JPH09127150A - Abnormality detecting device for yaw rate sensor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect the abnormality of a yaw rate sensor used in 4WS system or the like. SOLUTION: The respective detecting signals from a front wheel steering sensor 10, a car velocity sensor 12, a yaw rate sensor 24 and a G sensor 26 are fed to an electronic control device ECU18. The ECU 18 detects the abnormality of the yaw rate sensor 24 according to whether the yaw rate change rate to the steering angle change is within a designated range or not. The threshold value of judging normal/abnormal is adjusted to be increased and decreased depending upon the lateral acceleration, and set in such a manner that when a vehicle suddenly turns, the normal judging area is enlarged. Thus, it is possible to prevent a wrong judgement of the yaw rate sensor at the time of sudden turning.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a yaw rate sensor abnormality detection device, and more particularly to a device for determining normality / abnormality based on a yaw rate change with respect to a steering angle change.

[0002]

2. Description of the Related Art Conventionally, a 4WS system has been proposed in which a yaw rate sensor for detecting a disturbance is provided in addition to a vehicle speed sensor and a steering angle sensor, and rear wheel steering is controlled based on detection signals from these three sensors. . In such a system, a mechanism for determining normality / abnormality of the yaw rate sensor is provided in order to prevent the rear wheel steering control from being performed based on the abnormal yaw rate when the yaw rate sensor fails.

For example, in the four-wheel steering system disclosed in Japanese Unexamined Patent Publication No. 4-135980, a yaw rate change rate corresponding to a steering angle change (steering angular velocity) that can normally occur due to side winds, road surface conditions, etc. is obtained in advance by an actual vehicle running test. Based on this, the yaw rate change rate boundary value corresponding to the steering angle change serving as a threshold value is graphed and stored in a memory or the like. Then, a technique is disclosed in which a yaw rate change with respect to an actual steering angle change is detected and a failure is determined when the detected yaw rate change rate exceeds a preset yaw rate change rate threshold value.

FIG. 4 shows a normal / abnormal judgment graph used in this prior art. In the figure, the horizontal axis is the steering angle change (steering angular velocity), and the vertical axis is the yaw rate change rate. The area sandwiched between the two thresholds 1 and 2 is an area where the yaw rate sensor is determined to be normal, and the other areas are areas where the yaw rate sensor is determined to be abnormal.

[0005]

However, in consideration of the actual vehicle running, the yaw rate changes in a linear region in which the yaw rate changes following the steering operation and the steering operation during emergency avoidance or spinning is delayed. There is a non-linear region with low tracking ability. In the linear region, it is possible to accurately determine whether the yaw rate sensor is normal / abnormal by the above technique, but in the non-linear region, since the phases of the steering angle change and the yaw rate change are largely deviated, the threshold value similar to that in the linear region is set. If it is used, there is a possibility that the normality / abnormality may be erroneously determined. FIG. 5 shows the changes over time of the steering angle change and the yaw rate change in the linear region (A) and the non-linear region (B). In the linear region, the steering change and the yaw rate change have a small phase shift and are excellent in followability, but in the nonlinear region, a steep steering operation is performed, so that a large phase shift occurs in the steering angle change and the yaw rate change. Therefore, for example, FIG.
When a change in the steering angle and a change in the yaw rate are detected in FIG. 4A, only a small change in the yaw rate is detected for a large change in the steering angle, and it is determined that the yaw rate sensor is abnormal if the determination map of FIG. 4 is used. . of course,
This is because there is a large phase shift between the steering change and the yaw rate change, and the yaw rate sensor is originally operating normally and should not be determined to be abnormal.

As described above, in the prior art, it is difficult to always judge whether the yaw rate sensor is normal or abnormal with high accuracy regardless of various changes in the turning state of the vehicle. Of course, it is conceivable to expand the normality determination region in FIG. 4 in advance in consideration of the non-linear region of the steering angle change and the yaw rate change, but in this case, it leads to a decrease in the accuracy of the normality / abnormality determination in the linear region. It cannot be a countermeasure.

The present invention has been made in view of the above problems of the prior art, and an object thereof is to detect abnormality of the yaw rate sensor, which can always determine whether the yaw rate sensor is normal or abnormal with high accuracy regardless of various turning states of the vehicle. To provide a device.

[0008]

To achieve the above object, a first invention is an apparatus for detecting an abnormality of a yaw rate sensor based on a yaw rate change detected by a yaw rate sensor with respect to a steering angle change. , State detection means for detecting the turning state of the vehicle, and according to the detected turning state,
Threshold value setting means for changing the normal / abnormal determination threshold value of the yaw rate change with respect to the steering angle change.

As described above, the threshold value for determining the normality / abnormality of the output of the yaw rate sensor is not fixed, but is increased / decreased according to the turning state of the vehicle.
Normality / abnormality can always be determined with high accuracy, not limited to the linear region and the non-linear region. Specifically, when the turning state of the vehicle is in the linear region, the normal determination region is narrowed, and when it is in the non-linear region, the normal determination region is expanded. This makes it possible to prevent a decrease in accuracy in the linear region and prevent an erroneous determination in the nonlinear region.

Further, in order to achieve the above object, the second invention is characterized in that, in the first invention, the threshold value setting means changes the threshold value based on lateral acceleration.

Here, the magnitude of the lateral acceleration represents the turning state of the vehicle. That is, it can be determined that the vehicle is in the nonlinear region as the lateral acceleration increases.

[0012]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 shows a block diagram of the configuration of this embodiment. Steering 1 is front wheel steering mechanism 1
4, the front wheels are steered by operating the steering wheel 1. A front wheel steering sensor 10 is installed between the steering wheel 1 and the front wheel steering mechanism 14 to detect the steering angle. Further, the vehicle speed is detected by the vehicle speed sensor 12, and the detected steering angle and vehicle speed are output to the electronic control unit ECU 18. On the other hand, the yaw rate sensor 24 that detects the yaw rate of the vehicle and the G sensor 2 that detects the lateral acceleration of the vehicle
6 are provided at predetermined positions, and the detection signals are sent to the ECU 1 respectively.
8 The ECU 18 outputs a control signal to the electric motor 20 based on these detection signals, and the electric motor 2
Reference numeral 0 is a mechanism for driving the rear wheel steering actuator 22 to steer the rear wheels. The G sensor 26 detects a turning state, and the ECU 18 sets a threshold value according to the output. The steering angle of the rear wheels is detected by the rear wheel steering sensor 16 and output to the ECU 18.

The basic operation of the ECU 18 is to determine the rear wheel steering angle based on the vehicle speed, the steering angle and the yaw rate. However, when the yaw rate sensor 24 fails, the yaw rate sensor is used so that the rear wheel steering is not performed by the yaw rate signal. It is necessary to constantly monitor the normality / abnormality of. In the present embodiment, the yaw rate sensor 24 with such normal / normal
The abnormality is based on the yaw rate change with respect to the steering angle change and the output of the G sensor 26. Hereinafter, this ECU 18
The normality / abnormality determination process of the yaw rate sensor 24 in FIG.

FIG. 2 shows a processing flowchart in the ECU 18. First, the ECU 18 reads detection signals from the front wheel steering sensor 10, the vehicle speed sensor 12, the yaw rate sensor 24, and the G sensor 26 (S
101). The ECU 18 calculates a lateral acceleration change rate (lateral jerk) from the lateral acceleration detected by the G sensor 26 (S).
102). The calculation is performed by calculating the difference between the present detection value and the previous detection value. Then, the turning state value α is calculated from the calculated lateral jerk and lateral acceleration (S10).
3). This turning state value α is, specifically,

(Equation 1) Is calculated by This calculation is for quantitatively evaluating what the turning state of the vehicle is, and indicates that the yaw rate does not follow the steering operation as the turning state value α increases. .

Next, the ECU 18 determines a map for judging whether the yaw rate sensor 24 is normal or abnormal based on the state value α (S104). This map determination is specifically determined by increasing or decreasing the threshold 1 and the threshold 2 shown in FIG. FIG. 3 schematically shows this map determination, and shows how the threshold value is set according to the turning state value. In the figure, the horizontal axis represents the steering speed and the vertical axis represents the yaw rate change rate. As the turning state value increases, the threshold 1 shifts to the lower right in the figure, and the threshold 2 shifts to the upper left in the figure to expand the normal determination region. On the contrary, as the turning state value is smaller, the threshold value 1 shifts to the upper left, the threshold value 2 shifts to the lower right, and the normality determination region is set narrow. The maximum values of the steering speed and the yaw rate change rate are the maximum steering speed that the driver can steer and the maximum yaw rate change rate that the vehicle can generate. In this way, by changing the threshold value according to the turning state value and setting the normal determination region and the abnormality determination region, the normal determination region is narrow in the linear region where the yaw rate change follows the steering change well. On the contrary, in the non-linear region in which the yaw rate change does not follow the steering change and the phase shift is large, the normal determination region expands to maintain the normal / abnormal determination accuracy and to reliably prevent erroneous determination. it can.

After determining the normal / abnormal determination map as described above, the ECU 18 calculates the yaw rate change rate from the yaw rate detected by the yaw rate sensor 24 (S
105), on the other hand, the steering speed is calculated based on the detection signal from the front wheel steering sensor 10 (S106). Both of these calculations are calculated by calculating the difference between the current detection value and the previous detection value. Then, the calculated steering speed and yaw rate change rate are compared with the map determined in S104 to determine whether the yaw rate output is normal or abnormal (S107). Specifically, it is determined whether the yaw rate change rate at the calculated steering speed is located in the normal determination region or the abnormality determination region on the map. Then, when it is determined that the yaw rate output is in the normal region, the value of the counter value CNT (the initial value is CNT = 0)
Is decremented by 1 (S108), and on the other hand, when it is determined that it is in the abnormal region, the counter value CNT is set to a predetermined number N (N is set to a large value to prevent normal / abnormal hunting, for example, 200). Input) (S10
9). In this way, the counter value C based on normality / abnormality
NT is changed to determine whether the counter value CNT is positive or negative (S110). If it is determined that the yaw rate output is normal, the value of CNT becomes negative, so the counter value CNT is reset to 0 (S111), and the normal / abnormal determination flag FLAG is set to 0 to set the yaw rate sensor. Two
4 is normal (S112). On the other hand, when the counter value CNT is not negative, the yaw rate sensor 24
Is set to 1 as the flag FLAG (S113). When the flag FLAG is set to 1, the yaw rate sensor 24 is abnormal, so the ECU 18 stops the control based on the signal from the yaw rate sensor 24.

As described above, in the present embodiment, the turning state of the vehicle is evaluated based on the lateral acceleration, and the normal / abnormal determination threshold value is adaptively set according to the turning state value. Whether the yaw rate sensor is normal or abnormal can be reliably determined regardless of the state.

The essence of the present invention is to evaluate the turning state of the vehicle and set a normal / abnormal judgment threshold value based on the evaluation result. Therefore, the turning state is evaluated based on the lateral acceleration. However, the turning state of the vehicle can be evaluated by other means, for example, the vehicle body slip angle, and any method capable of quantitatively evaluating the phase shift between the steering change and the yaw rate change can be used. It goes without saying that it is included in the technical idea of the present invention.

[0020]

As described above, according to the abnormality detection device for the yaw rate sensor of the present invention, the abnormality of the yaw rate sensor can be surely detected regardless of various turning states of the vehicle. The reliability of the system can be improved.

[Brief description of the drawings]

FIG. 1 is a configuration block diagram of an embodiment of the present invention.

FIG. 2 is a processing flowchart of the embodiment.

FIG. 3 is an explanatory diagram of a normal / abnormality determination map in the same embodiment.

FIG. 4 is an explanatory diagram of a normal / abnormality determination map in a conventional device.

FIG. 5 is a graph showing changes over time in steering change and yaw rate change in a linear region and a non-linear region.

[Explanation of symbols]

10 front wheel steering sensor, 12 vehicle speed sensor, 1
4 front wheel steering mechanism, 16 rear wheel steering sensor, 18 electronic control unit ECU, 20 electric motor,
22 rear wheel steering actuator, 24 yaw rate sensor, 26 G sensor.

Claims (2)

[Claims] 1. A device for detecting an abnormality of a yaw rate sensor based on a yaw rate change detected by a yaw rate sensor with respect to a steering angle change, a state detecting means for detecting a turning state of a vehicle, and a detected turning state. A yaw rate sensor abnormality detecting device for changing a normal / abnormal judgment threshold value of a yaw rate change with respect to the steering angle change. 2. The yaw rate sensor abnormality detection device according to claim 1, wherein the threshold value setting means changes the threshold value based on lateral acceleration.