JPH04252776A - Control device for vehicle - Google Patents

Abstract

PURPOSE:To detect sensor trouble even without providing over two pieces of same kind sensors as sensors for detecting quantity of state, in the control device of a vehicle. CONSTITUTION:In a steering angle control device, front and rear wheel steering angle sensors 11, 12, a yaw rate sensor 13, and a lateral acceleration sensor 14 are at least used for steering angle control. A quantity of state estimation part 16 estimates output of the sensors 13, 14 from front and rear wheel steering angles. A trouble detection part 17 judges which sensor is troubled in the sensor group 11-14, by comparing the output of the sensors 13, 14 and the estimated value. Even using each sensor singly, a troubled sensor can be specified and the trouble can be judged, and cost against the sensors can be reduced.

Description

[Detailed description of the invention]

0001

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a control device for a vehicle, and more particularly to a control device for controlling a vehicle based on detected state quantities related to the motion of the vehicle.

0002

[Background Art] In a vehicle control device that controls a vehicle using output signals from sensors that detect various state quantities of the vehicle, two sensors are used to detect failure of the sensor. In a system that determines whether a failure has occurred by installing a sensor, a sensor failure can be detected by comparing the outputs of the two sensors. In other words, the output signals of two sensors that detect the same state quantity are compared, and if the difference between the values exceeds a predetermined value, it is determined that there is a failure in the sensor system.
For this purpose, two sensors will be installed. Therefore, for example, in the case of a steering angle control device for a 4WS vehicle with a rear wheel steering mechanism, if the steering angle sensor is to be used as a failure detection target, two steering angle sensors should be provided, and When using yaw rate as control information for steering angle calculation, if the yaw rate sensor that detects the yaw rate is also subject to failure detection, two yaw rate sensors should be provided to prepare for failure diagnosis for each sensor. Become.

0003

[Problem to be Solved by the Invention] However, in a vehicle control device that detects sensor failure using such a failure detection device, at least two sensors of the same type are installed and their outputs are compared. Therefore, at least two sensors that detect the same state quantity are required for fault diagnosis, which increases the number of sensors and increases cost. In addition, when trying to improve control by increasing the amount of state information necessary for control, and when adding a new type of sensor to the system, it is not enough to use one additional sensor, so two sensors are needed. will have to be added. In either case, the control system becomes expensive, which becomes a cost burden when an inexpensive system is desired.

[0004] Furthermore, even if it is possible to diagnose a malfunction in the detection system using two sensors of the same type, it is not possible to determine which of them is malfunctioning (that is, it must be possible to distinguish which one is normal). (b) After a failure occurs, it is impossible to continue the control that requires the state quantity to be detected by the detection system as control information.

An object of the present invention is to provide a vehicle control device that detects at least three types of state quantities related to the motion of a vehicle and uses the detected state quantities for control, in which state quantity detection means to be subjected to failure detection are of the same type. To provide a vehicle control device which can perform failure detection without providing two or more devices and can identify a failed state quantity detection means. Still another object is to provide a vehicle control device that can continue control even when the state quantity detection means fails.

[0006]

[Means for Solving the Problems] According to the present invention, as the concept is shown in FIG. 1, the following vehicle control device is provided.

[0007] A vehicle control device that detects a state quantity related to the motion of a vehicle and controls the vehicle based on the state quantity,
a state quantity detection means group having first, second, and third state quantity detection means for detecting at least three types of state quantities related to the motion of the vehicle; a second state quantity estimating means for outputting an estimated value of the output of the second state quantity detecting means from the output of the first state quantity detecting means;
a state quantity estimating section having a third state quantity estimating means for outputting an estimated value of the output of the third state quantity detecting means from the output of at least one of the first or second state quantity detecting means; From the combination of the comparison results of comparing the outputs of the second and third state quantity detection means and the respective estimated values by the state quantity estimating section, it is determined which detection means among the state quantity detection means group is malfunctioning. A vehicle control device (FIG. 1(a)) comprising: a determination means for determining whether the vehicle is moving; It has the above state quantity detection means group, and the output of one of the second and third state quantity detection means in the state quantity detection means group is connected to the output of the other state quantity detection means. It has a state quantity estimator that estimates from the output and the output of the first state quantity detection means, and when either the second or third state quantity detection means fails, the output of the state quantity estimator is This is a vehicle control device (FIG. 1(b)) having a failure compensation means that is used in place of the output of the failed state quantity detection means.

[0008]

[Operation] According to the invention as set forth in claim 1, the state quantity detection means group includes first, second, and third state quantity detection means for detecting at least three kinds of state quantities among the state quantities related to the motion of the vehicle. The second state quantity estimation means of the state quantity estimation section estimates the output of the second state quantity detection means from the output of the first state quantity detection means, and the third state quantity estimation means estimates the output of the second state quantity detection means from the output of the first state quantity detection means. The output of the third state quantity detection means is estimated from the output of at least one of the second state quantity detection means, and the failure determination means estimates the output of the second state quantity detection means and the state quantity estimating unit. It is determined which detection means among the state quantity detection means group is at fault based on the combination of the respective comparison results. As a result, it is possible to detect a failure in the state quantity detection means without having to provide one or more of the same type of detection means, thereby reducing the cost of the state quantity detection means, and also preventing failures from occurring. Detection means can be specified.

According to the second aspect of the invention, the state quantity estimating section receives the output of one of the second and third state quantity detection means from the other state quantity detection means. and the output of the first state quantity detection means, and the second,
When one of the third state quantity detection means fails, the failure compensation means uses the output of the state quantity estimator in place of the output of the failed one state quantity detection means. Thereby, when the second and third state quantity detection means fail, control can be continued using the estimated values.

0010

Embodiments Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

FIG. 2 shows an embodiment of the present invention, which is applied to a steering angle control system. In the diagram, 1L and 1R are the front wheels,
2L and 2R indicate the rear wheels, and 3 indicates the steering wheel. The front wheels 1L and 1R can be mainly steered by steering input to the steering wheel, and can also be auxiliary steered by a front wheel steering actuator 4 in the steering mechanism. Further, the rear wheels 2L and 2R can be steered by a rear wheel steering actuator 5 in the auxiliary steering mechanism. The operation of each actuator 4, 5 is controlled by a control system 9 including a signal processing section 6, a control calculation section (steering angle calculation section) 7, and a steering angle control section 8. Input information indicating state quantities related to motion (plane motion). In the illustrated example, a signal from the steering angle sensor 10 that detects the steering angle θ of the steering wheel 3, a signal from the front wheel steering angle (actual front wheel steering angle) sensor 11 that detects the actual front wheel steering angle δf, and an actual rear wheel steering angle are shown. Rear wheel steering angle to detect δr (actual rear wheel steering angle)
A signal from the sensor 12 (the front and rear wheel steering angle sensors 11 and 12 are the first state quantity detection means), and a signal from the yaw rate sensor 13 (the second state quantity detection means) which detects the yaw rate dφ/dt acting on the vehicle. , and a lateral acceleration sensor 14 (third state quantity detection means) that detects the lateral acceleration α of the vehicle.
, and a signal from a vehicle speed sensor 15 that detects the vehicle speed V, etc. are input, respectively. Each sensor here includes a yaw rate sensor, a lateral acceleration sensor, and a front and rear wheel steering angle sensor.
As shown in the figure, there is one sensor each detecting the corresponding state quantity information.

The control system 9 basically performs steering angle control as follows. That is, each signal from each sensor 10 to 15 is appropriately filtered and filtered in the signal processing section 6.
Based on the output of each sensor that has been subjected to A/D conversion and signal processing, the control calculation unit 7 calculates the steering angle of the front and rear wheels for vehicle control, and outputs a commanded steering angle to the steering angle control unit 8. Then, so that the actual rudder angle matches the commanded rudder angle,
A steering angle control section 8 controls the front wheel steering actuator 4 and the rear wheel steering actuator 5.

The control system 9 further includes a state quantity estimation section 16 and a failure detection section (failure judgment section) 17 in addition to the above-mentioned sections. The signal processed by the signal processing unit 6 is provided to the failure detection unit 17 and also to the state quantity estimation unit 16. Each sensor output input from the signal processing unit 6 to the failure detection unit 17 is subjected to control calculation when there is no abnormality in the sensor system (state quantity detection system) that is the target of failure detection by state quantity estimation and failure estimation, which will be described later. It is used as an input to the section 7 and applied to the steering angle calculation for steering angle control as described above. Further, for the corresponding sensor system, it is used for comparison with the input from the state quantity estimating unit 16 for failure determination. The state quantity estimating section 16 estimates the output of the sensor based on the input signal thereto and the vehicle motion mathematical model, and provides the estimated value as the other input to the failure detecting section 17.

The failure detection device according to the present invention, which includes a state quantity estimation section 16 and a failure detection section 17, extracts the output of a certain sensor (state quantity to be detected) from the output of another (different type) sensor. Estimated and sensor output (actual sensor detection value)
However, in this embodiment, the front and rear wheel steering angles, yaw rate, and lateral acceleration are respectively used as the state quantities related to the planar motion of the vehicle. Three types of compatible sensors to detect 1
1, 12, 13, and 14, the state quantity estimation unit 1
6, the front wheel actual steering angle δf and the rear wheel actual steering angle are calculated based on the input from the signal processing unit 6 of the signal corresponding to the front wheel actual steering angle δf and the signal corresponding to the rear wheel actual steering angle δr. Based on the steering angle δr, the second state quantity estimation means estimates the yaw rate, and the third state quantity estimation means estimates the lateral acceleration. By comparing these yaw rate estimated values, lateral acceleration estimated values, and output values of each sensor 13, 14, the failure detection unit 17 detects which of the front and rear wheel steering angle sensors, yaw rate sensor, and lateral acceleration sensor. Determine and identify which sensor is at fault.

In another example, instead of or in addition to the above, the state quantity estimator estimates the lateral acceleration α from the yaw rate dφ/dt, and estimates the yaw rate dφ/d from the lateral acceleration α.
Estimate t. The lateral acceleration estimated value from the yaw rate estimated in this way and the yaw rate estimated value from the lateral acceleration can also be input to the failure detection section as comparison information. The failure detection unit 17 desirably performs necessary failure compensation (fail-safe) upon detecting a failure. In that case, it may include using the estimated value as a substitute value for the faulty sensor system.

In the following, the estimation of yaw rate and lateral acceleration by the state quantity estimating section 16 and the estimation of sensor failure by the failure detecting section 17 will be explained in more detail. first,
The steering angle δf is the output of the front and rear wheel steering angle sensors 11 and 12.
, δr, a method for obtaining estimated values for each output of the yaw rate sensor 13 and the lateral acceleration sensor 14 will be described. When the vehicle is a 4WS vehicle that controls the steering angles of the front and rear wheels, the equation of motion of the vehicle is expressed by the following equation. dxp(t)/dt=Ap・xp(t)+
Bp・up(t)…(1)yp1(t)
= cp1・xp(t)+dp・up(t
) ... (2) Here, the above Ap etc. are each expressed by the following (Equation 3) Equation 1

[Math 1] The content is

[0017] Furthermore, the following contents are as follows. xp = [VyP(t), dφp(t)/
dt] T up = [δf (t), δr (t
)] Typ1= αp ap11= − (2/mV) ・(Kf + Kr
) ap12= − (2/mV) ・(Lf Kf
- Lf Kr ) - Vap21= - (
2/IV) ・(Lf Kf − Lf Kr
) ap22= − (2/IV) ・(Lf2Kf −
Lf2K r )bp11= (2/m)・Kf
bp12= (2/m)・Kf
bp21= (2/I)・Lf Kf
bp22=-(2/I) ・Lf Kf m
:Vehicle calculation I:
Vehicle yaw inertia moment Kf: Distance between axles in front of vehicle center of gravity Kr: Distance between axles after vehicle center of gravity V: Vehicle speed
dφp /dt: Vehicle yaw rate Vyp: Vehicle lateral speed αp:
Vehicle lateral acceleration δf: Front wheel actual steering angle
δr: Actual rear wheel steering angle

When the steering angle is input, the equation of motion regarding the planar motion of the vehicle is expressed as above, and the steering angles of the front and rear wheels δf, δr
When estimating the yaw rate dφp /dt and the lateral acceleration α from

[Math 2] (Formula 5) Number 3

[Math 3] Do this using

[0019] Here, x02 = [Vy02(t), dφ02(t)/
dt]T y02 = [α02, dφ02(t)/
dt].

FIG. 3 shows an example of a calculation block diagram for determining the estimated yaw rate dφ02(t)/dt and the estimated lateral acceleration α02 based on the above.

By the above calculation, the yaw rate dφ/d
The following two types of information are obtained for each of t and lateral acceleration α. That is, regarding the yaw rate, the sensor 13
The output dφ/dt value and the steering angles δf and δ of the front and rear wheels
The result estimated from r (estimated value dφ02(t)/dt
), and for lateral acceleration, there are two types of lateral acceleration: the output α value of the sensor 14 and the result estimated from the steering angles δf and δr of the front and rear wheels (estimated value α02). can get. The failure detection unit 17 estimates failures of the yaw rate sensor 13, lateral acceleration sensor 14, and front and rear wheel steering angle sensors 11 and 12 based on these values.

The failure estimation can be performed for each failure case (cases 1-1 to 1-3) from the following viewpoints.

Case 1-1: Yaw rate sensor failure In this case, if the front and rear wheel steering angle sensors are not malfunctioning, each estimated value dφ02(t)/
dt and α02 can also be considered normal, and can therefore be classified into abnormal and normal as follows. Abnormal output (a) Yaw rate sensor output is normal (c) Lateral acceleration sensor (d) Front and rear wheel steering angle sensors (f) Yaw rate estimated from front and rear wheel steering angles (g) Estimated from front and rear wheel steering angles lateral acceleration

Case 1-2: Failure of lateral acceleration sensor Similar to the above, in this case, the following occurs. Abnormal output (a) Normal lateral acceleration sensor output (c) Yaw rate sensor (d) Front and rear wheel steering angle sensors (f) Yaw rate estimated from front and rear wheel steering angles (g) Estimated from front and rear wheel steering angles lateral acceleration

Case 1-3: Failure of one or both of the front and rear wheel steering angle sensors In this case, an accurate estimated value cannot be obtained, so it can be classified as follows. Abnormal output (a) One or both of the front and rear wheel steering angle sensors (
(b) Yaw rate estimated from front and rear wheel steering angles (c) Lateral acceleration output estimated from front and rear wheel steering angles is normal (f) Yaw rate sensor (g) Lateral acceleration sensor

Table 1 below shows the state of the output in response to sensor abnormality in each of the above cases. In the table showing the relationship between sensor failure and each output, NG means abnormal;
OK means normal (the same applies to other tables to be described later).

[0027]

From the above results, the following can be said. That is, dφ/dt
If ≠ dφ02/dt and α= α02, the yaw rate sensor is faulty, and dφ/dt = dφ0
2/dt and α≠α02, the lateral acceleration sensor is faulty, and dφ/dt ≠ dφ02/dt and α≠
If α02, it can be determined that one or both of the front and rear wheel steering angle sensors is malfunctioning. In addition,
In the above judgment, it is desirable to consider the error and set a certain tolerance for the judgment of disagreement or even coincidence. For example, in the case of dφ/dt ≠ dφ02/dt, the difference between the two ( It is preferable to determine that they do not match when the deviation) is equal to or greater than a predetermined value.

FIG. 4 shows an example of a flowchart for performing the above-mentioned fault diagnosis in the fault detection section 17. First, the output value dφ/dt of the yaw rate sensor 13 and the above-mentioned yaw rate estimated value dφ02/dt are compared. It is checked whether the two are equal (step 41), and if they are equal, the output value α of the lateral acceleration sensor 14 is further compared with the lateral acceleration estimated value α02, and it is checked whether the two are equal (
Step 42). Then, if the sensor output value α and the estimated value α02 are equal, it is assumed that there is no abnormality (step 4
3) If they are not equal, it is determined that the lateral acceleration sensor 14 is abnormal and broken (step 44). As already mentioned, in each of the above checks, it is possible to determine whether the deviation is less than a predetermined value or not, and whether or not it matches can be determined based on whether or not the deviation is less than a predetermined value.
The same applies to other embodiments.

[0030] The above-mentioned processing checks whether or not cases 1 and 2 correspond to the above-mentioned case classification and as shown in Table 1.

On the other hand, the yaw rate sensor output value dφ/d
When t and the estimated yaw rate dφ02/dt are not equal, cases 1 and 3 of the above case 1 are expected ((a) and (f) in case 1 of 1).
There are two possibilities: a combination of abnormality and normality, and a combination of abnormality and normality of (b) and (f) in case 1 and 3). Therefore, in order to see which is the cause of the discrepancy, a comparison check is performed between the lateral acceleration sensor output value α and the lateral acceleration estimated value α02 as described above (
(Step 45) (Basically, if the front and rear wheel steering angle sensor systems are normal, the lateral acceleration information whose estimated value is obtained based on the sensor system output like the yaw rate is The idea is that if the sensor output value α and the estimated value α02 match and the front and rear wheel steering angle sensor system is abnormal, a mismatch will also occur between the sensor output value α and the estimated value α02. ). As a result, when it is determined that they are equal, in case 1 above
It is determined that the yaw rate sensor 13 is abnormal and that the sensor itself has failed (step 46). On the other hand, if they are not equal, in this program example, the cause of the mismatch between the sensor output value and the estimated value (in this case, both the yaw rate and the lateral acceleration are mismatched) is to use the information for estimation. It is assumed that the problem is in the front and rear wheel steering angle sensor system, that is, it is considered to correspond to case 1-3, and it is determined that the problem is an abnormality or failure in the front and rear wheel steering angle sensor system (step 47). This has the advantage of being able to detect failures in the steering angle sensor system.

FIGS. 5 to 9 show examples of simulation results for the above-mentioned failure detection. The simulation was performed under the assumption that a steering angle of 45° was given in steps at time 0, and FIG. 5 shows the front and rear wheel steering angle sensors 11,
12, the results when the yaw rate sensor 13 and the lateral acceleration sensor 14 are normal, and FIG. 6 shows the results of each sensor output and each estimated value when the yaw rate sensor 13 is broken,
Figure 7 shows similar results when the lateral acceleration sensor 14 fails, Figure 8 shows similar results when the front wheel actual steering angle sensor fails, and Figure 9 shows similar results when the rear wheel actual steering angle sensor fails. The results are shown below. Looking at Figure 5, we can see that under normal conditions, the figure (
For the actual front wheel steering angle, actual rear wheel steering angle, yaw rate, and lateral acceleration in a) to (d), the sensor output is the same for each true value ((a) in (a) to (d)). The estimated yaw rate dφ02/dt ((c)
(c)) and the estimated lateral acceleration α02 ((d) (c)) exhibit the same behavior as (c) (b) and (d) (b), respectively. ing. Furthermore, from the above, when driving straight ahead before steering, the value is 0.0 in both cases.
It can also be seen that

On the other hand, for example, in the case of the yaw rate sensor failure shown in FIG. 6 (after 0.8 seconds after step steering), in the failure state after the sensor output changes in the failure manner as shown in the figure, the yaw rate sensor output dφ/dt and yaw rate estimated value dφ02/dt are shown in (c) of the same figure.
B) and (C) do not match, and on the other hand, the lateral acceleration sensor output α and the estimated lateral acceleration value α02 remain in the same state as in the normal state shown in Figure 5 after 0.8 seconds. It has been shown that Therefore, the above two conditions regarding yaw rate and lateral acceleration, namely, dφ/ dt≠ dφ02
/ dt, and α= α02 are established, and by comparing each estimated value with the sensor output, it can be determined that the yaw rate sensor 13 has failed in this case, and it is also possible to accurately identify the failed sensor. I understand.

The cases shown in FIGS. 7 to 9 showing the simulation results in the case of other failures can also be explained in the same manner as above. Among these, taking as an example the case where the steering angle sensor system, for example the front wheel actual steering angle sensor 11 in FIG. 8, fails,
To explain more simply, after the failure occurs (after 0.8 seconds), as shown in (b) and (c) in (c) and (b) and (c) in (d) of the same figure, The sensor output dφ/dt and the estimated value dφ02/dt, and the sensor output α and the estimated value α02, do not match, and therefore, by comparing them, we can obtain the result that dφ/dt≠ dφ02/dt and α≠α02. It is shown that it is in a state where Therefore,
The above simulation results also show that in this case, it can be determined that the steering angle sensor system has failed, more specifically, the front wheel actual steering angle sensor 11 has failed.

As described above, according to this embodiment, at least two sensor outputs, the yaw rate sensor 13 and the lateral acceleration sensor 14, are obtained from the output of the vehicle speed sensor 15 and the outputs of the front and rear wheel steering angle sensors 11, 12. Estimate and estimate value dφ0
2/dt, the estimated value α02 is obtained, and by comparing each estimated value and each corresponding sensor output, the front and rear wheel steering angle sensors and yaw rate sensor are determined from the combination of the respective comparison results. Since it is possible to appropriately determine the failure of the lateral acceleration sensors, there is no need to provide two sensors of the same type for each failure detection. Therefore, the cost of the control system can be reduced to the extent that a single sensor is used to detect information on the front and rear wheel steering angles, yaw rate, and lateral acceleration.

Furthermore, in a control system having a steering angle sensor and a yaw rate sensor without providing two sensors of the same type, the output value of the yaw rate sensor may be 0 even though the output value of the steering angle sensor is 0. If not, it is conceivable to determine that there is a failure, but when such a method is used, it may not be possible to determine which type of failure it is, depending on the failure mode.

That is, in the above case, the output values of both sensors are 0 in the non-steering state, and if the steering angle sensor is normal, the output value of the yaw rate sensor is 0 when the output value is 0 (neutral position). The value should also indicate 0, but if it is not 0, it is based on the idea that the yaw rate sensor is malfunctioning. However, when the steering angle sensor output value = 0 and the yaw rate sensor output value ≠ 0, the following situation occurs: It may appear sometimes. In other words, the steering angle sensor itself is abnormal, and its output value shows 0 both when the vehicle is not steering and when the vehicle is steering, while the yaw rate sensor is not abnormal and normally detects the yaw rate and shows the corresponding output value. This is the case. Therefore, from this point of view, even if it is sufficient to use one sensor at a time, failure detection is performed by looking at the mutual relationship of the sensor output values themselves as information for failure diagnosis. The methods described above are insufficient. It is not possible to distinguish between a state in which the steering angle sensor is normal and the yaw rate sensor is abnormal, and a state in which the steering angle sensor is abnormal and the yaw rate sensor is normal. Unable to identify sensor.

The same can be said of the case where a failure is determined when the output value of the lateral acceleration sensor is not 0 even though the output value of the steering angle sensor is 0.

On the other hand, in this embodiment, as described above,
At least two estimated values dφ02/dt, α02 are used, and failure judgment is made by comparing the estimated values dφ02/dt, α02 with each corresponding sensor output dφ/dt, α. In addition to not having to install any sensors, it is possible to properly distinguish between the yaw rate sensor, lateral acceleration sensor, and front and rear wheel steering angle sensor systems to determine if there is an abnormality, making it possible to identify the sensor that has failed. .

Furthermore, when a failure is detected, the failure detection section 17 issues a warning and compensates for the failure. That is, when a failure in the output value of any of the above-mentioned sensors is detected, a message indicating that the corresponding sensor is in failure is displayed on the display. On the other hand, furthermore,
The faulty sensors are yaw rate sensor 13 and lateral acceleration sensor 1.
4, the output of the above estimated value is used instead of the sensor output value, and by doing this,
Almost accurate control can be performed even when a failure occurs. Therefore, the estimated value dφ02/dt and estimated value α02 in this case are information for fault diagnosis, and also have the property that when a failure occurs, the dφ02/dt value and α02 value can be used as substitute values. It is also information. Therefore, in this respect as well, the present invention is superior to a configuration in which two sensors of the same type are arranged to perform failure detection, and even compared to a configuration using the above-mentioned method.

Note that if it is determined that the front and rear wheel steering angle sensor system is malfunctioning in the above manner, in this embodiment, since no estimated value is specifically obtained for this, the steering angle control is stopped and normal operation is performed. 2WS may be used.

FIG. 10 is a modification of the above embodiment, and is an example of a flowchart for fault diagnosis when lateral acceleration is estimated from yaw rate. That is, the estimation of the lateral acceleration in the first embodiment is performed from the front and rear wheel steering angles, but is now performed from the yaw rate. In FIG. 10, steps 41 to 45 are steps for performing the same processing as in FIG. 4, respectively. As a result of the comparison check in step 45, if the answer is Yes and it is determined that they are equal, it is determined in step 46a that there is an abnormality or failure in the front and rear wheel steering angle sensor system, and if the answer is No and they do not match, step 47a is determined. In this case, it is determined that the yaw rate sensor 13 is abnormal or broken. In this way, the yaw rate sensor output is estimated from the outputs of the front and rear wheel steering angle sensors 11 and 12, and the lateral acceleration sensor output is estimated from the output of the yaw rate sensor 13, and each estimated value is compared with the output of each corresponding sensor. Based on the combination of the results, it is also possible to determine the failure of the front and rear wheel steering angle sensors, yaw rate sensor, and lateral acceleration sensor, and the same effects as in the above embodiment can be achieved.

Furthermore, as another modification, the yaw rate may be estimated from the lateral acceleration.

Next, explaining another example of the present invention, the one described below further adds one estimated value to each,
Two estimated values are obtained for each, and a sensor failure is estimated.

That is, in this embodiment, the state quantity estimation unit 16 estimates the lateral acceleration from the yaw rate dφ/dt in addition to the yaw rate estimated value dφ02/dt and the lateral acceleration estimated value α02, and estimates the yaw rate from the lateral acceleration α. The failure detection unit 17 uses these estimated values and the sensor output to perform a comparative judgment to detect a failure of the sensor. Estimation of yaw rate from lateral acceleration sensor 14, yaw rate sensor 1
The estimation of the lateral acceleration from 3 shall be performed using the following methods.

That is, from the lateral acceleration α to the yaw rate dφ/
The method for estimating dt is as follows using a same-dimensional observer.

Step 1: The following (Equation 6) Equation 4

[Math 4] The controllable canonical transformation matrix T is obtained by

Step 2: As shown in the following equation, set poles γ1 and γ2 of the observer are arbitrarily determined, and the gain vector k of the observer is determined. (S + γ1) (S + γ2) = S2+ ( γ1+
γ2) S + γ1 ・γ2 = S2+ d2S +
d1 kT = [d1-a, d2-a2]T -1

0
Step 3: Set the system matrix of the observer as shown below (Equation 7).

[Math 5] Then, the following (Equation 8) Equation 6

[Math 6] (Formula 9) Number 7

The yaw rate estimated value dφ01/dt is obtained by configuring a same-dimensional observer as shown in Equation 7.

Next, in order to estimate the estimated lateral acceleration value α01 from the yaw rate dφ/dt, the lateral velocity V y is estimated. As a method, we use the minimum dimension observer method. However, the following equation 10 is used instead of the above equation 2.

[0051] yp2= cP2・xp yp2=
[dφp/dt] ---
(10) Cp2= [0,1]

Step 1: First, the following (Equation 11) Equation 8

[Number 8
] Determine W appropriately so that the determinant of S shown in is not 0.

Step 2: The following (Equation 12) Equation 9

[Math. 9] Calculate.

Step 3: The following (formula 13) number 10

[Math. 10] j is determined so that the eigenvalue of is set to the desired value γ.

Step 4: Once j is determined above, the following (
Formula 14) Number 11

[Math. 11] The estimated lateral acceleration value α01 is determined by calculating the values of .

FIG. 11 shows yaw rate estimated values dφ01/dt,
An example of a calculation block diagram for determining the estimated lateral acceleration value α01 is shown. In addition, the steering angles δf and δ of the front and rear wheels
Each estimated value dφ02 of yaw rate and lateral acceleration from r
/dt and α02 are determined using the above-mentioned equations 4 and 5 and from FIG. 3, as in the above embodiment.

According to the above calculation, in this embodiment, the yaw rate is determined by the output dφ/dt value of the sensor 13,
The calculation result of the minimum dimension observer (estimated value dφ01/d
t) and the result estimated from the steering angles of the front and rear wheels (estimated value d
Three types of φ02/dt) were obtained, and lateral acceleration was estimated from the output α value of the sensor 14, the calculation result of the same-dimensional observer (estimated value α01), and the steering angle of the front and rear wheels. Three types of results (estimated value α02) are obtained, and these values determine the yaw rate sensor 13, lateral acceleration sensor 14, and front and rear wheel steering angle sensor 11.
, 12. In this embodiment, failure estimation can be performed in the following cases (cases 1 to 2 of case 2).

Case 2-1: Yaw rate sensor failure output is abnormal (a) Yaw rate sensor (b) lateral acceleration output estimated by the minimum dimension observer is normal (c) lateral acceleration sensor (d) front and rear wheels Rudder angle sensor (E) Yaw rate estimated by the same-dimensional observer (F) Yaw rate estimated from the front and rear wheel steering angles (G) Lateral acceleration estimated from the front and rear wheel steering angles

Case 2 of 2: The failure output of the lateral acceleration sensor is abnormal (a) Lateral acceleration sensor (b) The yaw rate output estimated by the same dimension observer is normal (c) The yaw rate sensor (d) Front and rear wheels Rudder angle sensor (e) Lateral acceleration estimated by the minimum dimension observer (
F) Yaw rate estimated from the front and rear wheel steering angles (G) Lateral acceleration estimated from the front and rear wheel steering angles

Case 2
3: The failure output of one or both of the front and rear wheel steering angle sensors is abnormal (a) Either one or both of the front and rear wheel steering angle sensors (b) The yaw rate estimated from the front and rear wheel steering angles (b) c) Lateral acceleration estimated by the front and rear wheel steering angles (d) Lateral acceleration estimated by the minimum dimension observer (
E) Yaw rate output estimated by the same dimension observer is normal (F) Yaw rate sensor (G) Lateral acceleration sensor

Table 2 shows the output in response to an abnormality of the sensor in this embodiment.

[0062]

From the above results, the following judgment can be made. That is, dφ/dt ≠ dφ01/dt =
If dφ02/dt and α01≠α=α02, the yaw rate sensor is faulty, and dφ01/dt≠ d
φ/ dt= dφ02/ dt and α≠α01=
If α02, the lateral acceleration sensor is faulty, and dφ/
dt≠ dφ01/ dt≠ dφ02/ dt and α
If ≠α01≠α02, it can be determined that one or both of the front and rear wheel steering angle sensors is malfunctioning.

FIGS. 12 to 16 show examples of simulation results in this embodiment when a steering angle of 45° is applied in steps. Figure 12 shows the results when all sensors are normal, Figure 13 shows the results of each sensor output and each estimated value when the yaw rate sensor 13 fails 0.8 seconds after steering, and Figure 14 shows the results of the horizontal 15 shows the results when the acceleration sensor 16 fails, FIG. 15 shows the results when the front wheel actual steering angle sensor 11 also fails, and FIG. 16 shows the results when the rear wheel actual steering angle sensor 12 also fails. It can be seen that the relationships shown in Table 2 or above hold true when the corresponding sensor fails.

[0065] In this embodiment, failure diagnosis can be performed more appropriately than in the previous embodiment. For example, if we consider a situation such as when steering on an icy road, depending on the vehicle situation such as excessive turning (spin state), the sensor may be incorrectly determined to be malfunctioning even though there is no malfunction. There is sex. On the other hand, there are two estimated values for yaw rate and lateral acceleration: dφ01/dt, dφ02/dt, α01
, α02 ((c) and (d) of each of (c) and (d) in Figures 12 to 16), the actual sensor output and the estimated values of these two types can be compared and judged. As a result of fault diagnosis, it becomes possible to distinguish between cases caused by vehicle conditions as described above.

Taking the pattern of yaw rate sensor failure as an example, in the case of the above embodiment, dφ/dt≠ d
If the pattern of φ02/dt and α=α02 is caused by vehicle behavior, it would not be possible to distinguish it from a yaw rate sensor failure based on that pattern alone, but in this example, in addition to this, dφ/d
t≠ dφ01/ dt, α≠α01 (therefore α01≠
It is also checked whether α02) holds true (here, it is also checked whether dφ01/dt=dφ02/dt holds true). Here, suppose that the yaw rate sensor is not malfunctioning, and the front and rear wheel steering angle sensors and lateral acceleration sensors are also not malfunctioning, but there is a discrepancy between dφ/dt≠dφ02/dt due to vehicle behavior. For example, at that time, between the normal yaw rate sensor output value dφ/dt and the estimated value dφ01/dt from the normal lateral acceleration sensor, and between the normal lateral acceleration sensor output value α and the estimated value α from the normal yaw rate sensor.
It can be said that there is little possibility that a mismatch will occur at the same time with 01. Considering this, nevertheless, dφ/ dt≠ dφ01/ dt, α≠α01
In this case, it can be determined that the cause of the discrepancy is due to the value dφ/dt, value α01 side, and therefore the failure of the yaw rate sensor (
Also, regarding the fact that the lateral acceleration sensor and front and rear wheel steering angle sensors are normal, α = α02, and furthermore, dφ01/
dt = dφ02/dt). Therefore, in the above example, it is also possible to avoid an erroneous determination that the yaw rate sensor is malfunctioning when it is not.

According to this embodiment, with the above-described configuration, even if the amount of state required to control the vehicle increases, the cost increase due to the increase in the number of sensors can be minimized, as in the previous embodiment. In addition to being able to identify the sensor in which the failure has occurred, it is also possible to make the failure diagnosis more appropriate.

Next, still another example of the present invention will be explained. The present embodiment is an extension of the second embodiment, in which failures are determined particularly for the yaw rate sensor and the lateral acceleration sensor, and compensation for these failures is made more accurate and appropriate.

FIG. 17 is a diagram of the control system in this embodiment.
In the illustrated example, the steering angle sensor, the front wheel actual steering angle sensor, the rear wheel actual steering angle sensor, and the vehicle speed sensor are each numbered 10.
a, 10b, 11a, 11b, 12a, 12b,
Two sensors of the same type, such as 15a and 15b, are arranged, while one each of the yaw rate sensor 13 and lateral acceleration sensor 14, which are subject to failure detection, are provided. As in the second embodiment, the state quantity estimation unit 16 calculates the yaw rate estimated value for the yaw rate.
dφ02/ dt and yaw rate estimated value dφ01/ d
t and two estimated values for lateral acceleration, lateral acceleration estimated value α02 and lateral acceleration estimated value α01, and input these to the failure detection unit (failure judgment unit) 17. The method of obtaining each estimated value is shown in FIG. 3, FIG. 11(a), (
It may be the same as that described above including the calculation block b).

The failure detection unit (failure determination unit) 17 detects the yaw rate and lateral acceleration using the respective sensors 13,
14 or, when either one of the sensors 13 and 14 is out of order, inputs the estimated value of the sensor output in accordance with the identified faulty sensor to the control calculation section (studder angle calculation section) 7. do. The failure determination of the yaw rate sensor 13 and the failure determination of the lateral acceleration sensor 14 may be performed according to the pattern described in the second embodiment. The control calculation unit 17 is
Similarly, for the yaw rate and lateral acceleration, front and rear steering angle calculations are performed using the respective sensor outputs themselves, or when applicable, the estimated values of the sensor outputs applied as substitute values.

In this way, this embodiment deals with the failure of the yaw rate sensor and the lateral acceleration sensor, each of which is provided as a single sensor, and when it is determined that one of them has failed, the state quantity estimation is performed. The estimated value obtained by the section 16 is used in place of the output of the failed sensor to continue control. Failure estimation for the yaw rate sensor and lateral acceleration sensor is based on the dφ/dt value, dφ01/dt value, and dφ0 for the yaw rate.
2/dt value, and α value and α01 value for lateral acceleration,
Using the α02 value, 1 of case 2 described in the second embodiment
Cases (a) to (g) (failure of the yaw rate sensor) and (b) to (g) (failure of the lateral acceleration sensor) in case 2, 2.
The results are shown in Table 3, which shows the relationship between sensor failure and each output.

[0072]

From the above, the failure of the yaw rate sensor 13,
Regarding the failure of the lateral acceleration sensor 14, dφ/dt≠
dφ01/dt= dφ02/dt and α01
If ≠ α = α02, it can be determined that the yaw rate sensor is faulty, and in this case, the above dφ01/ dt value or dφ will be used instead of the yaw rate sensor output.
The steering angle is calculated using the 02/dt value. Also, dφ
If 01/ dt≠ dφ/dt= dφ02/ dt and α≠α01= α02, it can be determined that the lateral acceleration sensor has failed.In this case, from now on, use the above α01 value or α02 value instead of the output of the lateral acceleration sensor. Use this to calculate the steering angle. When fault diagnosis and fault compensation are performed under the above conditions, for example, in the case of a yaw rate sensor failure, the alternative value is the condition where the estimated value dφ01/ dt and the estimated value dφ02/ dt match (dφ01/ dt = dφ02/d
As a result of applying it under t), it becomes possible to use a more correct value as a substitute value than in the case of failure compensation mentioned in the first embodiment, and the accuracy can be improved. can. Regarding this point, the same is true in the case of a lateral acceleration sensor failure, and it is possible to continue accurate steering angle control by using the α01 value or α02 value under the condition that α01 = α02 holds as a substitute value. be.

FIG. 18 shows the failure detection section 17 according to this embodiment.
2 is a flowchart illustrating an example of a simple failure diagnosis program including failure compensation processing for a yaw rate sensor and a lateral acceleration sensor, which is executed in FIG. In this program, first, the output value of the yaw rate sensor 13 dφ/
Yaw rate estimation value d using the same dimension observer as dt
It is checked whether φ01/dt are equal (step 51), and if dφ/dt=dφ01/dt, the output value α of the lateral acceleration sensor 14 and the lateral acceleration estimated value α01 by the minimum dimension observer are equal. It is checked whether or not (step 52), and if the result is α=α01, it is determined to be normal (step 53).

The simulation results according to this embodiment are also similar to those shown in the second embodiment, and the results when the sensor is normal are those shown in FIG. 12, and the results when the yaw rate sensor is malfunctioning. The results when this occurs are the same as those shown in FIG. 13, and the results when the lateral acceleration sensor fails are the same as those shown in FIG. 14. Here, the sensor output dφ/dt, the sensor output α, and the estimated value d applied in steps 51 and 52, particularly for each of the yaw rate and lateral acceleration, are
Focusing on the relationship between φ01/dt and estimated value α01,
During normal operation, as shown in (b) and (c) of Figures 12(c) and (d), dφ/dt = dφ01/dt, α
= α01 holds, and therefore, in such a case, it is determined to be normal. A yaw rate sensor 13 and a lateral acceleration sensor 14 as at least two types of state quantity detection means for detecting state quantities of the vehicle are each provided as a single sensor, and the output of one of these sensors is the output of the other sensor, In the case of a configuration in which estimation is made from the steering angle and vehicle speed, the output of each sensor is mutually estimated based on the output of the other sensor, and therefore, such mutual estimated values dφ01/dt, α
If the above-mentioned relationship holds between 01 and the sensor output value dφ/dt, α (as will be described later), each (b) of FIGS. As shown in (c), if a failure occurs in any of the sensors related to mutual estimation, the above relationship will not hold regardless of which one is). It can be seen that this has not occurred.

If the lateral acceleration sensor output value α and the estimated value α01 are not equal in step 52, it is determined that there is a system abnormality (step 54). That is, dφ/dt =
This is a case where dφ01/dt and α≠α01, but in such a case, neither the yaw rate sensor 13 nor the lateral acceleration sensor 4 are normal, and on the other hand, as shown in FIGS. 13 and 14, If either sensor fails, then dφ/ dt≠ dφ01/
Considering that dt and α≠α01 are satisfied at the same time, these sensors 13 and 14 are not in a malfunction state, so it is determined here that the system is abnormal. In addition, α≠α01 and dφ/ dt≠ dφ01/ dt
The same judgment can be made in the case of .

In step 51, dφ/dt≠d
When φ01/dt (Fig. 13(c), (b), (
If there is a sensor failure in the failure detection target sensors 13 and 14 (see the state after time 0.8 seconds in (c) or after time 0.8 seconds in (b) and (c) in (c) of Figure 14), In this program example, the program proceeds to a check process (step 55) to check whether the lateral acceleration sensor output value α and the estimated lateral acceleration value α02 from the front and rear wheel steering angles are equal. Here, if a check similar to step 52 is carried out prior to this check, and if α≠α01, a comparative judgment is made regarding the output value α and the estimated value α02, then d
Diagnosis can be proceeded by checking the conditions of φ/dt≠ dφ01/dt and α≠α01. Therefore, α= α
02, the relationship is as shown in (b) and (d) of Fig. 13(d), so in this case, the yaw rate sensor 1
3 is determined to be a failure (step 56), and the steering angle control is continued using the yaw rate estimated value as described above instead of the output of the yaw rate sensor (step 55).

On the other hand, if α≠α02, then (
Since the relationship is as shown in (b) and (d), in this case it is determined that the lateral acceleration sensor 14 has failed (step 58), and the estimated lateral acceleration value is used instead of the output of the lateral acceleration sensor as described above. The steering angle control is continued using (step 59). In addition, in order to distinguish which of the sensors 13 and 14 is at fault, (c), (b), and (b) in FIG.
It is also possible to create a program that uses the relationship in (d) and the relationships in (b) and (d) in FIG. 14(c).

Yaw rate sensor 1 is the target sensor for failure detection.
3 and the lateral acceleration sensor 14 can also be implemented with the above-described configuration. In detecting sensor failure, sensor failure can be determined without providing a spare sensor, and yaw rate sensor,
Even if two lateral acceleration sensors are installed, if it cannot be determined which of the two sensors has failed in the event of a failure, the calculation for steering angle control will be performed using one of the two sensors. Control can continue even when a sensor fails, whereas the system would have to stop if a sensor failed.

In the above embodiment, the front and rear wheel steering angles in the vehicle steering angle control device were used as the first state quantity, but at least one of the front and rear wheel steering angles is used as the first state quantity. 2. As the third state quantity, it may be implemented using either yaw rate and lateral acceleration, yaw rate and lateral acceleration, or lateral acceleration and lateral velocity. Furthermore, in addition to the steering angle control device, the present invention also provides a control device that detects state quantities related to vehicle motion and controls the vehicle based on the detected state quantities, such as a suspension active control device (the three state quantities are suspension stroke, yaw rate, and lateral (using acceleration).

[0081]

According to the invention as set forth in claim 1, the output of the second state quantity detection means can be changed from the output of the first state quantity detection means, and at least one of the first or second state quantity detection means. Estimate the output of the third state quantity detection means from the output of
Since it is possible to determine which detection means is at fault from the combination of the comparison results obtained by comparing the respective estimated quantities with the outputs of the second and third state quantity detection means, it is possible to determine which detection means is at fault. Fault diagnosis can be performed without installing two or more devices. Therefore, even if the amount of state required to control the vehicle increases, the cost increase due to the increase in the number of state amount detection means can be minimized. Further, it is possible to specify the state quantity detection means in which a failure has occurred, and it is possible to take more appropriate measures after the failure has occurred.

According to the invention described in claim 2, the second and third
The output of one of the state quantity detection means is estimated from the output of the other state quantity detection means and the output of the first state quantity detection means, and the second and third state quantity detection means are estimated. By using the above estimated value in place of the output of one of the state quantity detection means when one of the detection means fails,
Control can be continued even when the second and third state quantity detection means fail. Therefore, the second and third state quantity detection means can perform appropriate failure compensation when a failure occurs.

[Brief explanation of the drawing]

FIG. 1 is a conceptual diagram of the device of the present invention.

FIG. 2 is a configuration diagram of a steering angle control system according to an embodiment of the present invention.

FIG. 3 is a calculation block diagram showing an example of a method for estimating yaw rate and lateral acceleration from front and rear wheel steering angles.

FIG. 4 is a flowchart showing an example of failure diagnosis.

[Fig. 5] A diagram showing an example of simulation results,
It is a figure which shows the result when a sensor is normal.

FIG. 6 is a diagram similarly showing the results when the yaw rate sensor fails.

FIG. 7 is a diagram similarly showing the results when the lateral acceleration sensor fails.

FIG. 8 is a diagram similarly showing the results when the front wheel actual steering angle sensor fails.

FIG. 9 is a diagram similarly showing the results when the rear wheel actual steering angle sensor fails.

FIG. 10 is a flowchart illustrating an example of failure diagnosis in a modified example of the same embodiment.

FIG. 11 is a calculation block diagram showing an example of a method for mutually estimating yaw rate and lateral acceleration to explain another embodiment of the present invention.

FIG. 12 is a diagram showing simulation results when mutual estimation values are included, and is a diagram showing results when the sensor is normal.

FIG. 13 is a diagram showing the results when the yaw rate sensor fails.

FIG. 14 is a diagram similarly showing the results when the lateral acceleration sensor fails.

FIG. 15 is a diagram similarly showing the results when the front wheel actual steering angle sensor fails.

FIG. 16 is a diagram similarly showing the results when the rear wheel actual steering angle sensor fails.

FIG. 17 is a configuration diagram of a steering angle control system according to still another embodiment of the present invention.

FIG. 18 is a flowchart illustrating an example of failure diagnosis including failure compensation processing.

[Explanation of symbols]

1L, 1R Front wheels 2L, 2R Rear wheels 6 Signal processing unit 7 Control calculation unit 8 Steering angle control unit 10, 10a, 10b Steering angle sensor 11, 11a,
11b Front wheel steering angle sensor (first state quantity detection means) 1
2, 12a, 12b Rear wheel steering angle sensor (first state quantity detection means) 13 Yaw rate sensor (second state quantity detection means) 14 Lateral acceleration sensor (third state quantity detection means) 15, 15a, 15b Vehicle speed Sensor 16 State quantity estimation unit (second state quantity estimation means, third state quantity estimation means)

Claims (2)

[Claims] 1. A vehicle control device that detects state quantities related to the motion of a vehicle and controls the vehicle based on the state quantities, the device comprising: a control device for detecting state quantities related to the motion of the vehicle; A state quantity detection means group having first, second, and third state quantity detection means, and an output of the second state quantity detection means from the output of the first state quantity detection means of the state quantity detection means group. a second state quantity estimating means that outputs an estimated value of , and a third state quantity estimating means that outputs an estimated value of the output of the third state quantity detecting means from the output of at least one of the first or second state quantity detecting means. A combination of comparison results obtained by comparing the outputs of the second and third state quantity detection means and the respective estimated values by the state quantity estimation unit. and determining means for determining which detection means of the state quantity detection means group is at fault. 2. A vehicle control device that detects a state quantity related to the motion of a vehicle and controls the vehicle based on the state quantity, comprising the state quantity detection means group according to claim 1,
The output of one of the second and third state quantity detection means in the group of state quantity detection means is determined by the output of the other state quantity detection means and the output of the first state quantity detection means, respectively. When either the second or third state quantity detection means fails, the output of the state quantity estimation part is used as the output of the failed state quantity detection means. 1. A vehicle control device characterized by having a failure compensation means used instead of.