CN103944481B - A kind of AC Motor Vector Control System model parameter on-line amending method - Google Patents

A kind of AC Motor Vector Control System model parameter on-line amending method Download PDF

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CN103944481B
CN103944481B CN201410174726.7A CN201410174726A CN103944481B CN 103944481 B CN103944481 B CN 103944481B CN 201410174726 A CN201410174726 A CN 201410174726A CN 103944481 B CN103944481 B CN 103944481B
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parameter
constant
motor
electric machine
torque
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CN103944481A (en
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谭冠政
谭冠军
范必双
刘振焘
邓泽林
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中南大学
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Abstract

The invention discloses a kind of AC Motor Vector Control System model parameter on-line amending method, at load constant timing controlled motor speed, make motor speed keep constant and eliminate the impact of rotor flux coupling terms on dynamic state of parameters on-line identification.The present invention can meet the pinpoint accuracy of the dynamic on-line identification of the parameter of electric machine and the requirement of real-time.

Description

A kind of AC Motor Vector Control System model parameter on-line amending method

Technical field

The present invention relates to variable-frequency control technique field, particularly a kind of AC Motor Vector Control System model parameter on-line amending method.

Background technology

The use of the parameter of electric machine is all related to, as the decoupling computation etc. of magnetic flux calculating, torque calculation, magnetic flux angle calculation and d axle excitation component and q shaft torque component based on a lot of link of rotor field-oriented Vector Control System for Asynchronous Machine.Therefore the order of accuarcy of parameter of electric machine identification determines precision and the effect of vector control.Upgrading AC Motor Vector Control System model parameter real-time and accurately, is realize the prerequisite that high performance vector controls variable-frequency control technique.

Current parameter of electric machine offline identification method is equal comparative maturity in theory and practical application, and can reach higher parameter of electric machine identification precision.But the parameter of electric machine can be subject to the impact of the factors such as temperature rise and change in motor operation course, if parameter real-time update cannot be accomplished in running, then can cause very large impact to vector control effect, therefore in motor operation course, on-line identification be carried out to the parameter of electric machine and be necessary very much.

Current parameter of electric machine on-line identification algorithm is if it were not for realization complexity, and can take a large amount of cpu resources, real-time cannot ensure, it is exactly poor stability, easily affect by factors such as noise jamming, or under good given initial condition will be ensured, good identification precision could be obtained.In the middle of numerous parameter of electric machine recognizers, RLS is little due to amount of calculation, does not need large matrix to invert, and calculating and convergence rate comparatively fast, are widely adopted in engineering reality.But this algorithm is only successfully applied at present in parameter of electric machine off-line identification, and for on-line parameter identification, due to the impact that the rotating speed and magnetic linkage that cannot eliminate motor conversion are coupled, when motor mathematical model is not simplified, recursive least-squares cannot be applied recursive operation is carried out to the parameter of electric machine.Also RLS is utilized to carry out on-line identification calculating to the parameter of electric machine in existing on-line parameter discrimination method, but completely based on carrying out under a kind of prerequisite of hypothesis, namely suppose that motor speed is constant, is therefore also only limitted to simulation study, cannot applies in practice.

Vector control is the main flow of current industrial system frequency-changing speed-regulating application, it is on the Mathematical Modeling basis analyzing AC induction motor, by coordinate transform and rotor field-oriented, realize the full decoupled of stator current torque component and excitation component, obtain the dynamic mathematical models of similar direct current machine, then analog DC motor controls, and can obtain good quiet, dynamic property.Its shortcoming is that control precision depends on stator resistance R s, rotor resistance R r, stator inductance L s, inductor rotor L r, mutual inductance L metc. the accurate identification of multiple parameter of electric machine, especially the accuracy of detection of magnetic linkage closed-loop control system rotor magnetic flux is by rotor time constant τ rr=L r/ R r) impact comparatively large, due to rotor time constant τ r(mainly rotor resistance) affects comparatively large by factors such as temperature, in motor whole service process, change can reach 150%, must detect by real-time online.Therefore the correct identification of the parameter of electric machine is the prerequisite that vector control system realizes high performance motor speed governing.The method that the conventional offline parameter of electric machine detects has unloaded and stall experiment, but is often subject to the restriction of field condition and cannot implements.Some intelligent control algorithms such as particle cluster algorithm, ant group algorithm, genetic algorithm, neural net etc. have good precision for the offline inspection of the parameter of electric machine, but amount of calculation is very large, and convergence rate is not suitable for parameter slowly in line computation.Least square method of recursion is good to sensitivity to parameter, calculates and fast convergence rate, synchronously disposablely can pick out whole parameter, and highly versatile.But most research is in order to simplify computational process, is on actionless basis by Mathematical Models at motor, therefore can only be used for the static identification of parameter of electric machine off-line.Therefore how to simplify the computation model of the dynamic on-line identification of the parameter of electric machine further, raising computational speed and precision enter practical application for quickening parameter of electric machine on-line checkingi algorithm, and the performance improving motor vector control is most important.

Summary of the invention

Technical problem to be solved by this invention is, not enough for prior art, provides a kind of AC Motor Vector Control System model parameter on-line amending method, meets real-time and the pinpoint accuracy requirement of parameter of electric machine on-line identification.

For solving the problems of the technologies described above, the technical solution adopted in the present invention is: a kind of AC Motor Vector Control System model parameter on-line amending method, comprises the following steps:

1) motor initial parameter is accurately obtained by the static discrimination method of the parameter of electric machine: stator resistance R s, rotor resistance R r, stator inductance L s, inductor rotor L rwith mutual inductance L m(between stator and rotor mutual inductance);

2) using the parameter of above-mentioned motor initial parameter as vector control system model, for controlling driven by motor load running;

3) in load constant timing, double above on original basis if rotating speed controls fluctuation, constant control is carried out to rotor flux;

4) when rotor flux is constant, by torque reference electric current given for closed loop switch to constant reference torque current , make output electromagnetic torque keep constant;

5) control motor speed, when motor speed is constant, on-line identification calculating is carried out to motor initial parameter, obtain the up-to-date parameter of electric machine;

6) the up-to-date parameter of electric machine is utilized to upgrade the motor initial parameter participating in calculating in vector control system model, simultaneously by constant reference torque current switch to torque reference electric current , and cancel the constant control to rotor flux.

Described step 5) in, described step 5) in, to motor three-phase voltage u a, u b, u cwith three-phase current i a, i b, i csample, through coordinate transform, be separately converted to the excitation under two-phase rest frame and torque component u sd, u sqand i sd, i sq, and by u sd, u sqand i sd, i sqas input, recursive least-squares calculating is carried out to the parameter of electric machine.

Compared with prior art, the beneficial effect that the present invention has is: method of the present invention is carried out when motor load is constant, make it keep constant at load constant timing controlled motor speed to eliminate the impact of rotor flux coupling terms on dynamic state of parameters on-line identification, substantially increase accuracy and the real-time of the dynamic on-line identification of the parameter of electric machine.

Accompanying drawing explanation

Fig. 1 is one embodiment of the invention AC Motor Vector Control System model framework chart;

Fig. 2 is one embodiment of the invention flux estimator model framework chart;

Fig. 3 is one embodiment of the invention parameter of electric machine dynamic on-line identification rotor flux experimental waveform figure;

Fig. 4 is one embodiment of the invention parameter of electric machine dynamic on-line identification motor speed experimental waveform figure;

Fig. 5 is one embodiment of the invention parameter of electric machine dynamic on-line identification rotor resistance experimental waveform figure.

Embodiment

As shown in Figure 1, one embodiment of the invention parameter of electric machine dynamic on-line identification module Real-time Collection voltage, electric current and motor speed signal utilize least square method of recursion to carry out parameter of electric machine calculating, contain a flux ring in system, form the closed loop constant control to rotor flux.

Fig. 2 is flux estimator model framework chart, estimates as long as utilize d shaft voltage and current signal can complete rotor flux.

Fig. 3 is the parameter of electric machine dynamic on-line identification rotor flux experimental waveform, and before carrying out Dynamic Identification, setting rotor resistance with reference to initial value is R s=1.405 Ω, and increase by 0.5 Ω when being allowed to condition at 6.15 seconds, saltus step is to R s=1.905 Ω, and from this moment K switch 2 path shown in Fig. 1 is cut off, K switch 3 closes, closed-loop control is carried out to rotor flux, make it be tending towards steady state, after dynamic on-line parameter identification terminates, cancel the constant control (disconnecting K3, closed K2) to rotor flux.

Fig. 4 is the parameter of electric machine dynamic on-line identification motor speed experimental waveform, whole process, twice adjustment is carried out to motor speed reference value, first time is carried to 800r/min from 400r/min, second time is carried to 1200r/min from 800r/min again, its actual speed produces fluctuation between 6.15 seconds and 7.2 seconds, because there is larger Identification Errors at this time period rotor resistance, so have impact on the performance of this time period closed-loop vector control system, in addition during parameter of electric machine identification, due to will invariablenes turning speed be kept, so by torque reference electric current as shown in Figure 1 switch to artificially given torque reference electric current , thus rotating speed is within 7.0 seconds ~ 8.0 second time period and there is velocity deviation between reference rotation velocity.

Fig. 5 is the parameter of electric machine dynamic on-line identification rotor resistance experimental waveform, and because between 6.15 to 7.1 seconds, rotor flux and motor speed are also unstable, the rotor resistance identification result fluctuation therefore in this interval is larger.But along with rotor flux and speed become constant, rotor resistance identification result restrains gradually close to reference value.After rotor resistance on-line identification is completed, control system model parameter is upgraded, and cutting speed inner ring controls, then as shown in Figure 4, when second time motor raises speed, because control system model parameter is accurate, velocity deviation and steady state ripple are eliminated completely, and system presents ideal velocity close-loop control performance.

The dynamic on-line identification method of the parameter of electric machine of the present invention specifically comprises following steps:

Step one: obtain motor initial parameter accurately by the static identification of the parameter of electric machine: stator resistance R s, rotor resistance R r, stator inductance L s, inductor rotor L rwith mutual inductance L m;

Step 2: using the initial motor parameter obtained as the parameter of vector control system model, for controlling motor belt motor load running;

Step 3: in load constant timing, double above (as being ± 1% originally on original basis if rotating speed controls fluctuation, become now ± 2%), illustrate that the parameter of electric machine there occurs significant change, cause control system model parameter inaccurate, thus system control performance is declined, now cut rotor flux ψ rdcontrol module, (cut off by K switch 2 path shown in Fig. 1, K switch 3 closes, and carries out closed-loop control, makes it be tending towards steady state, can make ψ by pi regulator to rotor flux to carry out constant control to rotor flux rdclose , and a given constant, namely rotor flux is stablized);

Step 4: when rotor flux is constant, by torque reference electric current given for closed loop switch to artificially given constant reference torque current constant magnetic flux and torque current make to export electromagnetic torque and also keep constant, in load constant timing, rotating speed also will keep constant, but now there will be certain deviation between rotating speed and set-point, but it is the time very short (on-line parameter identification computing time once) that this rotating speed deviation exists, little to control system entire effect;

Step 5: when controlling rotating speed and making it reach constant, starter motor dynamic state of parameters on-line identification module, carries out on-line identification calculating to the parameter of electric machine;

Step 6: after the dynamic on-line identification of the parameter of electric machine terminates, is used for upgrading in each module of vector control system the parameter of electric machine participating in calculating, gains the torque reference electric current that closed loop is given simultaneously by the parameter of electric machine of up-to-date acquisition , and cancel rotor flux ψ rdconstant control.

Concrete principle is derived as follows:

The dynamic mathematical models of induction asynchronous machine are shown below:

d 2 i sd dt 2 = - ( ξ + 1 τ r ) di sd dt + L m η - τ r ξ τ r 2 i sd + 1 σ L s du sd dt + 1 σ L s τ r u sd - ω r di sq dt + ωr ( η L m τ r - ξ ) i sq + ω r σ L s u sq + η d ω r dt ψ rq - - - ( 1 )

Wherein σ = 1 - L m 2 L s L r , η = L m σ L s L r , ξ = R s σ L s + L m 2 σ L s L r T r , I sd, i sqfor stator current vector d, q axle component under two-phase rest frame, u sd, u sqfor stator voltage vector d, q axle component under two-phase rest frame, ψ rd, ψ rqfor two-phase rest frame lower rotor part flux linkage vector d, q axle component, τ rfor rotor time constant, L s, L rfor motor stator and rotor inductance, R s, R rfor motor stator and rotor resistance parameters, L mfor motor mutual inductance, σ is motor flux leakage coefficient.

For formula (1), as motor speed ω rconstant and non-vanishing time, ω rfor constant, have then can last relate to flux linkage calculation item to cancellation by formula, thus eliminate the impact of magnetic linkage coupling on parameter identifier.But when the parameter of electric machine changes, motor speed be kept constant, prerequisite must keep load to be constant, and it is constant to control rotor flux.According to torque formula:

T em = p L m L r i sq ψ rd - - - ( 2 )

In formula, p is motor number of pole-pairs, visible as rotor flux ψ rdwhen keeping constant, electromagnetic torque is with torque current i sqproportionally change, as long as holding torque current constant, just can stable electrical magnetic torque export, when load is constant, motor speed also just can be stablized.When motor speed is stablized, the magnetic linkage item ψ in formula (1) rqitem just can be eliminated, thus obtains:

d 2 i sd dt 2 = - ( ξ + 1 τ r ) di sd dt + L m η - τ r ξ τ r 2 i sd + 1 σ L s du sd dt + 1 σ L s τ r u sd - ω r di sq dt + ω r ( η L m τ r - ξ ) i sq + ω r σ L s u sq - - - ( 3 )

Stablize rotor flux, first will estimate rotor flux, in orientation on rotor flux system, induction machine electric current and voltage computation model are:

i rd = 1 L r ( ψ rd - L m i sd ) u sd = R s i sd + L s di sd dt + L m di rd dt - - - ( 4 )

Differential is carried out to first formula of formula (4), and to substitute in second formula of formula (4):

dψ rd dt = L r L m [ u sd - R s i sd - ( L s - L m 2 L r ) di sd dt ] - - - ( 5 )

Carry out integration to formula (5) both sides again to obtain:

ψ rd = L r L m [ ∫ ( u sd - R s i sd ) dt - σ L s i sd ] - - - ( 6 )

By the rotor flux computation model designed by formula (6) as shown in Figure 2.Only need detect voltage and current signal, and computational process does not relate to this parameter of electric machine of rotor resistance of the easiest temperature influence.

In vector control system, add magnetic flux closed-loop control, for stable rotor flux, least square method of recursion can be utilized to carry out dynamic state of parameters on-line identification by formula (3) when stabilization of speed.First formula (3) is expressed as:

d 2 i sd dt 2 = λ 1 di sd dt + λ 2 i sd + λ 3 du sd dt + λ 4 u sd - λ 5 di sq dt + λ 6 i sq + λ 7 u sq - - - ( 7 )

λ in formula 1~ λ 7for:

λ 1 = δ 1 + δ 2 - 1 T s 2 - - - ( 8 )

λ 2 = δ 3 + δ 4 T s 2 - - - ( 9 )

λ 3 = δ 3 T s - - - ( 10 )

λ 4 = δ 1 - 2 T s - - - ( 11 )

λ 5=ω r(12)

λ 6 = ω r ( η L m τ r - ξ ) - - - ( 13 )

λ 7 = ω r σ L s - - - ( 14 )

Wherein ω rfor constant, discretization is carried out to formula (7) and obtains:

i sd ( k + 2 ) = ( λ 1 T s + 2 ) i sd ( k + 1 ) + ( λ 2 T s 2 - 1 ) i sd ( k ) + λ 3 T s u sd ( k + 1 ) + ( λ 4 T s 2 - λ 3 T s ) u sd ( k ) - λ 5 T s i sq ( k + 1 ) + ( λ 6 T s 2 + λ 5 T s ) i sq ( k ) + λ 7 T s 2 u sq ( k ) - - - ( 15 )

Change formula (15) into least square form:

Y(k)=Φ(k)θ(k)+δ(k)(16)

Wherein Y (k)=i sd (k+2), other is:

Φ(k)=[i sd(k+1)i sd(k)u sd(k+1)u sd(k)i sq(k+1)i sq(k)u sq(k)](17)

θ ( k ) = λ 1 T s + 2 λ 2 T s 2 - 1 λ 3 T s λ 4 T s 2 - λ 3 T s - λ 5 T s λ 6 T s 2 + λ 5 T s λ 7 T s 2 T = δ 1 δ 2 δ 3 δ 4 δ 5 δ 5 δ 7 T - - - ( 18 )

In order to calculate δ 1~ δ 7seven parameters, input and output need to carry out 8 times with up-sampling, and carry out least square method of recursion calculating:

θ ^ ( n + 1 ) = θ ^ ( n ) + G n + 1 [ Y ( n + 1 ) - Φ T ( n + 1 ) θ ^ ( n ) ] - - - ( 19 )

G n + 1 = C n Φ ( n + 1 ) ϵ + Φ T ( n + 1 ) C n Φ ( n + 1 ) - - - ( 20 )

C n + 1 = C n - G n + 1 Φ T ( n + 1 ) C n ϵ - - - ( 21 )

In formula: G n+1for gain matrix, C n+1for covariance matrix, ε is forgetting factor (0< η≤1).Its computational process is as follows:

(1) initialization: C 0=10 ki, k get larger positive integer,

&theta; ^ ( 0 ) = 10 - 3 10 - 3 10 - 3 1 - 3 10 - 3 10 - 3 1 - 3 T , &epsiv; = 1 .

(2) according to actual measurement output valve Φ (n+1) and C nvalue utilizes formula (20) calculated gains matrix G n+1.

(3) by G n+1with (19) formula of substitution calculates one group of new parameter

(4) subsequent time covariance matrix C is calculated according to formula (21) n+1.

(5) recursive operation that (2) step is carried out next time is forwarded to.

Claims (1)

1. an AC Motor Vector Control System model parameter on-line amending method, is characterized in that, comprise the following steps:
1) motor initial parameter is accurately obtained by the static discrimination method of the parameter of electric machine: stator resistance R s, rotor resistance R r, stator inductance L s, inductor rotor L rwith mutual inductance L m;
2) using the parameter of above-mentioned motor initial parameter as vector control system model, for controlling driven by motor load running;
3) in load constant timing, double above on original basis if rotating speed controls fluctuation, constant control is carried out to rotor flux;
4) when rotor flux is constant, by torque reference electric current given for closed loop switch to constant reference torque current output electromagnetic torque is made to keep constant;
5) control motor speed, when motor speed is constant, on-line identification calculating is carried out to motor initial parameter, obtain the up-to-date parameter of electric machine;
6) the up-to-date parameter of electric machine is utilized to upgrade the motor initial parameter participating in calculating in vector control system model, simultaneously by constant reference torque current switch to torque reference electric current and the constant control of cancelling rotor flux;
Described step 5) in, on-line identification calculates and refers to motor three-phase voltage u a, u b, u cwith three-phase current i a, i b, i csample, through coordinate transform, be separately converted to the excitation under two-phase rest frame and torque component u sd, u sqand i sd, i sq, and by u sd, u sqand i sd, i sqas input, recursive least-squares calculating is carried out to the parameter of electric machine.
CN201410174726.7A 2014-04-28 2014-04-28 A kind of AC Motor Vector Control System model parameter on-line amending method CN103944481B (en)

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CN104362927B (en) * 2014-10-14 2017-02-15 浙江大学 Asynchronous motor key state information tracking method based on improved particle swarm optimization
CN105071735B (en) * 2015-07-31 2017-08-22 西安理工大学 Asynchronous machine energy-saving control method based on the simplified models of T 1
CN105490605A (en) * 2015-12-16 2016-04-13 上海新时达电气股份有限公司 Online adjustment method for prediction control model parameters of induction motor
CN107404271B (en) * 2017-08-21 2019-11-26 西安交通大学 A kind of non-synchronous motor parameter online recognition system and method
CN109256996A (en) * 2018-11-12 2019-01-22 河南工学院 Parameter self-tuning and frequency-changing control system and its unified device, parameter identification method

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CN102594253B (en) * 2012-02-21 2014-10-08 常州联力自动化科技有限公司 Parameter off-line identifying method and device of three-phase asynchronous motor
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