CN106130425B - The building method of hybrid vehicle switching magnetic-resistance BSG system intelligent controllers - Google Patents
The building method of hybrid vehicle switching magnetic-resistance BSG system intelligent controllers Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
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Abstract
The present invention discloses a kind of building method of hybrid vehicle switching magnetic-resistance BSG system intelligent controllers,By current controller module,Power conversion modules and switched reluctance machines are sequentially connected in series,With current detection module,Disturbance Detection module is as a whole equivalent switch magnetic resistance BSG system,By the optimal controller for constructing switching magnetic-resistance BSG systems,Supporting vector machine controller and robust controller,Effectively improve the static and dynamic performance of system,Significantly improve the antijamming capability of system and robust control performance,The controller design is simple,It is convenient to realize,And control effect is preferable,By the parameter time varying characteristic and load sudden change of hybrid vehicle switching magnetic-resistance BSG systems,External disturbance is equivalent to the external disturbance variable of switching magnetic-resistance BSG systems,The nonlinear model of its anti-interference intelligent controller is established using support vector machines,Effectively increase the real-time and robustness of the controller.
Description
Technical field
The invention belongs to hybrid vehicle control field, more particularly to a kind of switching magnetic-resistance bands for hybrid electric vehicle
Formula driving starts the building method of the intelligent controller of generator (hereinafter referred to as BSG) system.
Background technology
Hybrid vehicle has outstanding advantages of high efficiency, low stain, and belt driven starter generator (BSG) is mixing
One of critical component of power vehicle, it is desirable that BSG can efficiently, steadily work.BSG be different from traditional automobile current generator be by
Starter motor and generator separate, and BSG rolls into one starter motor and generator, replace primary motor, can not only simplify in this way
Engine designs, and can reduce car weight.At present, BSG is mostly mixed excitation claw-pole motor, induction machine or magneto.
However for mixed excitation claw-pole motor, in low speed, acquisition high torque (HT) is more difficult, and complex rotor structure, is unfavorable for transporting at a high speed
Row；For induction machine, speed adjusting performance is poor, is not easy to be precisely controlled, more demanding to the control system of motor；For
Magneto, due to there are permanent-magnet material, so the stability under high temperature and high magnetic field environments is difficult to ensure that.And switching magnetic-resistance
Motor, suitable for high-speed cruising and adverse circumstances, has been applied to its simple and strong in structure, at low cost and high reliability
In BSG systems.
The control of hybrid vehicle switching magnetic-resistance BSG systems is controlled using industrial common angle position at present
The methods of system, Current cut control and voltage chopping control, this is difficult to be suitable for hybrid vehicle BSG systems, particularly
Hybrid electric vehicle sails the complexity of operating mode, certainly will bring the parameter time varyings of switching magnetic-resistance BSG systems, load sudden change and
The interference of various random perturbations.Therefore, in order to inherently solve hybrid vehicle switching magnetic-resistance BSG system convention controlling parties
The problem that method control effect is not good enough, while ensure hybrid vehicle switching magnetic-resistance BSG system items Control performance standards again,
Such as dynamic responding speed, steady-state tracking precision and stronger antijamming capability, new control method need to be used.
Patent application disclosed in domestic same technique field has：Chinese Patent Application No. is 201410232599.1, title
It is " a kind of hybrid electric vehicle BSG torque ripples compensating controller and its building method " that the patent document is directed to hybrid electric vehicle
BSG system torque fluctuations devise a kind of torque ripple compensating controller, for inhibiting the fluctuation of torque, torque ripple compensation
Controller forms current inner loop by design current compensating module to q shaft currents, can only eliminate torque ripple, and can not meet
The complex working condition of BSG systematic parameters time-varying and load sudden change；Moreover, the object of controller research is common alternating current generator, and
Non-switching magnetic-resistance motor.
Invention content
The purpose of the present invention is being directed to the existing defect of existing hybrid vehicle switching magnetic-resistance BSG systems, one kind is provided
Switching magnetic-resistance BSG system items Control performance standards, particularly the hybrid vehicle switching magnetic-resistance of robustness can be effectively improved
The building method of BSG system intelligent controllers, the anti-interference intelligent controller of support vector machines constructed can meet BSG systems ginseng
The complex working condition of number time-varying and load sudden change.
The technical solution adopted by the present invention is to include the following steps：
1) current controller module, power conversion modules and switched reluctance machines are sequentially connected in series, with current detection module,
Disturbance Detection module as a whole equivalent switch magnetic resistance BSG system, switching magnetic-resistance BSG systems to control electric current I to input,
Using speed omega as output, and establish the rotor dynamics equation of switching magnetic-resistance BSG systemsA, B is opened respectively
The velocity coeffficient and current coefficient of magnetic resistance BSG systems are closed, Γ is disturbance；
2) by speed omega and the speed signal reference value ω of speed preset module outputrIt compares, obtains speed error value
eω, speed error value eωFilter tracking error model through concatenation, speed controller module, clipping module and torque distribution successively
Electric current asks for output current after modulek1And k2Respectively filter tracking Error model coefficients；
3) using formulaOptimal controller is formed, it is approximant using support vector machinesSupporting vector machine controller is formed, by electric current r
Respectively as the of optimal controller, the input of support vector machines controller parameter optimization module and supporting vector machine controller
One input, by second of the output γ, σ of support vector machines controller parameter optimization module as supporting vector machine controller
Input, using formula G3=δ sign (r) build robust controller, and δ is coefficient variation, using electric current r as the first of robust controller
A input, using formulaRobust controller parameter optimization module is built, the input of robust controller parameter optimization module is
Parameter learning rate ηδ, export and beIt willSecond input as robust controller；The output of optimal controller is electric current IG1、
The output of supporting vector machine controller is electric current IG2, robust controller output be electric current IG3；
4) intelligent controller will be formed after optimal controller, supporting vector machine controller and robust controller parallel connection, it will
Electric current IG1、IG2And IG3It is combined output control electric current I.
Further, it is approximant using support vector machines in step 3)Form supporting vector machine controller method be：It will
Speed error value eωInput torque distributes current control module, torque distribution current control module output control electric current I, to speed
Error amount eωIt quadratures respectively and obtains ∫ e with derivationω(τ) d τ andTo speed signal reference value ωrAsk single order and second dervative
It obtainsWithForm the training sample set of support vector machinesOff-line training branch
Vector machine is held, obtains the reality output I of support vector machines*, export I*In include the actual numerical value of disturbance Γ, off-line training obtains
Supporting vector machine controller.
The beneficial effects of the invention are as follows：
1st, the optimal controller, supporting vector machine controller and robust of the invention by constructing switching magnetic-resistance BSG systems
Controller effectively improves the static and dynamic performance of hybrid vehicle switching magnetic-resistance BSG systems, significantly improves hybrid vehicle and open
Close the antijamming capability of magnetic resistance BSG systems and robust control performance.The controller design is simple, it is convenient to realize, and controls effect
Fruit is preferable.
2nd, by the parameter time varying characteristic and load sudden change, external disturbance of hybrid vehicle switching magnetic-resistance BSG systems
The external disturbance variable of switching magnetic-resistance BSG systems is equivalent to, the non-of its anti-interference intelligent controller is established using support vector machines
Linear model effectively increases the real-time and robustness of the controller, can effectively overcome existing patent
201410232599.1 existing during using neural network cross study, Local Minimum problem.
3rd, using the controller that is constructed of the present invention, it is only necessary to can survey, easily survey output and input variable, therefore do not need to
Increase additional detection device；Corresponding control algolithm only needs to realize by software programming, therefore the controller is not increasing
Under the premise of control cost, the Control platform of controller can be effectively improved.
Description of the drawings
Fig. 1 is by current controller module 11, power conversion modules 12, switched reluctance machines 13, current detection module 14
16 equivalent schematic of switching magnetic-resistance BSG systems formed with Disturbance Detection module 15；
Fig. 2 is to utilize speed preset module 21, filter tracking error model 41, speed controller module 42, clipping module
43rd, torque distribution electric current asks for module 51, optimal controller 61, supporting vector machine controller 62, supporting vector machine controller ginseng
The intelligent controller 7 that number optimization module 63, robust controller 64 and robust controller parameter optimization module 65 are formed is to switching magnetic
The structure diagram that resistance BSG systems 16 are controlled；
Fig. 3 is 62 off-line training functional block diagram of supporting vector machine controller in Fig. 2.
In figure：7. intelligent controller；11. current controller module；12. power conversion modules；13. switched reluctance machines；
14. current detection module；15. Disturbance Detection module；16. switching magnetic-resistance BSG systems；21. speed preset module；22. position is examined
Survey module；23. actual speed computing module；24. position feedback module；31. torque distributes current control module；41. filtering with
Track error model；42. speed controller module；43. clipping module；51. torque distribution electric current asks for module；61. optimal control
Device；62. supporting vector machine controller；63. support vector machines controller parameter optimization module；64. robust controller；65. robust
Controller parameter optimization module.
Specific embodiment
The building method that hybrid vehicle switching magnetic-resistance of the present invention starts Generator system control device is specific as follows：
As shown in Figure 1, by current controller module 11, power conversion modules 12, switched reluctance machines 13, current detecting mould
Block 14 and Disturbance Detection module 15 are equivalent to switching magnetic-resistance BSG systems 16 as an entirety, switching magnetic-resistance BSG systems 16 with
Electric current I is controlled as input, using speed omega as output.Wherein, current controller module 11, power conversion modules 12 and switching magnetic-resistance
Motor 13 is sequentially connected in series.Current detection module 14 obtains output as electric current I to the electric current of detection switch reluctance motor 131, will
Electric current I1Input current controller module 11.Current controller module 11 is to control electric current I as input, by control electric current I and electricity
Flow the electric current I that detection module 14 exports1It compares, so as to obtain the output of current controller module 11 as voltage U, voltage U
As the input of power conversion modules 12, the output of power conversion modules 12 is duty cycle signals T, and duty cycle signals T drives
Switched reluctance machines 13.Total disturbance Γ of 15 detection switch reluctance motor 13 of Disturbance Detection module, disturbance Γ include parameter
Time-varying, the mutation of load and uncertain disturbances etc., the output for finally obtaining switched reluctance machines 13 are speed omega.
Switching magnetic-resistance BSG systems 16 are analyzed, is equivalent with deriving, the rotor for establishing switching magnetic-resistance BSG systems 16 moves
Mechanical equation is：
In formula, ω and I are the speed of output of switching magnetic-resistance BSG systems 16 and the control electric current of input respectively；
It is the single order and second dervative of speed omega respectively；A and B is the velocity coeffficient and current coefficient of switching magnetic-resistance BSG systems 16 respectively,
Γ is disturbance, related with the parameters of switching magnetic-resistance BSG systems 16, load and uncertain disturbances, in this way, establishing switch magnetic
Hinder the kinetic model of BSG systems 16.According to the real work situation of switching magnetic-resistance BSG systems 16, A=141.3, B=are determined
96.2。
As shown in Fig. 2, the rotor-position signal of switching magnetic-resistance BSG systems 16 is obtained using the detection of position detecting module 22,
The output of position detecting module 22 is sequentially connected position feedback module 24 and actual speed computing module 23, by rotor-position signal
The speed omega of switching magnetic-resistance BSG systems 16 is obtained by position feedback module 24 and actual speed computing module 23, will be opened
Close the speed signal reference value ω that the speed omega of magnetic resistance BSG systems 16 is exported with speed preset module 21rIt compares, obtains speed
Error amount eω, by speed error value eωAs the input of filter tracking error model 41, filter tracking error model 41 will input
Error amount eωIn the value that significantly interferes with filter out, export as speed control signal vω, the output of filter tracking error model 41 is successively
Concatenation speed controller module 42, clipping module 43 and torque distribution electric current ask for module 51, by speed control signal vωInput
Speed controller module 42, speed control signal vωBe converted to torque control signal vT, in order to make torque control signal vTIt can guarantee
Within the scope of controllable, by torque control signal vTInput saturation module 43 makes torque control signal vTIt is limited to controllable model
Within enclosing, output obtains the torque control signal after amplitude limitThe control signalModule is asked for as torque distribution electric current
51 input, torque distribution electric current ask for module 51 by the torque control signal after amplitude limitReasonable distribution is carried out, and is obtained
Current output signal r, i.e. output current r by analysis, equivalent can obtain the expression formula of electric current r with derivation and be：
Wherein,It is eωFirst derivative, k1And k2Respectively filter tracking Error model coefficients, according to switching magnetic-resistance BSG
The real work situation of system 16, determines k1=207, k2=119.5.
Equation (1-1) and (1-2) are combined, and consider 16 parameter time varying of switching magnetic-resistance BSG systems, load sudden change etc. no
Deterministic perturbation characteristic, the analytical expression G that can obtain the anti-interference intelligent controller of switching magnetic-resistance BSG systems 16 are：
Wherein,
G3=δ sign (r) (1-6)
Wherein, sign () is sign function, and δ is the coefficient variation of robust controller 64.
For expression formula therein：
It is forced using support vector machines
Nearly analytical expression G2, supporting vector machine controller 62 is formed, it is specific as follows：It is shown in Figure 3, pass through position detecting module 22
The rotor-position signal of switching magnetic-resistance BSG systems 16 is collected, by rotor-position signal input actual speed computing module 23
Speed omega is obtained, the speed signal reference value ω that speed omega and speed preset module 21 are exportedrIt compares to obtain velocity error
Value eω, with speed error value eωAs the input of torque distribution current control module 31, torque distributes current control module 31
Electric current I in order to control is exported, and control electric current I is added to the input terminal of switching magnetic-resistance BSG systems 16.To speed error value eωPoint
It does not quadrature and derivation, obtains ∫ eω(τ) d τ andThe speed signal reference value ω exported to speed preset module 21rSeek single order
And second dervative, it obtainsWithAnd standardization processing is done to signal, form the training sample set of support vector machinesLast off-line training support vector machines, obtains the reality output of support vector machines
I*, comprising probabilistic actual numerical value for disturbing Γ in the output, so as to which off-line training obtains the support vector machines control in Fig. 2
Device 62 processed.Support vector machines is so used to approach to recognize G2Analytical expression forms supporting vector machine controller 62, effectively
Ground solves the problems, such as that uncertain disturbances Γ can not Accurate Model.
As shown in Fig. 2, torque distribution electric current is asked for into the output r of module 51 as the first of supporting vector machine controller 62
A input, while torque distribution electric current is asked for into the output r of module 51 as support vector machines controller parameter optimization module 63
Input, second as supporting vector machine controller 62 of the output γ, σ of support vector machines controller parameter optimization module 63
Input, γ, σ are support vector machines key parameter, according to the real work situation of switching magnetic-resistance BSG systems 16, determine γ=
300, σ=0.24；It is supported using Optimal Parameters γ, the σ real-time optimization that support vector machines controller parameter optimization module 63 exports
Vectorial machine controller 62, the output for obtaining supporting vector machine controller 62 are electric current IG2。
Using formula (1-4),Optimal controller 61 is built, torque distribution electric current is asked for into module 51
Output current r controllers 61 as an optimization input, the output for obtaining optimal controller 61 is electric current IG1。
Utilize formula (1-6), G3=δ sign (r) build robust controller 64, and torque distribution electric current is asked for module 51
First inputs of the output current r as robust controller 64.
Using the following formula (1-7),Build robust controller parameter optimization module 65, robust controller parameter
Parameter learning rate η of the input of optimization module 65 for robust controller parameter optimization module 65δ, export as robust controller coefficient
Variable first derivativeFirst derivativeAs second input of robust controller 64, the output of robust controller 64 is electric current
IG3。
According to the real work situation of switching magnetic-resistance BSG systems 16, η is determinedδ=1.09.
By the output current I of optimal controller 61G1, supporting vector machine controller 62 output current IG2And robust control
The output current I of device 64 processedG3It is combined, the input of output control electric current I, i.e. switching magnetic-resistance BSG systems 16, to control switch magnetic
Hinder BSG systems 16.
In this way, by support vector machines controller parameter optimization module 63, supporting vector machine controller 62, optimal controller
61st, after 65 parallel connection of robust controller 64 and robust controller parameter optimization module, it is serially connected in the filter tracking being in series successively
After error model 41, speed controller module 42, clipping module 43 and torque distribution electric current ask for module 51, with speed preset
Module 21 forms anti-interference intelligent controller 7 together, realizes the high-performance Shandong to hybrid vehicle switching magnetic-resistance BSG systems 16
Stick controls.
Claims (5)
1. a kind of building method of hybrid vehicle switching magnetic-resistance BSG system intelligent controllers, it is characterized in that including following step
Suddenly：
1) current controller module (11), power conversion modules (12) and switched reluctance machines (13) are sequentially connected in series, with electric current
Detection module (14), Disturbance Detection module (15) are as a whole equivalent switch magnetic resistance BSG system (16), switching magnetic-resistance BSG
System (16) is to control electric current I using speed omega as output, and to establish the rotor dynamic of switching magnetic-resistance BSG systems (16) as input
Learn equationA, B is the velocity coeffficient and current coefficient of switching magnetic-resistance BSG systems (16) respectively, and Γ is disturbs
It is dynamic；
2) by speed omega and the speed signal reference value ω of speed preset module (21) outputrIt compares, obtains speed error value
eω, speed error value eωFilter tracking error model (41) through concatenation, speed controller module (42), clipping module successively
(43) and torque distribution electric current asks for module (51) output current afterwardsk1And k2Respectively filter
Wave tracking error model coefficient；τ is eωIntegration time interval；
3) using formulaOptimal controller (61) is formed, it is approximant using support vector machinesSupporting vector machine controller (62) is formed, it will
Electric current r respectively as optimal controller (61), support vector machines controller parameter optimization module (63) input and support to
First input of machine controller (62) is measured, using output γ, σ of support vector machines controller parameter optimization module (63) as branch
Second input of vectorial machine controller (62) is held, using formula G3=δ sign (r) structure robust controllers (64), δ are that coefficient becomes
Amount, using electric current r as first input of robust controller (64), using formulaBuild robust controller parameter optimization
Module (65), the input of robust controller parameter optimization module (65) is parameter learning rate ηδ, output beIt willAs robust
Second input of controller (64)；The output of optimal controller (61) is electric current IG1, supporting vector machine controller (62) it is defeated
It is electric current I to go outG2And the output of robust controller (64) is electric current IG3；
4) intelligence control will be formed after optimal controller (61), supporting vector machine controller (62) and robust controller (64) parallel connection
Device processed, by electric current IG1、IG2And IG3It is combined output control electric current I.
2. the building method of hybrid vehicle switching magnetic-resistance BSG system intelligent controllers according to claim 1, feature
It is：In step 1), output current I after the electric current of current detection module (14) detection switch reluctance motor (13)1, current controller
Module (11) will control electric current I and electric current I1It compares, obtains voltage U, inputs of the voltage U as power conversion modules (12),
Power conversion modules (12) output duty cycle signal T, duty cycle signals T driving switch reluctance motor (13), Disturbance Detection module
(15) the disturbance Γ of detection switch reluctance motor (13).
3. the building method of hybrid vehicle switching magnetic-resistance BSG system intelligent controllers according to claim 1, feature
It is：In step 1), position detecting module (22) detection obtains the rotor-position signal of switching magnetic-resistance BSG systems (16), by rotor
Position signal obtains switching magnetic-resistance BSG systems (16) through position feedback module (24) and actual speed computing module (23) successively
Speed omega.
4. the building method of hybrid vehicle switching magnetic-resistance BSG system intelligent controllers according to claim 1, feature
It is：In step 2), speed error value eωOutput speed controls signal v to input filter tracking error model (41) afterwardsω, speed control
Signal vωInput speed controller module is converted to torque control signal v after (42)T, torque control signal vTInput saturation module
(43) output torque controls signal afterwardsTorque distribution electric current asks for module (51) by torque control signalIt is allocated acquisition
Current signal r.
5. the building method of hybrid vehicle switching magnetic-resistance BSG system intelligent controllers according to claim 1, feature
It is：A=141.3, B=96.2, k1=207, k2=119.5, γ=300, σ=0.24, ηδ=1.09.
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| CN103414432A (en) * | 2013-07-12 | 2013-11-27 | 江苏大学 | Construction method of hybrid electric vehicle belt driven starter generator controller |
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