CN108563845A - A kind of building method of the EPS controllers based on composite power source - Google Patents
A kind of building method of the EPS controllers based on composite power source Download PDFInfo
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Abstract
The building method of the invention discloses a kind of automobile EPS controllers based on composite power source, there are three types of powering mode and different control methods for EPS system tool, Active Disturbance Rejection Control algorithm is used under composite power source powering mode, vehicle power-supply system and super capacitor provide steering power for motor jointly;It uses Fuzzy PID, vehicle power-supply system to be individually for motor and provide steering power, while load of the super capacitor as vehicle power-supply system under vehicle power supply powering mode, is in charged state, the energy of storage is in case low speed uses when turning to;When vehicle power failure, system is in super capacitor powering mode and neural network dynamic face control algolithm, super capacitor is used to be individually for motor and provide steering power, maintains the power steering of short time;It can effectively solve the problems, such as that heavy-duty commercial vehicle pivot stud or extremely low speed turn to vehicle power-supply system and provide underpower and ensure that stability of the EPS system in powering mode handoff procedure.
Description
Technical field
The invention belongs to power steering system field more particularly to a kind of constructions of the EPS controllers based on composite power source
Method.
Background technology
Heavy-duty commercial vehicle generally uses the single hydraulic power-assist steering system (HPS) of assist characteristic, and power-assisted size will not be with
The variation of speed and change, therefore road feel is poor when high speed steering, and vehicle is easily " unstable ";In addition, vehicle no matter in straight trip or
Turning, the steering pump of HPS run at high speed under engine driving always, and automobile most of the time straight trip operating mode is not required to turn to,
Therefore the reactive loss of HPS is big.Electro-Hydraulic Power Steering System (ECHPS) installs electronics executive device additional on the basis of HPS, makes
The pressure and flow of system change with the variation of driving cycle, to realize that it is light that low speed turns to, the mesh that high speed steering is stablized
Mark, but the steering pump of ECHPS is still directly driven by engine, therefore the reactive loss of steering is almost without reduction.
Electric boosting steering system (EPS) provides power steering by motor, and power-assisted size is controlled by software program, can be easily
It realizes with the variable assist characteristic of speed, helps to improve the control stability of vehicle;Under non-steering situation, EPS hardly consumes electricity
Can, therefore EPS is " on-demand " servo steering system truly.
EPS is widely used in passenger car and light commercial vehicle at present.Since the front axle load of heavy-duty commercial vehicle is big, vehicle electricity
Source system cannot meet the steering power needed for EPS, therefore existing EPS schemes are not suitable for heavy-duty commercial vehicle.Although heavy
Required steering power is very big when commercial car turns in situ or extremely low speed turns to, and vehicle power-supply system cannot meet steering power
Demand, but be in middle and high fast transport condition, corresponding steering resisting moment in the medium and heavy commercial car of most run time
Smaller, required steering power is also smaller, and vehicle power-supply system is entirely capable of meeting steering power demand, as long as therefore solving emphatically
Certainly good pivot stud or extremely low speed turn to the problem of vehicle power-supply system provides underpower, EPS can be promoted in heavy type commercial
Application on vehicle.
Invention content
It is low that the present invention according to electric boosting steering system under prior art vehicle power-supply system can not provide heavy-duty commercial vehicle
Speed turns to the problem of required power, it is proposed that a kind of EPS system and its building method based on composite power source, it is therefore intended that solution
Certainly heavy-duty commercial vehicle pivot stud or extremely low speed turn to the problem of vehicle power-supply system provides underpower.
The technical solution adopted by the present invention is as follows:
A kind of EPS system based on composite power source, including electric boosting steering system, composite power source and steeraxle;It is described
Composite power source includes vehicle power supply, super capacitor and charge-discharge circuit;Vehicle power supply it is in parallel with accumulator by generator and
At vehicle power supply is connected in series with charging circuit, then is connected in series with super capacitor;Super capacitor is first connected with discharge circuit
Connection, then connect with vehicle power sources in parallel.Electric boosting steering system include steering wheel, input shaft, torque/rotary angle transmitter,
Jackshaft, assist motor, ball-and-nut steering gear, steering gear output shaft, EPS controllers;Torque/rotary angle transmitter passes through input
Axis receives the angular signal that steering wheel angle transmits, and is transferred to EPS controllers, and EPS controllers pass through electric wire and assist motor
It is connected, the output shaft of assist motor is connected with ball-and-nut steering gear;EPS controllers are powered by composite power source, reception torque/turn
The current signal of angle signal, speed signal, the electric quantity signal of composite power source and assist motor, EPS controllers include fuzzy prison
Device, EPS system and controller are superintended and directed, the controller includes fuzzy controller, neural network dynamic face controller and resists certainly
Disturb controller.The steeraxle includes steering gear rocking arm, steering gear, steered wheel.
A kind of building method of the EPS based on composite power source, which is characterized in that the EPS system of composite power source is according to power supply
Pattern selects different control methods, and there are three types of powering modes for the composite power source tool:Composite power source powering mode, vehicle electricity
Source powering mode and super capacitor powering mode;Under vehicle power supply powering mode, using fuzzy controller;Super capacitor supplies
Under power mode, using neural network dynamic face controller;Under composite power source powering mode, using automatic disturbance rejection controller;
Composite power source EPS controller multi-mode switch operating processes based on fuzzy monitor are:Fuzzy monitor according to
The output state of EPS systems, the output state of controller and powering mode switching law output weighting coefficient σ1、σ2、σ3;Add
Weight coefficient σ1、σ2、σ3Respectively with the output u of corresponding controller1、u2、u3It is multiplied and carries out weighted sum and handle as controller most
Output u eventually, wherein u1Output for the fuzzy controller being made of Fuzzy PID, u2For neural network dynamic
The output for the neural network dynamic face controller that face control algolithm is constituted, u3For the active disturbance rejection control of Active Disturbance Rejection Control Algorithm constitution
The output of device processed.
Further, the rule between the switching powering mode is as follows:When EPS controllers are in vehicle power supply powering mode
m2When, if EPS controllers detect the output voltage U of vehicle power supplydc<Udc0, vehicle power supply powering mode m2To super capacitor
Powering mode m1Switching;If controller detects speed v≤v0, and steering wheel angle θh>θh0, vehicle power supply powering mode m2
To composite power source powering mode m3Switching;
When controller is in composite power source powering mode m3When, if controller detects speed v>v0, composite power source power supply mould
Formula m3To vehicle power supply powering mode m2Switching;If controller detects the output voltage U of vehicle power supplydc<Udc0, composite power source
Powering mode m3To super capacitor powering mode m1Switching;
When controller is in super capacitor powering mode m1When, if controller detects the output voltage U of vehicle power supplydc≥
Udc0, and speed v>Particular value v0, super capacitor powering mode m1To vehicle power supply powering mode m2Switching;If controller is examined
Measure the output voltage U of vehicle power supplydc≥Udc0, and speed v≤v0, and steering wheel angle θh>θh0, super capacitor power supply
Mode m1To composite power source powering mode m3Switching, wherein v0For the particular value of speed, θh0The particular value of steering wheel angle.
Further, the particular value v of the speed0, steering wheel angle particular value θh0It is obtained by following steps:
Step 1, tire and ground with Ka Te-Pohle Si Ji-richness bohr slip Theory based on friction binomial theory are established
Face frictional force mathematical model, with ABAQUS finite element software simulation analysis frictional force with tire rolling speed, tyre deflection
The variation relation of degree, tyre deflection speed, vertical load, surface friction coefficient, fitting obtain the relational expression of frictional force;It is logical
Tire is crossed to verify frictional force relational expression with frictional ground force bench test.
Step 2, aligning torque caused by Front wheel Alignment Parameters etc. is calculated, turns to and hinders caused by tire and frictional ground force
Aligning torque caused by moment and Front wheel Alignment Parameters etc. integrate to obtain low speed turn to comprehensive steering drag away from mathematical model;
Low speed rotation is carried out using the kart of no steering boost system on Matlab/Simulink platforms as object to imitate to the moment of resistance
Very, while by real train test it is verified and is corrected.
Step 3, the simulation model of the kart verified based on experiment, is built heavy-duty commercial vehicle and emulates mould accordingly
Type is emulated low speed steering resisting moment, analyzes it with speed, the changing rule of steering wheel angle, obtained using least square fitting
To heavy-duty commercial vehicle steering resisting moment about speed, the analytic expression of steering wheel angle.
Step 4, made away from the supply current conversed needed for electric boosting steering system by the steering drag of heavy-duty commercial vehicle
Go out electric current with speed, the change curve of steering wheel angle, electric current is with the change curve of speed and by vehicle source nominal electric current structure
At straight line intersection point be speed particular value v0, electric current is with the change curve of steering wheel angle and by vehicle source nominal
The intersection point for the straight line that electric current is constituted is the particular value θ of speedh0。
Further, fuzzy controller building method is under the vehicle power supply powering mode:By speed signal, turn to
Disk dtc signal inputs EPS assist characteristic databases, obtain EPS assist motors by searching for EPS assist characteristic databases
Target current iobj, by the target current i of EPS assist motorsobjWith actual current ifDifference input PID controller, fuzzy rule
Then library, fuzzy rule base export proportionality coefficient adjustment amount Δ K in PID controllerP, integral coefficient adjustment amount Δ KI, differential coefficient
Adjustment amount Δ KD, fuzzy controller output controlled quentity controlled variable u1To EPS system.
Further, which is characterized in that neural network dynamic face controller building method under the super capacitor powering mode
For:Speed signal, steering-wheel torque signal are inputted into EPS assist characteristic databases, by searching for EPS assist characteristic databases
Obtain the target current i of EPS assist motorsobj, by the target current i of EPS assist motorsobjWith actual current ifInput nerve
Network dynamic face controller is write the mathematical model of EPS as state equation form, is designed with the method for retrogressing and firstorder filter
First virtual controlling restrains α2, the second virtual controlling restrain α3With practical control law u2;It is non-using radial base neural net online approximating
Linear electrical servo steering system solves the ginseng of nerve network system with the parameter update law based on Sigmoid functions
Number;Lyapunov functions, the stability of analysis system are defined, neural network dynamic face controller exports controlled quentity controlled variable u2Give EPS systems
System.
Further, construction method for active-disturbance-rcontroller controller is under the composite power source powering mode:By speed signal, steering wheel
Dtc signal inputs EPS assist characteristic databases, and the target of EPS assist motors is obtained by searching for EPS assist characteristic databases
Electric current iobj, Nonlinear Tracking Differentiator is according to assist motor target current iobjObtain transition variable v1And its micro component v2, expansion state
Observer is according to the actual current i of assist motorf, automatic disturbance rejection controller controlled quentity controlled variable u3Export the electric power steering system of observation
The state variable z of system1With state variable z2And expansion state variable z3, nonlinear feedback model is according to v1With z1Difference e1
And v2With z2Difference e2Export the virtual controlling amount u of automatic disturbance rejection controller0, disturbance compensation module is by virtual controlling amount u0Become
It is changed to controlled quentity controlled variable u3。
Beneficial effects of the present invention:
Electric boosting steering system based on composite power source is conducive to improve the control stability of heavy-duty commercial vehicle and big
The big energy consumption for reducing steering, the controller of the automobile EPS based on composite power source of structure ensure that EPS system is being powered
Stability in mode handover procedure, the neural network dynamic face control algolithm under super capacitor powering mode improve vehicle
The dynamic response of EPS system when power-fail, the Active Disturbance Rejection Control algorithm under composite power source powering mode inhibit voltage disturbance
Power steering is buffeted caused by possible.
Description of the drawings
Fig. 1 is the automobile EPS composition schematic diagrams based on composite power source;
Fig. 2 be the automobile EPS powering mode classification charts based on composite power source, 2 (a) be composite power source powering mode figure, 2
(b) it is vehicle power supply powering mode figure, 2 (c) is super capacitor powering mode figure;
Fig. 3 is the composite power source EPS multi-mode switch controller composition schematic diagrams based on fuzzy monitor;
Fig. 4 is that the automobile EPS multi-modes based on composite power source switch automaton model;
Fig. 5 is the fuzzy controller composition schematic diagram under vehicle power supply powering mode;
Fig. 6 is the neural network dynamic face controller composition schematic diagram under super capacitor powering mode;
Fig. 7 is the automatic disturbance rejection controller composition schematic diagram under composite power source powering mode;
The reference numerals are as follows:1-steering wheel, 2-input shafts, 3-jackshafts, 4-steering gear output shafts, 5-turn
To device rocking arm, 6-steering gears, 7-steered wheels, 8-composite power sources.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that specific embodiment described herein is only used for explaining the present invention, and
It is not used in the restriction present invention.
As shown in Fig. 1, the present invention is a kind of EPS system based on composite power source, including electric boosting steering system, multiple
Close power supply and steeraxle;Electric boosting steering system includes that steering wheel 1 connects torque/rotary angle transmitter by input shaft 2, is turned
Square/rotary angle transmitter is connect by jackshaft 3 with ball-and-nut steering gear, and ball-and-nut steering gear is connected by steering gear output shaft 4
Steeraxle assist motor is mechanically connected with ball-and-nut steering gear;EPS controllers are passed by electric wire and assist motor, torque/corner
Sensor, composite power source be connected, receive torque/angular signal, speed signal, composite power source electric quantity signal and assist motor
Current signal;EPS controllers are powered by composite power source.
Steeraxle includes that steering gear Rocker arm 5, steering gear 6, steered wheel 7 are mechanically coupled successively;Steeraxle passes through
Steering gear Rocker arm 5 is connected with steering gear output shaft 4.
Composite power source includes vehicle power supply, super capacitor and charge-discharge circuit;The vehicle power supply is by generator and storage
Cell parallel forms, and vehicle power supply is connected in series with charging circuit, then is connected in series with super capacitor;The super capacitor is first
It is connected in series with discharge circuit, then is connect with vehicle power sources in parallel.
As shown in Fig. 2, the powering mode classification chart of the EPS system based on composite power source, there are three types of power supplies for composite power source tool
Pattern:Composite power source powering mode, vehicle power supply powering mode and super capacitor powering mode, EPS controllers according to speed,
Powering mode and vehicle power-supply system and super capacitor residing for the signal decidings such as steering wheel angle, vehicle supply voltage carry
For the mode and ratio of steering power.As shown in Fig. 2 (a), when speed is relatively low, system is in composite power source powering mode, whole
Vehicle power-supply system and super capacitor provide steering power for motor jointly;As shown in Fig. 2 (b), when speed is higher, at system
In vehicle power supply powering mode, vehicle power-supply system is individually for motor and provides steering power, while super capacitor is as vehicle electricity
The load of source system is in charged state, and the energy of storage is in case low speed uses when turning to;As shown in Fig. 2 (c), when vehicle electricity
When source is broken down, system is in super capacitor powering mode, and super capacitor is individually for motor and provides steering power, maintains short
The power steering of time.
As shown in figure 3, the composite power source EPS multi-mode switch controllers based on fuzzy monitor, supply in different power supplys
Power mode uses different control algolithms, under vehicle power supply powering mode, using Fuzzy PID;Super capacitor is powered
Under pattern, since the flash-over characteristic of super capacitor is nonlinear, system is improved using neural network dynamic face control algolithm
Dynamic response;Under composite power source powering mode, vehicle power supply provides steering power, vehicle power supply for EPS jointly with super capacitor
For constant pressure source, super capacitor is the voltage source of time-varying, and the fluctuation of super capacitor terminal voltage is considered as to the interference of internal system, is transported
The power-assisted as caused by voltage fluctuation is inhibited to buffet with Active Disturbance Rejection Control algorithm.
Fuzzy monitor is according to the output state of EPS system, the output state of controller and powering mode switching law
Export weighting coefficient σ1、σ2、σ3;Weighting coefficient σ1It is defeated with the fuzzy controller that is made of the Fuzzy PID
Go out u1It is multiplied, weighting coefficient σ2With the neural network dynamic face controller that is made of neural network dynamic face control algolithm
Export u2It is multiplied, weighting coefficient σ3With the output u of the automatic disturbance rejection controller by the Active Disturbance Rejection Control Algorithm constitution3It is multiplied, respectively
Final output u of the weighted sum that controller exports under pattern as controller.
As shown in Figure 4, it is specified that:Switching condition r1For the output voltage U of vehicle power supplydc<Udc0, r2For speed v≤v0;It cuts
Change condition r3For speed v≤v0, and steering wheel angle θh>θh0;Switching condition!r1For the output voltage U of vehicle power supplydc≥
Udc0;Switching law between EPS powering modes based on composite power source:When EPS controllers are in vehicle power supply powering mode
m2When, if EPS controllers detect the output voltage U of vehicle power supplydc<Udc0, vehicle power supply powering mode m2To super capacitor
Powering mode m1Switching;If controller detects speed v≤v0, and steering wheel angle θh>θh0, vehicle power supply powering mode m2
To composite power source powering mode m3Switching;
When controller is in composite power source powering mode m3When, if controller detects speed v>v0, composite power source power supply mould
Formula m3To vehicle power supply powering mode m2Switching;If controller detects the output voltage U of vehicle power supplydc<Udc0, composite power source
Powering mode m3To super capacitor powering mode m1Switching;
When controller is in super capacitor powering mode m1When, if controller detects the output voltage U of vehicle power supplydc≥
Udc0, and speed v>Particular value v0, super capacitor powering mode m1To vehicle power supply powering mode m2Switching;If controller is examined
Measure the output voltage U of vehicle power supplydc≥Udc0, and speed v≤v0, and steering wheel angle θh>θh0, super capacitor power supply
Mode m1To composite power source powering mode m3Switching, wherein v0For the particular value of speed, θh0The particular value of steering wheel angle.
The particular value v of speed0, steering wheel angle particular value θh0It is obtained by following steps:
Step 1, tire and ground with Ka Te-Pohle Si Ji-richness bohr slip Theory based on friction binomial theory are established
Face frictional force mathematical model, with ABAQUS finite element software simulation analysis frictional force with tire rolling speed, tyre deflection
The variation relation of degree, tyre deflection speed, vertical load, surface friction coefficient, fitting obtain the relational expression of frictional force;It is logical
Tire is crossed to verify frictional force relational expression with frictional ground force bench test.
Step 2, aligning torque caused by Front wheel Alignment Parameters etc. is calculated, turns to and hinders caused by tire and frictional ground force
Aligning torque caused by moment and Front wheel Alignment Parameters etc. integrate to obtain low speed turn to comprehensive steering drag away from mathematical model;
Low speed rotation is carried out using the kart of no steering boost system on Matlab/Simulink platforms as object to imitate to the moment of resistance
Very, while by real train test it is verified and is corrected.
Step 3, the simulation model of the kart verified based on experiment, is built heavy-duty commercial vehicle and emulates mould accordingly
Type is emulated low speed steering resisting moment, analyzes it with speed, the changing rule of steering wheel angle, obtained using least square fitting
To heavy-duty commercial vehicle steering resisting moment about speed, the analytic expression of steering wheel angle.
Step 4, made away from the supply current conversed needed for electric boosting steering system by the steering drag of heavy-duty commercial vehicle
Go out electric current with speed, the change curve of steering wheel angle, electric current is with the change curve of speed and by vehicle source nominal electric current structure
At straight line intersection point be speed particular value v0, electric current is with the change curve of steering wheel angle and by vehicle source nominal
The intersection point for the straight line that electric current is constituted is the particular value θ of speedh0。
As shown in figure 5, fuzzy controller building method is under vehicle power supply powering mode:By speed signal, steering wheel
Dtc signal inputs EPS assist characteristic databases, and the target of EPS assist motors is obtained by searching for EPS assist characteristic databases
Electric current iobj, by the target current i of EPS assist motorsobjWith actual current ifDifference input PID controller, fuzzy rule
Library, fuzzy rule base export proportionality coefficient adjustment amount Δ K in PID controllerP, integral coefficient adjustment amount Δ KI, differential coefficient tune
Whole amount Δ KD, fuzzy controller output controlled quentity controlled variable u1To EPS system.
As shown in fig. 6, the neural network dynamic face controller composition schematic diagram under super capacitor powering mode, the nerve
Network dynamic face controller, building method are as follows:Speed signal, steering-wheel torque signal are inputted into EPS assist characteristic data
Library obtains the target current i of EPS assist motors by searching for EPS assist characteristic databasesobj, by the target of EPS assist motors
Electric current iobjWith actual current ifFuzzy controller neural network dynamic face controller is inputted, the mathematical model of EPS is write as
State equation form designs the first virtual controlling with firstorder filter with the method for retrogressing and restrains α2, the second virtual controlling restrain α3And reality
Border control law u2;Using the non-linear electric boosting steering system of radial base neural net online approximating, with based on Sigmoid
The parameter update law of function solves the parameter of nerve network system;Definition Lyapunov functions, the stability of analysis system,
Neural network dynamic face controller output controlled quentity controlled variable u2To EPS system.Specific configuration process is as follows:
1st step:Define first dynamic surface error:
S1=x1-x1d (1)
Take first virtual controlling rule
In formula:k1For adjustable design parameter, x1For assist motor electric current, x1dFor assist motor target current.Allow α2Pass through one
Rank filter, and from obtaining a new variable x2d:
In formula:τ2For filter time constant, x2dFor the desired value of the second state variable of EPS system.
2nd step:Define second dynamic surface error:
S2=x2-x2d (4)
Take second virtual controlling rule:
In formula:k2For adjustable design parameter, x2For the second state variable of EPS system.Allow α3By firstorder filter, and from
Obtain a new variable x3d:
τ in formula3For filter time constant, x3dFor the desired value of EPS system third state variable.
3rd step:Defining third dynamic surface error is:
S3=x3-x3d (7)
To S3Derivation:
In formula:x3For EPS system third state variable, f (x)=θTζ(x)+e3, θ be neural network ideal weights to
Amount, ζ (x) are the radial base vector based on Sigmoid functions, e3For neural network approximate error.
β=1/b, the practical controlled quentity controlled variable of controller is enabled to be designed as:
In formula:For the parameter Estimation of β, d, d is system interference item,For the parameter Estimation of θ;k3For adjustable design
Parameter.
Selecting All Parameters estimation self-adaptive is restrained:
Wherein, rθ、ρb、rb、ρd、rdFor adjustable parameter.
4th step defines Lyapunov functions, derivation, the stability of analysis system is carried out to it.
As shown in fig. 7, under composite power source powering mode, automatic disturbance rejection controller is seen by Nonlinear Tracking Differentiator (TD), expansion state
Four device (ESO), nonlinear feedback (NLSEF), disturbance compensation module compositions are surveyed, are write the mathematical model of EPS as state equation
Form, automatic disturbance rejection controller receive speed signal, steering-wheel torque signal, are obtained by searching for EPS assist characteristic databases
The target current i of EPS assist motorsobj, Nonlinear Tracking Differentiator is according to assist motor target current iobjObtain transition variable v1And its
Micro component v2, extended state observer is according to the actual current i of assist motorf, automatic disturbance rejection controller controlled quentity controlled variable u3Output observation
Electric boosting steering system state variable z1With state variable z2And expansion state variable z3, nonlinear feedback model
According to v1With z1Difference e1And v2With z2Difference e2Export the virtual controlling amount u of automatic disturbance rejection controller0, disturbance compensation mould
Block is by virtual controlling amount u0It is transformed to controlled quentity controlled variable u3。
Each module of automatic disturbance rejection controller indicates as follows:
Nonlinear Tracking Differentiator:
Extended state observer:
Nonlinear feedback:
Disturbance compensation:
Wherein, v1For the transition variable of motor target current, v2For the micro component of transition variable,For v1Derivative,For
v2Derivative, fhan () be Han Shi functions, r0For transition parameter, h is step-length, and e is the state variable z of observation1With motor reality
Electric current ifDifference, fe1For fal functions 1, fe2For fal functions 2, fal () is filter function, β01、β02、β03Device ratio in order to control
Example coefficient, b0For compensation factor, r flow gains in order to control, h1For dilution of precision.
Above example is merely to illustrate the design philosophy and feature of the present invention, and its object is to make technology in the art
Personnel can understand the content of the present invention and implement it accordingly, and protection scope of the present invention is not limited to the above embodiments.So all
Revealed principle, equivalent variations or modification made by mentality of designing according to the present invention, protection scope of the present invention it
It is interior.
Claims (6)
1. a kind of building method of the EPS controllers based on composite power source, which is characterized in that the EPS system of composite power source according to
Powering mode selects different control methods, and there are three types of powering modes for the composite power source tool:Composite power source powering mode, vehicle
Power supply powering mode and super capacitor powering mode;Under vehicle power supply powering mode, using fuzzy controller;Super capacitor
Under powering mode, using neural network dynamic face controller;Under composite power source powering mode, using automatic disturbance rejection controller;
Composite power source EPS controller multi-mode switch operating processes based on fuzzy monitor are:Fuzzy monitor is according to EPS systems
The output state of system, the output state of controller and powering mode switching law output weighting coefficient σ1、σ2、σ3;Weighting coefficient
σ1、σ2、σ3Respectively with the output u of corresponding controller1、u2、u3It is multiplied and carries out final output of the weighted sum processing as controller
U, wherein u1Output for the fuzzy controller being made of Fuzzy PID, u2It controls and calculates for neural network dynamic face
The output for the neural network dynamic face controller that method is constituted, u3For Active Disturbance Rejection Control Algorithm constitution automatic disturbance rejection controller it is defeated
Go out.
2. a kind of building method of EPS controllers based on composite power source according to claim 1, which is characterized in that institute
The switching law stated between powering mode is as follows:When EPS controllers are in vehicle power supply powering mode m2When, if EPS controllers
Detect the output voltage U of vehicle power supplydc<Udc0, vehicle power supply powering mode m2To super capacitor powering mode m1Switching;If
Controller detects speed v≤v0, and steering wheel angle θh>θh0, vehicle power supply powering mode m2To composite power source powering mode
m3Switching;
When controller is in composite power source powering mode m3When, if controller detects speed v>v0, composite power source powering mode m3
To vehicle power supply powering mode m2Switching;If controller detects the output voltage U of vehicle power supplydc<Udc0, composite power source power supply
Mode m3To super capacitor powering mode m1Switching;
When controller is in super capacitor powering mode m1When, if controller detects the output voltage U of vehicle power supplydc≥Udc0,
And speed v>Particular value v0, super capacitor powering mode m1To vehicle power supply powering mode m2Switching;If controller detects whole
The output voltage U of vehicle power supplydc≥Udc0, and speed v≤v0, and steering wheel angle θh>θh0, super capacitor powering mode m1
To composite power source powering mode m3Switching, wherein v0For the particular value of speed, θh0The particular value of steering wheel angle.
3. a kind of building method of EPS controllers based on composite power source according to claim 2, which is characterized in that institute
State the particular value v of speed0, steering wheel angle particular value θh0It is obtained by following steps:
Step 1, it establishes and is rubbed with ground based on friction binomial theory and the tire of Ka Te-Pohle Si Ji-richness bohr slip Theory
Power mathematical model is wiped, with ABAQUS finite element software simulation analysis frictional force with tire rolling speed, tyre deflection degree, wheel
The variation relation of tire yaw rate, vertical load, surface friction coefficient, fitting obtain the relational expression of frictional force;Pass through tire
Frictional force relational expression is verified with frictional ground force bench test;
Step 2, calculate aligning torque caused by Front wheel Alignment Parameters etc., the steering drag caused by tire and frictional ground force away from
With aligning torque caused by Front wheel Alignment Parameters etc. integrate to obtain low speed turn to comprehensive steering drag away from mathematical model;Turned with nothing
It is that object carries out low speed rotation to moment of resistance emulation, simultaneously on Matlab/Simulink platforms to the kart of force aid system
It is verified and is corrected by real train test;
Step 3, the simulation model of the kart verified based on experiment, builds the corresponding simulation model of heavy-duty commercial vehicle, imitates
True low speed steering resisting moment analyzes it with speed, the changing rule of steering wheel angle, heavy type is obtained using least square fitting
Commercial car steering resisting moment is about speed, the analytic expression of steering wheel angle;
Step 4, by the steering drag of heavy-duty commercial vehicle electricity is made away from the supply current conversed needed for electric boosting steering system
It flows with speed, the change curve of steering wheel angle, what electric current was constituted with the change curve of speed and by vehicle source nominal electric current
The intersection point of straight line is the particular value v of speed0, electric current is with the change curve of steering wheel angle and by vehicle source nominal electric current structure
At straight line intersection point be speed particular value θh0。
4. a kind of building method of EPS controllers based on composite power source according to claim 1, which is characterized in that packet
The database of assist characteristic containing EPS, PID controller, fuzzy rule base, fuzzy controller under the vehicle power supply powering mode
Building method is:Speed signal, steering-wheel torque signal are inputted into EPS assist characteristic databases, by searching for EPS assist characteristics
Database obtains the target current i of EPS assist motorsobj, by the target current i of EPS assist motorsobjWith actual current ifDifference
Value input PID controller, fuzzy rule base, fuzzy rule base export proportionality coefficient adjustment amount Δ K in PID controllerP, integration system
Number adjustment amount Δ KI, differential coefficient adjustment amount Δ KD, fuzzy controller output controlled quentity controlled variable u1To EPS system.
5. a kind of building method of EPS controllers based on composite power source according to claim 1, which is characterized in that institute
Stating neural network dynamic face controller building method under super capacitor powering mode is:By speed signal, steering-wheel torque signal
EPS assist characteristic databases are inputted, the target current i of EPS assist motors is obtained by searching for EPS assist characteristic databasesobj,
By the target current i of EPS assist motorsobjWith actual current ifNeural network dynamic face controller is inputted, by the mathematical modulo of EPS
Type is write as state equation form, designs the first virtual controlling with firstorder filter with the method for retrogressing and restrains α2, the second virtual controlling restrain α3
With practical control law u2;Using the non-linear electric boosting steering system of radial base neural net online approximating, with based on
The parameter update law of Sigmoid functions solves the parameter of nerve network system;Define Lyapunov functions, analysis system it is steady
Qualitative, neural network dynamic face controller exports controlled quentity controlled variable u2To EPS system.
6. a kind of building method of EPS controllers based on composite power source according to claim 1, which is characterized in that institute
Stating construction method for active-disturbance-rcontroller controller under composite power source powering mode is:Speed signal, steering-wheel torque signal input EPS are helped
Force characteristic database obtains the target current i of EPS assist motors by searching for EPS assist characteristic databasesobj, Nonlinear Tracking Differentiator
According to assist motor target current iobjObtain transition variable v1And its micro component v2, extended state observer is according to assist motor
Actual current if, automatic disturbance rejection controller controlled quentity controlled variable u3Export the state variable z of the electric boosting steering system of observation1And state
Variable z2And expansion state variable z3, nonlinear feedback model is according to v1With z1Difference e1And v2With z2Difference e2Output
The virtual controlling amount u of automatic disturbance rejection controller0, disturbance compensation module is by virtual controlling amount u0It is transformed to controlled quentity controlled variable u3, export to EPS
System.
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Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109376413A (en) * | 2018-10-08 | 2019-02-22 | 四川大学 | Line neural network method for diagnosing faults based on data-driven |
CN109639194A (en) * | 2019-01-21 | 2019-04-16 | 广西师范大学 | A kind of neural network of three axis holder servo motor and the composite control method of active disturbance rejection |
CN110001766A (en) * | 2019-03-18 | 2019-07-12 | 江苏大学 | A kind of assist characteristic curve design method under composite power source EPS fault mode |
CN110597052A (en) * | 2019-09-24 | 2019-12-20 | 武汉理工大学 | Fuel cell air supply controller and control method for quick dynamic response |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105826972A (en) * | 2016-03-21 | 2016-08-03 | 江苏吾度新能源科技有限公司 | New energy electric vehicle rapid charging conversion management device |
CN107089261A (en) * | 2017-03-17 | 2017-08-25 | 江苏大学 | A kind of integrated EPS distributed driving automobile steering control system and method |
-
2018
- 2018-03-27 CN CN201810258304.6A patent/CN108563845B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105826972A (en) * | 2016-03-21 | 2016-08-03 | 江苏吾度新能源科技有限公司 | New energy electric vehicle rapid charging conversion management device |
CN107089261A (en) * | 2017-03-17 | 2017-08-25 | 江苏大学 | A kind of integrated EPS distributed driving automobile steering control system and method |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109376413A (en) * | 2018-10-08 | 2019-02-22 | 四川大学 | Line neural network method for diagnosing faults based on data-driven |
CN109639194A (en) * | 2019-01-21 | 2019-04-16 | 广西师范大学 | A kind of neural network of three axis holder servo motor and the composite control method of active disturbance rejection |
CN110001766A (en) * | 2019-03-18 | 2019-07-12 | 江苏大学 | A kind of assist characteristic curve design method under composite power source EPS fault mode |
CN110597052A (en) * | 2019-09-24 | 2019-12-20 | 武汉理工大学 | Fuel cell air supply controller and control method for quick dynamic response |
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