WO2023026688A1

WO2023026688A1 - Vehicle control device and vehicle control method

Info

Publication number: WO2023026688A1
Application number: PCT/JP2022/026057
Authority: WO
Inventors: 京士朗伊多倉; 満松原
Original assignee: 株式会社日立製作所
Priority date: 2021-08-25
Filing date: 2022-06-29
Publication date: 2023-03-02
Also published as: JP2023031547A

Abstract

Provided is a high-performance vehicle control device that integrally controls different types of actuators, and that improves path following characteristics while making it possible to control acceleration and jerk affecting riding comfort to a desired movement. This vehicle control device for operating a plurality of actuators to control the motion of a vehicle is characterized by comprising a predictor that predicts a future vehicle motion on the basis of a vehicle motion prediction model and an actuator command value, and an optimizer that calculates, by iterative computation, the actuator command value that will minimize the difference between an arbitrary motion target value and a prediction value predicted by the predictor, the predictor having a first motion predictor that calculates a first motion prediction state obtained by differentiating the dynamics of the vehicle by one or more stages.

Description

VEHICLE CONTROL DEVICE, VEHICLE CONTROL METHOD

The present invention relates to the configuration and control of a vehicle control device, and particularly to technology effective in improving ride comfort.

Conventionally, the development of autonomous driving technology for automobiles focused on the development of technologies essential for autonomous driving, such as route tracking. Demand for improved comfort is increasing.

Therefore, in recent years, vehicle control technology has been developed to improve the comfort of drivers and passengers by optimally controlling multiple and different types of actuators.

As a background technology in this technical field, there is a technology such as Patent Document 1, for example. Patent Document 1 describes "a roll angular acceleration detection device that detects the roll angular acceleration of the vehicle body, an actuator that generates a roll moment applied to the vehicle body, and a control unit that controls the actuator, and the control unit is the vehicle. A vehicle roll vibration damping control device that stores a roll moment of inertia, a roll damping coefficient, and an equivalent roll stiffness.

In addition, Patent Document 2 describes "predicting the behavior of the vehicle when it travels according to the travel plan of the own vehicle, calculating an evaluation value for the predicted behavior of the vehicle based on the travel plan, and controlling the vehicle based on the evaluation value. Driving Support Method for Calculating Control Amounts of Actuators to be Controlled” is disclosed.

JP 2020-59477 A Japanese Patent Application Laid-Open No. 2020-26189

According to the above Patent Document 1, it is possible to effectively damp the roll vibration of the vehicle body without changing the dynamic characteristics of the roll motion of the vehicle.

However, in Patent Document 1, as described in each embodiment, the roll vibration is only suppressed by controlling the same type of actuators. There is no specific explanation as to whether to control and suppress the roll vibration.

In addition, according to Patent Document 2, it is possible to reduce delays in vehicle control even when the behavior of the vehicle changes dynamically.

However, Patent Document 2 mentions a control technique that improves route followability by optimally controlling a plurality of actuators by predicting the vehicle motion with a state predictor, but it may affect ride comfort. There is no description of a specific control method for the known acceleration or jerk that is a change in acceleration.

SUMMARY OF THE INVENTION Accordingly, an object of the present invention is to provide a vehicle control system that can control different types of actuators in an integrated manner, and that is capable of controlling acceleration and jerk, which affect ride comfort, to desired movements while improving track followability. An object of the present invention is to provide a vehicle control device and a vehicle control method.

In order to solve the above problems, the present invention provides a vehicle control apparatus that operates a plurality of actuators to control the motion of a vehicle, and predicts the future motion of the vehicle based on a motion prediction model of the vehicle and actuator command values. a predictor; and an optimizer that calculates, by iterative calculation, the actuator command value that minimizes the difference between an arbitrary motion target value and the value predicted by the predictor, wherein the predictor calculates dynamics of the vehicle. It is characterized by having a first motion predictor that calculates a first motion prediction state obtained by differentiating one or more orders.

The present invention also provides a vehicle control method for controlling the motion of a vehicle by operating a plurality of actuators, comprising: (a) a step of predicting future vehicle motion based on a vehicle motion prediction model and actuator command values; (b) calculating by iterative calculation an actuator command value that minimizes the difference between an arbitrary motion target value and the predicted value predicted in step (a); is characterized by calculating a first motion prediction state obtained by differentiating the dynamics of the first order or more.

According to the present invention, in a vehicle control device that integrally controls different types of actuators, high-performance vehicle control can control acceleration and jerk, which affect ride comfort, to desired movements while improving route followability. An apparatus and vehicle control method can be implemented.

As a result, it is possible to improve the comfort of the driver and passengers while ensuring the route-following performance required for autonomous driving.

Problems, configurations, and effects other than those described above will be clarified by the following description of the embodiment.

1 is a diagram showing a schematic configuration of a vehicle according to Embodiment 1 of the present invention; FIG. 2 is a block diagram showing a schematic configuration of a control system that controls the vehicle of FIG. 1; FIG. 1 is a block diagram showing general model predictive control; FIG. 1 is a block diagram showing a control configuration of a vehicle control device according to Embodiment 1 of the present invention; FIG. FIG. 5 is a waveform diagram showing the effect of the vehicle control device of FIG. 4; FIG. 5 is a block diagram showing a control configuration of a vehicle control device according to Embodiment 2 of the present invention; FIG. 5 is a block diagram showing a control configuration of a vehicle control device according to Embodiment 3 of the present invention;

Hereinafter, embodiments of the present invention will be described with reference to the attached drawings. Similar components are denoted by similar reference numerals, and similar descriptions are not repeated.

A vehicle control device and a vehicle control method according to a first embodiment of the present invention will be described with reference to FIGS. 1 to 5. FIG. FIG. 1 is a diagram showing a schematic configuration of a vehicle according to this embodiment.

As shown in FIG. 1, the vehicle 1 of this embodiment has wheels 11, a motor 12, a suspension 13, a steering wheel 14, a brake 15, and a stabilizer 16 mounted on a vehicle body 10.

In the following description, the longitudinal direction of the vehicle 1 is the x-axis (the forward direction is positive), the left-right direction is the y-axis (leftward is positive), and the vertical direction is the z-axis (upward is the positive direction).

The wheels 11 support the vehicle body 10 and exert a gripping force in contact with the road surface. In this embodiment, the four wheels are a left front wheel 11FL, a right front wheel 11FR, a left rear wheel 11RL, and a right rear wheel 11RR. ing.

In the following description, reference numerals for structures corresponding to the left front wheel 11FL are denoted by FL, reference numerals for structures corresponding to the right front wheel 11FR are denoted by FR, and components corresponding to the left rear wheel 11RL are denoted by RL. , and RR is added to the reference numeral of the configuration corresponding to the right rear wheel 11RR. In addition, reference numerals corresponding to both the left front wheel 11FL and right front wheel 11FR are denoted by F, and reference numerals corresponding to both the left rear wheel 11RL and right rear wheel 11RR are denoted by R.

An in-wheel motor 12 (12FL, 12FR, 12RL, 12RR) is attached to each of the wheels 11, and each of the wheels 11 is independently rotated (forward and reverse) by these motors 12. can be done.

Suspensions 13 (13FL, 13FR, 13RL, 13RR) are provided between each of the motors 12 and the vehicle body 10. These suspensions 13 absorb vibrations and shocks generated in the respective wheels 11, 10's stability and ride comfort are improved.

These suspensions 13 are, for example, a semi-active suspension that combines a damper and a coil spring that can change the viscosity, a full active suspension that combines an actuator that can adjust the stroke, a damper, and a coil spring, a linear motor, There is an electric type that uses a combination of a rotary motor and a rotary direct acting mechanism.

The steering 14 is a device for steering the wheels 11 and determining the traveling direction of the vehicle 1. In this embodiment, the steering 14FL for steering the front left wheel 11FL, the steering 14FR for steering the front right wheel 11FR, and the steering 14FR for steering the left front wheel 11FR. It has three steering wheels 14R for steering the rear wheel 11RL and the right rear wheel 11RR.

The brake 15 is a device for braking the rotation of the wheel 11. In this embodiment, the brake 15FL for the front left wheel 11FL, the brake 15FR for the front right wheel 11FR, the brake 15RL for the rear left wheel 11RL, It has four brakes 15RR for the right rear wheel 11RR.

The stabilizer 16 is a device that works in conjunction with the vertical motion of the left and right wheels to suppress the amount of rolling of the vehicle, and the stabilizer of this embodiment is a control stabilizer that can electrically adjust its torsion angle. It is a device for tilting the vehicle body 10 in the roll direction, which is a rotational movement around the x-axis, when the vehicle 1 turns, and adjusting the roll amount. It has two of 16R.

FIG. 2 is a block diagram showing a schematic configuration of a control system that controls the vehicle 1 of FIG.

A vehicle control device 2 mounted on the vehicle 1 receives map information, self-location information, and a vehicle motion command value calculated by a host computer based on a target ride comfort index.
In addition, the vehicle control device 2 calculates a plurality of actuator commands so as to reduce the error between the received motion command value and the current motion information obtained from an acceleration sensor or the like, and transmits an operation command value to each actuator. It has functions.

In FIG. 2, as motion command values, a longitudinal command value, a lateral command value, a vertical command value, a roll command value, a pitch command value, and a yaw command value are inputted to the vehicle control device 2, and the driving actuator, the braking actuator, the active An example of outputting an operation command value for a suspension actuator, a steering actuator, etc. is shown.

Here, there is a technique called model predictive control as a means of optimally controlling the error between the target motion and the current value shown in FIG.

FIG. 3 shows a schematic configuration diagram of general model predictive control technology that is incorporated in the vehicle control device 2 and performs optimal actuator control based on vehicle motion prediction.

In model predictive control, the motion predictor 21 is equipped with a vehicle dynamics model to simulate vehicle motion, and the vehicle motion is predicted based on the operation commands of multiple actuators. Also, the optimizer 22 compares the motion command value received from the host computer 41 with the motion prediction value obtained from the motion predictor 21, and the error of the future motion prediction value for the motion command value is within a certain interval. The operation command value of the actuator 42 is optimized by iterative calculation so as to be minimized.

At this time, the evaluation weight setting unit 23 can adjust the weight of the evaluation function when optimizing so that arbitrary movement can be controlled among a plurality of vehicle movements. For example, it is possible to adjust the control such that suppression of change in the attitude angle of the vehicle 1 is prioritized over the route following error of the vehicle 1 .

In addition, the constraint condition setting unit 24 performs the optimization calculation after restricting an arbitrary motion state or actuator operation command so that it does not exceed preset upper and lower limit values in the optimization calculation of the optimizer 22. enable. For example, it is possible to travel while restricting the route following error to always be 10 m or less.

In this way, in general model predictive control, based on predictions of vehicle dynamics, optimization is performed so as to minimize the error from the target value and not to exceed various constraints, and the actuators are preferably operated. An operation command value to operate is calculated and transmitted to the actuator 42 .

FIG. 4 shows a control block diagram of the vehicle control device 2 in this embodiment. This embodiment also includes an optimizer 22, an evaluation weight setting section 23, and a constraint condition setting section 24, as in FIG.
The motion predictor 21 includes a first motion predictor 31 and a second motion predictor 32 . The first motion predictor 31 has a vehicle motion model obtained by second-order differentiation of a general vehicle motion model for calculating changes in acceleration of vehicle motion.

Here, the motion model of pitch θ, which is the rotational motion around the longitudinal x, vertical z, and y axes of a general vehicle motion model for calculating changes in acceleration of vehicle motion, is expressed by, for example, formulas (1) to (3). is a motion model shown in .

Here, m is the mass of the entire vehicle, ms is the mass on the sprung mass, hp is the deviation between the pitch center and the position of the center of gravity of the vehicle, ρ is the coefficient representing the influence of various motions, and f is the input of various actuators. is expressed as a linear state equation shown in Equation (4) according to these equations of motion.

However, X and U are the state and input, respectively, and A and B are the coefficient matrix of the state vector and the coefficient matrix of the input vector, respectively. In equation (4), for example, the state includes the position and velocity of the vehicle or the angle and angular velocity of the vehicle attitude.

Here, in the first motion predictor 31 of this embodiment, Equation (5) obtained by second-order differentiation of Equation (4) is provided as a vehicle motion prediction model.

At this time, since equations of motion shown in equations (1) to (3) are differentiated second-order in equation (5), acceleration and jerk as well as attitude angular acceleration and angular jerk are added to that state. state is included.

Also, by the second order differentiation, the input handled by the state equation gives the change rate of the actuator command change (the second order differential value of U) as an input.

Next, the second motion prediction state is obtained by second-order integration of the state predicted by Equation (5). The state obtained here is of the same kind as state X in equation (4).

Furthermore, the prediction state combiner 33 simultaneously converts the first motion prediction model, the second motion prediction model, and the actuator input U into an optimizable format. Specifically, an expansion system of the formula (6) is constructed.

However, in reality, U included in the input vector is uniquely determined by the integral of the input of the second derivative of U in Equation (5), so it is not appropriate to treat it as an independent control input.
Therefore, equation (7) in which U is included in the state vector is defined as a new extended system.

Equation (8) obtained in this manner includes position, velocity, acceleration, jerk, angle, angular velocity, angular acceleration, angular jerk, various actuator commands, etc. in the state at the same time. It is possible to predict and optimally control them at the same time with the optimizer 22 .

At this time, the value calculated as a result of optimization is the second-order differential value of the actuator command, so the signal actually transmitted to the actuator 42 is the second-order integrated value (actuator command value).

In the optimizer 22, the weight setting value Q by the evaluation weight setting unit 23 and the optimization function equation (10) based on the error E between the desired motion and the motion prediction value shown in equation (9) are defined, Constrained optimization calculations are performed based on equations (11) and (12), which are formulated as inequality constraints regarding the state and input of the augmented system expressed by equation (8).

Here, Hp is the prediction interval, Gx and Gu are coefficient matrices related to state and input constraints, respectively.

With the above configuration, in this embodiment, along with the route following control of the vehicle 1, the motion state of acceleration and jerk, which affect the ride comfort of the driver and passengers, can be controlled at the same time so as not to exceed the operation limit of the actuator. It becomes possible.

The effect of this embodiment will be explained using FIG. FIG. 5 shows waveforms of vehicle speed, in-wheel motor drive torque, front-rear jerk, pitch angular acceleration, and pitch angular velocity from the top. In the vehicle speed waveform, the dashed line indicates the speed command value, the dotted line indicates the control waveform of the conventional technology, and the solid line indicates the control waveform of the present invention.

With the conventional technology, it is not possible to control the longitudinal jerk and pitch angular acceleration at the same time as the speed follow-up control. Resulting in. On the other hand, according to the present invention, while performing speed follow-up control, it is possible to realize driving while considering the limit of drive torque and suppressing longitudinal jerk and pitch angular acceleration at the same time. It becomes possible.

As described above, the vehicle control system 2 of the present embodiment includes the motion predictor 21 for predicting the future vehicle motion based on the motion prediction model of the vehicle 1 and the actuator command value, and an arbitrary motion target value and the motion predictor The motion predictor 21 is provided with an optimizer 22 that calculates by iterative calculation an actuator command value that minimizes the difference from the predicted value by the motion predictor 21. The motion predictor 21 is a first It has a first motion predictor 31 for calculating the motion prediction state of.

The motion predictor 21 also has a second motion predictor 32 that calculates a second motion prediction state obtained by integrating the first motion prediction state by one or more orders.

The vehicle control device 2 also includes a prediction state combiner 33 that combines the first motion prediction state and the second motion prediction state.

The prediction state combiner 33 further combines the actuator command prediction value predicted based on the integration of the amount of change in the actuator command value.

The optimizer 22 calculates the optimization result based on the amount of change in the actuator command value obtained by differentiating the dynamics of the vehicle 1 by one or more orders.

The first motion predictor 31 and the second motion predictor 32 have a total of six degrees of freedom of roll, pitch, and yaw, which are translational motions of the vehicle 1 in the longitudinal, vertical, and lateral directions, and rotational motions around respective axes. predicts one or more of the movements of

Also, the first motion predictor 31 predicts one or more of the acceleration or jerk of the translational motion of the vehicle 1 and the angular acceleration or angular jerk of the rotational motion of the vehicle 1 .

Also, the second motion predictor 32 predicts one or more of the position or speed of translational motion and the angle or angular velocity of rotational motion of the vehicle 1 .

Also, the optimizer 22 has one or more predicted values consisting of the first motion prediction state, the second motion prediction state, and the actuator command prediction value predicted based on the integration of the change amount of the actuator command value. not exceed any limits.

As a result, it is possible to appropriately control the acceleration and jerk motion conditions, which affect the comfort of the driver and passengers, to below the allowable value, at the same time as the route following control required for automatic driving of the car.

A vehicle control device and a vehicle control method according to Embodiment 2 of the present invention will be described with reference to FIG. FIG. 6 is a block diagram showing the control configuration of the vehicle control device 2 of this embodiment.

As shown in FIG. 6, the vehicle control device 2 of the present embodiment converts the first motion prediction model and the second motion prediction model into a format that can be optimized by the prediction state coupler 33, when the actuator command This differs from the first embodiment (FIG. 4) in that no value is used. Other configurations are the same as those of the first embodiment (FIG. 4).

　Computational cost is often an issue in model predictive control. Then, the computation cost can be reduced by reducing the dimension of the state vector.

Therefore, for the control purpose of improving ride comfort, it is assumed that the performance limit of the actuator will not be used, and a configuration that does not include the actuator command value in the predictive state coupler 33 is conceivable.

By doing so, the number of dimensions required for optimization calculation can be reduced by the number of actuators to be handled, so the calculation cost can be expected to be reduced, and the cost of the computer installed in the vehicle can be reduced.

A vehicle control device and a vehicle control method according to Embodiment 3 of the present invention will be described with reference to FIG. FIG. 7 is a block diagram showing the control configuration of the vehicle control device 2 of this embodiment.

As shown in FIG. 7, the vehicle control device 2 of this embodiment does not use the second motion predictor 32 when the motion predictor 21 predicts the vehicle motion, This differs from Example 1 (FIG. 4) in that the format of one motion prediction model is not converted. Other configurations are the same as those of the first embodiment (FIG. 4).

This embodiment is a control configuration focusing only on the control of ride comfort. In this embodiment, only acceleration, angular acceleration of jerk and posture, and angular addition acceleration can be controlled as states.

By doing so, it is possible to further reduce the calculation cost.

It should be noted that the present invention is not limited to the above-described embodiments, and includes various modifications. For example, the above-described embodiments have been described in detail in order to explain the present invention in an easy-to-understand manner, and are not necessarily limited to those having all the described configurations. In addition, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Moreover, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

Reference Signs List 1 vehicle 2 vehicle control device 10 vehicle body 11 wheel 12 motor 13 suspension 14 steering 15 brake 16 stabilizer 21 motion predictor 22 optimizer 23...Evaluation weight setting unit, 24...Constraint condition setting unit, 31...First motion predictor, 32...Second motion predictor, 33...Predicted state combiner, 41...Higher-level computer, 42...Actuator.

Claims

A vehicle control device that controls motion of a vehicle by operating a plurality of actuators,
a predictor for predicting future vehicle motion based on the vehicle motion prediction model and the actuator command value;
an optimizer that calculates by iterative calculation the actuator command value that minimizes the difference between an arbitrary motion target value and the predicted value by the predictor,
The vehicle control device, wherein the predictor includes a first motion predictor that calculates a first motion prediction state obtained by differentiating vehicle dynamics by one or more orders.
The vehicle control device according to claim 1,
The vehicle control device, wherein the predictor has a second motion predictor that calculates a second motion prediction state obtained by integrating the first motion prediction state by one or more orders.
The vehicle control device according to claim 2,
A vehicle control device comprising a prediction state combiner that combines the first motion prediction state and the second motion prediction state.
The vehicle control device according to claim 3,
The vehicle control device, wherein the prediction state combiner further combines the actuator command prediction value predicted based on the integration of the change amount of the actuator command value.
The vehicle control device according to claim 3,
The optimizer is a vehicle control device that calculates an optimization result based on a change amount of an actuator command value obtained by differentiating vehicle dynamics by one or more orders.
The vehicle control device according to claim 3,
The first motion predictor and the second motion predictor are used for motion of a total of six degrees of freedom, namely roll, pitch, and yaw, which are longitudinal, vertical, horizontal translational motion of the vehicle, and rotational motion around each axis. A vehicle controller that predicts one or more of them.
The vehicle control device according to claim 3,
The first motion predictor predicts one or more of acceleration or jerk of translational motion of the vehicle and angular acceleration or angular jerk of rotational motion of the vehicle.
The vehicle control device according to claim 3,
The second motion predictor predicts one or more of position or velocity of translational motion, angle or angular velocity of rotational motion of the vehicle.
The vehicle control device according to claim 8,
The optimizer performs one or more predictions including the first motion prediction state and the second motion prediction state, and an actuator command prediction value predicted based on the integration of the change amount of the actuator command value. A vehicle controller that limits values from exceeding arbitrary limits.
A vehicle control method for controlling motion of a vehicle by operating a plurality of actuators,
(a) predicting future vehicle motion based on a vehicle motion prediction model and actuator command values;
(b) calculating by iterative calculation an actuator command value that minimizes the difference between an arbitrary motion target value and the predicted value predicted in step (a);
has
A vehicle control method in which, in step (a), a first motion prediction state obtained by differentiating vehicle dynamics by one or more orders is calculated.
A vehicle control method according to claim 10,
Between the (a) step and the (b) step, (c) a step of calculating a second motion prediction state obtained by integrating the first motion prediction state by one or more orders;
A vehicle control method comprising:
A vehicle control method according to claim 11,
(d) combining said first motion prediction state and said second motion prediction state, between said step (c) and said step (b);
A vehicle control method comprising:
A vehicle control method according to claim 12,
In the vehicle control method, in step (d), the predicted actuator command value predicted based on the integration of the amount of change in the actuator command value is further combined.
A vehicle control method according to claim 12,
In the step (b), the vehicle control device calculates the optimization result based on the amount of change in the actuator command value obtained by differentiating the dynamics of the vehicle by one or more orders.
A vehicle control method according to claim 12,
The first motion prediction state and the second motion prediction state are motions with a total of six degrees of freedom of roll, pitch, and yaw, which are longitudinal, vertical, horizontal translational motions of the vehicle, and rotational motions around respective axes. A vehicle control method that predicts one or more of them.