CN103684182A - Parameter identification method of permanent magnet synchronous motor - Google Patents

Abstract

A parameter identification method of a permanent magnet synchronous motor. A conventional model is improved with reference to an adaptive structure, i.e., based on an original MRAS1 module, a new MRAS2 module is constructed, so that a cascade model reference adaptive control (CMRAS) module is constructed; the MRAS1 is used for identification of a rotor speed; and the MRAS2 is used for identification of a stator resistance and rotor flux. In the invention, while the rotor speed is fed back in the real time manner, the stator resistance and rotor flux identification value is fed back to a vector control system, so that an influence of motor parameters on the system can be effectively lessened; and since the stator resistance identification value is updated in the real time manner at the low speed, the low speed control performance of the system can be effectively improved.

Description

A kind of permagnetic synchronous motor parameter identification method

Technical field

The invention belongs to electric machines control technology field, relate to a kind of permagnetic synchronous motor parameter identification method based on cascade model reference adaptive (CMRAS).

Background technology

Permagnetic synchronous motor (Permanent Magnet Synchronous Motor, PMSM) be the complex object of a multivariable, close coupling, non-linear, variable element, there is the advantages such as high accuracy, high dynamic performance, high reliability, small size, in high accuracy and high reliability request occasion, obtain extensive use.In recent years in permanent magnet synchronous motor vector control system, in order to overcome the defects such as use that mechanical pick-up device brings expensive, installation and maintenance are difficult, antijamming capability decline, reliability reduction, the Speedless sensor technology that obtains speed and positional information by various method of estimation, has become one of study hotspot in Motor Control Field.In numerous Speedless sensor motor control methods, model reference adaptive (Model Reference Adapt System, MRAS) because of its have algorithm not too the asymptotic Convergence Property, stable state accuracy of complexity, good in anti-interference performance, assurance parameter Estimation compared with advantages of higher, be subject to people and pay attention to, be suggested and be applied in permagnetic synchronous motor Speedless sensor vector control.Its basic thought be using not containing the equation of unknown parameter as with reference to model, containing needing the equation of estimated parameter as adjustable model, input signal acts on reference model and adjustable model simultaneously, and adaptive mechanism is adjusted controller parameter according to the generalized error of two model-composings makes generalized error go to zero to reach the object of adjustable model track reference model.Tradition MRAS needs accurate estimated position deviation, although Mathematical Modeling is accurate, estimated accuracy is subject to the impact that the parameter of electric machine changes, and cannot break away from the dependence to the parameter of electric machine.

Summary of the invention

The object of the present invention is to provide a kind of permagnetic synchronous motor parameter identification method, can carry out the identification of spinner velocity, stator resistance and rotor flux simultaneously, effectively weaken the parameter of electric machine and change the impact on system, improve the low speed control performance of system.

Technical scheme of the present invention is, a permagnetic synchronous motor parameter identification method, improves traditional model reference adaptive structure, is retaining on the basis of original MRAS1 module, newly set up MRAS2 module, build cascade model reference adaptive (CMRAS) module; Wherein MRAS1 realizes the identification of spinner velocity, and MRAS2 realizes the identification of stator resistance and rotor flux.

Feature of the present invention is also:

MRAS1 module, using permagnetic synchronous motor itself as with reference to model, using the current model that contains speed of permanent magnetic synchronous electromotor rotor as adjustable model, feeds back to current model the spinner velocity of identification, the spinner velocity identifier of output

after PI regulates, feed back to current model and realize closed-loop control.According to adaptive input error constantly adjust

until error

be zero, spinner velocity identifier

also just reached actual value ω _r; After obtaining stable spinner velocity identifier, sent into MRAS2 module, MRAS2 module is chosen PMSM conduct itself with reference to model, the parameter of adjustable model is output as reference with motor, the state equation of motor adopts the state equation based on dq axle, adopt the Popov superstability Theorem deduction identical with MRAS1, can obtain the identification algorithm of stator resistance and rotor flux.

CMRAS is input as motor measuring amount: i _d, i _q, u _d, u _q.Wherein, i _dwith i _qobtain in the following manner: by the stator winding current i of permagnetic synchronous motor module _a, i _b, i _c, be input to 3/2 coordinate transformation module in control circuit, obtain the current component i under two-phase rest frame _α, i _β, then be input to 2/2 coordinate transformation module, obtain the current component i under two-phase rotating coordinate system _d, i _q; u _dwith u _qobtain in the following manner: reference rotor speed w _r* with feedback spinner velocity w _rdifference by PI controller, obtain reference current i _q*, i _q* with feedback current i _qdifference through PI controller, obtain reference voltage u _q, reference current i _d* with feedback current i _ddifference by PI controller, obtain reference voltage u _d.CMRAS is output as spinner velocity, stator resistance and rotor flux, wherein spinner velocity is carried out to the positional information that integral operation can obtain rotor;

According to Popov superstability theorem, the identification algorithm of speed of permanent magnetic synchronous electromotor rotor, stator resistance and rotor flux can be expressed as:

${\widehat{\mathrm{\ω}}}_r=\underset{0}{\overset{t}{\∫}}{K}_i(i_d{\hat{i}}_q-i_q{\hat{i}}_d-\frac{{\widehat{\mathrm{\ψ}}}_r}{L_s}(i_q-{\hat{i}}_q))\mathrm{d\τ}+K_p(i_d{\hat{i}}_q-i_q{\hat{i}}_d-\frac{{\widehat{\mathrm{\ψ}}}_r}{L_s}(i_q-{\hat{i}}_q))+{\widehat{\mathrm{\ω}}}_r\left(0\right)---\left(1\right)$

$\frac{{\hat{R}}_s}{L_s}=\frac{R_s}{L_s}-K_1\underset{0}{\overset{t}{\∫}}(u_d(i_d-{\hat{i}}_d)+u_q(i_q-{\hat{i}}_q))\mathrm{dt}-K_2(u_d(i_d-{\hat{i}}_d)+u_q(i_q-{\hat{i}}_q))---\left(2\right)$

$\frac{{\widehat{\mathrm{\&psi;}}}_r}{L_s}=\frac{{\mathrm{\&psi;}}_r}{L_s}-{\mathrm{<figure-callout\; id="1"\; label="K"\; filenames="HDA0000414199540000022.png"\; state="\{\{state\}\}">K</figure-callout>}}_1\underset{0}{\overset{t}{\&Integral;}}{\widehat{\mathrm{\&omega;}}}_r(i_q-{\hat{i}}_q)\mathrm{dt}-K_2{\widehat{\mathrm{\&omega;}}}_r(i_q-{\hat{i}}_q)---\left(3\right)$

In identification process, first utilize the off-line identification value of stator resistance and rotor flux to carry out rotor speed omega _ridentification, when estimation spinner velocity is when stable and spinner velocity set-point is constant, its identification process step is as follows:

1) first by (1) formula, calculate spinner velocity identification result

2) will calculate

substitution (2) formula calculates

obtain Stator resistance identification result

3) will calculate substitution (3) formula calculates obtain rotor flux identification result

4) order ${\mathrm{\&omega;}}_r={\widehat{\mathrm{\&omega;}}}_r,R_s={\hat{R}}_s,{\mathrm{\&psi;}}_r={\widehat{\mathrm{\&psi;}}}_r,$ Upgrade identification result.

Spinner velocity, stator resistance and rotor flux information that CMRAS module identification is obtained feed back in permanent magnet synchronous motor vector control system loop, thereby realize the PMSM vector control based on CMRAS.

Above-mentioned vector control system comprises speed outer shroud and current inner loop two parts, also comprises main circuit, current signal detection circuit and control circuit; The motor rotor speed that CMRAS module identification obtains and rotor position information thereof are as the feedback quantity of controlling, reference rotor speed w _r* with feedback spinner velocity w _rdifference by PI controller, obtain reference current i _q*, i _q* with feedback current i _qdifference through PI controller, obtain reference voltage u _q, reference current i _d* with feedback current i _ddifference by PI controller, obtain reference voltage u _d, the u obtaining _qand u _dthrough anti-Park conversion, obtain u _α, u _β, the u obtaining _α, u _βby SVPWM, there is the adjusting of module, produce the work of PWM ripple control inverter, thereby drive the running of permagnetic synchronous motor module; And stator resistance and rotor flux that 8 identifications of CMRAS module obtain feed back to the mode by software in vector control algorithm, thus the control performance of raising system.

The present invention has following beneficial effect:

1, the present invention is retaining on the basis of original MRAS1 module, newly set up MRAS2 module, wherein MRAS1 carries out the identification of spinner velocity, MRAS2 carries out the identification of stator resistance and rotor flux, this has just formed cascade model reference adaptive system, can carry out the identification of spinner velocity, stator resistance and rotor flux simultaneously.

2, the present invention is by Real-time Feedback spinner velocity, stator resistance and rotor flux identifier are also fed back to vector control system, can effectively weaken the parameter of electric machine and change the impact on system, when low speed, due to real-time update Stator resistance identification value, can effectively improve the low speed control performance of system.

3, through experimental verification, CMRAS algorithm of the present invention is due to real-time update Stator resistance identification value when low speed, and in the time of can effectively weakening low speed, stator resistance changes the impact on system, than traditional MRAS algorithm, has better low speed control performance.

Accompanying drawing explanation

Fig. 1 is for the present invention is based on the permanent magnet synchronous motor vector control system block diagram of cascade model reference adaptive (CMRAS);

Fig. 2 is the basic structure block diagram that the present invention is based on conventional model reference adaptive algorithm;

Fig. 3 is the spinner velocity identification principle block diagram that the present invention is based on conventional model reference adaptive algorithm;

Fig. 4 is stator resistance and the rotor flux identification principle block diagram that the present invention is based on conventional model reference adaptive algorithm;

Fig. 5 is permagnetic synchronous motor parameter (comprising spinner velocity, stator resistance and rotor flux) the identification algorithm block diagram that the present invention is based on cascade model reference adaptive;

In Fig. 1,1. inverter, 2.PMSM module, 3. signal deteching circuit, 4.Clark conversion, 5.Park conversion, 6.SVPWM module, 7. anti-Park conversion, 8. cascade model reference adaptive (CMRAS) module.

Embodiment

Below in conjunction with the drawings and specific embodiments, the invention will be further described.

A permagnetic synchronous motor parameter identification method, improves traditional model reference adaptive structure,, retaining on the basis of original MRAS1 module, newly sets up MRAS2 module, is configured to cascade model reference adaptive (CMRAS) module; Wherein MRAS1 realizes the identification of spinner velocity, and MRAS2 realizes the identification of PMSM stator resistance and rotor flux.When Real-time Feedback spinner velocity, stator resistance and rotor flux identifier are also fed back to vector control system simultaneously, can effectively weaken the parameter of electric machine and change the impact on system.When low speed, due to real-time update Stator resistance identification value, can effectively improve the low speed control performance of system.

MRAS1 module, using permagnetic synchronous motor itself as with reference to model, using the current model that contains speed of permanent magnetic synchronous electromotor rotor as adjustable model, feeds back to current model the spinner velocity of identification, the spinner velocity identifier of output

after PI regulates, feed back to current model and realize closed-loop control.According to adaptive input error

constantly adjust

until error

be zero, spinner velocity identifier

also just reached actual value ω _r; After obtaining stable spinner velocity identifier, sent into MRAS2 module, MRAS2 module is chosen PMSM conduct itself with reference to model, the parameter of adjustable model is output as reference with motor, the state equation of motor adopts the state equation based on dq axle, adopt the Popov superstability Theorem deduction identical with MRAS1, can obtain the identification algorithm of stator resistance and rotor flux.

CMRAS is input as motor measuring amount: i _d, i _q, u _d, u _q.Wherein, i _dwith i _qobtain in the following manner: by the stator winding current i of permagnetic synchronous motor module _a, i _b, i _c, be input to 3/2 coordinate transformation module in control circuit, obtain the current component i under two-phase rest frame _α, i _β, then be input to 2/2 coordinate transformation module, obtain the current component i under two-phase rotating coordinate system _d, i _q; u _dwith u _qobtain in the following manner: reference rotor speed w _r* with feedback spinner velocity w _rdifference by PI controller, obtain reference current i _q*, i _q* with feedback current i _qdifference through PI controller, obtain reference voltage u _q, reference current i _d* with feedback current i _ddifference by PI controller, obtain reference voltage u _d.CMRAS is output as spinner velocity, stator resistance and rotor flux, wherein spinner velocity is carried out to the positional information that integral operation can obtain rotor.

Spinner velocity, stator resistance and rotor flux information that CMRAS module identification is obtained feed back in permanent magnet synchronous motor vector control system loop, thereby realize the PMSM vector control based on CMRAS.

MRAS is a kind of parameter identification method based on stability Design, has guaranteed the asymptotic convergence of parameter identification.As shown in Figure 2, its main thought be using not containing the equation of unknown parameter as with reference to model, and using the equation that contains parameter to be identified as adjustable model, the error of utilizing two models to have the output variable of same physical meaning forms suitable adaptive law and regulates in real time adjustable model parameter to be identified, finally reaches the object of the output tracking reference model of control object.

Below in conjunction with permagnetic synchronous motor Mathematical Modeling, parameter identification method involved in the present invention is done to following derivation:

The stator current Mathematical Modeling of known permagnetic synchronous motor under rotating coordinate system is

$\left\{\begin{array}{c}\frac{{\mathrm{di}}_d}{\mathrm{dt}}=-\frac{R_s}{L_s}{i}_d+{\mathrm{\&omega;}}_r{i}_q+\frac{u_d}{L_s}\\ \frac{{\mathrm{di}}_q}{\mathrm{dt}}=-{\mathrm{\&omega;}}_r{i}_d-\frac{R_s}{L}{i}_q+\frac{u_q-{\mathrm{\&omega;}}_r{\mathrm{\&psi;}}_r}{L}\end{array}\right.---\left(4\right)$

In formula, u _d, u _qfor the component of stator voltage at dq axle; i _d, i _qfor the component of stator current at dq axle; R _s, L _sfor stator resistance, inductance; ω _rfor spinner velocity, ψ _rfor rotor flux.

Formula (4) is rewritten as:

$\frac{d}{\mathrm{dt}}\left(\begin{array}{c}{i}_d+\frac{{\mathrm{\&psi;}}_r}{L_s}\\ i_q\end{array}\right)=\left(\begin{array}{cc}-\frac{R_s}{L_s}& {\mathrm{\&omega;}}_r\\ -{\mathrm{\&omega;}}_r& -\frac{R_s}{L_s}\end{array}\right)\left(\begin{array}{c}{i}_d+\frac{{\mathrm{\&psi;}}_r}{L_s}\\ i_q\end{array}\right)+\frac{1}{L_s}\left(\begin{array}{c}{u}_d+\frac{R_s{\mathrm{\&psi;}}_r}{L_s}\\ u_q\end{array}\right)---\left(5\right)$

Order

$\left\{\begin{array}{c}{i}_d^{\&prime;}=i_d+\frac{{\mathrm{\&psi;}}_r}{L_s}\\ i_q^{\&prime;}=i_q\\ u_d^{\&prime;}=u_d+\frac{R_s{\mathrm{\&psi;}}_r}{L_s}\\ u_q^{\&prime;}=u_q\end{array}\right.$

By formula (5), can be obtained

$\frac{d}{\mathrm{dt}}\left(\begin{array}{c}{i}_d^{\&prime;}\\ i_q^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}-\frac{R_s}{L_s}& {\mathrm{\&omega;}}_r\\ -{\mathrm{\&omega;}}_r& -\frac{R_s}{L_s}\end{array}\right)\left(\begin{array}{c}{i}_d^{\&prime;}\\ i_q^{\&prime;}\end{array}\right)+\frac{1}{L_s}\left(\begin{array}{c}{u}_d^{\&prime;}\\ u_q^{\&prime;}\end{array}\right)---\left(6\right)$

Formula (6) is abbreviated as

$\frac{d}{\mathrm{dt}}{i}_s^{\&prime;}={\mathrm{Ai}}_s^{\&prime;}+{\mathrm{Bu}}_s^{\&prime;}---\left(7\right)$

In formula $i_s^{\&prime;}=\left(\begin{array}{c}{i}_d^{\&prime;}\\ i_q^{\&prime;}\end{array}\right),u_s^{\&prime;}=\left(\begin{array}{c}{u}_d^{\&prime;}\\ u_q^{\&prime;}\end{array}\right),A=\left(\begin{array}{cc}-\frac{R_s}{L_s}& {\mathrm{\&omega;}}_r\\ -{\mathrm{\&omega;}}_r& -\frac{R_s}{L_s}\end{array}\right).$

Adjustable model is

$\left(\begin{array}{c}\frac{d\widehat{i_d^{\&prime;}}}{\mathrm{dt}}\\ \frac{d\widehat{i_q^{\&prime;}}}{\mathrm{dt}}\end{array}\right)=\left(\begin{array}{cc}-\frac{R_s}{L_s}& \widehat{{\mathrm{\&omega;}}_r}\\ -\widehat{{\mathrm{\&omega;}}_r}& -\frac{R_s}{L_s}\end{array}\right)\left(\begin{array}{c}\widehat{i_d^{\&prime;}}\\ \widehat{i_q^{\&prime;}}\end{array}\right)+\frac{1}{L_s}\left(\begin{array}{c}{u}_d^{\&prime;}\\ u_q^{\&prime;}\end{array}\right)---\left(8\right)$

Be abbreviated as

$\frac{d}{\mathrm{dt}}\widehat{i_s^{\&prime;}}=A^{\&prime;}\widehat{i_s^{\&prime;}}+{\mathrm{Bu}}_s^{\&prime;}---\left(9\right)$

According to Popov superstability theorem, can be suc as formula the spinner velocity identification algorithm shown in (1):

${\widehat{\mathrm{\&omega;}}}_r=\underset{0}{\overset{t}{\&Integral;}}{K}_{i1}(i_d{\hat{i}}_q-i_q{\hat{i}}_d-\frac{{\widehat{\mathrm{\&psi;}}}_r}{L_s}(i_q-{\hat{i}}_q))\mathrm{d\&tau;}+K_{p1}(i_d{\hat{i}}_q-i_q{\hat{i}}_d-\frac{{\widehat{\mathrm{\&psi;}}}_r}{L_s}(i_q-{\hat{i}}_q))+{\widehat{\mathrm{\&omega;}}}_r\left(0\right)---\left(1\right)$

In formula (1), i _dand i _qmotor measured value,

with

by adjustable model, calculated, the adaptive law of spinner velocity as shown in Figure 3,

after pi regulator effect, produced rate signal

can force adjustable model (adaptive model) to be estimated

with actual i _s' trend is consistent, makes stator current vector error convergence in zero, also just makes spinner velocity estimated value

approach gradually spinner velocity actual value ω _r.

Figure 4 shows that stator resistance and rotor flux identification principle block diagram based on MRAS, choose motor conduct itself with reference to model, the parameter of adjustable model is output as reference with motor, the state equation of motor still adopts the state equation based on dq axle, simultaneously when identification stator resistance and rotor flux, the estimation spinner velocity value using will be carried out first-order filtering to actual estimated value, and the filtering time is larger, thereby guarantees the level and smooth stable of spinner velocity value.According to Popov superstability theorem, can be suc as formula stator resistance and the rotor flux identification algorithm shown in (2), (3):

$\frac{{\hat{R}}_s}{L_s}=\frac{R_s}{L_s}-K_{i2}\underset{0}{\overset{t}{\&Integral;}}(u_d(i_d-{\hat{i}}_d)+u_q(i_q-{\hat{i}}_q))\mathrm{dt}-K_{p2}(u_d(i_d-{\hat{i}}_d)+u_q(i_q-{\hat{i}}_q))---\left(2\right)$

$\frac{{\widehat{\mathrm{\&psi;}}}_r}{L_s}=\frac{{\mathrm{\&psi;}}_r}{L_s}-{\mathrm{<figure-callout\; id="3"\; label="K\; i"\; filenames="HDA0000414199540000011.png"\; state="\{\{state\}\}">K</figure-callout>}}_i\underset{0}{\overset{t}{\&Integral;}}{\widehat{\mathrm{\&omega;}}}_r(i_q-{\hat{i}}_q)\mathrm{dt}-{\mathrm{<figure-callout\; id="3"\; label="K\; p"\; filenames="HDA0000414199540000011.png"\; state="\{\{state\}\}">K</figure-callout>}}_p{\widehat{\mathrm{\&omega;}}}_r(i_q-{\hat{i}}_q)---\left(3\right)$

In formula (2), (3), in equation, only contain i _d, i _q, u _dand u _qthese motor operating measurement amounts, ω _rfor identification amount, the form of equation is basic multiplication, addition and integration accumulation calculating.

In the permagnetic synchronous motor parameter based on cascade model reference adaptive (comprising spinner velocity, stator resistance and rotor flux) the identification algorithm block diagram shown in Fig. 5, first adopt the off-line identification value of stator resistance and rotor flux to carry out rotor speed omega _ridentification, when estimation spinner velocity is when stable and spinner velocity set-point is constant, its identification process step is as follows:

1) first by (1) formula, calculate spinner velocity identification result

2) by (2) formula, calculate again

obtain Stator resistance identification result

3) will calculate

substitution (3) formula calculates

obtain rotor flux identification result

4) order ${\mathrm{\&omega;}}_r={\widehat{\mathrm{\&omega;}}}_r,R_s={\hat{R}}_s,{\mathrm{\&psi;}}_r={\widehat{\mathrm{\&psi;}}}_r,$ Upgrade identification result.

Spinner velocity, stator resistance and rotor flux information that CMRAS module identification is obtained feed back in permanent magnet synchronous motor vector control system loop, thereby realize the PMSM vector control based on CMRAS, can carry out the identification of spinner velocity, stator resistance and rotor flux simultaneously, can effectively weaken the parameter of electric machine and change the impact on system.When low speed, due to real-time update Stator resistance identification value, can effectively improve the low speed control performance of system.

Permagnetic synchronous motor parameter identification method of the present invention, adopts vector control system, also comprises main circuit, current signal detection circuit and control circuit; Vector control system comprises speed outer shroud and current inner loop two parts, referring to Fig. 1.Main circuit comprises inverter 1 and PMSM module 2, and current signal detection circuit 3 detects the three-phase current of motor under three phase static coordinate system by Hall element, gets two-phase output current i wherein _a, i _b, through Clarke conversion 4, the current value i under convert to static two phase coordinate systems _α, i _β.At speed ring, the motor rotor speed that 8 identifications of CMRAS module obtain and rotor position information thereof be as the feedback quantity of controlling, the reference rotor w that hastens _r* with the feedback rotor w that hastens _rdifference by PI controller, obtain reference current i _q*, i _q* with feedback current i _qdifference through PI controller, obtain reference voltage u _q, reference current i _d* with feedback current i _ddifference by PI controller, obtain reference voltage u _d, the u obtaining _qand u _dthrough anti-Park conversion module 7, obtain u _α, u _β, the u obtaining _α, u _βby SVPWM, there is the adjusting of module 6, produce 1 work of PWM ripple control inverter, thereby drive 2 runnings of permagnetic synchronous motor module; And stator resistance and rotor flux that 8 identifications of CMRAS module obtain feed back to the mode by software in vector control algorithm, thus the control performance of raising system.

The present invention is directed to the parameter of electric machine and change the not high problem of traditional MRAS estimated accuracy causing, propose a kind of permagnetic synchronous motor Speedless sensor vector control strategy based on cascade model reference adaptive (CMRAS), can carry out the identification of spinner velocity, stator resistance and rotor flux simultaneously.Checking by experiment, CMRAS algorithm can effectively weaken the parameter of electric machine and change the impact on system; When low speed, due to real-time update Stator resistance identification value, can effectively improve the low speed control performance of system.The method has certain reference value for research and the engineering application of permagnetic synchronous motor Speedless sensor vector control.

Claims (5)

1. a permagnetic synchronous motor parameter identification method, is characterized in that: traditional model reference adaptive structure is improved,, retaining on the basis of original MRAS1 module, newly set up MRAS2 module, be configured to cascade model reference adaptive CMRAS module; Wherein MRAS1 realizes the identification of spinner velocity, and MRAS2 realizes the identification of stator resistance and rotor flux.

2. permagnetic synchronous motor parameter identification method as claimed in claim 1, it is characterized in that: MRAS1 module is using permagnetic synchronous motor itself as with reference to model, using the current model that contains speed of permanent magnetic synchronous electromotor rotor as adjustable model, the spinner velocity of identification is fed back to current model, the spinner velocity identifier of output

after PI regulates, feed back to current model and realize closed-loop control; According to adaptive input error

constantly adjust

until error

be zero, spinner velocity identifier also just reached actual value ω _r; After obtaining stable spinner velocity identifier, sent into MRAS2 module, MRAS2 module is chosen PMSM conduct itself with reference to model, the parameter of adjustable model is output as reference with motor, the state equation of motor adopts the state equation based on dq axle, adopt the Popov superstability Theorem deduction identical with MRAS1, can obtain the identification algorithm of stator resistance and rotor flux.

3. permagnetic synchronous motor parameter identification method as claimed in claim 2, is characterized in that: CMRAS is input as motor measuring amount: i _d, i _q, u _d, u _q, wherein, i _dwith i _qobtain in the following manner: by the stator winding current i of permagnetic synchronous motor module _a, i _b, i _c, be input to 3/2 coordinate transformation module in control circuit, obtain the current component i under two-phase rest frame _α, i _β, then be input to 2/2 coordinate transformation module, obtain the current component i under two-phase rotating coordinate system _d, i _q; u _dwith u _qobtain in the following manner: reference rotor speed w _r* with feedback spinner velocity w _rdifference by PI controller, obtain reference current i _q*, i _q* with feedback current i _qdifference through PI controller, obtain reference voltage u _q, reference current i _d* with feedback current i _ddifference by PI controller, obtain reference voltage u _d, CMRAS is output as spinner velocity, stator resistance and rotor flux, wherein spinner velocity is carried out to the positional information that integral operation can obtain rotor;

According to Popov superstability theorem, the identification algorithm of speed of permanent magnetic synchronous electromotor rotor, stator resistance and rotor flux can be expressed as:

${\widehat{\mathrm{\&omega;}}}_r=\underset{0}{\overset{t}{\&Integral;}}{K}_{i1}(i_d{\hat{i}}_q-i_q{\hat{i}}_d-\frac{{\widehat{\mathrm{\&psi;}}}_r}{L_s}(i_q-{\hat{i}}_q))\mathrm{d\&tau;}+K_{p1}(i_d{\hat{i}}_q-i_q{\hat{i}}_d-\frac{{\widehat{\mathrm{\&psi;}}}_r}{L_s}(i_q-{\hat{i}}_q))+{\widehat{\mathrm{\&omega;}}}_r\left(0\right)---\left(1\right)$

$\frac{{\hat{R}}_s}{L_s}=\frac{R_s}{L_s}-K_{i2}\underset{0}{\overset{t}{\&Integral;}}(u_d(i_d-{\hat{i}}_d)+u_q(i_q-{\hat{i}}_q))\mathrm{dt}-K_{p2}(u_d(i_d-{\hat{i}}_d)+u_q(i_q-{\hat{i}}_q))---\left(2\right)$

$\frac{{\widehat{\mathrm{\&psi;}}}_r}{L_s}=\frac{{\mathrm{\&psi;}}_r}{L_s}-K_{i3}\underset{0}{\overset{t}{\&Integral;}}{\widehat{\mathrm{\&omega;}}}_r(i_q-{\hat{i}}_q)\mathrm{dt}-K_{p3}{\widehat{\mathrm{\&omega;}}}_r(i_q-{\hat{i}}_q)---\left(3\right)$

。

4. permagnetic synchronous motor parameter identification method as claimed in claim 3, is characterized in that: first utilize the off-line identification value of stator resistance and rotor flux to carry out spinner velocity

identification, when estimation spinner velocity is when stable and spinner velocity set-point is constant, its identification process step is as follows:

1) first by (1) formula, calculate spinner velocity identification result

2) by (2) formula, calculate again obtain Stator resistance identification result

3) will calculate

substitution (3) formula calculates

obtain rotor flux identification result

4) order ${\mathrm{\&omega;}}_r={\widehat{\mathrm{\&omega;}}}_r,R_s={\hat{R}}_s,{\mathrm{\&psi;}}_r={\widehat{\mathrm{\&psi;}}}_r,$ Upgrade identification result;

Spinner velocity, stator resistance and rotor flux information that CMRAS module identification is obtained feed back in permanent magnet synchronous motor vector control system loop, thereby realize the PMSM vector control based on CMRAS.

5. permagnetic synchronous motor parameter identification method as claimed in claim 4, is characterized in that:

Described vector control system comprises speed outer shroud and current inner loop two parts, also comprises main circuit, current signal detection circuit and control circuit; The motor rotor speed that CMRAS module identification obtains and rotor position information thereof are as the feedback quantity of controlling, reference rotor speed w _r* with feedback spinner velocity w _rdifference by PI controller, obtain reference current i _q*, i _q* with feedback current i _qdifference through PI controller, obtain reference voltage u _q, reference current i _d* with feedback current i _ddifference by PI controller, obtain reference voltage u _d, the u obtaining _qand u _dthrough anti-Park conversion, obtain u _α, u _β, the u obtaining _α, u _βby SVPWM, there is the adjusting of module, produce the work of PWM ripple control inverter, thereby drive the running of permagnetic synchronous motor module; And stator resistance and rotor flux that 8 identifications of CMRAS module obtain feed back to the mode by software in vector control algorithm.

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