JP2013132938A - Stability factor estimation device for vehicle - Google Patents

Abstract

PROBLEM TO BE SOLVED: To estimate a stability factor for a vehicle.SOLUTION: The weight W of a vehicle is estimated by using the index value of deviation, between a transient yaw rate γtr of the vehicle set in the relationship of a primary delay with respect to a norm yaw rate γt of the vehicle and a real yaw rate γ of the vehicle, as a yaw rate deviation index value Δδ, and a correction gain Kgw is calculated based on the absolute value of the acceleration and deceleration Gy of the vehicle and the weight W of the vehicle (S75). The stability factor Kh of the vehicle is estimated based on a relationship between the integrated value Gay of the lateral acceleration of the vehicle, from which components of a first predetermined frequency or lower have been removed, and the integrated value Δδa of a yaw rate deviation index value, from which components of a second predetermined frequency or lower have been removed and which has been multiplied with the correction gain Kgw (S70 to S150).

Description

  The present invention relates to an apparatus for estimating the stability factor of a vehicle, and more specifically, estimates the stability factor of a vehicle based on the relationship between the deviation between a reference yaw rate and a transient yaw rate when the vehicle turns and the lateral acceleration of the vehicle. Related to the device.

  2. Description of the Related Art A stability factor estimation device that estimates the stability factor of a vehicle used for vehicle motion control is already known. For example, in Patent Document 1 below, the vehicle stability factor is calculated based on the relationship between the vehicle's lateral yaw rate and the deviation between the vehicle's transient yaw rate and the vehicle's actual yaw rate that are in a first order lag relationship with the vehicle's standard yaw rate. An apparatus for estimation is described. In particular, in the apparatus described in Patent Document 1, the lateral acceleration of the vehicle from which the component below the first predetermined frequency is removed and the yaw rate deviation index value from which the component below the second predetermined frequency is removed. A vehicle stability factor is estimated based on the relationship.

International Publication No. 2011/0336820

[Problems to be Solved by the Invention]
The actual stability factor of the vehicle is a function of the cornering power of the front and rear wheels, the position of the center of gravity of the vehicle, and the weight of the vehicle. The cornering power of the front and rear wheels and the position of the center of gravity of the vehicle vary depending on the forward / backward movement of the load accompanying the acceleration / deceleration of the vehicle. Therefore, the actual stability factor of the vehicle becomes a different value when the acceleration / deceleration of the vehicle is large than when the acceleration / deceleration of the vehicle is small.

  Further, in a vehicle or a freight vehicle with a large number of passengers, the weight of the vehicle and the position of the center of gravity of the vehicle change with changes in the number of passengers and loading conditions. Therefore, the actual stability factor of the vehicle becomes a different value when the number of occupants and the load capacity are large than when the number of occupants and the load capacity are small.

  However, in the conventional stability factor estimation device as described in the above-mentioned Patent Document 1, the stability of the vehicle in the standard state, that is, the case where the vehicle is the standard weight and the vehicle turns without acceleration / deceleration. Factor estimation has been optimized. In other words, the stability factor of the vehicle is estimated without considering the forward / backward movement of the load accompanying the acceleration / deceleration of the vehicle or the size of the vehicle weight. Therefore, there is a problem that the accuracy of estimating the stability factor is not high in a situation where the acceleration / deceleration of the vehicle is large or in a situation where the vehicle weight is significantly different from the standard weight.

A main object of the present invention is to provide a stability factor estimation device for a vehicle so that the accuracy of estimating the stability factor is improved in a situation where the acceleration / deceleration of the vehicle is large or the weight of the vehicle is significantly different from the standard weight. Is to improve.
[Means for Solving the Problems and Effects of the Invention]

  According to the present invention, an index value of a deviation between the transient yaw rate of the vehicle and the actual yaw rate of the vehicle that is in a first-order lag relationship with the reference yaw rate of the vehicle is used as the yaw rate deviation index value, and components below the first predetermined frequency are removed. In a vehicle turning characteristic estimation device for estimating a vehicle stability factor based on a relationship between a lateral acceleration of a vehicle and a yaw rate deviation index value from which a component equal to or lower than a second predetermined frequency is removed, A correction gain is calculated based on at least one of acceleration / deceleration and vehicle weight, the lateral acceleration of the vehicle from which the component below the first predetermined frequency is removed, and the component below the second predetermined frequency is removed and the correction is performed. A vehicle stability factor estimator characterized by estimating a vehicle stability factor based on a relationship with a yaw rate deviation index value multiplied by a gain. There is provided.

  According to this configuration, the correction gain is calculated based on at least one of the acceleration / deceleration of the vehicle and the weight of the vehicle, and the yaw rate deviation index value is removed from the second predetermined frequency component and multiplied by the correction gain. . Therefore, the stability factor of the vehicle is estimated based on the relationship between the yaw rate deviation index value corrected by multiplication of the correction gain and the lateral acceleration of the vehicle from which the component equal to or lower than the first predetermined frequency is removed. Therefore, the stability factor estimation accuracy can be improved in situations where the acceleration / deceleration of the vehicle is large or the vehicle weight is significantly different from the standard weight, as compared with the conventional stability factor estimation device. it can.

  In the above configuration, the lateral acceleration and yaw rate deviation index values of the vehicle are acquired over a plurality of times, and the integrated value of the lateral acceleration of the vehicle from which components below the first predetermined frequency are removed, and the second predetermined frequency or less. The stability factor of the vehicle may be estimated based on the relationship with the integrated value of the yaw rate deviation index value multiplied by the correction gain.

  According to this configuration, it is possible to obtain the relationship between the lateral acceleration of the vehicle and the yaw rate deviation index value regardless of the phase difference between the lateral acceleration of the vehicle and the yaw rate deviation index value. Therefore, compared with the case where the stability factor of the vehicle is estimated based on the relationship between the lateral acceleration of the vehicle and the yaw rate deviation index value, the vehicle's lateral acceleration and the phase difference between the yaw rate deviation index value are not affected. The stability factor can be estimated with high accuracy.

  In the above configuration, the first adjustment gain corresponding to the degree of change in the estimated stability factor value is calculated, and the value obtained by multiplying the previous integrated value of the lateral acceleration of the vehicle by the first adjustment gain is obtained this time. The sum of the lateral acceleration of the vehicle thus obtained is used as the integrated value of the lateral acceleration of the current vehicle, and the value obtained by multiplying the previous integrated value of the yaw rate deviation index value by the first adjustment gain is multiplied by the correction gain obtained this time. The sum of the current yaw rate deviation index value is the integrated value of the current yaw rate deviation index value, and the vehicle stability factor is based on the relationship between the current lateral acceleration integrated value and the current yaw rate deviation index value integrated value. May be estimated.

  According to this configuration, it is possible to appropriately calculate the integrated value of the lateral acceleration of the vehicle and the integrated value of the yaw rate deviation index value according to the degree of change in the estimated value of the stability factor. Therefore, compared to the case where the first adjustment gain according to the degree of change in the estimated value of stability factor is not calculated, the stability factor of the vehicle is increased even in a situation where the degree of change in estimated value of stability factor is high. The accuracy can be estimated.

  In the above configuration, the yaw rate deviation index value may be a value obtained by converting the deviation between the transient yaw rate of the vehicle and the actual yaw rate of the vehicle into the deviation of the steering angle of the front wheels.

  As will be described in detail later, the deviation between the transient yaw rate of the vehicle and the actual yaw rate of the vehicle depends on the vehicle speed, but the value obtained by converting the deviation between the transient yaw rate of the vehicle and the actual yaw rate of the vehicle into the deviation of the steering angle of the front wheels is It does not depend on the vehicle speed. The deviation of the steering angle of the front wheels is a difference between the steering angle of the front wheels and the actual steering angle of the front wheels for achieving the transient yaw rate of the vehicle.

  Therefore, according to the above configuration, the estimated value of the stability factor can be obtained based on the yaw rate deviation index value that does not depend on the vehicle speed, and thereby the stability factor of the vehicle can be estimated without being affected by the vehicle speed. . Further, it is possible to eliminate the necessity of estimating the vehicle stability factor for each vehicle speed.

  In the two-wheel model of the vehicle shown in FIG. 10, the mass and yaw moment of the vehicle are M and I, respectively, and the distances between the center of gravity 102 of the vehicle and the front and rear axles are Lf and Lr, respectively. The wheel base of the vehicle is L (= Lf + Lr). Further, the cornering forces of the front wheel 100f and the rear wheel 100r are Ff and Fr, respectively, and the cornering powers of the front wheel and the rear wheel are Kf and Kr, respectively. The actual steering angle of the front wheel 100f is δ, the slip angles of the front and rear wheels are βf and βr, respectively, and the slip angle of the vehicle body is β. Further, the lateral acceleration of the vehicle is Gy, the vehicle yaw rate is γ, the vehicle speed is V, and the vehicle yaw angular velocity (differential value of the yaw rate γ) is γd. The following formulas 1 to 6 are established depending on the balance of the force and moment of the vehicle.

MGy = Ff + Fr (1)
Iγd = LfFf−LrFr (2)
Ff = −Kfβf (3)
Fr = −Krβr (4)
βf = β + (Lf / V) γ−δ (5)
βr = β− (Lr / V) γ (6)

From the above equations 1 to 6, the following equation 7 is established.

Assuming that the vehicle speed V is substantially constant, the Laplace operator is converted to Laplace using the Laplace operator as s, and the following equations 8 to 10 are established by arranging the yaw rate γ. A normative yaw rate γ (s) is required.

Kh in the above equation 9 is a stability factor, and Tp in the above equation 10 is a coefficient relating to the vehicle speed V of the first-order lag system having a time constant depending on the vehicle speed, that is, the “steering response time constant coefficient” in this specification. It is a coefficient to call. These values are parameters that characterize the steering response related to the yaw motion of the vehicle, and indicate the turning characteristics of the vehicle. The above equation 8 is an equation for calculating the yaw rate γ of the vehicle from the actual steering angle δ of the front wheels, the vehicle speed V, and the lateral acceleration Gy. Assuming that the yaw rate calculated from this linearized model is the transient yaw rate γtr, the transient yaw rate γtr is a value of a first-order lag with respect to the steady standard yaw rate γt expressed by the following equation 11.

Therefore, in the above configuration, the transient yaw rate γtr may be calculated according to the following equation 12 corresponding to the above equation 8.

The deviation Δγt between the steady normative yaw rate γt and the detected yaw rate γ during steady turning of the vehicle is expressed by the following equation 13 where the design value and true value of the stability factor are Khde and Khre, respectively.

When the yaw rate deviation Δγt is converted into the steering wheel deviation Δδt by multiplying both sides of the above expression 13 by L / V, the steering wheel deviation Δδt of the front wheel is expressed by the following expression 14. This deviation Δδt of the steering angle of the front wheels is one of index values of deviation between the steady standard yaw rate γt and the detected yaw rate γ, and does not depend on the vehicle speed.
Δδt = (Khre−Khde) GyL (14)

  Therefore, the deviation Δδt of the steering angle of the front wheels can be calculated according to Equation 14 as an index value of the deviation between the steady normative yaw rate and the actual yaw rate γ.

From Equation 14, the relationship between the lateral acceleration Gy and the front wheel rudder angle deviation Δδt, in other words, the gradient (Khre-Khde) L of the relationship between the lateral acceleration Gy and the front wheel rudder angle deviation Δδt in the orthogonal coordinate system. It can be understood that the stability factor estimated value Khp can be obtained according to the following equation 15 by obtaining the value by least square method or the like.
Khp = Khde + gradient / L (15)

Also, if the sensor zero point offset errors for the vehicle yaw rate γ, lateral acceleration Gy, and front wheel steering angle δ are γ0, Gy0, and δ0, respectively, the detected values of the vehicle yaw rate, lateral acceleration, and front wheel steering angle are γ + γ0, Gy + Gy0 and δ + δ0. Therefore, the deviation Δγt between the steady reference yaw rate γt and the detected yaw rate at the time of steady turning of the vehicle is expressed by the following equation (16).

When the yaw rate deviation Δγt is converted into the steering wheel deviation Δδt by multiplying both sides of the above equation 16 by L / V, the steering wheel deviation Δδt of the front wheel is expressed by the following equation 17. The relationship between the lateral acceleration Gy of the vehicle and the deviation Δδt of the steering angle of the front wheels expressed by the following equation 17 is as shown in FIG.

  In Expression 17, δ0−KhdeGy0L is a constant, but γ0L / V changes according to the vehicle speed V. Therefore, the intercept of the vertical axis of the graph shown in FIG. Therefore, when the detected value of the yaw rate γ of the vehicle includes an error of the sensor zero offset, the relationship of the deviation Δδt of the steering angle of the front wheels to the lateral acceleration Gy changes depending on the vehicle speed, so the stability factor is accurately set. Cannot be estimated.

  Further, in order to increase the stability factor estimation accuracy, it is necessary to take measures such as estimating the stability factor for each vehicle speed. Therefore, there is a problem that the data such as the yaw rate γ necessary for the stability factor estimation becomes enormous, the calculation load of the turning characteristic estimation device becomes excessive, and it takes a long time to estimate the stability factor.

Here, the lateral acceleration of the vehicle from which the component below the first predetermined frequency is removed is Gyft, and the deviation of the steering angle of the front wheel from which the component below the second predetermined frequency is removed is Δδtft. If the first and second predetermined frequencies are sufficiently higher than the change speed of γ0 L / V accompanying the change in the vehicle speed V, the error Gy0 is not included in Gyft, and the errors γ0, δ0 are also included in Δδtft. The error due to is not included. Therefore, the following expression 18 corresponding to the above expression 14 is established. The relationship between the lateral acceleration Gyft of the vehicle expressed by the following equation 18 and the deviation Δδtft of the steering angle of the front wheels is as shown in FIG. 12, and the straight line of equation 18 passes through the origin regardless of the vehicle speed V.
Δδtft = (Khre−Khde) GyftL (18)

  Therefore, the relationship between the lateral acceleration Gyft and the deviation Δδtft of the front wheel rudder angle, in other words, the gradient (Khre−Khde) L of the relationship between the lateral acceleration Gyft and the front wheel rudder angle deviation Δδtft in the orthogonal coordinate system is obtained. By determining the estimated value Khp of the stability factor according to the above equation 15, the estimated value Khp of the stability factor can be determined without being affected by the error of the zero offset of the sensor.

  Accordingly, in the above configuration, the estimated value of the stability factor may be calculated according to the above equation 15 by using the ratio of the deviation Δδtft of the front wheel steering angle to the lateral acceleration Gyft as a gradient.

  13 to 15 are graphs showing the time series waveform X, the time series waveform Y, and the Lissajous waveform of X and Y. FIG. In particular, FIG. 13 shows the case where there is no phase difference between the two time series waveforms X and Y, FIG. 14 shows the case where the phase of the time series waveform Y is delayed from the phase of the time series waveform X, and FIG. The case where the phase of the series waveform Y is ahead of the phase of the time series waveform X is shown. In particular, in FIGS. 14 and 15, a thick alternate long and short dash line indicates a Lissajous waveform of the integrated value of X and the integrated value of Y.

  From FIG. 13 to FIG. 15, according to the ratio of the integrated value of Y to the integrated value of X, even when there is a phase difference between the two time series waveforms X and Y, the influence is reduced to obtain the ratio Y / X. I understand that I can do it.

  Therefore, in the above configuration, the estimated value of the stability factor may be calculated according to the above equation 15 using the ratio of the integrated value Δδtfta of the steering wheel deviation Δδtft to the integrated value Gyfta of the lateral acceleration Gyft as a gradient.

  In the above description, the case of steady turning of the vehicle has been described. However, in the case of transient turning of the vehicle, first-order lag filter processing is performed on the steering wheel deviation Δδtft and its integrated value Δδtfta, and the lateral acceleration Gyft A first-order lag filtering process is performed on the integrated value Gyfta. In this case, by making the time constant of the first-order lag filtering process the same, the gradient is calculated in the same manner as in the case of steady turning of the vehicle based on the value after the first-order lag filtering process, Can be calculated.

  In the above configuration, the vehicle weight may be estimated based on the relationship between the driver's acceleration / deceleration operation amount and the vehicle acceleration / deceleration.

  In the above configuration, the correction gain is 1 when the absolute value of the longitudinal acceleration of the vehicle is less than the reference value and the weight of the vehicle is less than the reference value, and the absolute value of the longitudinal acceleration of the vehicle is greater than the reference value. When it is large or when the weight of the vehicle is larger than the reference value, the value is larger than 1, and it may be larger as the absolute value of the longitudinal acceleration of the vehicle or the weight of the vehicle is larger.

  Further, in the above configuration, the component below the first predetermined frequency may be removed from the lateral acceleration of the vehicle by the high-pass filter processing, and the component below the second predetermined frequency may be removed from the yaw rate deviation index value by the high-pass filter processing. .

  In the above configuration, the first and second predetermined frequencies may be the same frequency.

  In the above configuration, the vehicle speed is set to V, the vehicle wheelbase is set to L, and the deviation between the vehicle's transient yaw rate and the vehicle's actual yaw rate is multiplied by L / V. A value obtained by converting the deviation from the actual yaw rate into the deviation of the steering angle of the front wheels may be calculated.

It is a schematic block diagram which shows one Embodiment of the stability factor estimation apparatus by this invention applied to the vehicle motion control apparatus. It is a flowchart which shows the estimation calculation routine of the stability factor Kh in embodiment. It is a graph which shows the relationship between the absolute value of the longitudinal acceleration Gx of a vehicle, the weight W of a vehicle, and the correction gain Kgw. It is a graph which shows the relationship between the convergence degree Ckh of the estimated value of a stability factor, and the reference value (gamma) 0. It is a flowchart which shows the principal part of the estimation calculation routine of the stability factor Kh in a 1st modification. It is a graph which shows the relationship between the steering frequency fs and the cutoff frequency fhc of a high-pass filter process. It is a flowchart which shows the principal part of the estimation calculation routine of the stability factor Kh in a 2nd modification. It is a graph which shows the relationship between the steering frequency fs, the cutoff frequency fhc of a high-pass filter process, and the absolute value of the longitudinal acceleration Gx of a vehicle. It is a flowchart which shows the principal part of the estimation calculation routine of the stability factor Kh in a 3rd modification. It is explanatory drawing which shows the two-wheel model of the vehicle for estimating a stability factor. It is a graph which shows the relationship between lateral acceleration Gy of a vehicle, and deviation (delta) t of the steering angle of a front wheel. It is a graph which shows the relationship between lateral acceleration Gyft of the vehicle from which the component below the 1st predetermined frequency was removed, and deviation (delta) tft of the steering angle of the front wheel from which the component below the 2nd predetermined frequency was removed. It is a graph which shows the Lissajous waveform of two time series waveforms X and Y, and X and Y about the case where there is no phase difference in two time series waveforms X and Y. 7 is a graph showing two time series waveforms X, Y and a Lissajous waveform of X and Y when the phase of the time series waveform Y is delayed from the phase of the time series waveform X. 6 is a graph showing two time-series waveforms X, Y, and a Lissajous waveform of X and Y when the phase of the time-series waveform Y is ahead of the phase of the time-series waveform X. It is a graph which shows the relationship between the absolute value of the longitudinal acceleration Gx of a vehicle, and correction | amendment gain Kg. It is a graph which shows the relationship between the weight W of a vehicle, and the correction | amendment gain Kw.

  Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

  FIG. 1 is a schematic configuration diagram showing an embodiment of a stability factor estimation device according to the present invention applied to a vehicle motion control device.

  In FIG. 1, reference numeral 50 denotes an overall motion control device for the vehicle 10, and the yaw rate estimation device according to the present invention forms part of the motion control device 50. The vehicle 10 has left and right front wheels 12FL and 12FR and left and right rear wheels 12RL and 12RR. The left and right front wheels 12FL and 12FR, which are steered wheels, are steered via tie rods 18L and 18R by a rack and pinion type power steering device 16 that is driven in response to steering of the steering wheel 14 by the driver.

  The braking force of each wheel is controlled by controlling the braking pressure of the wheel cylinders 24FR, 24FL, 24RR, 24RL by the hydraulic circuit 22 of the braking device 20. Although not shown in the drawing, the hydraulic circuit 22 includes an oil reservoir, an oil pump, various valve devices, and the like, and the braking pressure of each wheel cylinder is normally driven according to the depression operation of the brake pedal 26 by the driver. It is controlled by the master cylinder 28 and, if necessary, is controlled by the electronic control unit 30 as described later.

  The master cylinder 28 is provided with a pressure sensor 32 for detecting the master cylinder pressure Pm, that is, the pressure in the master cylinder, and the steering column connected with the steering wheel 14 is provided with a steering angle sensor 34 for detecting the steering angle θ. ing. A signal indicating the master cylinder pressure Pm detected by the pressure sensor 32 and a signal indicating the steering angle θ detected by the steering angle sensor 34 are input to the electronic control unit 30.

  The vehicle 10 includes a yaw rate sensor 36 for detecting the actual yaw rate γ of the vehicle, a longitudinal acceleration sensor 38 for detecting the longitudinal acceleration Gx of the vehicle, a lateral acceleration sensor 40 for detecting the lateral acceleration Gy of the vehicle, and a vehicle speed for detecting the vehicle speed V. 42 is provided. A signal indicating the actual yaw rate γ detected by the yaw rate sensor 36 is also input to the electronic control unit 30. The steering angle sensor 34, the yaw rate sensor 36, and the lateral acceleration sensor 40 detect the steering angle, the actual yaw rate, and the lateral acceleration, respectively, with the left turning direction of the vehicle being positive.

  Although not shown in detail in the figure, the electronic control unit 30 includes, for example, a CPU, a ROM, an EEPROM, a RAM, a buffer memory, and an input / output port device, which are connected to each other by a bidirectional common bus. Includes a microcomputer with a general configuration. The ROM stores a stability factor Kh used for calculating the reference yaw rate γt and default values Kh00 and Tp00 of the steering response time constant coefficient Tp. These default values are set for each vehicle when the vehicle is shipped. The EEPROM stores an estimated value of the stability factor Kh, etc., and the estimated value of the stability factor Kh is calculated based on the running data of the vehicle when the vehicle is turning as will be described in detail later. Updated as appropriate.

  As shown in FIG. 1, a signal indicating the accelerator opening Acc is input to the engine control device 44 from an accelerator opening sensor 48 provided on the accelerator pedal 46. The engine control device 44 controls the output of the engine (not shown) based on the accelerator opening degree Acc, and exchanges signals with the electronic control device 30 as necessary. The engine control device 44 may also be constituted by a single microcomputer including a CPU, a ROM, a RAM, an input / output port device and a drive circuit, for example.

  When the vehicle starts turning according to the flowchart shown in FIG. 2 as described later, the electronic control unit 30 calculates a steady reference yaw rate γt based on turning traveling data such as a steering angle. The electronic control unit 30 calculates a primary yaw transient yaw rate γtr by performing a first-order lag filter operation using the steering response time constant coefficient Tp with respect to the steady standard yaw rate γt. Further, the electronic control unit 30 calculates a front wheel rudder angle deviation conversion value Δδ of the yaw rate deviation obtained by replacing the deviation γtr−γ between the transient yaw rate γtr and the actual yaw rate γ of the vehicle with the deviation of the rudder angle of the front wheels.

  Particularly in this embodiment, the electronic control unit 30 estimates the weight W of the vehicle and calculates a correction gain Kgw based on the absolute value of the longitudinal acceleration Gx of the vehicle and the weight W of the vehicle. The electronic control unit 30 calculates the front wheel steering angle deviation converted value Δδ of the yaw rate deviation as the product of the yaw rate deviation γtr-γ, L / V, and the correction gain Kgw.

  Further, the electronic control unit 30 calculates the lateral acceleration Gyft of the vehicle after the first-order delay filtering process by performing a first-order delay filter operation with the steering response time constant coefficient Tp on the lateral acceleration Gy of the vehicle. The electronic control unit 30 then calculates the vehicle lateral acceleration Gyftbpf and yaw rate deviation front wheel steering angle deviation converted value Δδbpf after the bandpass filter processing based on the vehicle lateral acceleration Gyft and the yaw rate deviation front wheel steering angle deviation converted value Δδ. To do.

  Further, the electronic control unit 30 calculates the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle, and calculates the ratio Δδa / ΔGya of the integrated values. Further, the electronic control unit 30 calculates the estimated value of the stability factor Kh as the sum of the initial value of the stability factor Kh used for the calculation of the steady-state normative yaw rate γt and the correction amount based on the ratio Δδa / ΔGya of the integrated values. To do. The electronic control unit 30 stores the estimated value of the stability factor Kh in the EEPROM when a preset condition is satisfied.

  Further, the electronic control unit 30 calculates a target yaw rate γtt corresponding to the transient yaw rate γtr using the motion control stability factor Khd stored in the EEPROM, and calculates the deviation between the yaw rate detection value γ and the target yaw rate γtt. The yaw rate deviation Δγ is calculated. Then, the electronic control unit 30 determines whether or not the turning behavior of the vehicle has deteriorated by determining whether or not the magnitude of the yaw rate deviation Δγ exceeds the reference value γo (positive value). When the behavior is deteriorated, the movement of the vehicle is controlled so that the turning behavior of the vehicle is stabilized. The vehicle motion control performed by the electronic control unit 30 is an arbitrary control as long as the vehicle motion is controlled based on the target yaw rate γtt calculated using the stability factor Khd for motion control. Good.

  Further, the electronic control unit 30 calculates the convergence degree Ckh of the estimated value of the stability factor Kh. The electronic control unit 30 variably sets the reference value γo based on the degree of convergence Ckh, thereby variably setting the dead zone of the vehicle motion control.

  Next, the routine for estimating the stability factor Kh in the embodiment will be described with reference to the flowchart shown in FIG. The control according to the flowchart shown in FIG. 2 is started by closing an ignition switch not shown in the figure, and is repeatedly executed at predetermined time intervals.

  First, control is started from step 10. In step 10, the latest value updated in step 190 during the previous run is set as the initial value Kh0 of the stability factor Kh. Initialization is performed. When there is no stored value of stability factor Kh in the EEPROM, default value Kh00 preset at the time of shipment of the vehicle is set as initial value Kh0 of stability factor Kh.

  In step 20, a signal indicating the steering angle .theta. Detected by each sensor is read. In step 30, high frequency noise is removed from the steering angle .theta. Read in step 20. Therefore, a low-pass filter process is performed. The low-pass filter process in this case may be a primary low-pass filter process with a cutoff frequency of 3.4 Hz, for example.

  In step 40, the vehicle speed V is calculated based on the wheel speed Vwi, the steering angle δ of the front wheel is calculated based on the steering angle θ, and the steady standard yaw rate γt is calculated according to the above equation 11.

  In step 50, the steering response time constant coefficient Tp is set to a default value Tp00 that is preset at the time of shipment of the vehicle. When the steering response time constant coefficient Tp is estimated based on the travel data of the vehicle, the steering response time constant coefficient Tp may be set to the estimated value.

  In step 60, a transient yaw rate γtr based on the reference yaw rate γt calculated in step 40 is calculated by performing a first-order lag filter calculation using the steering response time constant coefficient Tp in accordance with the above equation 12.

In step 70, a first-order lag filter operation is performed on the lateral acceleration Gy of the vehicle by the steering response time constant coefficient Tp according to the following equation 19, thereby calculating the lateral acceleration Gyft of the vehicle after the first-order lag filter processing. Is done.

  In step 75, the estimated longitudinal acceleration Gxh of the vehicle is calculated based on the master cylinder pressure Pm indicating the amount of braking operation of the driver during braking, and based on the accelerator opening Acc indicating the amount of driving operation of the driver during driving. An estimated longitudinal acceleration Gxh of the vehicle is calculated. Then, based on the deviation between the estimated longitudinal acceleration Gxh and the longitudinal acceleration Gx detected by the longitudinal acceleration sensor 38, the weight W of the vehicle is estimated.

  In step 75, the correction gain Kgw is calculated from the map corresponding to the graph shown in FIG. 3 based on the absolute value of the longitudinal acceleration Gx of the vehicle and the weight W of the vehicle. In this case, the correction gain Kgw is 1 when the absolute value of the longitudinal acceleration Gx of the vehicle is not more than the reference value Gx0 (positive constant) and the weight W of the vehicle is not more than the reference value W0 (positive constant). On the other hand, the correction gain Kgw is a value larger than 1 when the absolute value of the longitudinal acceleration Gx of the vehicle is larger than the reference value Gx0 or when the weight W of the vehicle is larger than the reference value W0. The correction gain Kgw increases as the absolute value of the longitudinal acceleration Gx of the vehicle or the weight W of the vehicle increases.

In step 80, the front wheel rudder angle deviation conversion value Δδ of the yaw rate deviation obtained by replacing the product of the deviation between the transient yaw rate γtr and the actual yaw rate γ and the correction gain Kgw with the deviation of the rudder angle of the front wheels is calculated according to the following equation 20. Is done.

  In step 90, the zero point of the sensor is calculated with respect to the lateral acceleration Gyft of the vehicle after the first-order lag filtering process calculated in step 70 and the front wheel steering angle deviation conversion value Δδ of the yaw rate deviation calculated in step 80. A high-pass filter process for removing the influence of the offset is performed. The high-pass filter process in this case may be a primary high-pass filter process with a cutoff frequency of 0.2 Hz, for example.

  As described above, since the low-pass filter process is performed in step 30, the front wheel steering angle deviation converted value Δδ of the lateral acceleration Gyft and yaw rate deviation of the vehicle after the first-order lag filter process is performed by performing the high-pass filter process. The same result as that obtained when the band pass filter processing is performed is obtained. Therefore, the vehicle front acceleration Gyft and yaw rate deviation converted into the front wheel steering angle deviation Δδ subjected to the high-pass filter processing in step 90 are respectively converted into the vehicle front acceleration Gyftbpf and yaw rate deviation front wheel steering angle deviation converted values after the band pass filter processing. Expressed as Δδbpf.

  In step 100, it is determined whether or not the vehicle is in a turning state. If a negative determination is made, control returns to step 20, and if an affirmative determination is made, control proceeds to step 110. In this case, whether or not the vehicle is turning is determined whether or not the absolute value of the lateral acceleration Gy of the vehicle is greater than or equal to the reference value in a situation where the vehicle is traveling at a vehicle speed greater than or equal to the reference value. The determination is made by determining whether the absolute value of the actual yaw rate γ of the vehicle is greater than or equal to a reference value and whether the absolute value of the product of the yaw rate γ of the vehicle and the vehicle speed V is greater than or equal to the reference value. Good.

  In step 110, the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation after the current bandpass filter processing calculated in step 130 of the previous cycle and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle are obtained. A determination is made as to whether adjustment is necessary. When a negative determination is made, control proceeds to step 130, and when an affirmative determination is made, control proceeds to step 120.

In this case, when the following (A1) or (A2) is established, it may be determined that the integrated values Δδa and ΔGya need to be adjusted. (A2) is a determination condition when the steering response time constant coefficient Tp is estimated and the steering response time constant coefficient Tp is set to the estimated value in step 50.
(A1) The absolute value of the deviation ΔKh between the stability factor Kh when the integrated values Δδa and ΔGya were adjusted last time and the current stability factor Kh estimated in step 150 of the previous cycle is the stability factor. The standard value for deviation is exceeded.
(A2) The absolute value of the deviation ΔTp between the steering response time constant coefficient Tp when the integrated values Δδa and ΔGya were adjusted last time and the current steering response time constant coefficient Tp set in step 50 of the current cycle is The reference value for deviation of the steering response time constant coefficient is exceeded.

In step 120, the preset lower limit value of the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation after the bandpass filter processing is set to Δδamin (positive constant), and the vehicle after the bandpass filter processing is processed. The adjustment gain Gaj is calculated according to the following equation 21 with the preset lower limit value of the integrated value ΔGya of the lateral acceleration Gyftbpf as ΔGyamin (positive constant). In the following equation 21, MIN means that the minimum value in the parentheses is selected, and MAX means that the maximum value in the parentheses is selected.

In step 120, the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the adjusted yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle are calculated according to the following equations 22 and 23.
Δδa = current Δδa × Gaj (22)
ΔGya = Current ΔGya × Gaj (23)

In step 130, when the lateral acceleration Gyftbpf of the vehicle is a positive value, the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle are respectively expressed by the following Expression 24 and Is calculated according to 25.
Δδa = current Δδa + Δδbpf (24)
ΔGya = Current ΔGya + Gyftbpf (25)

When the lateral acceleration Gyftbpf of the vehicle is not a positive value, the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle are calculated according to the following equations 26 and 27, respectively. .
Δδa = current Δδa−Δδbpf (26)
ΔGya = Current ΔGya-Gyftbpf (27)

  In step 140, the integrated value ratio Δδa / ΔGya is calculated by dividing the integrated value Δδa of the yaw rate deviation converted into the front wheel steering angle deviation Δδbpf by the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle.

In step 150, the estimated value of the stability factor Kh is calculated according to the following equation 28 in which the design value Khde of the stability factor in the equation 15 is the initial value Kh0 of the stability factor.
Kh = Kh0 + (Δδa / ΔGya) / L (28)

In step 160, the first-order low-pass filter processing is performed on the estimated value of the stability factor Kh according to the following equation 29 with Tc as a cutoff frequency of 0.05 Hz, for example, so that the stability factor after the low-pass filter processing is performed. An estimated value Khlpf of Kh is calculated.

In step 160, the first-order low-pass filter processing is performed on the absolute value of the deviation between the estimated value of the stability factor Kh and the estimated value Khlpf of the stability factor Kh after the low-pass filter processing according to Equation 30 below. Thus, the deviation ΔKhlpf of the estimated value of the stability factor Kh after the low-pass filter processing is calculated. Then, the convergence degree Ckh of the estimated value of the stability factor Kh is calculated as the reciprocal 1 / ΔKhlpf of the deviation ΔKhlpf.

  In step 170, a vehicle motion control reference value γo based on the deviation Δγ between the yaw rate detection value γ and the target yaw rate γtt is calculated based on the convergence degree Ckh of the stability factor estimated value based on FIG. Thereby, the dead zone of the vehicle motion control is variably set.

  In step 180, by determining whether or not the convergence degree Ckh of the estimated value of the stability factor exceeds the reference value (positive value) of the memory determination, the estimated value of the stability factor Kh is stored in the EEPROM. A determination is made whether the situation is allowed. When a negative determination is made, the control returns to step 20, and when an affirmative determination is made, the estimated value of the stability factor Kh is stored in the EEPROM in step 190, and thereby the stability factor stored in the EEPROM. The estimated value of Kh is updated.

  In the operation of the embodiment configured as described above, the steady standard yaw rate γt is calculated in step 40, and the transient yaw rate γtr is calculated based on the steady standard yaw rate γt in step 60. Further, in step 70, the lateral acceleration Gyft of the vehicle after the first-order lag filtering is calculated, and in step 80, the deviation between the transient yaw rate γtr and the actual yaw rate γ is replaced with the deviation of the steering angle of the front wheels. The front wheel rudder angle deviation converted value Δδ is calculated.

  In step 90, a high-pass filter process is performed on the vehicle lateral acceleration Gyft and the front wheel steering angle deviation converted value Δδ of the yaw rate deviation, thereby calculating the actual yaw rate γbpf after the band-pass filter process. The front wheel rudder angle of the yaw rate deviation index value after the band pass filter processing is obtained as a value obtained by replacing the magnitude of the deviation between the actual yaw rate γbpf after the band pass filter processing and the transient yaw rate γ trbpf with the magnitude of the steering wheel deviation of the front wheels. A deviation converted value Δδbpf is calculated.

  In step 130, the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle are calculated. Also, in step 140, the integrated value ratio Δδa / ΔGya is calculated by dividing the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation by the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle.

  Further, in step 150, the estimated value of the stability factor Kh is obtained as the sum of the initial value Kh0 of the stability factor Kh used for the calculation of the steady-state standard yaw rate γt and the correction amount based on the ratio Δδa / ΔGya of the integrated values. Calculated.

  Thus, according to the above-described embodiment, the initial value of the stability factor used for the calculation of the steady-state standard yaw rate γt of the vehicle is set to the deviation of the yaw rate and the lateral acceleration of the vehicle so that the transient yaw rate γtr of the vehicle approaches the true yaw rate. The estimated value of the stability factor Kh can be calculated as a value corrected based on the relationship. Therefore, the estimated value of the stability factor is corrected so that the estimated value of the stability factor approaches the true stability factor, and thereby the estimated value of the stability factor can be obtained as a value close to the true stability factor.

  In particular, according to the above-described embodiment, in step 75, when the absolute value of the longitudinal acceleration Gx of the vehicle is large, the correction gain Kgw is calculated to be larger than when the absolute value of the longitudinal acceleration Gx is small. In step 80, the front wheel rudder of the yaw rate deviation replaced with the deviation of the rudder angle of the front wheel as the product of the deviation γtr-γ of the transient yaw rate γtr and the actual yaw rate γ, L / V, and the correction gain Kgw according to the equation (20). An angular deviation converted value Δδ is calculated.

  Therefore, compared to the conventional yaw rate estimation device in which the front wheel steering angle deviation converted value Δδ of the yaw rate deviation is calculated as the product of the yaw rate deviation γtr−γ and L / V, the load movement in the longitudinal direction of the vehicle is reduced. The front wheel steering angle deviation converted value Δδ can be calculated so that the influence is reflected. By using the front wheel rudder angle deviation conversion value Δδ, the vehicle stability factor Kh can be calculated to be more accurate than the conventional value in steps 130 to 150.

  According to the above-described embodiment, the vehicle weight W is estimated in step 75, and the correction gain Kgw is calculated to be larger when the vehicle weight W is larger than when the vehicle weight W is small. . Therefore, the correction gain Kgw can be increased when the weight W of the vehicle is large and the influence of load movement in the longitudinal direction of the vehicle is large. Therefore, compared with the case where the weight W of the vehicle is not taken into account, the front wheel rudder angle deviation converted value Δδ is calculated so that the influence of the load movement in the front-rear direction of the vehicle is effectively reflected, thereby further increasing the stability factor Kh. A more accurate value can be calculated.

  According to the above-described embodiment, the steady-state normative yaw rate γt is calculated based on the steering angle θ or the like subjected to the low-pass filter processing in Step 30. In step 90, the vehicle's lateral acceleration Gyft and yaw rate deviation front wheel rudder angle deviation converted value Δδ are subjected to a high-pass filter process, whereby the vehicle's lateral acceleration Gyftbpf and yaw rate deviation front wheel rudder after the band pass filter process are performed. An angular deviation converted value Δδbpf is calculated. Further, in step 130, the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle are calculated, and in step 140, the ratio Δδa / ΔGya of the integrated values is calculated as a ratio between them. Is calculated.

  Therefore, not only the high frequency noise included in the detected steering angle θ and the like can be removed, but also the influence of the zero point offset of the yaw rate sensor 36 and the like can be removed. Therefore, it is possible to calculate the lateral acceleration Gyftbpf of the vehicle and the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation by eliminating the influence of the zero offset of the sensor, so that the stability factor is compared with the case where the high-pass filter processing is not performed. Kh can be estimated accurately. In addition, the number of high-pass filter processes can be reduced as compared with the case where the high-pass filter process is performed on the steering angle θ, the lateral acceleration Gy, and the actual yaw rate γ used for the calculation of the steady-state standard yaw rate γt. The calculation load of the electronic control unit 30 can be reduced.

  Bandpass filter processing may be performed on the front wheel steering angle deviation converted value Δδ of the lateral acceleration Gy and yaw rate deviation of the vehicle without performing lowpass filter processing on the steering angle θ or the like. In this case, the stability factor Kh can be accurately estimated while effectively removing high-frequency noise, and the number of calculations required for the filter processing can be reduced as compared with the above-described embodiment. This can reduce the calculation load of the electronic control unit 30.

  Further, according to the above-described embodiment, the steady-state normative yaw rate γt is calculated based on the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle after the bandpass filter processing and the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation. A ratio Δδa / ΔGya for calculating a correction amount of the provided stability factor Kh with respect to the initial value Kh0 is calculated.

  Therefore, compared with the case where the ratio Δδbpf / ΔGyftbpf for calculating the correction amount is obtained based on the lateral acceleration Gyftbpf of the vehicle after the bandpass filter processing and the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation, the lateral acceleration of the vehicle is obtained. It is possible to reduce the possibility that the stability factor Kh is estimated inaccurately due to the instantaneous fluctuation of the front wheel steering angle deviation converted value Δδbpf of Gyftbpf or yaw rate deviation.

  Further, according to the above-described embodiment, the integrated value Δδa is an integrated value of the front wheel steering angle deviation converted value Δδ of the yaw rate deviation in which the deviation between the transient yaw rate γtr and the actual yaw rate γ is replaced with the deviation of the steering angle of the front wheels. Therefore, the stability factor Kh can be estimated without being affected by the vehicle speed V. Therefore, the stability factor Kh can be accurately estimated as compared with the case where the integrated value of the yaw rate deviation index value is, for example, the integrated value of the deviation between the transient yaw rate γtr and the actual yaw rate γ. Further, it avoids the complexity of estimating the stability factor Kh for each vehicle speed V and changing the stability factor Kh used for the calculation of the target yaw rate γtt according to the vehicle speed V. Can be reduced.

  Further, according to the above-described embodiment, in step 110, it is determined whether or not it is necessary to adjust the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle. Is done. When an affirmative determination is made, in step 120, an adjustment gain Gaj of 1 or less is calculated. In step 130, the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation after being adjusted by the adjustment gain Gaj and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle are calculated.

  Therefore, for example, when the loading state of the vehicle changes greatly, the stability factor Kh when the previous integrated values Δδa and ΔGya are adjusted and the current stability factor Kh estimated in step 150 of the previous cycle are calculated. In a situation where the magnitude of the deviation ΔKh is increased, the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle are estimated as the stability factor Kh. It is possible to reliably prevent adverse effects.

  Further, according to the above-described embodiment, in step 120, the adjustment gain Gaj is calculated according to the equation 21 based on the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle. The Accordingly, the adjustment gain Gaj can be variably set according to the magnitude of the integrated value Δδa of the front wheel steering angle deviation converted value Δδbpf of the yaw rate deviation and the integrated value ΔGya of the lateral acceleration Gyftbpf of the vehicle. Therefore, the possibility that the estimation error of the stability factor may increase due to the adjustment gain Gaj being too large can be reduced as compared with the case where the adjustment gain Gaj is constant. It is possible to reduce the possibility that the S / N ratio for estimating the stability factor is lowered due to being too small.

  Further, according to the above-described embodiment, it is determined whether or not the storage of the estimated value of the stability factor Kh is permitted in step 180, and if an affirmative determination is made, the process returns to step 190. At this point, the estimated value of the stability factor Kh is stored in the EEPROM. Therefore, the estimated value of the stability factor Kh can be stored in the EEPROM when the estimated value of the stability factor Kh substantially matches the actual stability factor. In other words, until the estimated value of the stability factor Kh substantially matches the actual stability factor, the estimation of the stability factor Kh is repeated without storing the estimated value of the stability factor Kh unnecessarily in the EEPROM. Thus, the estimated value of the stability factor Kh can be gradually brought closer to the actual stability factor.

  Further, according to the above-described embodiment, it is determined in step 100 whether or not the vehicle is in a turning traveling state, and when an affirmative determination is made, step 110 and subsequent steps are executed. Therefore, in a situation where the vehicle is not in a turning state and the stability factor Kh cannot be accurately estimated, it is possible to prevent the step 110 and subsequent steps from being performed unnecessarily and the stability factor Kh from being estimated incorrectly. can do.

  Further, according to the above-described embodiment, the deviation ΔKhlpf of the estimated value of the stability factor Kh after the low-pass filter processing is calculated in Step 160, and the estimated value of the stability factor Kh is converged as the reciprocal 1 / ΔKhlpf of the deviation ΔKhlpf. Degree Ckh is calculated. In step 170, the reference value γo is calculated based on the convergence degree Ckh so that the higher the convergence degree Ckh is, the smaller the vehicle movement control reference value γo based on the yaw rate deviation Δγ is. The dead zone is variably set.

Therefore, when the degree of convergence Ckh is low and the estimation accuracy of the stability factor Kh is low, the reference value γo is increased to increase the dead zone of the vehicle motion control, and the control amount based on the inaccurate estimation value of the stability factor Kh. Inaccurate vehicle motion control can be prevented. Conversely, when the degree of convergence Ckh is high and the estimation accuracy of the stability factor Kh is high, the reference value γo is reduced to reduce the dead zone of the vehicle motion control, and the control amount based on the accurate estimation value of the stability factor Kh is used. Necessary vehicle motion control can be performed.
[First modification]

  FIG. 5 is a flowchart showing the main part of the routine for estimating the stability factor Kh in the first modification in which the first and second embodiments are partially modified. In FIG. 5, steps corresponding to the steps shown in FIG. 3 are assigned the same step numbers as those shown in FIG. 2. The same applies to the flowchart of FIG.

  In this first modification, when step 80 is completed, the number of reciprocating steering operations by the driver per unit time is calculated as the steering frequency fs in step 82. Further, the cut-off frequency fhc is calculated from the map corresponding to the graph shown in FIG. 6 based on the steering frequency fs so that the cut-off frequency fhc of the high-pass filter processing in step 90 becomes smaller as the steering frequency fs becomes lower. .

  In the high-pass filter processing of the vehicle lateral acceleration Gyft and the yaw rate deviation front wheel steering angle deviation converted value Δδ in step 90, the cutoff frequency is set to the cutoff frequency fhc calculated in step 82. The

  In the above-described embodiment, the cutoff frequency fhc of the high-pass filter process in step 90 is constant. Therefore, when the cutoff frequency fhc is set to a high value so that the influence of the zero offset of the sensor is surely removed, the stability factor Kh is estimated in a situation where the number of reciprocating steering operations per unit time is small. There is a risk that you will not be able to. Conversely, if the cut-off frequency fhc is set to a low value, the influence of the zero offset of the sensor cannot be effectively removed in a situation where the number of reciprocating steerings by the driver per unit time is large. There is.

  On the other hand, according to the first modification, the cutoff frequency fhc is variably set according to the steering frequency fs so that the cutoff frequency fhc becomes smaller as the steering frequency fs becomes lower. Therefore, in the situation where the number of reciprocating steerings by the driver per unit time is large, the effect of the zero offset of the sensor is effectively removed, while in the situation where the number of reciprocating steerings by the driver per unit time is small. It is possible to prevent the ability factor Kh from being estimated.

The cut-off frequency fhc is calculated from the map based on the steering frequency fs, but may be calculated as a function of the steering frequency fs.
[Second modification]

  FIG. 7 is a flowchart showing a main part of a routine for estimating the stability factor Kh in the second modified example in which the above-described embodiment is partially modified.

  In the second modification, when step 80 is completed, the number of reciprocating steering operations by the driver per unit time is calculated as the steering frequency fs in step 184. Further, the lower the steering frequency fs, the lower the cut-off frequency fhc of the high-pass filter process, and the higher the absolute value of the longitudinal acceleration Gx of the vehicle, the higher the cut-off frequency fhc of the high-pass filter process. Based on the absolute value of the longitudinal acceleration Gx, the cutoff frequency fhc is calculated from a map corresponding to the graph shown in FIG.

  In the high-pass filter processing of the vehicle lateral acceleration Gyft and the yaw rate deviation front wheel rudder angle deviation converted value Δδ in step 190, the cutoff frequency is set to the cutoff frequency fhc calculated in step 184. The

  An error of the steering angle δ of the front wheels caused by the zero point offset of the steering angle sensor 34 is δ0, and an error of the vehicle lateral acceleration Gy caused by the zero point offset of the lateral acceleration sensor 40 is Gy0. An error in the yaw rate γ of the vehicle due to the zero point offset of the yaw rate sensor 36 is assumed to be γ0. Considering these errors, the deviation Δδt of the steering angle of the front wheels is expressed by the above equation 17.

  Therefore, the influence of the zero point offset of the sensor is the second to fourth terms of the above equation 17, that is, δ0−KhdeGy0L−γ0L / V. Therefore, the greater the change in the vehicle speed V, that is, the magnitude of the longitudinal acceleration Gx of the vehicle, the greater the influence of the zero offset of the sensor on the change in the steady-state standard yaw rate γt, and conversely the smaller the magnitude of the longitudinal acceleration Gx of the vehicle. Therefore, the influence of the zero offset of the sensor on the change in the steady-state standard yaw rate γt is reduced.

  According to the second modification, the cutoff frequency fhc is also based on the absolute value of the longitudinal acceleration Gx of the vehicle so that the higher the absolute value of the longitudinal acceleration Gx of the vehicle is, the higher the cutoff frequency fhc of the high-pass filter processing is. Variable setting. Therefore, it is possible to obtain the same operational effects as those of the first modification described above, and to effectively eliminate the influence of the zero offset of the sensor regardless of the change in the vehicle speed V.

The cut-off frequency fhc is calculated from the map based on the steering frequency fs and the absolute value of the longitudinal acceleration Gx of the vehicle, but is calculated as a function of the absolute value of the steering frequency fs and the longitudinal acceleration Gx of the vehicle. Also good.
[Third modification]

  FIG. 9 is a flowchart showing a main part of a routine for estimating the stability factor Kh in the third modified example in which the above-described embodiment is partially modified.

  In this third modification, if it is determined in step 100 that the vehicle is in a turning state, step 105 is executed prior to step 110. In step 105, it is determined whether or not the vehicle is in a state where the stability factor Kh can be estimated with high reliability. If a negative determination is made, the control returns to step 20 and an affirmative determination is made. If so, control proceeds to step 110.

In this case, when the following (B1) and (B2) are established, it may be determined that the vehicle is in a situation where the stability factor Kh can be estimated with high reliability.
(B1) The traveling road is not a bad road.
(B2) Not braking.

  The condition of B1 takes into consideration that noise is superimposed on the actual yaw rate γ on a rough road and that the grip state of the tire with respect to the road surface is likely to fluctuate. The condition of B2 is based on the fact that the calculation of the steady standard yaw rate γt according to the above equation 11 is premised on that there is no influence of the braking force.

  Therefore, according to the third modified example, the first and second embodiments or the first and second embodiments in which it is not determined whether or not the vehicle is in a state where the stability factor Kh can be estimated with high reliability. The stability factor Kh can be estimated with higher accuracy than in the second modification example.

  Although the present invention has been described in detail with respect to specific embodiments, the present invention is not limited to the above-described embodiments, and various other embodiments are possible within the scope of the present invention. It will be apparent to those skilled in the art.

  For example, in the above-described embodiment and modifications, the correction gain Kgw is calculated based on the absolute value of the longitudinal acceleration Gx of the vehicle and the weight W of the vehicle in step 75. However, the correction gain Kgw may be corrected so as to be calculated based only on the absolute value of the longitudinal acceleration Gx of the vehicle in step 75.

  Further, based on the absolute value of the longitudinal acceleration Gx of the vehicle and the weight W of the vehicle, correction gains Kg and Kw are calculated from maps corresponding to the graphs shown in FIGS. 16 and 17, respectively, and the product of the correction gains Kg and Kw is obtained. The correction gain Kgw may be calculated.

  In the above-described embodiment and each modification, the estimated longitudinal acceleration Gxh of the vehicle is calculated based on the master cylinder pressure Pm or the accelerator opening Acc, and the deviation between the estimated longitudinal acceleration Gxh and the longitudinal acceleration Gx of the vehicle is calculated. Based on this, the weight W of the vehicle is estimated. However, the vehicle weight W may be estimated by an arbitrary method. For example, in the case of a vehicle including a load sensor or a vehicle height sensor in the suspension, the vehicle weight W may be estimated based on the detection results.

  Further, in the above-described embodiment and each modified example, the convergence degree of the stability factor estimated value is calculated in step 160, and the dead zone of the vehicle motion control is variably set based on the convergence degree in step 170. It has come to be. However, the variable setting of the dead zone for motion control based on the degree of convergence may be omitted.

Further, in the above-described embodiment and each modified example, the front wheel rudder angle deviation converted value of the yaw rate deviation obtained by replacing the deviation between the transient yaw rate γtr and the actual yaw rate γ with the deviation of the rudder angle of the front wheels in step 80 is obtained. It is calculated. However, the deviation between the transient yaw rate γtr and the actual yaw rate γ is subjected to a high-pass filter process, whereby a yaw rate deviation Δγbpf after the band-pass filter process is calculated, and instead of the integrated value ratio Δδa / ΔGya, the integrated value of the lateral acceleration Gyftbpf of the vehicle The ratio of the integrated value Δγa of the yaw rate deviation Δγbpf to ΔGya may be calculated, and the estimated value of the stability factor Kh may be calculated according to the following equation 31 based on the integrated value ratio Δγbpf / ΔGya.
Kh = Kh0 + (Δγbpf / ΔGya) / V (31)

  When the estimated value of stability factor Kh is calculated according to Equation 31, it is preferable that a plurality of vehicle speed ranges are set and the estimated value of stability factor Kh is calculated for each vehicle speed range. It is also preferable that the degree of convergence of the estimated value of the stability factor Kh is also calculated for each vehicle speed range, whereby the dead zone of the vehicle motion control is variably set for each vehicle speed range. Furthermore, it is preferable that the stability factor Kh used for calculating the target yaw rate in the vehicle motion control is also set to a value estimated for each vehicle speed range.

  In the above-described embodiment and each modification, the adjustment gain Gaj is within the range of 1 or less, and the first adjustment gain (Δδamin / | current Δδa |) and the second adjustment gain (ΔGyamin / | current) Of ΔGya |) is set to the larger one. However, one of the first and second adjustment gains may be omitted, and the other of the first and second adjustment gains may be corrected to be the adjustment gain Gaj.

  DESCRIPTION OF SYMBOLS 16 ... Power steering device, 20 ... Braking device, 30 ... Electronic control device, 36 ... Yaw rate sensor, 38 ... Longitudinal acceleration sensor, 40 ... Lateral acceleration sensor, 44 ... Engine control device, 46 ... Accelerator opening sensor, 50 ... Movement Control device

Claims (4)

  The lateral acceleration of the vehicle from which the component below the first predetermined frequency is removed using the index value of the deviation between the transient yaw rate of the vehicle and the actual yaw rate of the vehicle that is in a first order lag relationship with the standard yaw rate of the vehicle as the yaw rate deviation index value And a vehicle turning characteristic estimation device for estimating a vehicle stability factor based on a relationship between a yaw rate deviation index value from which a component equal to or lower than a second predetermined frequency is removed. A yaw rate obtained by calculating a correction gain based on at least one of the following, the lateral acceleration of the vehicle from which the component below the first predetermined frequency is removed, and the component below the second predetermined frequency is removed and multiplied by the correction gain A vehicle stability factor estimation device characterized by estimating a vehicle stability factor based on a relationship with a deviation index value.   The lateral acceleration and yaw rate deviation index values of the vehicle are acquired over a plurality of times, the integrated value of the lateral acceleration of the vehicle from which the component below the first predetermined frequency is removed, and the component below the second predetermined frequency are removed and The vehicle stability factor estimation device according to claim 1, wherein the vehicle stability factor is estimated based on a relationship with an integrated value of yaw rate deviation index values multiplied by the correction gain.   The first adjustment gain according to the degree of change in the estimated stability factor value is calculated, and the value obtained by multiplying the previous integrated value of the lateral acceleration of the vehicle by the first adjustment gain and the lateral acceleration of the vehicle acquired this time Is the integrated value of the lateral acceleration of the current vehicle, and the value obtained by multiplying the previous integrated value of the yaw rate deviation index value by the first adjustment gain and the yaw rate deviation index value obtained this time and multiplied by the correction gain. The sum of the current yaw rate deviation index value is used as an integrated value, and the vehicle stability factor is estimated based on the relationship between the current lateral acceleration integrated value and the current yaw rate deviation index value integrated value. The vehicle stability factor estimation device according to claim 2.   4. The vehicle according to claim 1, wherein the yaw rate deviation index value is a value obtained by converting a deviation between a transient yaw rate of the vehicle and an actual yaw rate of the vehicle into a deviation of a steering angle of a front wheel. Stability factor estimation device.

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