speed detection means M4 Estimated yaw rate calculation means M5 Slip detection means M6 Abnormality determination means M7 Cancellation means

Claims (1)

[Claims] 1. A yaw rate sensor that detects an actual yaw rate that occurs as the vehicle turns; a left wheel speed detector that detects a left wheel speed; a right wheel speed detector that detects a right wheel speed; Estimated yaw rate calculating means for calculating an estimated yaw rate based on the speed difference between the left and right wheel speeds determined by the detecting means and the right wheel speed detecting means, and the left wheel speed determined by the left wheel speed detecting means and the right wheel speed determined by the right wheel speed detecting means. slip detection means for detecting wheel slip based on the above; and abnormality determination means for determining an abnormality of the yaw rate sensor by comparing the actual yaw rate determined by the yaw rate sensor and the estimated yaw rate determined by the estimated yaw rate calculation means;
A yaw rate detection device for a vehicle, comprising: a stop means for stopping abnormality determination by the abnormality determination means when a slip state of a wheel is detected by the slip detection means.