阅读说明：本技术 一种感应电机转速自适应观测方法及观测装置 (Self-adaptive observation method and device for rotating speed of induction motor ) 是由 董蕊 于 2021-08-25 设计创作，主要内容包括：一种感应电机转速自适应观测方法及观测装置,解决了现有转速观测器鲁棒性不强的问题,属于电机技术领域。本发明包括：采集感应电机的电压、电流,结合二阶滑模定子电流观测器求解z-(1)和z-(2)的估计值和其中,是以i-(sα),i-(sβ),z-(1),z-(2)为状态变量,构建感应电机在αβ坐标系下的状态方程,结合ST滑模算法得到的二阶滑模定子电流观测器；根据和获取转子磁链观测值和利用带有转速的观测值的转子磁链观测器得到转子磁链在αβ坐标系下α轴、β轴的转子磁链分量观测值：和利用转速估计的自适应律得到转速的观测值转速估计的自适应律为：(A self-adaptive observation method and an observation device for the rotating speed of an induction motor solve the problem that the existing rotating speed observer is not strong in robustness, and belong to the technical field of motors. The invention comprises the following steps: collecting voltage and current of induction motor, and solving z by combining second-order sliding mode stator current observer 1 And z 2 Is estimated value of And wherein is represented by i sα ，i sβ ，z 1 ，z 2 Constructing a state equation of the induction motor under an alpha beta coordinate system for a state variable, and combining an ST sliding mode algorithm to obtain a second-order sliding mode stator current observer; according to And obtaining rotor flux linkage observed value And using observed values with speed of rotation The rotor flux linkage observer obtains rotor flux linkage component observed values of an alpha axis and a beta axis of a rotor flux linkage under an alpha beta coordinate system: and obtaining an observed value of a rotational speed using an adaptive law of rotational speed estimation The self-adaptive law of the rotation speed estimation is as follows:)

1. An adaptive observation method for the rotating speed of an induction motor is characterized in that the method is applied to speed regulation control of the induction motor, and comprises the following steps:

s1, collecting voltage information and current information of the induction motor;

s2, solving by combining the collected voltage information and current information and a second-order sliding mode stator current observerAndandare each z₁And z₂An estimated value of (d);

the method for obtaining the second-order sliding mode stator current observer comprises the following steps:

with i_sα，i_sβ，z₁，z₂Constructing a state equation of the induction motor in an alpha beta coordinate system for a state variable, and combining the state equation with an ST sliding mode algorithm to obtain a second-order sliding mode stator current observer;

state variable z₁And z₂：

Wherein the content of the first and second substances,R_rdenotes the rotor resistance, L_rRepresenting rotor inductance, ω_rIndicating rotational speed, #_rαRepresenting the component of the rotor flux linkage in the α β coordinate system, ψ_rβRepresenting the beta-axis component, L, of the rotor flux linkage in the alpha-beta coordinate system_mRepresenting mutual inductance, i_sαRepresenting the component of the stator current in the α β coordinate system, i_sβRepresenting a beta axis component of the stator current in an alpha beta coordinate system;

s3, according toAndobtaining rotor flux linkage observed valueAnd

s4, utilizing observed value with rotating speedThe rotor flux linkage observer obtains rotor flux linkage component observed values of an alpha axis and a beta axis of a rotor flux linkage under an alpha-beta coordinate system, and the rotor flux linkage component observed values are respectivelyIs composed ofAnd

s5, establishing an adaptive law of the rotation speed estimation, and combining the rotation speed estimation obtained in S3And obtained in S4Andobtaining the observed value of the rotating speedThe self-adaptive law of the rotation speed estimation is as follows:

K_pdenotes the proportionality coefficient, K_iRepresenting the integral coefficient.

2. The adaptive observing method for the rotation speed of the induction motor according to claim 1, wherein in the step S3, the method is based onAndobtaining rotor flux linkage observed valueAndthe method comprises the following steps:

3. the adaptive observing method for the rotating speed of the induction motor according to claim 1, wherein the S3 further comprises: are respectively pairedAndlow-pass filtering is carried out to obtain the observed value of the flux linkage of the rotorAnd

4. the adaptive observation method for the rotating speed of the induction motor according to claim 3, wherein the transfer function of the low-pass filter is as follows:

wherein, ω is_cS is the laplacian operator for the cut-off frequency of the low-pass filter.

5. The adaptive observing method for the rotating speed of the induction motor according to claim 1, wherein the rotor flux linkage observer is:

andare respectively i_sαAnd i_sβAn estimate of (d).

6. The adaptive observing method for the rotating speed of the induction motor according to claim 1, wherein the state equation of the induction motor in an alpha and beta coordinate system is as follows:

u_sαrepresenting the component of the stator voltage in the α β coordinate system, u_sβRepresents the beta axis component of the stator voltage under an alpha beta coordinate system,σ＝1-L_m/(L_sL_r) And σ represents a leakage coefficient, R_sDenotes the stator resistance, L_sRepresenting the stator inductance.

7. The self-adaptive observation method for the rotating speed of the induction motor according to claim 6, wherein the second-order sliding mode stator current observer is as follows:

are respectively i_sα、i_sβ、z₁、z₂Estimate of (a) ("lambda₁、λ₂、σ₁、σ₂Is the sliding mode gain, s_αEstimated error value, s, representing the alpha-axis component of the stator current in the alpha-beta coordinate system_βAn estimated error value representing a beta axis component of the stator current in an alpha beta coordinate system;

8. the adaptive observing method for the rotating speed of the induction motor according to claim 7, further comprising S6:

observed value to be obtainedAngular frequency of and rotation difference omega_sAfter summing, integrating to obtain the observed value of magnetic chain angle

9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.

10. An adaptive observation device for the rotation speed of an induction motor, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1 to 8.

Technical Field

The invention provides a self-adaptive observation method for the rotating speed of an induction motor, and belongs to the technical field of motors.

Background

At present, in the application of an induction motor speed regulating system, a speed sensor is usually adopted to acquire the rotating speed of a motor, but on one hand, the cost of the speed regulating system is increased, and on the other hand, the reliability of the system is reduced. The speed sensor-free induction motor control can abandon a high-price speed sensor and is beneficial to simplifying a control structure. However, the control without the speed sensor not only requires that the rotation speed observer can realize rotation speed identification under a common working condition, but also requires that the observer has strong robustness to external disturbance and internal parameter perturbation.

Disclosure of Invention

Aiming at the problem that the existing rotating speed observer is not strong in robustness, the invention provides the rotating speed self-adaptive observation method and the rotating speed self-adaptive observation device of the induction motor, which are not influenced by the resistance change of a rotor and are strong in robustness.

The invention discloses a self-adaptive observation method for the rotating speed of an induction motor, which comprises the following steps:

s1, collecting voltage information and current information of the induction motor;

s2, solving by combining the collected voltage information and current information and a second-order sliding mode stator current observerAndandare each z₁And z₂An estimated value of (d);

the method for obtaining the second-order sliding mode stator current observer comprises the following steps:

with i_sα，i_sβ，z₁，z₂Constructing a state equation of the induction motor in an alpha beta coordinate system for a state variable, and combining the state equation with an ST sliding mode algorithm to obtain a second-order sliding mode stator current observer;

state variable z₁And z₂：

Wherein the content of the first and second substances,R_rdenotes the rotor resistance, L_rRepresenting rotor inductance, ω_rIndicating rotational speed, #_rαRepresenting the component of the rotor flux linkage in the α β coordinate system, ψ_rβRepresenting the beta-axis component, L, of the rotor flux linkage in the alpha-beta coordinate system_mRepresenting mutual inductance, i_sαRepresenting the component of the stator current in the α β coordinate system, i_sβRepresenting a beta axis component of the stator current in an alpha beta coordinate system;

s3, according toAndobtaining rotor flux linkage observed valueAnd

s4, utilizing observed value with rotating speedThe rotor flux linkage observer obtains rotor flux linkage component observed values of an alpha axis and a beta axis of a rotor flux linkage under an alpha-beta coordinate system respectivelyAnd

s5, establishing an adaptive law of the rotation speed estimation, and combining the rotation speed estimation obtained in S3And obtained in S4Andobtaining the observed value of the rotating speedThe self-adaptive law of the rotation speed estimation is as follows:

K_pdenotes the proportionality coefficient, K_iRepresenting the integral coefficient.

Preferably, in S3, according toAndobtaining rotor flux linkage observed valueAndthe method comprises the following steps:

preferably, S3 further includes: are respectively pairedAndlow-pass filtering is carried out to obtain the observed value of the flux linkage of the rotorAnd

preferably, the transfer function of the low-pass filter is:

wherein, ω is_cS is the laplacian operator for the cut-off frequency of the low-pass filter.

Preferably, the rotor flux linkage observer is:

andare respectively i_sαAnd i_sβAn estimate of (d).

Preferably, the state equation of the induction machine in the α β coordinate system is:

u_sαrepresenting the component of the stator voltage in the α β coordinate system, u_sβRepresents the beta axis component of the stator voltage under an alpha beta coordinate system,σ＝1-L_m/(L_sL_r) And σ represents a leakage coefficient, R_sDenotes the stator resistance, L_sRepresenting the stator inductance.

Preferably, the second-order sliding mode stator current observer is as follows:

are respectively i_sα、i_sβ、z₁、z₂Estimate of (a) ("lambda₁、λ₂、σ₁、σ₂Is the sliding mode gain, s_αEstimated error value, s, representing the alpha-axis component of the stator current in the alpha-beta coordinate system_βAn estimated error value representing a beta axis component of the stator current in an alpha beta coordinate system;

preferably, the method further comprises S6:

observed value to be obtainedAngular frequency of and rotation difference omega_sAfter summing, integrating to obtain the observed value of magnetic chain angleThe invention also provides a computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.

The invention also provides an induction motor rotating speed self-adaptive observation device which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the steps of the method are realized when the processor executes the computer program.

The method has the advantages that the state variable is reselected to reconstruct the state equation of the induction motor, the state equation does not contain related items of the rotor resistance, and the observation method has stronger robustness on the rotor resistance and is not influenced by the change of the rotor resistance. And only one observed state variable is involved in the process of solving the rotor flux linkage, and no motor parameter related item exists, so that the flux linkage observation result has better robustness, smaller error and simpler observation process.

Drawings

FIG. 1 is a schematic diagram illustrating the adaptive method for observing the rotating speed of an induction motor according to the present invention;

FIG. 2 is a schematic diagram of a rotational speed identification structure;

FIG. 3 is a schematic diagram of the sensorless induction motor control principle to which the present invention is applied; whereinRepresenting a rotor flux linkage value calculated by a rotor flux linkage observer,Representing the rotor flux linkage value calculated by integrating the state variable Z,Represents a state variable, i_sdRepresents the d-axis component of the stator current-the sampled feedback value,Representing stator current d-axis component-set value, i_sqRepresents the stator current q-axis component-the sampled feedback value,Representing the q-axis component of the stator current-given value,Indicates a given rotation speed,Observed value u representing rotational speed_sd,ffRepresenting the d-axis component of the stator voltage-a given value, u_sd,fbRepresenting the d-axis component of the stator voltage-the actual feedback value, u_sq,ffRepresenting stator voltage q-axis component-set value, u_sq,fbRepresents the stator voltage q-axis component-the actual feedback value,Representing stator voltage vector, e^jθRepresenting coordinate transformation,Representing stator electricity in an alpha beta coordinate systemPressure vector u_dcRepresents the DC bus voltage,An observed value representing a magnetic chain angle,Represents a stator current vector in dq coordinate system,Representing the stator current vector in the α β coordinate system.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.

The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.

The existing state equation of the induction motor in an alpha beta coordinate system is as follows:

the parameter of the motor is the rotor resistance R under the working condition of low-speed operation due to factors such as temperature rise and the like_rThe variation is large, which may reduce the accuracy of the flux linkage observer. Therefore, how to reduce the influence of the rotor resistance variation is the key to improve the observation accuracy of the rotor flux linkage. Therefore, the formula (1) contains a rotor resistance term as a disturbance part and a rotor flux linkage term as a part to be observed, and then the two terms are combined into an unknown part;

the adaptive observation method for the rotating speed of the induction motor in the embodiment uses_sα，i_sβ，z₁，z₂Redefining the state variable z for the state variable₁，z₂：

R_rDenotes the rotor resistance, L_rRepresenting rotor inductance, ω_rIndicating rotational speed, #_rαRepresenting the component of the rotor flux linkage in the α β coordinate system, ψ_rβRepresenting the beta-axis component, L, of the rotor flux linkage in the alpha-beta coordinate system_mRepresenting mutual inductance, i_sαRepresenting the component of the stator current in the α β coordinate system, i_sβRepresenting a beta axis component of the stator current in an alpha beta coordinate system;

as shown in fig. 1, the method for adaptively observing the rotational speed of an induction motor according to the present embodiment includes:

step one, collecting voltage information and current information of an induction motor;

step two, solving by utilizing a second-order sliding mode stator current observerAndandare each z₁And z₂An estimated value of (d);

the method for obtaining the second-order sliding mode stator current observer comprises the following steps:

with i_sα，i_sβ，z₁，z₂Constructing a state equation of the induction motor in an alpha-beta coordinate system for the state variable, and combining the state equationObtaining a second-order sliding mode stator current observer by an ST sliding mode algorithm;

step three, according toAndobtaining rotor flux linkage observed valueAnd

step four, utilizing the observed value with the rotating speedThe rotor flux linkage observer obtains rotor flux linkage component observed values of an alpha axis and a beta axis of a rotor flux linkage under an alpha-beta coordinate system respectivelyAnd

step five, establishing an adaptive law of the rotation speed estimation, and combining the adaptive law with the rotation speed estimation obtained in S3And obtained in S4Andobtaining the observed value of the rotating speedThe self-adaptive law of the rotation speed estimation is as follows:

K_pdenotes the proportionality coefficient, K_iRepresenting the integral coefficient.

The method comprises the steps of reconstructing a state equation of the induction motor by redefining state variables, constructing a second-order sliding mode stator current observer by combining a Super-Twisting sliding mode algorithm on the basis, and obtaining the second-order sliding mode stator current observer by taking the second-order sliding mode stator current observer as a reference modelAndfromAndto obtainAndestablishing observations with rotational speedAs an adjustable model, to obtainAndthen, based on a Model Reference Adaptive (MRAS) principle, a rotation speed identification structure is designed, and as shown in fig. 2, the real-time rotation speed of the motor is calculated through an adaptive law of rotation speed estimation. The observed rotation speed is used for realizing the closed-loop control of the rotation speed of the induction motor, and the software algorithm is used for replacing the speed codeThe device obtains the actual rotating speed of the motor, and further realizes the speed sensorless control of the induction motor.

In a preferred embodiment, the equation of state of the induction motor in the α β coordinate system in the step one is as follows:

u_sαrepresenting the component of the stator voltage in the α β coordinate system, u_sβRepresents the beta axis component of the stator voltage under an alpha beta coordinate system,σ＝1-L_m/(L_sL_r) And σ represents a leakage coefficient, R_sDenotes the stator resistance, L_sRepresenting the stator inductance.

The state equations of the stator current and rotor flux linkage of the present embodiment both contain a matrix Z, where Z is₁Occurs simultaneously in the equation of state of the stator current and rotor flux linkage for the alpha axis, and z₂And the state equation of the stator current and the rotor flux linkage of the beta axis is presented at the same time. Thus making use of the state variable z₁,z₂The complete decoupling of the stator current of the alpha shaft and the stator current of the beta shaft and the rotor flux linkage can be realized by replacing the public terms, so that the observer is greatly simplified, and the independent decoupling observation is realized.

In the preferred embodiment, the Super-Twisting sliding mode algorithm is combined to construct a second-order sliding mode stator current observer which is as follows:

are respectively i_sα、i_sβ、z₁、z₂Estimate of (a) ("lambda₁、λ₂、σ₁、σ₂Is the sliding mode gain, s_αEstimated error value, s, representing the alpha-axis component of the stator current in the alpha-beta coordinate system_βAnd an estimated error value representing an alpha axis component of the stator current in an alpha beta coordinate system.

The sliding mode surface of the present embodiment is defined as a stator current estimation error value:

the present embodiment finds:

newly defined state variable z₁，z₂Contains the mathematical meaning of the inverse of the derivative of the rotor flux linkage. Thus can pass through And performing integral operation to obtain an observed value of the rotor flux linkage. Due to rotor resistance R_rNo explicit appearance in the designed second order sliding mode stator current observer, so the rotor resistance R_rThe accuracy of the designed observer is not affected by the variation in (c).

When observed value of stator current is sumAll converge to their true values, in the preferred embodiment, the observed value of the rotor flux linkage can be obtained from equation (7) as follows:

however, in practical applications, a small amount of dc may be unavoidable due to non-ideal factors such as measurement noise, error accumulation and offsetThe current is accumulated and amplified continuously along with the integration process, so that the rotor flux linkage observation result generates a direct current offset phenomenon, a large error is generated between the observation value and the real value of the rotor flux linkage, and the control performance of the induction motor is further influencedAndlow-pass filtering is carried out to obtain the observed value of the flux linkage of the rotorAnd

therefore, in order to filter out DC components, the method of connecting a high-pass filter after an integrator in series is adopted in the preferred embodiment to obtain the observed value of the rotor flux linkageAndthe integrator is connected with a high-pass filter in series, namely a first-order low-pass filter, and the transfer function of the integrator is as follows:

in the formula of omega_cS is the laplacian operator for the cut-off frequency of the low-pass filter.

The second-order sliding mode stator current observer constructed in the embodiment does not contain a rotating speed variable, so that the second-order sliding mode stator current observer can be used as a reference model, and a rotor flux linkage observer containing the rotating speed variable is selected as an adjustable model. And (3) sending the observation errors of the two models into a self-adaptive law of rotation speed estimation as feedback input of an adjustable model, so that the adjustable model gradually approaches to a reference model until the error is 0, and obtaining the observation rotation speed by the method, wherein the specific process comprises the following steps:

the rotor flux linkage current model is as follows:

in the formula (10), ω_rAre parameters that need to be identified, and in the preferred embodiment, λ and L are used_mWhen the magnetic flux linkage observer is regarded as a constant, the magnetic flux linkage observer of the rotor is as follows:

andare respectively i_sαAnd i_sβAn estimate of (d).

The flux linkage error equation is as follows:

in the formula

The rotation speed is generally considered to be constant within a sampling period, so the system described by equation (12) can be considered to be composed of a linear time-invariant system and a nonlinear feedback system. The Popov hyperstability system requires that the transfer function of its linear time invariant system is strictly real, whereas the nonlinear feedback system needs to satisfy the Popov inequality:

where V is the output of a linear time invariant system and W is the output of a non-linear feedback system, γ₀For a finite real number, the Popov inequality is required to hold for any time.

Wherein the transfer function of the linear time-invariant system (sI-A)^-1It is easy to prove the strict validity, so it is only necessary to let the nonlinear feedback part satisfy the formula (13).

For the system described by equation (12), the nonlinear feedback section input and output variables are chosen as follows:

the self-adaptive law of the rotating speed is set as follows:

in the formula K_p，K_iAre adaptive parameters, are all greater than 0.

By bringing formula (14) and formula (15) into formula (13):

for the first term of equation (16), since the integrand is greater than 0, its value must be positive, while for the second term of equation (16), the following inequality can be used:

similarly, it can be considered that the actual rotation speed is constant in one sampling period, and f (t) is selected as follows, and the inequality of the equation (4-25) is satisfied.

Therefore, the constructed nonlinear feedback system is stable. Fig. 2 shows a schematic diagram of a rotational speed identification structure.

However, in practical systems, the true value of the rotor flux linkage is unknown, given that a second order sliding mode stator current observer can make it possible to do soConverge to its true value, so will passAnd (3) the rotor flux linkage obtained by calculation is regarded as a true value, namely:

through derivation, the self-adaptive law of the rotation speed estimation can be obtained as follows:

the steps of the method of the present embodiment are stored in a memory as a computer program, and the processor implements the method when executing the computer program.

As shown in fig. 3, the present embodiment further includes an observation value to be obtainedAngular frequency of and rotation difference omega_sAfter summing, integrating to obtain the observed value of magnetic chain angle

The present embodiment obtains a rotational speed estimateAfter, with a given rotational speedAnd (5) calculating the difference, and performing speed regulation control on the induction motor according to the control process shown in the figure 3.

The estimated value of the rotation speed in the speed identification structure of the embodiment is not used for observing the stator current and the rotor flux linkage, so the error of the rotation speed estimation does not cause the observation error of the current and the flux linkage. Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that features from different dependent claims and herein may be combined in ways other than those described in the original claims. It is also to be understood that features described in connection with individual embodiments may be used in other embodiments.