JP6628702B2 - Vehicle state quantity estimation device - Google Patents

Description

  The present invention relates to a vehicle state quantity estimation device that estimates a state quantity of a vehicle.

  State quantities such as sideslip angle, lateral speed, and roll angle of the vehicle body, which are difficult to detect directly with sensors, are estimated using detection values from inertial sensors and vehicle motion models, but due to errors in model parameters, etc. An estimation error occurs. Conventionally, in order to reduce the estimation error, in addition to correcting the estimation value using an observer or a Kalman filter, for example, a relative yaw directly detected using an external recognition unit such as a camera or GPS described in Patent Document 1 is used. There is known a method of estimating a vehicle state quantity that corrects an estimated sideslip angle using an angle.

Patent No. 5402244

  However, in the method of estimating the state of a vehicle described in Patent Literature 1, a high-precision estimated value can be obtained under favorable environmental conditions, but the estimated value can be obtained under bad conditions such as rainy weather, which is difficult to detect by the outside world recognition means. It cannot be corrected and the accuracy may be significantly reduced.

  The present invention is to solve the above-mentioned problem, and highly accurately estimates a state quantity such as a side slip angle, a lateral speed, and a roll angle of a vehicle body even under bad conditions where the external recognition means is difficult to detect. It is an object of the present invention to provide a vehicle state quantity estimating device capable of performing the above.

  In order to achieve the above object, a vehicle state quantity estimating apparatus according to the present invention is configured such that a detection value of an inertial sensor and a detection value of an external recognition unit are input, and the detection value of the inertia sensor and a preset vehicle parameter are used. In the vehicle state quantity estimating apparatus for outputting the state quantity of the vehicle, the vehicle parameter is updated using a detection value of the external world recognition means.

  According to the present invention, a vehicle state quantity can be estimated with high accuracy.

The conceptual diagram of the vehicle state quantity estimation apparatus 1. The figure which shows a four-wheeled vehicle model. The figure which shows the equivalent two-wheeled vehicle model of a four-wheeled vehicle. The figure which shows the roll motion accompanying the lateral acceleration which acts on the center-of-gravity point 11. FIG. The figure which shows the pitch motion accompanying longitudinal acceleration which acts on the center of gravity 11. The figure which shows the positional relationship of a center of gravity etc. FIG. 1 is a diagram showing a vehicle configuration equipped with a vehicle state quantity estimation device 1 according to a first embodiment. 5 is a flowchart showing an outline of processing by the vehicle state quantity estimation device 1 according to the first embodiment. 5 is a flowchart showing stability determination by the vehicle state quantity estimation device 1 according to the first embodiment. 5 is a flowchart showing parameter updating by the vehicle state quantity estimation device 1 according to the first embodiment. FIG. 5 is a diagram showing a time change of a processing result by the vehicle state quantity estimation device 1 according to the first embodiment. FIG. 4 is a diagram illustrating a positional relationship of a center of gravity point 11 with respect to a coordinate system fixed to the ground according to the first embodiment. FIG. 3 is a diagram illustrating a locus of a center of gravity 11 during a steady circular turn according to the first embodiment. 9 is a flowchart illustrating stability determination by the vehicle state quantity estimation device 1 according to the second embodiment. FIG. 9 is a diagram showing a time change of a processing result by the vehicle state quantity estimation device 1 according to the second embodiment. 9 is a flowchart showing parameter updating by the vehicle state quantity estimation device 1 according to the third embodiment. FIG. 9 is a diagram showing a time change of a processing result by the vehicle state quantity estimation device 1 according to the third embodiment. FIG. 9 is a conceptual diagram of a vehicle state quantity output device 30 according to a fourth embodiment. 13 is a flowchart showing output value determination by the vehicle state quantity output device 30 according to the fourth embodiment. The figure which shows the time change of the processing result by the vehicle state quantity output device 30 which concerns on Embodiment 4. The figure which shows the vehicle structure mounted with the vehicle state quantity estimation apparatus 1 or the vehicle state quantity output device 30 which concerns on Embodiment 5. FIG. 17 is a conceptual diagram of a suspension control unit 40 that performs ride comfort control, which is one function of the control suspension device 41 according to the fifth embodiment. FIG. 17 is a conceptual diagram of a suspension control unit 40 that performs anti-roll control, which is one function of the control suspension device 41 according to the fifth embodiment. FIG. 17 is a conceptual diagram of a suspension control unit 40 that performs anti-dive control and anti-squat control, which are one function of the control suspension device 41 according to the fifth embodiment. FIG. 18 is a diagram showing an acceleration PSD as a processing result of the suspension control unit according to the fifth embodiment. FIG. 17 is a diagram illustrating a time change of a processing result of the suspension control unit according to the fifth embodiment. The figure which shows the vehicle structure which mounts the vehicle state quantity estimation apparatus 1 or the vehicle state quantity output device 30 which concerns on Embodiment 6. Shows a vertical displacement of the vehicle body mass point of mass m _p according to the sixth embodiment is applied. The conceptual diagram of the vehicle state quantity estimation apparatus 1 'which concerns on Embodiment 7. The figure which shows the 1/4 vehicle model of 2 degrees of freedom which concerns on Embodiment 7. 17 is a flowchart showing parameter updating by the vehicle state quantity estimation device 1 'according to the seventh embodiment. The figure which shows the load movement accompanying the acceleration which acts on the center-of-gravity point 11 concerning Embodiment 7. The figure which shows the acceleration which acts on the center of gravity 11 of the vehicle which runs on the bank road of cant angle (sigma) which concerns on Embodiment 7. FIG.

  An embodiment for carrying out the present invention will be described in detail with reference to the drawings as appropriate.

  With reference to FIGS. 1 to 5, a method of determining the stability of the detection value of the external recognition unit, updating a parameter based on the detection value, and estimating a vehicle state quantity using the parameter will be described with reference to FIGS.

  FIG. 1 is a conceptual diagram of a vehicle state quantity estimating apparatus 1 that determines the stability of a detection value of the external world recognition means 2, updates a parameter based on the detection value, and estimates a vehicle state quantity using the parameter.

  The vehicle state quantity estimating apparatus 1 includes, for example, a first vehicle movement state quantity detection value 100 detected by an inertia sensor or a gyro sensor, a driver input quantity detection value detected by a steering angle sensor or a stroke sensor, an external world recognition. The second vehicle motion state amount detection value 200 detected by the means is input. Then, based on the input signal, it outputs a vehicle momentum state quantity estimation value 300.

  Here, the first vehicle motion state quantity detection value 100 is a value such as a wheel speed, a longitudinal acceleration, a lateral acceleration, and a yaw rate of the vehicle body. The driver input amount detection value is a value such as a steering angle, an accelerator opening, and a brake pedal force. The second vehicle motion state quantity detection value 200 is a value such as a side slip angle, a lateral speed, a yaw angle, a roll angle, and a pitch angle of the vehicle body detected by the external environment recognizing means 2. The vehicle motion state estimated value 300 is a side slip angle, a lateral speed, a roll angle, a pitch angle, or the like of the vehicle body.

  The vehicle state quantity estimating device 1 includes a stability determining unit 21, a parameter updating unit 22, and a state amount estimating unit 23. The vehicle state quantity estimating device 1 includes a stability determining unit 21, a parameter updating unit 22, and a state amount estimating unit 23.

  The state quantity estimating unit 23 stores preset vehicle parameters, and calculates a vehicle state quantity estimated value 300 using the vehicle motion state quantity detected value 100 and the parameters.

  The stability determination unit 21 determines whether the second vehicle motion state amount detection value 200, which is the input value from the external world recognition unit 2, is stable using the input value from the external world recognition unit 2 and the inertial sensor. , And outputs the determination result.

  The parameter updating unit 22 updates the parameters stored in the state quantity estimating unit 23 using the input values from the external world recognizing unit 2 and the inertia sensor and the determination result from the stability determining unit 21. Specifically, the vehicle parameters are updated so that the detected value of the vehicle motion state amount 200 detected by the external world recognizing means 2 and the value of the estimated value calculated by the state amount estimating unit using the inertial sensor and the parameter are the same. . In other words, by updating the parameters, the estimated value obtained by the state quantity estimating unit 23 is identified by the actually measured value obtained by the external recognition means.

  Here, the parameter update in the present invention means that parameters such as mass and center of gravity of the vehicle, moment of inertia, cornering power, and the like that change due to getting on and off of a person or changing tires are calculated based on input values, and stored parameters. Is replaced with the calculated parameter.

  The vehicle parameters change due to getting on / off of a person, tire replacement, tire deterioration, and the like. Therefore, a difference occurs between the vehicle parameters stored in advance and the actual vehicle parameters, and this difference becomes an error of the vehicle motion state amount estimated value 300. The present invention updates the parameters so that the detection value of the external world recognition means 2 matches the estimation value of the state quantity estimating unit 23, and based on the updated parameters and the value of the inertial sensor, the vehicle motion state quantity estimation value 300 Is calculated. Therefore, it is possible to cope with fluctuations in vehicle parameters, and it is possible to highly accurately estimate a state quantity, such as a side slip angle, a lateral speed, and a roll angle, which is difficult to directly detect with an inertial sensor using the value of the inertial sensor.

  Here, since the estimation accuracy in the state quantity estimating unit 23 depends on the accuracy of the update parameter, the vehicle motion state quantity detection value 200 used for updating is stable, that is, only a highly reliable value is used. Therefore, the stability determination of the vehicle motion state amount detection value 200 in the stability determination unit 21 is performed. Although FIG. 1 illustrates a case where only the vehicle motion state quantity estimation value 300 is output, a stability determination result and an update parameter may be output as necessary. The output value is not limited.

  According to the present invention, since the state quantity of the vehicle is estimated using the detection value of the inertial sensor and the updated parameter even in a situation where the external world recognition means 2 is difficult to detect, The state quantity can be estimated.

  A specific example of a method of estimating a vehicle motion state amount in the state amount estimating unit 23 and a parameter calculating method in the parameter updating unit 22 will be described with reference to FIGS.

  First, an example of a method of estimating the vehicle motion state amount in the state amount estimation unit 23 will be described.

FIG. 2 is a diagram showing a four-wheeled vehicle model. In the present embodiment, the center of gravity 11 of the vehicle is set as the origin, the front-back direction of the vehicle is x, the left-right direction of the vehicle is y, and the up-down direction of the vehicle is z. FIG. 2 shows the motion of the four-wheeled vehicle during turning. The actual steering angle is δ, the speed in the traveling direction of the vehicle is V, the speed in the front-rear direction of the vehicle is V _x , and the speed in the left-right direction of the vehicle is V _y , the side slip angle β, which is the angle between the traveling direction generated by the vehicle turning at the speed V and the front-rear direction of the vehicle, the moving speed directions and tires of the front right wheel, the front left wheel, the rear right wheel, and the rear left wheel The sideslip angles of the tire, which are angles formed by the front-rear direction, are β _fr , β _fl , β _rr , β _rl , and the cornering forces acting on these tires are Y _fr , Y _fl , Y _rr , Y _rl . Further, the yaw rate generated around the z-axis passing through the center of gravity point 11 is r, the distance between the center of gravity 11 and the front wheel axis, and the distance between the center and rear wheel axes are l _f and l _r , respectively, and the distance between the front and rear wheel axes. wheelbase l, respectively _d f a tread width of the vehicle front and rear wheels, and _{d r.}

FIG. 3 is a diagram showing an equivalent two-wheeled vehicle model of a four-wheeled vehicle. FIG. 3 shows that the front and rear left and right wheels and the axle are ignoring the tread of the vehicle in a range in which the side slip angles of the right and left tires are small and the value is small and the actual steering angle is small. It has been replaced with a model that concentrates on the intersection with. Here, the cornering forces 2Y _f and 2Y _r are the resultant forces of the cornering forces acting on the left and right wheels of the front and rear wheels shown in FIG.

FIG. 4 is a diagram showing a roll motion accompanying the lateral acceleration acting on the center of gravity 11. Figure 4 is a lateral acceleration G _y is showing how vehicle roll angle φ of the sprung mass m _b occurs acting. Here the moment generated by the expansion and contraction of the front and rear suspension per unit roll angle is sized roll stiffness _{K φf,} K _φr, the height from the ground of the roll center is a body of the geometric instantaneous rotation center h _f , _{h r,} the height of the center of gravity 11 h, the distance h _phi between the roll shaft 12 and the center of gravity 11 connecting the front and rear roll center, _K the spring constant of the front and rear suspensions containing tire _{sf, K sr, Let} C _sf and C _sr be the damping coefficients of the suspension before and after including the tire.

FIG. 5 is a diagram showing a pitch motion accompanying the longitudinal acceleration acting on the center of gravity 11. Figure 5 is a graph showing how the pitch angle ψ occurs in the vehicle sprung mass m _b acting longitudinal acceleration G _x. Here, the pitch rigidity, which is the magnitude of the moment generated by the expansion and contraction of the front and rear suspensions including the tires per unit pitch angle, is K _、, and the pitch stiffness between the pitch axis 13 and the center of gravity 11 which is the geometric instantaneous center of rotation of the vehicle body. _{Let the} distance be _hψ .

Here, as an example of the state quantity estimation in the state quantity estimating unit 23 shown in FIG. 1, first, the side slip angle β and the lateral velocity V of the vehicle body using the equivalent two-wheeled vehicle model of the four-wheeled vehicle shown in FIG. A method for calculating _y will be described. DV _y / dt, which is the time derivative of the lateral velocity V _y , and dr / dt, which is the time derivative of the yaw rate r generated around the z-axis, are the cornering force per unit slip angle of the front and rear tires with m as the vehicle mass. the cornering power each _K f, _{K r,} the yaw inertia moment of the vehicle as _{I z,} the following equation (1), the formula (2).

  Further, an observer that feeds back the output deviation of the yaw rate r is configured, and the following equations (3) and (4) are obtained by expressing the equations (1) and (2) by a state equation and an output equation.

And (V _y ＾, r ＾) is an estimated value of (V _y , r). In the observer, the observer input is corrected so that the deviation e decreases, and the estimation error of the state quantity is reduced. The estimated value V _y横 of the lateral speed is obtained from the formulas (3) and (4), and the estimated value β ＾ of the side slip angle of the vehicle body can be calculated using the following formula (5).

Then the method for calculating the vehicle body roll angle φ using a roll motion model with the lateral acceleration G _y acting on the center-of-gravity point 11 shown in FIG. 4, the longitudinal acceleration G _x acting on the center-of-gravity point 11 shown in FIG. 5 An example of a method of calculating the pitch angle ψ of the vehicle body using the pitch motion model accompanying the above will be described. Assuming that the vehicle has a constant acceleration and a constant inertia force acts on the center of gravity 11, the roll angle φ and the pitch angle ψ are represented by the following equations (6) and (7), where g is the gravitational acceleration. It can be calculated using the equation represented by

In formulas (1) to (7) above, the mass m of the vehicle, the sprung mass _{m b,} the distance between the center of gravity 11 and the front wheel shaft, and the distance _l f of the rear wheel axle, _{l r,} yaw inertia of the vehicle Moment I _z , cornering power K _f , K _r , roll stiffness K _φf , K _φr , pitch stiffness K _ψ , distance h _φ between roll axis 12 connecting the front and rear roll centers and center of gravity 11, body geometry The distance _hψ between the pitch axis 13 as the center of instantaneous rotation and the center of gravity 11 is a parameter, and the longitudinal acceleration _Gx , the yaw rate r, and the like other than those are the detection values described in FIG.

  Conventionally, based on the results of running tests and numerical analysis at the time of vehicle design, these parameters have been defined as values that take into account robustness corresponding to aging and environmental changes, and are used as constants for estimating state quantities. Has been. However, there is a problem that an estimation error always occurs because the constant is a value considering the robustness. On the other hand, in the present invention, this parameter is treated as a variable, and the estimation error is reduced by updating the parameter to a value suitable for the actual vehicle based on the detection value of the external recognition means 2 described in FIG. .

Next, an example of a parameter calculation method in the parameter update unit 22 will be described. 6, the center of gravity by mass 16 mass m _p is applied to the vehicle is a diagram showing a state that has moved to 14 from 15. In this embodiment, for ease of understanding, it is assumed that the mass point 16 is acting at a position where the roll angle φ of the vehicle body does not occur. It is desirable to consider the roll angle φ of the vehicle body. Further, in the present embodiment, parameters based on the results of a running test or numerical analysis at the time of vehicle design are design values, update parameters are update values, and symbols with 'in the formulas described below are update values. Here, l _f ′ and l _r ′ are the distance between the center of gravity (updated value) 15 and the front wheel axis and the distance between the rear wheel axle, and _xG is the center of gravity (design value) 14 and the center of gravity (updated value) 15. the distance, _{x P} is the distance between the mass point 16 and the center of gravity point (updated value) 15.

First, a method of calculating the mass m and the sprung mass m _b of the vehicle based on the detected value.

If the suspension-related parameters such as the spring constant have not changed and the spring constants K _sf and K _sr of the suspension before and after including the tire are assumed to be linear springs, the updated value m ′ of the mass of the vehicle and the sprung mass, _mb ′ can be calculated using the equation represented by the following equation (8).

Here m, m _b is the mass and the sprung mass of the design value of the vehicle of the formula (8), m _P is the mass of mass point 16, z _f, z _r is a vehicle body front side, the rear vertical displacement, respectively, It can be calculated using the equation represented by the following equation (9).

Here, the pitch angle の in the equation (9) is the vehicle motion state amount detection value 200 detected by the external world recognition means 2. In addition, l _f ′ and l _r ′ in equation (9) are updated values of the distance between the center of gravity (updated value) 15 shown in FIG. 6 and the front wheel axle, and the distance between the center of gravity 15 and the rear wheel axle. It can be calculated using the equation represented by 10).

Here, equation (10) is satisfied when the vehicle is turning at a low speed enough to consider the vehicle speed V to be 0. The vehicle sideslip angle β is obtained by detecting the vehicle motion state quantity 200 detected by the external recognition means 2 and the actual steering angle δ. Is a converted value of the driver input amount detection value. By using the above equations (8) to (10), the updated values m ′ and _mb ′ of the vehicle mass and the sprung mass can be calculated.

However, this calculation method is based on the premise that the pitch angle 変 化 changes in accordance with the change in the mass of the vehicle body, and does not change depending on the mass and position of the people and luggage in the vehicle. ) Alone may not be able to calculate the correct mass. Therefore, it is desirable to use a method of calculating using the equation represented by the following equation (11). Here, T in the equation (11) is a tire output torque, and R is a tire radius. The tire output torque T can be obtained by, for example, a method of calculating from a torque map of an engine or a motor, a speed ratio of a transmission, efficiency, or the like, or a method of directly detecting the torque of the drive shaft using a torque sensor. When equation (11) is used together, two updated values m ′ and _mb ′ of the vehicle mass and the sprung mass are respectively calculated, but when the pitch angle 変 化 changes, the values are equal. When the pitch angle し な い does not change, the updated value obtained by the equation (11) becomes larger than the updated value obtained by the equations (8) to (10). updated value of the sprung mass m _', m b' can be calculated.

Here, the method of calculating the updated values m ′ and _mb ′ of the mass of the vehicle and the sprung mass using the detection values of the external world recognition means 2 is not limited to the method described above. Is stored in the vehicle state quantity estimating apparatus 1 in advance, and the characteristic map representing the relationship between the detected value of the external world recognizing means 2 and the updated values m ′ and _mb ′ of the sprung mass of the vehicle in consideration of external mass and the sprung mass of the vehicle by inputting the detected value of the recognition unit 2 of the updated value m _', m b' may be calculated in. Further, the characteristic map in by adding the axis of the acceleration, updated value of the mass and the sprung mass of the vehicle to remove the influence of the gravitational acceleration due to road surface inclination m ', m _b' can be calculated.

Next, a method of calculating the position of the center of gravity such as the height h of the center of gravity and the distance _hφ between the roll shaft 12 and the center of gravity 11 based on the detected value will be described.

Roll stiffness K _.phi.f, K _{[phi] r,} assuming that the suspension-related parameters, such as pitch stiffness K _[psi has not changed, the distance between the roll shaft 12 and the center of gravity 11, the distance between the pitch axis 13 and the center of gravity 11, The updated values h _φ ′, h _ψ ′, and h ′ of the height of the center of gravity can be calculated using an equation represented by the following equation (12).

Next, based on the detected values, the distance x _G between the centroid point (design value) 14 and the centroid point (update value) 15 and the distance x _P between the mass point 16 and the centroid point (update value) 15 shown in FIG. 6 are calculated. The method will be described. The distance x _G is the absolute value of the difference between the design value lr and updating values lr of the distance between the center of gravity and a rear wheel axle, the distance x _P is the design value of the mass of the vehicle around the center of gravity (updated value) 15 m From the balance between the moment and the mass m _P of the mass point 16, the moment can be calculated using the equation represented by the following equation (13).

  Here, the method of calculating the position of the center of gravity such as the height h of the center of gravity using the detection value of the external world recognition means 2 is not limited to the method described above. A characteristic map representing the relationship between the detected value and the position of the center of gravity may be stored in the vehicle state quantity estimating device 1 in advance, and the position of the center of gravity may be calculated by inputting the detected value of the external environment recognizing means 2 into the characteristic map. Further, by adding an axis of acceleration to the characteristic map, it is possible to calculate the position of the center of gravity excluding the influence of the gravitational acceleration due to the road surface inclination.

Next, a method of calculating the moment of inertia of such a yaw inertia moment I _z on the basis of the detection value.

As an example of a method of calculating the moment of inertia, the updated value _Iz 'of the yaw moment of inertia can be calculated by the following equation (14) using the parallel axis theorem. Here, I _z in formula (14) is a design value of the yaw moment of inertia.

Next, cornering power K _f, a method for calculating a tire characteristic such as K _r will be described on the basis of the detection value.

As an example of a method for calculating the tire characteristics, the updated cornering power values K _f ′ and K _r ′ can be calculated using an equation represented by the following equation (15).

Here, the cornering forces Y _f , Y _r and the sideslip angles β _f , β _r of the tire shown in the equation (15) can be calculated using the equations represented by the following equations (16) and (17), respectively.

  The above is an example of the method of estimating the vehicle motion state quantity and the parameter calculating method according to the present invention.

  A specific embodiment of the above-described vehicle state quantity estimation device 1 of the present invention will be described with reference to FIGS.

  FIG. 7 shows a configuration diagram of a vehicle 10 equipped with the vehicle state quantity estimation device 1 according to the embodiment of the present invention.

  The vehicle state quantity estimating apparatus 1 according to the present embodiment is mounted on a vehicle 10. The vehicle state quantity estimating apparatus 1 includes a camera, GPS or other external environment recognizing means 2, an acceleration sensor 3, a gyro sensor 4, and a wheel speed sensor 6. The detection value of the state quantity related to the driver operation is acquired from the. The vehicle state quantity estimating apparatus 1 determines the stability of the external world recognizing means 2 using the detected value as described in FIG. 1, updates the parameter based on the determination result, and uses the updated parameter and the detected value. It estimates the side slip angle and lateral speed of the vehicle body and outputs the results to a drive control unit 8 and a brake control unit 9 for controlling the braking / driving force of the vehicle.

FIG. 8 is a flowchart illustrating an outline of processing of the vehicle state quantity estimation device 1. First, the vehicle state quantity estimating apparatus 1 obtains, from the acceleration sensor 3 and the gyro sensor 4, the detected values of the vehicle motion state quantity and the driver operation quantity necessary for parameter updating and state quantity estimation (step S801). Next, the vehicle motion state quantity detection value 100, which is the detection value of the acceleration sensor 3 and the like acquired in step S801, is compared with the vehicle motion state quantity detection value 200, which is the detection value of the external environment recognizing means 2, and based on the magnitude relation thereof. It is determined whether the vehicle motion state amount detection value 200 is stable, and the stability determination result is output (step S802). Then if the stability determination is made in step S802, the updated parameters such as the mass m and the yaw inertia moment I _z of the vehicle based on the detection value using the above equations (8) to (18), the update The parameters are output (step S803). Finally, based on the parameters updated in step S803, the vehicle motion state amount detection value 100, and the driver operation amount detection value, the side slip angle β and the lateral speed of the vehicle body are calculated using the above-described equations (1) to (7). V _y , roll angle φ, and pitch angle 推定 are estimated, and the vehicle motion state quantity estimated value 300 is output to the drive control unit 8 and the brake control unit 9 and the processing is terminated. In general, the output cycle of the detection value of the external world recognition means 2 is later than the output cycle of the detection value of the inertial sensor such as the acceleration sensor. Therefore, in order to prevent erroneous processing due to a difference in the output cycle in the stability determination and parameter update described later, the processing cycle is adjusted to the output cycle of the sensor having the slowest output cycle, or the detection value of the sensor having the slowest output cycle is detected. Is time-differentiated, and a value predicted based on the time-differentiated value is preferably used. In addition, the process of evaluating the reliability of the updated parameter based on information obtained from the fuel gauge, the seat sensor, the seat belt sensor, and the like, and determining whether to update the parameter based on the evaluation result includes steps S803 and S803. It may be added during S804.

  FIG. 9 is a flowchart illustrating an outline of processing of the stability determining unit 21 of the vehicle state quantity estimation device 1. In the present embodiment, it is assumed that the yaw angle θ, which is the time integrated value of the yaw rate r detected by the gyro sensor 4, is a true value, and the stability is determined based on the error of the yaw angle θ ＾ detected by the external environment recognizing means 2 with respect to the true value. The method for determining is described. First, the stability determining unit 21 acquires the yaw rate r from the gyro sensor 4 and the yaw angle θ ＾ from the external world recognizing means 2 (step S901). Next, the yaw rate r acquired in step S901 is integrated over time to calculate the yaw angle θ (step S902). Next, the yaw angle θ calculated in step S902 is set as a true value, and a yaw angle error which is a difference between the true value and the yaw angle θ ＾ obtained in step S901 is calculated (step S903). Next, it is determined whether or not the yaw angle error calculated in step S903 is smaller than a predetermined threshold (step S904). If it is smaller (step S904, YES), the process proceeds to step S905, and the count value is set to a predetermined value. Is performed, and if it is larger (step S904, NO), the process proceeds to step S906 to perform a count reset process for setting the count value to 0. Next, it is determined whether or not the count value subjected to the count-up process in step S905 or the count reset process in step S906 is larger than a predetermined threshold value (step S907). If the count value is larger (step S907, YES). The vehicle motion state amount detection value 200 detected by the external world recognizing means 2 is determined to be stable and reliable for a predetermined period of time, and the process proceeds to step S908 to output a stability determination. If the value is small (step S907, NO), it is determined that the vehicle motion state quantity detection value 200 detected by the external world recognition means 2 is not stable for a predetermined period and is not reliable, and the process proceeds to step S909 to output an unstable determination, and To end. Here, the method of determining the degree of stability in steps S901 to S909 is not limited to the above-described process of counting up, and for example, a determination method of counting down by subtracting a predetermined value from a count value, an external world recognition The determination method based on the information self-diagnosed by the means 2 may be used. The target of the stability determination is not limited to the yaw angle error described above. For example, the yaw rate r detected by the gyro sensor 4 is set as a true value, and the true value and the yaw angle detected by the external field recognizing means 2 are used. The yaw rate error, which is the difference from the yaw rate r ＾ obtained by time-differentiating the above, may be determined.

  FIG. 10 is a flowchart illustrating an outline of processing of the parameter updating unit 22 of the vehicle state quantity estimation device 1. First, the parameter updating unit 22 obtains a stability determination result output from the stability determining unit 21 (step S1001). Next, it is determined whether the stability determination result obtained in step S1001 is a stability determination or an unstable determination (step S1002). If the stability determination is a stability determination (step S1002, YES), the detection of the outside world recognizing means 2 is performed. It is determined that the value has reliability for updating the parameter, and the process proceeds to step S1003. If the determination is unstable (step S1002, NO), the reliability for updating the parameter to the detection value of the external environment recognizing unit 2 is determined. It is determined that there is no possibility, and the process ends without updating the parameters. If it is determined in step S1002 that the detection value of the external environment recognizing means 2 has reliability for updating the parameter, the detection values of the vehicle motion state amount and the driver operation amount are obtained from the acceleration sensor 3, the gyro sensor 4, and the like. Then (step S1003), the process proceeds to step S1004. In steps S1004 to S1007, based on the detection values acquired in step S1003, the mass, the center of gravity position, the moment of inertia, and the tire characteristics are calculated using the above equations (8) to (17), and the parameters are updated. The updated parameters are output, and the process ends.

Here, the parameter updating method is not limited to the above method, and the parameter may be updated from time-series data acquired by a sensor during traveling using, for example, an optimization technique or a system identification technique. In addition, in order to prevent the divergence of the updated value due to erroneous detection of the sensor, the range of the parameter value updated in the parameter updating unit 22 is, for example, in the case of mass, the empty mass is the lower limit, and the maximum loaded mass is the upper limit. It is desirable to define in advance a range that may vary with each parameter, such as a value, and update within that range. The storage form of the update parameter is not limited to a numerical value. For example, the tire characteristics based on the cornering forces Y _f , Y _r calculated using Equations (16) and (17) and the tire slip angles β _f , β _r. May be saved as a map.

  FIG. 11 is a diagram showing the detection value of the vehicle state quantity estimation device 1, the error of the detection value, the count value of the stable period, and the time change of the estimation value and the detection value. The detected value, the error of the detected value, and the count value of the stable period are examples of the processing result in the stability determining unit 21 described with reference to FIG. The estimated value is an example of a result obtained by the state quantity estimating unit 23 using the updated parameters output from the parameter updating unit 22 described in FIG. The stability judgment period shown in FIG. 11 is a period in which the error (Q) of the detected value is smaller than the threshold (a) and the count value (J) is larger than the threshold (b). This is a period in which the stability determining unit 21 outputs a stability determination assuming that the state quantity detection value 200 is stable and reliable over a predetermined period. The parameter update unit 22 updates the parameter during the stability determination period, and stops updating the parameter during the other period (unstable determination period). As a result, the state quantity estimating unit 23 can output a highly accurate estimated value substantially equal to the true value during the stability determination period, similarly to the conventional method. Further, since the state quantity estimating unit 23 of the present embodiment performs estimation using the latest parameters updated during the stability determination period, the state value estimation unit 23 cannot correct the estimated value based on the detection value of the external world recognition unit 2 during the unstable determination period. An estimated value closer to the true value can be output as compared with the method. As described above, the parameter which has been treated as a constant in the conventional method is treated as a variable, the parameter is updated to a value corresponding to the actual vehicle based on the detection value of the external environment recognizing means 2, and estimation is performed using the updated parameter. Thus, the estimation error can be reduced as compared with the conventional method.

  Effects when the above-described vehicle state quantity estimation device 1 is applied will be described below.

  In the case of a skid prevention device, for example, when replacing a tire with lower performance than at the time of design, or when tire pressure is reduced or a worn tire is used, in the conventional method, the braking force command of the skid prevention device is insufficient and the skid increases. However, running stability may be reduced. On the other hand, when the vehicle state quantity estimating apparatus 1 of the present embodiment is applied, the braking force command of the anti-skid device can be corrected based on the current tire characteristics, so that the sideslip is reduced and the running stability is improved as compared with the conventional method. Can be done.

  Further, when the vehicle state quantity estimating apparatus 1 of the present embodiment is applied, a highly accurate estimated value substantially equal to a true value is obtained, that is, a predicted value of a state quantity with respect to a driver's operation input is obtained. The braking force command of the sideslip prevention device can be corrected on the basis of the above, the sideslip can be reduced as compared with the conventional method, and the running stability can be improved.

  Also, in the case of a power steering device, for example, when replacing the tire with a lower-performance tire than at the time of design, or when using a tire with reduced tire pressure or worn tire, the assist of the power steering device does not change in the conventional method, so that the tire characteristic is not changed. Vehicle behavior occurred. On the other hand, when the vehicle state quantity estimation device 1 of the present embodiment is applied, the assist force and the steering angle of the power steering device can be increased or decreased according to the current tire characteristics. The same vehicle behavior as at the time can be realized. Further, when the vehicle state quantity estimating apparatus 1 of the present embodiment is applied, a decrease in tire air pressure can be detected by comparing the estimated value of the nominal model with the estimated value of the latest parameter estimation model, and can be transmitted to the driver.

  Further, in the case of an electric booster device, for example, when replacing the tire with a lower-performance tire than at the time of design, or when the tire pressure is reduced, or when a worn tire is used, the braking force command of the electric booster device does not change in the conventional method. A braking force corresponding to the characteristic is generated. On the other hand, when the vehicle state quantity estimation device 1 of the present embodiment is applied, the braking force command of the electric booster device can be corrected in accordance with the current tire characteristics. An equivalent braking force can be generated.

  In the case of an electric parking brake device, an appropriate braking force command can be generated based on the latest mass, so that power consumption can be reduced as compared with the conventional method.

  FIG. 12 is a diagram illustrating a positional relationship of the center of gravity 11 of the vehicle with respect to a coordinate system fixed to the ground. The locus of the center of gravity 11 of the vehicle is expressed by the following equation (18), where (X, Y) is the position of the center of gravity 11 of the vehicle with respect to the coordinate system fixed to the ground, and θ is the yaw angle with respect to the X axis of the vehicle. Is done.

Here, X ₀ , Y ₀ , and θ ₀ are the values of X, Y, and θ at t = 0, respectively, and t is an arbitrary time. The expression (18) uses a detection value of the external recognition means 2 such as the speed V in the traveling direction of the vehicle and the side slip angle β of the vehicle, or an estimated value calculated by the expression (1) using a vehicle model. In order to calculate the trajectory of the center of gravity 11 of the vehicle without using the detected value of the external recognition unit 2 or the estimated value calculated using the vehicle model, there is a method using, for example, the following equation (19). .

  FIG. 13 is a diagram showing a locus of the center of gravity 11 at the time of steady circular turning of a vehicle whose cornering power has been reduced due to replacement with a low-performance tire or a decrease in tire air pressure. The true value (e) is the actual locus of the center of gravity 11 of the vehicle calculated using Expression (18) and the detected value of the vehicle motion state amount 200, which is the detection value of the external world recognition means 2. No vehicle model (f) is the estimated locus of the center of gravity 11 of the vehicle calculated using equation (19). The vehicle model is present and the parameter is not updated (g) is the estimated value calculated using the vehicle model whose parameter is not updated and the estimated trajectory of the center of gravity 11 of the vehicle calculated using Expression (18). The vehicle model is present and the parameter is not updated (h) is an estimated value calculated using the vehicle model with updated parameters and the estimated trajectory of the center of gravity 11 of the vehicle calculated using Expression (18).

  As shown in FIG. 13, the estimated trajectory with the vehicle model and the parameter update (h) is substantially equal to the true value (e), which is the actual trajectory of the center of gravity 11 of the vehicle. The estimated trajectory with the vehicle model and no parameter update (g) has a large estimation error.

  In the case of an automatic driving device, in the conventional method, the self-position estimation is performed based on the detection value of the external recognition means, and in bad conditions such as rainy weather or lens contamination, the detection accuracy is reduced, and there is a possibility that the automatic driving cannot be continued. Was. As a method of continuing the automatic driving in response to the decrease in the detection accuracy of the external world recognition means, a method of performing map matching based on information such as a trajectory of a vehicle estimated using Expressions (18) and (19) is considered. However, there is a risk that safe automatic driving cannot be continued in a method having a large trajectory estimation error, such as the case without the vehicle model (f), the case with the vehicle model, and no parameter update (g). On the other hand, when the vehicle state quantity estimating apparatus 1 of the present embodiment is applied, since the trajectory of the vehicle and the like can be estimated with high accuracy, the automatic driving can be continued at least to a place where the vehicle can be safely stopped.

  In the second embodiment, differences from the first embodiment will be described, and the same description as in the first embodiment will be omitted.

  Note that the main difference between the second embodiment and the first embodiment is a method of determining the stability in the stability determining unit 21. The processing outline of the vehicle state quantity estimation device 1 in the second embodiment will be described with reference to FIGS. Will be described.

  FIG. 14 is a flowchart illustrating an outline of a process performed by the stability determination unit 21 of the vehicle state quantity estimation device 1 according to the second embodiment. The processing in steps S1401 to S1403 in FIG. 14 is the same as the processing in steps S901 to S903 in FIG. 9 in the first embodiment, and a description thereof will not be repeated. In step S1404, a value obtained by time-integrating the yaw angle error calculated in step S1403 for a predetermined period is calculated. Next, it is determined whether or not the integrated value of the yaw angle error calculated in step S1404 is smaller than a predetermined threshold value (step S1405). If it is smaller (step S1405, YES), the vehicle detected by the external environment recognizing means 2 is determined. It is determined that the motion state amount detection value 200 is stable for a predetermined period and is reliable, and the process proceeds to step S1406 to output a stability determination. If it is large (step S1405, NO), the external world recognition unit 2 detects the stability value. The determined vehicle motion state amount detection value 200 is not stable for a predetermined period and is determined to be unreliable, and the process advances to step S1407 to output an unstable determination, and the process ends. Here, the method of determining the stability in step S1404 and step S1405 is not limited to the above-described method of determining the integrated value, and may be, for example, a method of determining the average value.

  FIG. 15 is a diagram illustrating a detection value, an error of the detection value, an integral value of the error of the detection value, and a temporal change of the estimation value and the detection value of the vehicle state quantity estimation device 1 according to the second embodiment. The stability determination period shown in FIG. 15 is a period in which the integrated value (N) obtained by integrating the error (Q) of the detected value in a predetermined period is smaller than the threshold value (c). This is a period in which the stability determination unit 21 outputs a stability determination assuming that the detection value 200 is stable and reliable over a predetermined period. The instantaneous noise exceeding the threshold value (a) shown in the error between the detection value and the detection value in FIG. 15 may occur under the actual usage environment of the vehicle. When such noise occurs, the count value is reset in the vehicle state quantity estimation device 1 according to the first embodiment, and the parameter update is stopped. On the other hand, in the vehicle state quantity estimating apparatus 1 according to the second embodiment, the period during which the magnitude of noise is small and the integrated value (N) is smaller than the threshold (c) is set as the stability determination period, so that actual use of the vehicle is performed. In an environment, the parameter update frequency can be increased while ensuring a certain accuracy in parameter update.

  In the third embodiment, the difference between the first and second embodiments will be described, and the same description as in the first and second embodiments will be omitted.

  The main difference between the third embodiment, the first embodiment, and the second embodiment is a method of determining whether the parameter is updated / not updated in the parameter update unit 22. FIG. 16 and FIG. The processing outline of the state quantity estimation device 1 will be described.

  FIG. 16 is a flowchart illustrating an outline of processing of the parameter updating unit 22 of the vehicle state quantity estimation device 1 according to the third embodiment. First, the parameter updating unit 22 of the third embodiment acquires the vehicle motion state amount detection value 200 detected by the external world recognition unit 2 one processing cycle before and the estimated value estimated by the state amount estimation unit 23 (step S1601). . Here, in the present embodiment, the process from START to END in the flowchart showing the outline of the process of the vehicle state quantity estimation device 1 described in FIG. 8 is defined as one process. Next, an estimation error, which is a difference between the detected value and the estimated value acquired in step S1601, is calculated (step S1602). Next, it is determined whether or not the estimation error calculated in step S1602 is larger than a predetermined threshold (step S1603). If it is larger (step S1603, YES), it is determined that the accuracy of the estimated value is insufficient. Proceeding to S1604, if small (step S1603, NO), the accuracy of the estimated value is necessary and sufficient, and it is determined that updating of the parameter is unnecessary, and the process ends. In step S1604, the parameters are updated according to the flow described in FIG. 10, and the process ends.

  FIG. 17 is a diagram illustrating a detection value, an error of a detection value, a count value of a stable period, an estimation error, and a temporal change of the estimation value and the detection value of the vehicle state quantity estimation device 1 in the third embodiment. As shown in FIG. 17, when the estimation error is smaller than the predetermined threshold (d) even during the stability determination period, the parameter update is stopped. By determining whether the parameter is updated / not updated based on the magnitude of the estimation error, the calculation load of the vehicle state quantity estimation device 1 can be reduced while securing a certain estimation accuracy, and the power consumption can be reduced. And heat generation can be reduced.

  In the fourth embodiment, differences from the first to third embodiments will be described, and the same description as the first to third embodiments will be omitted.

  The main difference between the fourth embodiment and the first to third embodiments is that the vehicle state quantity output device 30 in which the output value determination unit 24 is added to the vehicle state quantity estimation device 1 of the first to third embodiments is configured. The processing outline of the vehicle state quantity output device 30 according to the fourth embodiment will be described with reference to FIGS.

  FIG. 18 is a conceptual diagram of the vehicle state quantity output device 30 according to the fourth embodiment. As shown in FIG. 18, the vehicle state quantity output device 30 has a configuration in which an output value determination unit 24 is added to the vehicle state quantity estimation device 1 of the first to third embodiments. The output value judging section 24 calculates the vehicle motion state quantity estimated value 300 output from the state quantity estimating section 23, the stability judgment result output from the stability judging section 21, and the vehicle motion state detected by the external world recognition means 2. Based on the amount of detected value 200, it is determined which of the vehicle motion state amount estimated value 300 and the vehicle motion state amount detected value 200 is to be output as the vehicle motion state amount output value 400. Here, FIG. 18 illustrates a case where only the vehicle motion state amount output value 400 is output. However, the stability determination result, the update parameter, and the vehicle motion state amount estimated value 300 may be output as necessary. The output value of the vehicle state quantity output device 30 is not limited.

  FIG. 19 is a flowchart illustrating an outline of a process performed by the output value determination unit 24 of the vehicle state quantity output device 30 according to the fourth embodiment. First, the output value determining unit 24 obtains a stability determination result output from the stability determining unit 21 (step S1901). Next, it is determined whether the stability determination result obtained in step S1901 is a stability determination or an unstable determination (step S1902). If the stability determination is a stability determination (step S1902, YES), the detection of the outside world recognizing means 2 is performed. It is determined that the value has reliability for updating the parameter, and the process proceeds to step S1903. If the determination is unstable (NO in step S1902), the reliability for updating the parameter to the detection value of the external environment recognizing unit 2 is determined. The process proceeds to step S1907 after judging that there is no possibility, and the process is terminated after outputting the estimated value. If it is determined in step S1902 that the detection value of the external environment recognizing unit 2 has reliability for updating the parameter, the vehicle motion state amount detection value 200 detected by the external world recognizing unit 2 one processing cycle before, and the state amount The estimation value estimated by the estimation unit 23 is obtained (Step S1903). Here, in the present embodiment, one process from START to END in the flowchart showing the outline of the process of the vehicle state quantity estimation device 1 described in FIG. 8 of the first embodiment is defined. Next, an estimation error which is a difference between the detection value and the estimation value acquired in step S1903 is calculated (step S1904). Next, it is determined whether the estimation error calculated in step S1904 is larger than a predetermined threshold (step S1905). If it is larger (step S1905, YES), it is determined that the accuracy of the estimated value is insufficient. Proceeding to S1906, the detection value is output. If it is smaller (step S1905, NO), it is determined that the accuracy of the estimated value is necessary and sufficient, and the flow proceeds to step S1907 to output the estimated value, thus ending the process.

  FIG. 20 is a diagram illustrating the detection value, the error of the detection value, the count value of the stable period, the estimation error, and the temporal change of the estimation value, the detection value, and the output value of the vehicle state quantity output device 30 in the fourth embodiment. As shown in FIG. 20, the vehicle state quantity output device 30 outputs the detected value as the output value when the stability determination period is over and the estimation error is larger than the threshold (d), and otherwise outputs the estimated value as the output value. Output as By determining the output value output from the vehicle state quantity output device 30 based on the stability determination result and the magnitude of the estimation error, the value closest to the true value in the vehicle state quantity output device 30 is determined. Can be output.

  In the fifth embodiment, differences from the first to fourth embodiments will be described, and the same description as in the first to fourth embodiments will be omitted.

  The main difference between the fifth embodiment and the first to fourth embodiments is that a vehicle 10 'in which a suspension control unit 40 and a control suspension device 41 are added to the vehicle 10 of the first to fourth embodiments is configured. The processing outline of the suspension control unit 40 according to the fifth embodiment will be mainly described with reference to FIGS. Note that the vehicle state quantity estimation device 1 in the fifth embodiment may be the vehicle state quantity output device 30.

  FIG. 21 shows a configuration diagram of a vehicle 10 ′ equipped with the vehicle state quantity estimation device 1 or the vehicle state quantity output device 30 in the fifth embodiment. FIG. 21 shows a configuration in which a suspension control unit 40 and a control suspension device 41 are added to FIG. The control suspension device 41 is a shock absorber of a damping force adjustment type capable of adjusting a damping characteristic or an active suspension capable of adjusting a vertical force between a vehicle body and wheels. The suspension control unit 40 determines a vehicle state necessary for ride comfort control, anti-roll control, and the like based on detection values of an inertial sensor, a gyro sensor, and the like, and updated parameters such as a mass and a center of gravity updated by the vehicle state quantity estimation device 1. The control signal for controlling the damping characteristic of the control suspension device 41 or the force in the vertical direction is generated by estimating the amount.

  Next, a processing outline of the ride comfort control, the anti-roll control, and the anti-dive / anti-squat control in the suspension control unit 40 using the updated parameters updated by the vehicle state quantity estimation device 1 will be described with reference to FIGS.

  FIG. 22 is a conceptual diagram of a suspension control unit 40 that performs ride comfort control, which is one function of the control suspension device 41 in the fifth embodiment. The suspension control unit 40 includes updated parameters such as the mass and the center of gravity updated by the vehicle state quantity estimating device 1 and vehicle motion state quantity detection values 100 such as sprung vertical acceleration and unsprung vertical acceleration detected by an inertial sensor. Is entered.

  The suspension control unit 40 includes a vertical speed estimation unit 43, a target damping force calculation unit 44, and a damping force map 45.

  The vertical speed estimating unit 43 receives the update parameters of the vehicle state quantity estimating apparatus 1 and the vehicle motion state amount detection value 100 as inputs and estimates the sprung and unsprung vertical speeds.

  The target damping force calculating unit 44 calculates a target damping force of the control suspension device 41 based on the vertical speed estimated by the vertical speed estimating unit 42 and the vehicle motion state amount detection value 100.

  The damping force map 45 is map information of characteristics of the control suspension device 41 stored in advance, and receives the target damping force calculated by the target damping force calculation unit 44 and the vehicle motion state amount detection value 100 as inputs, and outputs the control suspension device 41. Derives and outputs a command current for controlling.

  FIG. 23 is a conceptual diagram of a suspension control unit 40 that performs anti-roll control, which is one function of the control suspension device 41 in the fifth embodiment. The suspension control unit 40 includes updated parameters such as the mass and the center of gravity updated by the vehicle state quantity estimating device 1 and vehicle motion state quantity detection values 100 such as sprung vertical acceleration and unsprung vertical acceleration detected by an inertial sensor. A driver input amount detection value such as a steering angle detected by a steering angle sensor is input.

  The suspension control unit 40 mainly includes a vehicle motion model 46, and a roll control gain and a pitch control gain stored in advance.

  The vehicle motion model 46 estimates the lateral acceleration of the vehicle by using the updated parameters of the vehicle state quantity estimating device 1, the vehicle motion state amount detection value 100, and the driver input amount detection value as inputs.

  The suspension control unit 40 controls the control suspension device 41 based on the lateral jerk and the roll control gain obtained by differentiating the lateral acceleration estimated by the vehicle motion model 46, and the absolute value of the lateral acceleration and the pitch control gain estimated by the vehicle motion model 46. Calculate and output the command current to be controlled.

  FIG. 24 is a conceptual diagram of a suspension control unit 40 that performs anti-dive control and anti-squat control, which are one function of the control suspension device 41 in the fifth embodiment. The suspension control unit 40 receives the updated parameters such as the mass and the center of gravity updated by the vehicle state quantity estimating device 1 and the vehicle motion state quantity detected values 100 such as the brake master cylinder pressure, engine torque, and gear position. .

  The suspension control unit 40 mainly includes a vehicle motion model 46 and a pitch control gain stored in advance.

  The vehicle motion model 46 estimates the longitudinal acceleration of the vehicle using the updated parameters of the vehicle state quantity estimation device 1 and the vehicle motion state amount detection value 100 as inputs.

  The suspension control unit 40 calculates and outputs a command current for controlling the control suspension device 41 based on a longitudinal jerk and a pitch control gain obtained by differentiating the longitudinal acceleration estimated by the vehicle motion model 46.

  FIG. 25 and FIG. 26 are examples of simulation results showing the effect of inputting update parameters in the fifth embodiment. FIGS. 25 and 26 show the results of comparing the influence of the update of the mass, which is the update parameter, on the riding comfort on a high-speed undulating road. FIG. 25 shows the vertical acceleration PSD of the floor, the Fr tower, and the Rr tower, and FIG. It is a figure which shows the time change of a floor vertical displacement, a pitch angle, and a roll angle. As shown in FIG. 25 and FIG. 26, the parameter update (in the present invention) is more effective than the parameter update using the parameter at the time of design in consideration of the previously stored robustness (the conventional method). Since the PSD and the pitch angle are small, higher-performance riding comfort control can be realized.

  With the above configuration, it is possible to generate a command current for controlling the suspension based on vehicle state quantities such as sprung vertical velocity and lateral acceleration estimated with high accuracy using the latest parameters such as mass and center of gravity. Higher-performance suspension control can be realized as compared with the case where parameters at the time of design in consideration of robustness stored in advance are used. In addition, it is desirable to update the previously stored damping force map, roll control gain, and pitch control gain, which are affected by the mass and the position of the center of gravity, using the latest parameters such as the mass and the position of the center of gravity.

  In the sixth embodiment, differences from the fifth embodiment will be described, and the same description as in the fifth embodiment will be omitted.

  Note that the main difference between the sixth embodiment and the fifth embodiment is that a vehicle 10 ″ in which a vehicle height sensor 42 is added to the vehicle 10 ′ of the fifth embodiment is configured, and is mainly described with reference to FIGS. 27 to 28. The processing outline of the suspension control unit 40 in the sixth embodiment will be described.

  FIG. 27 is a diagram showing a configuration of a vehicle 10 ″ equipped with the vehicle state quantity estimation device 1 or the vehicle state quantity output device 30 according to the sixth embodiment. Has been added.

The vehicle height sensor 42 detects the relative distance between the road surface and the vehicle body in the z-axis direction or the amount of displacement of the vehicle suspension. The suspension control unit 40 determines the damping characteristic of the control suspension device 41 or the vertical force based on the detection values of various sensors such as the vehicle height sensor 42 and the update parameters of the vehicle state quantity estimation device 1 or the vehicle state quantity output device 30. Control. The vehicle height sensor 42 can directly detect the vertical displacements z _fr , z _fl , z _rr , and z _rl of the right front side, the left front side, the right rear side, and the left rear side of the vehicle body. mass updated value m ', m _b' can be calculated using the equation represented by the following formula (20).

In general, the vehicle height sensor 42 can directly detect the vertical displacement, so that the accuracy is higher than the vertical displacement calculated based on the pitch angle で detected by the external world recognizing means 2. In the state quantity output device 30, highly accurate parameter updating and high-performance suspension control using the updated parameters can be realized. Further, since the mass, the position of the center of gravity, and the moment of inertia can be calculated from the detection values of the external environment recognizing means 2 and the vehicle height sensor 42, even if one of these parameters fails, the vehicle state quantity estimating apparatus 1 or The parameter update by the vehicle state quantity output device 30 can be continued.

FIG. 28 is a diagram illustrating vertical displacement that occurs in a vehicle on which a mass point of mass m _P acts. FIG. 28 shows a manner in which a vertical displacement z _fr , z _fl , z _rr , z _rl on the right front side, the left front side, the right rear side, and the left rear side of the vehicle body on which the mass point of mass m _P acts. . Using this vertical displacement of the vehicle body, the roll angle φ and the pitch angle の of the vehicle body can be calculated using an equation represented by the following equation (21). Here, in this embodiment, in order to facilitate understanding, it is assumed that the tread width of the front and rear wheels of the vehicle is equal to d.

  By comparing the roll angle φ and the pitch angle ψ calculated using this equation (21) with the detection value of the external environment recognizing means 2, it is possible to determine the presence or absence of a sensor failure and the reliability of the detection value.

  In the seventh embodiment, differences from the fifth and sixth embodiments will be described, and the same description as in the fifth and sixth embodiments will be omitted. The main difference between the seventh embodiment, the fifth embodiment, and the sixth embodiment is that the vehicle state quantity estimation device 1 determines whether or not the parameter can be updated based on the tire contact load calculated by the suspension control unit 40. The processing outline of the suspension control unit 40 and the vehicle state quantity control device 1 or the vehicle state quantity output device 30 in the seventh embodiment will be mainly described with reference to FIGS.

FIG. 29 is a conceptual diagram of a vehicle state quantity estimation device 1 'according to the seventh embodiment. As shown in FIG. 29, the vehicle state quantity estimating apparatus 1 ′ inputs the tire contact load calculation value calculated by the suspension control unit 40 to the parameter updating unit 22 of the vehicle state quantity estimating apparatus 1 of the first to third embodiments. Configuration. In addition, since the cornering powers K _f and K _r described in the equation (15) and the like change in magnitude depending on the ground contact load, in order to improve the estimation accuracy of the vehicle motion state quantity estimated value 300, the ground contact load calculated value must be changed to a state. It is desirable that the input to the quantity estimating unit 23 be made. Further, a configuration in which the calculated contact load value is input to the parameter update unit 22 of the vehicle state quantity output device 30 according to the fourth embodiment may be employed.

  Next, a method of estimating the calculated value of the ground contact load of the tire in the suspension control unit 40 will be described.

FIG. 30 is a diagram illustrating a 車 両 vehicle model with one degree of freedom. Figure 30 is one in which the sprung mass m _b showed how the vertical displacement by the unsprung vertical displacement z _t of the mass m _t. Here, the spring constant of the suspension is K _s , the damping coefficient of the suspension is C _s , the vertical displacement above the spring is z _b , the vertical displacement below the spring is z _t , and the ground contact load of the tire is W ₀ . The sprung and unsprung motions are represented by the following equations (22) and (23), respectively.

Here Equation (22), the suspension damping coefficient C _s of formula (23), when controlled suspension apparatus 41 of the shock absorber of adjustable damping force adjustable damping characteristics to the command current of the suspension control unit 40 Enter the damping coefficient based on In the case of an active suspension in which the vertical force between the vehicle body and the wheels can be adjusted, the right side of Expressions (22) and (23) is replaced with the vertical force derived by the suspension control unit 40. Further, d ² z _b / dt ² and d ² z _t / dt ² are not limited to the detection values of the vertical acceleration sensors installed on the sprung and unsprung parts and the estimated values based on them. It may be an estimated value based on the detection value of the vehicle height sensor 3 or the vehicle height sensor 42 or the like.

ΔW _{0 in the} equation (23) is a variation of the contact load, and the contact load W ₀ is represented by the following equation (24) in which the variation is added to the contact load at rest.

  With the above method, the contact load of the tire can be calculated.

  FIG. 31 is a flowchart illustrating an outline of a process performed by the parameter updating unit 22 of the vehicle state quantity estimation device 1 'in the seventh embodiment. In the flowchart shown in FIG. 31, when correcting the parameters, the ground contact load fluctuation frequency and the ground contact load fluctuation difference are calculated. The ground load fluctuation frequency and the ground load fluctuation difference are calculated in order to derive a correction gain for correcting parameters such as vibration of the ground load generated by a rough road surface and slippage of the ground load generated by a depression on the road surface. First, prior to the description of FIG. 31, a method of calculating the difference in the variation in the contact load will be described with reference to FIGS. 32 and 33 so that FIG. 31 is easily understood.

FIG. 32 is a diagram illustrating a load movement accompanying acceleration acting on the center of gravity 11. Figure 32 shows how the variation amount [Delta] W _fl ground load on each tire of the vehicle sprung mass _{m b} acting longitudinal acceleration _{G x} and the lateral acceleration _{G y, ΔW fr, ΔW rl} , the [Delta] W _rr occur It is. FIG. 32 is an example in which the roll angle φ and the pitch angle 車体 of the vehicle body are assumed not to be generated for easy understanding, and when calculating the load movement in more detail, the roll angle φ and the pitch It is desirable to consider the load shift accompanying the angle ψ.

  FIG. 33 is a diagram showing acceleration acting on the center of gravity 11 of a vehicle traveling on a bank road having a cant angle σ. FIG. 33 is an example assuming that the roll angle φ of the vehicle body and the side slip angle β of the vehicle do not occur, for the sake of easy understanding. It is desirable to calculate the load transfer by using

An example of a method of calculating the variation amounts ΔW _fl , ΔW _fr , ΔW _rl , and ΔW _rr of the ground contact load of each tire will be described using the models shown in FIGS. Assuming that the vehicle has a constant acceleration and a constant inertial force is acting on the center of gravity 11, the estimated values ΔW _fl , ΔW _fr , ΔW _rl , and ΔW _rr of the amount of variation in the contact load are calculated by the following equation (25). ).

  Here, the first term on the right side of the equation (25) is the variation in the contact load associated with the longitudinal acceleration Gx, the second term on the right is the variation in the contact load associated with the lateral acceleration Gy, and the third term on the right is the vertical acceleration caused by the cant angle σ. This is the amount of change in the contact load due to the change. Further, the cant angle σ used in the equation (25) can be calculated by an equation represented by the following equation (26).

Next, the ground contact load fluctuation differences ΔW _FY , ΔW _RY , ΔW _LX , and ΔW _RX calculate the latest ground load input from the suspension control unit 40 as W _fl , W _fr , W _rl , W _rr , and the latest ground contact at rest. _Assuming that the loads are W _fl0 , W _fr0 , W _rl0 , and W _rr0 , using the estimated values ΔW _fl , ΔW _fr , ΔW _rl , and ΔW _rr of the contact load fluctuation amount calculated from Expressions (25) and (26), Expression (27).

  Here, the first expression of Expression (27) is the difference between the calculated value and the estimated value of the front-wheel left and right contact load fluctuation amount, the second expression is the difference between the calculated value of the rear-wheel left and right contact load fluctuation amount and the estimated value, The equation is the difference between the calculated value of the ground contact load fluctuation before and after the left wheel and the estimated value, and the fourth equation is the difference between the calculated value of the ground load fluctuation before and after the right wheel and the estimated value.

  Returning to FIG. 31, a flowchart illustrating an outline of processing of the parameter updating unit 22 of the vehicle state quantity estimation device 1 ′ in the seventh embodiment will be described.

  First, the parameter updating unit 22 of the seventh embodiment acquires the contact load calculation value calculated by the suspension control unit 40 (Step S3101). Here, in the present embodiment, the process from START to END in the flowchart showing the outline of the process of the vehicle state quantity estimation device 1 described in FIG. 8 is defined as one process.

  Next, the fluctuating frequency of the contact load is calculated by performing the FFT processing on the contact load calculation value acquired in step S3001 (step S3102).

Next, an estimated value of the contact load fluctuation amount is calculated based on the detected values of the longitudinal acceleration _Gx , the lateral acceleration _Gy , the yaw rate r, and the like, and the equations (25) and (26) (step S3103).

  Next, a difference in the contact load variation is calculated based on the estimated value of the contact load variation calculated in step S3103, the calculated value of the contact load acquired in step S3101, and equation (27) (step S3104).

  Next, a correction gain is calculated based on the contact load variation frequency calculated in step S3102 and the contact load variation difference calculated in step S3104. As a method of calculating the correction gain, a method of inputting a grounding load fluctuation frequency and a grounding load fluctuation difference and deriving the correction gain map based on a correction gain map stored in advance may be considered. There is no limitation on how to do this.

  In step S3105, the parameters are corrected using the correction gain calculated in step S3105. A method of correcting the parameter may be a method of multiplying the parameter by a correction gain, but may be a method of division, and the method of correcting the parameter by the correction gain is not limited.

  With the above-described configuration, even when the vehicle is running on a rough road having a large variation in the ground contact load in a state where the detection value of the external world recognition unit 2 is unstable, it is possible to use an appropriate parameter according to the ground contact state. Therefore, more accurate estimation in the state quantity estimating unit 23 and higher-performance suspension control in the suspension control unit 40 can be realized.

1: vehicle state quantity estimation device 2: external world recognition means 3: acceleration sensor 4: gyro sensor 5: steering angle sensor 6: wheel speed sensor 7: tire 8: drive control unit 9: brake control unit 10, 10 ': vehicle 11 : Center of gravity 12: Roll axis 13: Pitch axis 14: Center of gravity (design value)
15: Center of gravity (updated value)
16: Mass point 21: Stability determining unit 22: Parameter updating unit 23: State quantity estimating unit 24: Output value determining unit 30: Vehicle state quantity output device 40: Suspension control unit 41: Control suspension device 42: Vehicle height sensor 43: Vertical speed estimating unit 44: target damping force calculating unit 45: damping force map 46: vehicle motion model 100: vehicle state quantity detection value 200: vehicle state quantity detection value

Claims (5)

Vehicle including the detected value of the acceleration sensor or a gyro sensor, is inputted detected value of the external world recognizing unit, the acceleration sensor or the detection value and the vehicle of mass of the gyro sensor, the center of gravity position, moment of inertia, and any of the cornering power based on the parameters, the side slip angle of the vehicle body of the vehicle, lateral velocity, roll angle, and a vehicle state quantity estimation apparatus for estimating a state quantity of the vehicle including one of the pitch angle,
The vehicle state quantity estimation device includes a stability determination unit and a parameter update unit,
The stability determination unit is configured to determine whether the time difference between the time integration value of the acceleration sensor or the gyro sensor during a predetermined period and the detection value of the external world recognition unit is smaller than a predetermined value. Judge that the detection value is stable,
The parameter updating unit updates the vehicle parameter using the detection value of the external world recognition unit when the stability determination unit determines that the detection value of the external world recognition unit is stable. Vehicle state quantity estimating device. A characteristic map for outputting the vehicle parameters with the detection value of the acceleration sensor or the gyro sensor and the detection value of the external world recognizing means being input, and updating the vehicle parameters based on the characteristic map. The vehicle state quantity estimation device according to claim 1 .   The vehicle state quantity estimation device according to claim 1, wherein the vehicle parameter is updated within a range between a predetermined upper limit value and a predetermined lower limit value. Wherein the claim 1 is input vehicle parameters updated in the vehicle state quantity estimating apparatus according to any one of 3, a vehicle motion control device you output a control command value for controlling the vehicle,
A second vehicle different from the vehicle state quantity updated by the vehicle state quantity estimation device based on the updated vehicle parameter and a second detection value different from the detection value of the acceleration sensor or the gyro sensor. A vehicle motion control device for estimating a state quantity of the vehicle and outputting the control command value . 5. The vehicle according to claim 4 , further comprising: means for detecting a depression on the road surface ; and a characteristic map or gain to which the detected value of the depression on the road surface is input, wherein the vehicle parameter is updated using the characteristic map or the gain. A vehicle motion control device according to claim 1.

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