CN106685303B - The empty composite braking optimization method of electricity under permanent magnetism tractor-trailer train demagnetization failure tolerant - Google Patents
The empty composite braking optimization method of electricity under permanent magnetism tractor-trailer train demagnetization failure tolerant Download PDFInfo
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- CN106685303B CN106685303B CN201510764441.3A CN201510764441A CN106685303B CN 106685303 B CN106685303 B CN 106685303B CN 201510764441 A CN201510764441 A CN 201510764441A CN 106685303 B CN106685303 B CN 106685303B
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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
- H02P21/0021—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using different modes of control depending on a parameter, e.g. the speed
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Abstract
The present invention relates to the empty composite braking optimal control method of electricity under a kind of permanent magnetism tractor-trailer train demagnetization failure tolerant, reduced for electric braking torque caused by permanent magnet synchronous motor demagnetization failure, brake shoe wears away and rises, is unfavorable for the problems such as recycling of Brake Energy.Demagnetized state monitoring is carried out in the rail vehicle traction stage, by from it is different demagnetization operating conditions and load working condition under simulation status features similarity mode, adaptive generation preferably air damping characteristic curve, to be matched with the electric braking characteristic curve of degeneration, under the premise of guaranteeing service braking distance and maximum longitudinal deceleration, keep Block brake as minimum as possible.This method is suitable for the empty composite braking control of rail traffic vehicles electricity of permanent magnet synchronous motor driving.
Description
Technical field
The present invention relates to the empty composite braking optimal control methods of electricity under a kind of permanent magnetism tractor-trailer train demagnetization failure tolerant, belong to
In rail traffic vehicles field.
Background technique
Traction electric machine is the key component of Train electrical traction, in recent years, with the fast development of power electronic technique, column
The traction electric machine of vehicle is just gradually replaced traditional dc motor by asynchronous ac motor.But traditional threephase asynchronous
The problem that volume is larger, weight is heavy, output torque is limited, transmission efficiency is low constrains high-speed railway and urban rail transit vehicles
Further development.Permanent magnet synchronous motor is since small in size, light-weight, high-efficient, power factor is high, structure is simple, reliability
High series of advantages obtains application in many industrial circles such as aviation, automobile.At present, grinding with emerging permanent-magnet material
Study carefully the reduction of exploitation and permanent-magnet material cost, permanent magnet synchronous motor is as train traction motor also increasingly by railroad engineer
Attention.But the development of permanent magnet synchronous motor trailer system is also faced with lot of challenges, includes multi- drive synchronization, anti-electricity
Kinetic potential, permanent magnet demagnetization etc..Wherein, the demagnetization risk of permanent magnet is the problem of generally worry, since rail traffic is using electricity system
Dynamic preferential, the braking control strategy of air damping supplement, demagnetization failure not only results in the reduction of pull-up torque, can also make electric system
Kinetic moment decline leads to the aggravation of brake shoe abrasion and feeds back to contact net so that the Brake Energy for making to consume on brake shoe rises
Regenerative braking energy decline.
Summary of the invention
The electricity sky composite braking optimization control demagnetized under failure tolerant the purpose of the present invention is to propose to a kind of permanent magnetism tractor-trailer train
Method processed mitigates brake shoe abrasion rising, the decline of electric braking utilization rate caused by the electric braking torque because of caused by demagnetization reduces
Etc. health characteristics degenerate problem.
In order to reach above-mentioned purpose of design, The technical solution adopted by the invention is as follows:
The empty composite braking optimal control method of electricity under permanent magnetism tractor-trailer train demagnetization failure tolerant, considers demagnetization operating condition and load
Lotus operating condition, it is empty on this basis by braking moment during numerical simulation acquisition electric braking with the characteristic curve of velocity variations
Gas brake force compensates total brake force；The method includes the numerical simulation stage, offline optimization stage and the weighting of phase reliability
Three steps are matched, specific implementation method is as follows:
(1) the numerical simulation stage: three-phase permanent magnet synchronous motor d-q equation model is used, different demagnetization operating conditions and load are passed through
Train traction stage running data under lotus operating condition, the operation data include time, 3 phase currents, 3 phase voltages, linear speeds
Degree, displacement of the lines and output torque obtain data characteristic information, to constitute historical data matrix；The load working condition is choosing sky
Carry (AW0), seat visitor (AW1), fully loaded (AW2) and overload (AW3) on the basis of 4 kinds of operating conditions, inserted at equal intervals again between every kind of operating condition
Enter 3 load working conditions；The demagnetization amount that demagnetization operating condition chooses 3%, 6%, 9%, 12%, 15% and 18% is emulated；
The equation that permanent-magnetic synchronous motor stator voltage is listed under d-q coordinate system, is shown below:
ud=R1id+pψd-ωψq (1)
uq=R1iq+pψq+ωψd (2)
Wherein: p is differential operator, and ω is rotor rotation angular rate, ψdFor stator magnetic linkage direct-axis component, ψqFor stator magnet
Chain quadrature axis component；udFor stator voltage direct-axis component, uqFor stator voltage quadrature axis component；idFor stator voltage direct-axis component, iqFor
Stator voltage quadrature axis component；R1For stator resistance；
Stator magnetic linkage equation such as following formula under d-q coordinate system:
ψd=ψf+Ldid (3)
ψq=Lqiq (4)
Wherein: stator magnetic linkage direct-axis component ψdThe armature reacting field L generated including armature supply direct-axis componentdidWith turn
Sub- permanent magnetic field ψfTwo parts, stator magnetic linkage quadrature axis component ψqOnly include the armature reacting field of armature supply quadrature axis component generation
Lqiq；
Shown in the torque of permanent magnet synchronous motor and the equation of motion such as formula (5), formula (6):
Wherein: TeFor electromagnetic torque, TfFor drag torque, J is rotary inertia, npFor permanent magnet pole logarithm, B is damping system
Number；Simulation process carries out under simulink or labview platform, respectively record the time, 3 phase currents, 3 phase voltages, linear velocity,
Displacement of the lines and output torque amount to 10 groups of data, are used for offline optimization；Three-phase permanent magnet synchronous motor is obtained in different loads simultaneously
State characteristic under operating condition and demagnetization operating condition, constitutes historical data matrix D；
Wherein: MnIt is the train weight that air spring is monitored under n-th of operating condition；Idn、IqnFor under n-th of operating condition, three
Phase current obtained d-q phase current after coordinate transform；vnThe maximum speed accelerated to by train；tvnTo accelerate to highest
Time used in speed；
(2) characteristic curve that air brake force changes the offline optimization stage: is set as the quintic algebra curve about speed:
Fp=[k1,k2...k6]·[1,v1,v2...v5]T
Use quintic algebra curve coefficient for the object of optimization, the target of optimization is to keep Brake Energy consumed by brake block most
May be minimum, while guaranteeing the average retardation rate of train is 1m/s2, maximum deceleration be no more than emergency braking deceleration want
It asks, i.e. 1.3m/s2.Optimization method is as follows:
Constraint condition: v (t)=0
S (t) < 190m
amax< 1.3m/s2
Coefficient after optimized is constituted under n operating condition, establishes torque coefficient sample matrix K:
Wherein: kmnFor m-1 term coefficient under n-th of demagnetization operating condition；
(3) similarity mode weight phase: the data and historical data that train is measured in real time on the way are carried out based on space
Similarity weight is generated after the similarity mode of distance, and summation, gained are weighted to the torque sample matrix after different operating conditions
The quintic algebra curve that torque coefficient sample is constituted is air damping characteristic needed for this braking process；
The state vector in train traction stage:
Yin=[Mt,Idt,Iqt,tvt,vt]t
By the similarity mode with historic state matrix D, similarity weight is calculated, is shown below:
Oeprator in upperIt represents and takes turns doing similarity operation between the vector of each object, can usually choose based on Europe
The similarity of the space lengths such as family name's distance, mahalanobis distance, manhatton distance, similarity calculation mode are as follows:
Summation is weighted to the torque coefficient matrix by optimization using weight vector:
kt=K ωt=[kt1,kt2...kt6]
ktThe quintic algebra curve relevant to speed being fitted, the air brake force of required addition is special when as this time braking
Linearity curve optimizes energy consumed by train braking brake shoe.The multinomial mode of fitting is as follows:
Fpt=kt·[1,v1,v2...v5]T。
In the present invention, the modern optimization algorithms such as classic optimisations algorithm or genetic algorithm such as Newton method are can be selected in optimization algorithm,
It can be selected according to engineering practice.
The present invention offline optimizes the air brake force under different operating conditions using optimization algorithm.
Optimization algorithm includes that can select the classic optimisations such as Newton method algorithm or genetic algorithm, simulated annealing as needed
The modern optimization algorithms such as algorithm, and reserved corresponding setting interface.
The target of optimization is the average retardation rate for keeping Brake Energy consumed by brake block as minimum as possible, while making train
Guarantee to be 1m/s2, deceleration requirement of the maximum deceleration no more than emergency braking, i.e. 1.3m/s2。
The quintic algebra curve being set as about speed of electric braking force and air brake force with speed, air brake force multinomial
Coefficient be the object optimized, multinomial coefficient constitutes torque coefficient sample matrix under the different operating conditions after optimization, for into one
The similarity mode of step is prepared.
By numerical simulation, the train traction stage running data for obtaining different loads operating condition and demagnetizing under operating condition, including
Quality measured by air spring, d-q electric current, maximum speed and the time spent in accelerate to maximum speed etc., constitute history
Data matrix.Train generates phase after monitoring obtained data on the way and carrying out based on the similarity mode of space length with historical data
Like degree weight, summation is weighted to the torque coefficient sample matrix after different operation optimizations, resulting torque coefficient is constituted
Quintic algebra curve be air damping characteristic needed for this braking process.
The empty composite braking optimal control method of electricity under a kind of permanent magnetism tractor-trailer train demagnetization failure tolerant of the present invention
By numerical simulation, offline optimization, similarity mode and weighting, urban rail transit vehicles are become in load working condition
In the case where change, adaptively reconcile air brake force characteristic, thus reduce because demagnetization caused by brake shoe abrasion rise with
And the problem of electric braking utilization rate decline.
The present invention and the prior art the difference is that, the prior art is able to achieve the cooperation of electric braking and air damping,
But the target usually controlled is to maintain constant deceleration, not to permanent magnet synchronous motor demagnetization failure and its service life optimal control side
Method takes in.
Detailed description of the invention
Fig. 1 is the implementation process of the control method.
Fig. 2 is the process connection between each step.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples:
As shown in Figure 1, implementation steps of the invention include three numerical simulation, offline optimization, Similarity-Weighted matching steps
Suddenly, specific implementation method is as follows:
Numerical simulation model uses three-phase permanent magnet synchronous motor d-q equation model.
According to train load standard, whole train load working condition is chosen are as follows: 220t, 240.16t, 331.6t, 375.52t
Rotor flux is chosen for 4.20wb, 4.05wb, 3.90wb, 3.75wb, 3.60wb, wherein rotor flux normal condition
For 4.20wb, remaining is corresponding to be different demagnetization operating condition.
Stator resistance R1=0.12 Ω, braking resistor RB=1.9 Ω, d-q inductance Id=Iq=0.00824H.
By numerical simulation, while obtaining state of the three-phase permanent magnet synchronous motor under different loads operating condition and demagnetization operating condition
Characteristic constitutes historic state matrix D.
In optimization process, the characteristic curve of air brake force variation is set as the quintic algebra curve about speed:
Fp=[k1,k2...k6]·[1,v1,v2...v5]T=k1+k2·v1+...+k6·v5
Quintic algebra curve coefficient is the object of optimization, and the target of optimization is to make Brake Energy consumed by brake block as far as possible
Minimum, while guaranteeing the average retardation rate of train is 1m/s2(service braking distance is 190m when speed per hour 70km/h), maximum subtracts
Speed is no more than the deceleration requirement of emergency braking, i.e. 1.3m/s2.Optimization method is as follows:
S.t.v (t)=0
S (t) < 190m
amax< 1.3m/s2
The modern optimization algorithms such as classic optimisations algorithm or genetic algorithm such as Newton method can be selected in optimization algorithm, can be according to engineering
Actual conditions are selected.
Coefficient after optimized is constituted under n operating condition, torque coefficient sample matrix K:
During similarity mode, the state vector in train traction stage is measured in real time on the way first, in the present embodiment, turn
Sub- magnetic flux size is 4.00wb (demagnetization 0.2wb), and train load operating condition is 320t, obtains traction state vector through emulation:
Yin=[Mt,Idt,Iqt,tvt,vt]t=[320,18.3812, -0.11,33.80,70]t
By the similarity mode with historic state matrix D, similarity weight is calculated, is shown below:
Oeprator in upperIt represents and takes turns doing similarity operation between the vector of each object, can usually choose based on Europe
The similarity of the space lengths such as family name's distance, mahalanobis distance, manhatton distance, similarity calculation mode are as follows:
In the present embodiment, manhatton distance similarity is selected.
Summation is weighted to the torque coefficient matrix by optimization using weight vector:
ktThe quintic algebra curve relevant to speed being fitted, the air brake force of required addition is special when as this time braking
Linearity curve optimizes energy consumed by train braking brake shoe.The multinomial mode of fitting is as follows:
Fpt=[1, v1,v2...v5]T·kt=2.67e4-1.69e3v+335.46v2-32.49v3+0.59v4+
0.0102v5
In the deboost phase, required Block brake power is calculated according to train running speed and is applied.
In the present embodiment, brake shoe Brake Energy 1561kJ on single bogie, maximum deceleration are -1.17m/s2, and 1m/
s2Permanent deceleration-based controller Brake Energy be 1692kJ.In the present embodiment, system optimizing control can allow maximum deceleration model
In enclosing, Block brake is made to can be reduced 7.74%.
Those skilled in the art can do various modifications or additions to specific embodiment
Or be substituted in a similar manner, however, it does not deviate from the spirit of the invention and range defined in the appended claims.
Claims (2)
- The empty composite braking optimal control method of the electricity under failure tolerant 1. permanent magnetism tractor-trailer train demagnetizes, it is characterised in that consider demagnetization Operating condition and load working condition, by braking moment during numerical simulation acquisition electric braking with the characteristic curve of velocity variations, herein On the basis of air brake force total brake force is compensated；The method includes the numerical simulation stage, offline optimization stage and phase Like degree three steps of weighted registration, specific implementation method is as follows:(1) the numerical simulation stage: three-phase permanent magnet synchronous motor d-q equation model is used, different demagnetization operating conditions and load work are passed through Train traction stage running data under condition, the operation data include time, 3 phase currents, 3 phase voltages, linear velocity, lines Displacement and output torque obtain data characteristic information, to constitute historical data matrix；The load working condition is choosing unloaded, seat On the basis of objective, fully loaded and 4 kinds of operating conditions of overload, it is inserted into 3 load working conditions at equal intervals again between every kind of operating condition；Operating condition of demagnetizing choosing 3%, 6%, 9%, 12%, 15% and 18% demagnetization amount is taken to be emulated；The equation that permanent-magnetic synchronous motor stator voltage is listed under d-q coordinate system, is shown below:ud=R1id+pψd-ωψq (1)uq=R1iq+pψq+ωψd (2)Wherein: p is differential operator, and ω is rotor rotation angular rate, ψdFor stator magnetic linkage direct-axis component, ψqFor stator magnetic linkage friendship Axis component；udFor stator voltage direct-axis component, uqFor stator voltage quadrature axis component；idFor stator voltage direct-axis component, iqFor stator Quadrature axis component of voltage；R1For stator resistance；Stator magnetic linkage equation such as following formula under d-q coordinate system:ψd=ψf+Ldid (3)ψq=Lqiq (4)Wherein: stator magnetic linkage direct-axis component ψdThe armature reacting field L generated including armature supply direct-axis componentdidForever with rotor Magnetic magnetic field ψfTwo parts, stator magnetic linkage quadrature axis component ψqOnly include the armature reacting field L of armature supply quadrature axis component generationqiq；Shown in the torque of permanent magnet synchronous motor and the equation of motion such as formula (5), formula (6):Wherein: TeFor electromagnetic torque, TfFor drag torque, J is rotary inertia, npFor permanent magnet pole logarithm, B is damped coefficient；Simulation process carries out under simulink or labview platform, records time, 3 phase currents, 3 phase voltages, linear speed respectively Degree, displacement of the lines and output torque amount to 10 groups of data, are used for offline optimization；Three-phase permanent magnet synchronous motor is obtained in different loads simultaneously State characteristic under lotus operating condition and demagnetization operating condition, constitutes historical data matrix D；Wherein: MnIt is the train weight that air spring is monitored under n-th of operating condition；Idn、IqnFor under n-th of operating condition, three-phase electricity Flow through obtained d-q phase current after coordinate transform；vnThe maximum speed accelerated to by train；tvnTo accelerate to maximum speed Time used；(2) characteristic curve that air brake force changes the offline optimization stage: is set as the quintic algebra curve about speed:Fp=[k1,k2...k6]·[1,v1,v2...v5]TUse quintic algebra curve coefficient for the object of optimization, the target of optimization is to make Brake Energy consumed by brake block as far as possible Minimum, while guaranteeing the average retardation rate of train is 1m/s2, maximum deceleration be no more than emergency braking deceleration requirement, That is 1.3m/s2；Optimization method is as follows:Constraint condition: v (t)=0S (t) < 190mamax< 1.3m/s2Coefficient after optimized is constituted under n operating condition, establishes torque coefficient sample matrix K:Wherein: kmnFor m-1 term coefficient under n-th of demagnetization operating condition；(3) similarity mode weight phase: the data and historical data that train is measured in real time on the way are carried out based on space length Similarity mode after generate similarity weight, summation, gained torque are weighted to the torque sample matrix after different operating conditions The quintic algebra curve that coefficient sample is constituted is air damping characteristic needed for this braking process；The state vector in train traction stage:Yin=[Mt,Idt,Iqt,tvt,vt]TBy the similarity mode with historic state matrix D, similarity weight is calculated, is shown below:Oeprator in upperIt represents and takes turns doing similarity operation between the vector of each object, choose and be based on Euclidean distance, geneva The similarity of distance or manhatton distance space length, similarity calculation mode are as follows:Summation is weighted to the torque coefficient matrix by optimization using weight vector:kt=K ωt=[kt1,kt2...kt6]ktThe air damping force characteristic of the quintic algebra curve relevant to speed being fitted, required addition when as this time braking is bent Line optimizes energy consumed by train braking brake shoe；The multinomial mode of fitting is as follows:Fpt=kt·[1,v1,v2...v5]T。
- 2. according to the method described in claim 1, it is characterized in that optimization algorithm selects Newton method or heredity to calculate in step (2) Method can be selected according to engineering practice.
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