CN104859661B - The excessively curved time-optimized algorithm of vehicle - Google Patents
The excessively curved time-optimized algorithm of vehicle Download PDFInfo
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- CN104859661B CN104859661B CN201510246385.4A CN201510246385A CN104859661B CN 104859661 B CN104859661 B CN 104859661B CN 201510246385 A CN201510246385 A CN 201510246385A CN 104859661 B CN104859661 B CN 104859661B
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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
- B60W40/00—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
- 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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- 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
- B60W40/00—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
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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
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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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
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/12—Lateral speed
-
- 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
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/12—Lateral speed
- B60W2520/125—Lateral acceleration
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- Automation & Control Theory (AREA)
- Mathematical Physics (AREA)
- Transportation (AREA)
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- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
Abstract
The invention provides a kind of excessively curved time-optimized algorithm of vehicle, because the given control corner of road shape and motion state that driver travels according to vehicle first, onboard sensor obtains the operating motion state of vehicle, Kalman filter obtains the deviation of directivity and lateral displacement deviation between vehicle running orbit and racing track center line according to the vertical operating motion state of vehicle based on pre-defined rule, controller is according to motion state, the deviation of directivity and lateral displacement deviation obtain additional rotation angle based on optimal control algorithm, control corner and additional rotation angle have together decided on the optimal corner of front-wheel of vehicle, the excessively curved time-optimized algorithm of vehicle of the present invention obtains optimization corner so that vehicle use time when excessively curved is short by calculating, so as to shorten the time needed for racing driver completes whole schedules, the achievement obtained.
Description
Technical field
The present invention relates to a kind of excessively curved time algorithm of vehicle, and in particular to a kind of excessively curved time-optimized algorithm of vehicle.
Background technology
Racing car is the motion that race is done using automobile.In 1895, this motion was for the first time in France's appearance.Such as
The present, it has become the competitive sports that the whole world attracts most spectators' viewings.
In F1 equation motorcycle races or intelligent vehicle contest, individual pen time minimum is the final goal that players are pursued.Greatly
In the automobile race of most forms, when the link that comes off into the straightaway is entered in racing car, except driver needs skillfully to hold optimal shift time, match
The performance of car in itself also has a great impact to car speed.When enter various bends after, driver will simultaneously will brake,
Throttle, direction, gear link accomplish perfection, can just throw other opponents away, obtain leading.Thus for a racing driver,
Cross the effect that can triumph of the curved skill for finally obtain match play key.Therefore, how faster to complete curved, and be every
The problem of individual racing driver faces.
The content of the invention
The present invention is carried out to solve above-mentioned problem, it is therefore intended that provide a kind of car for reducing the racing car excessively curved time
Excessively curved time-optimized algorithm.
The invention provides a kind of excessively curved time-optimized algorithm of vehicle, for obtain vehicle along predetermined track it is excessively curved when described in
The optimal corner of front-wheel of vehicle is so that the Ackermann steer angle use time is minimum, it is characterised in that comprise the following steps：Step
Rapid 1, the given control corner of speed and direction that driver runs according to predetermined track and vehicle；Step 2, onboard sensor is gathered
The operating speed of vehicle and tyre slip angle；Step 3, Kalman filter is based on pre-defined rule and obtains vehicle fortune according to speed
The deviation of directivity and lateral displacement deviation between the center line in row track and predetermined track；Step 4, controller is according to speed, side
Additional rotation angle is obtained based on optimal control algorithm to deviation and lateral displacement deviation；Step 5, control corner is added with additional rotation angle
Obtain the optimal corner of front-wheel.
In the excessively curved time-optimized algorithm of vehicle provided by the present invention, it can also have the feature that：Wherein, speed bag
Contain：Yaw velocity, longitudinal velocity and side velocity.
In the excessively curved time-optimized algorithm of vehicle provided by the present invention, it can also have the feature that：Wherein, step 3
Comprise the following steps：
Step 3-1, Kalman filter gathers the center line information and boundary information in the predetermined track,
Step 3-2, Kalman filter is based on pre-defined rule and believed according to the speed and the center line information and border
Breath obtains the deviation of directivity and the lateral displacement between the center line in the vehicle running orbit and the predetermined track
Deviation.
In the excessively curved time-optimized algorithm of vehicle provided by the present invention, it can also have the feature that：Wherein, the step
Rapid 4 comprise the following steps：
Step 4-1：Obtained according to the speed, the tyre slip angle, the deviation of directivity and the lateral displacement deviation
To the increment of the vehicle movement distance,
Step 4-2：Quadratic objective function is set up according to the increment, the quadratic objective function J is：
Wherein, q1And q2Weight coefficient is represented, δ is the optimal corner of front-wheel, and Δ ψ is the deviation of directivity, and Δ y is that lateral displacement is inclined
Difference, rrFor the radius of the center line camber in the predetermined track,
Step 4-3：It is inclined according to the side velocity, the yaw velocity, the deviation of directivity and the lateral displacement
The quadratic objective function that difference is simplified：
Step 4-4：By solving Riccati equation, feedback oscillator K is obtainedLQG, it is described solution Riccati equation be：
A′P+PA-(PB+N)R-1(B ' P+N ')+Q=0
Wherein, R=1, N=0, vxFor longitudinal velocity, ayFor side acceleration, CyfFor front-wheel cornering stiffness,
CyrFor trailing wheel cornering stiffness, q3 and q4Represent weight coefficient, T takes aim at the time to be pre-, a be automobile barycenter to front axle distance, b is automobile
Barycenter is to rear axle distance, and I is Vehicular yaw rotary inertia, and m is car mass, and P is the solution of Riccati equation,
Step 4-5：The additional rotation angle is obtained based on pre-defined rule according to the feedback oscillator, the additional rotation angle is：
δLOG=-KLOGΔx
Wherein, Δ x=x-x0,Y*For predetermined track, ψ*For predetermined track tangent line and between X-axis
Angle, X-axis be inertial coodinate system under reference axis.
The effect of invention and effect
According to the excessively curved time-optimized algorithm of vehicle involved in the present invention, because the road that driver travels according to vehicle first
Shape and the given control corner of motion state, onboard sensor obtain the operating motion state of vehicle, Kalman filter
Obtained according to the operating motion state of vehicle based on pre-defined rule between the center line in vehicle running orbit and predetermined track
The deviation of directivity and lateral displacement deviation, controller are based on optimum control according to motion state, the deviation of directivity and lateral displacement deviation
Algorithm obtains additional rotation angle, and control corner and additional rotation angle have together decided on the optimal corner of front-wheel of vehicle, vehicle of the invention
Cross curved time-optimized algorithm and obtain optimization corner so that vehicle use time when excessively curved is short, so as to shorten racing driver by calculating
The time needed for whole schedules is completed, the achievement obtained.
Brief description of the drawings
Fig. 1 is the flow chart of the excessively curved time-optimized algorithm of vehicle in embodiments of the invention；
Fig. 2 is vehicle dynamic model figure in embodiments of the invention；
Fig. 3 is geometrical relationship figure of the vehicle on predetermined track in embodiments of the invention；
Fig. 4 is the excessively curved path profiles of intelligent vehicle model 2m/s in embodiments of the invention；
Fig. 5 is the excessively curved path profiles of intelligent vehicle model 3m/s in embodiments of the invention；
Fig. 6 is yaw velocity-time chart during intelligent vehicle model traveling in embodiments of the invention；
Fig. 7 is side velocity-time chart during intelligent vehicle model traveling in embodiments of the invention；
Fig. 8 is front wheel angle-time chart in embodiments of the invention；And
Fig. 9 is side slip angle-time chart in embodiments of the invention.
Embodiment
In order that the technical means, the inventive features, the objects and the advantages of the present invention are easy to understand, it is real below
Example combination accompanying drawing is applied to be specifically addressed the excessively curved time-optimized algorithm of vehicle of the present invention.
Fig. 1 is the flow chart of the excessively curved time-optimized algorithm of vehicle in embodiments of the invention.
As shown in figure 1, in the present embodiment, the excessively curved time-optimized algorithm 100 of vehicle is used to calculate vehicle in excessively curved mistake
The optimal corner of front-wheel in journey, so that vehicle completed curved within the shortest time.The tool of the excessively curved time-optimized algorithm 100 of vehicle
Body step is as follows：
Step S1, the road shape and motion state travelled according to vehicle, driver gives vehicle one control corner δLM, then,
Into step S2.
Step S2, onboard sensor obtains yaw velocity, longitudinal velocity and the side velocity of vehicle operation.
The present embodiment designed curved optimal corner using non-linear auto model, and the non-linear auto model is two free
Spend single-track vehicle handling dynamics model.It is specific as follows：
Fig. 2 is vehicle dynamic model figure in embodiments of the invention.
As shown in Fig. 2 the X-axis of terrestrial coordinate system (i.e. inertial coodinate system), Y-axis is vertical with X-axis, non-linear auto model
's；Two frees degree are respectively lateral movement and weaving.The equation of motion that vehicle is travelled on road is：
Wherein, m is car mass, vxFor longitudinal velocity, vyFor side velocity；For yaw velocity；A is automobile barycenter
Be vehicle parameter to front axle distance, b be automobile barycenter to rear axle distance, be vehicle parameter, FyfFor the total side force of front-wheel, FyrFor
The total side force of trailing wheel, I is Vehicular yaw rotary inertia.
The present embodiment obtains the total side force of front-wheel and the total side force of trailing wheel by setting up tire model." magic formula " takes turns
Loose tool type is as follows：
Fyi=2Disin(Cyiarctan(Byiαi-Eyi(Byiαi-arctan(Byiαi)))) (2)
It is approximately here linear time-varying (LTV) model it to simplify non-linear tire force.With Taylor's formula every
Individual current time expansion, retains first order component, high order component is cast out, then tire force can be converted into simple LTV expression formulas：
Fyi(t)=Cyi(t)αi(t)+Dyi(t) (3)
Wherein, Cyi(t) it is the tire cornering stiffness changed over time, Dyi(t) it is the tire force when side drift angle is zero, αi
Lower expression slip angle of tire, subscript i represents front-wheel comprising f and r, f, and r represents trailing wheel, and subscript y represents lateral.
Front and rear wheel side drift angle is calculated by following formula：
Wherein, αfFor front-wheel side drift angle；αrFor trailing wheel side drift angle；δ is the optimal corner of front-wheel, is used as the input of model.
Onboard sensor is able to detect that the motion state of automobile, and the motion state of wherein vehicle is included：Yaw velocitySide velocity vyWith longitudinal velocity vx.Then, into step S3.
Step S3, Kalman filter obtains vehicle running orbit based on pre-defined rule according to running status and made a reservation for described
The deviation of directivity and lateral displacement deviation between the center line in track.
The key of controller is the deviation of directivity and lateral displacement deviation of vehicle to be obtained in the process of moving.
Calculate for convenience, Δ y and Δ ψ is linearized.The center in predetermined track is collected by Kalman filter
Line information and boundary information.
Fig. 3 is geometrical relationship figure of the vehicle on predetermined track in embodiments of the invention.
As shown in figure 3, X-axis and Y-axis are the reference axis under terrestrial coordinate system (i.e. inertial coodinate system), empty camber line is predetermined car
The center line in road, real camber line is the border in predetermined track, rrFor the radius of the center line camber in predetermined track, with predetermined track
Center line is reference line, in T time, is ds along the distance that reference line is travelledr, and automobile forward travel distance is ds in this period
=VT ≈ uT, wherein, V is the speed of vehicle, and u is the average speed in vehicle T time.dψrFor in time T, vehicle relative to
The center line traveling ds in predetermined trackrApart from corresponding angle.
Vehicle is along center line forward travel distance dsrWith the positive angle ψ of X-axisr：
Then deviation of directivity Δ ψ is defined as yaw angle ψ and ψrDifference：
Wherein, ψrThe centerline tangent direction in predetermined track and the positive angle of X-axis for track.
In order to by lateral displacement error linear, in the case where speed is constant, corner is solely dependent upon.Lateral displacement is missed
Poor Δ y can be approximated to be：
Δ y=vycos(Δψ)+vxsin(Δψ) (8)
In order to keep vehicle in predetermined track, boundary condition is defined as form：
Wherein, wrFor the width in predetermined track, w is the half of car gage.
According to above-mentioned pre-defined rule, Kalman filter can draw the deviation of directivity Δ ψ of vehicle under steam and lateral
Offset deviation Δ y.Then, into step S4.
Step S4, controller applies optimal control according to side velocity, yaw velocity, the deviation of directivity and lateral displacement deviation
Theory processed obtains additional rotation angle.
Excessively it is curved it is time-optimized in, if bigger along the distance passed through with reference to route within the regular hour, you can recognize
To be to shorten the time in whole process.
Distance is obtained according to the lateral displacement error between the predicted state and racing track reference line of vehicle front wheel angle and vehicle
Increment：
Formula (10) is metWith Δ y ＜ ＜ rr。
When Δ s is maximized, i.e., in the set time, the distance that automobile is travelled along road reference line is more, then automobile is curved
That advances on road is more, and the whole excessively curved time will shorten.So, the present invention proposes quadratic objective function：
Wherein, q1And q2Weight coefficient is represented, δ is that front-wheel optimizes corner.
Vehicle dynamic model takes system state variablesWrite as state space equation, form
It is as follows：
Wherein,
CyfFor front-wheel cornering stiffness, CyrFor trailing wheel cornering stiffness.
Process noise w is introduced to formula (12) input point, its state space equation can be changed into following form：
Wherein G=B, w are Gaussian sequence.
Measurement equation z with sensor noise v can have following form to represent；
Z=Hx+v
Wherein,Z=[ψ Δ ψ Δs y], v=[vψ vΔψ vΔy]。
Calculate Kalman gains, it is assumed that the covariance of process disturbance is set as 102, yaw velocityLateral deviation Δ y,
0.01 is set to deviation of directivity Δ ψ noise2.It can be obtained by " Kalman " function in Matlab/simulink softwares
Estimate after to optimization
Quadratic objective function (11) can be turned to：
In condition Δ y ＜ ＜ rrUnder：
It can be obtained according to the theory of optimal control：
Wherein, ayFor side acceleration.
The Optimal Feedback of quadratic model object function can be solved, Riccati equation is by solving Riccati equation：
A′P+PA-(PB+N)R-1(B ' P+N ')+Q=0 (15)
Wherein, P is the solution of Riccati equation, it is possible to use " LQR " function in Matlab instruments is solved.
Solution formula (15), can obtain feedback oscillator KLOG, controller output additional rotation angle δLOG, additional rotation angle δLOGExpression
Formula is as follows：
δLQG=-KLQGΔx (16)
Wherein, Δ x=x-x0,x0For desired ride state, x0=[0,0, ψ*,Y*", Y*For predetermined track, ψ*For predetermined car
Road tangential direction and the positive angle of X-axis.Then, into step S5.
Step S5, control corner is added with additional rotation angle obtains the optimal corner of front-wheel.
In order to verify the validity of designed control algolithm, according to theory of similarity Buckingham Pi principles, think to block with winged
You are tested model of mind car.
Vibration equivalence：According to dimensional method, for a certain physical phenomenon, if two by differential equation
The corresponding dimensionless number Π of physical system is equal, then the differential equation of two physical systems has identical solution.By measuring
The basic parameter of Freescale intelligent vehicle model parameter and real vehicle is as shown in table 1.
The model car of table 1 and certain real vehicle basic parameter
By above-mentioned physical quantity composition nondimensionalization, it can obtain：
The dimension of parameter is as shown in table 2 in table 1.
The vehicle basic parameter dimension of table 2
Wherein：ΠiScaleFor the dimensionless of intelligent vehicle model, ΠiRealFor the dimensionless of real vehicle, subscript i=1,2,3.
The dimensionless deviation of model car and real vehicle is smaller, then intelligent vehicle model and real vehicle vibration equivalence is can consider, according to length
The ratio of dimension, about 1:10.
In order to simulate truth, the single-point that proposes here according to Guo Konghui academician is optimal pre- to take aim at curvature pilot model mould
Intend to control corner δ expected from one, vehicleRM.According to " principle of minimal error ", driver expects an optimal trajectory curvature
1/R*, meet when automobile is passed by preview distance d (after taking aim at time T in advance), vehicle after time T is taken aim in advance, the lateral coordinates y of vehicle
(t+T) it is consistent with desired trajectory lateral coordinates f (t+T) at this：
Optimal side acceleration is：
Optimal curvature is：
Driver's steering wheel angle is inputted：
Consider that reaction is with performing delay, the input of driver's steering wheel angle：
Wherein, KhFor steering angle gain, τrReflect for driver and be delayed, τhFor driver's operation delay.
Result of the test：On open flat ground, racing track is laid.Record is arranged on the sensing data on intelligent vehicle mould
And expend the time.
Fig. 4 is the excessively curved path profiles of intelligent vehicle model 2m/s in embodiments of the invention.
" S " that racing track is made up of two tangent quarter circular arcs is curved and two sections of straight line racing tracks are constituted.According to record
Data, when speed is 2m/s, correspondence real vehicle speed is 20m/s, with every the position of 1 second record intelligent vehicle mould.
Initial time, vehicle is travelled on straight racing track, and bend is entered afterwards, finally rolls bend away from into straight racing track.Knot
Fruit shows that intelligent vehicle model, when entering bend and coming off the curve, is all travelled in, when running at a low speed close to racing track edge,
The changeover portion of " S " bend, approximately with straight-line pass.The driving trace of vehicle reduced curved total kilometres, and whole process takes
20s, during without system optimizing control, whole process then needs 21.1s, so as to reduce the curved time.
Designed controller is further verified, when speed increases to 3m/s, correspondence real vehicle is 30m/s, i.e., at a high speed
During traveling.In this case, controller needs to ensure that vehicle passes through bend within racing track width range.
Fig. 5 is the excessively curved path profiles of intelligent vehicle model 3m/s in embodiments of the invention.
As shown in figure 5, intelligent vehicle model in traveling in the near future, it is predicted that front bend at hand, vehicle is entered in advance
Row control, controls it to provide turn signal, allows vehicle first lanes laterally, and enters the close to racing track with faster speed
One bend, in the changeover portion of two bends, is almost passed through with straight line track, finally show greatly close to bend one it is constant
Corner come off the curve.
Fig. 6 is yaw velocity-time chart during intelligent vehicle model traveling in embodiments of the invention；Fig. 7
It is side velocity-time chart in embodiments of the invention during intelligent vehicle model traveling；Fig. 8 is the implementation of the present invention
Front wheel angle-time chart in example；Fig. 9 is side slip angle-time chart in embodiments of the invention.
Such as Fig. 6, Fig. 7, Fig. 8 and Fig. 9, it is excellent that curve 10 represents vehicle excessively curved time of the intelligent vehicle model not using the present invention
Change algorithm, curve 20 represents vehicle excessively curved time-optimized algorithm of the intelligent vehicle model using the present invention, from Fig. 6, Fig. 7, Fig. 8 and figure
As can be seen that in the excessively curved time-optimized algorithm of vehicle using the present invention, the overshoot ratio of system dynamic response is not controlled in 9
Small during device processed, whole process takes about 13.3s, and in the presence of no controller, takes as 14.2s, therefore designed
Controller efficiently reduced the curved time.
Result of the test shows that designed excessively curved time-optimized control algolithm is ensureing the premise of vehicle run stability
Under, it can effectively reduce the curved time.
The effect of embodiment and effect
The excessively curved time-optimized algorithm of vehicle according to involved by the present embodiment, because what driver travelled according to vehicle first
Road shape and the given control corner of motion state, onboard sensor obtain the operating motion state of vehicle, Kalman filter
Device according to the vertical operating motion state of vehicle based on pre-defined rule obtain vehicle running orbit and predetermined track center line it
Between the deviation of directivity and lateral displacement deviation, controller according to motion state, the deviation of directivity and lateral displacement deviation be based on it is optimal
Control algolithm obtains additional rotation angle, and control corner and additional rotation angle have together decided on the optimal corner of front-wheel of vehicle, of the invention
The excessively curved time-optimized algorithm of vehicle obtains optimization corner so that vehicle use time when excessively curved is short, so as to shorten match by calculating
Driver completes the time needed for whole schedules, the achievement obtained.
Above-mentioned embodiment is the preferred case of the present invention, is not intended to limit protection scope of the present invention.
Claims (4)
1. a kind of excessively curved time-optimized algorithm of vehicle, optimal for obtaining front-wheel of the vehicle along predetermined track vehicle when excessively curved
Corner is so that the Ackermann steer angle use time is minimum, it is characterised in that comprise the following steps：
Step 1, the given control corner of speed and direction that driver runs according to the predetermined track and the vehicle；
Step 2, onboard sensor gathers the operating speed of vehicle and tyre slip angle；
Step 3, Kalman filter is based on pre-defined rule and obtains the vehicle running orbit and described predetermined according to the speed
The deviation of directivity and lateral displacement deviation between the center line in track；
Step 4, controller is obtained according to the speed, the deviation of directivity and the lateral displacement deviation based on optimal control algorithm
To additional rotation angle；
Step 5, the control corner is added with the additional rotation angle obtains the optimal corner of the front-wheel.
2. the excessively curved time-optimized algorithm of vehicle according to claim 1, it is characterised in that：
Wherein, the speed is included：Yaw velocity, longitudinal velocity and side velocity.
3. the excessively curved time-optimized algorithm of vehicle according to claim 1, it is characterised in that：
Wherein, step 3 comprises the following steps：
Step 3-1, Kalman filter gathers the center line information and boundary information in the predetermined track,
Step 3-2, Kalman filter is obtained based on pre-defined rule according to the speed and the center line information and boundary information
To the deviation of directivity between the vehicle running orbit and the center line in the predetermined track and the lateral displacement deviation.
4. the excessively curved time-optimized algorithm of vehicle according to claim 2, it is characterised in that：
Wherein, the step 4 comprises the following steps：
Step 4-1：Institute is obtained according to the speed, the tyre slip angle, the deviation of directivity and the lateral displacement deviation
The increment of vehicle movement distance is stated,
Step 4-2：Quadratic objective function is set up according to the increment, the quadratic objective function J is：
Wherein, q1And q2Weight coefficient is represented, δ is the optimal corner of front-wheel, and Δ ψ is the deviation of directivity, and Δ y is lateral displacement deviation, rr
For the radius of the center line camber in the predetermined track,
Step 4-3：Obtained according to the side velocity, the yaw velocity, the deviation of directivity and the lateral displacement deviation
To the simplified quadratic objective function：
Step 4-4：By solving Riccati equation, feedback oscillator K is obtainedLQG, it is described solution Riccati equation be：
A′P+PA-(PB+N)R-1(B ' P+N ')+Q=0
Wherein, R=1, N=0, vxFor longitudinal velocity, ayFor side acceleration, CyfFor front-wheel cornering stiffness,
CyrFor trailing wheel cornering stiffness, q3And q4Represent weight coefficient, T takes aim at the time to be pre-, a be automobile barycenter to front axle distance, b is automobile
Barycenter is to rear axle distance, and I is Vehicular yaw rotary inertia, and m is car mass, and P is the solution of Riccati equation,
Step 4-5：The additional rotation angle is obtained based on pre-defined rule according to the feedback oscillator, the additional rotation angle is：
δLOG=-KLOGΔx
Wherein, Δ x=x-x0,Y*For the predetermined track, ψ*For between the predetermined track tangent line and X-axis
Angle, X-axis be inertial coodinate system under reference axis.
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