CN109291932A - Electric car Yaw stability real-time control apparatus and method based on feedback - Google Patents
Electric car Yaw stability real-time control apparatus and method based on feedback Download PDFInfo
- Publication number
- CN109291932A CN109291932A CN201811201424.9A CN201811201424A CN109291932A CN 109291932 A CN109291932 A CN 109291932A CN 201811201424 A CN201811201424 A CN 201811201424A CN 109291932 A CN109291932 A CN 109291932A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- wheel
- stability
- yaw moment
- yaw
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 230000033001 locomotion Effects 0.000 claims abstract description 21
- 230000001133 acceleration Effects 0.000 claims description 9
- 230000008569 process Effects 0.000 abstract description 3
- 230000005484 gravity Effects 0.000 description 9
- 238000005457 optimization Methods 0.000 description 7
- 238000004364 calculation method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 238000013461 design Methods 0.000 description 4
- 238000005096 rolling process Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000006641 stabilisation Effects 0.000 description 2
- 238000011105 stabilization Methods 0.000 description 2
- SAZUGELZHZOXHB-UHFFFAOYSA-N acecarbromal Chemical compound CCC(Br)(CC)C(=O)NC(=O)NC(C)=O SAZUGELZHZOXHB-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 101150036841 minJ gene Proteins 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
Classifications
-
- 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
-
- 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
- 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
- B60W30/02—Control of vehicle driving stability
-
- 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
- B60W40/105—Speed
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- 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
- B60W40/112—Roll movement
-
- 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
-
- 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
- B60W2050/0019—Control system elements or transfer functions
- B60W2050/0028—Mathematical models, e.g. for simulation
- B60W2050/0031—Mathematical model of the vehicle
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/12—Lateral speed
- B60W2520/125—Lateral acceleration
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/28—Wheel speed
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/18—Steering angle
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Human Computer Interaction (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
- Steering Control In Accordance With Driving Conditions (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
Abstract
The invention discloses a kind of electric car Yaw stability real-time control apparatus and method based on feedback, device includes upper controller and lower layer's controller, and upper controller is equipped with three sensor unit, model predictive controller and direct yaw moment computing unit parts；Lower layer's controller, which is equipped with, judges two parts of decision package and direct yaw moment execution unit, and direct yaw moment execution unit controls the driving moment of target wheel.This method uses heterarchical architecture, required signal is provided by sensor, using measurable amount, upper controller is designed using sensor Real-time Feedback and Model Predictive Control Algorithm, calculates and keeps direct yaw moment required for Yaw stability in vehicle motion process.The direct yaw moment instruction that lower layer's controller guarantees that upper controller issues is achieved by the distribution of driving moment, is guaranteed that vehicle may be implemented to stablize traveling under different operating conditions, is improved the Yaw stability of electric car.
Description
Technical field
The present invention relates to electric car and its stability control technical fields, specially based on the distribution of sensor feedback
Drive electric car Yaw stability real-time control method more particularly to a kind of electric car Yaw stability based on feedback real
When control device and method.
Background technique
In today that energy shortages is increasingly sharpened, environmental pollution is got worse, the development trend of the times of electric car.Distribution
Formula driving electric car has four independent hub motors, meanwhile, motor fast response time, the parameters such as torque and revolving speed are held
Easily obtain.Therefore, can driving moment directly to each wheel carry out independent accurate control to improve electric car severe
Driving performance under pavement conditions.
Vehicular yaw stability contorting is extremely important for distributed-driving electric automobile, and effect is mainly to guarantee vehicle
Stability and controllability in turning, braking and driving, assist driver to control vehicle in extreme manoeuvre, prevent vehicle
There is excessive or understeer.
For distributed-driving electric automobile Yaw stability control problem, domestic and foreign scholars propose various control side
Method, including torque distribution, β method, differential torque distribution method etc. based on wheel slip, these methods mainly pass through wheelslip
The estimation strategy of rate or side slip angle is realized.However, the operating parameters such as slip rate and side slip angle can not pass through biography
Sensor accurately obtains and establishes effective Real-time Feedback, this makes Yaw stability control precision lower.On the other hand, sideway is steady
Qualitatively control needs the constraint condition in view of vehicle itself, for example, motor maximum output torque and vehicle safety
Property constraint etc., the needs of traditional algorithm is difficult to meet this kind of multi-objective constrained optimization control problem.
Summary of the invention
It is an object of the invention to solve at least the above problems, and provide the advantages of at least will be described later.
The application's is designed to provide a kind of distributed-driving electric automobile Yaw stability based on sensor feedback
Real-time control method, to solve the accurate control problem of Yaw stability in distributed-driving electric automobile driving process.
This method uses heterarchical architecture, and required signal is provided by sensor, using measurable amount, using biography
Sensor Real-time Feedback and Model Predictive Control Algorithm design upper controller, calculate in vehicle motion process and keep sideway steady
Direct yaw moment required for qualitative.The direct yaw moment instruction that lower layer's controller guarantees that upper controller issues passes through drive
The distribution of kinetic moment is achieved, and is guaranteed that vehicle may be implemented to stablize traveling under different operating conditions, is improved the cross of electric car
Pendulum stability.
In order to realize these purposes and other advantages according to the present invention, it is horizontal to provide a kind of electric car based on feedback
Pendulum stability real-time control apparatus, comprising:
Upper controller, equipped with sensor unit, model predictive controller and direct yaw moment computing unit three
Part, the sensor unit output end connect the model predictive controller input terminal, the model predictive controller it is defeated
Outlet connects the direct yaw moment computing unit input terminal；
Lower layer's controller is equipped with and judges two parts of decision package and direct yaw moment execution unit, the judgement
The input terminal of decision package connects the output end of the sensor unit, the input terminal point of the direct yaw moment execution unit
The output end of the judgement decision package and direct yaw moment computing unit, the direct yaw moment execution unit are not connected
Control the driving moment of target wheel.
Preferably, the sensor unit includes at least vehicle for acquiring vehicle motion information, the vehicle movement information
Speed measures angular speed of wheel ω 'i, side acceleration and steering wheel angle.
Preferably, the model predictive controller receives the output signal of the sensor unit, and generates for calculating
Keep the active steering angle δ of vehicle yaw stabilityfWith calculate to obtain angular speed of wheel ωi, i=fl, fr, rl, rr, wherein fl is indicated
Left front, before fr indicates right, rl indicates left back, after rr indicates right.
Preferably, the direct yaw moment computing unit receives the output signal of the model predictive controller, and counts
Calculate expectation direct yaw moment needed for guaranteeing vehicle yaw stability.
Preferably, the judgement decision package receives the vehicle movement information of the sensor unit acquisition, and according to vehicle
Holding stablizes required stability boundary and vehicle-state-judgement decision corresponding informance to judge vehicle status simultaneously
Selection guarantees the most effective target wheel of intact stability, the stability boundary and yaw rate and side slip angle
It is related.
Preferably, it is calculated straight to receive the direct yaw moment computing unit for the direct yaw moment execution unit
Connect yaw moment, and convert it into driving moment and the implementation of the target wheel, so control yaw rate and
Side slip angle is maintained at stability range.
A kind of stability control method of electric car, comprising the following steps:
Step 1: acquisition vehicle motion information, establishes angular speed of wheel Real-time Feedback；
The active steering angle δ for keeping vehicle yaw stability is generated Step 2: calculating according to vehicle movement informationfWith calculate
Angular speed of wheel ωi；
Step 3: according to angular speed of wheel ω is calculated to obtainiIt calculates and generates expectation direct yaw moment；
Step 4: judging vehicle-state according to the vehicle movement information, and select to correct excessive or understeer the most
Effective target wheel；
Step 5: the expectation direct yaw moment is converted into driving moment and implements to act on the target wheel.
The present invention is include at least the following beneficial effects:
Distributed-driving electric automobile Yaw stability real-time control method proposed by the present invention based on sensor feedback,
Using the individually controllable feature of distributed-driving electric automobile hub motor, the accurate trip information of sensor Real-time Feedback and
Model Predictive Control handles the ability of multi-objective restriction, is realized by the design of direct yaw moment control device to electric car cross
The real-time accurate control of pendulum stability achievees the effect that active control vehicle body deflects, ensure that vehicle in the sideway of limiting condition
Stability.
Further advantage, target and feature of the invention will be partially reflected by the following instructions, and part will also be by this
The research and practice of invention and be understood by the person skilled in the art.
Detailed description of the invention
Fig. 1: control principle block diagram of the invention；
Fig. 2: upper controller functional block diagram；
Fig. 3: body powered model schematic；
Fig. 4: tire model schematic diagram；
Fig. 5: Model Predictive Control functional block diagram；
Figure label: δ --- input vehicle steering angle, v --- car speed, γr--- expectation yaw velocity,
βr--- expectation side slip angle, β --- side slip angle, γ --- yaw velocity, ax--- longitudinal acceleration of the vehicle,
ay--- vehicle lateral acceleration, d --- vehicle wheelbase, O --- vehicle's center of gravity position, the pitch angle of ρ --- vehicle,
Mz--- vehicle yaw moment, δf--- the vehicle steering angle of controller output, Lr--- vehicle's center of gravity to rear axis distance,
Lf--- vehicle's center of gravity to front-wheel axle center distance, vx--- automobile longitudinal speed, α --- slip angle of tire.ωfl--- the near front wheel
Angular speed, ωfr--- off-front wheel angular speed, ωrl--- left rear wheel angular speed, ωrr--- off hind wheel angular speed, Tdfl--- it is left
Front-wheel direct yaw moment torque, Tdfr--- off-front wheel direct yaw moment torque, Tdrl--- left rear wheel direct yaw moment
Torque, Tdrr--- off hind wheel direct yaw moment torque, Tefl--- the near front wheel driving torque, Tefr--- off-front wheel driving turns
Square, Terl--- left rear wheel driving torque, Terr--- off hind wheel driving torque, Tcfl--- the near front wheel output torque, Tcfr——
Off-front wheel output torque, Tcrl--- left rear wheel output torque, Tcrr--- off hind wheel output torque.Fyfl--- the near front wheel is lateral
Power, Fyfr--- off-front wheel cross force, Fyrl--- left rear wheel cross force, Fyrr--- off hind wheel cross force, Fxfl--- the near front wheel
Longitudinal force, Fxfr--- off-front wheel longitudinal force, Fxrl--- left rear wheel longitudinal force, Fxrr--- off hind wheel longitudinal force, Fz--- vehicle
To the vertical stress component of wheel, minJ --- rolling optimization objective function.
Specific embodiment
Present invention will be described in further detail below with reference to the accompanying drawings, to enable those skilled in the art referring to specification text
Word can be implemented accordingly.
It should be appreciated that such as " having ", "comprising" and " comprising " term used herein do not allot one or more
The presence or addition of a other elements or combinations thereof.
As shown in Figure 1, a kind of electric car Yaw stability real-time control apparatus based on feedback, including upper controller
1 and lower layer's controller 2, upper controller 1 and lower layer's controller 2 be separated, pass through signal transmssion line and complete vehicle-state
Transmission.
As shown in Fig. 2, upper controller 1 is equipped with sensor unit 3, model predictive controller 4 and direct yaw moment meter
5 three parts of unit are calculated, 3 output end of sensor unit connects 4 input terminal of model predictive controller, and the model is pre-
The output end for surveying controller 4 connects 5 input terminal of direct yaw moment computing unit.
The sensor unit 3 for acquiring vehicle motion information, the vehicle movement information include at least car speed,
Measure angular speed of wheel ω 'i, side acceleration and steering wheel angle, and provide the angular speed of wheel information of Real-time Feedback, pass through
Steering wheel angle information would know that input vehicle steering angle δ.
The model predictive controller 4 mainly solves multi-objective constrained optimization problem, and calculates four according to reference model
Angular speed of wheel value.The model predictive controller 4 receives the output signal of the sensor unit 3, and generates for calculating
Keep the active steering angle δ of vehicle yaw stabilityfWith calculate to obtain angular speed of wheel ωi, i=fl, fr, rl, rr, wherein fl is indicated
Left front, before fr indicates right, rl indicates left back, after rr indicates right.Wherein, active steering angle δfThe vehicle of as controller output turns
To angle, active steering angle δfIt is distinguishing, active steering angle δ with input vehicle steering angle δfIt is that controller generates, inputs vehicle
Steering angle sigma is driver's input, active steering angle δfVehicle steering angle δ is inputted for correcting, to improve vehicle steering angle
Precision.Angular speed of wheel ω ' will be measured simultaneouslyiWith calculate to obtain angular speed of wheel ωiIt is compared, to eliminate the two error, improves,
Improve the accuracy of angular speed of wheel.
The direct yaw moment computing unit 5 receives the output signal of the model predictive controller 4, and calculates guarantee
Expectation direct yaw moment needed for vehicle yaw stability.
Lower layer's controller 2, which is equipped with, judges 24 two parts of decision package 23 and direct yaw moment execution unit, described to sentence
The input terminal of disconnected decision package 23 connects the output end of the sensor unit 3, the direct yaw moment execution unit 24
Input terminal is separately connected the output end of the judgement decision package 23 and direct yaw moment computing unit 5, the direct sideway
The driving moment of the control target wheel of torque execution unit 24.
As shown in Fig. 3 body powered model schematic, linear eight degrees of freedom kinetic model by auto model and
Tire model composition.
Auto model:
Tire model:
Auto model is derived by by magic equation (3), front and back wheel side drift angle, vehicle wheel rotation inertia.
Magic equation:
Fyi=-Dysin(Cyarctan(Byαi-Ey(Byαi-arctanByαi))) (3)
Front and back wheel side drift angle calculation formula:
Vehicle wheel rotation inertia calculation formula:
Wherein, β indicates that side slip angle, γ indicate vehicle body yaw velocity, Fyl、FyrRespectively indicate left side, right side tire
Cross force, m indicate that complete vehicle quality, v indicate Vehicle Speed, LfIndicate vertical range of the vehicle's center of gravity to front wheel axle, LrTable
Show vertical range of the vehicle's center of gravity to front wheel axle, IzIndicate that the rotary inertia of tire, δ indicate input vehicle steering angle.
Pass through vehicle yaw moment MzDerive kinetics equation (7).
Vehicle yaw moment MzCalculation formula are as follows:
Kinetics equation are as follows:
Wherein, d indicates vehicle wheelbase, Fxfl、Fxfr、Fxrl、FxrrRespectively indicate the near front wheel, off-front wheel, left rear wheel, off hind wheel
Longitudinal force, i=fl, fr, rl, rr, Lf、LrVehicle's center of gravity is respectively indicated to front-wheel, rear axis distance, MiIndicate directly horizontal
Torque is put, J indicates that vehicle wheel rotation inertia, r indicate that tire radius, δ indicate input vehicle steering angle, FxiIndicate direct yaw moment
The longitudinal force of generation, TeiIndicate the driving moment implemented on wheel.
As shown in figure 4, a, b are respectively indicated from the tire model laterally and longitudinally analyzed, tire model is by magic equation
(3), six Tayor expansion, front and back wheel side drift angle, vehicle wheel rotation inertia, angular speed of wheel, vertical parts form.
Tayor expansion formula are as follows:
Angular speed of wheel calculation formula are as follows:
Vertical calculation formula are as follows:
Magic equation considers the interaction between longitudinal force and lateral force, and vehicle lateral force and longitudinal force depend on vertical
Active force, drift angle and slip rate, wherein FyiCross force is indicated, by vehicle vertical FzWith tyre slip angle αiIt indicates, i
=fl, fr, rl, rr.It is unfolded to simplify magic model by Tayor, keeps its non-linear spy using the method for Tayor expansion
It levies, wherein Cf、CrFront-wheel is respectively indicated, rear-wheel turns rigidity.
Wherein, δfIndicate the tire steering angle of controller output, ka、kbIndicate fitting coefficient.J indicates vehicle wheel rotation inertia,
TeIndicate motor driven torque, r indicates tire radius, kiThe slip rate of expression wheel, ω expression angular speed of wheel, i=fl, fr,
Rl, rr,Fz0=4000N, pk1, pk2, pk319.061 are respectively indicated, -0.466168,0.483251, CkiBy
FziCalculating is got.Fzfl、Fzfr、Fzrl、FzrrRespectively indicate the near front wheel, off-front wheel, left rear wheel, off hind wheel vertical, g expression
Acceleration of gravity, hcgVertical height of the center of gravity apart from ground, axIndicate longitudinal acceleration of the vehicle, ayIndicate that lateral direction of car accelerates
Degree.Angular speed of wheel (9) is derived by vehicle wheel rotation inertia (5).
It is illustrated in figure 5 the functional block diagram of Model Predictive Control, mainly by prediction model 17, rolling optimization 18, feedback school
Positive 19 are constituted, and prediction model 17 designs continuous time system non-linear state space side according to linear eight degrees of freedom kinetic model
Journey (11), rolling optimization 18 are made of quadratic model object function (12).
Specifically, Model Predictive Control 4 is used based on discrete-time state-space equation as prediction model 17, through rolling
Optimization 18 and 19 link of feedback compensation calculate the active steering angle δ for keeping vehicle yaw stabilityfWith calculate to obtain angular speed of wheel ωi,
I=fl, fr, rl, rr.
Non-linear state space equation:
Quadratic model object function:
Wherein, i=fl, fr, rl, rr, TsIndicating the sampling time, R (k) indicates that reference trajectory, Y (k) indicate prediction output,
Q, R, S respectively indicate weighted value.U (k) indicates control variable Tci, u1For front wheel steering angle, u2-u5For wheel torque, x1(k) table
Show side slip angle β, x2(k) yaw velocity γ, x are indicated3(k)、x4(k)、x5(k)、x6(k) the near front wheel angular speed is respectively indicated
ωfl, off-front wheel angular velocity omegafr, left rear wheel angular velocity omegarl, off hind wheel angular velocity omegarr。
Feedback compensation 19 is made of closed loop feedback, calculates active steering angle δ according to reference modelfWith angular speed of wheel ωi,i
=fl, fr, rl, rr.It is multiple that the model predictive controller 4 that the present invention uses solves the multiple targets such as yaw velocity and side slip angle
Miscellaneous Optimal Control Problem handles at active steering angle as time-domain constraints, and effectively realizes intact stability and vehicle performance
Between compromise optimization, by constructing cost function, optimizing solves the angular velocity signal of four wheels after being optimized, this hair
Bright cost function considers mainly to include three aspects, comprising: intact stability (preventing oversteering or understeer) is driven
Sail comfort (angular speed of wheel variation cannot too greatly), performance driving economy (energy is saved under the premise of meeting performance).
As shown in Fig. 2, vehicle direct yaw moment is determined by vehicle angular speed, specifically, linear eight degrees of freedom is turned to
Kinetic model determines four angular speed of wheel sizes, direct yaw moment relational expression in direct yaw moment computing unit 5
(13) direct yaw moment for needing to implement is calculated according to angular speed of wheel.
Specifically, direct yaw moment relational expression is according to Model Predictive Control in the direct yaw moment computing unit 5
The angular speed of wheel information for 3 Real-time Feedback of four angular speed of wheel and sensor unit that device 4 exports, calculates four wheels
It is expected that direct yaw moment.The yaw velocity and the stability boundary of side slip angle building are sentencing for vehicle stabilization state
Disconnected foundation.
Direct yaw moment relational expression:
In formula: MiIndicate direct yaw moment, ωiIndicate angular speed of wheel, Df、DrBefore expression, rear tread, Lf、LrRespectively
Indicate vehicle's center of gravity to front-wheel, rear axis distance, FxiIndicate longitudinal force, FyiIndicate cross force.
Vehicle stabilization state is characterized by the stability range of yaw velocity and side slip angle.
Stability range characterizes formula are as follows:
In formula: E1And E2For stability boundaris constant, β is side slip angle, and γ is yaw velocity, and μ is ground attachment system
Number, v is car speed.
When inequality is set up, it is believed that vehicle-state is stablized, and when inequality is invalid, vehicle will occur insufficient or excessive
The trend of steering.
As shown in Figure 1, lower layer's controller 2, which is equipped with, judges 24 two portions of decision package 23 and direct yaw moment execution unit
Point, target is that the direct yaw moment instruction for guaranteeing that upper controller 1 issues is achieved by the distribution of driving moment.Judgement
Decision package 23 waits vehicles according to car speed, angular speed of wheel, side acceleration and the steering wheel angle that sensor unit 3 acquires
Motion information and stability boundary and judge decision table accurate judgement vehicle-state, and then the selection that makes a policy is corrected excessively
Or the wheel that understeer is maximally efficient, direct yaw moment execution unit 24 close direct yaw moment in upper controller 1
It is the calculated direct yaw moment M of formulai, i=fl, fr, rl, rr are converted to driving moment by kinetics equation and implement to make
With making yaw velocity and side slip angle be limited in stability region, keep the stability of vehicle.
Table 1 is to judge decision table
Note: in table each physical quantity be all in a counterclockwise direction for+, clockwise for-.
Stability control method specifically includes the following steps:
Step 1: acquisition vehicle motion information, establishes angular speed of wheel Real-time Feedback；Vehicle movement information includes vehicle speed
Degree, angular speed of wheel, side acceleration and steering wheel angle etc..
Step 2: model predictive controller 4 is calculated according to vehicle movement information generates the master for keeping vehicle yaw stability
Dynamic steering angle sigmafWith calculate to obtain angular speed of wheel ωi；
Step 3: direct yaw moment computing unit 5 it is expected direct sideway power according to calculating to obtain angular speed of wheel and calculate to generate
Square；
Step 4: judging vehicle-state according to the vehicle movement information, and select to correct excessive or understeer the most
Effective target wheel；
Step 5: to receive the direct yaw moment computing unit 5 calculated straight for direct yaw moment execution unit 24
Connect yaw moment, and convert it into driving moment and the implementation of the target wheel, so control yaw rate and
Side slip angle is maintained at stability range.
From the above mentioned, the distributed-driving electric automobile Yaw stability proposed by the present invention based on sensor feedback is real-time
Control method, using the individually controllable feature of distributed-driving electric automobile hub motor, sensor Real-time Feedback is accurately run
The ability of parameter information and Model Predictive Control processing multi-objective restriction passes through the design realization pair of direct yaw moment control device
The real-time accurate control of electric car Yaw stability achievees the effect that active control vehicle body deflects, ensure that vehicle in the limit
The Yaw stability of operating condition.
Although the embodiments of the present invention have been disclosed as above, but its is not only in the description and the implementation listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily
Realize other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, the present invention is simultaneously unlimited
In specific details and legend shown and described herein.
Claims (7)
1. a kind of electric car Yaw stability real-time control apparatus based on feedback characterized by comprising
Upper controller (1) is equipped with sensor unit (3), model predictive controller (4) and direct yaw moment computing unit
(5) three parts, sensor unit (3) output end connect model predictive controller (4) input terminal, and the model is pre-
The output end for surveying controller (4) connects direct yaw moment computing unit (5) input terminal；
Lower layer's controller (2) is equipped with and judges (24) two parts of decision package (23) and direct yaw moment execution unit, institute
The output end for judging that the input terminal of decision package (23) connects the sensor unit (3) is stated, the direct yaw moment executes
The input terminal of unit (24) is separately connected the output of judgement decision package (23) and direct yaw moment computing unit (5)
End, the driving moment of direct yaw moment execution unit (24) the control target wheel.
2. the electric car Yaw stability real-time control apparatus based on feedback as described in claim 1, which is characterized in that institute
It states sensor unit (3) and includes at least car speed for acquiring vehicle motion information, the vehicle movement information, measures wheel
Angular velocity omega 'i, side acceleration and steering wheel angle.
3. the electric car Yaw stability real-time control apparatus based on feedback as claimed in claim 2, which is characterized in that institute
The output signal that model predictive controller (4) receive the sensor unit (3) is stated, and keeps Vehicular yaw for calculating to generate
The active steering angle δ of stabilityfWith calculate to obtain angular speed of wheel ωi, i=fl, fr, rl, rr, wherein fl indicates left front, and fr is indicated
Before the right side, rl indicates left back, after rr indicates right.
4. the electric car Yaw stability real-time control apparatus based on feedback as claimed in claim 3, which is characterized in that institute
It states direct yaw moment computing unit (5) and receives the output signal of the model predictive controller (4), and calculate and guarantee that vehicle is horizontal
Expectation direct yaw moment needed for pendulum stability.
5. the electric car Yaw stability real-time control apparatus based on feedback as claimed in claim 4, which is characterized in that institute
The vehicle movement information for judging that decision package (23) receive sensor unit (3) acquisition is stated, and keeps stablizing according to vehicle
Required stability boundary and vehicle-state-judgement decision corresponding informance come judge vehicle status and select guarantee vehicle
The most effective target wheel of stability, the stability boundary are related to yaw rate and side slip angle.
6. the electric car Yaw stability real-time control apparatus based on feedback as claimed in claim 5, which is characterized in that institute
It states direct yaw moment execution unit (24) and receives the calculated direct sideway of expectation of the direct yaw moment computing unit (5)
Torque, and driving moment and the implementation of the target wheel are converted it into, and then control yaw rate and mass center side
Drift angle is maintained at stability range.
7. a kind of controlling party of the electric car Yaw stability real-time control apparatus based on feedback as claimed in claim 6
Method, which comprises the following steps:
Step 1: acquisition vehicle motion information, establishes angular speed of wheel Real-time Feedback；
The active steering angle δ for keeping vehicle yaw stability is generated Step 2: calculating according to vehicle movement informationfWith calculate to obtain wheel
Angular velocity omegai；
Step 3: according to angular speed of wheel ω is calculated to obtainiIt calculates and generates expectation direct yaw moment；
Step 4: judge vehicle-state according to the vehicle movement information, and select to correct excessive or understeer maximally efficient
Target wheel；
Step 5: the expectation direct yaw moment is converted into driving moment and implements to act on the target wheel.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811201424.9A CN109291932B (en) | 2018-10-16 | 2018-10-16 | Feedback-based electric vehicle yaw stability real-time control device and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811201424.9A CN109291932B (en) | 2018-10-16 | 2018-10-16 | Feedback-based electric vehicle yaw stability real-time control device and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109291932A true CN109291932A (en) | 2019-02-01 |
| CN109291932B CN109291932B (en) | 2021-03-12 |
Family
ID=65162762
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811201424.9A Active CN109291932B (en) | 2018-10-16 | 2018-10-16 | Feedback-based electric vehicle yaw stability real-time control device and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109291932B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110239362A (en) * | 2019-06-19 | 2019-09-17 | 北京理工大学 | A kind of more performances of distribution electro-motive vehicle optimize torque distribution method |
| CN110271534A (en) * | 2019-06-14 | 2019-09-24 | 百度在线网络技术（北京）有限公司 | Control method, device, computer equipment and the storage medium of automatic driving vehicle |
| CN110979303A (en) * | 2019-12-24 | 2020-04-10 | 大连理工大学 | Method for deciding additional yaw moment of running vehicle |
| CN111452576A (en) * | 2020-03-19 | 2020-07-28 | 武汉理工大学 | Driving force coordination method and device for amphibious vehicle and storage medium |
| EP3805057A4 (en) * | 2019-08-15 | 2021-08-25 | Huawei Technologies Co., Ltd. | Method for controlling stability of vehicle, and device |
| CN113479189A (en) * | 2021-07-23 | 2021-10-08 | 西安理工大学 | Electric automobile yaw stability control method based on self-adaptive reverse pushing controller |
| CN114475575A (en) * | 2022-04-15 | 2022-05-13 | 北京理工大学 | Automobile control system and method and automobile |
| WO2023062903A1 (en) * | 2021-10-15 | 2023-04-20 | Mitsubishi Electric Corporation | System and method for controlling motion of a vehicle |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6885931B2 (en) * | 2003-04-24 | 2005-04-26 | Visteon Global Technologies, Inc. | Control algorithm for a yaw stability management system |
| CN103057436A (en) * | 2012-12-27 | 2013-04-24 | 西安交通大学 | Yawing moment control method of individual driven electromobile based on multi-agent |
| CN103600744A (en) * | 2013-10-25 | 2014-02-26 | 山东省计算中心 | Path maintaining and wheel sideslip control method for four-wheel steering/driving vehicles |
| CN105416276A (en) * | 2015-12-14 | 2016-03-23 | 长春工业大学 | Method for controlling electric automobile stability direct yawing moment based on high-order slip mold |
| CN106004870A (en) * | 2016-06-23 | 2016-10-12 | 吉林大学 | Vehicle stability integrated control method based on variable-weight model prediction algorithm |
| CN106184199A (en) * | 2016-07-07 | 2016-12-07 | 辽宁工业大学 | The integrated control method of distributed AC servo system electric automobile stability |
| CN107179686A (en) * | 2017-05-10 | 2017-09-19 | 江苏大学 | A kind of distributed-driving electric automobile lateral stability high-order variable structure control method based on gray prediction |
| CN107719372A (en) * | 2017-09-30 | 2018-02-23 | 武汉理工大学 | Four-drive electric car dynamics multi objective control system based on dynamic control allocation |
| CN108454623A (en) * | 2018-01-22 | 2018-08-28 | 大连理工大学 | A kind of unmanned electric vehicle Trajectory Tracking Control method of four motorized wheels |
-
2018
- 2018-10-16 CN CN201811201424.9A patent/CN109291932B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6885931B2 (en) * | 2003-04-24 | 2005-04-26 | Visteon Global Technologies, Inc. | Control algorithm for a yaw stability management system |
| CN103057436A (en) * | 2012-12-27 | 2013-04-24 | 西安交通大学 | Yawing moment control method of individual driven electromobile based on multi-agent |
| CN103600744A (en) * | 2013-10-25 | 2014-02-26 | 山东省计算中心 | Path maintaining and wheel sideslip control method for four-wheel steering/driving vehicles |
| CN105416276A (en) * | 2015-12-14 | 2016-03-23 | 长春工业大学 | Method for controlling electric automobile stability direct yawing moment based on high-order slip mold |
| CN106004870A (en) * | 2016-06-23 | 2016-10-12 | 吉林大学 | Vehicle stability integrated control method based on variable-weight model prediction algorithm |
| CN106184199A (en) * | 2016-07-07 | 2016-12-07 | 辽宁工业大学 | The integrated control method of distributed AC servo system electric automobile stability |
| CN107179686A (en) * | 2017-05-10 | 2017-09-19 | 江苏大学 | A kind of distributed-driving electric automobile lateral stability high-order variable structure control method based on gray prediction |
| CN107719372A (en) * | 2017-09-30 | 2018-02-23 | 武汉理工大学 | Four-drive electric car dynamics multi objective control system based on dynamic control allocation |
| CN108454623A (en) * | 2018-01-22 | 2018-08-28 | 大连理工大学 | A kind of unmanned electric vehicle Trajectory Tracking Control method of four motorized wheels |
Non-Patent Citations (1)
| Title |
|---|
| 李刚等: "四轮轮毂电机电动汽车横摆力矩模糊PI控制研究", 《机械设计与制造》 * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11254304B2 (en) | 2019-06-14 | 2022-02-22 | Apollo Intelligent Driving Technology (Beijing) Co., Ltd. | Control method and apparatus for autonomous vehicle, computer device, and storage medium |
| CN110271534A (en) * | 2019-06-14 | 2019-09-24 | 百度在线网络技术（北京）有限公司 | Control method, device, computer equipment and the storage medium of automatic driving vehicle |
| CN110271534B (en) * | 2019-06-14 | 2021-05-28 | 百度在线网络技术（北京）有限公司 | Control method and device for automatic driving vehicle, computer equipment and storage medium |
| CN110239362A (en) * | 2019-06-19 | 2019-09-17 | 北京理工大学 | A kind of more performances of distribution electro-motive vehicle optimize torque distribution method |
| US11731611B2 (en) | 2019-08-15 | 2023-08-22 | Huawei Technologies Co., Ltd. | Vehicle stability control method and device |
| EP3805057A4 (en) * | 2019-08-15 | 2021-08-25 | Huawei Technologies Co., Ltd. | Method for controlling stability of vehicle, and device |
| CN110979303A (en) * | 2019-12-24 | 2020-04-10 | 大连理工大学 | Method for deciding additional yaw moment of running vehicle |
| CN110979303B (en) * | 2019-12-24 | 2021-06-11 | 大连理工大学 | Method for deciding additional yaw moment of running vehicle |
| CN111452576A (en) * | 2020-03-19 | 2020-07-28 | 武汉理工大学 | Driving force coordination method and device for amphibious vehicle and storage medium |
| CN111452576B (en) * | 2020-03-19 | 2021-08-24 | 武汉理工大学 | Driving force coordination method and device for amphibious vehicle and storage medium |
| CN113479189A (en) * | 2021-07-23 | 2021-10-08 | 西安理工大学 | Electric automobile yaw stability control method based on self-adaptive reverse pushing controller |
| CN113479189B (en) * | 2021-07-23 | 2022-07-01 | 西安理工大学 | Electric automobile yaw stability control method based on self-adaptive reverse pushing controller |
| WO2023062903A1 (en) * | 2021-10-15 | 2023-04-20 | Mitsubishi Electric Corporation | System and method for controlling motion of a vehicle |
| CN114475575A (en) * | 2022-04-15 | 2022-05-13 | 北京理工大学 | Automobile control system and method and automobile |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109291932B (en) | 2021-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109291932A (en) | Electric car Yaw stability real-time control apparatus and method based on feedback | |
| CN104773170B (en) | A kind of intact stability integrated control method | |
| CN107380161B (en) | A kind of active steering control device for aiding in driver to realize desired ride track | |
| CN103057436B (en) | Yawing moment control method of individual driven electromobile based on multi-agent | |
| CN108177692B (en) | A kind of differential power-assisted steering of electric wheel drive vehicle and stability control method for coordinating | |
| CN104773169B (en) | Vehicle yaw stability integrating control method based on tire slip angle | |
| CN106080553B (en) | A kind of the four-wheel steering automobile anti-rollover control system and method for the variation of fusion speed | |
| CN104176054B (en) | A kind of automatic lane change control system of automobile active anti-corrosion and method of work thereof | |
| CN104843057B (en) | A kind of rotating direction control method of four-wheel independent steering automobile | |
| CN106004870A (en) | Vehicle stability integrated control method based on variable-weight model prediction algorithm | |
| CN105857304A (en) | Four-wheel drive vehicle-based moment of force distribution control system | |
| CN106184363A (en) | The control method of four-wheel independent steering vehicle | |
| CN107627900A (en) | A kind of electric automobile dual wheel rims motor differential moment controlling system and control method | |
| CN107719372A (en) | Four-drive electric car dynamics multi objective control system based on dynamic control allocation | |
| CN103786602A (en) | Maneuverability improving and controlling method based on distributively driven electric vehicle | |
| CN102107660A (en) | Motion control unit for vehicle based on jerk information | |
| CN106515716A (en) | Coordination control device and method for chassis integrated control system of wheel driving electric vehicle | |
| CN108839652A (en) | A kind of automatic Pilot Emergency avoidance system of vehicle unstability controllable domain | |
| CN108216250A (en) | Four-drive electric car speed and road grade method of estimation based on state observer | |
| CN109606466A (en) | A kind of active steering control method of four motorized wheels electric vehicle | |
| CN108248454A (en) | Vehicle body stabilizing control system, method and automobile | |
| WO2022266824A1 (en) | Steering control method and apparatus | |
| CN107199884A (en) | Torque distribution method for reducing the average slippage rate of axletree | |
| CN109204599A (en) | Active attitude and all-wheel steering cooperative control method based on coaxial-type wheel leg structure | |
| CN102717726B (en) | Electronic differential control method and electrically driven mine car using same |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210128 Address after: 325600 268 Wei twelve Road, Yueqing Economic Development Zone, Yueqing, Wenzhou, Zhejiang Applicant after: ZHEJIANG DONGFANG ELECTROMECHANICAL Co.,Ltd. Address before: College of electrical engineering, Hunan University, 2 Lushan South Road, Changsha City, Hunan Province, 410082 Applicant before: Yuan Xiaofang |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |