JP5742253B2 - Tire contact state estimation device - Google Patents

Description

  The present invention relates to a tire ground contact state estimation device.

  The conventional technique described in Patent Document 1 estimates a tire state based on self-aligning torque, tire slip angle, tire lateral force, tire longitudinal force, and the like with reference to a map determined by tire characteristics. In this conventional technique, the tire condition represents a margin until the tire force reaches a limit.

Japanese Patent No. 4213994

However, the above-described conventional technology does not consider the effect of the slip ratio generated at the rear wheels, and therefore, the accuracy of estimating the tire condition may be reduced in a scene where the slip ratio increases due to sudden braking, for example. . In addition, since the grip degree of the tire is estimated as a feed forward based on a predetermined map, it is estimated that noise is included in, for example, self-aligning torque, tire slip angle, tire lateral force, tire longitudinal force, etc. It will reduce accuracy.
The subject of this invention is improving the estimation precision of a tire ground-contact state.

  The tire ground contact state estimation device according to the present invention estimates the road surface friction coefficient of steered wheels and non-steered wheels, and based on the steered angle, vehicle speed, and road surface friction coefficients of steered wheels and steered wheels, self-aligning steered wheels A torque estimated value, a non-steered wheel slip state estimated value, and a vehicle turning state estimated value are estimated. On the other hand, a self-aligning torque detection value of a steered wheel, a non-steered wheel slip state detection value, and a vehicle turning state detection value are detected. And in the steered wheel self-aligning torque, the non-steered wheel slip state, and the turning state, respectively, the difference between the estimated value and the detected value is calculated as an estimated error, and according to at least one of the estimated errors, The road surface friction coefficient of the steered wheel and the non-steered wheel is corrected.

  According to the tire ground contact state estimation device according to the present invention, according to at least one of the estimation errors of the steered wheel self-aligning torque, the non-steered wheel slip state, and the turning state, the steered wheel and the non-steered wheel By updating the estimated value of the road surface friction coefficient, it is possible to improve the estimation accuracy of the tire contact state including the road surface friction coefficient.

1 is a schematic configuration diagram of a vehicle. It is a system configuration diagram of a tire ground contact state estimation device. It is a system block diagram of a vehicle output estimation part. It is a system block diagram of a tire output estimation part. It is a figure which shows the characteristic change of tire slip angle-front wheel SAT. It is a system configuration figure of a second embodiment. It is a system block diagram of the vehicle output estimation part which shows 2nd embodiment. It is a schematic block diagram of the vehicle which shows 3rd embodiment. It is a system configuration | structure figure of the tire ground-contact-state estimation apparatus which shows 3rd embodiment. It is a system block diagram of the tire output estimation part which shows 3rd embodiment. It is a schematic block diagram of the vehicle which shows 4th embodiment. It is a system block diagram of the tire ground-contact state estimation apparatus which shows 4th embodiment. It is a system block diagram of the tire output estimation part which shows 4th embodiment. It is a system block diagram of the tire ground-contact-state estimation apparatus which shows 5th embodiment. It is a system block diagram of the vehicle output estimation part which shows 5th embodiment. It is a system block diagram of the tire output estimation part which shows 5th embodiment.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
In this specification, vehicle parameters, variables, and tire force functions defined below are used.
[Vehicle parameters]
m: vehicle weight I _z: vehicle yaw inertia moment I _w: wheel inertia l _f about the wheel rotational axis: length of the vehicle center of gravity to the front wheel l _r: to the rear wheels from the vehicle center of gravity length l: Tires Contact surface length R _w : Effective tire radius g: Gravitational acceleration l _t : Half of tread base C _f : Front tire cornering stiffness C _r : Front tire cornering stiffness C _s : Tire driving stiffness

[variable]
V: vehicle speed ω _r : rear wheel speed ω _rl : left rear wheel speed ω _rr : left rear wheel speed F _yf : front tire lateral force F _yr : rear tire lateral force F _yrl : left rear wheel tire lateral force _F yrr: the right rear wheel tire lateral force F _xr: a rear wheel tire longitudinal forces s _r: rear-wheel slip ratio s _rl: left rear wheel slip ratio s _rr: left rear wheel slip ratio F _zf: the front wheel load F _zr: after Wheel load M _z : Front wheel SAT
T _r : Rear wheel braking / driving torque T _rl : Left rear wheel braking / driving torque T _rr : Right rear wheel braking / driving torque α _f : Front wheel tire slip angle α _r : Rear wheel tire slip angle β: Vehicle slip angle r: Yaw rate a _y : Lateral acceleration μ _f : Front wheel road friction coefficient μ _r : Rear wheel road friction coefficient μ _rl : Left rear wheel road friction coefficient μ _rr : Right rear wheel road friction coefficient δ: Front wheel turning angle ξ: Dimensionless tire adhesion area Length ρ: Static front and rear wheel load ratio

[Tire force function]
h _f : Front wheel tire lateral force h _r : Rear wheel tire lateral force h _xr : Rear wheel tire longitudinal force J _f : Front wheel SAT characteristics

<< First embodiment >>
"Constitution"
FIG. 1 is a schematic configuration diagram of a vehicle.
This vehicle includes a drive motor 107H as a drive force generation source, and a drive motor output shaft is connected to a rear wheel axle via a reduction gear 106H, and drives the left and right rear wheels 104HRL and 104HRR. The drive circuit 102H drives the drive motor 107H with electric power from the lithium ion battery 103H so that the drive motor output torque matches the torque command value received from the integrated controller 130H.
The front wheels 104HFL and 104HFR are not only mechanically steered mechanically via the steering gear 114H by the rotational movement of the steering wheel 111H operated by the driver, but are also auxiliary steered by torque from the auxiliary steering motor 112H.

  The integrated controller 130H includes a steering wheel angle signal detected by a steering angle sensor 121H attached to the rotation shaft of the steering wheel 111H, an auxiliary steering motor current detection value detected from the auxiliary steering motor 112H, and a steering system. Steering torque detection value detected by the torque sensor 115H, wheel speed detected by the wheel speed sensors 105HFL, 105HFR, 105HRL, 105HRR attached to each wheel, lateral acceleration detection value detected by the lateral acceleration sensor 108H, and The longitudinal acceleration detection value, the yaw rate detection value detected by the yaw rate sensor 109H, and the drive motor current detection value detected from the drive motor 107H are input. The integrated controller 130H includes a tire ground contact state estimation device described below.

Next, an algorithm in the present embodiment will be described.
FIG. 2 is a system configuration diagram of the tire ground contact state estimation device.
The tire ground contact state estimation device includes a turning angle detection unit 110, a rear wheel braking / driving torque detection unit 111, a vehicle speed detection unit 120, a vehicle output estimation unit 130, a front wheel road surface friction coefficient estimation unit 150, and a rear wheel road surface. A friction coefficient estimation unit 160, a front wheel SAT detection unit 170, a rear wheel slip ratio detection unit 180, a lateral acceleration detection unit 190, and an estimation error calculation unit 200 are provided.

For example, the turning angle detection unit 110 detects the turning angle from the steering wheel angle sensor value provided in the steering system in consideration of the steering gear ratio and the suspension geometric structure.
For example, the rear wheel braking / driving torque detection unit 111 detects braking / driving torque from the rear wheel driving motor current in consideration of the torque coefficient of the driving motor.

The vehicle speed detection unit 120 detects the vehicle speed based on the measured value of the driven wheel speed, for example. In the present embodiment, since the driven wheel speed is detected by the left front wheel speed sensor 105HFL and the right front wheel speed sensor 105HFR, the vehicle speed is detected from these detected values.
The vehicle output estimation unit 130 determines the front wheel self-aligning torque (hereinafter referred to as the front wheel SAT) based on the steered angle detection value, the vehicle speed detection value, the front wheel road surface friction coefficient estimation value, and the rear wheel road surface friction coefficient estimation value. Estimated value, rear wheel slip ratio estimated value, lateral acceleration estimated value, and vehicle slip angle estimated value are estimated.

Here, the vehicle output estimation unit 130 will be described.
FIG. 3 is a system configuration diagram of the vehicle output estimation unit.
The vehicle output estimation unit 130 includes a vehicle body slip angle estimation unit 131, a yaw rate estimation unit 132, and a tire output estimation unit 133.
The vehicle slip angle estimation unit 131 estimates the vehicle slip angle based on the front wheel lateral force estimated value, the rear wheel lateral force estimated value, the vehicle speed detection value, and the estimation error. The dynamics of the body slip angle is expressed by the following equation.

  As a method for converting a continuous-time differential equation into discrete time, for example, when the discretization is performed using the Euler method, the following equation is obtained.

The subscript k represents the discrete time, and the letter with k represents the amount that changes at each calculation time. Δt is the discrete sample time. Based on the above equation, the estimated slip angle is updated in consideration of the estimated error calculated by the estimated error calculator 200.
That is, the vehicle slip angle is estimated by the following equation.

Here, each estimated value is described with a symbol of ^. _ek is a column vector composed of estimation errors for the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration, which are calculated by the estimation error calculation unit. That is, it is expressed by the following equation.

Here, the superscript T indicates transposition of a vector.
Lβ _k is a gain related to the slip angle of the vehicle body and has the following structure.

Of the components of Lβ _k , Lβ _1k is a coefficient related to the front wheel SAT estimation error, Lβ _2k is a coefficient related to the estimation error of the rear wheel slip ratio, and Lβ _3k is a coefficient related to the lateral acceleration estimation error. It can be seen that the estimation is based on the errors of the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration.
In general, the vehicle body slip angle is determined based on the turning state of the vehicle, the front wheel road surface friction coefficient, and the rear wheel friction coefficient. Therefore, as in the present embodiment, the vehicle slip angle is estimated using the lateral acceleration representing the turning state, the SAT including the information on the front wheel friction coefficient, and the slip ratio including the information on the rear wheel friction coefficient. Thus, the estimation accuracy can be improved. A detailed method for setting the gain Lβ _k will be described later.
The yaw rate estimation unit 132 estimates the yaw rate according to the following equation based on the front wheel lateral force estimated value, the rear wheel lateral force estimated value, the left and right rear wheel longitudinal force estimated value, and the estimation error.

  When discretized in the same manner as the vehicle slip angle dynamics, the following equation is obtained.

  Based on the dynamics expressed by this equation, the estimated slip angle is updated as shown below in consideration of the estimation error calculated by the estimation error calculation unit 180.

L _rk is a gain vector related to the yaw rate. Similar to the estimation of the vehicle slip angle, the yaw rate is generally determined based on the turning state, the front wheel road surface friction coefficient, and the rear wheel friction coefficient. Therefore, the estimation error is included in the e _k, and a lateral acceleration representing the turning state, the SAT including information of the front wheel friction coefficient and a slip ratio including information of the rear wheel friction coefficient, by using the same time, the precision yaw rate Can be estimated well. The method for setting _Lrk will be described in detail later.

  The tire output estimation unit 133 includes a vehicle speed detection value, a vehicle body slip angle estimation value, a yaw rate estimation value, a turning angle detection value, a rear wheel driving torque detection value, a front wheel road surface friction coefficient estimation value, and a rear wheel road surface. Based on the friction coefficient estimated value and the estimation error, the front wheel SAT estimated value, the rear wheel slip rate estimated value, the lateral acceleration estimated value, the front wheel lateral force estimated value, the rear wheel lateral force estimated value, and the rear wheel Estimate and output the estimated longitudinal force.

FIG. 4 is a system configuration diagram of the tire output estimation unit.
The tire output estimating unit 133 includes a tire slip angle estimating unit 134, a SAT estimating unit 135, a lateral force estimating unit 136, a lateral acceleration estimating unit 137, a longitudinal force estimating unit 138, a wheel speed estimating unit 139, a slip A rate estimator 140.
The tire slip angle estimating unit 134 calculates the tire slip angle based on the yaw rate estimated value, the vehicle slip angle estimated value, the turning angle detected value, and the vehicle speed detected value by the following equation.

The SAT estimation unit 135 obtains a front wheel SAT estimated value using a previously acquired SAT characteristic J _f (,) based on a front wheel slip angle estimated value, a front wheel road surface friction coefficient estimated value, and a braking slip ratio. That is, it can be expressed by the following equation.

  In general, the SAT characteristic also changes depending on the amount of slip rate generated, but in this embodiment, the front wheels are driven wheels, and the slip rate is negligibly small. For example, when a filar model is used as the SAT characteristic, the front wheel SAT can be calculated by the following equation.

However, φ ^ _k is as follows.

Alternatively, the front wheel SAT may be calculated using a magic formula or a map that is numerically defined based on data obtained through experiments.
In the lateral force estimation unit 136, a front wheel slip angle estimated value, a rear wheel slip angle estimated value, a front wheel road surface friction coefficient estimated value, a rear wheel friction coefficient estimated value, a turning angle detected value, and a rear wheel slip ratio estimated Based on the value, the front wheel lateral force estimated value and the rear wheel lateral force estimated value are calculated.
The estimated front wheel lateral force value is calculated as shown in the following equation in accordance with the estimated front wheel slip angle value and the estimated front wheel road surface friction coefficient.

h _f (,) is a front wheel lateral force characteristic. In general, the tire lateral force characteristics vary depending on the amount of slip rate generated, but in this embodiment, the front wheels are driven wheels, and the slip rate is negligibly small. For example, when the filar model is used as the lateral force characteristic, the front wheel lateral force is expressed by the following equation.

However, φ ^ _k is as follows.

  Further, a magic formula or a numerical map may be used as the lateral force characteristic. The estimated rear wheel lateral force value is determined by the estimated rear wheel slip angle value, the estimated rear wheel road surface friction coefficient, and the estimated rear wheel slip ratio. That is, it is calculated by the following formula.

Various models can be used for the rear wheel lateral force characteristics h _r (,) as in the case of the front wheels.
Further, the lateral acceleration estimation unit 137 calculates the lateral acceleration by the following equation based on the front wheel lateral force estimated value and the rear wheel lateral force estimated value.

  The longitudinal force estimator 138 calculates a rear wheel longitudinal force estimated value based on the following equation based on the rear wheel slip ratio estimated value, the rear wheel road surface friction coefficient estimated value, and the rear wheel slip angle.

Here, h _xr (,) is a tire longitudinal force characteristic. For example, when a brush model is used as the longitudinal force characteristic, the estimated rear wheel longitudinal force value is expressed by the following equation at the time of braking (by automobile movement and control, by Sankaido and Masato Abe).

However, ξ ^ _k is as follows.

Also, cos θ ^ _k is as follows.

  In driving, it is expressed by the following equation (movement and control of automobiles, by Sankaido and Masato Abe).

However, ξ ^ _k is as follows.

Also, cos θ ^ _k is as follows.

  The wheel speed estimation unit 139 estimates the wheel speed estimation value based on the detected value of the rear wheel braking / driving torque, the estimated value of the rear wheel longitudinal force, and the estimation error. The dynamics of the wheel speed when the braking / driving torque is applied is given by the following equation.

  When this equation is discretized using, for example, the Euler method, the following equation is obtained.

  Δt is the sample time. Based on the discrete time dynamics, the rear wheel speed is calculated according to the estimation error. That is, the rear wheel speed is calculated by the following equation.

Here, e _k is an estimation error. Lω _k is a gain vector related to the wheel speed, and the determination method will be described in detail later.
The slip ratio estimation unit 140 estimates the rear wheel slip ratio from the wheel speed estimated value and the vehicle speed detected value.

In the denominator, the vehicle body speed and the rear wheel speed are compared and a larger value is selected. In general, the vehicle speed is higher during braking and the wheel speed is higher during driving.
The front wheel road surface friction coefficient estimation unit 150 in FIG. 3 estimates the front wheel road surface friction coefficient from the estimation error based on the road surface friction coefficient dynamics model. Assuming that the road friction coefficient is piecewise constant, the road friction coefficient dynamics model is defined as:

  Based on an equation obtained by discretizing this equation, a front wheel road surface friction coefficient is estimated according to an estimation error. That is, the front wheel road surface friction coefficient is estimated by the following equation.

Here, a method for determining the gain Lμ _fk will be described later. The dynamics of the road surface friction coefficient may be defined such that the first derivative of time is 0 as in this example, or a model in which the second derivative is defined as 0 may be used, for example.
The rear wheel road surface friction coefficient estimation unit 160 estimates the front wheel road surface friction coefficient from the estimation error based on the road surface friction coefficient dynamics model. Assuming that the road friction coefficient is piecewise constant, the road friction coefficient dynamics model is defined as:

  Based on an equation obtained by discretizing this equation, a front wheel road surface friction coefficient is estimated according to an estimation error. That is, the front wheel road surface friction coefficient is estimated by the following equation.

Here, a method for determining the gain Lμ _fk will be described later. The dynamics of the road surface friction coefficient may be defined such that the first derivative of time is 0 as in this example, or a model in which the second derivative is defined as 0 may be used, for example.
In this way, by defining the dynamics of the road friction coefficient, based on the correction signal calculated by multiplying the estimation error by the gain, the next discrete time estimation value μ ^ _fk from the current estimation value μ ^ _fk , μ ^ _{rk +1} and μ ^ _{rk + 1} can be estimated. This calculation is performed in the same calculation step as the calculation for estimating the next discrete time estimated value β ^ _{k + 1} from the current estimated value β ^ _k of the vehicle slip angle in the vehicle slip angle estimating unit 131. The slip angle and the road surface friction coefficient can be estimated simultaneously.

  When estimating the road surface friction coefficient of the front and rear wheels based on tire force and SAT, information on the vehicle slip angle is necessary, and in many cases, estimation is performed using a vehicle dynamics model. In general, however, the vehicle slip angle is determined on the basis of the road surface friction coefficient, which is an amount to be estimated, because the generation amount is determined depending on the road surface friction coefficient of the front and rear wheels. In the configuration of the present embodiment, it is possible to simultaneously estimate the vehicle body slip angle and the road surface friction coefficient of the front and rear wheels, and the accuracy of the estimated value can be improved.

The front wheel SAT detection unit 170 detects the front wheel SAT. The front wheel SAT is detected from, for example, a torque sensor value, an assist motor current value, and a steering wheel angle in electric power steering based on steering system rotational motion dynamics .

Further, the SAT may not be directly detected, and for example, the tie rod axial force may be output from the front wheel SAT detection unit 170.
The rear wheel slip ratio detector 180 detects the rear wheel slip ratio. For example, the rear wheel slip ratio is detected from the vehicle speed and the rear wheel speed .

The lateral acceleration detector 190 detects lateral acceleration. For example, the lateral acceleration is detected by referring to the measured value of the acceleration sensor in the skid prevention device mounted on the commercial vehicle.
In the estimation error calculating unit 200, the difference between the front wheel SAT estimated value estimated by the vehicle output estimating unit 130, the front wheel SAT detected value detected by the front wheel SAT detecting unit 170, and the rear wheel estimated by the vehicle output estimating unit 130. The difference between the slip ratio estimated value, the rear wheel slip ratio detected value detected by the rear wheel slip ratio detecting unit 180, the lateral acceleration estimated value estimated by the vehicle output estimating unit 130, and the rear wheel slip ratio detecting unit 180 The difference between the detected lateral acceleration detection values is calculated. That is, the estimation error _ek is calculated by the following equation.

The superscript T indicates vector transposition.
The estimation error e _y is used in the vehicle output estimation unit to estimate the vehicle slip angle and the yaw rate. In the front wheel road surface friction coefficient estimation unit and the rear wheel road surface friction coefficient estimation unit, the front wheel road surface friction coefficient and the rear wheel surface friction coefficient are used. Used for coefficient estimation.
Next, a method for setting the gain used for updating the estimated value will be described.
Using the state vector x _k = [β _k r _k ω _rk μ _fk μ _rk ] ^T , the vehicle slip angle, yaw rate, wheel speed, front wheel road surface friction coefficient, rear wheel road surface friction coefficient, and the equations used to estimate each When expressed together, it can be expressed as:

Here, the input is u _k = [δ _k T _rk ], and the gain L is L _k = [Lβ _k L _rk Lω _k Lμ _fk Lμ _rk ] ^T.
This formula shows that the time k + 1 in state x ^ k _{+ 1} is the state x ^ _k in the previous discrete time k input u _k, and the estimated error e _k, which is determined.
Also define the output of the system as _{y k = [M zk s k} a yk] T. Since the output y _k is algebraically calculated by the body slip angle, yaw rate, rear wheel speed, front and rear road surface friction coefficient included in the state vector x ^ _k , and the input u _k to the vehicle, It can be expressed as:

  Based on the above equation, the system Jacobian matrix is calculated as:

Jacobian example, by taking the difference from the value of the function at state x ^ and the value of the function at _k, state micro changing state x ^ _k + [Delta] x, numerically be calculated. That is, it is calculated by the following formula.

  Based on the Jacobian matrix calculated in this way, an appropriate gain can be determined by using, for example, a Kalman filter algorithm at each calculation step. The Kalman filter algorithm performs the following operations at each calculation step.

Here, the subscript-represents a prior estimated value, and P _k is a covariance matrix of estimated values. Q _k is a process noise covariance matrix, and R _{k + 1} is an observation noise covariance matrix included in the detected value. These are parameters for adjusting a trade-off between noise tolerance and estimated value response, and are practically determined by a designer. For example, if the diagonal component of R _k is set to be large, the resistance to noise included in the detected values of SAT, slip ratio, and yaw rate is improved, but tracking of the road surface friction coefficient estimated value when the road surface friction coefficient changes suddenly. Responsiveness decreases. Further, if the diagonal component of Q _k is set to be large, the resistance to noise included in the detected values of SAT, slip ratio, and yaw rate is reduced, but tracking of the road surface friction coefficient estimated value when the road surface friction coefficient changes suddenly. Responsiveness is improved.

When this algorithm is used to determine the gain, the state is estimated so as to minimize the noise variance of the estimated state. Therefore, when the noise included in the observation amount is significant or when it is desired to assume process noise, accurate estimation is possible. A value can be obtained.
Alternatively, when the pole placement method is used instead of the present algorithm, the gain can be determined using the estimated response time and the attenuation coefficient as design specifications.
Further, the gain characteristic may be adjusted based on the front wheel SAT, the rear wheel slip ratio, and the yaw rate.
First, when the absolute value of the detected rear wheel slip ratio is smaller than a predetermined threshold value near 0, or when the rear wheel slip ratio estimation error is larger than a predetermined threshold value, the front wheel SAT estimation error and the yaw rate estimation are performed. Set the gain so that the error is small.

Further, when the absolute value of the front wheel SAT detection value is smaller than a predetermined threshold value near 0, or when the front wheel SAT estimation error is larger than a predetermined threshold value, the rear wheel slip ratio estimation error and the yaw rate estimation error are Set the gain so that it becomes smaller.
Further, when the absolute value of the yaw rate detection value is smaller than a predetermined threshold value near 0, or when the yaw rate estimation error is larger than a predetermined threshold value, the front wheel SAT estimation error and the rear wheel slip rate estimation error are small. Set the gain so that

<Action>
In a rear-wheel drive vehicle, if you try to estimate the road surface friction coefficient of the front wheels without considering the effect of the slip ratio generated on the rear wheels, for example, in a scene where the slip ratio increases due to sudden braking, the estimation of the tire condition Accuracy may be reduced. In addition, since the grip degree of the tire is estimated as a feed forward based on a predetermined map, it is estimated that noise is included in, for example, self-aligning torque, tire slip angle, tire lateral force, tire longitudinal force, etc. It will reduce accuracy.

FIG. 5 is a diagram showing a change in characteristics of the tire slip angle-front wheel SAT.
Also, based on the driving wheel wheel speed, driven wheel speed, driven wheel acceleration, driving wheel wheel speed differential value, driven wheel wheel speed differential value, driven wheel acceleration differential value, and driving wheel ground load, It is also conceivable to estimate the road surface friction coefficient based on the amount of change in the road surface friction coefficient. However, since the road surface friction coefficient of the rear wheels is estimated without considering the change in the longitudinal force characteristics with respect to the slip ratio due to the slip angle that occurs on the front and rear wheels during turning, the road surface friction coefficient is estimated accurately during turning. Difficult to do. Further, when the driven wheel speed difference value and the driven wheel speed difference value are calculated, noise included in the wheel speed is amplified, and the estimation accuracy may be reduced.

Therefore, the road surface friction coefficients μ ^ _f and μ ^ _r are estimated, and based on the turning angle δ, the vehicle speed V, the road surface friction coefficients μ ^ _f and μ ^ _r , the front wheel SAT estimated value M ^ _z and the rear wheel slip The estimated rate value s ^ and the lateral acceleration estimated value a ^ _y are estimated. On the other hand, the front wheel SAT detection value M _z , the rear wheel slip ratio detection value s, and the lateral acceleration detection value a _y are detected. Then, a front wheel SAT, and the rear wheel slip state, in a turning state, respectively, calculates the difference e _k between the estimated value and the detected value as an estimated error, according to at least one of the estimated error e _k, road Correct the friction coefficients μ ^ _f and μ ^ _r .

Thus, the front wheel aligning torque, and the rear wheel slip state, in response to at least one of the estimated error e _k with the turning state, the road surface friction coefficient estimated value mu ^ _fk and mu ^ _rk, mu By updating to ^ _{fk + 1} and μ ^ _{rk + 1} , the estimation accuracy of the road friction coefficient can be improved.
In addition, considering the front wheel SAT and the rear wheel slip ratio to the estimation of the other wheel, the front wheel road friction coefficient and the rear wheel road friction coefficient can be estimated independently while being associated in the estimator. The road surface friction coefficient of the rear wheel can be accurately estimated. That is, the front wheel road surface friction coefficient is estimated in consideration of the effect of the slip ratio generated at the rear wheel, and the rear wheel road surface friction coefficient is estimated in consideration of the effect of the slip angle generated at the front wheel and the rear wheel. The estimation accuracy can be improved compared to the prior art.

By using the front wheel SAT equivalent amount and the rear wheel slip state as the amount detected from the vehicle, for example, the SAT equivalent amount can be detected from the steering assist motor current and the torque sensor value provided in the electric power steering system. Since the slip state can be detected based on the wheel speed, it is not necessary to add a new sensor in many commercial vehicles, and an increase in vehicle cost can be suppressed.
As described above, based on the independently estimated road surface friction coefficient of the front and rear wheels, for example, when the vehicle travels at a low speed, the front wheel and the rear wheel have different trajectories, and the front wheel and the rear wheel have different road surface friction coefficients. Can be carried out with higher accuracy.

In general, the generation amount of the vehicle slip angle β is determined mainly by the front wheel road surface friction coefficient μ _f , the rear wheel road surface friction coefficient μ _r, and the lateral acceleration a _y. The difference between the detected value and the estimated value of the front wheel SAT equivalent amount that includes a relatively large amount of road surface friction coefficient information, and the difference between the detected value and the estimated value of the rear wheel slip ratio that includes a relatively large amount of information of the rear wheel road surface friction coefficient The vehicle slip angle β is estimated based on the difference between the lateral acceleration detection value and the estimated value. As a result, the vehicle slip angle β can be estimated with high accuracy, and the estimation accuracy of the front-wheel road surface friction coefficient μ _f and the rear-wheel friction coefficient μ _r estimated based thereon can be improved.

Further, when the front wheel road surface friction coefficient μ _f and the rear wheel road surface friction coefficient μ _r are estimated based on the front wheel SAT model and the tire force model, information on the front wheel tire slip angle α _f and the rear wheel tire slip angle α _r is obtained. While it is necessary, on the one hand, those to estimate the tire slip angle alpha _f and alpha _r is required front wheel road surface friction coefficient mu _f and the rear wheel road surface friction coefficient mu _r information that is intended to be estimated is there.

Therefore, based on the difference between the detected value of the front wheel SAT equivalent amount and the estimated value, the difference between the detected value of the rear wheel slip state and the estimated value, and the difference between the detected value of the vehicle turning state and the estimated value, the front wheel road surface friction is determined. Each estimated value can be estimated with high accuracy by employing a configuration in which the coefficient, the rear wheel road surface friction coefficient, and the vehicle slip angle necessary for calculating the tire slip angle are simultaneously estimated.
In addition, the estimation of the road surface friction coefficients μ ^ _f and μ ^ _r includes a dynamic characteristic model in which the first-order derivative with _{respect to} time is defined as 0, and the detected value and estimated value of the front wheel SAT equivalent amount are included in this dynamic characteristic model. By inputting the amount calculated from the difference, the difference between the detected value of the rear wheel slip condition and the estimated value, and the difference between the detected value of the vehicle turning condition and the estimated value, the noise of the road surface friction coefficient is determined by the noise included in each detected value. It is possible to prevent the estimation accuracy from being lowered.

"effect"
From the above, the turning angle detection unit 110 corresponds to the “steering angle detection unit”, the vehicle speed detection unit 120 corresponds to the “vehicle speed detection unit”, and the front wheel road surface friction coefficient estimation unit 150 and the rear wheel road surface friction coefficient estimation unit. 160 corresponds to “road surface friction coefficient estimating means”. Further, the SAT estimation unit 135 of the tire output estimation unit 133 in the vehicle output estimation unit 130 and the calculations of Equations 10 and 11 correspond to “steered wheel self-aligning torque estimation means”, and the tire output in the vehicle output estimation unit 130 The slip ratio estimating unit 140 of the estimating unit 133 and the calculation of Equation 28 correspond to “non-steered wheel slip state estimating means”, the lateral acceleration estimating unit 137 of the tire output estimating unit 133 in the vehicle output estimating unit 130, and Equation 17 Corresponds to the “turning state estimating means”. Further, the front wheel SAT detection unit 170 corresponds to “steered wheel self-aligning torque detection means”, the rear wheel slip rate detection unit 180 corresponds to “non-steered wheel slip state detection means”, and the lateral acceleration detection unit 190 corresponds to “ Corresponds to "turning state detection means". Further, the estimation error calculation unit 200 and the calculation of Equation 33 correspond to the “steered wheel self-aligning torque estimation error calculation means”, and the calculation of the estimation error calculation unit 200 and Equation 33 corresponds to the “non-steered wheel slip state estimation error”. Corresponding to the “calculation means”, the estimation error calculation unit 200 and the calculation of Equation 33 correspond to the “turning state estimation error calculation means”. The front wheel road surface friction coefficient estimation unit 150, the rear wheel road surface friction coefficient estimation unit 160, and the calculations of Equations 30 and 32 correspond to “road surface friction coefficient correction means”.

  Further, the vehicle slip angle estimation unit 131 of the vehicle output estimation unit 130 corresponds to “vehicle slip angle estimation means”, and the calculation of the vehicle slip angle estimation unit 131 of the vehicle output estimation unit 130 and Equation 3 is “vehicle slip angle correction”. The yaw rate estimation unit 132 of the vehicle output estimation unit 130 corresponds to the “yaw rate estimation unit”, the yaw rate estimation unit 132 of the vehicle output estimation unit 130 and the equation 8 correspond to the “yaw rate correction unit”, The wheel speed estimation unit 139 of the tire output estimation unit 133 in the vehicle output estimation unit 130 corresponds to “rear wheel vehicle speed estimation means”, the wheel speed estimation unit 139 of the tire output estimation unit 133 in the vehicle output estimation unit 130, and Equation 27 Corresponds to “rear wheel speed correction means”.

(1) The tire ground contact state estimating device estimates the road surface friction coefficient of the rear wheel and the front wheel, estimates the front wheel SAT estimated value based on the turning angle, the vehicle speed, and the road surface friction coefficient of the front wheel, and based on the vehicle speed. Then, the estimated rear wheel slip ratio is estimated, and the estimated lateral acceleration of the vehicle is estimated based on the turning angle, the vehicle speed, and the road surface friction coefficient of the rear and front wheels. On the other hand, the front wheel SAT detection value is detected, the rear wheel slip ratio detection value is detected, and the vehicle lateral acceleration detection value is detected. Then, the front wheel SAT estimation error defined by the difference between the estimated value of the front wheel SAT and the detected value is calculated, and the rear wheel slip ratio estimated error defined by the difference between the estimated value of the rear wheel slip ratio and the detected value is calculated. The lateral acceleration estimation error defined by the difference between the lateral acceleration estimated value and the detected value is calculated. Then, the road surface friction coefficient of the rear wheels and the front wheels is corrected according to at least one of the front wheel SAT estimation error, the rear wheel slip ratio estimation error, and the lateral acceleration estimation error.
Thus, the road surface friction coefficient is updated by updating the estimated value of the road surface friction coefficient of the rear wheels and the front wheels according to at least one of the estimation errors of the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration. It is possible to improve the estimation accuracy of the ground contact state of the tire.

(2) The tire ground contact state estimation device estimates a vehicle slip angle, and the vehicle slip angle estimator determines at least one of a front wheel SAT estimation error, a rear wheel slip ratio estimation error, and a lateral acceleration estimation error. Correct the estimated vehicle slip angle.
Thus, the estimated value of the vehicle slip angle is updated by updating the estimated value of the vehicle slip angle according to at least one of the estimation errors of the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration. be able to. Accordingly, it is possible to improve the estimation accuracy of the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration estimated using the vehicle body slip angle.

(3) In the tire ground contact state estimating device, the estimation of the road surface friction coefficient and the estimation of the vehicle slip angle are executed at the same calculation cycle.
As described above, the estimation accuracy can be improved by executing the estimation of the road surface friction coefficient and the estimation of the vehicle slip angle in the same calculation time step.

(4) The tire ground contact state estimation device estimates the yaw rate, and corrects the yaw rate according to at least one of the front wheel SAT estimation error, the rear wheel slip ratio estimation error, and the lateral acceleration estimation error.
In this way, the yaw rate estimation accuracy can be improved by updating the yaw rate estimation value according to at least one of the estimation errors of the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration. Accordingly, it is possible to improve the estimation accuracy of the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration estimated using the yaw rate.

(5) The tire ground contact state estimation device estimates the wheel speed of the rear wheel, and determines the rear wheel speed according to at least one of a front wheel SAT estimation error, a rear wheel slip ratio estimation error, and a lateral acceleration estimation error. to correct.
In this way, the estimated value of the rear wheel speed is updated by updating the estimated value of the rear wheel speed according to at least one of the estimation errors of the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration. Can be improved. Therefore, it is possible to improve the estimation accuracy of the lateral acceleration estimated using the rear wheel speed.

(6) The tire ground contact state estimation device estimates a road surface friction coefficient using a dynamic characteristic model in which a first-order derivative with respect to time is defined as zero.
Thus, by using the dynamic characteristic model in which the first-order derivative with respect to time is defined as 0, it is possible to prevent the estimation accuracy of the road surface friction coefficient from deteriorating due to noise included in each detection value.

(7) When the absolute value of the slip state detection value is smaller than a predetermined threshold value near 0, or when the slip state estimation error is larger than a predetermined threshold value, the tire ground contact state estimation device determines the front wheel SAT estimation error. And the road surface friction coefficient of the rear wheels and the front wheels are corrected so that the lateral acceleration estimation error is reduced.
As described above, by adjusting the correction weighting according to the slip state detection value or the slip state estimation error, it is possible to improve the estimation accuracy of the road surface friction coefficient of the rear wheels and the front wheels.

(8) When the absolute value of the detected value of the front wheel SAT is smaller than a predetermined threshold value near 0, or when the front wheel SAT estimation error is larger than the predetermined threshold value, the tire ground contact state estimating device The road surface friction coefficient of the rear wheels and the front wheels is corrected so that the estimation error and the lateral acceleration estimation error are reduced.
As described above, by adjusting the correction weighting according to the front wheel SAT detection value or the front wheel SAT estimation error, it is possible to improve the estimation accuracy of the road surface friction coefficient of the rear wheels and the front wheels.

(9) When the absolute value of the lateral acceleration detection value is smaller than a predetermined threshold value near 0, or when the lateral acceleration estimation error is larger than a predetermined threshold value, the tire ground contact state estimation device determines the front wheel SAT estimation error. Further, the road surface friction coefficient of the rear wheels and the front wheels is corrected so that the rear wheel slip ratio estimation error is reduced.
Thus, by adjusting the correction weighting according to the lateral acceleration detection value or the lateral acceleration estimation error, it is possible to improve the estimation accuracy of the road surface friction coefficient of the rear wheels and the front wheels.

<< Second Embodiment >>
"Constitution"
In the second embodiment, the front wheel SAT estimated value, the rear wheel wheel speed estimated value, and the yaw rate estimated value are output, and according to these estimation errors, the vehicle slip angle, the front wheel road surface friction coefficient, the rear wheel road surface The coefficient of friction is estimated.
FIG. 6 is a system configuration diagram of the second embodiment.
In the present embodiment, the turning angle detection unit 110, the rear wheel braking / driving torque detection unit 111, the vehicle speed detection unit 120, the vehicle output estimation unit 130, the front wheel road surface friction coefficient estimation unit 150, and the rear wheel road surface friction coefficient. An estimation unit 160, a front wheel SAT detection unit 170, a rear wheel speed detection unit 181, a yaw rate detection unit 191, and an estimation error calculation unit 200 are provided.

With respect to the above components, the description of the elements common to the first embodiment will be omitted, and the blocks that are changed in the present embodiment will be described in detail.
The rear wheel speed detector 181 detects the rear wheel speed.
The yaw rate detector 191 detects the yaw rate. For example, the yaw rate may be detected by referring to a yaw rate sensor detection value provided in a vehicle side slip prevention device that is installed in many existing commercial vehicles.
The estimation error calculation unit 200 calculates the difference between the front wheel SAT estimated value and the front wheel SAT detected value, the difference between the rear wheel wheel speed estimated value and the rear wheel wheel speed detected value, and the difference between the yaw rate estimated value and the yaw rate detected value. That is, the estimation error _ek is calculated by the following equation.

The superscript T indicates vector transposition. As in the first embodiment, the estimation error _ek is used by the vehicle output estimation unit 130 to estimate the vehicle slip angle and the yaw rate, and the front wheel surface friction coefficient estimation unit 150 and the rear wheel surface friction coefficient estimation unit 160 are used. Is used to estimate the front wheel road surface friction coefficient and the rear wheel road surface friction coefficient.

FIG. 7 is a system configuration diagram of the vehicle output estimation unit showing the second embodiment.
The vehicle output estimation unit 130 is based on the turning angle detection value, the rear wheel braking / driving torque detection value, the vehicle speed detection value, the front wheel road surface friction coefficient detection value, the rear wheel road surface friction coefficient detection value, and the estimation error. Thus, the vehicle body slip angle, the front wheel SAT, the rear wheel speed, and the yaw rate are estimated.
The yaw rate estimation unit 132 estimates the yaw rate based on the front wheel lateral force estimated value, the rear wheel lateral force estimated value, and the rear wheel longitudinal force estimated value, and becomes an output of the vehicle output estimating unit 130.
The tire output estimating unit 133 is configured to detect a turning angle detection value, a rear wheel braking / driving torque detection value, a vehicle body slip angle estimation value, a yaw rate estimation value, a front wheel road surface friction coefficient estimation value, and a rear wheel road surface friction coefficient estimation value. Based on the above, the front wheel SAT estimated value and the rear wheel wheel speed estimated value are output.

The slip angle estimation unit 131 estimates the slip angle, the yaw rate estimation unit 132 estimates the yaw rate, the tire output estimation unit 133 estimates the rear wheel speed, and the front wheel road surface friction coefficient estimation unit 150 estimates the front wheel road surface friction coefficient. The estimation of the rear wheel road surface friction coefficient in the rear wheel road surface friction coefficient estimation unit 160 is performed according to the principle described in the first embodiment. The gain to be multiplied by the estimation error is determined as follows. Using the state vector x _k = [β _k r _k ω _rk μ _fk μ _rk ] ^T , the numbers used to estimate the body slip angle, yaw rate, rear wheel speed, front wheel friction coefficient, and rear wheel friction coefficient are summarized. State space can be expressed as the following equation.

Here, the input is u _k = [δ _k T _rk ], and the gain L is L _k = [Lβ _k L _rk Lω _k Lμ _fk Lμ _rk ] ^T. This formula shows that the time k + 1 in state x ^ k _{+ 1} is the state x ^ _k in the previous discrete time k input u _k, and the estimated error e _k, which is determined.
The system output is _defined as y _k = [M _zk ω _k r _k ] ^T. The output y _k is algebraically calculated by the vehicle slip angle, yaw rate, rear wheel speed, front and rear wheel road surface friction coefficient, and vehicle input u _k included in the state vector x ^ _k. Can be expressed as

  Based on the above equation, the Jacobian of the system is calculated as:

Based on this Jacobian, an appropriate gain can be determined by using, for example, a Kalman filter algorithm at each calculation step.
<Action>
According to the configuration of the present embodiment, each state is estimated based on the yaw rate error. Therefore, even when it is difficult to detect the lateral acceleration required in the first embodiment, it can be performed. In the rear wheel slip state, the slip ratio may be detected as described in the first embodiment, or the wheel speed may be detected as in the present embodiment.
Other functions and effects are the same as those of the first embodiment described above.

"effect"
As described above, the rear wheel speed detection unit 181 corresponds to the “non-steered wheel slip state detection unit”, and the yaw rate detection unit 191 corresponds to the “turning state detection unit”. Further, the wheel speed estimation unit 139 of the tire output estimation unit 133 in the vehicle output estimation unit 130 and the calculations of Equations 25 to 27 correspond to the “non-steered wheel slip state estimation means”, and the yaw rate estimation in the vehicle output estimation unit 130 The unit 132 and the calculations of Equations 6 to 8 correspond to “turning state estimation means”.
In the following, effects unique to the present embodiment will be described. In addition, the same operational effects as those of the first embodiment can be obtained for portions having the same configuration as that of the first embodiment.

(1) The tire ground contact state estimating device estimates the road surface friction coefficient of the front wheels and the rear wheels, estimates the front wheel SAT estimated value based on the turning angle, the vehicle speed, and the road surface friction coefficient of the front wheel, and based on the vehicle speed. The estimated wheel speed of the rear wheel is estimated, and the estimated yaw rate of the vehicle is estimated based on the turning angle, the vehicle speed, and the road surface friction coefficient of the front and rear wheels. On the other hand, a front wheel self-aligning torque detection value is detected, a rear wheel speed detection value is detected, and a vehicle yaw rate detection value is detected. Then, the front wheel SAT estimation error defined by the difference between the estimated value of the front wheel SAT and the detected value is calculated, and the rear wheel speed estimation error defined by the difference between the estimated value of the rear wheel speed and the detected value is calculated. Then, the yaw rate estimation error defined by the difference between the estimated value of the yaw rate and the detected value is calculated. Then, the road surface friction coefficient of the front wheels and the rear wheels is corrected according to at least one of the front wheel SAT estimation error, the rear wheel speed estimation error, and the yaw rate estimation error.
Thus, the road surface friction coefficient is included by updating the estimated value of the road surface friction coefficient of the front wheels and the rear wheels according to at least one of the estimation errors of the front wheel SAT, the rear wheel speed, and the yaw rate. In addition, the estimation accuracy of the tire contact state can be improved.

<< Third embodiment >>
"Constitution"
In the third embodiment, a tire ground contact state estimating device when braking force is applied to four wheels will be described. Since this embodiment includes the same elements as the first embodiment, different elements will be described.
FIG. 8 is a schematic configuration diagram of a vehicle showing the third embodiment.
In this embodiment, brake pressure sensors 141HL and 141HR are provided on the left rear wheel and the right rear wheel, respectively.

FIG. 9 is a system configuration diagram of the tire ground contact state estimation device showing the third embodiment.
The rear wheel braking / driving torque detector 111 detects the rear wheel braking / driving torque. From the current of the rear wheel drive motor to the braking / driving torque generated by the motor calculated in consideration of the torque coefficient of the drive motor, for example, the braking torque calculated via the map obtained experimentally in advance from the brake pressure Is added to detect the braking / driving torque acting on the rear wheels.

The front wheel slip ratio detection unit 112 detects the front wheel slip ratio during braking. During braking, the braking force acts on all the wheels, and no driven wheels exist, so it is difficult to estimate the vehicle speed from the driven wheels. Therefore, for example, the vehicle speed is calculated by integrating the longitudinal acceleration detected by the sensor, and the slip ratio of the front wheels is detected by comparing with the detected value of the wheel speed of the front wheels.
FIG. 10 is a system configuration diagram of a tire output estimation unit showing the third embodiment.

The tire output estimation unit 133 includes a tire slip angle estimation unit 134, a SAT estimation unit 135, a lateral force estimation unit 136, a lateral acceleration estimation unit 137, a longitudinal force estimation unit 138, a wheel speed estimation unit 139, A slip ratio estimation unit 140. In the present embodiment, the tire slip angle estimating unit 134, the lateral acceleration estimating unit 137, the longitudinal force estimating unit 138, the wheel speed estimating unit 139, and the slip rate estimating unit 140 are the same as those in the first embodiment.
The SAT estimation unit 135 estimates the front wheel SAT based on the braking force detection value, the front wheel road surface friction coefficient estimation value, and the front wheel slip angle estimation value. The front wheel SAT is obtained using a previously acquired SAT characteristic J _f (,). That is, it can be expressed by the following equation.

s _fk is a detected value of the front wheel slip ratio generated during braking. For example, when a brush model is used as the SAT characteristic, the front wheel SAT is calculated by the following equation at the time of braking.

However, ξ ^ _k is as follows.

Also, cos θ ^ _k is as follows.

In the lateral force estimation unit 136, a front wheel slip angle estimated value, a rear wheel slip angle estimated value, a front wheel road surface friction coefficient estimated value, a rear wheel friction coefficient estimated value, a turning angle detected value, and a front wheel slip ratio detected value And a front wheel lateral force estimated value and a rear wheel lateral force estimated value are calculated based on the rear wheel slip ratio estimated value.
The front wheel lateral force estimated value is determined according to the front wheel slip angle estimated value, the front wheel road surface friction coefficient estimated value, and the front wheel slip ratio detected value. That is, it is calculated by the following formula.

h _f (,) is a front wheel lateral force characteristic. For example, when a brush model is used, the lateral force when the slip ratio is generated can be calculated. The estimated rear wheel lateral force value is determined by the estimated rear wheel slip angle value, the estimated rear wheel road surface friction coefficient, and the estimated rear wheel slip ratio. That is, it is calculated by the following formula.

Various models can be used for the rear wheel lateral force characteristics h _r (,) as in the case of the front wheels.
<Action>
According to this embodiment, even when a braking force is applied to each wheel, the front wheel SAT and the front wheel lateral force are calculated in accordance with the front wheel slip coefficient, It is possible to accurately estimate the estimated value including the road surface friction coefficient.
Other functions and effects are the same as those of the first embodiment described above.

"effect"
From the above, the brake pressure sensors 141HL and 141HR and the rear wheel braking / driving torque detection unit 111 correspond to the “braking state detection unit”, and the front wheel slip ratio detection unit 112 corresponds to the “front wheel slip state detection unit”. Further, the SAT estimation unit 135 of the tire output estimation unit 133 and the calculations of Equations 43 and 44 in the vehicle output estimation unit 130 correspond to “steered wheel self-aligning torque estimation means”.
In the following, effects unique to the present embodiment will be described. In addition, the same operational effects as those of the first embodiment can be obtained for portions having the same configuration as that of the first embodiment.

(1) The tire ground contact state estimation device detects a front wheel slip ratio detection value according to a braking state, and based on the turning angle, the vehicle speed, the road surface friction coefficient of the front wheel, and the front wheel slip ratio detection value, the front wheel SAT estimation value The lateral acceleration estimated value is estimated based on the turning angle, the vehicle speed, the road surface friction coefficient of the rear wheels and the front wheels, and the detected value of the front wheel slip ratio.
Thus, since the front wheel SAT and lateral acceleration are estimated in consideration of the detected value of the front wheel slip ratio during braking, the front wheel SAT and lateral acceleration can be accurately estimated even when braking force acts on the four wheels. Can do. Accordingly, it is possible to improve the estimation accuracy of the front wheel road surface friction coefficient and the rear wheel road surface friction coefficient which are corrected using the front wheel SAT and the lateral acceleration.

<< 4th embodiment >>
"Constitution"
In the fourth embodiment, the left rear wheel road surface friction coefficient and the right rear wheel road surface friction coefficient are estimated independently when the slip ratio and the drive torque can be detected independently for the left and right wheels for the rear wheel.
In addition, description is abbreviate | omitted about the component same as 1st embodiment, and a different element is demonstrated.
FIG. 11 is a schematic configuration diagram of a vehicle showing the fourth embodiment.
The vehicle of the present embodiment includes drive motors 107HL and 107HR as drive force generation sources, and the drive motor output shaft is connected to the rear wheels 104HRL and 104HRR via the reduction gears 106HL and 106HR. Drive the wheels independently.

FIG. 12 is a system configuration diagram of the tire ground contact state estimation device showing the fourth embodiment.
The left rear wheel braking / driving torque detector 114 detects the left rear wheel braking / driving torque. For example, the braking / driving torque is detected by measuring the current value of the left wheel drive motor and considering the torque coefficient.
In the same manner, the right rear wheel braking / driving torque detecting unit 113 detects the right rear wheel braking / driving torque.

FIG. 13 is a system configuration diagram of a tire output estimation unit according to the fourth embodiment.
In the tire output estimation unit 133, a slip angle estimation value, a yaw rate estimation value, a turning angle detection value, a left rear wheel braking drive torque detection value, a right rear wheel braking drive torque detection value, and a front wheel road surface friction coefficient estimation Value, left rear wheel road surface friction coefficient estimated value, right rear wheel road surface friction coefficient estimated value, and estimation error, front wheel SAT estimated value, left rear wheel slip ratio estimated value, right rear wheel slip ratio The estimated value, lateral acceleration estimated value, front wheel lateral force, rear wheel lateral force, and rear wheel longitudinal force are estimated.

In the lateral force estimation unit 136, a front wheel road surface friction coefficient estimated value, a front wheel slip angle estimated value, a rear wheel slip angle estimated value, a left rear wheel road surface friction coefficient estimated value, a right rear wheel road surface friction coefficient estimated value, The front wheel lateral force and the rear wheel lateral force are estimated based on the detected turning angle value and the left and right rear wheel slip ratio estimated value.
The front wheel lateral force estimated value is determined according to the front wheel slip angle estimated value and the front wheel road surface friction coefficient estimated value. That is, it is calculated by the following formula.

h _f (,) is a front wheel lateral force characteristic. For example, as a lateral force characteristic, for example, a filar model is used as described in the first embodiment. Further, as the lateral force characteristic, a magic formula or a numerical map obtained experimentally may be used. The left and right rear wheel lateral force estimated values are determined by the rear wheel slip angle estimated value, the rear wheel road surface friction coefficient estimated value, and the rear wheel slip ratio estimated value. That is, the left rear wheel lateral force is calculated by the following equation.

  The right rear wheel lateral force is calculated by the following equation.

Various models can be used for the rear wheel lateral force characteristics h _r (,) as in the case of the front wheels.
The lateral acceleration estimation unit 137 calculates the lateral acceleration using the following equation based on the front wheel lateral force estimated value and the left and right rear wheel lateral force estimated values.

  The longitudinal force estimation unit 138 estimates the left and right rear wheel longitudinal forces based on the left rear wheel road surface friction coefficient estimated value, the right rear wheel road surface friction coefficient estimated value, and the left and right rear wheel slip ratio estimated values. The left rear wheel lateral force is calculated by the following equation.

  The right rear wheel lateral force is calculated by the following equation.

The wheel speed estimation unit 139 estimates the left and right wheel speed estimation values based on the left and right rear wheel braking drive torque detection values, the left and right rear wheel longitudinal force estimation values, and the estimation error calculated by the estimation error calculation unit 200. .
First, the dynamics of the wheel speed when the braking / driving torque acts on the left rear wheel is given by the following equation.

  When this equation is discretized using, for example, the Euler method, the following equation is obtained.

  Δt is the sample time. Based on the discrete time dynamics, the rear wheel speed is calculated according to the estimation error. That is, the rear wheel speed is calculated by the following equation.

Here, e _k is an estimation error. L _rl ω _k is a gain vector related to the left wheel speed, and the determination method will be described in detail later.
On the other hand, the wheel speed is similarly calculated for the right rear wheel. That is, it is calculated by the following equation.

  The slip ratio estimation unit 140 calculates the left and right rear wheel slip ratios based on the left and right wheel speed estimation values and the vehicle speed detection value. First, the left rear wheel slip ratio is calculated by the following equation.

  Similarly, the right rear wheel slip ratio is calculated by the following equation.

In the denominator, the vehicle body speed and the rear wheel speed are compared and a larger value is selected. In general, the vehicle speed is higher during braking and the wheel speed is higher during driving.
The left rear wheel road surface friction coefficient estimation unit 161 in FIG. 12 estimates the left rear wheel road surface friction coefficient from the estimation error based on the road surface friction coefficient dynamics model. Assuming that the road friction coefficient is piecewise constant, the road friction coefficient dynamics model is defined as:

  Based on an equation obtained by discretizing this equation, a left rear wheel road surface friction coefficient is estimated according to an estimation error. That is, the front wheel road surface friction coefficient is estimated by the following equation.

Here, a method for determining the gain Lμ _rlk will be described later.
The right rear wheel road surface friction coefficient estimation unit 162 estimates the right rear wheel road surface friction coefficient from the estimation error based on the road surface friction coefficient dynamics model. Assuming that the road friction coefficient is piecewise constant, the road friction coefficient dynamics model is defined as:

  Based on an equation obtained by discretizing this equation, a left rear wheel road surface friction coefficient is estimated according to an estimation error. That is, the front wheel road surface friction coefficient is estimated by the following equation.

Here, a method for determining the gain Lμ _rlk will be described later.
In the estimation error calculator 200, the difference between the front wheel SAT estimated value estimated by the vehicle output estimator 130, the front wheel SAT detected value detected by the front wheel SAT detector 170, and the left rear estimated by the vehicle output estimator 130. The difference between the wheel slip ratio estimated value, the left rear wheel slip ratio detected value detected by the left rear wheel slip ratio detecting unit 183, the right rear wheel slip ratio estimated value estimated by the vehicle output estimating unit 130, and the right rear The difference between the right rear wheel slip ratio detection value detected by the wheel slip ratio detection unit 182, the lateral acceleration estimation value estimated by the vehicle output estimation unit 130, and the lateral acceleration detection detected by the rear wheel slip ratio detection unit 180 Calculate the difference in values.
That is, the estimation error _ek is calculated by the following equation.

The superscript T indicates vector transposition. The estimation error e _y is used in the vehicle output estimation unit to estimate the vehicle slip angle and the yaw rate. In the front wheel road surface friction coefficient estimation unit and the rear wheel road surface friction coefficient estimation unit, the front wheel road surface friction coefficient and the rear wheel surface friction coefficient are used. Used for coefficient estimation.
Next, a method for setting a gain used for calculating each estimated value will be described.
Using the state vector x _k = [β _k r _k ω _rlk ω _rrk μ _fk μ _rlk μ _rrk ], body slip angle, yaw rate, left rear wheel speed, right rear wheel speed, front wheel road friction coefficient, left rear When the expressions used for estimating the road surface friction coefficient and the right rear wheel road surface friction coefficient are collectively expressed, the following expression can be obtained.

Here, the input is u _k = [δ _k T _rlk T _rrk ], and the gain L _k is expressed by the following equation.

This formula shows that the time k + 1 in state x ^ k _{+ 1} is the state x ^ _k in the previous discrete time k input u _k, and the estimated error e _k, which is determined.
The system output is _defined as y _k = [M _zk s _rlk s _rrk a _yk ] ^T. The output y _k algebraically depends on the vehicle slip angle, yaw rate, left and right rear wheel speed, front wheel road surface friction coefficient, left and right rear wheel road surface friction coefficient, and vehicle input u _k included in the state vector x ^ _k. Since it is calculated, it can be expressed by the following equation.

  Based on the above equation, the system Jacobian matrix is calculated as:

Using this Jacobian matrix, the gain L _k is determined by the method described in the first embodiment.
In the present embodiment, since the road surface friction coefficient of the left and right rear wheels is independently estimated based on the rear wheel slip ratio detected independently on the left and right, each road friction coefficient is different between the left and right wheels. The road surface friction coefficient can be accurately estimated, and the estimation accuracy of the vehicle slip angle can also be improved.

<Action>
In this embodiment, the left rear wheel slip ratio s _rl and the right rear wheel slip ratio s _rr are estimated separately, and the left rear wheel road surface friction coefficient μ ^ _rl and the right rear wheel road friction coefficient μ ^ _rr are _calculated . By estimating separately, the left rear wheel slip ratio s _rl and the right rear wheel slip ratio s _rr are individually detected, and the left rear wheel slip ratio estimation error and the right rear wheel slip ratio estimation error are estimated separately. Even when the road surface friction coefficient differs between the left and right wheels, the road surface friction coefficient of each wheel can be accurately estimated, and the estimation accuracy of the vehicle slip angle can also be improved.
Other functions and effects are the same as those of the first embodiment described above.

"effect"
From the above, the slip rate estimating unit 140 of the tire output estimating unit 133 and the calculations of Equations 59 and 60 in the vehicle output estimating unit 130 correspond to the “non-steered wheel slip state estimating means”, and the left rear wheel road surface friction coefficient estimation. 161, right rear wheel road surface friction coefficient estimating unit 162, and equations 62 and 64 correspond to “road surface friction coefficient estimating means”, and left rear wheel slip rate detecting unit 183 and right rear wheel slip rate detecting unit 182 Corresponding to “non-steered wheel slip state detecting means”, the estimation error calculating unit 200 and the calculation of Expression 65 correspond to “non-steered wheel slip state estimating error calculating means”.
In the following, effects unique to the present embodiment will be described. In addition, the same operational effects as those of the first embodiment can be obtained for portions having the same configuration as that of the first embodiment.

(1) The tire ground contact state estimating device estimates the slip ratio of the left rear wheel and the right rear wheel separately, estimates the road surface friction coefficient of the left rear wheel and the right rear wheel individually, and determines the left rear wheel and the right rear wheel. Are separately detected, and slip rate estimation errors of the left rear wheel and the right rear wheel are individually calculated.
In this way, by calculating the slip ratio, road friction coefficient, and slip ratio estimation error for the rear wheels separately for the left and right wheels, even if the values for the left and right wheels are different, the slip ratio and the road surface friction coefficient are estimated. The accuracy and the calculation accuracy of the slip ratio estimation error can be improved. Accordingly, it is possible to improve the estimation accuracy of the tire contact state estimated using the slip ratio, the road surface friction coefficient, and the slip ratio estimation error.

<< 5th embodiment >>
"Constitution"
In the first embodiment to the fourth embodiment, the configuration in which the vehicle body slip angle and the front and rear wheel road surface friction coefficient are estimated at the same time has been described, but in the fifth embodiment, these are not estimated at the same time, and the road surface friction coefficient is estimated. A value obtained by calculating the necessary slip angle in the previous calculation step is used.
Since the vehicle configuration necessary to realize this embodiment is the same as that of the first embodiment, description thereof is omitted.

FIG. 15 is a system configuration diagram of the tire ground contact state estimation device showing the fifth embodiment.
The vehicle output estimator 130 estimates the front wheel SAT and the rear wheel slip ratio based on the detected steering angle value, the detected vehicle speed, the front wheel road surface friction coefficient estimated value, and the rear wheel road surface friction coefficient estimated value. Value, lateral acceleration estimated value, and vehicle slip angle estimated value are estimated.
FIG. 16 is a system configuration diagram of a vehicle output estimation unit according to the fifth embodiment.
The vehicle slip angle estimation unit 131 estimates the vehicle slip angle based on the front wheel lateral force estimated value, the rear wheel lateral force estimated value, and the vehicle speed detection value. The vehicle slip angle is estimated using the following equation obtained by discretizing the dynamics of the vehicle slip angle described in the first embodiment.

  The yaw rate estimation unit 132 estimates the yaw rate based on the front wheel lateral force estimated value, the rear wheel lateral force estimated value, and the left and right rear wheel longitudinal force estimated values. The yaw rate is estimated using the following equation obtained by discretizing the dynamics of the yaw rate described in the first embodiment. That is, it is calculated by the following formula.

In the tire output estimation unit 133, a vehicle speed detection value, a vehicle slip angle estimation value, a yaw rate estimation value, a turning angle detection value, a rear wheel drive torque detection value, a front wheel road surface friction coefficient estimation value, and a rear wheel road surface Based on the friction coefficient estimated value, the front wheel SAT estimated value, the rear wheel slip rate estimated value, the lateral acceleration estimated value, the body slip angle estimating unit 131, the front wheel lateral force estimated value, and the rear wheel lateral force estimated value, The rear wheel longitudinal force estimated value, the front wheel tire slip angle, the rear wheel longitudinal force estimated value, and the rear wheel slip angle estimated value are estimated and output.
The wheel speed estimation unit 139 estimates the wheel speed estimation value based on the rear wheel longitudinal force estimation value and the rear wheel braking / driving torque detection value.
The wheel speed is estimated using an expression obtained by discretizing the dynamics of the wheel speed described in the first embodiment. That is, the rear wheel speed is calculated by the following equation.

The other components included in the tire output estimating unit 133 are the same as those in the first embodiment, and thus the description thereof is omitted.
The front wheel road surface friction coefficient estimation unit 150 estimates the front wheel road surface friction coefficient based on the front wheel tire slip angle, the front wheel SAT estimated value, and the estimation error. First, a first component of the estimated wheel SAT detection value error _{e k = [M zk -M ^} zk s k -s ^ k a yk -a ^ yk] T, it is calculated from the front wheel SAT estimated value. That is, the following formula is used for calculation.

e (1) _k represents the first component of the estimation error.
Further, for example, according to the filar model, the front wheel SAT is calculated by the following equation.

However, φ ^ _k is as follows.

  The front wheel road surface friction coefficient is estimated using an equation obtained by solving this formula for the front wheel road surface friction coefficient. That is, it estimates using the following formula.

Unlike the first embodiment to the fourth embodiment, this embodiment does not define dynamics in the road surface friction coefficient. Therefore, when calculating the road surface friction coefficient, in order to avoid an algebraic loop, the input of the front wheel road surface friction coefficient estimation unit 150 needs to use a value in the previous discrete time.
In this example, the road surface friction coefficient is estimated based on the filar model. However, for example, the relationship from the SAT to the road surface friction coefficient may be estimated using a map obtained experimentally.
The rear wheel road surface friction coefficient estimating unit 160 determines the rear wheel tire slip angle, the rear wheel tire lateral force estimated value, the rear wheel tire longitudinal force estimated value, the rear wheel slip ratio estimated value, and the estimated error from the rear wheel. Estimate the road friction coefficient.
First, calculated from the rear wheel slip rate estimated value, and the second component of the estimated error _{e k = [M zk -M ^} zk s rk -s ^ rk a yk -a ^ yk] T, the slip rate estimated value . That is, the following formula is used for calculation.

e (2) _k represents the second component of the estimation error. Assume that the rear wheel tire force characteristics can be modeled by, for example, a brush model.
In order to obtain the road surface friction coefficient, first, the tire force adhesion ratio P ^ _rk defined by the following equation is calculated.

However, the rear wheel tire force F _rk-1 , which is the resultant of the rear wheel longitudinal force and the rear wheel lateral force, is calculated from the rear wheel longitudinal force estimated value and the rear wheel lateral force estimated value by the following equation.

The tire force adhesion ratio has the following relationship with the tire adhesion area length ξ ^ _k .

Solve this equation for ξ ^ _k . Specifically, for example, ξ ^ _k can be _obtained by using a numerical calculation algorithm such as Newton's method. Further, a road surface friction coefficient is calculated from the obtained ξ ^ _k based on the following equation.

<Action>
In the tire ground contact state estimation device according to the present embodiment, the relationship between the SAT and the front wheel road surface friction coefficient and the slip ratio from the rear wheel road surface friction coefficient are derived from the tire models, respectively, and using these, the SAT and the slip ratio are directly back and forth. Since it is the structure which calculates the road surface friction coefficient of a wheel, the calculation of the Jacobian matrix for setting the gain which was required in 1st embodiment to 4th embodiment is unnecessary, and can reduce calculation amount more.

"effect"
From the above, the front wheel road surface friction coefficient estimation unit 150, the rear wheel road surface friction coefficient estimation unit 160, and the calculations of Equations 76 and 81 correspond to the “road surface friction coefficient estimation unit” and the “road surface friction coefficient correction unit”.
In the following, effects unique to the present embodiment will be described. In addition, the same operational effects as those of the first embodiment can be obtained for portions having the same configuration as that of the first embodiment.

(1) The tire ground contact state estimating device estimates the road surface friction coefficient of the rear wheel and the front wheel, estimates the front wheel SAT estimated value based on the turning angle, the vehicle speed, and the road surface friction coefficient of the front wheel, and based on the vehicle speed. Then, the estimated rear wheel slip ratio is estimated, and the estimated lateral acceleration of the vehicle is estimated based on the turning angle, the vehicle speed, and the road surface friction coefficient of the rear and front wheels. On the other hand, the front wheel SAT detection value is detected, the rear wheel slip ratio detection value is detected, and the vehicle lateral acceleration detection value is detected. Then, the front wheel SAT estimation error defined by the difference between the estimated value of the front wheel SAT and the detected value is calculated, and the rear wheel slip ratio estimated error defined by the difference between the estimated value of the rear wheel slip ratio and the detected value is calculated. The lateral acceleration estimation error defined by the difference between the lateral acceleration estimated value and the detected value is calculated. Then, the road surface friction coefficient of the rear wheels and the front wheels is corrected according to at least one of the front wheel SAT estimation error, the rear wheel slip ratio estimation error, and the lateral acceleration estimation error.

  Thus, the road surface friction coefficient is updated by updating the estimated value of the road surface friction coefficient of the rear wheels and the front wheels according to at least one of the estimation errors of the front wheel SAT, the rear wheel slip ratio, and the lateral acceleration. It is possible to improve the estimation accuracy of the ground contact state of the tire. In particular, the front wheel road surface friction coefficient is derived from the tire model from the front wheel SAT, and the rear wheel road surface friction coefficient is derived from the tire model from the rear wheel slip ratio, that is, the road surface of the front and rear wheels directly from the front wheel SAT and the rear wheel slip ratio. Since the friction coefficient is calculated, an increase in calculation load can be suppressed.

102H Drive circuit 103H Lithium ion battery 104HFL Left front wheel 104HFR Right front wheel 104HRL Left rear wheel 104HRL Right rear wheel 105HFL Left front wheel speed sensor 105HFR Right front wheel speed sensor 106H Reduction gear 106HL Left rear wheel reduction gear 106HR Right rear wheel reduction gear 107H Drive Motor 107HL Left rear wheel drive motor 107HR Right rear wheel drive motor 108H Lateral acceleration sensor 109H Yaw rate sensor 111H Steering wheel 112H Auxiliary steering motor 114H Steering gear 115H Torque sensor 121H Steering angle sensor 130H Integrated controller 141HL Brake pressure sensor 110 Steering angle detection Unit 111 rear wheel braking / driving torque detecting unit 112 front wheel slip ratio detecting unit 113 right rear wheel braking / driving torque detecting unit 114 left rear wheel braking / driving torque Detection unit 120 vehicle speed detection unit 130 vehicle output estimation unit 131 vehicle slip angle estimation unit 132 yaw rate estimation unit 133 tire output estimation unit 134 angle estimation unit 135 estimation unit 136 lateral force estimation unit 137 lateral acceleration estimation unit 138 longitudinal force estimation unit 139 Wheel speed estimation unit 140 Slip rate estimation unit 150 Front wheel road surface friction coefficient estimation unit 160 Rear wheel road surface friction coefficient estimation unit 161 Left rear wheel road surface friction coefficient estimation unit 162 Right rear wheel road surface friction coefficient estimation unit 170 Front wheel SAT detection unit 180 Rear wheel Slip rate detection unit 181 Rear wheel speed detection unit 182 Right rear wheel slip rate detection unit 183 Left rear wheel slip rate detection unit 190 Lateral acceleration detection unit 191 Yaw rate detection unit 200 Estimated error calculation unit

Claims (10)

A turning angle detecting means for detecting a turning angle of the turning wheel;
Vehicle speed detection means for detecting the vehicle speed;
Road surface friction coefficient estimating means for estimating road surface friction coefficients of steered wheels and non-steered wheels;
Vehicle slip angle estimating means for estimating the vehicle slip angle;
Vehicle slip angle estimated by the vehicle body slip angle estimating means, steering angle detected by the steering angle detecting means, and based on the vehicle speed detected by the vehicle speed detecting means, steered wheel slip angle estimating the steered wheels slip angle An estimation means;
Non-steered wheel slip angle estimating means for estimating a non-steered wheel slip angle based on the vehicle slip angle estimated by the vehicle body slip angle estimating means and the vehicle speed detected by the vehicle speed detecting means;
Based on the steered wheel slip angle estimated by the steered wheel slip angle estimating means and the road surface friction coefficient of the steered wheel estimated by the road surface friction coefficient estimating means, the steered wheel self aligning torque estimated value is estimated. Lining torque estimation means;
A non-steered wheel wheel that estimates a non-steered wheel speed based on a non-steered wheel slip angle estimated by the non-steered wheel slip angle estimating unit and a road surface friction coefficient of the non-steered wheel estimated by the road surface friction coefficient estimating unit Speed estimation means;
Non -steered wheel slip state estimating means for estimating a non-steered wheel slip state estimated value based on the non -steered wheel speed estimated by the non-steered wheel speed estimating means and the vehicle speed detected by the vehicle speed detecting means;
Based on the turning angle detected by the turning angle detection means, the vehicle speed detected by the vehicle speed detection means, and the road surface friction coefficient of the steered wheels and non-steered wheels estimated by the road surface friction coefficient estimation means, the turning state of the vehicle A turning state estimating means for estimating an estimated value;
Steering torque detection means for detecting steering torque;
A steered wheel self-aligning torque detecting means for detecting a self-aligning torque detection value of the steered wheel based on the steering torque detected by the steering torque detecting means and the steered angle of the steered wheel detected by the steered angle detecting means. When,
Non-steering wheel speed detecting means for detecting non-steering wheel speed;
Non -steered wheel slip state detection means for detecting a non-steered wheel slip state detection value based on the non -steered wheel speed detected by the non-steered wheel speed detection means and the vehicle speed detected by the vehicle speed detection means;
A turning state detecting means for detecting a turning state detection value of the vehicle;
A steered wheel defined by the difference between the steered wheel self-aligning torque estimated value estimated by the steered wheel self-aligning torque estimating means and the steered wheel self-aligning torque detected value detected by the steered wheel self-aligning torque detecting means. Steered wheel self-aligning torque estimation error calculating means for calculating self-aligning torque estimation error;
Non-steering wheel slip state estimation value defined by the difference between the non-steering wheel slip state estimation value estimated by the non-steering wheel slip state estimation unit and the non-steering wheel slip state detection value detected by the non-steering wheel slip state detection unit Non-steered wheel slip state estimation error calculating means for calculating an error;
A turning state estimation error calculating means for calculating a turning state estimation error defined by a difference between the vehicle turning state estimation value estimated by the turning state estimation means and the vehicle turning state detection value detected by the turning state detection means; ,
The steered wheel self-aligning torque estimation error computed by the steered wheel self-aligning torque estimation error computing means, the non-steered wheel slip state estimated error computed by the non-steered wheel slip state estimation error computing means, and the turning state estimated error computation Road surface friction coefficient correction means for correcting the road surface friction coefficient of the steered wheel and the non-steered wheel estimated by the road surface friction coefficient estimation means according to at least one of the turning state estimation errors calculated by the means ,
The road surface friction coefficient correction means is
When the absolute value of the slip state detection value is smaller than a predetermined threshold value near 0, or when the slip state estimation error is larger than a predetermined threshold value, the steered wheel self-aligning torque estimation error, and A tire ground contact state estimation device , wherein the road surface friction coefficient of the steered wheel and the non-steered wheel estimated by the road surface friction coefficient estimation means is corrected so that a turning state estimation error is reduced . A turning angle detecting means for detecting a turning angle of the turning wheel;
Vehicle speed detection means for detecting the vehicle speed;
Road surface friction coefficient estimating means for estimating road surface friction coefficients of steered wheels and non-steered wheels;
Vehicle slip angle estimating means for estimating the vehicle slip angle;
Vehicle slip angle estimated by the vehicle body slip angle estimating means, steering angle detected by the steering angle detecting means, and based on the vehicle speed detected by the vehicle speed detecting means, steered wheel slip angle estimating the steered wheels slip angle An estimation means;
Non-steered wheel slip angle estimating means for estimating a non-steered wheel slip angle based on the vehicle slip angle estimated by the vehicle body slip angle estimating means and the vehicle speed detected by the vehicle speed detecting means;
Based on the steered wheel slip angle estimated by the steered wheel slip angle estimating means and the road surface friction coefficient of the steered wheel estimated by the road surface friction coefficient estimating means, the steered wheel self aligning torque estimated value is estimated. Lining torque estimation means;
A non-steered wheel wheel that estimates a non-steered wheel speed based on a non-steered wheel slip angle estimated by the non-steered wheel slip angle estimating unit and a road surface friction coefficient of the non-steered wheel estimated by the road surface friction coefficient estimating unit Speed estimation means;
Non -steered wheel slip state estimating means for estimating a non-steered wheel slip state estimated value based on the non -steered wheel speed estimated by the non-steered wheel speed estimating means and the vehicle speed detected by the vehicle speed detecting means;
Based on the turning angle detected by the turning angle detection means, the vehicle speed detected by the vehicle speed detection means, and the road surface friction coefficient of the steered wheels and non-steered wheels estimated by the road surface friction coefficient estimation means, the turning state of the vehicle A turning state estimating means for estimating an estimated value;
Steering torque detection means for detecting steering torque;
A steered wheel self-aligning torque detecting means for detecting a self-aligning torque detection value of the steered wheel based on the steering torque detected by the steering torque detecting means and the steered angle of the steered wheel detected by the steered angle detecting means. When,
Non-steering wheel speed detecting means for detecting non-steering wheel speed;
Non -steered wheel slip state detection means for detecting a non-steered wheel slip state detection value based on the non -steered wheel speed detected by the non-steered wheel speed detection means and the vehicle speed detected by the vehicle speed detection means;
A turning state detecting means for detecting a turning state detection value of the vehicle;
A steered wheel defined by the difference between the steered wheel self-aligning torque estimated value estimated by the steered wheel self-aligning torque estimating means and the steered wheel self-aligning torque detected value detected by the steered wheel self-aligning torque detecting means. Steered wheel self-aligning torque estimation error calculating means for calculating self-aligning torque estimation error;
Non-steering wheel slip state estimation value defined by the difference between the non-steering wheel slip state estimation value estimated by the non-steering wheel slip state estimation unit and the non-steering wheel slip state detection value detected by the non-steering wheel slip state detection unit Non-steered wheel slip state estimation error calculating means for calculating an error;
A turning state estimation error calculating means for calculating a turning state estimation error defined by a difference between the vehicle turning state estimation value estimated by the turning state estimation means and the vehicle turning state detection value detected by the turning state detection means; ,
The steered wheel self-aligning torque estimation error computed by the steered wheel self-aligning torque estimation error computing means, the non-steered wheel slip state estimated error computed by the non-steered wheel slip state estimation error computing means, and the turning state estimated error computation Road surface friction coefficient correction means for correcting the road surface friction coefficient of the steered wheel and the non-steered wheel estimated by the road surface friction coefficient estimation means according to at least one of the turning state estimation errors calculated by the means ,
The road surface friction coefficient correction means is
When the absolute value of the detected value of the steered wheel self-aligning torque is smaller than a predetermined threshold value near zero, or when the estimated error value of the steered wheel self-aligning torque is larger than a predetermined threshold value, the non-steered wheel A tire ground contact state estimation device , wherein the road surface friction coefficient of the steered wheel and the non-steered wheel estimated by the road surface friction coefficient estimation unit is corrected so that the slip state estimation error and the turning state estimation error are reduced . A turning angle detecting means for detecting a turning angle of the turning wheel;
Vehicle speed detection means for detecting the vehicle speed;
Road surface friction coefficient estimating means for estimating road surface friction coefficients of steered wheels and non-steered wheels;
Vehicle slip angle estimating means for estimating the vehicle slip angle;
Vehicle slip angle estimated by the vehicle body slip angle estimating means, steering angle detected by the steering angle detecting means, and based on the vehicle speed detected by the vehicle speed detecting means, steered wheel slip angle estimating the steered wheels slip angle An estimation means;
Non-steered wheel slip angle estimating means for estimating a non-steered wheel slip angle based on the vehicle slip angle estimated by the vehicle body slip angle estimating means and the vehicle speed detected by the vehicle speed detecting means;
Based on the steered wheel slip angle estimated by the steered wheel slip angle estimating means and the road surface friction coefficient of the steered wheel estimated by the road surface friction coefficient estimating means, the steered wheel self aligning torque estimated value is estimated. Lining torque estimation means;
A non-steered wheel wheel that estimates a non-steered wheel speed based on a non-steered wheel slip angle estimated by the non-steered wheel slip angle estimating unit and a road surface friction coefficient of the non-steered wheel estimated by the road surface friction coefficient estimating unit Speed estimation means;
Non -steered wheel slip state estimating means for estimating a non-steered wheel slip state estimated value based on the non -steered wheel speed estimated by the non-steered wheel speed estimating means and the vehicle speed detected by the vehicle speed detecting means;
Based on the turning angle detected by the turning angle detection means, the vehicle speed detected by the vehicle speed detection means, and the road surface friction coefficient of the steered wheels and non-steered wheels estimated by the road surface friction coefficient estimation means, the turning state of the vehicle A turning state estimating means for estimating an estimated value;
Steering torque detection means for detecting steering torque;
A steered wheel self-aligning torque detecting means for detecting a self-aligning torque detection value of the steered wheel based on the steering torque detected by the steering torque detecting means and the steered angle of the steered wheel detected by the steered angle detecting means. When,
Non-steering wheel speed detecting means for detecting non-steering wheel speed;
Non -steered wheel slip state detection means for detecting a non-steered wheel slip state detection value based on the non -steered wheel speed detected by the non-steered wheel speed detection means and the vehicle speed detected by the vehicle speed detection means;
A turning state detecting means for detecting a turning state detection value of the vehicle;
A steered wheel defined by the difference between the steered wheel self-aligning torque estimated value estimated by the steered wheel self-aligning torque estimating means and the steered wheel self-aligning torque detected value detected by the steered wheel self-aligning torque detecting means. Steered wheel self-aligning torque estimation error calculating means for calculating self-aligning torque estimation error;
Non-steering wheel slip state estimation value defined by the difference between the non-steering wheel slip state estimation value estimated by the non-steering wheel slip state estimation unit and the non-steering wheel slip state detection value detected by the non-steering wheel slip state detection unit Non-steered wheel slip state estimation error calculating means for calculating an error;
A turning state estimation error calculating means for calculating a turning state estimation error defined by a difference between the vehicle turning state estimation value estimated by the turning state estimation means and the vehicle turning state detection value detected by the turning state detection means; ,
The steered wheel self-aligning torque estimation error computed by the steered wheel self-aligning torque estimation error computing means, the non-steered wheel slip state estimated error computed by the non-steered wheel slip state estimation error computing means, and the turning state estimated error computation Road surface friction coefficient correction means for correcting the road surface friction coefficient of the steered wheel and the non-steered wheel estimated by the road surface friction coefficient estimation means according to at least one of the turning state estimation errors calculated by the means ,
The road surface friction coefficient correction means is
When the absolute value of the turning state detection value is smaller than a predetermined threshold value near 0, or when the turning state estimation error is larger than a predetermined threshold value, the steered wheel self-aligning torque estimation error, and A tire ground contact state estimation device for correcting a road surface friction coefficient of a steered wheel and a non-steered wheel estimated by the road surface friction coefficient estimating means so that a non-steered wheel slip state estimation error is reduced . Before SL steered wheel aligning torque estimated error calculating unit steerable wheels calculated in the self-aligning torque estimation error, the non-steered wheel slip condition estimation error non steered wheel slip state estimation error calculated by the calculating means, the turning state estimation error The vehicle slip angle correcting means for correcting the vehicle slip angle estimated by the vehicle slip angle estimating means according to at least one of the turning state estimation errors calculated by the calculating means. The tire ground contact state estimation device according to any one of 1 to 3 . The estimation of the road surface friction coefficient by the road surface friction coefficient estimation unit and the estimation of the vehicle body slip angle by the vehicle body slip angle estimation unit are performed in the same calculation cycle . The tire ground contact state estimation device according to one item . A yaw rate estimating means for estimating the yaw rate;
The steered wheel self-aligning torque estimation error computed by the steered wheel self-aligning torque estimation error computing means, the non-steered wheel slip state estimated error computed by the non-steered wheel slip state estimation error computing means, and the turning state estimated error computation 6. A yaw rate correction unit that corrects the yaw rate estimated by the yaw rate estimation unit according to at least one of the turning state estimation errors calculated by the unit. 6. The tire ground contact state estimation device according to Item. Driving wheel wheel speed estimating means for estimating the wheel speed of the driving wheel;
The steered wheel self-aligning torque estimation error computed by the steered wheel self-aligning torque estimation error computing means, the non-steered wheel slip state estimated error computed by the non-steered wheel slip state estimation error computing means, and the turning state estimated error computation Non-steering wheel speed correcting means for correcting the driving wheel speed estimated by the driving wheel speed estimation means according to at least one of the turning state estimation errors calculated by the means, The tire ground contact state estimation device according to any one of claims 1 to 6 . The tire ground contact state estimation device according to any one of claims 1 to 7 , wherein the road surface friction coefficient estimation means includes a dynamic characteristic model in which a first-order derivative with respect to time is defined as zero. Braking state detecting means for detecting a braking state;
A steered wheel slip state detection unit that detects a steered wheel slip state detection value according to the braking state detected by the braking state detection unit,
The steered wheel self-aligning torque estimating means is
The turning angle detected by the turning angle detection means, the vehicle speed detected by the vehicle speed detection means, the road surface friction coefficient of the turning wheel estimated by the road surface friction coefficient estimation means, and the turning wheel detected by the turning wheel slip state detection means Based on the slip state detection value, estimate the steered wheel self-aligning torque estimated value,
The turning state estimating means includes
The turning angle detected by the turning angle detection means, the vehicle speed detected by the vehicle speed detection means, the road surface friction coefficient of the steered wheels and non-steering wheels estimated by the road surface friction coefficient estimation means, and the steered wheel slip state detection means The tire ground contact state estimation device according to any one of claims 1 to 8 , wherein the estimated turning state estimated value of the vehicle is estimated based on the detected detected value of the steered wheel slip state. The non-steered wheel slip state estimating means individually estimates the slip state of the left non-steered wheel and the right non-steered wheel,
The road surface friction coefficient estimating means individually estimates the road surface friction coefficient of the left non-steered wheel and the right non-steered wheel,
The non-steered wheel slip state detecting means individually detects the slip state of the left non-steered wheel and the right non-steered wheel,
The tire according to any one of claims 1 to 9 , wherein the non-steered wheel slip state estimation error calculating means individually calculates a slip state estimation error of the left non-steered wheel and the right non-steered wheel. Ground state estimation device.

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