CN111231937A - Control method for unstable motion of unmanned vehicle after collision - Google Patents
Control method for unstable motion of unmanned vehicle after collision Download PDFInfo
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- CN111231937A CN111231937A CN202010115954.2A CN202010115954A CN111231937A CN 111231937 A CN111231937 A CN 111231937A CN 202010115954 A CN202010115954 A CN 202010115954A CN 111231937 A CN111231937 A CN 111231937A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/02—Control of vehicle driving stability
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W2030/082—Vehicle operation after collision
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Abstract
The invention discloses a control method for unstable motion of an unmanned vehicle after collision, which is applied to the unmanned vehicle with a distributed independent driving braking execution function and can realize the unstable motion control of the unmanned vehicle under different collision conditions. Through simulation verification, the control strategy provided by the invention can effectively reduce the motion deviation of the vehicle in the collision process, further reduce the occurrence probability of subsequent collision, and has important engineering practical application significance of quick response, strong real-time performance and the like.
Description
Technical Field
The invention relates to the technical field of automobile control, in particular to a method for controlling unstable motion of an unmanned vehicle after collision.
Background
Accident data shows that secondary collisions tend to result in higher rates of injury and mortality than primary collisions. When the traditional automobile is in initial collision, the automobile is impacted in the longitudinal and transverse directions and rotates at a high speed, so that a driver can easily make unreasonable driving operation, and the motion state of the automobile is further deteriorated. The distributed driving/braking mode becomes one of the technologies of the automatic driving vehicle at present, and the transverse motion control of the vehicle and the driving safety of the vehicle can be effectively realized by the characteristic of overdrive. Meanwhile, the feasible region of the traditional vehicle on the motion control actuator is enlarged, and the stability of the vehicle is guaranteed under the condition of emergency driving.
Conventional crash instability control generally only considers feedback control of steering and braking. Where the provision of a counter yaw moment to suppress a collision yaw movement disturbance by braking alone is very limited. And elimination of disturbances in the case of feedback control alone may have a problem of time lag, possibly leading to oversteer. The method of the invention combines the effective suppression of the strong disturbance of the collision by the feedforward control and the utilization of the residual potential of the tire force.
Feedforward-based model predictive control requires that the system inputs generated by feedforward control be provided to the MPC feedback control algorithm for global input constraints. Conventional vehicle stability envelope constraints are not applicable to vehicle conditions after initial crash instability. If the MPC soft constraint method is adopted, a large relaxation variable and relaxation weight are needed to meet the feasibility requirement of the MCP optimization problem, the control cost of the constraint optimization problem is increased, and the proportion of the control cost of the transverse position error and the heading error in the main control target to the total cost is reduced. This is disadvantageous for achieving the destabilizing control of the lateral motion and yaw motion after the vehicle collision.
In summary, in order to meet the requirement of instability after initial collision on vehicle motion safety control, the influence of strong system disturbance caused by collision cannot be quickly and effectively eliminated by the traditional single feedback control method. Therefore, the research on how to realize the direct, reasonable and effective motion control method has important practical significance on the research on the collision motion of the unmanned automobile.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the problem that the traditional vehicle stability motion control method cannot meet the requirement of timely and effectively eliminating the influence of collision on the lateral and yaw motion of the vehicle and the feasibility of the problem of vehicle constraint in feedback control, the invention provides a control method for the unstable motion of an unmanned vehicle after collision, which is realized by combining feedforward control based on the steepest reduction of collision energy and feedback control based on model prediction.
The invention adopts the following technical scheme:
a control method for unstable motion after collision of an unmanned vehicle is characterized in that the method designs the prerequisite inputs of a front wheel steering angle and distributed driving/braking torque by using the kinetic energy of transverse motion and the kinetic energy of rotary motion generated by collision together by a feed-forward method, improves the dissipation speed of collision energy, and avoids secondary collision caused by time lag and untimely motion control only depending on feedback control. And then adding the input action of the feedforward control into a feedback control algorithm (MPC) based on model prediction for further optimization and constraint. The method effectively solves the limitation of the traditional envelope control on high-speed rotation instability after collision, fully utilizes the potential of the generalized force of a nonlinear tire to obtain the reverse yaw moment for correcting the posture of the vehicle body, provides a method for converting the state discomfort constraint into the feasibility constraint of control input, enables the vehicle which is unstable and yawed after collision to continuously reduce the transverse position deviation and continuously correct the course deviation through reasonably intervening the combined controller, regresses and tracks the original expected track, and reduces the driving interference on autonomous vehicles on other lanes.
As a further improvement of the invention, a feedforward term is designed as an input to the system model. In the method, the system inputs of the unmanned vehicle are a front wheel steering angle and a distributed driving/braking moment, and the feedforward control aims to reduce generalized lateral force and a yaw moment generated due to collision. For generalized lateral force, the front wheels of the vehicle can obtain the maximum reverse tire lateral force as far as possible through the reverse control of front wheel steering, so that the generalized lateral force generated by collision is reduced, and the transverse motion offset and the transverse speed are reduced. For the collision yaw movement, the vehicle can obtain the maximum reverse yaw moment as far as possible by utilizing the residual longitudinal tire force of the four wheels, so that the high-speed rotation speed and the yaw error generated by collision can be effectively reduced.
As a further improvement of the present invention, dynamic constraints of the input states and discomfortable constraint transitions of the partial states are used. The feedforward input is also constrained by physical and kinematic conditions in the feedback control MPC algorithm. Different from the constraint on the tire side deflection angle of the front wheel tire in the traditional vehicle stability requirement, the vehicle state is far away from the boundary of envelope control under the initial condition of the collision condition, and the traditional method needs large relaxation variables and relaxation gains to ensure the solution of the constraint optimization problem, so that the control cost is increased. The method converts the uncomfortable constraint of the tire slip angle into the input dynamic constraint of the steering angle through a dynamic equation.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention combines the advantages of feedforward control and feedback control, and can realize the safe motion control and the original expected trajectory tracking of the unmanned automobile under the condition of primary collision instability. Lateral motion kinetic energy and yaw motion kinetic energy generated by collision are reduced as much as possible through feedforward, a front wheel steering angle and distributed driving/braking input are respectively designed to obtain the reverse lateral force and the reverse yaw moment of the vehicle, effective system disturbance compensation can be achieved, and the method has a promoting effect on the optimization of bad states in feedback control.
(2) The distributed driving/braking execution mode improves the accessibility of the unmanned automobile motion control, and further improves the robustness of the vehicle to different initial collision disturbances. By converting the discomfort constraint of the extreme unstable vehicle state into the feasibility constraint of control input, the MPC problem solving difficulty is reduced, the calculation time is shortened, and the real-time performance of the algorithm is improved.
(3) Different from the traditional methods which need switching control, the method of the invention has downward compatibility to the initial collision condition, namely, for the collision movement generated by smaller collision force, the method can ensure good control effect and realize safety control. The method is beneficial to the universality and feasibility of the method in practical application.
Drawings
Fig. 1 is a plane dynamics model diagram of a distributed driving unmanned vehicle.
FIG. 2 is a block diagram of a control algorithm system.
FIG. 3 is a diagram showing the verification effect of simulation software on the control algorithm of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
In order to realize safe motion control of an unmanned automobile under the condition of instability after collision, the invention provides a combined motion control strategy of feedforward control and feedback control, which utilizes strong disturbance caused by feedforward compensation collision and the optimization problem of feedback processing with constraint and can solve the problems of control time lag, small control feasible region, small collision condition applicability and the like caused by only using feedback control in the traditional method. The feasibility and the control effect of the method are verified through simulation software. A planar dynamics model of a distributed drive unmanned vehicle is shown in FIG. 1. Wherein FlijIndicating the longitudinal driving force of the wheels of the mobile robot, FcijThe lateral force of the wheels of the mobile robot is shown, wherein the subscript i is f, r is respectively shown as front and rear wheels, the subscript j is l, r is respectively shown as left and right wheels, αijIs the tire slip angle, δijIs the steering angle of the wheels. v. ofx,vyThe longitudinal speed and the transverse speed of the vehicle are respectively, and r is the yaw rate. lf,lrRespectively, the distance between the front and rear axes to the center of gravity,/sHalf of the track width. The sum of the lateral motion kinetic energy and the yaw motion kinetic energy generated by the collision is as follows:
from this equation, it can be seen that the feedforward control requires the use of a reverse lateral force FygAnd a counter yaw moment DeltaMzgTo compensate for E as much as possiblek. According to non-linear tyre dynamicsFor sex and residual tire potential, the trend target for reverse generalized lateral force in feed forward control should be αf→-sgn(αf0)αfpeakThe following feed forward input equations may be listed:
FIG. 2 is a block diagram of a control algorithm system. And a reference model updating module is formed by the reference vehicle model and the expected heading angle correction model, and the corrected heading angle error, the pre-aiming error, the expected state quantity and the expected front wheel side slip angle are input into the joint controller. The feed forward compensation FCC control input is calculated from the state estimator at the previous time and the tire force. Then inputting the input into an MPC controller for constraint and optimization, and finally obtaining the total input (u)FCC+uMPC) To a crash-unstable vehicle. It should be noted that the state-incompatibility constrained transformation is implemented within the MPC controller as follows:
namely, the dynamic constraint boundary of the sidewall deflection angle of the front wheel is converted into the dynamic boundary of the steering angle of the front wheel. Also the torque dynamics constraint can be expressed as:
FIG. 3 is a partial trajectory diagram of simulation software versus the control algorithm of the present invention. The effectiveness of the method is verified through simulation software, wherein a thin black solid line is a lane line, a thick black solid line is the method, and a thick black dotted line is a traditional control method for front wheel active steering and ESC/ESP pure braking. The method has the advantages that the control effect of the traditional method is poor, the driving behaviors of vehicles in other lanes can be influenced in actual conditions, the better control effect is reflected, and the superiority of the method is reflected in error convergence and convergence speed.
The method of the invention designs the vehicle motion controller with the combination of feedforward compensation and feedback control after collision, rapidly reduces the adverse effects of transverse motion deviation and high-speed rotation generated by initial collision, can reduce the probability of secondary collision and realizes the safe motion control of the vehicle under the condition of ultimate instability. Meanwhile, the problem of control phase lag in the traditional control method is solved. Compared with the traditional method, the method has the advantages that the robustness of resisting the disturbance of the vehicle system is greatly improved, and the method can adapt to more serious initial collision conditions. The method is applied to the distributed driving unmanned automobile, and has high engineering application value under the condition of ultimate unstable driving due to quick response and small calculation complexity.
Claims (3)
1. A method for controlling destabilizing motion of an unmanned vehicle following a collision, comprising the steps of: designing the front wheel steering angle and the distributed driving/braking torque by using a feedforward method to integrate the kinetic energy of the transverse motion and the kinetic energy of the rotary motion generated by collision; and then adding the input action of the feedforward control into a feedback control algorithm based on model prediction for further optimization and constraint.
2. The method of claim 1, wherein the feedforward term of the system model input is designed with the system inputs of the unmanned vehicle being the front wheel steering angle and the distributed driving/braking torque; for the generalized lateral force, the front wheels of the vehicle obtain the maximum reverse tire lateral force through the reverse control of front wheel steering; for a crash yaw motion, the vehicle acquires a maximum counter yaw moment through the use of the four-wheel remaining longitudinal tire force.
3. A control method for destabilizing motion of an unmanned vehicle after a collision according to claim 1, wherein the feedforward input is also constrained by physical and kinematic conditions in the feedback control MPC algorithm in dynamic constraint of input states and ill-constrained transition of partial states.
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| CN202010115954.2A CN111231937A (en) | 2020-02-25 | 2020-02-25 | Control method for unstable motion of unmanned vehicle after collision |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112092805A (en) * | 2020-09-23 | 2020-12-18 | 北京理工大学 | Integrated control method and system for collision avoidance and collision damage reduction of intelligent vehicle |
| CN112257267A (en) * | 2020-10-23 | 2021-01-22 | 华人运通(江苏)技术有限公司 | Method and system for manufacturing vehicle tire envelope |
| CN116520857A (en) * | 2023-07-05 | 2023-08-01 | 华东交通大学 | Vehicle track tracking method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112257267A (en) * | 2020-10-23 | 2021-01-22 | 华人运通(江苏)技术有限公司 | Method and system for manufacturing vehicle tire envelope |
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| CN116520857B (en) * | 2023-07-05 | 2023-09-08 | 华东交通大学 | Vehicle track tracking method |
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