JP2003326933A - Damping force control device and fluctuation amount estimating device of shock absorber - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a damping force control device which can easily and accurately estimate a damping coefficient of a shock absorber, the sprung mass and change of a spring constant of a suspension. <P>SOLUTION: The damping force control device according to the present invention is a damping force control device of the shock absorber arranged between a sprung and an unsprung mass and generating a damping force corresponding to a target damping coefficient, and this device comprises a state quantity detecting means for detecting state quantity consisting of a relative displacement and relative speed of the sprung and the unsprung mass as well as a vertical acceleration of the sprung mass, a fluctuation amount estimating means for estimating a fluctuation amount of the damping coefficient of the shock absorber and the spring constant of the suspension using data of the state quantity and information on the given sprung mass, and a target damping coefficient determining means for determining the target damping coefficient of the shock absorber using the estimated fluctuation amount. <P>COPYRIGHT: (C)2004,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a shock absorber damping force control device, and more particularly, to a damping force control capable of highly accurately estimating fluctuation amounts of various parameters affecting damping force control of a shock absorber. Regarding the device.

[0002]

2. Description of the Related Art A vehicle suspension system is provided with a shock absorber capable of changing the damping force characteristic between sprung and unsprung portions, and damping force control means for controlling the damping force characteristic of the shock absorber. . This damping force control means determines the target damping coefficient of the shock absorber based on the detected motion information about the sprung member and unsprung member of the vehicle and the mass of the sprung member, and determines the damping force characteristic of the shock absorber. Have control.

For example, in the device disclosed in Japanese Unexamined Patent Publication No. 10-119528, the target damping coefficient is determined by the vertical acceleration of the sprung member, the relative speed of the sprung member with respect to the unsprung member, etc. based on the skyhook theory. The damping force of the shock absorber is controlled using the determined target damping coefficient.

The damping force of the shock absorber is given by the product of the relative velocity of the sprung member with respect to the unsprung member and the damping coefficient. In addition, a plurality of damping coefficients of the shock absorber are set in advance, and are gradually changed by an actuator incorporated in the shock absorber according to the determined target damping coefficient.

[0005]

However, the damping coefficient of the shock absorber changes from the initial damping coefficient as the shock absorber deteriorates over time. Also, the damping coefficient of the shock absorber depends on the viscosity change and temperature change of the fluid filled in the cylinder of the shock absorber, so determine the target damping coefficient of the shock absorber based on the given control law. However, the actual damping coefficient may differ greatly from the target damping coefficient.

On the other hand, it is possible to detect the temperature of the fluid in the cylinder by using the temperature sensor and consider the detection result when determining the target damping coefficient, but only the detection result of the temperature sensor is available. In that case, it is not possible to estimate the deterioration of the shock absorber over time, and it is also disadvantageous in terms of cost. Furthermore, it is extremely difficult to identify the temperature change and the target damping coefficient, and it is not suitable for controlling vehicle mobility.

On the other hand, using the pressure sensor to detect the magnitude of the damping force actually generated by the shock absorber is most effective in that the target damping coefficient can be determined according to the actual damping force of the shock absorber. However, if the actual damping coefficient of the shock absorber can be estimated with high accuracy without using such a pressure sensor, it will be advantageous in terms of cost.

The control law of the damping force characteristic of the shock absorber is typically a predetermined parameter, for example, the vertical acceleration of the sprung member, the damping coefficient of the shock absorber,
It is designed by constructing a vehicle model that considers the mass of sprung members, the spring constant of the suspension, and the like.
Of these parameters, the vertical acceleration of the sprung member is based on the value actually detected by the acceleration sensor, but the mass of the sprung member and the spring constant of the suspension are the same as the damping coefficient of the shock absorber described above. Similarly,
Actually, this is a parameter that involves fluctuations (for example, the mass of the sprung member depends on the number of passengers and fuel consumption, and the spring constant of the suspension depends on deterioration over time) It is based on.

Therefore, if the fluctuations of these parameters can be estimated with high accuracy, the target damping coefficient can be determined in consideration of the fluctuations, and the control law at the time of design can be determined without redesigning the control law itself. Original performance can be brought out over a longer span.

Therefore, the present invention provides a fluctuation amount estimating device and a damping force using the same which can easily and accurately estimate changes in the damping coefficient of the shock absorber, the mass of the sprung member, and the spring constant of the suspension. It is intended to provide a control device.

[0011]

According to the first aspect of the present invention, there is provided a damping force control for a shock absorber which is arranged between a sprung portion and an unsprung portion to generate a damping force corresponding to a target damping coefficient. A state quantity detecting means for detecting a state quantity consisting of relative displacement and relative velocity between sprung and unsprung parts, and vertical acceleration on the spring, and data of the state quantity and mass information on a given spring. By using the fluctuation amount estimating means for estimating the fluctuation amount of the damping coefficient of the shock absorber and the fluctuation amount of the spring constant of the suspension, and determining the target damping coefficient of the shock absorber in consideration of the estimated fluctuation amount. It is achieved by a damping force control device including a target damping coefficient determining means.

In the present invention, the amount of change in the damping coefficient of the shock absorber and the amount of change in the spring constant of the suspension due to deterioration over time are estimated with high accuracy without using a sensor, and the estimated amount of change is Since the target damping coefficient is determined based on this, it is possible to maintain the vehicle performance intended during design over a long span without changing the design of the control law.

The state quantity detecting means may be various sensors such as an acceleration sensor, but if one state quantity can be estimated based on another state quantity, the state quantity detecting means also includes means for performing such estimation. .

Further, in the damping force control device according to the first aspect, as described in the second aspect, the fluctuation amount estimating means uses the least squares method based on the single wheel model and using the data of the state amount. When estimating the fluctuation amount of the damping coefficient of the absorber and the fluctuation amount of the spring constant of the suspension, the fluctuation amount of the damping coefficient of the shock absorber and the fluctuation amount of the spring constant of the suspension should be accurately estimated with a small calculation load. Is possible.

Further, as described in claim 3, the above object is to provide a state quantity detecting means for detecting a state quantity consisting of relative displacement and relative velocity between sprung and unsprung, and vertical acceleration on the spring, and a shock absorber. Estimate the fluctuation amount of any two parameters among the three parameters consisting of the damping coefficient, the spring constant of the suspension, and the mass on the spring, based on the single-wheel model by the least-squares method using the data of the above state quantities And a fluctuation amount estimating means for controlling the fluctuation amount.

According to the present invention, the fluctuation amount of two of the three parameters is estimated, which contributes to the improvement of the reliability of various vehicle controls including the damping force control of the shock absorber using these parameters. can do. This estimation is an estimation method based on the state quantity data detected by the state quantity detecting means, and the known minimum 2
It may be realized by multiplication.

Further, in the fluctuation amount estimating device according to claim 3, as described in claim 4, the fluctuation amount estimating means takes into account the disturbance affecting the vertical acceleration on the spring, while taking into account the two fluctuations. When estimating the amount, it is possible to improve the estimation accuracy of the variation amount of the parameter by performing the estimation including the disturbance such as the coupled vibration and the air resistance.

Further, in the fluctuation amount estimating device according to claim 3 or 4, as described in claim 5, the fluctuation amount estimating means assumes that the fluctuation amount of one parameter is a predetermined value, and the remaining 2 When estimating the variation amount of one parameter, the variation amount of two of the three parameters can be estimated at the same time.

Further, as described in claim 6, the above-mentioned object is a fluctuation amount estimating device for estimating the fluctuation amount of the mass on the spring, wherein the state amount of the vertical acceleration on the spring is calculated for four wheels. State amount detecting means for detecting the state amount, and variation amount estimating means for estimating the variation amount of the mass on the spring by the least square method using the data of the state amount based on the four-wheel model provided with the center of gravity position information of the vehicle. It is achieved by a fluctuation amount estimation device, which comprises:

According to the present invention, the sprung mass can be estimated at low cost without using a vehicle height sensor which is disadvantageous in terms of mountability and cost. Further, since the variation amount of the sprung mass is estimated in consideration of the coupling of the four wheels, it is possible to significantly improve the estimation accuracy of the variation amount of the sprung mass. The vehicle center-of-gravity position information may be a fixed value based on a design value or the like.

[0021]

BEST MODE FOR CARRYING OUT THE INVENTION First, prior to the description of the parameter estimation method and damping force control device according to the present invention, the configuration of the components related to the damping force control of the damping force variable shock absorber will be schematically described.

Referring to FIG. 1, the vehicle is equipped with a variable damping force shock absorber 3A provided on each of front, rear, left and right wheels.
~ 3D (hereinafter, simply "shock absorber 3A ~ 3D"
And the suspensions 19A to 19 arranged for each wheel together with the shock absorbers 3A to 3D.
D and acceleration sensors 4A to 4A arranged corresponding to the respective wheels.
4D and vehicle height sensors 5A to 5D are mounted. The acceleration sensors 4A to 4D detect the vertical acceleration on the spring and output a detection signal to the electronic control unit 70 (hereinafter, referred to as “ECU”).
70 "). Vehicle height sensor 5A ~
5D detects the relative displacement (stroke displacement) between the sprung part and the unsprung part, and outputs a detection signal to ECU 70. The suspensions 19A to 19D may be springs such as coil springs, leaf springs, and air springs.

The shock absorbers 3A to 3D are provided with actuators 6A to 6D, respectively. The drive force of the actuators 6A to 6D is adjusted to adjust the damping force to be generated.

Each of the shock absorbers 3A to 3D has, for example, an adjusting rod (not shown) arranged therein, and the adjusting rods are used to change the damping force from the actuators 6A to 6A.
By rotating at 6D, the area of the orifice is changed. In this way, the damping force of the shock absorbers 3A to 3D can be changed in multiple steps by changing the flow rate of the fluid passing through the orifice.

The optimum damping force of the shock absorbers 3A to 3D is determined by the ECU 70 in accordance with a predetermined control law in consideration of the mobility, riding comfort and reliability of the vehicle. This control law constructs a vehicle model considering predetermined parameters such as vertical acceleration on a spring, relative displacement between sprung and unsprung, damping coefficient of shock absorber, mass on spring, spring constant of suspension, etc. Designed by

By the way, in a general vehicle model,
For parameters such as vertical acceleration on a spring that constantly fluctuates when the vehicle is traveling, actual detection values by various sensors such as an acceleration sensor are used. On the other hand, reference values (nominal values) determined when designing the shock absorber and the suspension are adopted for the damping coefficient of the shock absorber and the spring constant of the suspension, which have relatively small variations. Similarly, with respect to the mass on the spring, a standard value that is determined in advance assuming a general number of passengers, a load, and the like is adopted.

However, the damping coefficient of the shock absorber is a parameter that depends on the viscosity of the fluid (oil) in the cylinder and the temperature of the fluid and that fluctuates due to deterioration over time. Further, the spring constant of the suspension is a value that varies from product to product and is a parameter that changes due to deterioration over time. Further, the mass on the spring is also a parameter that varies depending on the number of passengers in the vehicle, the remaining amount of fuel, and the weight of the load. Fluctuations of these parameters have a great influence on the damping force control of the shock absorber, so it is desirable to construct a vehicle model in consideration of these fluctuations.

Therefore, according to the first parameter estimation method of the present invention which will be described below, when the vehicle model is constructed, 3
In order to take into account the fluctuations of three parameters, namely, the mass on the spring, the spring constant of the suspension, and the damping coefficient of the shock absorber, we introduced three parameter fluctuation rates corresponding to these parameters. It is possible to estimate the two at the same time.

<First Parameter Estimation Method> The first parameter estimation method of the present invention uses a single-wheel model as shown in FIG.
m, αk, αc) are introduced.

The symbols in the figure are as follows. Mb: sprung mass Ks: suspension spring constant C: damping coefficient xb: sprung displacement xw: unsprung mass αm: sprung mass variation rate αk: suspension spring constant variation rate αc: damping coefficient variation rate In this single wheel model , The equation of motion shown in the following Equation 1 is established.

Xb ″ = Ks × αk / (Mb × αm) × (xw−xb) + C × αc / (Mb × αm) × (xw′−xb ′) (Formula 1) The symbol "" represents the second differentiation, and the symbol "'" is 1
Represents the time derivative. Here, if xs = xw−xb is set,
Equation 1 becomes as follows.

Xb ″ = [Ks / Mb × xs, C / Mb × xs ′] [αk / αm, αc / αm] ^* ... (Equation 1 ′) Note that the symbol “ ^* ” is the transpose of the matrix. Represents

Here, y≡xb ″, ψ ^* ≡ [Ks / M
b × xs, C / Mb × xs ′], θ≡ [θ1, θ2] ^*
= [Αk / αm, αc / αm] ^* , Equation 1 ′ becomes
It looks like this:

Y = ψ ^* × θ (Equation 2) Here, the state quantities xb ″, xs, and xs ′ are sensors (acceleration sensors 4A to 4D and vehicle height sensors 5A to 5).
Db) or xb ″ or xs can be estimated based on the detected value of either one. Therefore, since y and ψ ^* are known, the known recursive Least Squares algorithm (RLS) is used.
Method can be used to obtain θ.

In this way, θ≡ [αk / αm, αc /
αm] ^* is derived, the three parameter fluctuation rates α
Any two of m, αk, and αc can be estimated simultaneously. That is, when one parameter variation rate is given as in (1), (2) and (3) below, the remaining two parameter variation rates can be obtained. (1) When Ks is a reference value (αk = 1), αm = 1
/ Θ1 and αc = θ1 / θ2 are obtained. (2) When C is the reference value (αc = 1), αm = 1 /
θ2 and αk = θ1 / θ2 are obtained. (3) When Mb is the reference value (αm = 1), αk = θ
1, αc = θ2 is obtained.

According to the above first parameter estimation method, the parameter fluctuation rates αm, α are calculated based on the single wheel model.
By introducing k and αc, it is possible to simultaneously estimate up to two parameter variations. This allows
Changes in damping coefficient of shock absorber due to heat and deterioration over time, increase / decrease of passengers and loads, deterioration of suspension over time,
It becomes possible to estimate any two of them at the same time. For example, can the increase and decrease of passengers and loads be ignored,
Alternatively, if it can be estimated by another method, it is possible to estimate the deterioration with time of the shock absorber and the suspension, and it is also possible to perform appropriate control according to the degree of deterioration. Further, in various vehicle controls including damping force control of a shock absorber, it is possible to selectively derive any two parameter fluctuation rates using this parameter estimation method and feed them back to various vehicle controls.

In this parameter estimation method, 3
One of the three parameter fluctuation rates αm, αk, and αc is set to 1 (no fluctuation), and the remaining parameter fluctuation rates are derived.
If any one of m, αk, and αc can be estimated by other means (including actual measurement), the value of the parameter fluctuation rate that can be estimated (a value other than 1) is used, and the remaining 2
It is also possible to derive one parameter variation rate.

<Second Parameter Estimating Method> A second parameter estimating method of the present invention described below is an extension of the above-mentioned first parameter estimating method, and is used for disturbances on the sprung (air resistance and each The parameter fluctuation rates αm, αk, and αc are estimated in consideration of the wheel coupling input). That is, in the above formula 1 ′, the parameter δ indicating the disturbance is further introduced to obtain the following formula. Note that each symbol is the same as in the above-described first parameter estimation method, and therefore its description is omitted here.

Xb ″ = [Ks / Mb × xs, C / Mb × xs ′, −1] [αk / αm, αc / αm, δ] ^* (Formula 3) The above-mentioned first parameter Similar to the estimation method, y≡x
b ″, ψ ^* ≡ [Ks / Mb × xs, C / Mb × x
s ′, −1], θ≡ [θ1, θ2, θ3] ^* = [αk /
[alpha] m, [alpha] c / [alpha] m, [delta]] ^* , then Equation 3 becomes as follows.

Y = ψ ^* × θ (Equation 4) Here, the state quantities xb ″, xs and xs ′ are sensors (acceleration sensors 4A-4D and vehicle height sensors 5A-5).
Db) or xb ″ or xs can be estimated based on the detected value of either one. Therefore, since y and ψ ^* are known, θ can be obtained by the known recursive least squares method.

In this way, θ≡ [αk / αm, αc /
When αm, δ] ^* is derived, any two of the three parameter fluctuation rates (αm, αk, αc) can be estimated simultaneously. That is, when one parameter variation rate is given as in (1), (2) and (3) below, the remaining two parameter variation rates can be obtained. (1) When Ks is a reference value (αk = 1), αm = 1
/ Θ1, αc = θ1 / θ2, θ3 = δ are obtained. (2) When C is the reference value (αc = 1), αm = 1 /
θ2, αk = θ1 / θ2, θ3 = δ are obtained. (3) When Mb is the reference value (αm = 1), αk = θ
1, αc = θ2, θ3 = δ are obtained.

According to the second parameter estimation method described above, the parameter fluctuation rates αm, α are calculated based on the single wheel model.
By introducing k and αc, up to two parameter fluctuations among them can be estimated at the same time in the form including the disturbance. This makes it possible to simultaneously estimate any two of changes in the damping coefficient of the shock absorber due to heat and deterioration over time, increase / decrease in occupants and loads, and deterioration over time of the suspension. Further, by estimating including the disturbance, the calculation load is increased as compared with the first parameter estimation method, but the estimation accuracy can be improved. Further, in various vehicle controls including damping force control of a shock absorber, it is possible to selectively derive any two parameter fluctuation rates using this parameter estimation method and feed them back to various vehicle controls.

In this parameter estimation method, 3
There is no variation in any one of the two parameters (ie α
However, if any one of these parameters can be estimated by other means (including actual measurement), the remaining two parameters can be estimated. It is also possible to estimate the remaining two parameters using the value of the parameter variation rate (a numerical value other than 1).

<Third Parameter Estimation Method> By the way,
In the above-described first and second parameter estimation methods, each parameter is estimated based on the single wheel model.
The actual behavior of the vehicle consists of four wheels, and in order to realize control that can further improve the mobility, riding comfort, and reliability of the vehicle, four wheels are coupled. Vibration (By combining two or more vibration system elements,
It is useful to consider vibrations that affect each other.

Therefore, in the third parameter estimation method of the present invention, the damping coefficient C of the shock absorber and the spring constant Ks of the suspension are assumed to be reference values (ie, αk =
1, αc = 1), the fluctuation of the sprung mass is estimated in consideration of the coupling of the four wheels of the vehicle.

FIG. 3 shows a vehicle model taking into consideration the coupling of four wheels. Here, the symbols in the figure are as follows. M: Sum of sprung mass Tf: Front tread Tr: Rear tread Wb: Wheel base Ffr: Sum of spring force and damping force of front right wheel Ffl: Sum of spring force and damping force of front left wheel Frr: Spring of rear right wheel Sum of force and damping force Frl: Sum of spring force and damping force of left rear wheel xfr ″: Acceleration of sprung front right wheel xfl ″: Acceleration of sprung front left wheel xrr ″: At rear right wheel Sprung acceleration xrl ″: sprung acceleration at the left rear wheel αm: sprung mass variation rate r ″: sprung acceleration at the position of the center of gravity In this coupled model, the equation of motion shown in Equation 5 below holds. .

Αm × M × r ″ = Ffr + Ffl + Frr + Frl (Equation 5) On the other hand, the sprung acceleration r ″ at the center of gravity is the sprung acceleration xl ′ in consideration of the coupling of the two wheels on the left side. 'And the sprung acceleration xr''considering the coupling of the two wheels on the right side are expressed as follows.

R ″ = (lr × xl ″ + ll × xr ″) / (lr + ll) (Equation 6) In addition, as shown in FIG. 3, lr connects two wheels on the right side. The distance of the center of gravity position to the straight line, 11 is substantially equivalent to the distance of the center of gravity position to the straight line connecting the two left wheels.
Further, xl ″ is xl ″ ≡ (Lr × xfl ″ + Lf × xr by using the sprung accelerations of the two left wheels.
l ″) / (Lf + Lr), xr ″ is xr ″ ≡ (Lr × xf, using the sprung acceleration of the two right wheels.
r ″ + Lf × xrr ″) / (Lf + Lr).
As shown in FIG. 3, Lf corresponds to the distance of the center of gravity position to the straight line connecting the two front wheels, and Lr corresponds to the distance of the center of gravity position to the straight line connecting the two rear wheels.

Here, in the above formula 5, y≡Ffr +
When Ffl + Frr + Frl, ψ≡M × r ″, and θ≡αm are set, the equation 5 is as follows.

Y = ψ × θ (Equation 7) Since y and ψ are known, θ can be obtained by the successive least squares method.

According to the third parameter estimation method described above, the variation of the sprung mass can be estimated based on the vehicle model considering the coupling of four wheels by introducing the parameter variation rate αm. As a result, it is possible to consider the variation in the center of gravity of the vehicle due to the increase or decrease of the occupants and the load, and to further improve the estimation accuracy.

<Method of Determining Target Damping Coefficient> Next, a method of determining the optimum target damping coefficient of the shock absorber using the above-described parameter estimation method will be described.

In the reference state intended by the design, the target damping coefficient C _{0 at} the piston speed (stroke speed) V ₀ of the shock absorber uses the optimum damping coefficient ratio ζ ₀ at the piston speed V ₀ and the following relational expression: It is set by.

Ζ ₀ = C ₀ / 2√ (Ks × Mb) (Equation 8) Note that the optimum damping coefficient ratio ζ ₀ is determined in consideration of the vehicle maneuverability, riding comfort, steerability, and the like. It is set in advance.

When the sprung mass, the suspension spring constant, and the shock absorber damping coefficient fluctuate, the damping coefficient ratio ζ fluctuates as follows when expressed using the parameter fluctuation rates αm, αk, and αc.

Ζ = αc × C ₀ / 2√ (αk × Ks × αm × Mb) (Equation 9) In this case, the damping coefficient such that this damping coefficient ratio ζ becomes the optimum damping coefficient ratio ζ ₀ By modifying the target damping coefficient C ₀ to C _T , the optimal damping coefficient ratio ζ ₀
Can be maintained.

More specifically, the damping coefficient C _T satisfies the following equation, ζ ₀ = αc × C _T / 2√ (αk × Ks × αm × Mb) (Equation 9 '). 8 and Equation 9 ′, C _T = √ (αk × αm) / αc × C ₀ .

The three parameter fluctuation rates αm and α
If one of the parameters k and αc is determined, the remaining two parameter fluctuation rates are determined at the same time by the above-described parameter estimation method, so that the target damping coefficient C ₀ can be calculated.

According to the above target damping coefficient determination method, even if the sprung mass, the suspension spring constant, and the shock absorber damping coefficient fluctuate, the optimum target damping coefficient that compensates for the fluctuations is determined. Therefore, by changing the control input (target damping coefficient) without changing the control law, it becomes possible to achieve the maneuverability, riding comfort, steerability, etc. of the vehicle in the initial state.

Next, the operation of the ECU 70 functioning as a damping force control device for the shock absorber will be described.

FIG. 4 is a flowchart showing the operation of the ECU 70.

In step 100, the ECU 70 receives information about the state quantity from various sensors in a predetermined cycle. Specifically, the ECU 70 controls the acceleration sensors 4A to 4A.
D and vehicle height sensors 5A to 5D receive detection signals indicating vertical acceleration on the spring and stroke displacement. When the other state quantity is estimated from the state quantity of one of the vertical acceleration on the spring and the stroke displacement, the ECU
70 executes the following steps using only one of the above state quantities.

In the following step 110, the ECU 70
In the next step 120, necessary data is extracted or calculated from the data relating to the state quantity input in step 100, and these data are subjected to a filtering process in advance as necessary. For example, the ECU 70 sets the stroke displacement x input or estimated in step 100 above.
The stroke speed xs ′ may be calculated from s.

In the following step 120, the ECU 70
Parameter estimation is performed using the first or second estimation method described above. Specifically, the ECU 70 controls the three parameter fluctuation rates αm, αk, and α related to the sprung mass, the suspension spring constant, and the shock absorber damping coefficient.
Estimate the parameter variation rate of two of c. In this embodiment, the ECU 70 estimates the parameter fluctuation rates αk and αc using the parameter fluctuation rate αm as a reference value.

In the following step 130, the ECU 70
The target damping coefficient determination method described above is used to determine the optimum target damping coefficient for each of the shock absorbers 3A to 3D, and then the ECU 70 determines that the shock absorbers 3A to 3D.
A drive signal for rotating the rotary valve is transmitted to the actuators 6A to 6D for switching the damping force of 3D so that the area of the orifice that achieves the determined target damping coefficient is obtained.

According to the damping force control apparatus described above, even if the suspension spring constant and the shock absorber damping coefficient fluctuate due to deterioration over time after the control law is designed, the control law is not redesigned. Only by changing the control input (target damping coefficient), the performance of the vehicle intended at the time of design can be maintained. In addition, it is possible to realize highly precise control using the minimum number of sensors,
It is possible to achieve both cost reduction and accuracy improvement.

The claims 1 and 2 of the claims are as follows.
Corresponding to the damping force control device described in the detailed description of the invention,
Claims 3 and 5 relate to the first parameter estimation method described in the detailed description of the invention, and claims 4 and 5 relate to the second method.
And a third parameter estimation method.

More specifically, the "state amount detecting means" in the claims corresponds to "acceleration sensors 4A to 4D and vehicle height sensors 5A to 5D" described in the detailed description of the invention, but one of them It includes means for estimating the other state quantity using the detection value from the sensor. Further, in the “variation amount estimating means” in the claims, the ECU 70 is configured so that the first, second and third
It is realized by estimating the variation using the parameter estimation method of. The “target damping coefficient determining means” in the claims is realized by the ECU 70 performing the process of step 130.

Although the preferred embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various modifications can be made to the above-described embodiments without departing from the scope of the present invention. And substitutions can be added.

[0070]

Since the present invention is as described above, it has the following effects. According to the first and second aspects of the present invention, the amount of change in the damping coefficient of the shock absorber and the amount of change in the spring constant of the suspension due to deterioration over time can be estimated with high accuracy without using a sensor, and can be estimated. Since the target damping coefficient is determined based on the variation amount, it is possible to maintain the vehicle performance intended at the time of design over a long span without changing the control law.

According to the inventions of claims 3 to 5, it is possible to simultaneously estimate two of the three parameters, and it is also possible to perform highly accurate estimation in consideration of disturbance. According to the invention of claim 6, since the variation amount of the sprung mass is estimated in consideration of the coupling of the four wheels, it is possible to significantly improve the estimation accuracy.

[Brief description of drawings]

FIG. 1 is a block configuration diagram of components related to damping force control.

FIG. 2 is a diagram showing a single wheel model used in the estimation method according to the present invention.

FIG. 3 is a diagram showing a four-wheel model used in the estimation method according to the present invention.

FIG. 4 is a diagram showing a flowchart of damping force control according to the present invention.

[Explanation of symbols] 3A-3D shock absorber 4A-4D acceleration sensor 5A-5D Vehicle height sensor 6A-6D actuator 19A-19D suspension 70 ECU

Claims (6)

[Claims] 1. A damping force control device for a shock absorber, which is arranged between an unsprung part and an unsprung part and generates a damping force corresponding to a target damping coefficient, wherein the relative displacement and relative velocity between the sprung part and the unsprung part. , And a state quantity detecting means for detecting a state quantity consisting of vertical acceleration on the spring, and using the state quantity data and given mass information on the spring, the variation of the damping coefficient of the shock absorber and the suspension. A damping force, comprising: a fluctuation amount estimating means for estimating a fluctuation amount of a spring constant; and a target damping coefficient determining means for determining a target damping coefficient of the shock absorber in consideration of the estimated fluctuation amount. Control device. 2. The variation estimating means estimates the variation of the damping coefficient of the shock absorber and the variation of the spring constant of the suspension by a least square method using the data of the state quantity based on a single wheel model. The damping force control device according to claim 1. 3. A state quantity detecting means for detecting a state quantity consisting of relative displacement and relative velocity between sprung and unsprung, and vertical acceleration on the spring, a damping coefficient of a shock absorber, a spring constant of a suspension, and a sprung. And a fluctuation amount estimating means for estimating a fluctuation amount of any two parameters out of the three parameters consisting of the mass by a least-squares method using the above-mentioned state data based on a single-wheel model. A fluctuation amount estimating device. 4. The fluctuation amount estimating device according to claim 3, wherein the fluctuation amount estimating means estimates the two fluctuation amounts while considering a disturbance affecting vertical acceleration on the spring. 5. The fluctuation amount estimating device according to claim 3, wherein the fluctuation amount estimating means estimates the fluctuation amounts of the remaining two parameters on the assumption that the fluctuation amount of one parameter is a predetermined value. 6. A variation amount estimating device for estimating a variation amount of mass on a spring, comprising: a state amount detecting means for detecting a state amount of vertical acceleration on the spring for four wheels; and a center of gravity of a vehicle. A fluctuation amount estimating device for estimating the fluctuation amount of the mass on the spring by a least-squares method using the data of the state quantity based on a four-wheel model provided with position information. .