JPH11160205A - Vehicle's state quantity estimating device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To correct model parameters which fluctuates according to conditions contained in a vehicle model without harmfully affecting estimation accuracy in an observer. SOLUTION: A vehicle's state quantity estimating device 3 to estimate the immeasurable quantity of the state, etc., of a vehicle on the basis of the measurable quantity of the state of the vehicle among the quantity of the state of the vehicle is added to a vehicle 1 in which the quantity of the state of the vehicle is freely changed by the operation of a driver 2. Then, an observer 4 to perform estimation and a parameter correcting part 5 to correct model parameters in the observer 4 according to adaptation rules are provided in the vehicle's state quantity estimating device 3.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle state quantity estimating apparatus for estimating a vehicle state quantity, and more particularly, to a measurement using a vehicle model mathematically constructed using model parameters and a vehicle state quantity. In a device that estimates the vehicle state quantity, which is difficult to estimate, among the model parameters included in the vehicle model, by appropriately correcting model parameters such as cornering power that change depending on the situation, high accuracy is achieved. Can be estimated.

[0002]

2. Description of the Related Art As a conventional technique of this kind, for example, a technique disclosed in Japanese Patent Application Laid-Open No. 8-268306 (first conventional example) is known. In the conventional method disclosed in this publication, an estimated sideslip angle calculated based on an observer's equation of state, an estimated yaw rate, and an estimated front-rear speed are calculated. The ratio of the estimated lateral acceleration to the estimated lateral acceleration is calculated as a correction coefficient, and the correction coefficient is multiplied by a factor relating to the cornering power in the observer's state equation, whereby the sideslip angle is estimated based on the observer's state equation. Then, since the cornering power is accurately corrected, the accuracy of estimating the sideslip angle is improved.

[0003] Further, as an example in which an adaptive algorithm is applied to an observer, for example, "Rajamani, Hedrick" Ada
ptive observers for active Automotive suspensions
; theory and experiment "IEEE transactions on Co
ntrol system technology vol.3, no.1 ”(second conventional example) is known. In addition, the sign of the output signal shall be used in the one according to the adaptive algorithm, for example, “Tom Connolly” Longitudinal
Transition Maneuvers in an Automated HighwaySystem
"1996 ASME, ICE" and "Chia-shang Liu and Huei Pen"
g "Road Friction coefficent estimation for vehicl
e Path prediction "14th IAUSD Synposium on Dynami
cs of Vehicles on roads and tracks pp. 100-102 (third conventional example) is known.

[0004]

Here, since the lateral force and the cornering force of the tire generally have nonlinear characteristics in a region where the tire slip angle is large, an estimation formula based on a tire model is used for the vehicle. When estimating the vehicle body side slip angle, it has been found that the estimation accuracy of the vehicle body side slip angle decreases in a region where the tire characteristics (the relationship between the tire side slip angle and the cornering force) are nonlinear.

[0005] Therefore, as in the first conventional example, the cornering power included in the estimation formula is corrected by using a correction coefficient corresponding to the ratio between the detected lateral acceleration and the estimated lateral acceleration. It is conceivable that the estimation accuracy of the angle is not reduced.

However, in the first conventional example, since the cornering power of the tire is simply corrected in accordance with the ratio between the detected value and the estimated value of the lateral acceleration, the correction operation and the observer And the calculation for estimating the vehicle state quantity is mutually performed at the same time, and one of the errors affects the other error. For this reason, it is extremely unstable mathematically,
Therefore, it cannot be guaranteed that a high estimation accuracy can be obtained in the observer.

SUMMARY OF THE INVENTION The present invention has been made in view of such unresolved problems of the prior art. Even if a vehicle model includes a model parameter which fluctuates according to a situation, the model parameter may be changed. Is appropriately corrected without adversely affecting the estimation accuracy at the observer,
It is an object of the present invention to provide a vehicle state quantity estimating device capable of stably estimating a vehicle state quantity.

[0008]

In order to achieve the above object, a vehicle state quantity estimating apparatus according to the first aspect of the present invention comprises:
A vehicle state quantity detection unit that detects a measurable vehicle state quantity among the plurality of vehicle state quantities included in a vehicle model mathematically configured using a plurality of vehicle state quantities, based on the vehicle model; An observer for obtaining an estimated value of a desired vehicle state quantity among the plurality of vehicle state quantities using an estimation formula and the vehicle state quantity detected by the vehicle state quantity detection means; and a detected value of the vehicle state quantity And a parameter correcting means for correcting a model parameter included in the vehicle model according to an adaptive law based on an error between the estimated value and the estimated value.

According to a second aspect of the present invention, in the vehicle state quantity estimating apparatus according to the first aspect of the present invention, the parameter correcting means inputs the error into an arithmetic expression according to the adaptive law. The obtained values were integrated to obtain a correction value of the model parameter.

According to a third aspect of the present invention, in the vehicle state quantity estimating apparatus according to the first aspect of the present invention, the parameter correcting means inputs the error to an arithmetic expression according to the adaptive law. The obtained value is input to a predetermined recurrence formula to determine a correction value of the model parameter.

According to a fourth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the first to third aspects, the parameter correcting means may be configured so that the parameter correction means replaces the error or together with the error together with the vehicle state quantity. The model parameters are corrected based on an error between a detection value and an estimated value of the substitute state quantity that substitutes the quantity.

According to a fifth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the fourth aspect, the observer does not use the substitute state quantity. According to a sixth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the fourth or fifth aspect, the substitute state quantity is a differential value of the vehicle state quantity.

Further, according to a seventh aspect of the present invention, in the vehicle state quantity estimating apparatus according to the fourth to sixth aspects, the parameter correction means is configured to determine the error of the vehicle state quantity or the substitute state quantity. The model parameters are corrected based on the sign.

According to an eighth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the fourth to seventh aspects,
The parameter correction means is configured to correct the model parameter using an output of a function that receives the error of the vehicle state quantity or the substitute state quantity as an input, and outputs the function as an input of the error as the input. When the absolute value exceeds a predetermined threshold value, saturation occurs.

According to a ninth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the first to eighth aspects, the plurality of vehicle state quantities include a yaw rate, a vehicle body skid angle, a vehicle speed, a lateral acceleration and The vehicle state quantity detecting means detects at least a yaw rate, a vehicle speed, a lateral acceleration, and a steering angle. The observer includes a yaw rate, a vehicle body side slip angle, and a vehicle body lateral speed. And at least one of

According to a tenth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the first to third aspects, the plurality of vehicle state quantities include a yaw rate, a vehicle body slip angle, a vehicle speed, a lateral acceleration, and The vehicle state quantity detecting means detects at least a yaw rate, a vehicle speed, a lateral acceleration, and a steering angle. The observer includes a yaw rate, a vehicle body side slip angle, and a vehicle body lateral speed. And the parameter correction means substitutes at least one of an error between the detected value and the estimated value of the yaw rate and at least one of the vehicle body side slip angle and the vehicle body lateral speed. The model parameters are corrected based on an error between the detected value of the state quantity and the estimated value.

The invention according to claim 11 is the invention according to claim 10.
In the vehicle state quantity estimating apparatus according to the invention, the observer does not use the substitute state quantity.
The invention according to claim 12 is the invention according to claim 10 or 1.
In the vehicle state quantity estimating apparatus according to the first aspect, the substitute state quantity is a differential value of at least one of a vehicle body side slip angle and a vehicle body lateral speed, and the parameter correction unit includes a yaw rate detection value and an estimated value. And the model parameters are corrected based on the error between the estimated value and the estimated value of the substitute state quantity.

According to a thirteenth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the tenth or eleventh aspect, the substitute state quantity is at least one of a vehicle body side slip angle and a vehicle body lateral speed. A differential value, wherein the parameter correction means corrects the model parameter based on an error between the detected value and the estimated value of the yaw rate and a sign of the error between the detected value and the estimated value of the substitute state quantity. I made it.

Further, according to a fourteenth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the tenth or eleventh aspect, the substitute state quantity is a differential of at least one of a vehicle body side slip angle and a vehicle body lateral velocity. The parameter correction means is configured to calculate the model parameter based on an error between a detected value and an estimated value of the yaw rate and an output of a function having an input of an error between the detected value and the estimated value of the substitute state quantity. The output of the function is saturated when the absolute value of the input exceeds a predetermined threshold.

According to a fifteenth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the tenth or eleventh aspect, the substitute state quantity is a lateral acceleration, and the parameter correcting means includes a yaw rate The model parameters are corrected based on an error between the detected value and the estimated value and an error between the detected value and the estimated value of the substitute state quantity.

According to a sixteenth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the tenth or eleventh aspect, the substitute state quantity is a lateral acceleration, and the parameter correction means determines a yaw rate. The model parameters are corrected based on an error between a detected value and an estimated value and a sign of an error between the detected value and the estimated value of the substitute state quantity.

Further, according to a seventeenth aspect of the present invention, in the vehicle state quantity estimating apparatus according to the tenth or eleventh aspect, the substitute state quantity is a lateral acceleration, and the parameter correcting means includes a yaw rate An error between the detected value and the estimated value, and an output of a function having an input of the error between the detected value and the estimated value of the substitute state quantity, and the model parameters are corrected based on the error. The output was saturated when the absolute value of the input exceeded a predetermined threshold.

Here, a system as shown in FIG. 1 is considered. In other words, the system shown in FIG. 1 can measure the vehicle state quantities δ _f , δ _r , r, V, α _lat,. A vehicle state quantity estimating device 3 for estimating a vehicle state quantity or the like that cannot be measured based on the vehicle state quantity is added. Here, the vehicle state quantity includes a front wheel steering angle δ _f and a rear wheel steering angle δ _r directly generated on the vehicle 1 by the operation of the driver 2, and a yaw rate r generated as a result of such operation being applied to the vehicle 1. , _Vehicle speed V, lateral acceleration α _lat , and the like.

The vehicle 1 has the following (1) and (2)
It can be represented by a mathematical model such as an expression.

[0025]

(Equation 1)

(1) y = Cx + Du (2) Here, x indicates an actual vehicle state quantity, and y indicates an output of the vehicle state quantity estimation device 3.

A, B, C, and D are m ×
a matrix of m, m × n, l × m, l × n, where m is a vehicle model among vehicle state quantities resulting from the operation of the driver 2 applied to the vehicle 1 such as the yaw rate r or the like. the number of those employed in, n represents the number of those used in the vehicle model of the vehicle state amount generated directly in the vehicle 1 by the operation of the driver 2 as the front wheel steering angle [delta] _f, l
Is the number of vehicle state quantities estimated by the observer 4 in the vehicle state quantity estimation device 3.

The observer 4 is designed as follows for the vehicle model represented by the above equations (1) and (2). Note that, in the following description, the symbol with “＾” on the right shoulder is obtained by the adaptive calculation of the parameter correction unit 5 in the vehicle state quantity estimation device 3 when the symbol is a model parameter. Indicates that it is obtained by the estimation calculation of the observer 4 if it is the vehicle state quantity. Similarly, the symbol with “〜” on the right shoulder indicates the estimated value obtained by the observer 4,
An error from the actually detected value, or
This represents an error between the correction value obtained by the parameter correction unit 5 and the true value. L is a gain for determining the correction amount of the estimated vehicle state quantity.

[0029]

(Equation 2)

... (3)

[0031]

[Outside 1]

[0032]

(Equation 3)

(4) There is an error between the model parameters used in the observer 4 and the actual vehicle model, which are expressed as in the following equations (5) and (6). You.

[0034]

(Equation 4)

... (5)

[0036]

(Equation 5)

(6) The error e of the vehicle state quantity x is expressed by the following equation (7), and the differential value of the error e is expressed by the following equation (8).

E = xx− ＾ (7)

[0039]

(Equation 6)

(8) The expression (8) can be modified as in the following expression (9).

[0041]

(Equation 7)

(9) The second term on the right side of the equation (9) is a known quantity constituted by an adaptive parameter θ considered to vary in the vehicle model and parameters other than the adaptive parameter θ such as a vehicle state quantity. When W is used, it can be rewritten as the following equation (10).

[0043]

(Equation 8)

(10) An error signal of the adaptive parameter θ is represented by the following equation (11).

[0045]

(Equation 9)

(11) The following equation (12) is an equation known as a Lyapunov function when P and Q are positively definite weighted matrices. Furthermore, it is known from Lyapunov's law that the Lyapunov function _Vlyap converges to zero if the following equation (13), which is the first derivative of the following equation (12), is negative.

[0047]

[Outside 2]

[0048]

(Equation 10)

... (12)

[0050]

[Equation 11]

(13) Here, the above equation (13) can be rewritten as the following equation (14) by using the above equation (10).

[0052]

(Equation 12)

(14) The second term of the equation (14) becomes a negative constant function by appropriately selecting the gain L, and the above equation (12) converges to zero. Therefore, the model parameters should be selected so as to satisfy the following equation (15).

[0054]

(Equation 13)

(15) Further, by using the function of the following equation (16) obtained by differentiating the above equation (11), the following equation (17) is obtained.
The adaptive law represented by the equation is obtained.

[0056]

[Equation 14]

... (16)

[0058]

(Equation 15)

(17) P, C, M satisfying the following equation (18) are added to the equation (17).
If the output signal y in which is used is used, the final adaptive law (19) is determined.

[0060]

(Equation 16)

... (18)

[0062]

[Equation 17]

... (19)

[0064]

[Outside 3]

[0065]

(Equation 18)

... (20)

[0067]

[Outside 4]

Although the above equation (20) is mathematically correct, it is unsuitable for a device such as a computer that handles discrete value models. Therefore, in a discrete value system,
As in the invention according to claim 3, the adaptive parameter θ is obtained by a recurrence formula as shown in the following formula (21). Note that Δt is a sampling time in a discrete value system.

[0069] θ ^ (k) = θ ^ (k-1) + ΔtQ -1 W T M (y (k-1) -Cx ^ (k-1) -Du (k-1)) ...... (21)

[0070]

[Outside 5]

That is, in a system having a vehicle state quantity represented by the following equation (22), one of the vehicle state quantities x ₁ cannot be measured, and the other vehicle state quantity x ₁ cannot be measured.
₂ is measurable, and the vehicle state quantity x ₁
Consider a system where the derivative of is measurable.

[0072]

[Equation 19]

(22) Such a system is represented by the following equation (23).

[0074]

(Equation 20)

(23) Further, in such a vehicle state quantity x, an error e of the vehicle state quantity x is expressed by the following equation (24).

[0076]

(Equation 21)

... (24)

[0078]

[Outside 6]

[0079]

(Equation 22)

(25) Therefore, in such a case, instead of the vehicle state quantity x ₁ that cannot be measured, a substitute state quantity that substitutes the vehicle state quantity as in the invention according to claim 4 will be considered.

[0081]

[Outside 7]

[0082]

(Equation 23)

(26) The differential value (dx ₁ ＾ / dt) is obtained by the following equation (27).

[0084]

(Equation 24)

(27) As a result, even when it is impossible to obtain the adaptive law from the original output signal y, a substantially effective adaptive law can be obtained, and the model parameters of the vehicle model can be obtained. Can be corrected and highly accurate estimation can be performed.

As a specific example in such a case, the vehicle body slip angle β is a vehicle state quantity measured by the observer, and the vehicle body slip angle β is a vehicle state quantity that cannot be measured, and the vehicle body skid angular velocity (dβ / dt) is a derivative thereof. Conceivable.

[0087] Next, the (22) to (24) as well as assume a system of the formula, as the Lyapunov function V _lyap such as (28) below which are also shown in the third conventional example described above The first derivative is given by the following equation (29), and can be rewritten as the following equation (31) by using the following equation (30).

[0088]

(Equation 25)

... (28)

[0090]

(Equation 26)

... (29)

[0092]

[Equation 27]

[0093] (30)

[0094]

[Equation 28]

(31) Further, when the above equation (9) and the following equation (33) are used, the following equation (34) is obtained.

[0096]

(Equation 29)

... (32)

[0098]

[Equation 30]

(33) As a result, the following equation (34) is obtained as an adaptive law.
It can be seen that the adaptive parameter θ can be corrected by using the sign e ^{* of the} error e as in the invention according to claim 7.

[0100]

(Equation 31)

(34) Further, instead of the above equation (30), a saturation function as shown in FIG. 2 can be used as in the invention according to claim 8. The error e ^{* in} this case is as shown in the following equation (35).

[0102]

(Equation 32)

(35) As shown in FIG. 2, the saturation functions include the errors e ₁ and e ₂
Is a function that takes as input the errors e ₁ , e
_If the absolute value of ₂ is less than the predetermined threshold value Φ, the output is 0
1 linearly changes between ₁ and errors e ₁ and e ₂ as inputs.
Is a function that saturates to, for example, 1 or -1 when the absolute value of.

With such a configuration, the same operation as that of the first aspect can be obtained. Furthermore, the above (25)-
In the state estimating method as shown in the equation (27), the vehicle state quantity is basically estimated based on a signal flow as shown in FIG. Here, the estimation of the vehicle state quantity and the estimation of the adaptive parameter θ are performed using the substitute state quantity.

However, since the substitute state quantity is not the original signal itself, it often includes an error with respect to the original signal. Moreover, the estimation of the vehicle state quantity is more sensitive to errors than the adaptation of model parameters. Therefore, according to the invention of claim 5, as shown in FIG.
It is desirable to limit the use of the surrogate state variables to only the adaptation of the model parameters. This object is achieved, for example, by using the following equation (37) instead of the above equation (27).

[0106]

[Equation 33]

... (37)

[0108]

According to the present invention, based on the error between the detected value and the estimated value of the vehicle state quantity, the error is set to 0 so that the error becomes zero.
Since the parameter correction means for correcting the model parameters included in the vehicle model according to the adaptive law is provided, even if the model parameters fluctuate according to the situation, it can be corrected satisfactorily and the estimation accuracy at the observer can be improved, and the accuracy can be improved. Since the vehicle state quantity can be estimated, and the correction is performed according to the adaptive law, there is an effect that the stability of the system can be secured.

In particular, in the invention according to claims 4 to 8, even if it is impossible to measure the vehicle state quantity originally required for the adaptive law for correcting the model parameters, the model parameters can be corrected appropriately. There is an effect that can be.

Further, the model parameters are corrected based on the sign of the error as in the invention of claim 7, or based on the output when the error is input to a predetermined function as in the invention of claim 8. If the model parameters are corrected in this way, there is an effect that the stability of the corrected model parameters is ensured even when the detection accuracy of the vehicle state quantity detecting means is not so high.

[0111]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 5 is a block diagram showing the overall configuration of one embodiment of the present invention. In the vehicle according to the present embodiment, a vehicle body slip angle estimation device 10, a target braking force setting device 20, a braking force control device 30 , Is configured. The target braking force setting device 20 sets an appropriate braking force on the basis of the values supplied by the vehicle body slip angle estimating device 10 (the yaw rate r, the target yaw rate r _d, the vehicle speed V and the vehicle body slip angle beta ^) to The specific configuration of the device is a control to be executed (for example, VDC, A
It is appropriately determined according to the control applicable to the vehicle, such as BS, TCS, etc.), but the details thereof are not the essence of the present invention, and the specific description thereof will be omitted. Also,
As the braking force control device 30 can also adopt a known configuration as appropriate according to the control to be performed, a specific description thereof is omitted.

The vehicle body side slip angle estimating apparatus 10 is actually constituted by a microcomputer, necessary interface circuits and the like, and comprises a yaw rate r supplied from a yaw rate sensor 11 for detecting a yaw rate generated in the vehicle, and a vehicle The lateral acceleration α _lat supplied from the lateral acceleration sensor 13 for detecting the lateral acceleration occurring in the vehicle, the vehicle speed V supplied from the vehicle speed sensor 14 for detecting the vehicle speed, and the steering angles of the front wheels and the rear wheels are detected. Based on the front wheel steering angles δ _f , δ _r supplied from the steering angle sensor 15
A predetermined calculation process is executed to obtain the vehicle body side slip angle β ＾.

Here, the vehicle body side slip angle estimating apparatus 10 calculates a vehicle slip angle based on an estimation formula described later based on a vehicle model as shown in FIG. 6 and each detection signal supplied from each sensor.
An observer function for estimating the vehicle body side slip angle β ＾, and a parameter for correcting cornering powers CP _f and CP _r , which are model parameters that change depending on the situation, among the model parameters of the vehicle model on which the observer function is based. And a correction function.

The vehicle model shown in FIG. 6 can be expressed mathematically as the following equations (38) to (46). Where M is the mass of the vehicle, I is the yaw inertia, β
Is the side slip angle of the vehicle body, r is the yaw rate, α is the lateral acceleration, a
Is the horizontal distance from the vehicle center of gravity to the front wheel axle, b is the horizontal distance from the vehicle center of gravity to the rear wheel axle, V is the vehicle speed, δ _f is the front wheel steering angle, δ _r is the rear wheel steering angle, and Y _f is the front wheel steering angle. Tire lateral force, Y
tire lateral force _r is the rear wheel, the CP _f front wheel cornering power, the CP _r a cornering power of the rear wheel, in FIG. 6, W _F is the front wheel, W _R is the rear wheel. Further, the front wheel steering angle [delta] _f can also be obtained from the steering angle of the steering wheel by the driver, a front wheel steering system steering gear ratio.

[0115]

(Equation 34)

... (38)

[0117]

(Equation 35)

... (39)

[0119]

[Equation 36]

... (40)

[0121]

(37)

... (41)

[0123]

(38)

... (42)

[0125]

[Equation 39]

... (43)

[0127]

(Equation 40)

... (44)

[0129]

[Equation 41]

... (45)

[0131]

(Equation 42)

(46) In such a vehicle model, among the vehicle state quantities, the adaptive parameter θ that needs to be corrected to fluctuate according to the situation and the other known quantities W are calculated as described above. (9),
From equation (10), it is obtained as follows.

[0133]

[Equation 43]

... (47)

[0135]

[Equation 44]

... (48)

[0137]

[Equation 45]

... (49)

[0139]

[Equation 46]

... (50)

[0141]

[Equation 47]

... (51)

[0143]

[Equation 48]

(52) Here, the first derivative of the vehicle body slip angle β and its estimated value β ＾ is defined as follows.

[0145]

[Equation 49]

An error signal is generated from a yaw rate r as a vehicle state quantity and its first derivative β _dot which is a substitute state quantity of the vehicle body slip angle β as a vehicle state quantity. If a saturation function as shown in FIG. 2 is used as an input, the adaptive law in the present embodiment is as shown in the following equation (53). Where p
₁ , p ₂ , q ₁ and q ₂ are positive constants for performing weighting, and a matrix including these constants is a positive definite matrix.

[0147]

[Equation 50]

(53) Here, the substitute state quantity β _dot and its estimated value β ＾ _dot ,
Can be obtained by the following equations (54) and (55).

[0149]

(Equation 51)

... (54)

[0151]

(Equation 52)

(55) Then, the above equations (53) and (55) are used for the arithmetic processing in the microcomputer in the vehicle body side slip angle estimating apparatus 10, so that the following equations (56) and (57) are used. Such a recurrence formula can be used.

[0153]

(Equation 53)

... (56)

[0155]

(Equation 54)

(57) FIG. 7 is a flowchart showing the outline of the processing in the vehicle body slip angle estimating apparatus 10. The operation of this embodiment will be described below with reference to FIG.

First, in step 101, the above-mentioned (39) to (39) are used by using the model parameters stored in advance, the input values from the sensors, the vehicle body side slip angle β ＾ and the yaw rate r ＾ estimated in the previous processing. (46), (49)-(5
Each parameter in accordance 2) _{A 11 ~A 22, B 11 ~B} 22,
W _{11 to} W ₂₂ are calculated.

Then, the process proceeds to a step 102, wherein a differential value β _dot as a substitute state quantity is calculated according to the above equation (54) based on the detected values of the lateral acceleration α _lat , the vehicle speed V and the yaw rate r.

Then, the process proceeds to a step 103, wherein a differential value β ＾ _dot as a substitute state quantity is calculated in accordance with the above equation (55) using the vehicle body side slip angle β ＾ and the yaw rate r ＾ estimated in the previous processing. I do.

Then, the flow shifts to step 104, where the cornering power C is calculated according to the adaptive law of the above equation (56).
The correction values CP _f ＾, CP _rの of P _f , CP _r are calculated, and the calculated correction values CP _r ＾, CP _r用_いる are used as future model parameters.

Next, the routine proceeds to step 105, where the estimated values β ＾, r ＾ of the vehicle body side slip angle β and the yaw rate r are calculated according to the above equation (57). The estimated values β ＾, r ＾ are
In step 106, the target yaw rate r _d and the vehicle speed V
Is output to the target braking force setting device 20 together with the above. The target yaw rate r _d is, for example, as is set so as to achieve a desired vehicle steering characteristic based on the front wheel steering angle [delta] _f and the vehicle speed V.

Then, the flow shifts to step 107, where the estimated values and the like obtained in the current processing are stored in a memory, and the processing in FIG. 7 is completed. When the next interrupt timing comes, the flow returns to step 101. The above process is repeatedly executed.

As described above, in this embodiment, the cornering powers CP _f and CP _r are appropriately corrected in accordance with the adaptive law shown in the above equation (56), so that the stability of the system is impaired. Thus, the model parameters can be made close to the true values, and the estimation accuracy of the vehicle body side slip angle β 角 and the like can be improved.

Further, since the error signal used in the above equation (56) is not the error itself but the output when the error is input to the function shown in FIG. 2, so-called sliding mode control is executed. Is equivalent to For this reason, even when the detection accuracy of the yaw rate sensor 11 or the like is not so high, a highly stable adaptive operation can be performed.

Further, instead of the vehicle body side slip angle β, the differential value β
_{Since dot} is used as a substitute state quantity, there is also an advantage that the cornering powers CP _f and CP _r can be corrected using an adaptive law even though the actual measurement of the vehicle body side slip angle β is impossible.

Here, in the present embodiment, the yaw rate sensor 11, the lateral acceleration sensor 13, and the vehicle speed sensor 14
The vehicle state quantity detecting means is constituted by the steering angle sensor 15 and the processing of step 105 in the vehicle body side slip angle estimating apparatus 10 corresponds to the observer, and the processing of step 104 in the vehicle body side slip angle estimating apparatus 10 corresponds to the parameter correcting means. Corresponding.

In the above-described embodiment, the final error signal used for the adaptive law is obtained using the saturated function as shown in FIG. 2. However, the present invention is not limited to this. The sign (positive or negative) of the original error may be used, and even in such a configuration, the estimation accuracy of the vehicle body side slip angle β and the like can be improved as in the above-described embodiment. Moreover, if the adaptation is based on codes,
As in the case of using the above function, highly stable adaptive operation can be performed.

If the detection accuracy of the yaw rate sensor 11 or the like is sufficiently high, the error itself may be used for the application rule. Further, in the above embodiment,
As a substitute state quantity of the vehicle body slip angle β, its derivative value β _dot
However, the substitute state quantity of the vehicle body side slip angle β is not limited to this. For example, the lateral acceleration α _lat can be used as the substitute state quantity. In this case, the estimated value α _{lat の} of the lateral acceleration α _lat can be obtained from the above equation (54) by the following equation (58).

Α _lat ＾ = V (β ＾ _dot + r) (58) Then, the adaptive law in such a case is that if an output of a function as shown in FIG. And the following equation (59). Note that the sign of the original error may be used instead of the output of the function, or the error itself may be used.

[0170]

[Equation 55]

(59) That is, as a substitute state quantity of the vehicle body side slip angle β, the differential value β _dot is suitable as described above, and other estimated values are used for the differential value β _dot . The relation may be expressed by a linear relational expression including the target yaw rate r, for example, such as a lateral acceleration α _lat , and in essence, a differential value β _dot indicating a behavior similar to the vehicle body side slip angle β. Vehicle state quantity, or other vehicle state quantity showing the vehicle body slip angle β or a behavior similar thereto, or vehicle state approximated to the vehicle state quantity obtained by using a calculation such as a linear combination from the vehicle body slip angle β and the yaw rate r. If it is a quantity, it can be applied sufficiently as a substitute state quantity.

In the above embodiment, the vehicle body side slip angle β is estimated. However, the present invention is not limited to this. For example, the present invention can be applied to a device for estimating the vehicle body lateral speed. It is.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a basic configuration of the present invention.

FIG. 2 is a diagram illustrating an example of a function applicable to the present invention.

FIG. 3 is a block diagram showing a basic signal flow.

FIG. 4 is a block diagram illustrating a signal flow when the use of the substitute state quantity is limited to parameter correction.

FIG. 5 is a block diagram showing a configuration of an embodiment of the present invention.

FIG. 6 is a diagram showing a vehicle model.

FIG. 7 is a flowchart showing an outline of processing.

[Explanation of symbols]

 REFERENCE SIGNS LIST 1 vehicle 2 driver 3 vehicle state quantity estimation device 10 vehicle body side slip angle estimation device 11 yaw rate sensor 13 lateral acceleration sensor 14 vehicle speed sensor 15 steering angle sensor 20 target braking force setting device 30 braking force control device

Claims (17)

[Claims] 1. A vehicle state quantity detecting means for detecting a measurable vehicle state quantity among the plurality of vehicle state quantities included in a vehicle model mathematically constructed using a plurality of vehicle state quantities; An observer for obtaining an estimated value of a desired vehicle state quantity among the plurality of vehicle state quantities using an estimation formula based on a vehicle model and the vehicle state quantity detected by the vehicle state quantity detection means; Parameter correction means for correcting model parameters included in the vehicle model according to an adaptive law based on an error between the detected value of the state quantity and the estimated value so that the error becomes zero. Vehicle state quantity estimation device. 2. The method according to claim 1, wherein said parameter correction means integrates a value obtained by inputting said error into an arithmetic expression in accordance with said adaptive law to obtain a correction value of said model parameter. 2. The vehicle state quantity estimation device according to 1. 3. The method according to claim 1, wherein the parameter correction unit inputs a value obtained by inputting the error into an arithmetic expression according to the adaptive law into a predetermined recurrence formula to obtain a correction value of the model parameter. The vehicle state quantity estimating device according to claim 1, wherein 4. The method according to claim 1, wherein the parameter correction unit corrects the model parameter based on an error between a detection value and an estimated value of a substitute state quantity that substitutes for the vehicle state quantity instead of or in addition to the error. The vehicle state quantity estimating device according to any one of claims 1 to 3, wherein: 5. The vehicle state quantity estimating apparatus according to claim 4, wherein the observer does not use the substitute state quantity. 6. The vehicle state quantity estimation device according to claim 4, wherein the substitute state quantity is a differential value of the vehicle state quantity. 7. The parameter correction unit according to claim 4, wherein the parameter correction unit corrects the model parameter based on a sign of the error of the vehicle state quantity or the substitute state quantity. The vehicle state quantity estimation device according to any one of claims 1 to 3. 8. The parameter correction means is configured to correct the model parameter using an output of a function having the error of the vehicle state quantity or the substitute state quantity as an input, and the output of the function is 8. The vehicle state quantity estimating device according to claim 4, wherein the saturation is performed when the absolute value of the error as the input exceeds a predetermined threshold value. 9. The vehicle state quantity includes a yaw rate,
The vehicle state quantity detecting means detects at least a yaw rate, a vehicle speed, a lateral acceleration and a steering angle, and the observer includes a yaw rate; 9. The vehicle state quantity estimating device according to claim 1, wherein at least one of the vehicle body side slip angle and the vehicle body lateral speed is estimated. 10. The vehicle state quantity includes a yaw rate, a vehicle body side slip angle, a vehicle speed, a lateral acceleration, and a steering angle, and the vehicle state quantity detecting means calculates at least a yaw rate, a vehicle speed, a lateral acceleration, and a steering angle. The observer estimates the yaw rate, at least one of the vehicle body side slip angle and the vehicle body lateral speed, and the parameter correction unit detects the yaw rate and the detected value of the yaw rate. The model parameter is corrected based on an error from an estimated value, and an error between a detected value and an estimated value of a substitute state quantity that substitutes at least one of the vehicle body slip angle and the vehicle body lateral speed. Claim 1
The vehicle state quantity estimating device according to claim 3. 11. The vehicle state quantity estimating device according to claim 10, wherein the observer does not use the substitute state quantity. 12. The substitute state quantity is a differential value of at least one of a vehicle body side slip angle and a vehicle body lateral speed, and the parameter correction means includes an error between a detected value of a yaw rate and an estimated value, and 12. The vehicle state quantity estimating device according to claim 10, wherein the model parameter is corrected based on an error between a detected value of the state quantity and an estimated value. 13. The substitute state quantity is a differential value of at least one of a vehicle body side slip angle and a vehicle body lateral speed, and the parameter correction unit determines an error between a detected value of a yaw rate and an estimated value and the substitute state amount. 12. The vehicle state quantity estimating device according to claim 10, wherein the model parameter is corrected based on a sign of an error between the detected value of the amount and the estimated value. 14. The substitute state quantity is a differential value of at least one of a vehicle body side slip angle and a vehicle body lateral speed, and the parameter correction means includes an error between a detected value of a yaw rate and an estimated value, and the substitute state quantity. And correcting the model parameters based on an output of a function having an error between the detected value and the estimated value as an input. The output of the function is such that the absolute value of the input is a predetermined threshold. 10. The method according to claim 10, wherein the saturation occurs when the pressure exceeds
2. The vehicle state quantity estimation device according to 1. 15. The substitute state quantity is a lateral acceleration, and the parameter correction unit calculates an error between the detected value and the estimated value of the yaw rate and an error between the detected value and the estimated value of the substitute state quantity. The vehicle state quantity estimating device according to claim 10 or 11, wherein the model parameter is corrected based on the model parameter. 16. The substitute state quantity is a lateral acceleration, and the parameter correction unit calculates an error between a detected value and an estimated value of the yaw rate and a sign of an error between the detected value and the estimated value of the substitute state quantity. The vehicle state quantity estimating device according to claim 10 or 11, wherein the model parameter is corrected based on the following. 17. The substitute state quantity is a lateral acceleration, and the parameter correction means inputs an error between a detected value and an estimated value of the yaw rate and an error between the detected value and the estimated value of the substitute state quantity. And correcting the model parameters based on the output of the function, and the output of the function is saturated when the absolute value of the input exceeds a predetermined threshold value. 10 or 1
2. The vehicle state quantity estimation device according to 1.