CN106585425B - A kind of hierarchical system and control method for four hub motor driven electric vehicles - Google Patents

A kind of hierarchical system and control method for four hub motor driven electric vehicles Download PDF

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Publication number
CN106585425B
CN106585425B CN201611162392.7A CN201611162392A CN106585425B CN 106585425 B CN106585425 B CN 106585425B CN 201611162392 A CN201611162392 A CN 201611162392A CN 106585425 B CN106585425 B CN 106585425B
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hub motor
road
coefficient
motor
wheel
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CN201611162392.7A
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CN106585425A (en
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张政
赵宁
王俊晗
熊志强
远绍羊
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西安交通大学
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60LPROPULSION 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
    • B60L15/00Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/20Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60LPROPULSION 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
    • B60L2220/00Electrical machine types; Structures or applications thereof
    • B60L2220/40Electrical machine applications
    • B60L2220/42Electrical machine applications with use of more than one motor
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60LPROPULSION 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
    • B60L2220/00Electrical machine types; Structures or applications thereof
    • B60L2220/40Electrical machine applications
    • B60L2220/44Wheel Hub motors, i.e. integrated in the wheel hub
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60LPROPULSION 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
    • B60L2240/00Control parameters of input or output; Target parameters
    • B60L2240/10Vehicle control parameters
    • B60L2240/12Speed
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60LPROPULSION 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
    • B60L2240/00Control parameters of input or output; Target parameters
    • B60L2240/10Vehicle control parameters
    • B60L2240/24Steering angle
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60LPROPULSION 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
    • B60L2240/00Control parameters of input or output; Target parameters
    • B60L2240/40Drive Train control parameters
    • B60L2240/42Drive Train control parameters related to electric machines
    • B60L2240/423Torque
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00Road transport of goods or passengers
    • Y02T10/60Other road transportation technologies with climate change mitigation effect
    • Y02T10/72Electric energy management in electromobility

Abstract

The invention discloses a kind of hierarchical systems and control method for four hub motor driven electric vehicles, yaw moment is calculated according to vehicle speed sensor, steering wheel angle sensor, efp and Inertial Measurement Unit first, as yaw moment decision-making level;Further according to the limitation of maximum adhesion power, motor maximum output torque that automobile longitudinal force constraint, yaw moment constraint, road surface can be provided, the target torque of each hub motor is calculated, as objective optimization analysis layer;Finally, two parameters of attachment coefficient and wheel slip are input in coefficient of road adhesion ambiguous estimation controller with current road, it obtains and six kinds of standard road surface similarity degrees, the attachment coefficient estimated value of current road is obtained after being weighted and averaged, as coefficient of road adhesion monitor layer, the present invention is that control target improves the maneuverability, stability, economy of vehicle according to operating condition reasonable distribution motor torque with whole vehicle stability.

Description

A kind of hierarchical system and control method for four hub motor driven electric vehicles
Technical field
The invention belongs to electric car field of intelligent control technology, and in particular to one kind is electronic for four In-wheel motor drivings The hierarchical system and control method of automobile.
Background technique
In recent years, it is become increasingly conspicuous due to environmentally friendly, energy security two fold problem, electric car leaps to the view of people again It is wild.Since electric car uses efficient rechargeable battery, zero exhaust emissions can greatly reduce to environment in the process of running Pollution.Meanwhile four hub motor driven electric vehicle compared with traditional fuel power automobile, have following advantages: firstly, electricity The torque responsing speed of machine is 50-100 times of internal combustion engine, and can accurately control each wheel torque size and revolving speed.Secondly, eliminating The mechanisms such as transmission shaft, clutch alleviate the weight of vehicle and substantially increase transmission efficiency and course continuation mileage.Finally, four-wheel Hub motor driven electric car can integrate a variety of safety control technologies, such as steady program ESP (the Electric Stability of electronics Program), anti-lock braking system ABS (Anti-Lock Brake System), traction control system TCS (Traction Control System) etc..
Currently, the development of four hub motor driven electric vehicles is also more primary, the control method of application is mostly with transmission PID control (Proportional Integral derivative), logical threshold control etc..Its control effect is in general road conditions When can reach stability control requirement, but when four wheel hubs driving electric car is in the feelings such as steering, high speed or approach road be severe Under condition, our desired value is often not achieved in the effect of these control methods.Furthermore the safety control system of each dispersion is simultaneously When work, it also will appear the coupling effect between control system and reduce control effect.
Summary of the invention
The purpose of the present invention is to overcome the above shortcomings and to provide a kind of layerings for four hub motor driven electric vehicles System and control method, to improve vehicle maneuverability, stability and economy.
In order to achieve the above object, a kind of hierarchical system for four hub motor driven electric vehicles, including the first round Hub motor, the second hub motor, third hub motor and fourth round hub motor, first wheel motor, the second hub motor, third Hub motor and fourth round hub motor pass through corresponding first motor controller, the second electric machine controller, third motor control respectively Device processed and the 4th electric machine controller are connected, first motor controller, the second electric machine controller, third electric machine controller and the 4th electricity Machine controller is all connected with entire car controller, and entire car controller connects steering wheel angle sensor, efp, electric brake Pedal, Inertial Measurement Unit and vehicle speed sensor.
A kind of control method of the hierarchical system for four hub motor driven electric vehicles, comprising the following steps:
Step 1 combines two degrees of freedom vehicle by vehicle speed sensor, steering wheel angle sensor and efp Reference model obtain deviate ideal movements state yaw velocity and side slip angle difference, in conjunction with Inertial Measurement Unit into Row feedforward compensation and Optimal Feedback compensation obtain vehicle holding and stablize required yaw moment Mzd
Step 2, with yaw moment MzdFor input, joint considers automobile longitudinal force constraint, yaw moment constraint, road surface institute The limitation of the maximum adhesion power, motor maximum output torque that can provide carries out quadratic programming as target using stability and seeks optimal solution, The target torque for obtaining each hub motor is sent in each hub motor control device by CAN communication network, is realized and is stablized Property control;
Step 3 is input to road using two parameters of current road utilization service μ and wheel slip λ as input In the attachment coefficient ambiguous estimation controller of face, obtain and six kinds of standard road surface similarity degree ki, worked as after being weighted and averaged The attachment coefficient estimated value μ on preceding road surfacemax, then by coefficient of road adhesion estimated value μmaxBack to step 2 as next suboptimum Change the restrictive condition solved.
In the step 1, longitudinal vehicle velocity V is monitored by vehicle speed sensorxWith turning for steering wheel angle sensor acquisition Angle θ determines ideal side slip angle βdWith yaw velocity γd, calculation formula is as follows:
Wherein g is acceleration of gravity, and μ is coefficient of road adhesion, and K is stability factor, and L is front and back wheel base, and a is center of gravity To front axle distance, b is center of gravity to rear axle distance, k1For front axle cornering stiffness, k2For rear axle cornering stiffness, m is complete vehicle quality, Vx For longitudinal speed, δ is steering angle, and μ is coefficient of road adhesion;
The side slip angle β and yaw velocity γ detected at this time with Inertial Measurement Unit make the difference to obtain respectively Δ β and Δγ;
Δ β=β-βd
Δ γ=γ-γd
According to the size of side slip angle difference DELTA β and yaw velocity difference Δ γ, joint motor longitudinal direction vehicle velocity VxWith Rotational angle theta carries out feedforward compensation+Optimal Feedback compensation it can be concluded that yaw moment Mzd
In the step 2, quadratic programming is asked in optimal solution, and equality constraint matrix is as follows:
F in formulaxiFor the longitudinal force of each wheel, FxdFor the total longitudinal force demand of automobile, wheelspan of the d between two wheels;
Two inequality constraints of maximum moment that the maximum adhesion power and hub motor that road surface can be provided can be output are such as Under:
Wherein FyiFor the lateral force of each wheel, FziFor the vertical force of each wheel;
Wherein, TimaxFor the maximum moment that hub motor can be output, RwIt is tire radius;
Optimization aim is as follows:
Wherein Cx1, Cy1, Cx2, Cy2, Cx3, Cx4The weighting coefficient of respectively each wheel longitudinal force and lateral force distribution.
In the step 3, attachment coefficient estimated value μmaxCalculation formula it is as follows:
Compared with prior art, the present invention is first according to vehicle speed sensor, steering wheel angle sensor, efp Yaw moment is calculated with Inertial Measurement Unit, as yaw moment decision-making level;Further according to automobile longitudinal force constraint, yaw moment The limitation of maximum adhesion power, motor maximum output torque that constraint, road surface can be provided, calculates the target of each hub motor Torque, as objective optimization analysis layer;Finally, being input to two parameters of current road utilization service and wheel slip In coefficient of road adhesion ambiguous estimation controller, obtain with six kinds of standard road surface similarity degrees, worked as after being weighted and averaged The attachment coefficient estimated value on preceding road surface, as coefficient of road adhesion monitor layer, the present invention is control target, root with whole vehicle stability According to operating condition reasonable distribution motor torque, the maneuverability, stability, economy of vehicle are improved.
Detailed description of the invention
Fig. 1 is system structure diagram of the invention;
Fig. 2 is control flow chart of the invention;
Wherein, 1, first wheel motor;2, the second hub motor;3, third hub motor;4, fourth round hub motor;5, One electric machine controller;6, the second electric machine controller;7, third electric machine controller;8, the 4th electric machine controller;9, steering wheel angle Sensor;10, efp;11, electric brake pedal;12, Inertial Measurement Unit;13, vehicle speed sensor;14, vehicle Controller.
Specific embodiment
The present invention will be further described with reference to the accompanying drawing.
Referring to Fig. 1, a kind of hierarchical system for four hub motor driven electric vehicles includes first wheel motor 1, Two hub motors 2, third hub motor 3 and fourth round hub motor 4, first wheel motor 1, the second hub motor 2, third wheel hub Motor 3 and fourth round hub motor 4 pass through first motor controller 5, the second electric machine controller 6,7 and of third electric machine controller respectively 4th electric machine controller 8, first motor controller 5, the second electric machine controller 6, third electric machine controller 7 and the 4th motor control Device 8 is all connected with entire car controller 14, and entire car controller 14 connects steering wheel angle sensor 9, efp 10, electronics and stops Vehicle pedal 11, Inertial Measurement Unit 12 and vehicle speed sensor 13.
The angular signal that 13 collecting direction disk rotary angle transmitter 9 of entire car controller detects, efp 10 accelerate Signal, the reduce-speed sign of electric car brake pedal 11, the acceleration signal and angular velocity signal that Inertial Measurement Unit 12 detects, vehicle The speed signal that fast sensor 13 detects, after the target torque of internal hierarchical control algorithm four hub motors of calculating Distribution is sent to four electric machine controllers by CAN communication network 15 and realizes whole vehicle stability control, is collected simultaneously four motors The motor speed signal that controller returns is monitored into entire car controller according to underpavement attachment coefficient in hierarchical control algorithm Layer estimates current coefficient of road adhesion, the limit that then feedback to middle layer objective optimization Distribution Layer optimizes as subsequent time Condition processed.
As shown in Fig. 2, specific step is as follows for hierarchical control algorithm:
1) yaw moment decision-making level in upper layer mainly show that vehicle keeps yaw moment required for stability under current state, Its reference model is two degrees of freedom linear model.The longitudinal vehicle velocity V detected according to velocity sensor 13xIt is passed with steering wheel angle The steering angle sigma that sensor detects first calculates the yaw velocity and side slip angle of ideally vehicle.Wherein according to two It is as follows that free ideal model can obtain yaw velocity desired value calculation formula:
In formula
Wherein K is stability factor, and L is front and back wheel base, and a is center of gravity to front axle distance, and b is center of gravity to rear axle distance, k1For front axle cornering stiffness, k2For rear axle cornering stiffness, m is complete vehicle quality.
Since the yaw velocity of vehicle is also related to coefficient of road adhesion, maximum yaw velocity that road surface can be provided Calculation formula is as follows:
Wherein g is acceleration of gravity, and μ is coefficient of road adhesion.
The ideal yaw velocity after accomplishing can be obtained in conjunction with above two formula are as follows:
According to two degrees of freedom ideal model it can be concluded that the calculation formula of side slip angle is as follows:
The limitation of coefficient of road adhesion is considered simultaneously, and it is as follows that road surface can be provided maximum side slip angle calculation formula
β2=tan-1(0.02μg)
The modified computing formulae that yaw velocity can be obtained in conjunction with above two formula is as follows:
The yaw velocity γ and side slip angle β measured at this time according to Inertial Measurement Unit 12, does with ideal value respectively Difference can obtain Δ β and Δ γ:
Δ β=β-βd
Δ γ=γ-γd
Difference DELTA β, Δ γ, steering wheel angle δ and the automobile between this moment vehicle-state and perfect condition are indulged later To vehicle velocity VxIt is passed in feedforward+Optimal Feedback module to calculate and currently keeps stablizing required yaw moment, wherein feedforward section Divide compensation calculation as follows:
Automobile our available following state equations in steering procedure:
Wherein MzIt is the feedforward compensation yaw moment applied, A, B, E, X coefficient are as follows:
Wherein IzFor the rotary inertia of automobile about the z axis.
It can be obtained after carrying out Laplace transform to above formula:
Enable βd(s) and γd(s) yaw moment feedforward compensation coefficient G can be obtainedff:
According to yaw moment feedforward compensation coefficient, we can obtain feedforward compensation torque Mff:
Mff=Gffδ
Rear feed part calculates as follows:
Optimal controller is devised based on linear quadratic optimum control LQR (Linear Quadratic Regulator), Its objective function are as follows:
Wherein Q is positive semidefinite m*m rank symmetrical matrix, and R is positive definite r*r rank symmetrical matrix.According in optimal control theory Minimal principle, the optimum control amount of the problem are the linear combination of side slip angle and yaw velocity deviation, it may be assumed that
Mfb(t)=- Kx (t)
K is feedback factor matrix in above formula, is calculated as follows:
K=R-1BTP
And P therein is positive definite matrix, is the solution of following formula Riccati equation:
PA+ATP-PBR-1BP+Q=0
And Q therein is diagonal matrix,
Wherein q1 reflects the controlling extent to vehicle centroid lateral deviation angle error, and q2, which is reflected, misses yaw rate The controlling extent of difference, is arranged according to actual needs.
And performance indicator can be used to judge control amount to the tracking ability and jamproof performance of instruction.Joint is above each Formula evaluation index becomes:
Solving above formula finally can be obtained feedback factor k1、k2Yaw moment M is compensated with Optimal Feedbackfb
Mfb=-K*E=-k1Δβ-k2Δγ
Joint feed-forward compensates MffM is compensated with Optimal FeedbackfbIt may finally obtain total yaw moment Mzd:
Mzd=Mff+Mfb
2) middle layer optimizes Distribution Layer, mainly according to the dynamic property demand and durability requirements of vehicle, and considers road The limitation of the physical conditions such as face situation, the operating status of driving motor, carries out the distribution of driving force optimization, wherein according to vehicle It is as follows that equality constraint can be obtained in dynamics:
It can be obtained according to longitudinal force constraint:
Fx1+Fx2+Fx3+Fx4=Fxd
Wherein FxiFor the longitudinal force of each wheel, FxdFor total longitudinal force demand of automobile, yaw moment constraint condition is such as Under:
Wherein wheelspan of the d between two wheels indicates that above equation constraint can be as follows with matrix form:
It is as follows without equality constraint:
FyiFor the cross force of each wheel, FziFor the vertical force of each wheel, it is contemplated that different road surfaces can be provided to The adhesive force size of tire, there is following inequality constraints:
Simultaneously in view of the torque that hub motor executing agency can be output limits:
Wherein RwFor tire radius, TimaxFor the maximum moment that hub motor can be output, and optimize calculating when It waits, we are using whole vehicle stability as optimization aim, and specific implementation is to be up to target with tire stability margin, specific to count It is as follows to calculate formula:
And electric car is when turning to the left and to the right, the vertical load of inboard wheel can be less than outside, and front axle wheel hangs down It is less than rear-wheel to load.Joint motor friction circle theory can obtain, and an equal amount of load is allocated, the cross of the generation of four wheels Put that torque effect is not identical, therefore we improve objective function, increase weighting coefficient this, formula is as follows:
Wherein Cx1, Cy1, Cx2, Cy2, Cx3, Cx4The weighting coefficient of respectively each wheel longitudinal force and lateral force distribution.
If some motor breaks down simultaneously, its that corresponding distribution coefficient can also be changed to 0, so that it may carry out motor Drive force optimization distribution under malfunction.
It eventually passes through Novel Algorithm and calculates the torque for solving each hub motor, sent out by CAN communication network 15 It is sent in each hub motor control device, realizes each motor torque of reasonable distribution.
3) underpavement attachment coefficient monitor layer mainly estimates current coefficient of road adhesion, and input is cunning Shifting rate and road surface utilization service, wherein slip rate λ is calculated as follows:
Wherein wiFor the revolving speed of each wheel, led to by the data of each hub motor control device acquisition hub motor by CAN Communication network 15 returns in entire car controller 14, and VtiFor each wheel longitudinal velocity, specific formula for calculation is as follows:
And road surface utilization service μ calculation formula is as follows:
Coefficient of road adhesion is estimated, uses 6 kinds of common standard road surfaces as reference, and for standard road surface Relationship between slip rate and coefficient of road adhesion can be expressed from the next:
Wherein c1, c2, c3For fitting coefficient, and following two formula can calculate the optimal slip rate and peak on different road surfaces It is worth coefficient of road adhesion,
The 6 kinds of standard road surfaces chosen are dry pitch, dry cement, wet pitch, wet cobblestone, snow, ice tunnel road respectively, are intended The utilization service and optimal slip rate for closing available 6 kinds of standard road surfaces are as follows:
Road surface c1 c2 c3 λopt μmax
Dry pitch 1.2801 29.9900 0.5200 0.17 1.1700
Dry cement 1.1979 25.1680 0.5373 0.16 1.0900
Wet pitch 0.8570 33.8220 0.3470 0.13 0.8013
Wet cobblestone 0.4004 33.7080 0.1204 0.14 0.3800
Snow 0.1946 94.1290 0.0646 0.06 0.1900
Ice 0.0500 306.3900 0.0010 0.03 0.0500
And the subordinating degree function in fuzzy controller is designed as the mould of the two fuzzy domains of middle slippage rate and big slippage rate Subset is pasted to be blurred to the slippage rate of input.And fuzzy inference rule is devised, wherein DS represents dissmilarity, and NS is represented It is general similar, CS represent it is more similar, S represent it is similar, VS represent it is closely similar, wherein the formulation of specific fuzzy rule is as follows:
After fuzzy controller fuzzy reasoning and anti fuzzy method, we are available to the similar journey on 6 kinds of standard road surfaces Spend ki, it is weighted the averagely available estimation to current road attachment coefficient and optimal slippage rate, calculation formula is as follows:
After obtaining the attachment coefficient estimated value of current road, this estimated value is distributed back to middle layer objective optimization Layer, the restrictive condition as lower suboptimization.

Claims (4)

1. a kind of control method of the hierarchical system for four hub motor driven electric vehicles, which is characterized in that hierarchical system Including first wheel motor (1), the second hub motor (2), third hub motor (3) and fourth round hub motor (4), first wheel Motor (1), the second hub motor (2), third hub motor (3) and fourth round hub motor (4) are controlled by first motor respectively Device (5), the second electric machine controller (6), third electric machine controller (7) and the 4th electric machine controller (8), first motor controller (5), the second electric machine controller (6), third electric machine controller (7) and the 4th electric machine controller (8) are all connected with entire car controller (14), entire car controller (14) connection steering wheel angle sensor (9), efp (10), electric brake pedal (11), Inertial Measurement Unit (12) and vehicle speed sensor (13);
Control method the following steps are included:
Step 1, freely by vehicle speed sensor (13), steering wheel angle sensor (9) and efp (10) simultaneous two Degree vehicle reference model obtains the yaw velocity and side slip angle difference that deviate ideal movements state, in conjunction with inertia measurement Unit (12) carries out feedforward compensation and Optimal Feedback compensation, obtains vehicle holding and stablizes required yaw moment Mzd
Step 2, with yaw moment MzdFor input, joint considers that automobile longitudinal force constraint, yaw moment constraint, road surface can mention The limitation of the maximum adhesion power, motor maximum output torque of confession carries out quadratic programming as target using stability and seeks optimal solution, obtains The target torque of each hub motor is sent in each hub motor control device by CAN communication network (15), is realized and is stablized Property control;
It is attached to be input to road surface using two parameters of current road utilization service μ and wheel slip λ as input for step 3 In coefficient ambiguous estimation controller, obtain and six kinds of standard road surface similarity degree ki, current road is obtained after being weighted and averaged The attachment coefficient estimated value μ in facemax, then by coefficient of road adhesion estimated value μmaxIt is asked back to step 2 as next suboptimization The restrictive condition of solution.
2. a kind of control method of hierarchical system for four hub motor driven electric vehicles according to claim 1, It is characterized in that, monitoring longitudinal vehicle velocity V by vehicle speed sensor (13) in the step 1xAnd steering wheel angle sensor (9) rotational angle theta acquired determines ideal side slip angle βdWith yaw velocity γd, calculation formula is as follows:
Wherein g is acceleration of gravity, and μ is coefficient of road adhesion, and K is stability factor, and L is front and back wheel base, and a is before center of gravity arrives Wheelbase is from b is center of gravity to rear axle distance, k1For front axle cornering stiffness, k2For rear axle cornering stiffness, m is complete vehicle quality, VxIt is vertical To speed, δ is steering angle, and μ is coefficient of road adhesion;
The side slip angle β and yaw velocity γ detected at this time with Inertial Measurement Unit (12) make the difference to obtain respectively Δ β and Δγ;
Δ β=β-βd
Δ γ=γ-γd
According to the size of side slip angle difference DELTA β and yaw velocity difference Δ γ, joint motor longitudinal direction vehicle velocity VxAnd rotational angle theta Feedforward compensation+Optimal Feedback compensation is carried out it can be concluded that yaw moment Mzd
3. a kind of control method of hierarchical system for four hub motor driven electric vehicles according to claim 1, It is characterized in that, quadratic programming is asked in optimal solution in the step 2, equality constraint matrix is as follows:
F in formulaxiFor the longitudinal force of each wheel, FxdFor the total longitudinal force demand of automobile, wheelspan of the d between two wheels;
Two inequality constraints of maximum moment that the maximum adhesion power and hub motor that road surface can be provided can be output are as follows:
Wherein FyiFor the lateral force of each wheel, FziFor the vertical force of each wheel;
Wherein, TimaxFor the maximum moment that hub motor can be output, RwIt is tire radius;
Optimization aim is as follows:
Wherein Cx1, Cy1, Cx2, Cy2, Cx3, Cx4The weighting coefficient of respectively each wheel longitudinal force and lateral force distribution.
4. a kind of control method of hierarchical system for four hub motor driven electric vehicles according to claim 1, It is characterized in that, in the step 3, attachment coefficient estimated value μmaxCalculation formula it is as follows:
CN201611162392.7A 2016-12-15 2016-12-15 A kind of hierarchical system and control method for four hub motor driven electric vehicles CN106585425B (en)

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