CN106004870B

CN106004870B - A kind of intact stability integrated control method based on variable weight model prediction algorithm

Info

Publication number: CN106004870B
Application number: CN201610462960.9A
Authority: CN
Inventors: 郭洪艳; 马骉; 刘风
Original assignee: Jilin University
Current assignee: Jiangsu XCMG Construction Machinery Institute Co Ltd
Priority date: 2016-06-23
Filing date: 2016-06-23
Publication date: 2018-06-12
Anticipated expiration: 2036-06-23
Also published as: CN106004870A

Abstract

The invention discloses a kind of intact stability integrated control method based on variable weight model prediction algorithm, weaving and roll motion mainly for vehicle, to improve the stability of vehicle and riding comfort.Mainly comprise the steps of：Step 1: collection vehicle running condition information, and carry out estimation processing；Step 2: make separate decisions out holding vehicle yaw stability and the reference state value of roll stability；Step 3: selecting variable weight Model Predictive Control Algorithm, with front wheel angle and tire brake force, variable, integrated Vehicular yaw and roll stability control in order to control；Step 4: comparative tire desired braking power and brake pipe actual pressure, determine solenoid valve action command, while additional front wheel angle is superimposed with the go to action of driver, obtain final front wheel angle；Step 5: brake actuator and steering actuator perform solenoid valve action command and front wheel angle instruction, so as to which vehicle be made to keep Yaw stability and roll stability.

Description

A kind of intact stability integrated control method based on variable weight model prediction algorithm

Technical field

Design method more particularly to one kind the present invention relates to a kind of vehicle stability controller is pre- based on variable weight model The Vehicular yaw of method of determining and calculating and the design method of roll stability integrated manipulator.

Background technology

In recent years, increasingly complicated traffic environment results in the frequent generation of traffic accident, the wherein rollover of vehicle and side Sliding accident has become the chief threat of human life and property safety, this mainly has with the weaving of vehicle and roll motion It closes.At present, most research is individually controlled both for the sideway or roll motion of vehicle or is controlled two kinds of movements System is simply superimposed.But there are serious couplings between the sideway and roll motion of vehicle, and two kinds of controls are to a certain degree On can mutually promote.But under limiting condition, may there are certain contradiction, such as when high vehicle speeds height adhere to Road surface on urgent avoidance when, vehicle has understeer trend, and Yaw stability control can make vehicle follow desired traveling Track, and with the drastically steering of driver, the rollover degree of danger of vehicle can also be continuously improved.Therefore independent or simple superposition Control program the Yaw stability and roll stability of vehicle cannot be completely secured.

Invention content

The purpose of the present invention is being directed to the sideway of vehicle and roll motion, propose a kind of based on variable weight model prediction algorithm Intact stability integrated control method, with front wheel angle and tire brake force variable in order to control, according to the different traveling of vehicle State is based on variable weight model prediction algorithm and carries out integrated control to sideway and roll motion, while ensures sideway and the side of vehicle Incline stability, the generation for the phenomenon that effectively prevents from breakking away or turn on one's side.

Intact stability integrated control method based on variable weight model prediction algorithm proposed by the invention be by with What lower technical solution was realized：

1. a kind of intact stability integrated control method based on variable weight model prediction algorithm, includes the following steps：

Step 1: collecting vehicle car status information, and the estimated more freshly harvested car status information of processing in real time, including The steering wheel angle of vehicle, yaw velocity, side slip angle, angle of heel, roll velocity, longitudinal speed, lateral load turn Shifting rate, Brake pipe pressure and coefficient of road adhesion；

Step 2: handling obtained car status information in real time according to the step 1, make separate decisions out holding vehicle horizontal stroke The reference state value of pendulum stability and roll stability；

Step 3: based on variable weight model prediction algorithm, with front wheel angle and tire brake force variable in order to control, vehicle is designed Sideway and roll stability integrated manipulator：Select variable weight model prediction algorithm, using front wheel angle and tire brake force as Variable is controlled, integrates Vehicular yaw and roll stability control, and with yaw velocity track reference value and minimize lateral carry Target, selection fuzzy logic profile update two weight coefficients in object function to the lotus rate of transform in real time in order to control, Complete the design of controller；

Step 4: the tire desired braking power that controller in the step 3 is exported is opposed with brake pipe actual pressure Than so as to which decision goes out to brake the supercharging, pressurize or decompression state of execution system, and be converted into corresponding electromagnetism valve events and refer to It enables, while the additional front wheel angle exported in the step 3 is superimposed with the go to action of driver, obtain final front-wheel Corner；

Step 5: brake actuator and steering actuator perform solenoid valve action command and preceding rotation in the step 4 Angle instructs, and vehicle is made to keep Yaw stability and roll stability.

The present invention has the positive effect that as a result of above-mentioned technical solution, the present invention：

1st, on the basis of the sideway and roll stable performance demand for considering vehicle, the present invention proposes a kind of novel Intact stability integrated manipulator, and with front wheel angle and tire brake force variable in order to control, on the one hand have modified steering wheel and turn Longitudinal dynamics of the relationship of angle and active front corner without influencing vehicle, on the other hand further through to different wheel applications Brake force generates additional yaw moment.Influence of the lateral movement control to vehicular longitudinal velocity, while energy can not only be weakened in this way Enough ensure that tire has good control effect in any region, ensures the stability and riding comfort of vehicle.

2nd, the present invention utilizes Model Predictive Control Algorithm, when predicting that vehicle is one section following according to the operating status of current vehicle Interior state, simple in structure, strong robustness, while can handle with constrained Multi-variables optimum design problem, to develop vehicle Stabilitrak lays a solid foundation.

3rd, during optimal control, for the different transport conditions and durability requirements of vehicle, the present invention selects fuzzy Logic strategy updates the weight coefficient of sideway control and Roll control in object function in real time, realizes variable weight molality The design of type predictive controller meets stability demand of the vehicle for weaving and roll motion, ensure that stabilization The optimization of performance.

Description of the drawings

Fig. 1 is vehicle stabilization control conceptual scheme proposed by the invention；

Fig. 2 is steering wheel angle membership function figure；

Fig. 3 is lateral load rate of transform membership function figure；

Fig. 4 is Roll control weight coefficient membership function figure；

Fig. 5 schemes for Roll control weight coefficient three-dimensional map；

Fig. 6 is limiting condition steering wheel angle figure；

Fig. 7 is limiting condition yaw velocity figure；

Fig. 8 is limiting condition lateral load rate of transform figure；

Fig. 9 is limiting condition front wheel angle figure；

Figure 10-13 tries hard to for the braking of limiting condition tire.

Specific embodiment

Below in conjunction with the accompanying drawings, the technical solution proposed to invention is further elaborated and illustrates.

The present invention provides a kind of vehicle stability controller design method based on variable weight model prediction algorithm, such as Fig. 1 Shown, this method includes the following steps：

1. acquisition in real time and processing vehicle's current condition information：

First, the car status information that acquisition onboard sensor is fed back in real time, acquires including rotation direction sensor The steering wheel angle signal come, the yaw velocity and angle of heel speed at vehicle centroid that deflection efficiency sensor (gyroscope) acquires Signal, the acceleration signal longitudinally and laterally that acceleration transducer measures are spent, pressure sensor is detected to obtain and be braked at wheel The actual pressure signal of pipe.By these signals are filtered or estimation processing, so as to which the current steering wheel of real-time update vehicle turns Angle, yaw velocity, angle of heel, roll velocity, side slip angle, lateral load transfer, longitudinal speed and wheel cylinder braking The status informations such as pressure.

2. with handling obtained car status information in real time according to step 1, the holding vehicle yaw stability that makes separate decisions out and The reference state value of roll stability：

Since yaw velocity can really react the weaving state of vehicle, and with can be measured directly excellent Gesture, therefore the present invention really reacts the driving intention of driver by calculating the value with reference to yaw velocity, as vehicle Keep the reference state of Yaw stability.In this step, the yaw velocity r of reference is calculated by formula (1)_ref：

Wherein：L is car gage, v_xFor longitudinal speed, δ_fFor front wheel angle, k represents stability factor, is characterization automobile The important parameter of steady-state response, the present invention in value be 0.0025s²/m²

For the roll motion of vehicle, the present invention selects the lateral load rate of transform (Lateral-transfer-ratio) to make For the rollover index of automobile, referred to as LTR.It is defined as the vertical load of tire both sides difference with vertical load and ratio Exhausted angle value, shown in expression such as formula (2)：

Wherein, F_zlRepresent the sum of vertical load of vehicle the near front wheel and left rear wheel, F_zrRepresent vehicle off-front wheel and off hind wheel The sum of vertical load.

From the expression-form of the lateral load rate of transform, it can be seen that LTR is a variable between 0 and 1.Work as LTR Numerical value be 0 when, the vertical load of vehicle left side tire is equal with the vertical load of right side tire, illustrates vehicle at this time just In stable traveling；When the numerical value of LTR is 1, the vertical load of vehicle left side tire or right side tire is 0, and wheel has Leave the danger on ground, it is easy to rollover event occur.Therefore it is to keep vehicle roll stability that the present invention, which selects LTR=0, Reference state value.

3. based on variable weight model prediction algorithm, with front wheel angle and tire brake force, variable, design vehicle are horizontal in order to control Pendulum and roll stability integrated manipulator：

(1) system prediction model

For the weaving, lateral movement and roll motion of vehicle, simplified Three Degree Of Freedom auto model conduct is established Prediction model.Hypothesis below is made first：

I does not consider the influence of wheel steering system, front wheel angle δ_fInput as system；

II ignores the effect of suspension, it is believed that displacement of the automobile along z-axis, the angle of heel around x-axis are with the pitch angle around y-axis Zero；

III does not consider the influence of the variation of tyre load and ground tangential force to tire cornering characteristics；

IV ignores aerodynamic effect, and driving force is little；

V automobile is constant along the longitudinal velocity of x-axis.

Using iso standard vehicle axis system, coordinate origin is located at the barycenter of vehicle the present invention, and vehicle is along headstock to moving ahead The direction sailed is set as positive direction of the x-axis, and horizontal is the positive direction of y-axis to the left, and z-axis positive direction is determined by right-hand screw rule.Due toVehicle centroid lateral deviation angular rate of change is obtained according to up to bright BELL'S THEOREMAbout resulting side force ∑ F_y, sideway resultant force Square ∑ M_zAnd roll resultant moment ∑ M_xExpression formula：

Yaw velocity change rateAbout resulting side force ∑ F_y, sideway resultant moment ∑ M_zAnd roll resultant moment ∑ M_xTable Up to formula：

Roll velocity change rateAbout resulting side force ∑ F_y, sideway resultant moment ∑ M_zAnd roll resultant moment ∑ M_xTable Up to formula：

Wherein, D=I_xs-m_s ²e²/m-I_xzI_xzs/I_z

In order to describe the relationship between side force of tire and side drift angle, the present invention selects linear tire model, it is assumed that left front Wheel and off-front wheel, left rear wheel and off hind wheel have identical steering characteristic, then vehicle front-wheel lateral force F_yfWith front-wheel side drift angle α_f、 Trailing wheel lateral force F_yrWith trailing wheel side drift angle α_rRelational expression such as following formula (6) shown in：

Therefore tire resulting side force ∑ F is obtained_y, sideway resultant moment ∑ M_zAnd roll resultant moment ∑ M_xExpression formula such as formula (7) shown in-(9)：

∑F_y=K_fα_fcosδ_f+K_rα_r (7)

∑M_z=L_f·K_fα_fcosδ_f-L_r·K_rα_r+ΔM_z (8)

In above formula, m is complete vehicle quality, m_sFor vehicle spring carried mass, L_fFor front-wheel axle center to the distance of automobile barycenter, L_rFor Rear axis to vehicle centroid distance, e be vehicle spring carried mass barycenter to roll center distance.G is acceleration of gravity. v_xRepresent longitudinal direction of car speed, v_yThe lateral speed of vehicle is represented, r is yaw velocity, and β is side slip angle, and φ is body of a motor car Angle of heel, δ_fIt is front wheel angle.M_zIt is yaw moment of the vehicle around z-axis, Δ M_zFor additional yaw moment, M_xIt is vehicle around x-axis Moment resulting from sidesway.K_φFor the roll stiffness of vehicle, C_φInclination for vehicle damps, K_fFor front-wheel cornering stiffness, K_rFor trailing wheel lateral deviation Rigidity.I_zIt is complete vehicle quality around the rotary inertia of z-axis, I_xzIt is complete vehicle quality around x, the product of inertia of z-axis, I_xsFor vehicle spring carried mass Around the rotary inertia of vehicle axis system x-axis, I_xzsIt is vehicle spring carried mass around vehicle axis system x, the product of inertia of z-axis.

Do not depend on what driver inputted since electronic control unit can apply front-wheel one by wire-controlled steering system Additional rotation angle is superimposed maneuverability, stability and track retention property so as to improve vehicle with the go to action of driver.Cause This, additional front wheel angle can be superimposed as a controlled variable of control system with go to action, and final synthesis obtains preceding rotation Angle δ_fAs shown in following formula (10)：

δ_f=δ_fd+Δδ_f (10)

Wherein, Δ δ_fBe control system output additional front wheel angle, δ_fdIt is the steering wheel angle δ process steerings of driver Mechanism is applied to the corner on front-wheel, δ and δ_fdRelational expression such as following formula (11) shown in.

δ_fd=δ/I_sw (11)

In formula：I_swFor steering gear ratio.

There is nonlinear cornering behavior, when lateral force is in saturation state, course changing control however, as tire The lateral dynamic characteristic of vehicle cannot be directly changed.And differential braking is made by the way that four tires are applied with different longitudinal directions Power, so as to generate the additional yaw moment Δ M around Full Vehicle System z-axis_zEven if still have when lateral force saturation Certain validity.Therefore, using front wheel angle and tire brake force simultaneously as control variable.Set tire brake force positive direction The direction advanced with vehicle is on the contrary, formula (12) gives additional yaw moment Δ M_zWith the brake force Δ F of four tires_xiPass System.

Wherein, d₁、d₂Respectively vehicle wheel base, Δ F_yflFor the near front wheel brake force, Δ F_yfrFor off-front wheel brake force, ΔF_yrlFor left rear wheel brake force, Δ F_yrrFor off hind wheel brake force.

The basic control targe of Yaw stability is tracking of the yaw velocity for reference value, the root of roll stability This control targe is to reduce the lateral load rate of transform of vehicle, therefore it is controlled to select yaw velocity and the lateral load rate of transform Output quantity.Since the vertical load of both sides tire is not easy to measure, dynamic lateral load transfer rate LTR expression is obtained by shifting onto Formula is as follows：

Wherein, d=(d₁+d₂)/2 are averaged wheelspan for front and back wheel, h_RFor height of roll center.

From formula (13) as can be seen that LTR with β, r, φ andVariation and change.Therefore it is assumed herein that angle of heel Change rate isAnd it is state variable i.e. x to select side slip angle, yaw velocity, angle of heel and inclination angular rate of change =[β, r, φ, p], yaw velocity and the lateral load rate of transform are y=[r as controlled output；LTR], it will additional preceding rotation Angle and tire brake force are as control input i.e. u=[Δ δ_f,ΔF_xfl,ΔF_xfr,ΔF_xrl,ΔF_xrr].Due to δ_fdIt is by driving Member's output determines, it is impossible to it be predicted, therefore in the entire prediction time domain in each sampling period, it is believed that δ_fdIt is normal Value.

Composite type (3)-(13), the continuous time state space equation expression formula that final arrangement obtains prediction model are as follows：

For the design of subsequent controllers, need, by continuous state-space model discretization, to select the sampling time as Ts =0.01, after discretization, state-space model can be described as formula (15)：

Here definition prediction time domain is p, and control time domain is m, and p>m.Since the variation of longitudinal speed is continuous and slow Slow, therefore assume that speed is steady state value in prediction time domain.It is adapted with the rule of Nonlinear Model Predictive Control, it is assumed that vehicle Current time is k, and dynamic can be based on vehicle's current condition to vehicle in [k+1, k+p] prediction time domain and prediction model obtains It arrives.I.e. at the k+p moment, vehicle-state is x (k+p)=F (x (k), u (k), u (k+1) ..., u (k+m) ..., u (k+p-1)).

When being more than control time domain m in the sampling time, keep control input constant until predicting time domain, i.e. u (k+m-1)=u (k+m)=u (k+m+1)=...=u (k+p-1).

Therefore the optimum control input at k moment is defined：

Correspondingly, the prediction output of k moment yaw velocities r can be calculated by above-mentioned state equation (17)：

Equally, the lateral load rate of transform LTR prediction outputs at k moment are as follows：

It is corresponding with prediction output equation (17), it should predict real-time update in time domain each with reference to yaw velocity, Reference input sequence definition is as follows：

(2) based on the feedback optimized of Fuzzy strategy

Consider the Yaw stability of vehicle and roll stability demand, the yaw velocity r of vehicle reality should use up Yaw velocity r is referred in fast tracking_ref, while the reduction that lateral load rate of transform LTR should be as possible, therefore obtain integrated control Shown in the object function of device processed such as following formula (20)：

J=Γ_y||(Y₁(k+1|k)-R(k+1))||²+Γ_r||(Y₂(k+1|k))||² (20)

Herein, Γ_y=diag (τ_y,1,τ_y,2,…,τ_y,p), for the weight coefficient of vehicle yaw stability control, Γ_r= diag(τ_r,1,τ_r,2,…,τ_r,p) it is the weight coefficient that vehicle roll stability controls, work as Γ_yWhen relatively large, control system side The control to weaving is overweighted, i.e., practical yaw velocity has preferable tracking effect to its reference value, works as Γ_rIt is relatively large When, control system lays particular emphasis on the Roll control to vehicle, i.e., the size of the reduction lateral load rate of transform as possible.

Γ in object function_yAnd Γ_rThe weight that control system controls weaving and roll motion is represented respectively, The two has opposite meaning, therefore in order to realize variable weight control to adapt to the different stability energy demand of vehicle, herein We fix Γ_yValue, change Γ_rValue.Since the lateral load rate of transform of vehicle is the change of direct characterization vehicle roll state Amount, and steering wheel angle is to directly result in the input quantity that vehicle is turned on one's side, therefore the two parametric variables are to automobile roll shape The influence of state is maximum.So weight coefficient Γ for Roll control_rDesign one has two inputs and the Fuzzy Control singly exported Device processed, wherein input quantity are lateral load rate of transform LTR and steering wheel angle δ, and output quantity is Roll control weight coefficient Γ_r。

Since the degree of danger that vehicle is turned on one's side is more than the degree of danger breakked away, so when the rollover of vehicle is dangerous gradually When increase, Roll control weight coefficient should also increase therewith.With the aggravation that driver turns to, the LTR of vehicle also exists Gradual increase, this also gradually increases the danger of vehicle side turning, and Roll control is also more and more important in integrated control, so Γ_rIt should be gradually increased with the increase of δ and LTR.Illustrate herein, when LTR is smaller, vehicle rollover is dangerous Degree is relatively low, Γ_rIt should be slowly increased with the increase of δ；When LTR is larger, vehicle rollover degree of danger steeply rises, Therefore Γ_rSize should aggravate with the increase of δ.

Herein, LTR is blurred, is divided into 3 grades：S (low), M (in), B (height)；δ is obscured and is divided into 3 grades：S (low), M (in), B (height)；By Γ_rIt is fuzzy to be divided into 4 grades：S (low), M (in), MB (higher), B (height), membership function such as Fig. 2-4 It is shown.It is analyzed according to above-mentioned theory and emulates experience, final design goes out weight coefficient Γ_rSpecific fuzzy control about LTR and δ Rule, as shown in table 1.

1 fuzzy control rule of table

Input/output variable is blurred using Mamdani minimax rationalistic methods and anti fuzzy method operation, finally Obtain weight coefficient Γ_rAbout the three-dimensional map curved surfaces of input quantity LTR and δ, as shown in Figure 5.By above-mentioned fuzzy control strategy, The design that most weight coefficient is optimized at last.

For the stable constraint problem of vehicle, side slip angle should be made firstPhase plane movement locus is protected It holds and is stablizing in phase region.That is vehiclePhase plane movement locus should meet the inequality constraints shown in formula (21)：

Wherein, k, b are stable constraint constant.

Secondly consider the practical yaw velocity r of vehicle and reference yaw velocity r_refDeviation delta r, lateral load transfer The size of rate LTR should be limited within stable threshold, therefore there are the stable constraints shown in formula：

Finally consider the saturated characteristic of Vehicular system mechanical structure, control input should meet safety shown in following formula about Beam：

Wherein, i={ fl, fr, rl, rr }, Δ F_xiThe brake force of four tires is represented respectively.

Based on above analysis, most above-mentioned intact stability integrated control problem is described as following optimization problem at last：

4. the tire desired braking power that controller in step 3 is exported is compared with brake pipe actual pressure, so as to decision Go out to brake the supercharging, pressurize or decompression state of execution system, and be converted into corresponding solenoid valve action command, while will step The additional front wheel angle exported in rapid 3 is superimposed with the go to action of driver, obtains final front wheel angle；

Optimization problem as shown in formula (24) is solved by non-linear solution tool, and by first item, that is, u of optimized variable (k) as controller output quantity.Tire brake force Δ F_xiIt is expected pressure firstly the need of corresponding wheel cylinder is converted to by formula (25) Power P_di:

In above formula：I={ fl, fr, rl, rr }.P_diFor corresponding wheel cylinder brake pressure.D_wThe diameter of wheel cylinder is represented, C is represented Braking effectiveness factor, R_bThe radius of brake is represented, n represents oil cylinder number, r_dRepresent the rolling radius of tire.

By taking single wheel as an example, the wheel cylinder desired braking pressure P that will obtain_{i_ref}With wheel cylinder actual pressure P_iMaking deviation can obtain ΔP_i=P_i-P_{i_ref}.In control, according to the deviation Δ P of brake pressure_i, boosted, protected for the pressure of each wheel cylinder The adjusting of three kinds of states of pressure and decompression.Frequently switching in order to avoid solenoid valve herein, set the threshold value of pressure divergence as ΔP_th, only when deviation exceeds this threshold value, just boosted or Decompression Controlling, be converted into the transmission of solenoid valve action command To executing agency.Specific judgement situation is as follows：

(1) as-Δ P_th＜ Δs P_i＜ Δs P_thPressurize is adjusted

(2) as Δ P_i＞ Δs P_thDecompression is adjusted

(3) as Δ P_i＜-Δ P_thBoost pressure regulation

Additional front wheel angle is superimposed with driver's go to action, final synthesis obtains front wheel angle δ_fFor δ_fd+Δδ_f。

5th, brake actuator and the solenoid valve action command and front wheel angle that turn in actuator execution step 4 instruct, and make Vehicle restores stability：

The front wheel angle signal that decision in step 4 goes out is applied to and turns to executing agency, while by the solenoid valve in step 4 Action command is applied to brake actuator, after the completion of being performed by executing agency, vehicle is made to restore to stablize traveling.

Using vehicle dynamics simulation software veDYNA, light auto models are selected, under simulink simulated environment, The controller model for realizing above-mentioned control program is built, emulation experiment has been done under limit open loop operating mode：It is 0.8 in friction coefficient Road on, vehicle accelerates to 80km/h, gives steering wheel angle signal as shown in Figure 6, and simulation time is 35 seconds.It is emulated As a result as illustrated in figures 7 to 13.Find out from simulation result, under the driving cycles of the limit, the intact stability collection designed by the present invention It can make the ideal yaw velocity of the vehicle upper reference value of tracking, and the lateral load rate of transform also can well into control method It is fluctuated in stable threshold range, while meets front wheel angle and tire brake force within restriction range, meet vehicle Yaw stability and roll stability requirement.

Claims

1. a kind of intact stability integrated control method based on variable weight model prediction algorithm, which is characterized in that including following Step：

Step 1: collecting vehicle car status information, and the estimated more freshly harvested car status information of processing in real time, including vehicle Steering wheel angle, yaw velocity, side slip angle, angle of heel, roll velocity, longitudinal speed, the lateral load rate of transform, Brake pipe pressure and coefficient of road adhesion；

Step 2: handling obtained car status information in real time according to the step 1, the holding Vehicular yaw that makes separate decisions out is steady Qualitative and roll stability reference state value；

Step 3: based on variable weight model prediction algorithm, with front wheel angle and tire brake force, variable, design vehicle are horizontal in order to control Pendulum and roll stability integrated manipulator：Variable weight model prediction algorithm is selected, with front wheel angle and tire brake force in order to control Variable integrates Vehicular yaw and roll stability control, and with yaw velocity track reference value and minimizes lateral load turn Target, selection fuzzy logic profile update two weight coefficients in object function, are completed shifting rate in real time in order to control The design of controller；

Specifically include following steps：

3.1) for the weaving of vehicle, lateral movement and roll motion, simplified Three Degree Of Freedom auto model conduct is established Prediction model：

Tire resulting side force ∑ F_y, sideway resultant moment ∑ M_zAnd roll resultant moment ∑ M_xExpression formula be respectively：

∑F_y=K_fα_fcosδ_f+K_rα_r

∑M_z=L_f·K_fα_fcosδ_f-L_r·K_rα_r+ΔM_z

In formula, m_sFor vehicle spring carried mass, L_fFor front-wheel axle center to the distance of automobile barycenter, L_rFor rear axis to vehicle centroid Distance, e be the barycenter of vehicle spring carried mass to the distance of roll center, g is acceleration of gravity, v_xRepresent longitudinal direction of car vehicle Speed, v_yRepresent the lateral speed of vehicle, r is yaw velocity, and β is side slip angle, and φ is body of a motor car angle of heel, δ_fIt is front-wheel Corner, M_zIt is yaw moment of the vehicle around z-axis, Δ M_zFor additional yaw moment, M_xIt is moment resulting from sidesway of the vehicle around x-axis, K_φFor The roll stiffness of vehicle, C_φInclination for vehicle damps, K_fFor front-wheel cornering stiffness, K_rFor trailing wheel cornering stiffness, α_fFor front wheel side Drift angle, α_rFor trailing wheel side drift angle, b is stable constraint constant；

Dynamic lateral load transfer rate LTR expression formulas are as follows：

Wherein, d=(d₁+d₂)/2 are averaged wheelspan for front and back wheel, d₁For vehicle front tread, d₂It is vehicle rear wheel away from h_RFor in inclination Heart height；

The continuous time state space equation expression formula of prediction model is as follows：

By continuous state-space model discretization, the sampling time is selected as Ts=0.01, after discretization, state space mould Type can be described as：

Definition prediction time domain is p, and control time domain is m, and p>m；

3.2) based on the feedback optimized of Fuzzy strategy：

Consider the Yaw stability of vehicle and roll stability demand, the object function for obtaining integrated manipulator is：

J=Γ_y||(Y₁(k+1|k)-R(k+1))||²+Γ_r||(Y₂(k+1|k))||²

Wherein, Γ_y=diag (τ_y,1, τ _y,2, … , τ _y,p), the weight for vehicle yaw stability control Coefficient, Γ_r=diag (τ_r,1,τ_r,2,…,τ_r,p) it is the weight coefficient that vehicle roll stability controls；

Intact stability integrated control problem is described as following optimization problem：

Meet

Step 4: the tire desired braking power that controller in the step 3 is exported is compared with brake pipe actual pressure, from And decision goes out to brake the supercharging, pressurize or decompression state of execution system, and is converted into corresponding solenoid valve action command, together When the additional front wheel angle exported in the step 3 is superimposed with the go to action of driver, obtain final front wheel angle；

Step 5: brake actuator and the solenoid valve action command and front wheel angle that turn in the actuator execution step 4 refer to It enables, vehicle is made to keep Yaw stability and roll stability.

2. a kind of intact stability integrated control method based on variable weight model prediction algorithm as described in claim 1, It is characterized in that, the step 4 includes the following steps：

The excellent of Vehicular yaw that the step 3 designs and roll stability integrated manipulator is solved by non-linear solution tool Change problem；

By the following formula by tire brake force Δ F_xiBe converted to corresponding wheel cylinder desired pressure P_di：

In formula：I={ fl, fr, rl, rr }；P_diFor corresponding wheel cylinder brake pressure；D_wRepresent the diameter of wheel cylinder；C represents braking effect It can factor；R_bRepresent the radius of brake；N represents oil cylinder number；r_dRepresent the rolling radius of tire；

The wheel cylinder desired braking pressure P that will be obtained_{i_ref}With wheel cylinder actual pressure P_iΔ P can be obtained by making deviation_i=P_i-P_{i_ref}；It is controlling When, according to the deviation Δ P of brake pressure_i, for each wheel cylinder pressure boosted, pressurize and be depressured three kinds of states tune Section；

The threshold value of pressure divergence is set as Δ P_th, only when deviation exceeds this threshold value, just boosted or depressurized control System, is converted into solenoid valve action command and sends executing agency to, specific to judge that situation is as follows：

(1) as-Δ P_th＜ Δs P_i＜ Δs P_thPressurize is adjusted

(2) as Δ P_i＞ Δs P_thDecompression is adjusted

(3) as Δ P_i＜-Δ P_thBoost pressure regulation

Additional front wheel angle is superimposed with driver's go to action, final synthesis obtains front wheel angle.