CN113183953A - Vehicle post-collision active safety control method and system based on distributed driving chassis - Google Patents
Vehicle post-collision active safety control method and system based on distributed driving chassis Download PDFInfo
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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
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
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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
- B60W30/095—Predicting travel path or likelihood of collision
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- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
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Abstract
The invention discloses a vehicle post-collision active safety control method and system based on a distributed driving chassis, which comprises the steps of constructing a post-collision vehicle motion track planning model based on a polynomial curve method, and updating the model according to vehicle post-collision environment information and vehicle information; processing the updated vehicle motion track planning model after collision by adopting an artificial potential field method to determine a preset vehicle motion track; updating the time-varying state transition matrix according to the motion trail, and replacing the steady state transition matrix of the LQR theory by the updated transition matrix so as to update the time-varying LQR motion trail tracking controller; and optimizing a function constructed based on the overdrive characteristics of the distributed drive chassis and the multiple actuators based on the updated tracking controller, the tire model combining an elliptic formula and a magic formula and the preset vehicle motion track to obtain the longitudinal force of each wheel. The invention can actively and effectively carry out intervention control on the vehicle after the vehicle is impacted by the outside.
Description
Technical Field
The invention relates to the technical field of vehicle post-collision active safety control, in particular to a vehicle post-collision active safety control method and system based on a distributed driving chassis.
Background
With the progress and development of society, traffic transportation systems develop rapidly, the popularity of automobiles is gradually increased, and the quantity of automobile reserves in China is also rising in a straight line. As the number of road vehicles increases, the frequency of traffic accidents increases, and effective passenger protection in vehicle collision accidents has become a major concern in current research. Particularly, under a high-speed working condition, a primary collision accident can cause the vehicle to be rapidly out of control, and secondary and even chain collision accidents caused by the primary collision accident can bring more serious harm. The traditional vehicle mostly adopts a passive safety system represented by an air bag, a safety belt and a crumple energy absorption design, although the protection of passengers in the vehicle can be effectively improved, the continuous accidents caused by the out-of-control vehicle cannot be fundamentally relieved or even avoided.
In recent years, with the rapid development of intelligent vehicle control technology, stability control systems represented by ESP and the like have been widely popularized, but such stability control systems cannot effectively function under severe sideslip drift conditions after impact due to the nonlinear characteristics of tires. There is therefore a pressing need for the development of an active safety system that can effectively exercise intervention control over a vehicle after an external impact has been applied to the vehicle.
Disclosure of Invention
The invention aims to provide a vehicle post-collision active safety control method and system based on a distributed driving chassis, so that the vehicle can be actively and effectively subjected to intervention control after being subjected to external impact.
In order to achieve the purpose, the invention provides the following scheme:
a vehicle post-collision active safety control method based on a distributed drive chassis comprises the following steps:
acquiring front road information, obstacle information and vehicle state information after vehicle collision in real time;
updating a vehicle motion trail planning model after collision according to the current front road information, the current obstacle information and the current vehicle state information; the post-collision vehicle motion track planning model is used for describing coordinates of the vehicle under a geodetic coordinate system and a yaw angle of the vehicle relative to the geodetic coordinate system; the vehicle motion trail planning model after collision is constructed according to the front road information, the obstacle information, the vehicle state information and a polynomial curve method;
processing the updated vehicle motion track planning model after collision by adopting an artificial potential field method, and determining a current expected speed, a current expected yaw angular velocity, a current expected acceleration and a current yaw angular acceleration corresponding to a preset vehicle motion track;
updating a time-varying state transition matrix according to the current expected speed, the current expected acceleration and the current yaw angular acceleration, and replacing a steady state transition matrix of the LQR theory by the updated time-varying state transition matrix so as to update a time-varying LQR motion trail tracking controller; the output of the time-varying LQR motion trail tracking controller is yaw moment; the time-varying LQR motion trail tracking controller is used for cooperatively tracking multiple targets in a motion state after the vehicle is collided;
calculating a minimum value of the target cost function based on the updated time-varying LQR motion trajectory tracking controller, a tire model combining an elliptic formula and a magic formula, the current vehicle state information, and the current expected yaw angular velocity; the minimum value is the longitudinal force of each wheel of the vehicle; the target cost function is a function constructed based on the multi-actuator overdrive characteristic of the distributed drive chassis.
Optionally, the method further includes:
calculating an output torque of each wheel of the vehicle based on the longitudinal force of each wheel of the vehicle.
Optionally, before acquiring the front road information, the obstacle information, and the vehicle state information after the vehicle collision in real time, the method further includes:
judging whether the vehicle is collided or not by adopting an acceleration threshold value method; and if so, acquiring front road information, obstacle information and vehicle state information after the vehicle collides in real time.
Optionally, an acceleration threshold method is adopted to determine whether the vehicle is collided; if yes, then obtain the preceding road information after the vehicle collision, barrier information and vehicle state information in real time, specifically include:
acquiring longitudinal acceleration and lateral acceleration of the vehicle, which are acquired by an acceleration sensor;
calculating a real-time absolute value of the total acceleration of the vehicle according to the longitudinal acceleration and the lateral acceleration of the vehicle;
judging whether the real-time absolute value of the combined acceleration is larger than a set absolute value of the combined acceleration or not;
if yes, acquiring front road information, obstacle information and vehicle state information after the vehicle collides.
Optionally, the construction process of the post-collision vehicle motion trajectory planning model is as follows:
and describing the full state of the collided vehicle by adopting a fifth-order polynomial according to the front road information, the barrier information and the vehicle state information so as to construct a collision vehicle motion trail planning model.
Optionally, the processing, by using an artificial potential field method, the updated vehicle motion trajectory planning model after the collision to determine a current desired speed, a current desired yaw rate, a current desired acceleration, and a current yaw acceleration corresponding to the predetermined vehicle motion trajectory specifically includes:
determining the numerical value of the planned motion trail parameter of the updated vehicle motion trail planning model after collision according to the vehicle state information, and forming a target vector by the motion trail parameter to be planned of the updated vehicle motion trail planning model after collision;
determining a first potential function and a second potential function based on the target vector; the first potential function is a function describing obstacle avoidance by the vehicle; the second potential function is a function describing avoidance of the vehicle to the road boundary;
determining a synthesis function; the comprehensive function is a function which calculates a maximum value after the first potential function and the second potential function are synthesized in a weighting mode;
determining a cost function based on the target vector; the cost function is a function for punishing the vehicle average mass center slip angle;
determining an objective function; the objective function is obtained by processing the comprehensive function and the cost function in a weighting mode;
determining linear constraints and non-linear constraints of the objective function; the linear constraint is the constraint that the lateral displacement and the course angle of the vehicle meet the road constraint and the yaw velocity and the lateral speed are 0 when the vehicle control is finished; the nonlinear constraint is the constraint that the maximum acceleration of the vehicle meets the road adhesion constraint and the lateral force of the rear axle does not exceed the adhesion limit of the rear axle;
processing the target function by adopting an artificial potential field method according to the linear constraint and the nonlinear constraint to determine the numerical value of the motion trail parameter to be planned;
updating the vehicle motion trail planning model after collision according to the numerical value of the planned motion trail parameter and the numerical value of the motion trail parameter to be planned;
and carrying out derivation processing on the updated vehicle motion trail planning model after collision to obtain the expected speed, the expected yaw rate, the expected acceleration and the yaw acceleration corresponding to the preset vehicle motion trail.
Optionally, the time-varying LQR motion trajectory tracking controller is constructed by:
constructing a nonlinear system according to a vehicle dynamics equation and a kinematics equation;
carrying out local linearization on the nonlinear system to obtain a linear state space expression;
discretizing the linear state space expression through sampling time to obtain a discrete state space expression;
respectively carrying out coordinate transformation on the expected speed, the expected acceleration and the yaw angular acceleration to a vehicle coordinate system to obtain a reference state matrix; the reference state matrix comprises a resultant force and a yaw moment;
carrying out difference processing on the discrete state space expression and the reference state matrix to obtain a vehicle deviation dynamic system; wherein the vehicle deviation dynamics system includes a time-varying state transition matrix;
and forming a time-varying LQR motion trail tracking controller based on the LQR theory and the vehicle deviation dynamic system.
A vehicle collision rear active safety control system based on a distributed driving chassis adopts a layered control architecture and comprises an upper information acquisition module, a collision rear vehicle motion track planning model updating module and a speed and acceleration calculation module, a middle time-varying LQR motion track tracking controller updating module and a lower longitudinal force distribution module;
the information acquisition module is used for acquiring front road information, obstacle information and vehicle state information after vehicle collision in real time;
the vehicle motion trail planning model updating module is used for updating the vehicle motion trail planning model after collision according to the current front road information, the current obstacle information and the current vehicle state information; the post-collision vehicle motion track planning model is used for describing coordinates of the vehicle under a geodetic coordinate system and a yaw angle of the vehicle relative to the geodetic coordinate system; the vehicle motion trail planning model after collision is constructed according to the front road information, the obstacle information, the vehicle state information and a polynomial curve method;
the speed and acceleration calculation module is used for processing the updated vehicle motion trail planning model after collision by adopting an artificial potential field method, and determining a current expected speed, a current expected yaw angular velocity, a current expected acceleration and a current yaw angular acceleration corresponding to a preset vehicle motion trail;
the time-varying LQR motion trail tracking controller updating module is used for updating a time-varying state transition matrix according to the current expected speed, the current expected acceleration and the current yaw angular acceleration, and replacing a constant state transition matrix of an LQR theory by the updated time-varying state transition matrix so as to update the time-varying LQR motion trail tracking controller; the output of the time-varying LQR motion trail tracking controller is yaw moment; the time-varying LQR motion trail tracking controller is used for cooperatively tracking multiple targets in a motion state after the vehicle is collided;
the longitudinal force distribution module is used for calculating the minimum value of the target cost function based on the updated time-varying LQR motion trail tracking controller, a tire model combining an elliptic formula and a magic formula, the current vehicle state information and the current expected yaw angular velocity; the minimum value is the longitudinal force of each wheel of the vehicle; the target cost function is a function constructed based on the multi-actuator overdrive characteristic of the distributed drive chassis.
Optionally, the method further includes:
an output torque calculation module for calculating an output torque of each wheel of the vehicle based on the longitudinal force of each wheel of the vehicle.
Optionally, the method further includes:
the judging module is used for judging whether the vehicle is collided or not by adopting an acceleration threshold value method;
and the returning module is used for returning the information acquisition module when the vehicle collides.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention designs a vehicle full-state post-collision motion planning module based on the combination of an artificial potential field method and a polynomial curve method, and realizes the gradual stability of the vehicle after collision while avoiding obstacles. The invention is improved based on a linear quadratic programming (LQR), and designs a time-varying LQR motion trail tracking controller, thereby realizing multi-target cooperative tracking of the motion state of the vehicle after collision. Therefore, by adopting the technical scheme provided by the invention, the intervention control can be actively and effectively carried out on the vehicle after the vehicle is impacted by the outside.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a vehicle post-collision active safety control method based on a distributed drive chassis according to the present invention;
FIG. 2 is a schematic structural diagram of a vehicle post-collision active safety control system based on a distributed drive chassis according to the present invention;
fig. 3 is a process schematic diagram of the vehicle post-collision active safety control method based on the distributed drive chassis.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a vehicle post-collision active safety control method and system based on a distributed driving chassis, so that the vehicle can be actively and effectively subjected to intervention control after being subjected to external impact.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Term of art
Course angle: and under a ground coordinate system, the included angle between the vehicle mass center speed and the transverse axis.
Centroid slip angle: the included angle between the speed direction of the mass center of the vehicle and the direction of the head of the vehicle.
Vehicle yaw angle: difference between heading angle and centroid slip angle.
In recent years, a distributed drive chassis is taken as an advanced chassis configuration, and an important development direction of future automobiles is provided by the multi-actuator overdrive characteristic of the distributed drive chassis. Therefore, the active safety control system for avoiding the obstacle after collision is developed based on the distributed driving chassis configuration.
Lqr (linear quadratic regulator), which is a linear system given in state space form in modern control theory, and the objective function is a quadratic function of the state of the object and the control input. The optimal LQR design means that the designed state feedback controller K is to make the quadratic objective function J take the minimum value, and the state feedback controller K is uniquely determined by the weight matrix Q and the weight matrix R, so the selection of the weight matrix Q and the weight matrix R is particularly important. The LQR theory is a state space design method which is developed earliest and maturely in modern control theory. Particularly, the LQR can obtain the optimal control rule of state linear feedback, and the closed-loop optimal control is easy to form.
Existing vehicle stability control systems and active safety systems such as ESP or ESC better conform to the steering characteristics expected by the driver, by generating an additional yaw moment using four-wheel braking torque in response to steering wheel angle signals, to track the desired yaw rate or centroid yaw angle. However, under the working conditions aimed at by the patent, on one hand, the panic of the driver caused by the impact is difficult to give reasonable operation instructions in a short time, so that the traditional vehicle active stability control is difficult to obtain an effective stability target; on the other hand, a control system represented by an ESP (electronic stability program) usually restrains longitudinal force according to road surface adhesion so as to avoid attenuation of lateral force, and under the working condition that a vehicle is in drift sideslip due to external collision and impact, wheels are usually in an over-saturation stage, so that the control system is limited to play a role to a great extent.
Thus, the disadvantages and shortcomings of the above prior art solutions are addressed. The method comprises the steps of designing a vehicle motion track planning model after collision based on a polynomial curve and an artificial potential field method, improving the traditional steady-state LQR to form a time-varying LQR motion track tracking controller, and then cooperatively tracking a multi-state target by using the time-varying LQR motion track tracking controller; and then aiming at the tire over-saturation problem under the limit working condition after the vehicle is collided, a multi-actuator coordination controller based on optimal distribution is designed by utilizing the characteristic of multi-actuator over-drive of a distributed driving system, and the upper layer generalized force and the yaw moment are optimally distributed.
Example one
As shown in fig. 1, the active safety control method after vehicle collision based on the distributed drive chassis provided in this embodiment includes the following steps:
step 101: and acquiring front road information, obstacle information and vehicle state information after the vehicle is collided in real time.
Step 102: updating a vehicle motion trail planning model after collision according to the current front road information, the current obstacle information and the current vehicle state information; the post-collision vehicle motion track planning model is used for describing coordinates of the vehicle under a geodetic coordinate system and a yaw angle of the vehicle relative to the geodetic coordinate system; the vehicle motion trail planning model after collision is constructed according to the front road information, the obstacle information, the vehicle state information and a polynomial curve method.
Step 103: and processing the updated vehicle motion track planning model after collision by adopting an artificial potential field method, and determining the current expected speed, the current expected yaw angular velocity, the current expected acceleration and the current yaw angular acceleration corresponding to the preset vehicle motion track.
Step 104: updating a time-varying state transition matrix according to the current expected speed, the current expected acceleration and the current yaw angular acceleration, and replacing a steady state transition matrix of the LQR theory by the updated time-varying state transition matrix so as to update a time-varying LQR motion trail tracking controller; the output of the time-varying LQR motion trail tracking controller is yaw moment; the time-varying LQR motion trail tracking controller is used for cooperatively tracking multiple targets in a motion state after the vehicle is collided.
Step 105: calculating a minimum value of the target cost function based on the updated time-varying LQR motion trajectory tracking controller, a tire model combining an elliptic formula and a magic formula, the current vehicle state information, and the current expected yaw angular velocity; the minimum value is the longitudinal force of each wheel of the vehicle; the target cost function is a function constructed based on the multi-actuator overdrive characteristic of the distributed drive chassis.
Step 106: calculating an output torque of each wheel of the vehicle based on the longitudinal force of each wheel of the vehicle.
Preferably, before executing step 101, the method further comprises:
judging whether the vehicle is collided or not by adopting an acceleration threshold value method; and if so, acquiring front road information, obstacle information and vehicle state information after the vehicle collides in real time.
Judging whether the vehicle is collided or not by adopting an acceleration threshold value method; if yes, then obtain the preceding road information after the vehicle collision, barrier information and vehicle state information in real time, specifically include:
acquiring longitudinal acceleration and lateral acceleration of the vehicle, which are acquired by an acceleration sensor; calculating a real-time absolute value of the total acceleration of the vehicle according to the longitudinal acceleration and the lateral acceleration of the vehicle; judging whether the real-time absolute value of the combined acceleration is larger than a set absolute value of the combined acceleration or not; if yes, acquiring front road information, obstacle information and vehicle state information after the vehicle collides.
The construction process of the post-collision vehicle motion trajectory planning model in step 102 is as follows:
and describing the full state of the collided vehicle by adopting a fifth-order polynomial according to the front road information, the barrier information and the vehicle state information so as to construct a collision vehicle motion trail planning model.
Step 103 specifically comprises:
and determining the numerical value of the planned motion trail parameter of the updated vehicle motion trail planning model after collision according to the vehicle state information, and forming a target vector by the motion trail parameter to be planned of the updated vehicle motion trail planning model after collision. Determining a first potential function and a second potential function based on the target vector; the first potential function is a function describing obstacle avoidance by the vehicle; the second potential function is a function describing avoidance of the vehicle to the road boundary. Determining a synthesis function; the comprehensive function is a function which calculates a maximum value after the first potential function and the second potential function are synthesized in a weighting mode. Determining a cost function based on the target vector; the cost function is a function for punishing the vehicle average mass center slip angle. Determining an objective function; the objective function is obtained by processing the comprehensive function and the cost function in a weighting mode. Determining linear constraints and non-linear constraints of the objective function; the linear constraint is the constraint that the lateral displacement and the course angle of the vehicle meet the road constraint and the yaw velocity and the lateral speed are 0 when the vehicle control is finished; the nonlinear constraint is the constraint that the maximum acceleration of the vehicle meets the road adhesion constraint and the lateral force of the rear axle does not exceed the adhesion limit of the rear axle. And processing the target function by adopting an artificial potential field method according to the linear constraint and the nonlinear constraint to determine the numerical value of the motion trail parameter to be planned. And updating the vehicle motion trail planning model after collision according to the numerical value of the planned motion trail parameter and the numerical value of the motion trail parameter to be planned. And carrying out derivation processing on the updated vehicle motion trail planning model after collision to obtain the expected speed, the expected yaw rate, the expected acceleration and the yaw acceleration corresponding to the preset vehicle motion trail.
The time-varying LQR motion trajectory tracking controller in step 104 is constructed by: and constructing a nonlinear system according to a vehicle dynamic equation and a kinematic equation. And carrying out local linearization on the nonlinear system to obtain a linear state space expression. And discretizing the linear state space expression through sampling time to obtain a discrete state space expression. Respectively carrying out coordinate transformation on the expected speed, the expected acceleration and the yaw angular acceleration to a vehicle coordinate system to obtain a reference state matrix; the reference state matrix includes a resultant force and a yaw moment. Carrying out difference processing on the discrete state space expression and the reference state matrix to obtain a vehicle deviation dynamic system; wherein the vehicle deviation dynamics system includes a time-varying state transition matrix. And forming a time-varying LQR motion trail tracking controller based on the LQR theory and the vehicle deviation dynamic system.
The specific processing procedure of step 105 refers to the third embodiment, and will not be described herein.
Example two
As shown in fig. 2, the present embodiment provides a vehicle post-collision active safety control system based on a distributed drive chassis, where the vehicle post-collision active safety control system adopts a layered control architecture, and includes an upper information acquisition module, a post-collision vehicle motion trajectory planning model updating module, a speed and acceleration calculation module, a middle time-varying LQR motion trajectory tracking controller updating module, and a lower longitudinal force distribution module.
The information acquiring module 201 is configured to acquire front road information, obstacle information, and vehicle state information after a vehicle collision in real time.
The after-collision vehicle motion trail planning model updating module 202 is used for updating the after-collision vehicle motion trail planning model according to the current front road information, the current obstacle information and the current vehicle state information; the post-collision vehicle motion track planning model is used for describing coordinates of the vehicle under a geodetic coordinate system and a yaw angle of the vehicle relative to the geodetic coordinate system; the vehicle motion trail planning model after collision is constructed according to the front road information, the obstacle information, the vehicle state information and a polynomial curve method.
The speed and acceleration calculation module 203 is configured to process the updated vehicle motion trajectory planning model after the collision by using an artificial potential field method, and determine a current desired speed, a current desired yaw rate, a current desired acceleration, and a current yaw acceleration corresponding to a predetermined vehicle motion trajectory.
The time-varying LQR motion trajectory tracking controller updating module 204 is configured to update a time-varying state transition matrix according to the current desired speed, the current desired acceleration, and the current yaw angular acceleration, and replace a steady state transition matrix of an LQR theory with the updated time-varying state transition matrix to update the time-varying LQR motion trajectory tracking controller; the output of the time-varying LQR motion trail tracking controller is yaw moment; the time-varying LQR motion trail tracking controller is used for cooperatively tracking multiple targets in a motion state after the vehicle is collided.
The longitudinal force distribution module 205 is configured to calculate a minimum value of the target cost function based on the updated time-varying LQR motion trajectory tracking controller, a tire model combining an elliptic formula and a magic formula, the current vehicle state information, and the current desired yaw rate; the minimum value is the longitudinal force of each wheel of the vehicle; the target cost function is a function constructed based on the multi-actuator overdrive characteristic of the distributed drive chassis.
An output torque calculation module 206 for calculating an output torque of each wheel of the vehicle based on said longitudinal force of each wheel of the vehicle.
Wherein, this system still includes:
the judging module is used for judging whether the vehicle is collided or not by adopting an acceleration threshold value method; and the returning module is used for returning the information acquisition module when the vehicle collides.
EXAMPLE III
As shown in fig. 3, the method for actively controlling the vehicle after collision based on the distributed drive chassis according to the present embodiment includes the following steps:
firstly, an acceleration threshold method is adopted to effectively judge whether a vehicle is collided, and the method specifically comprises the following steps:
by means of an acceleration sensor mounted on the vehicle, for longitudinal acceleration axAnd lateral acceleration ayCollecting; then, the real-time absolute value a of the resultant acceleration of the vehicle is calculatedabs(ii) a Then, comparing the real-time absolute value a of the resultant accelerationabsAnd setting an absolute value with the resultant acceleration to judge whether the vehicle collides.
Since the conventional road adhesion coefficient is more than 0.1 to 1.2, the absolute value of the set vehicle acceleration during normal running does not exceed 1.2g, wherein g is the gravity acceleration value. The total acceleration setting absolute value can be set to 1.5g, taking into account the difference and the sensor measurement error. When in useReal-time absolute value a of resultant accelerationabsAbove 1.5g, the vehicle is considered to have encountered an external collision impact and the active safety control system for a subsequent vehicle collision is activated.
The real-time absolute value a of the resultant accelerationabsCalculation methods, e.g. formulae
As shown.
The active safety control system after the vehicle collides with the vehicle provided by the embodiment adopts a layered control architecture, and comprises an upper-layer motion planning module based on a polynomial curve, a motion trajectory tracking controller based on time-varying LQR and a lower-layer torque distributor.
After the collision detection module determines that the vehicle collision occurs, the environment sensing module and the state estimation module collect front road information, obstacle information and current vehicle state information. The motion planning module describes the full state of the vehicle using a fifth order polynomial as shown in the following equation:
wherein (X, Y) is the coordinate of the vehicle under the geodetic coordinate system, psi is the yaw angle of the vehicle relative to the geodetic coordinate system, ak,bk,ckFor the fifth-order polynomial parameter to be optimized, τ0And τ are the initial time of the planning process and a certain moment in the planning time domain, respectively. Some of the parameters may be determined based on the current state of the vehicle, as shown in the following equation:
and the other motion trajectory parameters to be planned form an optimal solved target vector:
p(1:12)＝[a2,a3,a4,a5,b2,b3,b4,b5,c2,c3,c4,c5] (1.4)。
describing the distribution of the impassable area by using an exponential cost function, wherein U is used1And U2Describing the avoidance of obstacles by the vehicle and of the road boundaries by the vehicle, X, respectivelyb，YbFor describing the position of the obstacle in the geodetic coordinate systemmin，YmaxRespectively a lower boundary and an upper boundary describing the road boundary.
And integrating the two potential functions in a weighting mode, and taking the maximum value as the punishment degree of the path, wherein the punishment degree is shown as the following formula:
wherein tau isf、k1、k2The weighting coefficients of the artificial potential field function of the terminal time, the obstacles and the road boundary are planned. Meanwhile, in order to describe the gradual stability requirement of the vehicle, the average centroid slip angle of the vehicle is punished to form a cost function Q, which is shown as the following formula:
and combining the function representing the obstacle avoidance performance and the function representing the stability by weighting to form a final optimization objective function, which is shown as the following formula:
S＝k3U+k4Q (1.9)。
before solving, first defining linear constraints and non-linear constraints of the vehicle, wherein the linear constraints are mainlyConsidering the kinematic attitude of the vehicle end, the lateral displacement Y (τ) of the vehicle at the end of the controlf) And heading angle psi (tau)f) Should satisfy road constraints, and yaw rate
And lateral vehicle speed
Should be 0, so the following linear equation can be obtained:
the nonlinear constraint mainly considers the dynamic constraint of the vehicle, firstly, the maximum acceleration of the vehicle should meet the road adhesion constraint, and the resultant acceleration of a specified motion track can be calculated by solving a second derivative through a polynomial curve, as shown in the following formula:
and (3) performing road adhesion constraint limitation on the maximum resultant acceleration of the path to be obtained, as shown in the following formula:
by taking the derivative from the fifth-order polynomial curve of the vehicle, the expected lateral force and yaw moment corresponding to the path can be obtained based on the darnaebel principle, as shown in the following formula:
the expected lateral force of the rear wheel can be obtained by carrying out static analysis on the vehicle based on the single-track model, and the following formula is shown:
the rear axle lateral force should not theoretically exceed the attachment limit of the rear axle, and therefore there is an inequality constraint as shown below:
and finally, solving the parameter vector p which minimizes the optimization objective function in the linear and nonlinear constraint ranges, so as to obtain a complete optimal motion track uniquely. The optimal solution problem can be summarized as follows:
through the optimized track characterized by the quintic curve, the expected speed and the yaw rate corresponding to the preset track, and the expected acceleration and the yaw acceleration can be obtained by solving the derivative and the second derivative respectively.
According to the course angle of the vehicle, the speed vector of the vehicle under the geodetic coordinate system can be subjected to coordinate transformation to the vehicle coordinate system, wherein TcoIs a coordinate transformation matrix.
Likewise, the ideal reference force and yaw moment can be obtained by coordinate transformation of the desired acceleration and yaw acceleration into the vehicle coordinate system.
The vehicle dynamics equations and kinematics equations are as follows:
the differential equation can form a nonlinear system, and through local linearization, the following linear state space expression can be formed, as shown in the following formula:
wherein, A is a system Jacobian matrix, and B is an input matrix of the system.
Discretizing the continuous system by sampling time T:
a discrete state space expression is formed:
and obtaining a vehicle deviation dynamic system by performing difference processing on the discrete state space expression and a reference state, wherein the following formula is shown:
wherein x isdkAnd urkThe expected vehicle state and the desired control input at k steps, respectively, are as follows:
a closed-loop motion tracking controller is designed based on an LQR theory, and a time-varying state transition matrix is adopted to replace a traditional steady state transition matrix, so that the time-varying LQR motion trajectory tracking controller is formed.
Defining a controller design objective as shown in the following equation:
wherein Q and R are weight coefficient matrix and feedback gain control law KkSolving the Riccati matrix as shown in the following formula:
the amount of correction input by the controller can then be determined as shown in the following equation:
Δuk＝-Kkξk (1.29)。
the final closed-loop controller control quantity is:
uk＝Δuk+urk (1.30)。
after the resultant force and the yaw torque output by the closed-loop controller are obtained, the invention designs a multi-actuator coordination control method based on optimal control distribution aiming at the multi-actuator overdrive characteristic of the distributed drive chassis. First, a cost function for optimal control is defined as follows:
V＝ε1(Fxo-Fx)2+ε2(Fyo-Fy)2+ε3(Mzo-Mz)2 (1.31)。
wherein epsilon1,ε2,ε3Weighting factors, F, for the control targetsxo，Fyo，MzoVehicle assembly derived for LQR tracking controller respectivelyLongitudinal body forces, lateral forces, and yaw moments. The longitudinal force and yaw moment of the vehicle (which is determined from the time-varying LQR motion trajectory tracking controller) may be represented according to a vehicle dual-rail model, as shown in the following equation:
where δ is the steering angle of the front wheel of the vehicle, and due to the strong non-linear characteristic of the tire and the highly coupled characteristic in the longitudinal and lateral directions, a tire model needs to be established to characterize the tire force in the longitudinal and lateral directions so as to better determine the effective constraint of the tire force.
Velocity vectors at the four wheel centers of the vehicle can be calculated based on the vehicle center-of-mass velocity and the yaw-rate:
further, the slip angle alpha under the pure side slip working condition of the tire can be obtained through the wheel center velocity vectoriFor the front and rear axle tires, there are:
calculating the lateral force of the tire in pure sideslip under the current working condition by adopting a magic formula
Wherein b is1-b8The tire model parameters can be identified off-line by the least squares method from the tire test data.
The longitudinal force and lateral force coupling relation of the tire is expressed by an ellipse formula:
according to the configuration of the distributed driving actuator, the variables to be optimized are set as follows:
xc＝[δFx1 Fx2 Fx3 Fx4] (1.38)。
therefore, the optimal control problem can be summarized as finding optimal optimization variables, namely the steering angle of the front wheels and the differential longitudinal force of the four wheels, obtaining a minimized optimization cost function shown in 1.8 while satisfying the constraint shown in the formula 1.13, efficiently solving the nonlinear optimization problem on line by adopting an interior point method, and summarizing the solved problem into
After the longitudinal force of each wheel of the vehicle is obtained, the output torque of the four wheels can be determined by the following equation, ignoring the inertia and rolling resistance of the wheels.
Ti≈Fxireff (1.40)。
Compared with the prior art, the invention has the core creation points that:
firstly, by utilizing the over-driving characteristic of a plurality of actuators of a distributed driving chassis, an active safety obstacle avoidance stability control system after a vehicle is impacted by the outside is designed, and the blank of the current related technical scheme is filled.
Secondly, based on the combination of an artificial potential field method and a polynomial curve method, a vehicle full-state post-collision motion planning module is designed, and the vehicle post-collision progressive stability is realized while obstacle avoidance is carried out.
And thirdly, a time-varying LQR motion trail tracking controller is designed on the basis of improvement of a linear quadratic planner (LQR), and multi-target cooperative tracking of the motion state of the vehicle after collision is realized.
And fourthly, establishing a tire model combining an elliptic formula and a magic formula, and performing coordination control on front wheel steering and a plurality of hub motor actuators based on an optimal control distribution method.
Compared with the prior art, the invention has the advantages that:
firstly, the distributed driving chassis is used as the output of the control actuator, so that the response precision and the control freedom degree of the system are improved, the response difficulty of the controller is reduced, and the control effect is improved.
Secondly, a layered control architecture and a triggering condition based on a combined acceleration threshold are adopted, full-automatic vehicle take-over and controller intervention are realized, and the vehicle is controlled to a stable state when the vehicle is out of control;
and thirdly, a multi-actuator coordination control method based on optimal control distribution is developed, a combined tire model is established according to the limit working condition of vehicle drifting and sideslip, boundary constraint conditions are determined according to the combined tire model, and tire force can be further fully excavated to realize optimal tracking of a control target.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (10)
1. A vehicle post-collision active safety control method based on a distributed drive chassis is characterized by comprising the following steps:
acquiring front road information, obstacle information and vehicle state information after vehicle collision in real time;
updating a vehicle motion trail planning model after collision according to the current front road information, the current obstacle information and the current vehicle state information; the post-collision vehicle motion track planning model is used for describing coordinates of the vehicle under a geodetic coordinate system and a yaw angle of the vehicle relative to the geodetic coordinate system; the vehicle motion trail planning model after collision is constructed according to the front road information, the obstacle information, the vehicle state information and a polynomial curve method;
processing the updated vehicle motion track planning model after collision by adopting an artificial potential field method, and determining a current expected speed, a current expected yaw angular velocity, a current expected acceleration and a current yaw angular acceleration corresponding to a preset vehicle motion track;
updating a time-varying state transition matrix according to the current expected speed, the current expected acceleration and the current yaw angular acceleration, and replacing a steady state transition matrix of the LQR theory by the updated time-varying state transition matrix so as to update a time-varying LQR motion trail tracking controller; the output of the time-varying LQR motion trail tracking controller is yaw moment; the time-varying LQR motion trail tracking controller is used for cooperatively tracking multiple targets in a motion state after the vehicle is collided;
calculating a minimum value of the target cost function based on the updated time-varying LQR motion trajectory tracking controller, a tire model combining an elliptic formula and a magic formula, the current vehicle state information, and the current expected yaw angular velocity; the minimum value is the longitudinal force of each wheel of the vehicle; the target cost function is a function constructed based on the multi-actuator overdrive characteristic of the distributed drive chassis.
2. The vehicle post-impact active safety control method based on the distributed drive chassis according to claim 1, characterized by further comprising:
calculating an output torque of each wheel of the vehicle based on the longitudinal force of each wheel of the vehicle.
3. The active safety control method for the vehicle after the collision based on the distributed drive chassis as claimed in claim 1, further comprising, before acquiring the road information ahead of the vehicle after the collision, the obstacle information and the vehicle state information in real time:
judging whether the vehicle is collided or not by adopting an acceleration threshold value method; and if so, acquiring front road information, obstacle information and vehicle state information after the vehicle collides in real time.
4. The active safety control method after the vehicle collides based on the distributed drive chassis is characterized in that an acceleration threshold method is adopted to judge whether the vehicle collides; if yes, then obtain the preceding road information after the vehicle collision, barrier information and vehicle state information in real time, specifically include:
acquiring longitudinal acceleration and lateral acceleration of the vehicle, which are acquired by an acceleration sensor;
calculating a real-time absolute value of the total acceleration of the vehicle according to the longitudinal acceleration and the lateral acceleration of the vehicle;
judging whether the real-time absolute value of the combined acceleration is larger than a set absolute value of the combined acceleration or not;
if yes, acquiring front road information, obstacle information and vehicle state information after the vehicle collides.
5. The vehicle post-collision active safety control method based on the distributed drive chassis is characterized in that the construction process of the vehicle post-collision motion trail planning model is as follows:
and describing the full state of the collided vehicle by adopting a fifth-order polynomial according to the front road information, the barrier information and the vehicle state information so as to construct a collision vehicle motion trail planning model.
6. The method according to claim 1, wherein the updated post-collision vehicle motion trajectory planning model is processed by using an artificial potential field method to determine a current desired speed, a current desired yaw rate, a current desired acceleration and a current yaw acceleration corresponding to a predetermined vehicle motion trajectory, and specifically comprises:
determining the numerical value of the planned motion trail parameter of the updated vehicle motion trail planning model after collision according to the vehicle state information, and forming a target vector by the motion trail parameter to be planned of the updated vehicle motion trail planning model after collision;
determining a first potential function and a second potential function based on the target vector; the first potential function is a function describing obstacle avoidance by the vehicle; the second potential function is a function describing avoidance of the vehicle to the road boundary;
determining a synthesis function; the comprehensive function is a function which calculates a maximum value after the first potential function and the second potential function are synthesized in a weighting mode;
determining a cost function based on the target vector; the cost function is a function for punishing the vehicle average mass center slip angle;
determining an objective function; the objective function is obtained by processing the comprehensive function and the cost function in a weighting mode;
determining linear constraints and non-linear constraints of the objective function; the linear constraint is the constraint that the lateral displacement and the course angle of the vehicle meet the road constraint and the yaw velocity and the lateral speed are 0 when the vehicle control is finished; the nonlinear constraint is the constraint that the maximum acceleration of the vehicle meets the road adhesion constraint and the lateral force of the rear axle does not exceed the adhesion limit of the rear axle;
processing the target function by adopting an artificial potential field method according to the linear constraint and the nonlinear constraint to determine the numerical value of the motion trail parameter to be planned;
updating the vehicle motion trail planning model after collision according to the numerical value of the planned motion trail parameter and the numerical value of the motion trail parameter to be planned;
and carrying out derivation processing on the updated vehicle motion trail planning model after collision to obtain the expected speed, the expected yaw rate, the expected acceleration and the yaw acceleration corresponding to the preset vehicle motion trail.
7. The vehicle post-impact active safety control method based on the distributed drive chassis is characterized in that the time-varying LQR motion trail tracking controller is constructed by the following steps:
constructing a nonlinear system according to a vehicle dynamics equation and a kinematics equation;
carrying out local linearization on the nonlinear system to obtain a linear state space expression;
discretizing the linear state space expression through sampling time to obtain a discrete state space expression;
respectively carrying out coordinate transformation on the expected speed, the expected acceleration and the yaw angular acceleration to a vehicle coordinate system to obtain a reference state matrix; the reference state matrix comprises a resultant force and a yaw moment;
carrying out difference processing on the discrete state space expression and the reference state matrix to obtain a vehicle deviation dynamic system; wherein the vehicle deviation dynamics system includes a time-varying state transition matrix;
and forming a time-varying LQR motion trail tracking controller based on the LQR theory and the vehicle deviation dynamic system.
8. A vehicle collision rear active safety control system based on a distributed driving chassis is characterized in that the vehicle collision rear active safety control system adopts a layered control architecture and comprises an upper information acquisition module, a collision rear vehicle motion track planning model updating module and a speed and acceleration calculation module, a middle time-varying LQR motion track tracking controller updating module and a lower longitudinal force distribution module;
the information acquisition module is used for acquiring front road information, obstacle information and vehicle state information after vehicle collision in real time;
the vehicle motion trail planning model updating module is used for updating the vehicle motion trail planning model after collision according to the current front road information, the current obstacle information and the current vehicle state information; the post-collision vehicle motion track planning model is used for describing coordinates of the vehicle under a geodetic coordinate system and a yaw angle of the vehicle relative to the geodetic coordinate system; the vehicle motion trail planning model after collision is constructed according to the front road information, the obstacle information, the vehicle state information and a polynomial curve method;
the speed and acceleration calculation module is used for processing the updated vehicle motion trail planning model after collision by adopting an artificial potential field method, and determining a current expected speed, a current expected yaw angular velocity, a current expected acceleration and a current yaw angular acceleration corresponding to a preset vehicle motion trail;
the time-varying LQR motion trail tracking controller updating module is used for updating a time-varying state transition matrix according to the current expected speed, the current expected acceleration and the current yaw angular acceleration, and replacing a constant state transition matrix of an LQR theory by the updated time-varying state transition matrix so as to update the time-varying LQR motion trail tracking controller; the output of the time-varying LQR motion trail tracking controller is yaw moment; the time-varying LQR motion trail tracking controller is used for cooperatively tracking multiple targets in a motion state after the vehicle is collided;
the longitudinal force distribution module is used for calculating the minimum value of the target cost function based on the updated time-varying LQR motion trail tracking controller, a tire model combining an elliptic formula and a magic formula, the current vehicle state information and the current expected yaw angular velocity; the minimum value is the longitudinal force of each wheel of the vehicle; the target cost function is a function constructed based on the multi-actuator overdrive characteristic of the distributed drive chassis.
9. The active safety control system for vehicle after-impact based on distributed drive chassis of claim 8, further comprising:
an output torque calculation module for calculating an output torque of each wheel of the vehicle based on the longitudinal force of each wheel of the vehicle.
10. The active safety control system for vehicle after-impact based on distributed drive chassis of claim 9, further comprising:
the judging module is used for judging whether the vehicle is collided or not by adopting an acceleration threshold value method;
and the returning module is used for returning the information acquisition module when the vehicle collides.
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