CN106004870A - Vehicle stability integrated control method based on variable-weight model prediction algorithm - Google Patents

Abstract

The invention discloses a vehicle stability integrated control method based on a variable-weight model prediction algorithm. The method is mainly aimed at yawing motion and side-tipping motion of a vehicle to improve the stability and the riding comfort of the vehicle. The method mainly comprises steps as follows: step one, vehicle driving state information is acquired and subjected to estimation processing; step two, reference state values for keeping the yawing stability and the side-tipping stability of the vehicle are decided respectively; step three, a variable-weight model prediction control algorithm is used, a front wheel rotating angle and tire braking force are taken as control variables, and vehicle yawing and side-tipping stability control are integrated; step four, expected tire braking force is compared with actual pressure of a brake tube, an action instruction of an electromagnetic valve is determined, an additional front wheel rotation angle and steering action of a driver are superposed, and a final front wheel rotation angle is obtained; step five, a brake executer and a steering executer execute the action instruction of the electromagnetic valve and a front wheel rotation angle instruction, so that the vehicle keeps the yawing stability and side-tipping stability.

Description

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

Technical field

The present invention relates to the method for designing of a kind of vehicle stability controller, particularly relate to a kind of pre-based on variable weight model The Vehicular yaw of method of determining and calculating and the method for designing of roll stability integrated manipulator.

Background technology

In recent years, day by day complicated traffic environment result in the frequent generation of vehicle accident, wherein the rollover of vehicle and side Sliding accident has become as the chief threat of human life and property safety, and this main weaving and roll motion with vehicle has Close.At present, most research is both for the yaw of vehicle or roll motion individually controls, or by two kinds of motion controls System carries out simple superposition.But there is serious coupling between the yaw of vehicle and roll motion, two kinds control to a certain degree On can mutually promote.But under limiting condition, certain contradiction may be there is, such as adhere at height when high vehicle speeds Road surface on urgent avoidance time, vehicle has understeer trend, and Yaw stability controls to make vehicle follow desired traveling Track, and drastically turning to along with driver, also can improve constantly the rollover degree of danger of vehicle.Therefore individually or simple superposition Control program Yaw stability and the roll stability of vehicle can not be completely secured.

Summary of the invention

It is an object of the invention to the yaw for 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 as control variable, according to the traveling that vehicle is different State carries out integrating control based on variable weight model prediction algorithm to yaw and roll motion, ensures yaw and the side of vehicle simultaneously Incline stability, effectively prevent from breakking away or the generation of rollover phenomenon.

Intact stability integrated control method based on variable weight model prediction algorithm proposed by the invention be by with Lower technical scheme realizes:

1. an intact stability integrated control method based on variable weight model prediction algorithm, comprises the following steps:

Step one, Real-time Collection car car status information, and the estimated car status information processing renewal collection, 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, processing the car status information obtained in real time according to described step one, the holding vehicle that makes separate decisions out is horizontal 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 as control variable, design car Yaw and roll stability integrated manipulator: select variable weight model prediction algorithm, with front wheel angle and tire brake force be Control variable, integrated Vehicular yaw and roll stability control, and laterally carry with minimizing with yaw velocity track reference value The lotus rate of transform, for controlling target, selects fuzzy logic profile that two weight coefficients in object function carry out real-time renewal, Complete the design of controller；

Step 4, by described step 3 middle controller export tire desired braking power oppose with brake pipe actual pressure Ratio, thus decision-making goes out to brake the supercharging of execution system, pressurize or decompression state, and be converted into corresponding electromagnetic valve action and refer to Order, superposes the additional front wheel angle of output in described step 3 with the go to action of driver simultaneously, obtains final front-wheel Corner；

Step 5, brake actuator and turn to the electromagnetic valve action command and front round that executor performs in described step 4 Angle instructs, and makes vehicle keep Yaw stability and roll stability.

Due to the fact that and have employed above-mentioned technical scheme, the present invention has the positive effect that:

1, on the basis of the yaw considering vehicle and roll stable performance demand, the present invention proposes a kind of novel Intact stability integrated manipulator, and with front wheel angle and tire brake force as control variable, on the one hand have modified steering wheel and turn Angle and the relation of active front corner and do not affect the longitudinal dynamics of vehicle, on the other hand apply further through to different wheels Brake force produces additional yaw moment.The most not only can weaken lateral movement and control the impact on vehicular longitudinal velocity, energy simultaneously Enough ensure that tire all has good control effect in any region, it is ensured that the stability of vehicle and riding comfort.

2, the present invention utilizes Model Predictive Control Algorithm, when predicting following one section of vehicle according to the running status of Current vehicle Interior state, simple in construction, strong robustness, the constrained Multi-variables optimum design problem of band can be processed, for exploitation vehicle simultaneously Stabilitrak lays a solid foundation.

3, during optimal control, for different transport conditions and the durability requirements of vehicle, the present invention selects fuzzy Yaw in object function is controlled by logic strategy and the weight coefficient of Roll control carries out real-time renewal, it is achieved that variable weight mould The design of type predictive controller, meets the vehicle stability demand for weaving and roll motion, it is ensured that stable The optimization of performance.

Accompanying drawing explanation

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 is Roll control weight coefficient three-dimensional map figure；

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.

Detailed description of the invention

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

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

1. Real-time Collection and process vehicle's current condition information:

First, the car status information that Real-time Collection onboard sensor feeds back, including rotation direction sensor collection The steering wheel angle signal come, the yaw velocity at vehicle centroid and angle of heel that deflection efficiency sensor (gyroscope) gathers are fast Degree signal, the acceleration signal longitudinally and laterally that acceleration transducer is measured, pressure transducer detection obtains braking at wheel The actual pressure signal of pipe.By these signals, after filtering or estimation processes, thus 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 processing the car status information obtained 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:

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

$r_{ref}=\frac{v_x/L}{1+k\·{v^2}_x}{\mathrm{\δ}}_f---\left(1\right)$

Wherein: L is car gage, v_xFor longitudinal speed, δ_fFor front wheel angle, k represents stability factor, is to characterize automobile The important parameter of steady-state response, in the present invention, value is 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 tire both sides vertical load difference and vertical load and ratio Exhausted angle value, shown in expression such as formula (2):

$\left|LTR\right|=\left|\frac{F_{zl}-F_{zr}}{F_{zl}+F_{zr}}\right|---\left(2\right)$

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

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 when be 0, the vertical load of vehicle left side tire is equal with the vertical load of right side tire, illustrates that vehicle is the most just In stable traveling；When the numerical value of LTR is 1 when, 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 occurs.Therefore the present invention selects LTR=0 to be to keep vehicle roll stability Reference state value.

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

(1) system prediction model

For weaving, lateral movement and the roll motion of vehicle, set up the Three Degree Of Freedom auto model conduct simplified Forecast model.First hypothesis below is made:

I impact not considering wheel steering system, front wheel angle δ_fInput as system；

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

III change not considering tyre load and the impact on tire cornering characteristics of the ground tangential force；

IV ignores aerodynamic effect, and driving force is little；

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

The present invention uses iso standard vehicle axis system, and zero is located at the barycenter of vehicle, vehicle along headstock to moving ahead The direction sailed is set to x-axis positive direction, and level 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 side drift angle rate of change is obtained according to reaching bright BELL'S THEOREMAbout resulting side force ∑ F_y, yaw make a concerted effort Square ∑ M_zAnd roll resultant moment ∑ M_xExpression formula:

$\stackrel{\·}{\mathrm{\β}}=\frac{{m_s}^2{e}^2+mD}{m^2{\mathrm{Dv}}_x}{\mathrm{\ΣF}}_y-\frac{m_s{\mathrm{eI}}_{xzs}}{{\mathrm{mI}}_z{\mathrm{Dv}}_x}{\mathrm{\ΣM}}_z+\frac{m_{s}e}{{\mathrm{mDv}}_x}{\mathrm{\ΣM}}_x---\left(3\right)$

Yaw velocity rate of changeAbout resulting side force ∑ F_y, yaw resultant moment ∑ M_zAnd roll resultant moment ∑ M_xTable Reach formula:

$\stackrel{\·}{r}=\frac{-I_{xz}{m}_{s}e}{mD}{\mathrm{\ΣF}}_y+\frac{I_{z}D+I_{xz}{I}_{xzs}}{{I_z}^{2}D}{\mathrm{\ΣM}}_z-\frac{I_{xz}}{I_{z}D}{\mathrm{\ΣM}}_x---\left(4\right)$

Roll velocity rate of changeAbout resulting side force ∑ F_y, yaw resultant moment ∑ M_zAnd roll resultant moment ∑ M_xTable Reach formula:

$\stackrel{\·\·}{\mathrm{\φ}}=\frac{m_{s}e}{mD}{\mathrm{\ΣF}}_y-\frac{I_{xzs}}{I_{z}D}{\mathrm{\ΣM}}_z+\frac{1}{D}{\mathrm{\ΣM}}_x---\left(5\right)$

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

In order to describe the relation 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 side force F_yfWith front wheel side drift angle α_f、 Trailing wheel side force F_yrWith rear wheel-side drift angle α_rRelational expression such as following formula (6) shown in:

$\begin{array}{c}{F}_{yf}=K_f{\mathrm{\α}}_f\\ F_{yr}=K_r{\mathrm{\α}}_r\end{array}---\left(6\right)$

Therefore tire resulting side force ∑ F is obtained_y, yaw 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)

${\mathrm{\ΣM}}_x=m_s\·g\·e\·\mathrm{\φ}-K_{\mathrm{\φ}}\·\mathrm{\φ}-C_{\mathrm{\φ}}\·\stackrel{\·}{\mathrm{\φ}}---\left(9\right)$

In above formula, m is complete vehicle quality, m_sFor vehicle spring carried mass, L_fFor the distance in front-wheel axle center to automobile barycenter, L_rFor Rear axis is to the distance of vehicle centroid, and e is the barycenter distance to roll center of vehicle spring carried mass.G is acceleration of gravity. v_xRepresent longitudinal direction of car speed, v_yRepresenting 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 it is front wheel angle.M_zIt is the vehicle yaw moment around z-axis, Δ M_zFor additional yaw moment, M_xIt is that vehicle is 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_zFor complete vehicle quality around the rotary inertia of z-axis, I_xzFor 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_xzsFor vehicle spring carried mass around vehicle axis system x, the product of inertia of z-axis.

It is independent of driver's input owing to electronic control unit can apply one by wire-controlled steering system to front-wheel Additional rotation angle, superposes with the go to action of driver thus improves the maneuverability of vehicle, stability and track and keep performance.Cause This, additional front wheel angle can superpose with go to action as control system a controlled variable, the most comprehensively obtain front round Angle δ_fAs shown in following formula (10):

δ_f=δ_fd+Δδ_f (10)

Wherein, Δ δ_fIt is the additional front wheel angle of control system output, δ_fdIt is that the steering wheel angle δ of driver is through turning to 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.

Yet with tire, there is nonlinear cornering behavior, when side force is in saturation when, course changing control Can not directly change the lateral dynamic characteristic of vehicle.And differential braking is by four tires are applied different longitudinal direction systems Power, thus produce the additional yaw moment Δ M around Full Vehicle System z-axis_zEven if still having side force is saturated when Certain effectiveness.Therefore, by front wheel angle and tire brake force simultaneously as control variable.Set tire brake force positive direction In opposite direction with what vehicle advanced, formula (12) gives additional yaw moment Δ M_zBrake force Δ F with four tires_xiPass System.

${\mathrm{\ΔM}}_z=(-\frac{d_1}{2}{\mathrm{cos\δ}}_f+L_f{\mathrm{sin\δ}}_f){\mathrm{\ΔF}}_{xfl}-\frac{d_2}{2}{\mathrm{\ΔF}}_{xrl}+(\frac{d_1}{2}{\mathrm{cos\δ}}_f+L_f{\mathrm{sin\δ}}_f){\mathrm{\ΔF}}_{xfr}+\frac{d_2}{2}{\mathrm{\ΔF}}_{xrr}---\left(12\right)$

Wherein, d₁、d₂It is respectively 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.

Basic control of Yaw stability aims at the yaw velocity tracking for reference value, the root of roll stability This control target is to reduce the lateral load rate of transform of vehicle, and it is controlled for therefore selecting yaw velocity and the lateral load rate of transform Output.Owing to the vertical load of both sides tire is not easy to measure, through and shifting onto obtain the expression of dynamic lateral load transfer rate LTR Formula is as follows:

$\left|LTR\right|=|\frac{2}{d\·m_s\·g}\[m_s\·h_R\·(v_x\·r+v_x\·\stackrel{\·}{\mathrm{\β}}-e\·\stackrel{\·\·}{\mathrm{\φ}})+K_{\mathrm{\φ}}\·\mathrm{\φ}+C_{\mathrm{\φ}}\·\stackrel{\·}{\mathrm{\φ}}\]|---\left(13\right)$

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

From formula (13) it can be seen that LTR along with β, r, φ andChange and change.Therefore it is assumed herein that angle of heel Rate of change isAnd to select side slip angle, yaw velocity, angle of heel and angle of heel rate of change be state variable i.e. x =[β, r, φ, p], yaw velocity and the lateral load rate of transform are as controlled output i.e. y=[r；LTR], will additional front round Angle and tire brake force are as controlling 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 be enough predicted it, therefore in the whole prediction time domain in each sampling period, it is believed that δ_fdIt is normal Value.

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

$\left\{\begin{array}{c}\stackrel{\·}{x}\left(t\right)=f\left(x\right(t),u(t\left)\right)\\ y\left(t\right)=g\left(x\right(t),u(t\left)\right)\end{array}\right.---\left(14\right)$

For the design of subsequent controllers, needing continuous print state-space model discretization, the selection sampling time is Ts =0.01, after discretization, state-space model can be described as formula (15):

$\left\{\begin{array}{c}x(k+1)=F\left(x\right(k),u(k\left)\right)\\ y\left(k\right)=G\left(x\right(k),u(k\left)\right)\end{array}\right.---\left(15\right)$

Here definition prediction time domain is p, and control time domain is m, and p > m.Owing to the change of longitudinal speed is continuous and slow Slow, therefore in prediction time domain, assume that speed is steady state value.Adapt with the rule of Nonlinear Model Predictive Control, it is assumed that car Current time is k, and vehicle dynamically can obtain based on vehicle's current condition and forecast model in [k+1, k+p] prediction time domain Arrive.I.e. in the k+p moment, vehicle-state be x (k+p)=F (x (k), u (k), u (k+1) ..., u (k+m) ..., u (k+p-1)).

When the sampling time is more than control time domain m, keep controlling 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 in definition k moment:

$U\left(k\right)=\left[\begin{array}{c}u\left(k\right|k)\\ u(k+1|k)\\ .\\ .\\ .\\ u(k+m-1|k)\end{array}\right]---\left(16\right)$

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

$Y_1(k+1|k)=\left[\begin{array}{c}r(k+1|k)\\ r(k+2|k)\\ .\\ .\\ .\\ r(k+p|k)\end{array}\right]---\left(17\right)$

Equally, the lateral load rate of transform LTR prediction output in k moment is as follows:

$Y_2(k+1|k)=\left[\begin{array}{c}LTR(k+1|k)\\ LTR(k+2|k)\\ .\\ .\\ .\\ LTR(k+p|k)\end{array}\right]---\left(18\right)$

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

$R(k+1|k)=\left[\begin{array}{c}{r}_{ref}(k+1)\\ r_{ref}(k+2)\\ .\\ .\\ .\\ r_{ref}(k+p)\end{array}\right]---\left(19\right)$

(2) based on Fuzzy strategy feedback optimized

Considering Yaw stability and the roll stable sexual demand of vehicle, the yaw velocity r of vehicle reality should use up Fast tracking is upper with reference to yaw velocity r_ref, lateral load rate of transform LTR should be tried one's best simultaneously reduction, 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)

Here, Γ_y=diag (τ_y,1,τ_y,2,…,τ_y,p), the weight coefficient controlled for vehicle yaw stability, Γ_r= diag(τ_r,1,τ_r,2,…,τ_r,p) be vehicle roll stability control weight coefficient, work as Γ_yTime relatively large, control system side Overweighting the control to weaving, actual yaw velocity has preferable tracking effect to its reference value, works as Γ_rRelatively large Time, control system lays particular emphasis on the Roll control to vehicle, the size of the reduction lateral load rate of transform i.e. as far as possible.

Γ in object function_yAnd Γ_rRepresent the weight that control system controls for weaving and roll motion respectively, Both have relative meaning, control to adapt to the different stability energy demand of vehicle, here therefore to realize variable weight We fix Γ_yValue, change Γ_rValue.Owing to the lateral load rate of transform of vehicle is directly to characterize the change of vehicle roll state Amount, and steering wheel angle is to directly result in vehicle the input quantity of rollover occurs, therefore the two parametric variable is to automobile roll shape The impact of state is maximum.So for the weight coefficient Γ of Roll control_rDesign a Fuzzy Control with two inputs and single output Device processed, wherein input quantity is lateral load rate of transform LTR and steering wheel angle δ, and output is Roll control weight coefficient Γ_r。

Owing to there is the degree of danger degree of danger more than sideslip of rollover in vehicle, so working as the rollover danger of vehicle gradually The when of increase, Roll control weight coefficient also should increase therewith.The aggravation turned to along with driver, the LTR of vehicle also exists Gradually increasing, this most gradually increases the danger of vehicle side turning, and Roll control is more and more important in integrating control, so Γ_rShould be gradually increased along with the increase of δ and LTR.Here illustrating, when LTR is less when, vehicle rollover is dangerous Degree is relatively low, Γ_rAlong with the increase of δ should be slowly increased；When LTR is bigger when, vehicle rollover degree of danger steeply rises, Therefore Γ_rSize should aggravate along with the increase of δ.

Here, by LTR obfuscation, be divided into 3 grades: S (low), M (in), B (high)；δ obfuscation is divided into 3 grades: S (low), M In (), B (high)；By Γ_rObfuscation be divided into 4 grades: S (low), M (in), MB (higher), B (high), its membership function such as Fig. 2-4 Shown in.According to above-mentioned theory analysis and emulation experience, final design goes out weight coefficient Γ_rConcrete fuzzy control about LTR and δ Rule, as shown in table 1.

Table 1 fuzzy control rule

Mamdani minimax rationalistic method is used input/output variable to carry out obfuscation and anti fuzzy method computing, finally Obtain weight coefficient Γ_rAbout input quantity LTR and the three-dimensional map curved surface of δ, as shown in Figure 5.Through above-mentioned fuzzy control strategy, Weight coefficient has carried out optimized design the most at last.

For the stable constraint problem of vehicle, side slip angle first should be madePhase plane movement locus is protected Hold in stable phase region.I.e. vehiclePhase plane movement locus should meet the inequality constraints shown in formula (21):

$|\stackrel{\·}{\mathrm{\β}}-k\mathrm{\β}|\≤\left|b\right|.---\left(21\right)$

Wherein, k, b are stable constraint constant.

Secondly vehicle actual yaw velocity r and reference yaw velocity r is considered_refDeviation delta r, lateral load transfer Within the size of rate LTR should be limited to stable threshold, therefore there is the stable constraint shown in formula:

$\begin{array}{c}\left|\mathrm{\&Delta;}r\right|<{\mathrm{\&Delta;r}}_{th}\\ 0\&le;LTR\&le;{\mathrm{LTR}}_{th}\end{array}---\left(22\right)$

Finally consider the saturated characteristic of Vehicular system frame for movement, control input and should meet the safety shown in following formula about Bundle:

$\begin{array}{c}{\mathrm{\&Delta;\&delta;}}_{f\min }\&le;{\mathrm{\&Delta;\&delta;}}_f\&le;{\mathrm{\&Delta;\&delta;}}_{fmax}\\ {\mathrm{\&Delta;F}}_{x\min }\&le;{\mathrm{\&Delta;F}}_{xi}\&le;{\mathrm{\&Delta;F}}_{x\max }\end{array}---\left(23\right)$

Wherein, i={fl, fr, rl, rr}, Δ F_xiRepresent the brake force of four tires respectively.

Based on above analysis, the most above-mentioned intact stability integrating control problem is described as following optimization problem:

4. the tire desired braking power that step 3 middle controller exports is compared with brake pipe actual pressure, thus decision-making Go out to brake the supercharging of execution system, pressurize or decompression state, and be converted into corresponding electromagnetic valve action command, simultaneously will step In rapid 3, the additional front wheel angle of output superposes with the go to action of driver, obtains final front wheel angle；

The optimization problem as shown in formula (24) is solved by nonlinear solution instrument, and by the Section 1 of optimized variable i.e. u K () is as controller output.Tire brake force Δ F_xiCorresponding wheel cylinder expectation pressure is converted to firstly the need of by formula (25) Power P_di:

${\mathrm{\&Delta;F}}_{xi}=P_{di}\&CenterDot;\frac{{\mathrm{\&pi;D}}_w}{4}\&CenterDot;n\&CenterDot;C\&CenterDot;\frac{R_b}{r_d}---\left(25\right)$

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

As a example by single wheel, the wheel cylinder desired braking pressure P that will obtain_{i_ref}With wheel cylinder actual pressure P_iMake deviation can obtain ΔP_i=P_i-P_{i_ref}.When controlling, according to inclined difference DELTA P of brake pressure_i, the pressure for each wheel cylinder carries out boosting, protecting Pressure and the regulation of three kinds of states of blood pressure lowering.Frequently switching in order to avoid electromagnetic valve here, set the threshold value of pressure divergence as ΔP_th, only when deviation value is beyond this threshold value, just carry out boosting or Decompression Controlling, be converted into electromagnetic valve action command transmission To actuator.Concrete judgement situation is as follows:

(1) as-Δ P_th＜ Δ P_i＜ Δ P_thPressurize regulates

(2) as Δ P_i＞ Δ P_thDecompression regulation

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

Additional front wheel angle is superposed with driver's go to action, the most comprehensively obtains front wheel angle δ_fFor δ_fd+Δδ_f。

5, brake actuator and turn to the electromagnetic valve action command and front wheel angle instruction that executor performs in step 4, makes Vehicle resume stability:

Front wheel angle signal decision-making in step 4 gone out is applied to turn to actuator, simultaneously by the electromagnetic valve in step 4 Action command is applied to brake actuator, after actuator has performed, makes vehicle recover stable and travels.

Utilize vehicle dynamics simulation software veDYNA, select light auto model, under simulink simulated environment, Build the controller model realizing above-mentioned control program, under limit open loop operating mode, done emulation experiment: be 0.8 at coefficient of friction Road on, vehicle accelerates to 80km/h, and given steering wheel angle signal as shown in Figure 6, simulation time is 35 seconds.Its emulation Result is as illustrated in figures 7 to 13.Find out from simulation result, the intact stability collection under the driving cycles of the limit, designed by the present invention Become control method that the preferable yaw velocity of vehicle can be made well to follow the tracks of reference value, and the lateral load rate of transform also can Fluctuate in stable threshold range, meet front wheel angle and tire brake force simultaneously within restriction range, meet vehicle Yaw stability and roll stability requirement.

Claims (3)

1. an intact stability integrated control method based on variable weight model prediction algorithm, it is characterised in that include following Step:

Step one, Real-time Collection car car status information, and the estimated car status information processing renewal collection, 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, processing the car status information obtained in real time according to described step one, the holding Vehicular yaw that makes separate decisions out is steady The qualitative reference state value with roll stability；

Step 3, based on variable weight model prediction algorithm, with front wheel angle and tire brake force as control variable, design vehicle is horizontal Pendulum and roll stability integrated manipulator: select variable weight model prediction algorithm, with front wheel angle and tire brake force for controlling Variable, integrated Vehicular yaw and roll stability control, and with yaw velocity track reference value with minimize lateral load and turn Shifting rate, for controlling target, is selected fuzzy logic profile that two weight coefficients in object function are carried out real-time renewal, is completed The design of controller；

Step 4, by described step 3 middle controller export tire desired braking power compare with brake pipe actual pressure, from And decision-making goes out to brake the supercharging of execution system, pressurize or decompression state, and it is converted into corresponding electromagnetic valve action command, with Time by described step 3 output additional front wheel angle superpose with the go to action of driver, obtain final front wheel angle；

Step 5, brake actuator and turn to electromagnetic valve action command that executor performs in described step 4 and front wheel angle to refer to Order, makes vehicle keep Yaw stability and roll stability.

A kind of intact stability integrated control method based on variable weight model prediction algorithm, its Being characterised by, described step 3 is based on variable weight model prediction algorithm, with front wheel angle and tire brake force as control variable, if Meter Vehicular yaw and roll stability integrated manipulator comprise the following steps:

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

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

∑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 is complete vehicle quality, m_sFor vehicle spring carried mass, L_fFor the distance in front-wheel axle center to automobile barycenter, L_rFor hind axle The heart is to the distance of vehicle centroid, and e is the barycenter distance to roll center of vehicle spring carried mass.G is acceleration of gravity, v_xRepresent Longitudinal direction of car speed, v_yRepresenting the lateral speed of vehicle, r is yaw velocity, and β is side slip angle, and φ is that body of a motor car rolls Angle, δ_fIt is front wheel angle, M_zIt is the vehicle yaw moment around z-axis, Δ M_zFor additional yaw moment, M_xIt it is the vehicle side around x-axis Go all out square, K_φFor the roll stiffness of vehicle, C_φInclination for vehicle damps, K_fFor front-wheel cornering stiffness, K_rFirm for trailing wheel lateral deviation Degree, I_zFor complete vehicle quality around the rotary inertia of z-axis, I_xzFor 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_xzsFor vehicle spring carried mass around vehicle axis system x, the product of inertia of z-axis；

Dynamic lateral load transfer rate LTR expression formula is as follows:

Wherein, d=(d₁+d₂)/2 are the average wheelspan of front and back wheel, h_RFor height of roll center；

State space equation expression formula continuous time of forecast model is as follows:

By continuous print state-space model discretization, the selection sampling time is Ts=0.01, after discretization, and 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 Fuzzy strategy feedback optimized:

Considering Yaw stability and the roll stable sexual demand of vehicle, the object function 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 coefficient controlled for vehicle yaw stability, Γ_r=diag (τ_r,1,τ_r,2,…,τ_r,p) be vehicle roll stability control weight coefficient；

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

Meet。

A kind of intact stability integrated control method based on variable weight model prediction algorithm, its Being characterised by, described step 4 comprises the following steps:

The Vehicular yaw of described step 3 design and the excellent of roll stability integrated manipulator is solved by nonlinear solution instrument Change problem；

By below equation 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 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 obtain_{i_ref}With wheel cylinder actual pressure P_iMake deviation and can obtain Δ P_i=P_i-P_{i_ref}；Controlling Time, according to inclined difference DELTA P of brake pressure_i, carry out boosting for the pressure of each wheel cylinder, pressurize and the tune of three kinds of states of blood pressure lowering Joint；

Set the threshold value of pressure divergence as Δ P_th, only when deviation value is beyond this threshold value, just carry out control of boosting or reduce pressure System, is converted into electromagnetic valve action command and sends actuator to, and concrete judgement situation is as follows:

(1) as-Δ P_th＜ Δ P_i＜ Δ P_thPressurize regulates

(2) as Δ P_i＞ Δ P_thDecompression regulation

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

Additional front wheel angle is superposed with driver's go to action, the most comprehensively obtains front wheel angle.