CN113306545A - Vehicle trajectory tracking control method and system - Google Patents

Vehicle trajectory tracking control method and system Download PDF

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CN113306545A
CN113306545A CN202110799914.9A CN202110799914A CN113306545A CN 113306545 A CN113306545 A CN 113306545A CN 202110799914 A CN202110799914 A CN 202110799914A CN 113306545 A CN113306545 A CN 113306545A
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vehicle
control
tire
longitudinal force
moment
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CN113306545B (en
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吴海东
李子晗
卢荡
黄世庆
龙祥
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Jilin University
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Jilin University
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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
    • B60W30/02—Control of vehicle driving stability
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0031—Mathematical model of the vehicle
    • B60W2050/0034—Multiple-track, 2D vehicle model, e.g. four-wheel model

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Human Computer Interaction (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

The invention relates to a vehicle track tracking control method and a vehicle track tracking control system, wherein a UniTire tire model with full working condition and high precision is introduced, and is embedded into a linear time-varying MPC control algorithm to realize track tracking, so that the adaptive scenes of intelligent vehicle track tracking control, such as high speed, low adhesion road surface, large slip ratio and the like, are further expanded, and the tracking performance is improved. Meanwhile, the process of local linearization of the model is calculated by adopting a numerical calculation method, so that the calculation complexity is reduced on the premise of not influencing the calculation precision, and the expected track can be tracked and the stability of the vehicle can be controlled under the condition of large tire slip rate.

Description

Vehicle trajectory tracking control method and system
Technical Field
The invention relates to the technical field of intelligent vehicle control, in particular to a vehicle track tracking control method and system.
Background
The tire is used as the only contact part of the vehicle and the ground, the tire dynamic model has close relation with the whole vehicle dynamic model and the vehicle stability control, and the precision of the tire model directly influences the precision of the vehicle control and the driving safety.
The research of the intelligent vehicle is generally divided into three aspects of perception, planning and vehicle control, the control of the intelligent vehicle generally refers to tracking an expected track calculated by a perception layer and a planning layer, the track tracking comprises tracking an expected path and an expected vehicle speed, and meanwhile, proper constraint conditions are established to ensure the stability of the vehicle. As one of the key technologies for intelligent vehicle research, there are many control methods that can be implemented in intelligent vehicle trajectory tracking.
However, in the conventional vehicle trajectory tracking control, the adopted tire model often needs complex numerical operation, so that the tire characteristics are simplified in order to reduce the solving complexity, and the robustness of a control system is influenced.
Disclosure of Invention
The invention aims to provide a vehicle track tracking control method and a vehicle track tracking control system, which improve the control precision by applying a UniTire tire model to vehicle track tracking control.
In order to achieve the purpose, the invention provides the following scheme:
a vehicle trajectory tracking control method, the method comprising:
acquiring transverse control parameters and longitudinal control parameters of a vehicle;
obtaining a yaw moment by combining the transverse control parameters with a UniTire tire model;
obtaining a total longitudinal force through a sliding mode controller according to the longitudinal control parameters;
and obtaining the control moment of the vehicle according to the yaw moment and the total longitudinal force, and realizing the track tracking control of the vehicle according to the control moment.
Optionally, the obtaining a yaw moment according to the lateral control parameter and by combining a UniTire model includes:
establishing an output equation according to a slip angle formula in a UniTire tire model;
establishing a nonlinear state equation according to the transverse control parameters and a seven-degree-of-freedom model of the vehicle;
discretizing and linearizing the output equation and the nonlinear state equation to obtain a Jacobian matrix;
constructing a first objective function according to the Jacobian matrix, and sorting the first objective function to obtain a quadratic objective function;
and solving the yaw moment variation when the quadratic form objective function is minimum, and obtaining the yaw moment at the next moment according to the yaw moment variation.
Optionally, after obtaining the jacobian matrix, the method further includes:
and calculating the Jacobian matrix by using a numerical derivation method to obtain a deformed Jacobian matrix, and replacing the Jacobian matrix in the quadratic objective function acquisition process with the deformed Jacobian matrix.
Optionally, the first objective function includes:
Figure BDA0003164273140000021
wherein the content of the first and second substances,
Figure BDA0003164273140000022
is the difference between the system output and the reference output,
Figure BDA0003164273140000023
is the yaw angle of the vehicle,
Figure BDA0003164273140000024
is yaw rate, Y is ordinate of centroid relative to geodetic coordinate system, xi is state variable, t is time, mu is control variable, delta U (t) is variation of control quantity, rho is weight coefficient, epsilon is relaxation factor,
Figure BDA0003164273140000025
indicating that the desired yaw angle is desired,
Figure BDA0003164273140000026
indicating the desired yaw rate, YrefDenotes the desired ordinate, HpTo predict the time domain, HcQ, R, S are all used to control the time domainA weight matrix.
Optionally, obtaining the total longitudinal force through the sliding mode controller according to the longitudinal control parameter includes:
constructing a switching function of the sliding mode controller;
and obtaining the total longitudinal force by combining the switching function and the vehicle longitudinal dynamic equation.
Optionally, the obtaining the control moment of the vehicle according to the yaw moment and the total longitudinal force comprises:
constructing a second objective function;
establishing a constraint condition according to the yaw moment and the total longitudinal force;
solving the tire longitudinal force variation when the second objective function is minimum under the constraint condition, and obtaining the tire longitudinal force at the next moment according to the tire longitudinal force variation;
and obtaining a control moment according to the tire longitudinal force at the next moment and a wheel dynamic model.
Optionally, when the yaw moment is obtained by combining the UniTire tire model according to the lateral control parameter, the method further includes:
obtaining a front wheel corner by combining the transverse control parameter with a UniTire tire model;
and realizing the track tracking control of the vehicle according to the front wheel rotation angle and the control torque.
Optionally, the track following control of the vehicle according to the front wheel rotation angle and the control torque includes:
controlling a steering of the vehicle according to the front wheel steering angle;
and independently controlling each wheel of the vehicle according to the control torque.
A vehicle trajectory tracking control system for implementing the above method, the system comprising: a lateral controller and a sliding mode controller;
the transverse controller is used for calculating a yaw moment according to the transverse control parameters; the lateral controller comprises a linear time-varying model predictive controller and a UniTire tire model for providing a Jacobian matrix to the linear time-varying model predictive controller to participate in the calculation of the yaw moment;
the sliding mode controller is used for calculating total longitudinal force according to longitudinal control parameters;
the transverse controller and the sliding mode controller are respectively connected with the distribution controller;
the distribution controller is used for receiving the yaw moment and the total longitudinal force and obtaining a tire longitudinal force according to the yaw moment and the total longitudinal force;
the distribution controller is connected with a driving brake system; the driving and braking system is used for receiving the longitudinal force of the tire, obtaining a control moment according to the longitudinal force of the tire, and realizing the track tracking control of the vehicle according to the control moment.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a vehicle track tracking control method and a vehicle track tracking control system, wherein a UniTire tire model is introduced, the complicated lateral longitudinal coupling characteristic is considered, and the UniTire tire model has the modeling characteristics of dimensionless force characteristic expression, theoretical model boundary conditions and the like, so that the vehicle track tracking control has higher overall identification precision.
In the specific implementation mode of the invention, the process of the local linearization of the model is calculated by adopting a numerical calculation method, so that the calculation complexity is reduced on the premise of not influencing the calculation precision, and the expected track can be tracked and the vehicle can be controlled to be stable under the condition of large tire slip rate.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed 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 creative efforts.
Fig. 1 is a system block diagram of a vehicle trajectory tracking control system according to embodiment 1 of the present invention;
fig. 2 is a flowchart of a method of a vehicle trajectory tracking control method according to embodiment 2 of the present invention;
FIG. 3 is a diagram illustrating a seven-degree-of-freedom model of a vehicle according to embodiment 2 of the present invention;
FIG. 4(a) is a comparison graph of lateral position results using two tire models in scenario 1 provided in example 2 of the present invention; FIG. 4(b) is a comparison of yaw angle results using two tire models in scenario 1 as provided in example 2 of the present invention;
fig. 5 is a comparison graph of results obtained by using two tire models in scenario 2 provided in example 2 of the present invention.
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 track tracking control method and a vehicle track tracking control system, which have higher tracking control precision, can track an expected track under a large tire slip rate and ensure the stability of a vehicle.
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.
Example 1
The intelligent vehicle track tracking control is applied to vehicle control from the earliest proposed sighting theory and driver model to the advanced control method such as sliding mode control, linear matrix inequality, neural network control, model prediction control and the like by tracking the sighting point through simulating the driving behavior of the driver. The model prediction control is good at processing the multi-coupling problem with explicit constraint, can be better suitable for a multi-free vehicle model and a complex UniTire tire model, and ensures the robustness of the algorithm and the stability of the control due to the existence of prediction, optimization and feedback links and the solution of the optimal control problem.
The tire model is a highly nonlinear model, and the tire models commonly used in vehicle trajectory tracking control generally include the following: the first is the simplest linear tire model, which can simplify the operation to the greatest extent, but the linear tire model can only approximately express the tire characteristics of a pure working condition linear region, and cannot describe the coupling characteristics under the composite working condition of lateral deviation, longitudinal slip and lateral slip and the nonlinear characteristics when the slip rate is large, so that the application scene of a control algorithm is greatly limited; the second is a simple empirical model, which is a Burckhardt tire model more commonly used, the model can express the characteristics of the nonlinear tire to a certain extent, and a road adhesion coefficient is introduced into the model, but because the parameters are too few, the expression precision under nonlinear and complex working conditions is very limited; the third is a complex tire model, the most widely applied is a magic formula proposed by Pacejka, the magic formula comprises multiple versions, however, in order to reduce the solving complexity, the version is usually applied after simplifying the mechanical characteristics of the complex working condition due to the need of complex numerical operation in vehicle control, and errors caused by the simplification of the tire characteristics are compensated by the robustness of a control system.
Based on this, the present embodiment provides a vehicle trajectory tracking control system, as shown in fig. 1, including: a lateral controller and a sliding mode controller;
the transverse controller is used for calculating a yaw moment according to the transverse control parameters; the lateral controller comprises a linear time-varying model predictive controller and a UniTire tire model for providing a Jacobian matrix to the linear time-varying model predictive controller to participate in the calculation of the yaw moment;
the sliding mode controller is used for calculating total longitudinal force according to longitudinal control parameters;
the transverse controller and the sliding mode controller are respectively connected with the distribution controller;
the distribution controller is used for receiving the yaw moment and the total longitudinal force and obtaining a tire longitudinal force according to the yaw moment and the total longitudinal force;
the distribution controller is connected with a driving brake system; the driving and braking system is used for receiving the longitudinal force of the tire, obtaining a control moment according to the longitudinal force of the tire, and realizing the track tracking control of the vehicle according to the control moment.
In an alternative embodiment, the lateral controller is connected to a steering gear of the vehicle, and the lateral controller is configured to output a front wheel steering angle to control a steering angle of a front wheel of the vehicle, so as to implement trajectory tracking control of the vehicle by combining the control torque and the front wheel steering angle.
Example 2
The present embodiment provides a vehicle trajectory tracking control method, which uses the system according to embodiment 1, as shown in fig. 2, and includes:
step 101: acquiring transverse control parameters and longitudinal control parameters of a vehicle;
step 102: obtaining a yaw moment by combining the transverse control parameters with a UniTire tire model;
step 103: obtaining a total longitudinal force through a sliding mode controller according to longitudinal control parameters;
step 104: and obtaining the control moment of the vehicle according to the yaw moment and the total longitudinal force, and realizing the track tracking control of the vehicle according to the control moment.
The following embodiment will specifically describe the trajectory tracking control applied to the four-wheel independent drive electric vehicle as an example.
When the track tracking control is carried out on the four-wheel independent drive electric vehicle, the moment T is controlled by controlling the four wheelsiAnd front wheel steering angle delta to achieve path tracking and speed tracking. The target vehicle to be controlled is a four-wheel hub motor driven electric vehicle with four wheels independently driven/braked and front wheels steered, so that the four wheels of the target vehicle can be independently controlled, and it is assumed that the front wheel steering angles of the vehicle are the same. In this exampleThe proposed trajectory tracking controller decouples the longitudinal and lateral dynamics of the vehicle. The transverse tracking Control adopts linear time-varying Model Predictive Control, transverse Control parameters are input into a Model Predictive Controller (MPC), and a yaw moment and a front wheel corner are obtained according to the transverse Control parameters and a Unitire Model. The lateral control parameters include: desired yaw angle
Figure BDA0003164273140000061
Desired yaw rate
Figure BDA0003164273140000062
And an expected ordinate YrefAnd the current centroid lateral velocity v of the vehicleyYaw angle
Figure BDA0003164273140000071
Yaw rate
Figure BDA0003164273140000072
Abscissa X and ordinate Y of centroid relative to geodetic coordinate system, centroid longitudinal acceleration axCenter of mass longitudinal acceleration ayAnd wheel rotational speed omegai。
The longitudinal control adopts a sliding mode controller SMC, longitudinal control parameters are input into the sliding mode controller SMC, and the total longitudinal force F is obtained according to the longitudinal control parametersX. The longitudinal control parameters include: desired vehicle speed VxrefAnd the current center of mass longitudinal acceleration a of the vehiclexAnd centroid longitudinal velocity Vx。
The yaw moment and the total longitudinal force are used as the input of a distribution controller of the lower layer, and quadratic programming is adopted to solve and distribute the input quantity in an optimal form to obtain the tire longitudinal force FiAnd obtaining the independent control torque T of four wheels according to the dynamics of the wheelsiControlling the torque TiI.e. the driving/braking torque TiThe vehicle is directly controlled by the obtained front wheel angle and the driving/braking torques of the four wheels. Wherein the front wheel steering angle controls the steering gear of the vehicle, i.e. four-wheel independent driveA four-wheel hub motor for braking and front wheel steering drives the front wheel steering angle of the electric vehicle; the driving/braking torque of each wheel controls the driving force applied to the wheel, thereby achieving control of the target vehicle.
According to the principle of balance of forces and moments, a seven-degree-of-freedom model of the vehicle applied in the MPC controller is given with a body coordinate system as a reference coordinate system, and only two degrees of freedom of the vehicle in the yaw and the lateral directions are considered in the MPC controller as shown in FIG. 3.
In the seven-degree-of-freedom model of the vehicle, a lateral motion equation is as follows:
Figure BDA0003164273140000073
yaw motion equation:
Figure BDA0003164273140000074
wherein the content of the first and second substances,
Figure BDA0003164273140000075
in the formula, Mz combines all terms containing longitudinal force in the yaw movement into one term, and the physical meaning of the term is the yaw moment generated by the longitudinal force of the wheels; while the Y-axis component of the lateral motion due to the longitudinal force is small, the longitudinal force in the prediction domain is considered approximately constant. Further delta is the front wheel angle FxiAnd FyiDenotes a tire longitudinal force and a tire lateral force, i is 1,2,3,4 denotes four wheels of a vehicle, i is a front left wheel, a front right wheel, a rear left wheel, and a rear right wheel, v is a front right wheel, a rear right wheel, and a rear left wheel, and a rear right wheel, v is a rear right wheelxAnd vyIs the centroid longitudinal and transverse velocities, JZIs the moment of inertia of the vehicle about the z-axis,
Figure BDA0003164273140000081
and
Figure BDA0003164273140000082
is a yaw angleVelocity and yaw angular acceleration,/aAnd lbIs the centroid to fore/aft axle distance, and c is the wheel track.
The seven-degree-of-freedom model of the vehicle is established by using a vehicle body coordinate system as a reference system, and when the reference system for vehicle running is converted into a geodetic coordinate system, the longitudinal and lateral speeds of the vehicle center of mass relative to the geodetic coordinate system can be expressed as follows according to a conversion principle:
Figure BDA0003164273140000083
Figure BDA0003164273140000084
meanwhile, the transverse moment is calculated by combining the all-condition UniTire tire model in the transverse control, and the lateral force in the all-condition UniTire tire model can be expressed as the following functional form:
Fyi＝fUniTire(αi,κi,Vi,Fzi)
wherein, the tire vertical load is:
Figure BDA0003164273140000085
Figure BDA0003164273140000086
Figure BDA0003164273140000087
Figure BDA0003164273140000088
wherein H is the height of the center of mass of the vehicle, L is the wheelbase of the vehicle, axAnd ayIs the longitudinal sum of the mass centers of the vehiclesLateral acceleration.
The tire slip angle is:
Figure BDA0003164273140000091
Figure BDA0003164273140000092
Figure BDA0003164273140000093
Figure BDA0003164273140000094
in a geodetic coordinate system, the speed of the wheel center relative to the ground can be expressed as:
Figure BDA0003164273140000095
Figure BDA0003164273140000096
Figure BDA0003164273140000097
Figure BDA0003164273140000098
the longitudinal speed of the wheel center under the tire coordinate system is as follows:
Figure BDA0003164273140000099
Figure BDA00031642731400000910
Figure BDA00031642731400000911
Figure BDA00031642731400000912
the longitudinal slip ratio is:
Figure BDA0003164273140000101
in the formula, ωiFor wheel rolling angular velocity, RieIs the tire rolling radius.
Selecting state variables
Figure BDA0003164273140000102
Control variable μ ═ Mz δ]TAnd taking the tire slip angle as a constraint condition,
Figure BDA0003164273140000103
for outputting variables, establishing a nonlinear state equation according to two degrees of freedom of lateral motion and yaw motion in a seven-degree-of-freedom vehicle model and longitudinal and lateral speed formulas of a vehicle center of mass relative to a geodetic coordinate system, and establishing an output equation according to a tire sideslip angle formula, wherein the nonlinear state equation and the output equation are as follows:
Figure BDA0003164273140000104
Figure BDA0003164273140000105
wherein the content of the first and second substances,
Figure BDA0003164273140000106
Figure BDA0003164273140000107
and discretizing and linearizing the nonlinear state equation and the output equation to obtain a linear time-varying system. In order to ensure the calculation efficiency of the algorithm and reduce the complexity of the solution of the optimization function, the seven-degree-of-freedom vehicle model adopted in the model predictive control is linearized, and the nonlinear model predictive control is converted into the linear time-varying model predictive control problem, so that the complex solution of the nonlinear model prediction is avoided. Performing first-order Taylor expansion by taking the state quantity and the control quantity of the system at the current moment as reference points, neglecting high-order terms to realize local linearization of the system, and performing discretization to obtain a linear time-varying state equation and an output equation:
ξk+1,t＝Ak,tξk,t+Bk,tμk,t+dk,t，k＝t,…,t+Hp-1
ηk,t＝Ck,tξk,t+Dk,tμk,t+ek,t，k＝t,…,t+Hp
wherein the content of the first and second substances,
Figure BDA0003164273140000111
to reduce complexity, a linear time-varying system is simplified according to the following rules:
Ak,t＝At,t,Bk,t＝Bt,t,dk,t＝dt,t
Ck,t＝Ct,t,Dk,t＝Dt,t,ek,t＝et,t
wherein A istAnd BtIs a nonlinear state space equation with respect to stateThe Jacobian matrix of the quantities and the controlled quantities can be calculated by a partial derivative solving function jacobian in Matlab for a general nonlinear system. However, UniTire is considered as a semi-empirical tire model, and contains empirical expressions to adapt to test data, the analytical method is still adopted for solving, and the finally obtained expression data volume is huge and the optimization function cannot be correctly solved. Therefore, the embodiment calculates A by numerical derivationtAnd Bt。
When numerical derivation is performed, assuming that the current time is k, the vehicle state at the time k-1 can be represented as:
vy(k-1)＝vy(k)-T·f1(ξ(k),μ(k))
Figure BDA0003164273140000121
let the tire slip angle at time k-1 be:
Figure BDA0003164273140000122
Figure BDA0003164273140000123
Figure BDA0003164273140000124
similarly, the wheel center speed at the moment k-1 is as follows:
Figure BDA0003164273140000125
Figure BDA0003164273140000126
Figure BDA0003164273140000127
Figure BDA0003164273140000128
Figure BDA0003164273140000129
the longitudinal slip ratio of the tire at the k-1 moment is as follows:
Figure BDA00031642731400001210
Figure BDA00031642731400001211
Figure BDA00031642731400001212
the tire lateral force at the moment k-1 is as follows:
Figure BDA00031642731400001213
Figure BDA00031642731400001214
Figure BDA00031642731400001215
Fyi,δ(k-1)＝fUniTire(αi,δ(k-1),κi,δ(k-1),Vi,Fzi) And the lateral speed and the yaw rate of the mass center of the vehicle at the moment i is 1,2k-1 are as follows:
Figure BDA0003164273140000131
Figure BDA0003164273140000132
Figure BDA0003164273140000133
Figure BDA0003164273140000134
Figure BDA0003164273140000135
Figure BDA0003164273140000136
the difference mode of the Jacobian matrix can be obtained according to the state of the vehicle at the moment k-1 and the state of the vehicle at the current moment (the moment k), so that the traditional derivation method is replaced, the mode of directly calculating the Jacobian matrix is adopted, and the solving complexity caused by the nonlinear model is reduced to the maximum extent on the basis of ensuring the precision of the tire model.
Finally obtaining A calculated by adopting a numerical approximation methodtAnd Bt：
Figure BDA0003164273140000141
Figure BDA0003164273140000142
The first objective function form is constructed as follows:
Figure BDA0003164273140000143
wherein in the first item
Figure BDA0003164273140000144
Is the difference between the system output and the reference output; the second term is the variable quantity of the control quantity, and the penalty of the term represents the requirement of stable control variable quantity; the third item is the control quantity, and the penalty of the third item represents the requirement of the maximum and minimum values of the control quantity; the fourth term is a relaxation factor, which expands the constraint range of the soft constraint output quantity, so that the optimal solution can be replaced by the first objective function suboptimal solution. HpTo predict the time domain, HcTo control the time domain.
In the fourth term, rho is a weight coefficient and represents the punishment on each item, and the larger the value is, the larger the influence of the item on the target function is; ε represents the relaxation factor.
The first objective function is sorted to obtain:
Figure BDA0003164273140000151
wherein, thetatrt＝ΥtrΘt；ΥtrDecomposing the output variables for the blocking matrix;
Figure BDA0003164273140000152
Figure BDA0003164273140000153
and
Figure BDA0003164273140000154
jacobian matrix A solved for the preambletAnd BtDeformation of (2).
The following settings were made:
Figure BDA0003164273140000155
Gt＝[2σ(t)TQeΘtrt+2U(t-1)TSeM 0]
Pt＝σ(t)TQeσ(t)+U(t-1)TSeU(t-1)+ρε2
and (3) arranging into a standard quadratic objective function:
Figure BDA0003164273140000156
solving the amount of change in the control quantity when the function is minimized
Figure BDA0003164273140000157
Wherein is Δ μt＝[Δδt,ΔMZt]Further, the control amount μ (t | t) ═ μ (t-1| t) + Δ μ at the next time is obtainedtFront wheel corner deltaexpActing directly on the vehicle, yaw moment MZexpThe distribution of tire torque is made to a distribution controller.
A sliding mode controller is adopted for longitudinal control, and a switching function is defined firstly:
s＝Vx-Vxd+b∫(Vx-Vxd)dt
selecting an approach rate:
Figure BDA0003164273140000161
wherein the content of the first and second substances,
Figure BDA0003164273140000162
according to the longitudinal kinetic equation of the vehicle
Figure BDA0003164273140000163
The desired total longitudinal force can be obtained in combination:
Figure BDA0003164273140000164
the distribution controller is based on the desired total yaw moment MZexpAnd total longitudinal force FXexpThe distribution of the longitudinal force of the tyre is carried out, firstly a second objective function is constructed:
Figure BDA0003164273140000165
wherein: r1、Q1Is a weighting matrix; rho1、ρ2Is a weighting coefficient; Δ F ═ Δ Fx1,ΔFx2,ΔFx3,ΔFx4]T，F＝[Fx1,Fx2,Fx3,Fx4]T。
Write the quadratic programming problem to the standard form:
Figure BDA0003164273140000166
in the formula: x ═ Δ FT，ε1，ε2]T，H＝[R1+Q1,04×2；02×4,ρ1,ρ2]，
Figure BDA0003164273140000167
Constraint conditions are as follows:
Figure BDA0003164273140000168
in the formula:
Figure BDA0003164273140000171
Figure BDA0003164273140000172
lb＝[lb1,lb2,lb3,lb4,0,0]T
ub＝[ub1,ub2,ub3,ub4,ε1max,ε2max]T
Figure BDA0003164273140000173
solving the variation delta F of the tire longitudinal force when the function is minimum, further obtaining the tire longitudinal force at the next moment, and obtaining the tire longitudinal force according to the wheel dynamics
Figure BDA0003164273140000174
Obtaining a driving/braking torque TiActing on the vehicle, wherein JwiFor each wheel moment of inertia; riIs the effective rolling radius of the tire; w is aiFor each wheel rotational speed; b isiIs the coefficient of viscous drag.
Therefore, the UniTire tire model with high precision under all working conditions is introduced into the method, the UniTire tire model is embedded into a linear time-varying MPC control algorithm to realize track tracking, the adaptive scenes of intelligent vehicle track tracking control such as high speed, low adhesion road surface, large slip ratio and the like are further expanded, and the tracking performance is improved. The UniTire tire model considers the complex lateral longitudinal coupling characteristic, the UniTire model adopted by the embodiment has similar expression capacity with a complex magic formula, but the UniTire model has higher overall identification precision and better model expansion capacity due to the modeling characteristics of dimensionless force characteristic expression, insertion dynamic friction coefficient, theoretical model boundary conditions and the like. Therefore, the vehicle track tracking control method based on the UniTire tire model provided by the embodiment can improve the track tracking precision in a high-speed scene and the vehicle stability in a large slip rate. And the speed prediction, load prediction and dynamic friction coefficient expression of the tire model can also improve the adaptability and expansibility of vehicle control on vehicle speed, vehicle type, tire type and road surface conditions.
The embodiment simplifies the process of the local linearization of the model in the control algorithm, and the process is obtained by approximation by adopting a numerical calculation method, so that complex formula derivation and complex numerical solution are avoided. Compared with a method adopting a simplified tire model, the designed control algorithm has higher tracking accuracy in a high-speed scene, can still track an expected track under a large tire slip rate and ensures the stability of a vehicle.
In order to further prove the effect of the embodiment, a Matlab/Simulink and Carsim combined simulation platform is also set up in the embodiment, track tracking simulation verification of road surface working conditions with different speeds and different adhesion coefficients is carried out, and tracking accuracy of a Pacejka5.2 and UniTire tire model is compared.
Scene 1: the road adhesion coefficient is 0.8, and the vehicle speed is 90 km/h. As shown in fig. 4, in which (a) is a comparison graph of the results of the lateral positions of the two models and (b) is a comparison graph of the results of the yaw angles of the two models, it can be seen that the maximum value of the absolute value of the lateral position deviation is 3.06m and the root mean square value of the lateral position deviation is 1.06m when the UniTire model is used; the PAC5.2 tire model was used with a maximum of 3.21m and a root mean square value of 1.13 m. Adopting a UniTire tire model, wherein the maximum value of the absolute value of the yaw angle deviation is 9.16 degrees, and the root mean square value of the yaw angle deviation is 3.55 degrees; using the PAC5.2 tire model, the maximum value was 10.28 ° and the root mean square value was 3.89 °.
Scene 2: the road adhesion coefficient is 0.4, and the vehicle speed is 70 km/h. As shown in fig. 5, in which (a) is a comparison graph of the results of the lateral positions of the two models and (b) is a comparison graph of the results of the yaw angles of the two models, it can be seen that the maximum value of the absolute value of the lateral position deviation is 2.45m and the root mean square value of the lateral position deviation is 0.85m when the UniTire model is used; the PAC5.2 tire model was used with a maximum of 2.50m and a root mean square value of 0.90 m. Adopting a UniTire tire model, wherein the maximum value of the absolute value of the yaw angle deviation is 9.78 degrees, and the root mean square value of the yaw angle deviation is 3.67 degrees; by using the PAC5.2 tire model, the maximum absolute value of the yaw angle deviation is 9.34 degrees, and the root mean square value of the yaw angle deviation is 4.02 degrees.
Therefore, the performance of tracking control on the vehicle by adopting the UniTire tire model in the embodiment is obviously better than that of the scheme adopting the PAC5.2 tire model, and the accuracy of tracking control on the vehicle track is improved.
The emphasis of each embodiment in the present specification is on the difference from the other embodiments, and the same and similar parts among the various embodiments may be referred to each other.
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 trajectory tracking control method, characterized by comprising:
acquiring transverse control parameters and longitudinal control parameters of a vehicle;
obtaining a yaw moment by combining the transverse control parameters with a UniTire tire model;
obtaining a total longitudinal force through a sliding mode controller according to the longitudinal control parameters;
and obtaining the control moment of the vehicle according to the yaw moment and the total longitudinal force, and realizing the track tracking control of the vehicle according to the control moment.
2. The vehicle trajectory tracking control method of claim 1, wherein the deriving a yaw moment from the lateral control parameters in combination with a UniTire tire model comprises:
establishing an output equation according to a slip angle formula in a UniTire tire model;
establishing a nonlinear state equation according to the transverse control parameters and a seven-degree-of-freedom model of the vehicle;
discretizing and linearizing the output equation and the nonlinear state equation to obtain a Jacobian matrix;
constructing a first objective function according to the Jacobian matrix, and sorting the first objective function to obtain a quadratic objective function;
and solving the yaw moment variation when the quadratic form objective function is minimum, and obtaining the yaw moment at the next moment according to the yaw moment variation.
3. The vehicle trajectory tracking control method according to claim 2, further comprising, after obtaining the jacobian matrix:
and calculating the Jacobian matrix by using a numerical derivation method to obtain a deformed Jacobian matrix, and replacing the Jacobian matrix in the quadratic objective function acquisition process with the deformed Jacobian matrix.
4. The vehicle trajectory tracking control method according to claim 2, wherein the first objective function includes:
Figure FDA0003164273130000011
wherein the content of the first and second substances,
Figure FDA0003164273130000021
is the difference between the system output and the reference output,
Figure FDA0003164273130000022
is the yaw angle of the vehicle,
Figure FDA0003164273130000023
is yaw rate, Y is ordinate of centroid relative to geodetic coordinate system, xi is state variable, t is time, mu is control variable, delta U (t) is variation of control quantity, rho is weight coefficient, epsilon is relaxation factor,
Figure FDA0003164273130000024
indicating that the desired yaw angle is desired,
Figure FDA0003164273130000025
indicating the desired yaw rate, YrefDenotes the desired ordinate, HpTo predict the time domain, HcQ, R, S are weight matrices for the control time domain.
5. A vehicle trajectory tracking control method according to claim 1, wherein said deriving a total longitudinal force by a sliding mode controller in accordance with said longitudinal control parameter comprises:
constructing a switching function of the sliding mode controller;
and obtaining the total longitudinal force by combining the switching function and the vehicle longitudinal dynamic equation.
6. A vehicle trajectory tracking control method according to claim 1, wherein said deriving a control moment of the vehicle from said yaw moment and said total longitudinal force comprises:
constructing a second objective function;
establishing a constraint condition according to the yaw moment and the total longitudinal force;
solving the tire longitudinal force variation when the second objective function is minimum under the constraint condition, and obtaining the tire longitudinal force at the next moment according to the tire longitudinal force variation;
and obtaining a control moment according to the tire longitudinal force at the next moment and a wheel dynamic model.
7. The vehicle trajectory tracking control method of claim 1, wherein when a yaw moment is obtained in combination with a UniTire tire model according to the lateral control parameters, the method further comprises:
obtaining a front wheel corner by combining the transverse control parameter with a UniTire tire model;
and realizing the track tracking control of the vehicle according to the front wheel rotation angle and the control torque.
8. The vehicle trajectory tracking control method according to claim 7, wherein the performing trajectory tracking control of the vehicle based on the front wheel rotation angle and the control torque includes:
controlling a steering of the vehicle according to the front wheel steering angle;
and independently controlling each wheel of the vehicle according to the control torque.
9. A vehicle trajectory tracking control system for implementing the method of claim 1, the system comprising: a lateral controller and a sliding mode controller;
the transverse controller is used for calculating a yaw moment according to the transverse control parameters; the lateral controller comprises a linear time-varying model predictive controller and a UniTire tire model for providing a Jacobian matrix to the linear time-varying model predictive controller to participate in the calculation of the yaw moment;
the sliding mode controller is used for calculating total longitudinal force according to longitudinal control parameters;
the transverse controller and the sliding mode controller are respectively connected with the distribution controller;
the distribution controller is used for receiving the yaw moment and the total longitudinal force and obtaining a tire longitudinal force according to the yaw moment and the total longitudinal force;
the distribution controller is connected with a driving brake system; the driving and braking system is used for receiving the longitudinal force of the tire, obtaining a control moment according to the longitudinal force of the tire, and realizing the track tracking control of the vehicle according to the control moment.
10. A vehicle tracking control system according to claim 9, wherein the lateral controller is connected to a steering gear of the vehicle, and the lateral controller is configured to output a front wheel steering angle to control a steering angle of the front wheels of the vehicle.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114454893A (en) * 2022-01-27 2022-05-10 中国矿业大学 Track tracking prediction control method for road surface self-adaptive mine card
CN114859733A (en) * 2022-05-23 2022-08-05 南京林业大学 Differential steering unmanned vehicle trajectory tracking and attitude control method

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108454623A (en) * 2018-01-22 2018-08-28 大连理工大学 A kind of unmanned electric vehicle Trajectory Tracking Control method of four motorized wheels
WO2019042453A1 (en) * 2017-09-04 2019-03-07 郑州宇通客车股份有限公司 Road surface adaptive anti-slip regulation method and system for distributed-drive electric vehicle
CN110235071A (en) * 2016-11-10 2019-09-13 俄亥俄州立大学 Autonomous driving vehicle guidance and track following
CN110780674A (en) * 2019-12-04 2020-02-11 哈尔滨理工大学 Method for improving automatic driving track tracking control
CN112373459A (en) * 2020-10-21 2021-02-19 北京理工大学 Method for controlling upper-layer motion state of four-hub motor-driven vehicle
CN112882474A (en) * 2021-01-26 2021-06-01 北京科技大学 Integrated unmanned automobile lane change control method based on time-varying model predictive control

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110235071A (en) * 2016-11-10 2019-09-13 俄亥俄州立大学 Autonomous driving vehicle guidance and track following
WO2019042453A1 (en) * 2017-09-04 2019-03-07 郑州宇通客车股份有限公司 Road surface adaptive anti-slip regulation method and system for distributed-drive electric vehicle
CN108454623A (en) * 2018-01-22 2018-08-28 大连理工大学 A kind of unmanned electric vehicle Trajectory Tracking Control method of four motorized wheels
CN110780674A (en) * 2019-12-04 2020-02-11 哈尔滨理工大学 Method for improving automatic driving track tracking control
CN112373459A (en) * 2020-10-21 2021-02-19 北京理工大学 Method for controlling upper-layer motion state of four-hub motor-driven vehicle
CN112882474A (en) * 2021-01-26 2021-06-01 北京科技大学 Integrated unmanned automobile lane change control method based on time-varying model predictive control

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
钱丹剑: "分布式驱动电动汽车横摆力矩控制与转矩分配研究", 《中国优秀硕士学位论文全文数据库 (工程科技Ⅱ辑)》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114454893A (en) * 2022-01-27 2022-05-10 中国矿业大学 Track tracking prediction control method for road surface self-adaptive mine card
CN114859733A (en) * 2022-05-23 2022-08-05 南京林业大学 Differential steering unmanned vehicle trajectory tracking and attitude control method
CN114859733B (en) * 2022-05-23 2023-03-14 南京林业大学 Differential steering unmanned vehicle trajectory tracking and attitude control method

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