CN106184207B - Four motorized wheels electric vehicle adaptive cruise control system Torque distribution method - Google Patents

Four motorized wheels electric vehicle adaptive cruise control system Torque distribution method Download PDF

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CN106184207B
CN106184207B CN201610548104.5A CN201610548104A CN106184207B CN 106184207 B CN106184207 B CN 106184207B CN 201610548104 A CN201610548104 A CN 201610548104A CN 106184207 B CN106184207 B CN 106184207B
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control system
moment
adaptive cruise
electric vehicle
acceleration
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CN106184207A (en
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郭烈
林肖
乔彦夫
岳明
李琳辉
杨彪
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Dalian University of Technology
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Dalian University of Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/14—Adaptive cruise control
    • B60W30/16—Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/32—Control or regulation of multiple-unit electrically-propelled vehicles
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
    • 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
    • B60W40/107—Longitudinal acceleration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/42—Drive Train control parameters related to electric machines
    • B60L2240/423—Torque
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/48—Control modes by fuzzy logic
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • B60W2050/0003—In analogue systems, e.g. continuous systems
    • 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • 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
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/08—Electric propulsion units
    • B60W2710/083—Torque

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  • Engineering & Computer Science (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Power Engineering (AREA)
  • Feedback Control In General (AREA)
  • Arrangement And Driving Of Transmission Devices (AREA)

Abstract

The invention discloses a kind of four motorized wheels electric vehicle adaptive cruise control system Torque distribution methods, desired acceleration is calculated by top level control method to instruct and be input in lower coating control method, the desired acceleration instruction that lower coating control method is calculated according to top level control method calculates ideal driving force square and distributes torque to four wheels, solves the problems, such as that traditional adaptive cruise control system can not directly apply to four motorized wheels electric vehicle.Top level control method uses the Model Predictive Control of soft and smooth constraint, improves the practicability of adaptive cruise control system, meets the requirement of safety needed for driver, comfort and economy.Lower coating control method obtains preferable longitudinal moment using fuzzy control and distributes torque to four wheels according to vertical load size, while four motorized wheels electric powered motor is ensured, the robustness and practicability of four motorized wheels electric vehicle adaptive cruise control system are improved.

Description

Four motorized wheels electric vehicle adaptive cruise control system Torque distribution method
Technical field
The invention belongs to safety assistant drivings and field of intelligent control, and it is adaptive to be related to four motorized wheels electric vehicle The design method of cruise system is related specifically to the Torque distribution of four motorized wheels electric vehicle adaptive cruise control system Method.
Background technology
Increasingly serious with energy problem, the development of electric vehicle has been to be concerned by more and more people.Four-wheel independently drives Dynamic electric vehicle refers to four motors being separately mounted to automobile near four hub interiors or wheel, with orthodox car phase Than four motorized wheels electric vehicle has very big technical advantage：Four motors can independent control, and the response speed pole of motor Soon, therefore for this special drive form of four motorized wheels electric vehicle, increasingly complex control method is used, Easily realize the intelligence of automobile.
The adaptive cruise of automobile is that speed is controlled based on cruise, further realizes the assurance adjusted the distance. Constant speed cruising system is travelled according to the speed that driver sets, and adaptive cruise is in addition to that can make automobile reach preset vehicle It is fast outer, automobile can also be made to keep preset following distance, and automatically control the speed of automobile according to the variation of spacing.Both at home and abroad The research of adaptive cruise control system is concentrated mainly in traditional vehicle, reaches regulation speed by adjusting throttle opening With the purpose of spacing.Orthodox car is concentrated mainly on to the research of adaptive cruise control system at present, can not be directly applied to Four motorized wheels electric vehicle, therefore develop a set of suitable for four motorized wheels electric vehicle adaptive learning algorithms system Torque distribution method of uniting is necessary.In addition to this, the orthodox car designed for the method using Model Predictive Control Adaptive cruise control system, constraints is usually " hard constraint ", in Model Predictive Control problem, due to depositing for constraint , it is understood that there may be the problem of can not find feasible solution.In this case if still taking " hard constraint ", Model Predictive Control The solution being obtained may deteriorate control effect far beyond the boundary of constraints, this causes the adaptive learning algorithms of design The practicability of system is restricted, and demand of the driver to safety, comfort and economy is not achieved.
Invention content
To solve the above problem of the existing technology, it is adaptive that the present invention will design a kind of four motorized wheels electric vehicle Cruise control system Torque distribution method is answered, can solve traditional adaptive cruise control system can not directly apply to four-wheel The problem of independent driving electric vehicle, and the practicability of adaptive learning algorithms device can be improved, meet the safety needed for driver The requirement of property, comfort and economy.
In order to achieve the above object, technical scheme is as follows：A kind of four motorized wheels electric vehicle is adaptive Cruise control system Torque distribution method including top level control method and lower coating control method, is calculated by top level control method Desired acceleration is instructed and is input in lower coating control method, and lower coating control method adds according to the ideal that top level control method calculates Speed command calculates ideal driving force square and distributes torque to four wheels；It is as follows：
A, top level control method calculates the desired acceleration of this vehicle
According to the preferable longitudinal acceleration of this vehicle of the state of this vehicle and the state computation of front truck, pass through procedure below reality It is existing：
A1, twisting movement characteristic model between this vehicle and front truck is established
According to the twisting movement characteristic between this vehicle of adaptive cruise control system and front truck, obtain as follows from Dissipate kinematical equation：
vrel(k+1)=vrel(k)+ap(k)*Ts-a(k)*Ts
V (k+1)=v (k)+a (k) * Ts
Wherein, the spacing of carving copy vehicle and front truck when Δ x (k) is kth, vrel(k) for kth when between carving copy vehicle and front truck Relative velocity, ap(k) it is the acceleration of kth moment front truck, the acceleration of carving copy vehicle when a (k) is kth, u (k) is engraved when being kth The desired acceleration order of coating control method, the time constant of the lower coating control method of τ characterizations, TsIt is electronic to characterize four motorized wheels Automotive self-adaptive cruise control system sampling time, the change rate of carving copy vehicle acceleration when j (k) is kth；
With Ben Che and separation delta x, this vehicle speed v of front truck, the relative velocity v between Ben Che and front truckrel, this vehicle accelerate A and Ben Che rate of acceleration change j is spent as four motorized wheels electric vehicle adaptive cruise control system state variable, by before Vehicle acceleration obtains phase between Ben Che and front truck as four motorized wheels electric vehicle adaptive cruise control system disturbance quantity Mutual longitudinal movement characteristic model：
X (k+1)=Ax (k)+Bu (k)+Gw (k)
Wherein
X (k)=[Δ x (k), v (k), vrel(k),a(k),j(k)]T,
A2, state equation is established
The design of four motorized wheels electric vehicle adaptive cruise control system needs to meet safety and with vehicle Basic object, while for the top level control method of adaptive cruise control system that play driver role, take and relax Adaptive and economy are also its important evaluation index.Therefore, this vehicle and interval error δ, Ben Che of front truck and the phase of front truck are chosen To speed vrel, this vehicle acceleration a and Ben Che rate of acceleration change j performance indicators as an optimization, four motorized wheels electric vehicle The output equation of adaptive cruise control system is as follows：
Y (k)=Cx (k)-Z
Wherein
thCharacterize time headway value, doCharacterize the most spacing of small capital vehicle and front truck.
Finally formed state equation is as follows：
A3, predictive equation is established
According to kinematics characteristic model mutual between this vehicle and front truck established, to the x (k) of each step in prediction time domain =[Δ x (k), v (k), vrel(k),a(k),j(k)]T, y (k)=[δ (k), vrel(k),a(k),j(k)]TIt is predicted：
Wherein
Wherein, p is prediction time domain, c time domains in order to control,For At the kth moment to the four motorized wheels electric vehicle adaptive cruise control system state variable of each step in prediction time domain Predicted value,For at the kth moment to each step in prediction time domain Output quantity y (k)=[δ (k), vrel(k),a(k),j(k)]TPredicted value, u (k), u (k+1) ..., u (k+c-1) waits to ask Control variable, w (k), w (k+1) ..., w (k+p) be the kth moment predict time domain in each step disturbance quantity, i.e. front truck acceleration Degree, x (k) are the four motorized wheels electric vehicle adaptive cruise control system state variable at kth moment,For At -1 moment of kth to the predicted value of kth moment four motorized wheels electric vehicle adaptive cruise control system state variable, ex (k) it is the k moment actually detected four motorized wheels electric vehicle adaptive cruise control system state variable arrived and k-1 moment The difference of the four motorized wheels electric vehicle adaptive cruise control system state variable of prediction, prediction matrixIt is shown below：
At the kth moment, the disturbance quantity w (k) at current time can not be obtained, it is assumed that the disturbance quantity at -1 moment of kth and kth moment Value it is equal, and assume entirely prediction time domain in remain unchanged, then the kth moment and its prediction time domain in disturbance quantity estimation Calculation formula is as follows：
W (k+i)=w (k), (i=1,2 ... p-1)
WhereinFor the estimated value at the kth moment to -1 time of kth disturbance quantity.
A4, calculating target function
By the optimality criterion in four motorized wheels electric vehicle adaptive cruise control system driving process with mesh The form of scalar functions provides.The object function includes object function first item and object function Section 2, convenient for writing, Below willIt is written asU (k+c) is written as Uc；
A41, calculating target function first item
Using model predictive control method, the first control targe is：Predict output valve and with reference to the difference between output valve Value minimizes；The control targe is write as to the form of minimum two norms：
Cast out the useless item ρ not acted to optimization problem1, obtain object function first item:
Wherein
Represent the matrix of the reference output composition of each step in prediction time domain,
Fa=diag [fa1,fa2,fa3,fa4] represent to predict the reference output matrix of the first step in time domain, fa1、fa2、 fa3、fa4For damped expoential, fa is taken1=fa2=fa3=fa4=0.94.
Represent the matrix of each step output weight matrix composition in prediction time domain, q=diag [q1, q2,q3,q4] represent the weight matrix of each output, q1、q2、q3、q4For four weight coefficients.
A42, calculating target function Section 2
In order to reduce the variable quantity of each step control output so that control signal intensity is gentle, by the variable quantity of input quantity As the second control targe as, which is write to the form of minimum two norms：
Wherein s represents the weight matrix of input variable quantity, because the dimension of input variable is 1, therefore takes s=1.
Cast out the useless item ρ not acted to optimization problem2, obtain object function Section 2：
A5, design constraint
The constraints of design includes following three：
A51, the first constraints
In Model Predictive Control problem, it is necessary to fully consider four motorized wheels electric vehicle adaptive learning algorithms system The physical condition limitation of system.Wherein the maximum value of input quantity and minimum value are most common constraints in Model Predictive Control problem. If the constraint that the bound of input quantity is formed is shown below：
That is Umin≤Uc≤Umax, wherein uminFor the minimum value of input quantity, umaxMaximum value for input quantity.
A52, the second constraints
It is limited to physical condition, the variable quantity of the input quantity between each step is unlikely to be infinitely great, the change of input quantity Change amount has boundary, is represented with the following formula：
Obtaining the second constraints is：
Wherein Δ uminRepresent the minimum value of input quantity variable quantity, Δ umaxRepresent the maximum value of input quantity variable quantity.
A53, third constraints
In order to reach preferable control targe so that the output of four motorized wheels electric vehicle adaptive cruise control system Value meets the needs of control targe, separation delta x, relative velocity v to Ben Che and front truckrel, this vehicle acceleration a and Ben Che accelerate Degree change rate j is constrained, definition vector χ=[Δ x, v, a, j]T, the χ of each step in prediction space is constrained, is used The following formula represents：
I.e.
Wherein
χmin、χmaxThe minimum value and maximum value of χ is represented respectively
The obtained predictive equations of step A3 are updated to inequality above, are obtained：
Therefore third constraints is
A6, constraint softening
Object function after A61, constraint softening
Soften constraint by way of adding in penalty item in object function.Increased penalty item such as following formula institute Show：
WhereinRepresent the slack of the input quantity of the i-th step.Represent the weight matrix of the slack of each step, η (k+i) the accurate penalty factor of the slack of the i-th step is represented.
After increasing the optimization item, the more Ψ of the optimized variable of former optimization problem, therefore new optimized variable is：
New optimization problem becomes：
Constraints after A62, constraint softening
After constraining softening, due to introducing new optimized variable, three constraintss in former optimization problem will Make corresponding change.
A621, the first constraints
I.e.
A622, the second constraints
I.e.
A623, third constraints
ConstraintIt is write as：
ConstraintIt is write as：
Two constraints of simultaneous obtains：
Therefore third constraints becomes：
Formed final optimization problem be：
The optimization problem is the quadratic programming problem of typicalness, is solved by active set m ethod.The quadratic programming problem Solve first elementAs desired acceleration controlled quentity controlled variable.
B, lower coating control method calculates ideal driving force square/braking moment
Lower coating control method calculates desired acceleration controlled quentity controlled variable according to top level control method, calculates ideal driving force Square/braking moment, and the torque is reasonably assigned to four wheels, it is realized by procedure below：
B1, ideal driving force square/braking moment is calculated
Ideal driving force square/braking moment is obtained using fuzzy control method, the longitudinal dynamics equation of automobile is：
Ma=Fd-Fr
Gross masses of the wherein M for automobile, acceleration of a for automobile, FdRepresent the driving force or brake force of automobile, FrIt represents Resistance suffered by automobile.
In actual conditions, roughness, the gradient and the air drag on ground are difficult to measure, and are hardly resulted in suffered by automobile The exact value of resistance, selection obtain ideal driving force square/braking moment by the way of fuzzy control.
If the input of fuzzy control method is the desired acceleration of top level control method calculating and the difference e of actual acceleration (t) and the change rate de (t) of difference, output quantity are driving force or brake force Fd, seven are defined on its respectively domain Fuzzy subset：Negative big (NB), it is negative in (NM), bear small (NS), zero (Z), just small (PS), center (PM), honest (PB)；
Designed fuzzy control rule is as follows：
Final ideal driving force square/braking moment calculates as follows：
Td=Fd·r
Wherein TdFor ideal driving force square/braking moment, r is the effective rolling radius of wheel.
B2, distribution torque
In order to improve the driving force of four motorized wheels electric vehicle, the size of the vertical load according to suffered by with wheel Carry out Torque distribution：
Wherein, T1、T2、T3And T4To be finally allocated to the driving/braking power of the near front wheel, off-front wheel, left rear wheel and off hind wheel Square, Fz1、Fz2、Fz3And Fz4To act on the near front wheel, off-front wheel, left rear wheel and the vertical load of off hind wheel, FzIt represents suffered by automobile The total vertical load arrived.
Compared with prior art, the invention has the advantages that：
1st, the present invention devises a kind of four motorized wheels electric vehicle adaptive cruise control system Torque distribution method, Including top level control method and lower coating control method, desired acceleration is calculated by top level control method and instructs and is input to lower floor In control method, the desired acceleration instruction that lower coating control method is calculated according to top level control method calculates ideal driving force square simultaneously Torque is distributed to four wheels.This method that the present invention designs be according to the design feature of four motorized wheels electric vehicle into Row design, asking for four motorized wheels electric vehicle can not be directly applied to by solving traditional adaptive cruise control system Topic.
2nd, the top level control method that designs of the present invention uses the Model Predictive Control of soft and smooth constraint, chooses this vehicle and front truck Interval error, the relative velocity of Ben Che and front truck, this vehicle acceleration and Ben Che rate of acceleration change performance indicator as an optimization, choosing Take spacing, relative velocity, this vehicle acceleration and the Ben Che acceleration changes of input quantity, the variable quantity of input quantity, Ben Che and front truck Rate has carried out softening as constraints and to them, improves the practicability of adaptive cruise control system, meets driving The requirement of safety, comfort and economy needed for member.
3rd, the lower coating control method that the present invention designs obtains preferable longitudinal moment and according to vertical load using fuzzy control Size distributes torque to four wheels so that four wheel co-ordinations are moved in guarantee four motorized wheels electric vehicle While power, the robustness and practicability of four motorized wheels electric vehicle adaptive cruise control system are improved.
Description of the drawings
Fig. 1 is the flow diagram of the present invention.
Specific embodiment
The specific embodiment of the present invention is implemented according to the step in flow shown in FIG. 1 and invention content.The present invention The present embodiment is not limited to, any equivalent concepts or change in the technical scope of present disclosure are classified as the present invention Protection domain.

Claims (1)

  1. A kind of 1. four motorized wheels electric vehicle adaptive cruise control system Torque distribution method, it is characterised in that：Including Top level control method and lower coating control method calculate desired acceleration by top level control method and instruct and be input to lower floor's control In method, the desired acceleration instruction that lower coating control method is calculated according to top level control method calculates ideal driving force square and distributes Torque is to four wheels；It is as follows：
    A, top level control method calculates the desired acceleration of this vehicle
    According to the preferable longitudinal acceleration of this vehicle of the state of this vehicle and the state computation of front truck, realized by procedure below：
    A1, twisting movement characteristic model between this vehicle and front truck is established
    According to the twisting movement characteristic between this vehicle of adaptive cruise control system and front truck, following discrete fortune is obtained It is dynamic to learn equation：
    vrel(k+1)=vrel(k)+ap(k)*Ts-a(k)*Ts
    V (k+1)=v (k)+a (k) * Ts
    Wherein, the spacing of carving copy vehicle and front truck when Δ x (k) is kth, vrel(k) for kth it is opposite between carving copy vehicle and front truck when Speed, ap(k) it is the acceleration of kth moment front truck, the acceleration of carving copy vehicle when a (k) is kth, u (k) is the upper strata control of kth moment The desired acceleration order of method processed, the time constant of the lower coating control method of τ characterizations, TsCharacterize four motorized wheels electric vehicle Adaptive cruise control system sampling time, the change rate of carving copy vehicle acceleration when j (k) is kth；Carving copy vehicle when v (k) is kth Speed；W (k) is the front truck acceleration perturbation motion estimator at kth moment.
    With Ben Che and separation delta x, this vehicle speed v of front truck, the relative velocity v between Ben Che and front truckrel, this vehicle acceleration a and This vehicle rate of acceleration change j as four motorized wheels electric vehicle adaptive cruise control system state variable, by front truck plus Speed obtains mutually vertical between Ben Che and front truck as four motorized wheels electric vehicle adaptive cruise control system disturbance quantity To kinematics characteristic model：
    X (k+1)=Ax (k)+Bu (k)+Gw (k)
    Wherein
    X (k)=[Δ x (k), v (k), vrel(k),a(k),j(k)]T,
    A2, state equation is established
    The design of four motorized wheels electric vehicle adaptive cruise control system needs to meet safety and with the basic of vehicle Purpose, while for the top level control method of adaptive cruise control system that play driver role, riding comfort With economy and its important evaluation index；Therefore, interval error δ, Ben Che of this vehicle and front truck and the speed relatively of front truck are chosen Spend vrel, performance indicator, four motorized wheels electric vehicle are adaptive as an optimization by this vehicle acceleration a and Ben Che rate of acceleration change j The output equation for answering cruise control system is as follows：
    Y (k)=Cx (k)-Z
    Wherein
    thCharacterize time headway value, doCharacterize the most spacing of small capital vehicle and front truck；
    Finally formed state equation is as follows：
    A3, predictive equation is established
    According to mutual kinematics characteristic model between this vehicle and front truck established, to the x (k) of each step in prediction time domain= [Δx(k),v(k),vrel(k),a(k),j(k)]T, y (k)=[δ (k), vrel(k),a(k),j(k)]TIt is predicted：
    Wherein
    Wherein, p is prediction time domain, c time domains in order to control,For in kth Prediction of the moment to the four motorized wheels electric vehicle adaptive cruise control system state variable of each step in prediction time domain Value,For in output of the kth moment to each step in prediction time domain Measure y (k)=[δ (k), vrel(k),a(k),j(k)]TPredicted value, u (k), u (k+1) ..., u (k+c-1) be control to be asked Variable, w (k), w (k+1) ..., w (k+p) be the kth moment predict time domain in each step disturbance quantity, i.e. front truck acceleration, x (k) it is the four motorized wheels electric vehicle adaptive cruise control system state variable at kth moment,For The k-1 moment is to the predicted value of kth moment four motorized wheels electric vehicle adaptive cruise control system state variable, ex(k) It is pre- for the k moment actually detected four motorized wheels electric vehicle adaptive cruise control system state variable arrived and k-1 moment The difference of the four motorized wheels electric vehicle adaptive cruise control system state variable of survey, prediction matrixIt is shown below：
    At the kth moment, the disturbance quantity w (k) at current time can not be obtained, it is assumed that the disturbance quantity at -1 moment of kth and the value at kth moment It is equal, and assume to remain unchanged in entirely prediction time domain, then the estimation of kth moment and its disturbance quantity in prediction time domain calculates Formula is as follows：
    W (k+i)=w (k), (i=1,2 ... p-1)
    WhereinFor the estimated value at the kth moment to -1 time of kth disturbance quantity；Carving copy vehicle and front truck when δ (k) is kth Practical following distance and the interval error for it is expected following distance；A, B, G, C, Z are matrix, defined in step A1 and A2, H 5 × 1 unit matrix, is defined as follows：
    A4, calculating target function
    By the optimality criterion in four motorized wheels electric vehicle adaptive cruise control system driving process with target letter Several forms provide；The object function includes object function first item and object function Section 2, convenient for writing, below It willIt is written asU (k+c) is written as Uc；
    A41, calculating target function first item
    Using model predictive control method, the first control targe is：Difference between prediction output valve and reference output valve is most Smallization；The control targe is write as to the form of minimum two norms：
    Cast out the useless item ρ not acted to optimization problem1, obtain object function first item:
    Wherein
    Represent the matrix of the reference output composition of each step in prediction time domain, fa=diag [fa1,fa2,fa3, fa4] represent to predict the reference output matrix of the first step in time domain, fa1、fa2、fa3、fa4For damped expoential, fa is taken1=fa2=fa3 =fa4=0.94；Represent the matrix of each step output weight matrix composition in prediction time domain, q=diag [q1,q2,q3,q4] represent the weight matrix of each output, q1、q2、q3、q4For four weight coefficients；JyFor with prediction output valve with The object function represented with reference to the difference between output valve；H1Matrix isProduct expression,Determine in step A3 Justice；g1Matrix isProduct expression,It is defined in step A3；
    H2Matrix is speciallyWherein s is input variation moment matrix；
    g2Matrix is speciallyWherein s input variation moment matrixs, u (k-1) is control acceleration to be asked；
    UcMatrix is speciallyU (k), u (k+1) ..., u (k+c-1) is control variable to be asked；
    A42, calculating target function Section 2
    In order to reduce the variable quantity of each step control output so that control signal intensity is gentle, using the variable quantity of input quantity as The control targe is write as the form of minimum two norms by the second control targe：
    Wherein s represents the weight matrix of input variable quantity, because the dimension of input variable is 1, therefore takes s=1；
    Cast out the useless item ρ not acted to optimization problem2, obtain object function Section 2：
    A5, design constraint
    The constraints of design includes following three：
    A51, the first constraints
    In Model Predictive Control problem, it is necessary to fully consider four motorized wheels electric vehicle adaptive cruise control system Physical condition limits；Wherein the maximum value of input quantity and minimum value are most common constraints in Model Predictive Control problem；It is if defeated Enter the constraint that the bound of amount is formed to be shown below：
    That is Umin≤Uc≤Umax, wherein uminFor the minimum value of input quantity, umaxMaximum value for input quantity；
    A52, the second constraints
    It is limited to physical condition, the variable quantity of the input quantity between each step is unlikely to be infinitely great, the variable quantity of input quantity There is boundary, represented with the following formula：
    Obtaining the second constraints is：
    Wherein Δ uminRepresent the minimum value of input quantity variable quantity, Δ umaxRepresent the maximum value of input quantity variable quantity；
    A53, third constraints
    In order to reach preferable control targe so that the output valve of four motorized wheels electric vehicle adaptive cruise control system expires The demand of sufficient control targe, separation delta x, relative velocity v to Ben Che and front truckrel, this vehicle acceleration a and Ben Che acceleration become Rate j is constrained, definition vector χ=[Δ x, v, a, j]T, the χ of each step in prediction space is constrained, use is following Formula represents：
    I.e.
    Wherein
    χmin、χmaxThe minimum value and maximum value of χ is represented respectively
    The obtained predictive equations of step A3 are updated to inequality above, are obtained：
    Therefore third constraints is
    Metzler matrix is speciallyWherein χminFor χ minimum values, χ is defined in step A53, χ=[Δ x, v, a, j]T。
    N matrix is speciallyWherein χmaxFor χ maximum values；
    Φ1It is embodied asProduct expression formula, whereinW(k+p)、ex(k) Defined in A3, x (k) is defined in step A1
    A6, constraint softening
    Object function after A61, constraint softening
    Soften constraint by way of adding in penalty item in object function；Increased penalty item is shown below：
    WhereinRepresent the slack of the input quantity of the i-th step；Represent the weight matrix of the slack of each step, η (k+i) Represent the accurate penalty factor of the slack of the i-th step；
    After increasing the optimization item, the more Ψ of the optimized variable of former optimization problem, therefore new optimized variable is：
    New optimization problem becomes：
    Constraints after A62, constraint softening
    After constraining softening, due to introducing new optimized variable, three constraintss in former optimization problem will be made It is corresponding to change；
    A621, the first constraints
    I.e.
    A622, the second constraints
    I.e.
    A623, third constraints
    ConstraintIt is write as：
    ConstraintIt is write as：
    Two constraints of simultaneous obtains：
    Therefore third constraints becomes：
    Formed final optimization problem be：
    The optimization problem is the quadratic programming problem of typicalness, is solved by active set m ethod；The solution of the quadratic programming problem Obtain first elementAs desired acceleration controlled quentity controlled variable；
    B, lower coating control method calculates ideal driving force square/braking moment
    Lower coating control method calculates desired acceleration controlled quentity controlled variable according to top level control method, calculates ideal driving force square/system Kinetic moment, and the torque is reasonably assigned to four wheels, it is realized by procedure below：
    B1, ideal driving force square/braking moment is calculated
    Ideal driving force square/braking moment is obtained using fuzzy control method, the longitudinal dynamics equation of automobile is：
    Ma=Fd-Fr
    Gross masses of the wherein M for automobile, acceleration of a for automobile, FdRepresent the driving force or brake force of automobile, FrRepresent automobile Suffered resistance；
    In actual conditions, roughness, the gradient and the air drag on ground are difficult to measure, and hardly result in the resistance suffered by automobile Exact value, selection ideal driving force square/braking moment is obtained by the way of fuzzy control；
    If the input of fuzzy control method is the desired acceleration of top level control method calculating and the difference e (t) of actual acceleration And the change rate de (t) of difference, output quantity are driving force or brake force Fd, seven are defined on its respectively domain and is obscured Subset：Negative big (NB), it is negative in (NM), bear small (NS), zero (Z), just small (PS), center (PM), honest (PB)；
    Designed fuzzy control rule is as follows：
    Final ideal driving force square/braking moment calculates as follows：
    Td=Fd · r
    Wherein TdFor ideal driving force square/braking moment, r is the effective rolling radius of wheel；
    B2, distribution torque
    In order to improve the driving force of four motorized wheels electric vehicle, the size of the vertical load according to suffered by with wheel carries out Torque distribution：
    Wherein, T1、T2、T3And T4To be finally allocated to the driving/braking torque of the near front wheel, off-front wheel, left rear wheel and off hind wheel, Fz1、Fz2、Fz3And Fz4To act on the near front wheel, off-front wheel, left rear wheel and the vertical load of off hind wheel, FzIt represents suffered by automobile Total vertical load.
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