JP2005326239A - Yaw rate detection apparatus and yaw rate zero-point correction method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a yaw rate detection apparatus and a yaw rate zero-point correction method capable of performing yaw rate zero-point correction under any road conditions. <P>SOLUTION: By identifying the transfer function of a yaw rate with respect to a steering angle of a self vehicle through the use of a steering angle of the self vehicle detected by a steering detecting part 110, a yaw rate detected by a yaw rate detecting part 130, and a zero-point history of the yaw rate detecting part 130 stored in a yaw rate zero-point history storage part 160, a zero point of the yaw rate detecting part 130 is estimated. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a yaw rate detection device and a yaw rate zero correction method.

  It is known that a neutral point (that is, a zero point) drifts with the lapse of time in a yaw rate sensor used for vehicle running control or the like due to sensor ambient temperature or the like. Therefore, in order to calculate the accurate yaw rate of the vehicle, it is necessary to estimate the neutral point of the yaw rate sensor by some method and correct the output value from the yaw rate sensor.

Conventionally, a yaw rate detection device for a vehicle has been proposed in which neutral point correction of the yaw rate can be performed while the vehicle is traveling (see, for example, Patent Document 1). According to the yaw rate detection device disclosed in Patent Document 1, for example, when the vehicle is traveling at a certain speed, the steering angle change is within a predetermined steering angle that can be regarded as a straight traveling state, and the angular speed change Is within the predetermined angular velocity, the maximum angular velocity and the minimum angular velocity from the yaw rate sensor are adopted and stored in the memory as angular velocity candidate values, and then the steering angle candidate values are stored in the memory for a predetermined distance to obtain the angular velocity candidate values. The angular velocity correction is performed based on the sum of the values and the number of candidate angular velocity values.
JP 2002-107147 A

  As described above, since the yaw rate sensor is used for vehicle running control or the like, it is necessary to estimate the zero point of the yaw rate sensor in any road condition. However, the conventional yaw rate detection device can correct the angular velocity only when the change in the steering angle is within a predetermined steering angle that can be regarded as a straight traveling state and the change in the angular velocity is within the predetermined angular velocity.

  Therefore, for example, in a road situation in which curved roads are continuous, the steering angle and the angular velocity often change remarkably, so the opportunity to estimate the zero point of the yaw rate sensor is reduced, and as a result, the zero point cannot be corrected.

  The present invention has been made in view of such a problem, and an object of the present invention is to provide a yaw rate detection device and a yaw rate zero correction method that can correct the zero of the yaw rate even in any road conditions.

  The yaw rate detection apparatus according to claim 1, which has been made to solve the above-described problem, is a steering angle detection unit that detects a steering angle of a vehicle, a yaw rate detection unit that detects a yaw rate of the vehicle, and an estimation of a yaw rate zero point estimation unit. Using the yaw rate zero point history storage means for storing the zero point history of the yaw rate detection means, the steering angle and yaw rate detected by the steering angle detection means and the yaw rate detection means, and the zero point history stored in the yaw rate zero history storage means And yaw rate zero point estimating means for estimating a zero point used for correcting the zero point of the yaw rate detected by the yaw rate detecting means by identifying a transfer function of the yaw rate of the vehicle with respect to the steering angle of the vehicle.

  According to the present invention, a vehicle such as an automobile moves on a plane, and a transfer function of a yaw rate with respect to a steering angle of the vehicle is obtained from a motion equation of a plane two-wheel model that does not consider the load movement in the left-right direction of the vehicle. It is the one that paid attention.

  That is, the transfer function of the yaw rate with respect to the steering angle of the vehicle is identified using the history of the steering angle of the vehicle, the yaw rate, and the zero point history of the yaw rate detecting means estimated so far (system identification).

  By identifying the transfer function of the yaw rate with respect to the steering angle of the vehicle, the zero point of the yaw rate detecting means can be estimated. Therefore, the zero point drifts over time due to the ambient temperature of the yaw rate detecting means, or the curve road is continuous. Even in such a road situation, the zero point of the yaw rate can be corrected using the estimated zero point.

  According to a second aspect of the present invention, there is provided a yaw rate detecting device comprising zero point correcting means for correcting the zero point of the yaw rate detected by the yaw rate detecting means using the zero point estimated by the yaw rate zero point estimating means. Thereby, the zero point of the yaw rate can be corrected.

  According to the yaw rate detection apparatus of claim 3, the yaw rate zero point estimation means estimates the zero point by identifying a transfer function of at least one of the first-order lag system and the second-order lag system. . In general, since the transfer function obtained from the equation of motion of the planar two-wheel model is represented by a second-order lag system, the zero point of the yaw rate detection means can be estimated by identifying the transfer function of the second-order lag system. .

  In a situation where the vehicle motion does not fluctuate significantly (stable), the transfer function of the second-order lag system obtained from the equation of motion of the planar two-wheel model is approximated by the transfer function of the first-order lag system, and this first-order lag The zero point of the yaw rate detection means may be estimated by identifying the transfer function of the system. As a result, it is possible to reduce the arithmetic processing required for zero point estimation.

  The yaw rate detection device according to claim 4 includes a yaw rate history storage unit that stores a history of the yaw rate detected by the yaw rate detection unit, and the yaw rate zero point estimation unit includes the current steering detected by the steering angle detection unit and the yaw rate detection unit. The zero point is estimated by identifying the transfer function of the first-order lag system using the angle and yaw rate, the yaw rate history stored in the yaw rate history storage means, and the zero history stored in the yaw rate zero history storage means. It is characterized by that. Thereby, the zero point of the yaw rate detecting means can be estimated based on the transfer function of the first-order lag system.

  According to a fifth aspect of the present invention, there is provided a yaw rate detection device comprising: a steering angle history storage means for storing a history of the steering angle detected by the steering angle detection means; and a yaw rate history storage means for storing a history of the yaw rate detected by the yaw rate detection means. The yaw rate zero point estimation means includes the current steering angle and yaw rate detected by the steering angle detection means and the yaw rate detection means, the history of the steering angle stored in the steering angle history storage means, and the yaw rate stored in the yaw rate history storage means. The zero point is estimated by identifying the transfer function of the second-order lag system using the history and the zero point history stored in the yaw rate zero point history storage means. Thereby, the zero point of the yaw rate detecting means can be estimated based on the transfer function of the second order lag system.

  According to a sixth aspect of the present invention, there is provided a yaw rate detection device comprising speed detection means for detecting the speed of the vehicle, and the yaw rate zero point estimation means estimates when the vehicle travels at a constant speed. The transfer function of the yaw rate with respect to the steering angle of the vehicle has the vehicle speed as a variable. Therefore, since this variable can be treated as a constant when the vehicle travels at a constant speed, the zero point of the yaw rate detection means can be calculated without considering the speed fluctuation of the vehicle by estimating when the vehicle travels at a constant speed. Can be estimated.

  According to the yaw rate detection apparatus of the seventh aspect, the yaw rate zero estimation means sequentially estimates the zero included as the coefficient of the difference equation derived from the transfer function using the exponential weighted sequential least square method. It is characterized by being.

  In general, it is estimated by performing sequential estimation using the exponential weighted sequential least squares method (REWLS method), which is said to be robust against disturbances such as sensor noise, and responsiveness until an estimation result is obtained. The zero point accuracy of the yaw rate detection means can be improved.

  Since the yaw rate zero point correction method according to claims 8 to 14 is the same as the function and effect of the yaw rate detection device according to claims 1 to 7, the description thereof is omitted.

  Hereinafter, embodiments of a yaw rate detection device and a yaw rate zero correction method of the present invention will be described with reference to the drawings. In the present embodiment, a yaw rate detection device that is mounted on a vehicle such as an automobile and detects a yaw rate generated in the host vehicle will be described.

  FIG. 1 is a block diagram showing the overall configuration of the yaw rate detection apparatus according to this embodiment. As shown in the figure, the yaw rate detection device 100 of the present embodiment includes a steering angle detection unit 110, a steering angle history storage unit 120, a yaw rate detection unit 130, a yaw rate history storage unit 140, a yaw rate zero point estimation unit 150, and a yaw rate zero point history. The storage unit 160 is configured by a vehicle speed sensor that detects the speed of the host vehicle every predetermined time and a yaw rate zero point correction unit, both of which are not shown.

  The steering angle detector 110 is a steering sensor that detects the steering angle of the steering wheel (hereinafter referred to as “steering”) of the host vehicle, and indicates a steering angle {str (k), k indicating the magnitude of the steering angle detected every predetermined time. = 1, 2,..., N} signals are output to the steering angle history storage unit 120 and the yaw rate zero point estimation unit 150.

  The steering angle {str (k)} signal output from the steering angle detection unit 110 is a value in which the zero point (neutral point) is sufficiently corrected. In general, the zero point of the steering angle during traveling is calculated using, for example, a steering angle neutral learning device disclosed in JP-A-11-034899. Therefore, the steering angle has sufficient accuracy in many aspects. When the accuracy of the steering angle zero point is low, the zero point of the yaw rate detection unit 130 may be temporarily estimated by another method.

  The steering angle history storage unit 120 receives the steering angle {str (k)} signal output from the steering angle detection unit 110, and sequentially stores the steering angle {str (k)} data according to the reception order. .

Yaw rate detecting section 130 is a yaw rate sensor for detecting a yaw rate generated on the vehicle (angular velocity and the vertical direction of the vehicle axis), yaw rate that indicates the magnitude of the yaw rate detected every predetermined time {yaw eng _(k )} Signal is output to the yaw rate history storage unit 140 and the yaw rate zero point estimation unit 150. Note that the yaw rate {yaw _eng (k)} signal output from the yaw rate detector 130 is not zero-corrected.

The yaw rate history storage unit 140 receives the yaw rate {yaw _eng (k)} signal output from the yaw rate detection unit 130, and sequentially stores the yaw rate {yaw _eng (k)} data according to the reception order.

The yaw rate zero point estimation unit 150 stores the steering angle {str (k)} signal and the yaw rate {yaw _eng (k)} signal from the steering angle detection unit 110 and the yaw rate detection unit 130, and the yaw rate zero point history storage unit 160. Using the yaw rate sensor zero {Y _c (k−n)} data indicating the zero of the yaw rate detector 130 estimated n times before, the zero of the current yaw rate {y _eng (k)} detected by the yaw rate detector 130 The yaw rate sensor zero point {Y _c (k)} used for correction is sequentially estimated every predetermined time.

The yaw rate correction unit (not shown) uses the yaw rate sensor zero {Y _c (k)} data output from the yaw rate zero estimation unit 150 to detect the yaw rate {y _eng (k)} detected by the yaw rate detection unit 130. Correct the zero point. This makes it possible to correct the zero point of the yaw rate.

The yaw rate zero point history storage unit 160 acquires the yaw rate sensor zero point {Y _c (k)} data output from the yaw rate zero point estimation unit 150 and sequentially stores the data according to the output order.

  As described above, the yaw rate detection apparatus 100 of the present embodiment having such a configuration assumes that the host vehicle moves on a plane, and the equation of motion of a plane two-wheel model that does not consider load movement in the left-right direction of the host vehicle. Therefore, the transfer function of the yaw rate of the own vehicle with respect to the steering angle of the own vehicle is obtained.

  That is, the transfer function of the yaw rate with respect to the steering angle of the host vehicle is identified by using the steering angle and yaw rate of the host vehicle and the history of the zero point of the yaw rate detecting unit 130 estimated so far (system identification). Then, the zero point of the yaw rate detector 130 is estimated by identifying the transfer function of the yaw rate with respect to the steering angle of the host vehicle.

Here, the fact that the zero point of the yaw rate detection unit 130 can be estimated by identifying the transfer function of the yaw rate with respect to the steering angle of the host vehicle will be described using mathematical expressions. First, when the host vehicle travels at a constant speed, the transfer function (yaw / str) of the yaw rate (yaw) with respect to the steering angle (str) of the host vehicle is transmitted in a second-order lag system as shown in Equation 1 below. It is indicated by a function. In Formula 1, coefficients (a ₁ , a ₂ , b ₁ , b ₂ ) that change according to the operator (z) and the motion state of the host vehicle are shown.

(Equation 1)
Transfer function (yaw / str) = {(b ₁ + b ₂ z ⁻¹ ) / (1 + a ₁ z ⁻¹ + a ₂ z ⁻² )}
From the transfer function (yaw / str) of Equation 1 above, as shown in Equation 2 below, a 1-input / output difference equation with the steering angle {str (k)} as input and the yaw rate {yaw (k)} as output. Can be derived.

(Equation 2)
yaw (k) = {− a ₁ × yaw (k−1)} − {a ₂ × yaw (k−2)} + {b ₁ × str (k)} + {b ₂ × str (k−1) }
From the above formula 2, the yaw rate {yaw _eng (k)} before the zero correction can be expressed as the following formula 3. The yaw rate {yaw _eng (k)} and the steering angle {str (k)} in the equation are detected by the steering angle detection unit 110 and the yaw rate detection unit 130. Also, the yaw rate {yaw _eng (k-1)}, {yaw _eng (k-2)}, yaw rate sensor zero {Y _c (k-1)}, {Y _c (k-2)} in this equation, and The steering angle steering angle {str (k−1)} is data stored in the steering angle history storage unit 120, the yaw rate history storage unit 140, and the yaw rate zero point history storage unit 160.

(Equation 3)
yaw _eng (k) = − a ₁ × {yaw _eng (k−1) −Y _c (k−1)} − a ₂ × {yaw _eng (k−2) −Y _c (k−2)} + { b ₁ × str (k)} + {b ₂ × str (k−1)} + c ₀
(C ₀ ) in Equation 3 indicates a zero point to be used for zero point correction of the yaw rate {yaw _eng (k)}. Accordingly, by sequentially identifying the coefficients (a ₁ , a ₂ , b ₁ , b ₂ ) that change according to the motion state of the host vehicle in Formula 3, the zero (c ₀ ) used for the zero correction of the yaw rate detection unit 130. Can be estimated.

As described above, when the zero point (c ₀ ) used for the zero point correction of the yaw rate detection unit 130 is estimated based on the one-input / output difference equation derived from the transfer function of the second-order lag system, the current and previous steerings are estimated. Angular {str (k)}, {str (k-1)}, current, previous and previous yaw _rates {yaw _eng (k)}, {yaw _eng (k-1)}, {yaw _eng (k-2) }, Yaw rate sensor zeros {Y _c (k−1)} and {Y _c (k−2)} of the previous time and the previous time can be sequentially estimated.

In this embodiment, generally, an exponentially weighted sequential least square method (hereinafter referred to as a RWLS method), which is said to be excellent in robustness against disturbances such as sensor noise, and response until obtaining an estimation result, is used. Then, the aforementioned coefficients (a ₁ , a ₂ , b ₁ , b ₂ ) are sequentially identified. Thereby, the precision of the estimated zero can be improved.

Next, an example of identifying coefficients (a ₁ , a ₂ , b ₁ , b ₂ ) by the RWLS method will be described. First, variables are defined as shown in Equations 4 to 6 below. Note that the coefficient vector {θ (k)} in Expression 5 and the vector {Ψ (k)} in Expression 6 indicate vectors.

(Equation 4)
y (k) = yaw _eng (k)
(Equation 5)
θ (k) = [a ₁ a ₂ b ₁ b ₂ c ₀ ] ^T
(Equation 6)
Ψ (k) = [− {yaw _eng (k−1) −Y _c (k−1)} − {yaw _eng (k−2) −Y _c (k−2)} str (k) str (k− 1) 1] ^T
By defining variables as in Equations 4 to 6, the yaw rate {y _h (k)} before zero correction is expressed as Equation 7 below.

(Equation 7)
y _h (k) = Ψ ^T (k) θ (k)
Here, when the RWLS method is applied, the coefficient vector {θ (k)} is sequentially calculated according to the following formulas 9 to 11 so as to minimize the value of the following formula 8. In Equations 9 to 11, (I) indicates a unit matrix (unit vector).

(Equation 9)
K (k) = P (k−1) Ψ (k) {λI + Ψ ^T (k) P (k−1) Ψ (k)} ⁻¹
(Equation 10)
P (k) = {I−K (k) Ψ ^T (k)} P (k−1) / λ
(Equation 11)
θ (k) = θ (k−1) + K (k) {y (k) −Ψ ^T (k) θ (k−1)}
By sequentially calculating this coefficient vector {θ (k)}, the zero point (c ₀ ) used for the zero point correction of the yaw rate detection unit 130 can be obtained.

  Next, yaw rate zero point estimation processing by the yaw rate detection apparatus 100 of the present embodiment will be described using the flowchart shown in FIG. The processing for the cases of variables (k = 1), (k = 2), and (k ≧ 3) will be described. In addition, the yaw rate zero point estimation process is repeatedly performed every predetermined time.

{In case of variable (k = 1)}
First, in step (hereinafter referred to as S) 10 in the figure, whether or not the yaw rate zero point estimation process is executed for the first time, that is, whether or not the variable (k) incremented every predetermined time is less than 2. Determine. If the determination is affirmative, the process proceeds to S20. If the determination is negative, the process proceeds to S30.

In S20, initial parameters for sequentially calculating the coefficient vector {θ (k)} using the RWLS method are set. Parameters set here include λ (for example, 0.95, 0.98, etc., close to a value of 1), P (1): a predetermined value, and Y _c (1): the ambient temperature of the yaw rate detector 130. This is the zero point of the yaw rate detection unit 130 when it is low.

In S30, the current speed {Vn (k)} of the host vehicle, the current yaw rate {yaw _eng (k)}, and the current steering angle {str (k)} are acquired. In S40, it is determined whether or not a condition for satisfying the one-input / output difference equation derived from the transfer function of the second-order lag system of Equation 3 is satisfied.

  That is, the transfer function of Formula 1 has the speed of the host vehicle as a variable, as described above. Therefore, when the vehicle travels at a constant speed, this variable can be treated as a constant. Therefore, when the vehicle travels at a constant speed, the zero point of the yaw rate detection unit 130 can be estimated without considering the speed fluctuation of the vehicle. it can.

  In addition, since the one-input / output difference equation derived from the transfer function of Formula 1 is obtained using data from the previous two times, the host vehicle has a constant speed from the previous two times to the present. In this case, the condition for satisfying the one-input / output difference equation is satisfied.

  Accordingly, in S40, if the speeds {Vn (k)}, {Vn (k-1)}, and {Vn (k-2)} of the host vehicle are substantially the same (constant speed), the process proceeds to S50. If not, the process proceeds to S70. Note that the process proceeds in S70 even when the speeds {Vn (k-1)} and {Vn (k-2)} of the host vehicle up to the past two times have not been acquired.

  In S70, coefficient vectors {θ (k)} and P (k) are replaced with coefficient vectors {θ (k−1)} and P (k−1), respectively. In the case of (k = 1), the coefficient vector {θ (1)} is set to a predetermined value that can be obtained in advance from the transfer function shown in Equation 1, and P (1) is set in S20. Set initial parameters.

In S80, the speed {Vn (1)} of the own vehicle, the yaw rate {yaw _eng (1)}, the steering angle {str (1)}, the coefficient vector {θ (1)}, and P (1) are stored. In S90, the variable (k) is incremented by 1.

{In case of variable (k = 2)}
Since a negative determination is made in S10, the process proceeds to S30. In S30, the current speed {Vn (k)} of the host vehicle, the current yaw rate {yaw _eng (k)}, and the current steering angle {str (k)} are acquired. In S40, it is determined whether or not a condition for satisfying the one-input / output difference equation derived from the transfer function of the second-order lag system of Equation 3 is satisfied. Here, since it is a variable (k = 2), the process proceeds to S70.

  In S70, coefficient vectors {θ (k)} and P (k) are replaced with coefficient vectors {θ (k−1)} and P (k−1), respectively. In the case of a variable (k = 2), the coefficient vector {θ (2)} replaces the previous coefficient vector {θ (1)}, and P (2) is also replaced with the previous P (1). .

In S80, the vehicle speed {Vn (2)}, yaw rate {yaw _eng (2)}, steering angle {str (2)}, coefficient vector {θ (2)}, and P (2) are stored. In S90, the variable (k) is incremented by 1.

{In case of variable (k ≧ 3)}
Since a negative determination is made in S10, the process proceeds to S30. In S30, the current speed {Vn (k)} of the host vehicle, the current yaw rate {yaw _eng (k)}, and the current steering angle {str (k)} are acquired.

  In S40, it is determined whether or not a condition for satisfying the one-input / output difference equation derived from the transfer function of the second-order lag system of Equation 3 is satisfied. Here, if it is a variable (k = 3) and the speed {Vn (k)} of the host vehicle is substantially the same for three consecutive times (constant speed), the process proceeds to S50.

In S50, y (k) expressed by Formula 4 and Ψ (k) expressed by Formula 6 are generated. In S60, P (3) and coefficient vector {θ (3)} are identified by the RWLS method using y (k) and Ψ (k) generated in S50. Thereby, the zero point (c ₀ ) for correcting the zero point of the yaw rate {yaw _eng (3)} included in the coefficient vector {θ (3)} is estimated.

In S80, the speed {Vn (3)} of the own vehicle, the yaw rate {yaw _eng (3)}, the steering angle {str (3)}, the coefficient vector {θ (3)}, and P (3) are stored. In S90, the variable (k) is incremented by 1. Thereafter, the above-described processing is repeated.

  As described above, the yaw rate detection apparatus 100 according to the present embodiment includes the history of the steering angle of the host vehicle detected by the steering detection unit 110, the yaw rate detected by the yaw rate detection unit 130, and the zero point history of the yaw rate detection unit 130 estimated so far. The transfer function of the yaw rate with respect to the steering angle of the host vehicle is identified (system identification). Then, the zero point of the yaw rate detection unit 130 is estimated by identifying the transfer function of the yaw rate with respect to the steering angle of the host vehicle.

  Thereby, even if the zero point drifts with the passage of time due to the ambient temperature of the yaw rate detection unit 130, or as shown in FIG. The zero point of the yaw rate can be corrected using the estimated zero point.

(Modification)
For example, in a situation where the motion of the host vehicle does not vary significantly (stable), the transfer function of the second-order lag system obtained from the equation of motion of the plane two-wheel model is approximated by the transfer function of the first-order lag system. The zero point of the yaw rate detector 130 may be estimated by identifying the transfer function of the delay system.

For example, by calculating from the one-input / output difference equation shown in Equation 12 below, it is possible to reduce the arithmetic processing required for zero point estimation. Incidentally, the identification of the coefficients in the formula _(a 1, _{b 1)} may be applied to REWLS method like this embodiment.

(Equation 12)
yaw _eng (k) = − a ₁ × {yaw _eng (k−1) −Y _c (k−1)} + {b ₁ × str (k)} + c ₀
When estimating the zero point (c ₀ ) used for the zero point correction of the yaw rate detection unit 130 based on the one-input / output difference equation derived from the transfer function of the first-order lag system, the current steering angle {str (k )}, Current and previous yaw _rates {yaw _eng (k)}, {yaw _eng (k-1)}, and previous yaw rate sensor zero {Y _c (k-1)} .

1 is a block diagram showing an overall configuration of a yaw rate detection apparatus 100 according to an embodiment of the present invention. It is a flowchart which shows the flow of the yaw rate zero point estimation process concerning embodiment of this invention. It is a figure which shows the driving | running | working condition which can estimate the zero point of a yaw rate in a prior art and this invention.

Explanation of symbols

100 Yaw Rate Detection Device 110 Steering Angle Detection Unit 120 Steering Angle History Storage Unit 130 Yaw Rate Detection Unit 140 Yaw Rate History Storage Unit 150 Yaw Rate Zero Point Estimation Unit 160 Yaw Rate Zero Point History Storage Unit

Claims (14)

Steering angle detection means for detecting the steering angle of the vehicle;
Yaw rate detection means for detecting the yaw rate of the vehicle;
Yaw rate zero point history storage means for storing a history of the zero point of the yaw rate detection means estimated by the yaw rate zero point estimation means described later;
Using the steering angle and yaw rate detected by the steering angle detection means and the yaw rate detection means, and the zero point history stored in the yaw rate zero point history storage means, a transfer function of the vehicle yaw rate with respect to the steering angle of the vehicle is obtained. A yaw rate detection device comprising: a yaw rate zero point estimation unit that estimates a zero point of the yaw rate detected by the yaw rate detection unit by identifying.   2. The yaw rate detection device according to claim 1, further comprising a zero point correction unit that corrects a zero point of the yaw rate detected by the yaw rate detection unit using the zero point estimated by the yaw rate zero point estimation unit.   The yaw rate detection device according to claim 1 or 2, wherein the yaw rate zero point estimation means estimates the zero point by identifying the transfer function of at least one of a first-order lag system and a second-order lag system. . Yaw rate history storage means for storing the history of the yaw rate detected by the yaw rate detection means,
The yaw rate zero point estimation means stores the current steering angle and yaw rate detected by the steering angle detection means and the yaw rate detection means, the history of the yaw rate stored in the yaw rate history storage means, and the yaw rate zero point history storage means. 4. The yaw rate detection apparatus according to claim 3, wherein the zero point is estimated by identifying a transfer function of the first-order lag system using a history of zero points. Steering angle history storage means for storing the history of the steering angle detected by the steering angle detection means;
Yaw rate history storage means for storing the history of the yaw rate detected by the yaw rate detection means,
The yaw rate zero point estimation means includes a current steering angle and yaw rate detected by the steering angle detection means and the yaw rate detection means, a history of steering angles stored in the steering angle history storage means, and a storage in the yaw rate history storage means. 4. The zero point is estimated by identifying the transfer function of the second-order lag system using the history of the yaw rate to be performed and the zero point history stored in the yaw rate zero point history storage means. The yaw rate detection device described. Comprising speed detecting means for detecting the speed of the vehicle;
6. The yaw rate detection device according to claim 1, wherein the yaw rate zero point estimation means estimates when the vehicle travels at a constant speed.   The yaw rate zero estimation means sequentially estimates the zero included as a coefficient of a difference equation derived from the transfer function using an exponentially weighted sequential least square method. The yaw rate detection device according to any one of 6.   Using the steering angle detection means for detecting the steering angle of the vehicle, the steering angle and yaw rate output from the yaw rate detection means for detecting the yaw rate of the vehicle, and the zero point history of the yaw rate detection means estimated so far A yaw rate zero correction method for estimating the zero point of the yaw rate detected by the yaw rate detecting means by identifying a transfer function of the yaw rate of the vehicle with respect to the steering angle of the vehicle.   9. The yaw rate zero correction method according to claim 8, wherein the yaw rate zero detected by the yaw rate detection means is corrected using the estimated zero.   10. The yaw rate zero correction method according to claim 8, wherein the zero is estimated by identifying the transfer function of at least one of a first-order lag system and a second-order lag system.   The zero point includes the current steering angle and yaw rate output from the steering angle detection unit and the yaw rate detection unit, the history of the yaw rate output from the yaw rate detection unit so far, and the yaw rate detection estimated so far. 11. The yaw rate zero point correction method according to claim 10, wherein the yaw rate zero point correction method is estimated by identifying a transfer function of the first-order lag system using a zero point history of the means.   The zero point includes the current steering angle and yaw rate output from the steering angle detection unit and the yaw rate detection unit, and the history of the steering angle and yaw rate output from the steering angle detection unit and the yaw rate detection unit so far. 11. The yaw rate zero point correction method according to claim 10, wherein the yaw rate zero point correction method is estimated by identifying the transfer function of the second-order lag system using the zero point history of the yaw rate detection means estimated so far.   The yaw rate zero correction method according to any one of claims 8 to 12, wherein the zero point is estimated when the vehicle travels at a constant speed.   The zero is included as a coefficient of a difference equation derived from the transfer function, and the zero is sequentially estimated by applying an exponentially weighted sequential least square method to the difference equation. The yaw rate zero point correction method according to any one of claims 8 to 13, wherein the yaw rate zero point correction method is provided.

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