CN106059424A - Improved Kalman observer based control method free of speed sensor - Google Patents

Abstract

The invention discloses an improved Kalman observer based control method free of a speed sensor. A sliding-mode observer of a Kalman filter is used to estimate the rotating speed and the rotor position, and speed regulation of a motor is controlled according to the estimated rotor position and rotor speed. A speed-sensor-free control algorithm is used to replace a mechanical sensor, the rotor position and rotating speed information of the motor are obtained, errors in closed-loop feedback information is reduced, and the control method based on the sliding-mode controller is low the computational complexity and easy to realize in the engineering aspect. The method of the invention has the advantages of including low cost, simple control algorithm, and capable of estimating the rotating speed and rotor position rapidly and precisely.

Description

A kind of based on the Speed Sensorless Control Method improving Kalman's observer

Technical field

The present invention relates to Speedless sensor velocity measuring technique field, particularly to a kind of based on improving Kalman's observer Speed Sensorless Control Method.

Background technology

Permagnetic synchronous motor because of its compact conformation, dependable performance and in fields such as wind-power electricity generation, electric automobile, boats and ships drivings It is widely used.Because the control of permagnetic synchronous motor generally completes under rotor rotating coordinate system, so in order to complete The control of permagnetic synchronous motor, needs to obtain the angle of its rotor and speed.Wherein, angle and velocity sensor is used to obtain This information is a kind of directly mode, but in many applications, setting angle and velocity sensor add installation, safeguard Cost, simultaneously because site environment is more severe, the precision of sensor is easily subject to vibrations, dust and the impact of greasy dirt so that System is easily disturbed by external environment condition, reduces the reliability of system.

The control system of Speedless sensor, without detecting hardware, eliminates all troubles that velocity sensor brings, carries The high reliability of system, reduces the cost of system；On the other hand so that the volume of system reduces, weight, and subtracts Lack the line of motor and controller.And the rotor angle of permagnetic synchronous motor of based on Speedless sensor, speed estimate side Method only need to detect the stator current of motor, voltage, in conjunction with the model of motor, can therefrom extract angle and the speed letter of rotor Breath, thus eliminate angle and velocity sensor, reach to improve the reliability of system, reduce the purpose of cost.

Summary of the invention

In order to overcome deficiency of the prior art, the present invention propose a kind of be prone to Project Realization based on improve Kalman The Speed Sensorless Control Method of observer estimates position and the spinner velocity of rotor, and for vector controlled closed loop system In, it is to avoid the information that mechanical pick-up device provides under the working environment that some are special is inaccurate.

In order to reach foregoing invention purpose, solve the technical scheme that its technical problem used as follows:

A kind of Speed Sensorless Control Method based on improvement Kalman's observer, comprises the following steps:

Step 1: select d axle reference currentIt is 0, AC permanent magnet synchronous motor detection output three-phase current I_a、I_bAnd I_c；

Step 2: three-phase current I_a、I_bAnd I_cConverting through Clark, export under biphase static rectangular coordinate system alpha-beta is biphase Stator current i_αAnd i_β；

Step 3: biphase stator current i_αAnd i_βConverting through Park, export under biphase synchronous rotating frame d-q is biphase Electric current I_dAnd I_q；

Step 4: the three-phase voltage U of inverter output_a、U_bAnd U_cConvert through Clark, export biphase static rectangular coordinate It it is biphase stator voltage u under alpha-beta_αAnd u_β；

Step 5: by the biphase stator current i of gained in step 2_αAnd i_βWith biphase stator voltage u of gained in step 4_αAnd u_βOne And input card Germania observer carries out estimation process, estimate the estimated value of rotor speedEstimated value with rotor-position

Step 6: the estimated value of rotor speed will be estimated in step 5It is multiplied by a constant and obtains rotor speed n of estimation, and It is poor rotor speed n of estimation and actual rotor speed n* to be carried out, and difference exports q axle reference current after being regulated by PI

Step 7: by q axle reference currentWith the electric current I obtained in step 3_qIt is poor to carry out, and difference is defeated after being regulated by PI Go out q axle reference voltage

Step 8: by d axle reference currentWith the electric current I obtained in step 3_dIt is poor to carry out, and difference is defeated after being regulated by PI Go out d axle reference voltage

Step 9: by the q axle reference voltage of output in step 7With the d axle reference voltage of output in step 8Pass through Park inverse transformation, exports two phase control voltages under biphase static rectangular coordinate system alpha-betaWith

Step 10: by two phase control voltagesWithCarrying out space vector modulation, output PWM waveform is to inverter, inversion Device inputs three-phase voltage U to permagnetic synchronous motor_a、U_bAnd U_c, thus control permagnetic synchronous motor.

Further, in steps of 5, following steps are specifically included:

Step 51: by biphase stator voltage u in step 4_αAnd u_βElectric current estimation is obtained after SMO optimized algorithm calculates ValueWith

Step 52: by electric current estimated valueWithWith the biphase stator current i in step 2_αAnd i_βIt is poor to carry out, and obtains α β Current error value on axleWith

Step 53: by current error valueWithCounter electromotive force is obtained after saturation function computing and sliding formwork gain process e_αAnd e_β；

Step 54: on the one hand, counter electromotive force e_αAnd e_βSend back in step 51, join in the calculating of SMO optimized algorithm；Separately On the one hand, counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filterWith

Step 55: the counter electromotive force estimated value of sliding mode observer estimationWithPassed through after Kalman filtering Counter electromotive force estimated value after Kalman filteringWith

Step 56: the counter electromotive force estimated value after Kalman filteringWithRotor speed is obtained by turn count Estimated value

Step 57: the counter electromotive force estimated value after Kalman filteringWithRotor-position is obtained by position estimation Estimated value before not compensating

Step 58: by phase place is carried out lag compensation, draw the phase compensation amount after Kalman filtering

Step 59: the estimated value before the rotor-position in step 57 is not compensatedWith the phase compensation amount in step 58Sue for peace, obtain the estimated value of rotor-position

As an embodiment, in step 51, specifically include following steps:

First, AC permanent magnet synchronous motor mathematical model in biphase static rectangular coordinate system alpha-beta is set up:

$\stackrel{\·}{i_{\mathrm{\α}}}=-\frac{R_s}{L_s}{i}_{\mathrm{\α}}-\frac{1}{L_s}{e}_{\mathrm{\α}}+\frac{u_{\mathrm{\α}}}{L_s}---\left(1\right)$

$\stackrel{\·}{i_{\mathrm{\β}}}=-\frac{R_s}{L_s}{i}_{\mathrm{\β}}-\frac{1}{L_s}{e}_{\mathrm{\β}}+\frac{u_{\mathrm{\β}}}{L_s}---\left(2\right)$

Wherein,For electric current i current value i on α axle_αDerivative,For electric current i current value i on β axle_βLead Number, R_SFor stator winding resistance, Ls is equivalent inductance, e_αFor sliding mode observer counter electromotive force on α axle, e_βObserve for sliding formwork Device counter electromotive force on β axle, u_αFor voltage U magnitude of voltage on α axle, u_βFor voltage U magnitude of voltage on β axle；

Secondly, counter electromotive force equation is substituted into:

e_α=-ψ_fω_rsinθ (3)

e_β=ψ_fω_rcosθ (4)

Wherein, ψ_fThe magnetic linkage produced for permanent magnet on rotor, ω_rFor synchronous rotational speed, θ is rotor angle location；

Furthermore, AC permanent magnet synchronous motor SMO in biphase static rectangular coordinate system alpha-beta optimizes accounting equation and is:

$\stackrel{\·}{\widehat{i_{\mathrm{\α}}}}=-\frac{R_s}{L_s}\widehat{i_{\mathrm{\α}}}+\frac{u_{\mathrm{\α}}}{L_s}-\frac{k}{L_s}sat(\widehat{i_{\mathrm{\α}}}-i_{\mathrm{\α}})---\left(5\right)$

$\stackrel{\·}{\widehat{i_{\mathrm{\β}}}}=-\frac{R_s}{L_s}\widehat{i_{\mathrm{\β}}}+\frac{u_{\mathrm{\β}}}{L_s}-\frac{k}{L_s}sat(\widehat{i_{\mathrm{\β}}}-i_{\mathrm{\β}})---\left(6\right)$

Wherein,It is respectively i_α、i_βEstimated value, k is sliding formwork handoff gain；

Finally, by the above-mentioned current estimation error equation that obtains:

$\stackrel{\·}{\widetilde{i_{\mathrm{\α}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\α}}}+\frac{e_{\mathrm{\α}}}{L_s}-\frac{k}{L_s}sat\left(\widetilde{i_{\mathrm{\α}}}\right)---\left(7\right)$

$\stackrel{\·}{\widetilde{i_{\mathrm{\β}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\β}}}+\frac{e_{\mathrm{\β}}}{L_s}-\frac{k}{L_s}sat\left(\widetilde{i_{\mathrm{\β}}}\right)---\left(8\right)$

Wherein,For the current error value on α axle,For the current error value on β axle.

As an embodiment, in step 52, current error valueWithAccounting equation be:

$\widetilde{i_{\mathrm{\α}}}={\hat{i}}_{\mathrm{\α}}-i_{\mathrm{\α}}---\left(9\right)$

$\widetilde{i_{\mathrm{\β}}}={\hat{i}}_{\mathrm{\β}}-i_{\mathrm{\β}}---\left(10\right)$

Wherein,And i_αFor the current error value on α axle, electric current estimated value and current value,And i_βFor β axle On current error value, electric current estimated value and current value.

As an embodiment, in step 53, counter electromotive force e_αAnd e_βCalculating process comprise the following steps respectively:

First, choosing sat is that saturation function carries out saturation function computing, it may be assumed that

$sat=\left\{\begin{array}{cc}1& x>h\\ x/h& \left|x\right|\&le;h\\ -1& x<h\end{array}\right.---\left(11\right)$

Secondly, liapunov function is chosen:To V derivation, work as k > max (| e_α|,|e_β|) time, thenV ＞ 0, is known by Lyapunov theorem of stability, and electric current sliding mode observer is stable；

Furthermore, choosing current error is sliding formwork diverter surface, then, when entering sliding mode, haveWithTime,

$e_{\mathrm{\&alpha;}}=ksat\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(12\right)$

$e_{\mathrm{\&beta;}}=ksat\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(13\right)$

Wherein, e_αAnd e_βFor the counter electromotive force of sliding mode observer,For the current error value on α axle,For the electric current on β axle Error amount, k is sliding formwork handoff gain.

As an embodiment, in step 54, by low pass filter obtain sliding mode observer estimation counter electromotive force estimate EvaluationWithCalculating process include:

Using low pass filter, discontinuous switching signal is converted to the continuous signal of equivalence, corresponding computing formula is such as Under:

${\hat{z}}_{\mathrm{\&alpha;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&alpha;}}---\left(14\right)$

${\hat{z}}_{\mathrm{\&beta;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&beta;}}---\left(15\right)$

Wherein,WithFor the counter electromotive force estimated value of sliding mode observer estimation, ω_cCutoff frequency for low pass filter Rate, s is Laplace operator, e_αAnd e_βCounter electromotive force for sliding mode observer.

As an embodiment, after step 54, further comprising the steps of:

First, the estimated value of rotor-position is tried to achieve by below equation:

$\widehat{\mathrm{\&theta;}}=-\arctan \left(\frac{\widehat{z_{\mathrm{\&alpha;}}}}{\widehat{z_{\mathrm{\&beta;}}}}\right)---\left(16\right)$

Wherein,For the estimated value of rotor-position,WithCounter electromotive force for sliding mode observer estimation；

Secondly as the use of low pass filter, its phase place has certain hysteresis quality, phase place must be carried out delayed benefit Repaying, its phase compensation amount is:

$\mathrm{\&Delta;}\widehat{\mathrm{\&theta;}}=-\arctan \left(\frac{\mathrm{\&omega;}}{{\mathrm{\&omega;}}_c}\right)---\left(17\right)$

Wherein,It is phase compensation amount, rotating speed when ω is stable state, ω_cCut-off frequency for low pass filter；

Furthermore, the estimated value of rotor speed is tried to achieve by below equation:

$\widehat{\mathrm{\&omega;}}=\frac{\sqrt{{\widehat{z_{\mathrm{\&alpha;}}}}^2+{\widehat{z_{\mathrm{\&beta;}}}}^2}}{{\mathrm{\&psi;}}_f}---\left(18\right)$

Wherein,For rotor speed estimated value,WithFor the counter electromotive force of sliding mode observer estimation, ψ_fFor on rotor forever The magnetic linkage that magnet produces.

As an embodiment, in step 55, Kalman filter is used to obtainWithFiltered the most electronic GestureWithObtaining optimum observation from random noise signal, the state equation of Kalman filter is as follows:

${\stackrel{g}{\hat{e}}}_{\mathrm{\&alpha;}}=-{\widehat{\mathrm{\&omega;}}}_e{\hat{e}}_{\mathrm{\&beta;}}-K_k({\hat{e}}_{\mathrm{\&alpha;}}-{\hat{z}}_{\mathrm{\&alpha;}})---\left(19\right)$

${\stackrel{g}{\hat{e}}}_{\mathrm{\&beta;}}={\widehat{\mathrm{\&omega;}}}_e{\hat{e}}_{\mathrm{\&alpha;}}-K_k({\hat{e}}_{\mathrm{\&beta;}}-{\hat{z}}_{\mathrm{\&beta;}})---\left(20\right)$

${\stackrel{g}{\widehat{\mathrm{\&omega;}}}}_e=({\hat{e}}_{\mathrm{\&alpha;}}-{\hat{z}}_{\mathrm{\&alpha;}}){\hat{e}}_{\mathrm{\&beta;}}-({\hat{e}}_{\mathrm{\&beta;}}-{\hat{z}}_{\mathrm{\&beta;}}){\hat{e}}_{\mathrm{\&alpha;}}---\left(21\right)$

Wherein, K_kFor the gain of Kalman filter,For the rotor angular rate estimated value of Kalman filter,WithFor counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filter,WithFor cunning The counter electromotive force estimated value of mould observer estimationWithObtained after Kalman filtering after Kalman filtering is anti- Electromotive force estimated value.

As an embodiment, at step 56, the estimated value of the rotor speed after Kalman filtering is by following public affairs Formula is tried to achieve:

${\widehat{\mathrm{\&omega;}}}_K=\frac{\sqrt{{{\hat{e}}^2}_{\mathrm{\&alpha;}}+{{\hat{e}}^2}_{\mathrm{\&beta;}}}}{{\mathrm{\&psi;}}_f}---\left(22\right)$

Wherein,For the rotor speed estimated value after Kalman filtering,WithFor after Kalman filtering The counter electromotive force of sliding mode observer estimation, ψ_fThe magnetic linkage produced for permanent magnet on rotor.

As an embodiment, in step 57, the estimated value of the rotor-position after Kalman filtering is by following public affairs Formula is tried to achieve:

${\widehat{\mathrm{\&theta;}}}_{Kc}=-\arctan \left(\frac{{\hat{e}}_{\mathrm{\&alpha;}}}{{\hat{e}}_{\mathrm{\&beta;}}}\right)---\left(23\right)$

Wherein,For the estimated value of the rotor-position after Kalman filtering,WithFor after Kalman filtering Sliding mode observer estimation counter electromotive force.

As an embodiment, in step 58, due to the use of low pass filter, its phase place has certain hysteresis quality, Phase place must be carried out lag compensation, the phase compensation amount after Kalman filtering is:

$\mathrm{\&Delta;}{\widehat{\mathrm{\&theta;}}}_K=-\arctan \left(\frac{\mathrm{\&omega;}}{{\mathrm{\&omega;}}_c}\right)---\left(24\right)$

Wherein,It is phase compensation amount, rotating speed when ω is stable state, ω_cCut-off frequency for low pass filter.

Due to the fact that the above technical scheme of employing, be allowed to compared with prior art, have the following advantages that and actively imitate Really:

1, the present invention is a kind of based on the Speed Sensorless Control Method improving Kalman's observer, it is achieved that permanent-magnet synchronous The high accuracy senseless control of motor, instead of traditional mechanical pick-up device, decreases volume and the cost of system, increases Add the reliability of system, and extend the range of application of permagnetic synchronous motor；

2, a kind of Speed Sensorless Control Method based on improvement Kalman's observer of the present invention, can effectively suppress synovial membrane The high frequency that variable-structure control introduces is buffeted, have concurrently simultaneously Sliding mode variable structure control response rapidly, without the advantages such as system identification with And the anti-random disturbances of EKF and noise immune are strong, can the advantage such as real-time parameter renewal；

3, the present invention is the highest to the required precision of the mathematical model of control system for permanent-magnet synchronous motor, the most true to systematic parameter Qualitative, external disturbance has adaptivity and stronger robustness, has excellent dynamic and static in permagnetic synchronous motor control Step response；

4, the Kalman filter in the present invention is not only to the estimation error caused due to parameter of electric machine error, has very well Elimination effect, and the ripple component in counter electromotive force can be filtered, there is stronger robustness so that permagnetic synchronous motor Control system have more preferable steady state effect and dynamic response；

5, the present invention have that low cost, control algolithm be simple, rotating speed and the estimated speed of position and precision advantages of higher.

Accompanying drawing explanation

In order to be illustrated more clearly that the technical scheme of the embodiment of the present invention, required use in embodiment being described below Accompanying drawing be briefly described.It is clear that the accompanying drawing in describing below is only some embodiments of the present invention, for ability From the point of view of field technique personnel, on the premise of not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.Attached In figure:

Fig. 1 is sliding moding structure in a kind of Speed Sensorless Control Method based on improvement Kalman's observer of the present invention The motor process figure of control system；

Fig. 2 is Kalman's observation in a kind of Speed Sensorless Control Method based on improvement Kalman's observer of the present invention Device structure chart；

Fig. 3 is a kind of overall flow based on the Speed Sensorless Control Method improving Kalman's observer of the present invention Figure；

Fig. 4 is that the present invention is a kind of based on the step 5 in the Speed Sensorless Control Method improving Kalman's observer Particular flow sheet；

Fig. 5 is the system corresponding to a kind of Speed Sensorless Control Method based on improvement Kalman's observer of the present invention Analogous diagram；

When Fig. 6 is a kind of Speed Sensorless Control Method medium speed sudden change based on improvement Kalman's observer of the present invention Simulation waveform figure；

When Fig. 7 is torque sudden change in a kind of Speed Sensorless Control Method based on improvement Kalman's observer of the present invention Simulation waveform figure.

Detailed description of the invention

Below with reference to the accompanying drawing of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete description And discussion, it is clear that a part of example of the only present invention as described herein, is not whole examples, based on the present invention In embodiment, the every other enforcement that those of ordinary skill in the art are obtained on the premise of not making creative work Example, broadly falls into protection scope of the present invention.

See Fig. 1, the situation that consideration is general now in patent of the present invention, there is diverter surface s (x)=s (x₁, x₂,···,x_n)=0, it is by x=f (x) (x ∈ Rⁿ) state space of this system is divided into upper and lower two parts s>0 and s<0. As it is shown in figure 1, there is the motor point of 3 kinds of situations on diverter surface.Point A is usual point, when arriving near diverter surface s=0, and motion Point passes through an A and mistake；Point B is starting point, and when arriving near diverter surface s=0, a B is left from diverter surface both sides in motor point；Point C is terminating point, and when arriving near diverter surface s=0, motor point levels off to a C from diverter surface both sides.

In sliding moding structure, terminating point has special meaning, and what meaning starting point and usual point do not have substantially. When being all terminating point in a certain section of region on diverter surface, the motor point when, and will be at this once trend towards this region Move in region.Now, this region is called " sliding mode " district i.e. " sliding formwork " district, and the system motion in this region is called " sliding formwork Motion ".

With reference to Fig. 3, the invention discloses a kind of Speed Sensorless Control Method based on improvement Kalman's observer, bag Include following steps:

Step 1: select d axle reference currentIt is 0, AC permanent magnet synchronous motor detection output three-phase current I_a、I_bAnd I_c；

Step 2: three-phase current I_a、I_bAnd I_cConverting through Clark, export under biphase static rectangular coordinate system alpha-beta is biphase Stator current i_αAnd i_β；

Step 3: biphase stator current i_αAnd i_βConverting through Park, export under biphase synchronous rotating frame d-q is biphase Electric current I_dAnd I_q；

Step 4: the three-phase voltage U of inverter output_a、U_bAnd U_cConvert through Clark, export biphase static rectangular coordinate It it is biphase stator voltage u under alpha-beta_αAnd u_β；

Step 5: by the biphase stator current i of gained in step 2_αAnd i_βWith biphase stator voltage u of gained in step 4_αWith u_βInput card Germania observer carries out estimation process in the lump, estimates the estimated value of rotor speedEstimated value with rotor-position

Step 6: the estimated value of rotor speed will be estimated in step 5It is multiplied by a constant and obtains rotor speed n of estimation, And rotor speed n of estimation and actual rotor speed n* are carried out poor, difference regulated by PI after output q axle reference current

Step 7: by q axle reference currentWith the electric current I obtained in step 3_qIt is poor to carry out, and difference is defeated after being regulated by PI Go out q axle reference voltage

Step 8: by d axle reference currentWith the electric current I obtained in step 3_dIt is poor to carry out, and difference is defeated after being regulated by PI Go out d axle reference voltage

Step 9: by the q axle reference voltage of output in step 7With the d axle reference voltage of output in step 8Pass through Park inverse transformation, exports two phase control voltages under biphase static rectangular coordinate system alpha-betaWith

Step 10: by two phase control voltagesWithCarrying out space vector modulation, output PWM waveform is to inverter, inversion Device inputs three-phase voltage U to permagnetic synchronous motor_a、U_bAnd U_c, thus control permagnetic synchronous motor.

In step 2, by three-phase current I_a、I_bAnd I_cConvert through Clark, export under biphase static rectangular coordinate system alpha-beta Biphase stator current i_αAnd i_βThe reduction formula being specifically related to is as follows:

$\left[\begin{array}{c}{i}_{\mathrm{\&alpha;}}\\ i_{\mathrm{\&beta;}}\end{array}\right]=\frac{2}{3}\left[\begin{array}{ccc}1& -1/2& -1/2\\ 0& \sqrt{3}/2& -\sqrt{3}/2\end{array}\right]\left[\begin{array}{c}{i}_a\\ i_b\\ i_c\end{array}\right]$

In step 3, by biphase stator current i_αAnd i_βConvert through Park, export under biphase synchronous rotating frame d-q Biphase current I_dAnd I_qThe reduction formula being specifically related to is as follows:

$\left[\begin{array}{c}{I}_d\\ I_q\end{array}\right]=\left[\begin{array}{cc}\cos \widehat{\mathrm{\&theta;}}& \sin \widehat{\mathrm{\&theta;}}\\ -\sin \widehat{\mathrm{\&theta;}}& \cos \widehat{\mathrm{\&theta;}}\end{array}\right]\left[\begin{array}{c}{i}_{\mathrm{\&alpha;}}\\ i_{\mathrm{\&beta;}}\end{array}\right]$

Wherein,Rotor angle for estimation.

In step 4, three-phase voltage U inverter exported_a、U_bAnd U_cThrough Clark convert, export biphase static directly Biphase stator voltage u under angle coordinate system alpha-beta_αAnd u_βThe reduction formula being specifically related to is as follows:

$\left[\begin{array}{c}{u}_{\mathrm{\&alpha;}}\\ u_{\mathrm{\&beta;}}\end{array}\right]=\frac{2}{3}\left[\begin{array}{ccc}1& -1/2& -1/2\\ 0& \sqrt{3}/2& -\sqrt{3}/2\end{array}\right]\left[\begin{array}{c}{U}_a\\ U_b\\ U_c\end{array}\right]$

Further, in conjunction with Fig. 2 and Fig. 4, in steps of 5, following steps are specifically included:

Step 51: by biphase stator voltage u in step 4_αAnd u_βThrough SMO (Sliding mode observer, sliding formwork Observer) optimized algorithm calculate after obtain electric current estimated valueWith

Step 52: by electric current estimated valueWithWith the biphase stator current i in step 2_αAnd i_βIt is poor to carry out, and obtains α β Current error value on axleWith

Step 53: by current error valueWithCounter electromotive force is obtained after saturation function computing and sliding formwork gain process e_αAnd e_β；

Step 54: on the one hand, counter electromotive force e_αAnd e_βSend back in step 51, join in the calculating of SMO optimized algorithm；Separately On the one hand, counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filterWith

Step 55: the counter electromotive force estimated value of sliding mode observer estimationWithPassed through after Kalman filtering Counter electromotive force estimated value after Kalman filteringWith

Step 56: the counter electromotive force estimated value after Kalman filteringWithRotor speed is obtained by turn count Estimated value

Step 57: the counter electromotive force estimated value after Kalman filteringWithRotor-position is obtained by position estimation Estimated value before not compensating

Step 58: by phase place is carried out lag compensation, draw the phase compensation amount after Kalman filtering

Step 59: the estimated value before the rotor-position in step 57 is not compensatedWith the phase compensation amount in step 58Sue for peace, obtain the estimated value of rotor-position

As an embodiment, in step 51, specifically include following steps:

First, AC permanent magnet synchronous motor mathematical model in biphase static rectangular coordinate system alpha-beta is set up:

$\stackrel{\&CenterDot;}{i_{\mathrm{\&alpha;}}}=-\frac{R_s}{L_s}{i}_{\mathrm{\&alpha;}}-\frac{1}{L_s}{e}_{\mathrm{\&alpha;}}+\frac{u_{\mathrm{\&alpha;}}}{L_s}---\left(1\right)$

$\stackrel{\&CenterDot;}{i_{\mathrm{\&beta;}}}=-\frac{R_s}{L_s}{i}_{\mathrm{\&beta;}}-\frac{1}{L_s}{e}_{\mathrm{\&beta;}}+\frac{u_{\mathrm{\&beta;}}}{L_s}---\left(2\right)$

Wherein,For electric current i current value i on α axle_αDerivative,For electric current i current value i on β axle_βLead Number, R_SFor stator winding resistance, Ls is equivalent inductance, e_αFor sliding mode observer counter electromotive force on α axle, e_βObserve for sliding formwork Device counter electromotive force on β axle, u_αFor voltage U magnitude of voltage on α axle, u_βFor voltage U magnitude of voltage on β axle；

Secondly, counter electromotive force equation is substituted into:

e_α=-ψ_fω_rsinθ (3)

e_β=ψ_fω_rcosθ (4)

Wherein, ψ_fThe magnetic linkage produced for permanent magnet on rotor, ω_rFor synchronous rotational speed, θ is rotor angle location；

Furthermore, AC permanent magnet synchronous motor SMO in biphase static rectangular coordinate system alpha-beta optimizes accounting equation and is:

$\stackrel{\&CenterDot;}{\widehat{i_{\mathrm{\&alpha;}}}}=-\frac{R_s}{L_s}\widehat{i_{\mathrm{\&alpha;}}}+\frac{u_{\mathrm{\&alpha;}}}{L_s}-\frac{k}{L_s}sat(\widehat{i_{\mathrm{\&alpha;}}}-i_{\mathrm{\&alpha;}})---\left(5\right)$

$\stackrel{\&CenterDot;}{\widehat{i_{\mathrm{\&beta;}}}}=-\frac{R_s}{L_s}\widehat{i_{\mathrm{\&beta;}}}+\frac{u_{\mathrm{\&beta;}}}{L_s}-\frac{k}{L_s}sat(\widehat{i_{\mathrm{\&beta;}}}-i_{\mathrm{\&beta;}})---\left(6\right)$

Wherein,It is respectively i_α、i_βEstimated value, k is sliding formwork handoff gain；

Finally, by the above-mentioned current estimation error equation that obtains:

$\stackrel{\&CenterDot;}{\widetilde{i_{\mathrm{\&alpha;}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\&alpha;}}}+\frac{e_{\mathrm{\&alpha;}}}{L_s}-\frac{k}{L_s}sat\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(7\right)$

$\stackrel{\&CenterDot;}{\widetilde{i_{\mathrm{\&beta;}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\&beta;}}}+\frac{e_{\mathrm{\&beta;}}}{L_s}-\frac{k}{L_s}sat\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(8\right)$

Wherein,For the current error value on α axle,For the current error value on β axle.

As an embodiment, in step 52, current error valueWithAccounting equation be:

$\widetilde{i_{\mathrm{\&alpha;}}}={\hat{i}}_{\mathrm{\&alpha;}}-i_{\mathrm{\&alpha;}}---\left(9\right)$

$\widetilde{i_{\mathrm{\&beta;}}}={\hat{i}}_{\mathrm{\&beta;}}-i_{\mathrm{\&beta;}}---\left(10\right)$

Wherein,And i_αFor the current error value on α axle, electric current estimated value and current value,And i_βFor β axle On current error value, electric current estimated value and current value.

As an embodiment, in step 53, counter electromotive force e_αAnd e_βCalculating process comprise the following steps respectively:

First, choosing sat is that saturation function carries out saturation function computing, it may be assumed that

$sat=\left\{\begin{array}{cc}1& x>h\\ x/h& \left|x\right|\&le;h\\ -1& x<h\end{array}\right.---\left(11\right)$

Secondly, liapunov function is chosen:To V derivation, work as k > max (| e_α|,|e_β|) time, thenV ＞ 0, is known by Lyapunov theorem of stability, and electric current sliding mode observer is stable；

Furthermore, choosing current error is sliding formwork diverter surface, then, when entering sliding mode, haveWithTime,

$e_{\mathrm{\&alpha;}}=ksat\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(12\right)$

$e_{\mathrm{\&beta;}}=ksat\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(13\right)$

Wherein, e_αAnd e_βFor the counter electromotive force of sliding mode observer,For the current error value on α axle,For the electricity on β axle Stream error value, k is sliding formwork handoff gain.

As an embodiment, in step 54, by low pass filter obtain sliding mode observer estimation counter electromotive force estimate EvaluationWithCalculating process include:

Using low pass filter, discontinuous switching signal is converted to the continuous signal of equivalence, corresponding computing formula is such as Under:

${\hat{z}}_{\mathrm{\&alpha;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&alpha;}}---\left(14\right)$

${\hat{z}}_{\mathrm{\&beta;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&beta;}}---\left(15\right)$

Wherein,WithFor the counter electromotive force estimated value of sliding mode observer estimation, ω_cCutoff frequency for low pass filter Rate, s is Laplace operator, e_αAnd e_βCounter electromotive force for sliding mode observer.

As an embodiment, after step 54, further comprising the steps of:

First, the estimated value of rotor-position is tried to achieve by below equation:

$\widehat{\mathrm{\&theta;}}=-\arctan \left(\frac{\widehat{z_{\mathrm{\&alpha;}}}}{\widehat{z_{\mathrm{\&beta;}}}}\right)---\left(16\right)$

Wherein,For the estimated value of rotor-position,WithCounter electromotive force for sliding mode observer estimation；

Secondly as the use of low pass filter, its phase place has certain hysteresis quality, phase place must be carried out delayed benefit Repaying, its phase compensation amount is:

$\mathrm{\&Delta;}\widehat{\mathrm{\&theta;}}=-\arctan \left(\frac{\mathrm{\&omega;}}{{\mathrm{\&omega;}}_c}\right)---\left(17\right)$

Wherein,It is phase compensation amount, rotating speed when ω is stable state, ω_cCut-off frequency for low pass filter；

Furthermore, the estimated value of rotor speed is tried to achieve by below equation:

$\widehat{\mathrm{\&omega;}}=\frac{\sqrt{{\widehat{z_{\mathrm{\&alpha;}}}}^2+{\widehat{z_{\mathrm{\&beta;}}}}^2}}{{\mathrm{\&psi;}}_f}---\left(18\right)$

Wherein,For rotor speed estimated value,WithFor the counter electromotive force of sliding mode observer estimation, ψ_fFor on rotor forever The magnetic linkage that magnet produces.

Owing to system is with the presence of high frequency ripple, utilize low pass filter that counter electromotive force is filtered, it is impossible to well to filter Except estimation error and ripple component, and Kalman filter is not only to the estimation error caused due to parameter of electric machine error, has Well elimination effect, and the ripple component in counter electromotive force can be filtered, there is stronger robustness so that permanent-magnet synchronous The control system of motor has more preferable steady state effect and dynamic response.Utilize low-pass first order filter that it is carried out low-pass filtering, Obtaining continuous print counter electromotive force isWithIn high performance motor application,WithCan not directly utilize, because estimating The counter electromotive force calculatedWithIn containing measuring noise, thus use Kalman filter to obtainWithFiltered instead Electromotive forceWithOptimum observation is obtained from random noise signal.As an embodiment, in step 55, Kalman is used Wave filter will obtainWithFiltered counter electromotive forceWithOptimum observation, karr is obtained from random noise signal The state equation of graceful wave filter is as follows:

${\stackrel{g}{\hat{e}}}_{\mathrm{\&alpha;}}=-{\widehat{\mathrm{\&omega;}}}_e{\hat{e}}_{\mathrm{\&beta;}}-K_k({\hat{e}}_{\mathrm{\&alpha;}}-{\hat{z}}_{\mathrm{\&alpha;}})---\left(19\right)$

${\stackrel{g}{\hat{e}}}_{\mathrm{\&beta;}}={\widehat{\mathrm{\&omega;}}}_e{\hat{e}}_{\mathrm{\&alpha;}}-K_k({\hat{e}}_{\mathrm{\&beta;}}-{\hat{z}}_{\mathrm{\&beta;}})---\left(20\right)$

${\stackrel{g}{\widehat{\mathrm{\&omega;}}}}_e=({\hat{e}}_{\mathrm{\&alpha;}}-{\hat{z}}_{\mathrm{\&alpha;}}){\hat{e}}_{\mathrm{\&beta;}}-({\hat{e}}_{\mathrm{\&beta;}}-{\hat{z}}_{\mathrm{\&beta;}}){\hat{e}}_{\mathrm{\&alpha;}}---\left(21\right)$

Wherein, K_kFor the gain of Kalman filter,For the rotor angular rate estimated value of Kalman filter,WithFor counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filter,WithFor cunning The counter electromotive force estimated value of mould observer estimationWithObtained after Kalman filtering after Kalman filtering is anti- Electromotive force estimated value.

As an embodiment, at step 56, the estimated value of the rotor speed after Kalman filtering is led to

Cross below equation to try to achieve:

${\widehat{\mathrm{\&omega;}}}_K=\frac{\sqrt{{{\hat{e}}^2}_{\mathrm{\&alpha;}}+{{\hat{e}}^2}_{\mathrm{\&beta;}}}}{{\mathrm{\&psi;}}_f}---\left(22\right)$

Wherein,For the rotor speed estimated value after Kalman filtering,WithFor after Kalman filtering The counter electromotive force of sliding mode observer estimation, ψ_fThe magnetic linkage produced for permanent magnet on rotor.

As an embodiment, in step 57, the estimated value of the rotor-position after Kalman filtering is by following public affairs Formula is tried to achieve:

${\widehat{\mathrm{\&theta;}}}_{Kc}=-\arctan \left(\frac{{\hat{e}}_{\mathrm{\&alpha;}}}{{\hat{e}}_{\mathrm{\&beta;}}}\right)---\left(23\right)$

Wherein,For the estimated value of the rotor-position after Kalman filtering,WithFor after Kalman filtering Sliding mode observer estimation counter electromotive force.

As an embodiment, in step 58, due to the use of low pass filter, its phase place has certain hysteresis quality, Phase place must be carried out lag compensation, the phase compensation amount after Kalman filtering is:

$\mathrm{\&Delta;}{\widehat{\mathrm{\&theta;}}}_K=-\arctan \left(\frac{\mathrm{\&omega;}}{{\mathrm{\&omega;}}_c}\right)---\left(24\right)$

Wherein,It is phase compensation amount, rotating speed when ω is stable state, ω_cCut-off frequency for low pass filter.

In step 6, step 5 estimates the estimated value of rotor speedAnd the relation between rotor speed n of estimation For:

$n=\frac{60\widehat{\mathrm{\&omega;}}}{2\mathrm{\&pi;}}=9.55\widehat{\mathrm{\&omega;}}$

That is, described constant is 9.55.

In step 9, by the q axle reference voltage of output in step 7With the d axle reference voltage of output in step 8Warp Cross Park inverse transformation, export two phase control voltages under biphase static rectangular coordinate system alpha-betaWithIt is specifically related to following conversion Formula:

$\left[\begin{array}{c}{u}_{\mathrm{\&alpha;}}^{*}\\ u_{\mathrm{\&beta;}}^{*}\end{array}\right]=\left[\begin{array}{cc}\cos \widehat{\mathrm{\&theta;}}& -\sin \widehat{\mathrm{\&theta;}}\\ \sin \widehat{\mathrm{\&theta;}}& \cos \widehat{\mathrm{\&theta;}}\end{array}\right]\left[\begin{array}{c}{u}_d^{*}\\ u_q^{*}\end{array}\right]$

Wherein,Rotor angle for estimation.

Fig. 6 and Fig. 7 is to emulate, by Fig. 5, the experimental result reached.When test result indicate that rotating speed sudden change or load changing Angular errors is almost 0, and the error of rotating speed is between-6.5 3, and the pulsation of torque is between 2.5 3.3.Indicate this invention The sliding mode observer of the fusion card Germania designed by patent, in rotating speed sudden change or in the case of load changing, can be followed the tracks of very well The rotating speed of motor and corner change, control accuracy is high, and dynamic property is good, has certain practicality.

The above, the only present invention preferably detailed description of the invention, but protection scope of the present invention is not limited thereto, Any those familiar with the art in the technical scope that the invention discloses, the change that can readily occur in or replacement, All should contain within protection scope of the present invention.Therefore, protection scope of the present invention should be with scope of the claims It is as the criterion.

Claims (11)

1. a Speed Sensorless Control Method based on improvement Kalman's observer, it is characterised in that comprise the following steps:

Step 1: select d axle reference currentIt is 0, AC permanent magnet synchronous motor detection output three-phase current I_a、I_bAnd I_c；

Step 2: three-phase current I_a、I_bAnd I_cConvert through Clark, export the biphase stator under biphase static rectangular coordinate system alpha-beta Electric current i_αAnd i_β；

Step 3: biphase stator current i_αAnd i_βConvert through Park, export the biphase current under biphase synchronous rotating frame d-q I_dAnd I_q；

Step 4: the three-phase voltage U of inverter output_a、U_bAnd U_cConvert through Clark, export biphase static rectangular coordinate system alpha-beta Under biphase stator voltage u_αAnd u_β；

Step 5: by the biphase stator current i of gained in step 2_αAnd i_βWith biphase stator voltage u of gained in step 4_αAnd u_βOne And input card Germania observer carries out estimation process, estimate the estimated value of rotor speedEstimated value with rotor-position

Step 6: the estimated value of rotor speed will be estimated in step 5It is multiplied by a constant and obtains rotor speed n of estimation, and will It is poor that rotor speed n of estimation and actual rotor speed n* are carried out, and difference exports q axle reference current after being regulated by PI

Step 7: by q axle reference currentWith the electric current I obtained in step 3_qIt is poor to carry out, and difference exports q axle after being regulated by PI Reference voltage

Step 8: by d axle reference currentWith the electric current I obtained in step 3_dIt is poor to carry out, and difference exports d axle after being regulated by PI Reference voltage

Step 9: by the q axle reference voltage of output in step 7With the d axle reference voltage of output in step 8Anti-through Park Conversion, exports two phase control voltages under biphase static rectangular coordinate system alpha-betaWith

Step 10: by two phase control voltagesWithCarry out space vector modulation, output PWM waveform to inverter, inverter to Permagnetic synchronous motor input three-phase voltage U_a、U_bAnd U_c, thus control permagnetic synchronous motor.

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 1, it is special Levy and be, in steps of 5, specifically include following steps:

Step 51: by biphase stator voltage u in step 4_αAnd u_βElectric current estimated value is obtained after SMO optimized algorithm calculatesWith

Step 52: by electric current estimated valueWithWith the biphase stator current i in step 2_αAnd i_βIt is poor to carry out, and obtains on α β axle Current error valueWith

Step 53: by current error valueWithCounter electromotive force e is obtained after saturation function computing and sliding formwork gain process_αWith e_β；

Step 54: on the one hand, counter electromotive force e_αAnd e_βSend back in step 51, join in the calculating of SMO optimized algorithm；The opposing party Face, counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filterWith

Step 55: the counter electromotive force estimated value of sliding mode observer estimationWithObtain through karr after Kalman filtering Graceful filtered counter electromotive force estimated valueWith

Step 56: the counter electromotive force estimated value after Kalman filteringWithEstimating of rotor speed is obtained by turn count Evaluation

Step 57: the counter electromotive force estimated value after Kalman filteringWithObtain rotor-position by position estimation not mend Estimated value before repaying

Step 58: by phase place is carried out lag compensation, draw the phase compensation amount after Kalman filtering

Step 59: the estimated value before the rotor-position in step 57 is not compensatedWith the phase compensation amount in step 58Enter Row summation, obtains the estimated value of rotor-position

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 2, it is special Levy and be, in step 51, specifically include following steps:

First, AC permanent magnet synchronous motor mathematical model in biphase static rectangular coordinate system alpha-beta is set up:

$\stackrel{\&CenterDot;}{i_{\mathrm{\&alpha;}}}=-\frac{R_s}{L_s}{i}_{\mathrm{\&alpha;}}-\frac{1}{L_s}{e}_{\mathrm{\&alpha;}}+\frac{u_{\mathrm{\&alpha;}}}{L_s}---\left(1\right)$

$\stackrel{\&CenterDot;}{i_{\mathrm{\&beta;}}}=-\frac{R_s}{L_s}{i}_{\mathrm{\&beta;}}-\frac{1}{L_s}{e}_{\mathrm{\&beta;}}+\frac{u_{\mathrm{\&beta;}}}{L_s}---\left(2\right)$

Wherein,For electric current i current value i on α axle_αDerivative,For electric current i current value i on β axle_βDerivative, R_S For stator winding resistance, Ls is equivalent inductance, e_αFor sliding mode observer counter electromotive force on α axle, e_βFor sliding mode observer at β Counter electromotive force on axle, u_αFor voltage U magnitude of voltage on α axle, u_βFor voltage U magnitude of voltage on β axle；

Secondly, counter electromotive force equation is substituted into:

e_α=-ψ_fω_rsinθ (3)

e_β=ψ_fω_rcosθ (4)

Wherein, ψ_fThe magnetic linkage produced for permanent magnet on rotor, ω_rFor synchronous rotational speed, θ is rotor angle location；

Furthermore, AC permanent magnet synchronous motor SMO in biphase static rectangular coordinate system alpha-beta optimizes accounting equation and is:

$\stackrel{\&CenterDot;}{\widehat{i_{\mathrm{\&alpha;}}}}=-\frac{R_s}{L_s}\widehat{i_{\mathrm{\&alpha;}}}+\frac{u_{\mathrm{\&alpha;}}}{L_s}-\frac{k}{L_s}sat(\widehat{i_{\mathrm{\&alpha;}}}-i_{\mathrm{\&alpha;}})---\left(5\right)$

$\stackrel{\&CenterDot;}{\widehat{i_{\mathrm{\&beta;}}}}=-\frac{R_s}{L_s}\widehat{i_{\mathrm{\&beta;}}}+\frac{u_{\mathrm{\&beta;}}}{L_s}-\frac{k}{L_s}sat(\widehat{i_{\mathrm{\&beta;}}}-i_{\mathrm{\&beta;}})---\left(6\right)$

Wherein,It is respectively i_α、i_βEstimated value, k is sliding formwork handoff gain；

Finally, by the above-mentioned current estimation error equation that obtains:

$\stackrel{\&CenterDot;}{\widetilde{i_{\mathrm{\&alpha;}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\&alpha;}}}+\frac{e_{\mathrm{\&alpha;}}}{L_s}-\frac{k}{L_s}sat\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(7\right)$

$\stackrel{\&CenterDot;}{\widetilde{i_{\mathrm{\&beta;}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\&beta;}}}+\frac{e_{\mathrm{\&beta;}}}{L_s}-\frac{k}{L_s}sat\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(8\right)$

Wherein,For the current error value on α axle,For the current error value on β axle.

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 2, it is special Levy and be, in step 52, current error valueWithAccounting equation be:

$\widetilde{i_{\mathrm{\&alpha;}}}={\hat{i}}_{\mathrm{\&alpha;}}-i_{\mathrm{\&alpha;}}---\left(9\right)$

$\widetilde{i_{\mathrm{\&beta;}}}={\hat{i}}_{\mathrm{\&beta;}}-i_{\mathrm{\&beta;}}---\left(10\right)$

Wherein,And i_αFor the current error value on α axle, electric current estimated value and current value,And i_βFor the electricity on β axle Stream error value, electric current estimated value and current value.

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 2, it is special Levy and be, in step 53, counter electromotive force e_αAnd e_βCalculating process comprise the following steps respectively:

First, choosing sat is that saturation function carries out saturation function computing, it may be assumed that

$sat=\left\{\begin{array}{cc}1& x>h\\ x/h& \left|x\right|\&le;h\\ -1& x<h\end{array}\right.---\left(11\right)$

Secondly, liapunov function is chosen:To V derivation, work as k > max (| e_α|,|e_β|) time, then V ＞ 0, is known by Lyapunov theorem of stability, and electric current sliding mode observer is stable；

Furthermore, choosing current error is sliding formwork diverter surface, then, when entering sliding mode, haveWith Time,

$e_{\mathrm{\&alpha;}}=ksat\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(12\right)$

$e_{\mathrm{\&beta;}}=ksat\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(13\right)$

Wherein, e_αAnd e_βFor the counter electromotive force of sliding mode observer,For the current error value on α axle,For the current error on β axle Value, k is sliding formwork handoff gain.

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 2, it is special Levy and be, in step 54, obtained the counter electromotive force estimated value of sliding mode observer estimation by low pass filterWithMeter Calculation process includes:

Using low pass filter, discontinuous switching signal is converted to the continuous signal of equivalence, corresponding computing formula is as follows:

${\hat{z}}_{\mathrm{\&alpha;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&alpha;}}---\left(14\right)$

${\hat{z}}_{\mathrm{\&beta;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&beta;}}---\left(15\right)$

Wherein,WithFor the counter electromotive force estimated value of sliding mode observer estimation, ω_cFor the cut-off frequency of low pass filter, s is Laplace operator, e_αAnd e_βCounter electromotive force for sliding mode observer.

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 6, it is special Levy and be, after step 54, further comprising the steps of:

First, the estimated value of rotor-position is tried to achieve by below equation:

$\widehat{\mathrm{\&theta;}}=-\arctan \left(\frac{\widehat{z_{\mathrm{\&alpha;}}}}{\widehat{z_{\mathrm{\&beta;}}}}\right)---\left(16\right)$

Wherein,For the estimated value of rotor-position,WithCounter electromotive force for sliding mode observer estimation；

Secondly as the use of low pass filter, its phase place has certain hysteresis quality, phase place must be carried out lag compensation, its Phase compensation amount is:

$\mathrm{\&Delta;}\widehat{\mathrm{\&theta;}}=-\arctan \left(\frac{\mathrm{\&omega;}}{{\mathrm{\&omega;}}_c}\right)---\left(17\right)$

Wherein,It is phase compensation amount, rotating speed when ω is stable state, ω_cCut-off frequency for low pass filter；

Furthermore, the estimated value of rotor speed is tried to achieve by below equation:

$\widehat{\mathrm{\&omega;}}=\frac{\sqrt{{\widehat{z_{\mathrm{\&alpha;}}}}^2+{\widehat{z_{\mathrm{\&beta;}}}}^2}}{{\mathrm{\&psi;}}_f}---\left(18\right)$

Wherein,For rotor speed estimated value,WithFor the counter electromotive force of sliding mode observer estimation, ψ_fFor permanent magnet on rotor The magnetic linkage produced.

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 2, it is special Levy and be, in step 55, use Kalman filter to obtainWithFiltered counter electromotive forceWithFrom at random Obtaining optimum observation in noise signal, the state equation of Kalman filter is as follows:

${\stackrel{g}{\hat{e}}}_{\mathrm{\&alpha;}}=-{\widehat{\mathrm{\&omega;}}}_e{\hat{e}}_{\mathrm{\&beta;}}-K_k({\hat{e}}_{\mathrm{\&alpha;}}-{\hat{z}}_{\mathrm{\&alpha;}})---\left(19\right)$

${\stackrel{g}{\hat{e}}}_{\mathrm{\&beta;}}={\widehat{\mathrm{\&omega;}}}_e{\hat{e}}_{\mathrm{\&alpha;}}-K_k({\hat{e}}_{\mathrm{\&beta;}}-{\hat{z}}_{\mathrm{\&beta;}})---\left(20\right)$

${\stackrel{g}{\widehat{\mathrm{\&omega;}}}}_e=({\hat{e}}_{\mathrm{\&alpha;}}-{\hat{z}}_{\mathrm{\&alpha;}}){\hat{e}}_{\mathrm{\&beta;}}-({\hat{e}}_{\mathrm{\&beta;}}-{\hat{z}}_{\mathrm{\&beta;}}){\hat{e}}_{\mathrm{\&alpha;}}---\left(21\right)$

Wherein, K_kFor the gain of Kalman filter,For the rotor angular rate estimated value of Kalman filter,WithFor Counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filter,WithSee for sliding formwork Survey the counter electromotive force estimated value of device estimationWithObtained after Kalman filtering after Kalman filtering is the most electronic Gesture estimated value.

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 2, it is special Levying and be, at step 56, the estimated value of the rotor speed after Kalman filtering is tried to achieve by below equation:

${\widehat{\mathrm{\&omega;}}}_K=\frac{\sqrt{{{\hat{e}}^2}_{\mathrm{\&alpha;}}+{{\hat{e}}^2}_{\mathrm{\&beta;}}}}{{\mathrm{\&psi;}}_f}---\left(22\right)$

Wherein,For the rotor speed estimated value after Kalman filtering,WithFor the sliding formwork after Kalman filtering The counter electromotive force of observer estimation, ψ_fThe magnetic linkage produced for permanent magnet on rotor.

A kind of Speed Sensorless Control Method based on improvement Kalman's observer the most according to claim 2, it is special Levying and be, in step 57, the estimated value of the rotor-position after Kalman filtering is tried to achieve by below equation:

${\widehat{\mathrm{\&theta;}}}_{Kc}=-\arctan \left(\frac{{\hat{e}}_{\mathrm{\&alpha;}}}{{\hat{e}}_{\mathrm{\&beta;}}}\right)---\left(23\right)$

Wherein,For the estimated value of the rotor-position after Kalman filtering,WithFor the cunning after Kalman filtering The counter electromotive force of mould observer estimation.

11. a kind of Speed Sensorless Control Methods based on improvement Kalman's observer according to claim 2, it is special Levying and be, in step 58, due to the use of low pass filter, its phase place has certain hysteresis quality, must carry out stagnant to phase place Post-compensation, the phase compensation amount after Kalman filtering is:

$\mathrm{\&Delta;}{\widehat{\mathrm{\&theta;}}}_K=-\arctan \left(\frac{\mathrm{\&omega;}}{{\mathrm{\&omega;}}_c}\right)---\left(24\right)$

Wherein,It is phase compensation amount, rotating speed when ω is stable state, ω_cCut-off frequency for low pass filter.