A method, system and device for current control and inductance identification of a linear induction motor

Abstract

The application discloses a kind of excitation inductance identification method, current control method and system of linear induction motor, belong to linear motor control technical field;In each control cycle, with back electromotive force as observation, the reference model based on sliding mode observer is constructed to calculate back electromotive force observation value, and adjustable model containing excitation inductance is used to calculate back electromotive force, and the adaptive rate of excitation inductance and back emf error is calculated to calculate the corresponding excitation inductance, to realize the identification of excitation inductance.The application constructs reference model irrelevant to the change of excitation inductance, and uses sliding mode instead of current differential term, eliminates the noise caused by current differential term in existing reference model, avoids the interference of current noise on back emf observation result, improves the accuracy of excitation inductance identification;On this basis, the inherent chattering problem of sliding mode observer is further eliminated by using cascaded low-pass filter, and the accuracy of excitation inductance identification is further improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of linear motor control, and more particularly relates to a method for identifying excitation inductance of a linear induction motor, a current control method and system. BACKGROUND

[0002] A linear induction motor (LIM) is derived from a rotary induction motor (RIM) by cutting along the diameter direction, which can generate thrust in the linear direction, and has the advantages of simple structure, high reliability, fast acceleration and deceleration, etc. It has been widely used in many fields such as rail transportation, military industry and industrial manufacturing. However, due to the influence of the primary core break, LIM has a special end effect: the primary always enters the secondary area without a magnetic field. According to Faraday's law, in the primary entry and exit area, the secondary induction plate will generate eddy current to prevent the change of the magnetic field, and then generate a distorted air gap magnetic field. With the increase of running speed, the air gap magnetic field distortion will be more serious, and the equivalent excitation inductance parameter will change significantly, which will cause the controller parameter mismatch and deteriorate the control performance. Considering that the parameter affected by the end effect in LIM is only the excitation inductance, which has a serious impact on the control performance, it is urgent to research a method for identifying the excitation inductance of a linear induction motor to further control the current so that the speed and flux of the motor reach the preset value.

[0003] At present, the existing excitation inductance identification method of linear induction motor often obtains the excitation inductance parameter through offline parameter identification method or online parameter identification method. Among them, the offline parameter identification method mainly obtains the excitation inductance parameter by querying the direct relationship curve between speed, slip and excitation inductance parameter; however, with the change of speed, slip and other working conditions, the LIM excitation inductance parameter changes complexly, and the existing offline identification method is difficult to cover the complex changes of running conditions comprehensively, so it is only suitable for simple working condition scenes. In order to avoid the above problems, the existing technology usually adopts online parameter identification method to obtain the excitation inductance parameter, which often samples the motor phase current first, and then substitutes it into the existing observer reference model to calculate the excitation inductance. The existing observer reference model relies on the current differential term for processing, which is very sensitive to current noise and will increase the back EMF harmonics in the reference model, which will further lead to large error in inductance parameter identification result and low identification accuracy. SUMMARY

[0004] In view of the above defects or improvement needs of the prior art, the present application provides a method for identifying excitation inductance of a linear induction motor, a current control method and system to solve the technical problem that the prior art cannot accurately identify the excitation inductance.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for identifying the excitation inductance of a linear induction motor, comprising: performing the following operations during the current control period t:

[0006] The primary current i of the αβ axis of the linear induction motor under the current control period t. 1αβ (t), voltage vector u αβ Substituting the secondary angular velocity ω2(t) and the secondary angular velocity ω2(t) into the reference model based on the sliding mode observer, the observed value of the back electromotive force is obtained. The reference model is as follows:

[0007]

[0008] in, For i 1αβ Observed values ​​of (t); Leakage inductance coefficient of motor L1 = L m0 +L l1 L m0 L is the magnetizing inductance when the motor is stationary. l1 R is the primary leakage inductance; R is the primary resistance of the motor; k m and k n All are preset gain parameters, and all are positive numbers; sign(·) is the sign function;

[0009] The motor excitation current i is calculated. m (t)=i 1αβ (t)+L2i 2αβ (t) / L m ; where i 2αβ (t) represents the αβ axis secondary current of the linear induction motor under the current control cycle t; L2 = L m0 +L l2 L l2 For secondary leakage inductance;

[0010] will i 1αβ (t), ω2(t) and i m (t) Substitute into the adjustable model for calculation to obtain the calculated value of the back electromotive force e. m (t); where the adjustable model is:

[0011]

[0012] in, and These are the observed values ​​of the excitation inductance and the corresponding secondary inductance under the previous control cycle t-1, respectively; j is the imaginary number sign; R1 is the secondary time constant under the previous control cycle t-1; R2 is the secondary resistance;

[0013] Will and e m (t) Substitute The calculation is performed to obtain the observed value of the excitation inductance under the current control period t. And output as the excitation inductance identification result under the current control cycle t; where k p and k i All are positive numbers; s is the integral symbol.

[0014] More preferably, the above-mentioned method for identifying the excitation inductance of a linear induction motor further includes:

[0015] After obtaining the observed value of the back electromotive force Afterwards, After filtering using n cascaded, identical low-pass filters, the result is... right To receive compensation And Updated to

[0016] in, for The result after passing through the first i-th stage low-pass filter; For the initial input i = 1, 2, ..., n, n ≥ 2.

[0017] In a second aspect, the present invention provides a magnetizing inductance identification system for a linear induction motor, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor executes the magnetizing inductance identification method provided in the first aspect of the present invention when executing the computer program.

[0018] Thirdly, the present invention provides a current control method for a linear induction motor, comprising:

[0019] Obtain the primary current i of the αβ axis of the linear induction motor under the current control period t. 1αβ (t) and secondary angular velocity ω2(t), and voltage vector u αβ (t) After that, the excitation inductance observation value is identified using the excitation inductance identification method provided in the first aspect of the present invention.

[0020] The primary current i of the αβ axis of the linear induction motor under the current control period t. 1αβ (t), secondary angular velocity ω2(t), secondary magnetic flux ψ 2αβ (t) and observed values ​​of excitation inductance Substitute the mathematical model of the linear induction motor, calculate the secondary flux ψ 2αβ (t+1) in the next control period t+1

[0021] The difference between the secondary flux ψ 2αβ (t+1) and the secondary flux reference value ψ 2ref is subjected to PI control to obtain the d-axis current reference value i dref ; the difference between the secondary speed v2(t) of the linear induction motor in the current control period t and the speed reference value v ref is subjected to PI control to obtain the q-axis current reference value i qref ;

[0022] Convert the d-axis current reference value i dref and the q-axis current reference value i qref to αβ axis to obtain the αβ axis primary current reference value i 1αβref ;

[0023] For each selectable voltage vector, substitute it with the αβ axis primary current i 1αβ (t), the secondary angular velocity ω2(t), the secondary flux ψ 2αβ (t) and the excitation inductance observation value into the mathematical model of the linear induction motor to obtain the αβ axis primary current i 1αβ (t+1) of the next control period t+1 corresponding to the voltage vector, and calculate the difference between the αβ axis primary current reference value i 1αβref and the difference as a cost function;

[0024] Select the voltage vector with the minimum cost function as the voltage vector u αβ (t+1) in the next control period t+1, generate the corresponding inverter switching signal, and then in the next control period t+1, apply the generated switching signal to the inverter for controlling the linear induction motor.

[0025] Further preferably, the mathematical model of the linear induction motor is as follows:

[0026]

[0027] wherein, L1=L m0 +L l1 , L m0 is the excitation inductance when the motor is stationary, and L l1 is the primary leakage inductance; is the secondary inductance in the current control period t; T s(t) is the time length of the current control period t; R1 and R2 are the primary resistance and the secondary resistance of the linear induction motor respectively; j represents the imaginary operator; i 2αβ (t) is the αβ-axis secondary current of the linear induction motor in the current control period t.

[0028] Further preferably, the expression of the cost function is:

[0029] g = (i 1αref -i 1α (t+1)) 2 +(i 1βref -i 1β (t+1)) 2

[0030] wherein g represents the cost function value; i 1αref and i 1βref are the α-axis component and the β-axis component of the αβ-axis primary current reference i 1αβref ; i 1α (t+1) and i 1β (t+1) are the α-axis component and the β-axis component of the αβ-axis primary current i 1αβ (t+1) respectively.

[0031] Further preferably, the acquisition method of the αβ-axis primary current i 1αβ (t) and the secondary angular velocity ω2(t) of the linear induction motor in the current control period t comprises:

[0032] acquiring the phase current i 1abc of the linear induction motor in the current control period t and converting it to the αβ axis to obtain the αβ-axis primary current i 1αβ (t);

[0033] acquiring the speed signal v2(t) of the linear induction motor in the current control period t and calculating the secondary angular velocity ω2(t) according to

[0034] wherein τ represents the pole pitch of the linear induction motor.

[0035] In the fourth aspect, the present application provides a current control system of a linear induction motor, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to execute the current control method provided in the third aspect of the present application.

[0036] In the fifth aspect, the present application provides a linear induction motor system, comprising:

[0037] a linear induction motor;

[0038] ​An inverter, whose three-phase bridge arm midpoints are connected with three-phase windings of the linear induction motor respectively;

[0039] And a model predictive current control system of the linear induction motor provided by the fourth aspect of the application, which is connected with the linear induction motor and the inverter respectively.

[0040] Overall, the above technical solutions conceived by the application can achieve the following beneficial effects:

[0041] 1. The application provides a method for identifying excitation inductance of a linear induction motor, which uses back electromotive force as an observation value in each control cycle, calculates a back electromotive force observation value by constructing a reference model based on a sliding mode observer, calculates the back electromotive force by means of an adjustable model containing excitation inductance, and calculates the corresponding excitation inductance by describing the adaptive rate of the excitation inductance and the back electromotive force error, so as to realize identification of the excitation inductance. The application constructs a reference model irrelevant to the change amount of the excitation inductance, and uses a sliding mode term instead of a current differential term, thereby eliminating the noise caused by the current differential term in the existing reference model, avoiding the interference of the current noise on the observation result of the back electromotive force, and improving the accuracy of the excitation inductance identification.

[0042] 2. The method for identifying excitation inductance of a linear induction motor provided by the application further filters the observation value of the back electromotive force by using multiple cascaded and identical low-pass filters, compensates the obtained result, and takes the result as the final observation value of the back electromotive force. This process eliminates the inherent chattering problem of the sliding mode observer, and further improves the accuracy of the excitation inductance identification.

[0043] 3. The application provides a current control method of a linear induction motor, which uses the excitation inductance identification method provided by the first aspect of the application to identify the observation value of the excitation inductance, so as to realize accurate identification of the excitation inductance, and further improve the parameter robustness and control accuracy of the current control method. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 A linear induction motor excitation inductance identification method block diagram provided for the embodiment of the application;

[0045] Figure 2 A linear induction motor current control method block diagram provided for the embodiment of the application. DETAILED DESCRIPTION

[0046] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application. In addition, the technical features involved in the various embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0047] In the present application, the terms "first", "second", etc. (if any) in the present application and the drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence.

[0048] Before the technical solutions of the present application are explained in detail, the existing online identification method of excitation inductance of linear induction motor is analyzed and explained. In the following description, if no special description, the symbol represents the basic principle adopted is:

[0049] The superscript "^" represents the observation value;

[0050] The subscript "αβ" represents the αβ-axis quantity, and the subscripts "α" and "β" represent the α component and the β-axis component of the corresponding αβ-axis parameter, respectively;

[0051] The subscript "1" represents the primary parameter of the linear induction motor, and the subscript "2" represents the secondary parameter of the linear induction motor.

[0052] In a first aspect, the present application provides an excitation inductance identification method of a linear induction motor, as shown in Figure 1 The method comprises the following steps:

[0053] a. Calculation of the observation value of back electromotive force

[0054] Substitute the αβ-axis primary current i 1αβ (t) of the linear induction motor at the current control period t, the voltage vector u αβ (t) and the secondary angular velocity ω2(t) into the reference model based on the sliding mode observer to calculate the observation value of the back electromotive force

[0055] The reference model is:

[0056]

[0057] Wherein, is the observation value of i 1αβ (t); The leakage inductance coefficient of the motor L1=L m0 +L l1 , L m0 ​L is the magnetizing inductance of the motor at standstill l1 L is the primary leakage inductance; R is the primary resistance of the motor; k m and k n are preset gain parameters and are positive numbers; sign(·) is a sign function, which is 1 when the sign in the parentheses is positive, -1 when the sign in the parentheses is negative, and 0 when the sign in the parentheses is 0.

[0058] It should be noted that the T-type equivalent circuit model of the linear induction motor is obtained as follows:

[0059]

[0060] where u αβ = [u α , u β ] Τ , i 1αβ = [i 1α , i 1β ] Τ are the primary voltage and current, respectively; L1= L m0 + L l1 , L l1 is the primary leakage inductance, L m0 is the magnetizing inductance of the motor at standstill, and e m is the back electromotive force.

[0061] The magnetizing inductance based on identification can be established as a state equation with the primary current vector i 1αβ and the secondary flux linkage ψ 2αβ as state variables:

[0062]

[0063] where L2= L m0 + L l2 , L l2 is the secondary leakage inductance; ω2= vπ / τ is the secondary angular velocity; τ is the pole pitch; R1 and R2 are the primary and secondary resistances, respectively,

[0064] The above equation can be transformed as follows:

[0065]

[0066] It is noted that the reference model is also affected by the identified parameter L m , and the interaction between them will result in poor identification accuracy. The back electromotive force is selected as the observation quantity, which is defined as:

[0067]

[0068] where L mAnd L2 is LIM excitation inductance and secondary inductance respectively, ψ2 is LIM secondary flux linkage.

[0069] However, it still has current differential term, is easy to be affected by current noise, and the parameter identification accuracy and subsequent current control accuracy are difficult to guarantee. In view of this technical problem, the reference model is improved to eliminate the influence of current noise on back electromotive force observation result, thereby improving the accuracy of online identification of linear induction motor excitation inductance, and further improving the control accuracy of linear induction motor model predictive current control.

[0070] Because the voltage changes periodically, the following can be derived:

[0071]

[0072] Wherein, ω2=vπ / τ, is the secondary angular velocity.

[0073] Based on this, the above reference model can be further derived.

[0074] It should be noted that the observation error of the above reference model is:

[0075]

[0076] Wherein,

[0077] In order to ensure that the current observation error tends to 0, according to Lyapunov stability theorem, the condition Then the observer coefficient k m Satisfy the following constraints:

[0078]

[0079] Further derivation can be obtained:

[0080] k m > | RΔi 1αβ (t) + Δe m (t)|

[0081] When the current observation error converges, that is, Δi 1αβ (t) = 0, the following can be obtained:

[0082] Δe m (t) = -k m sign(Δi 1αβ (t))

[0083] Further derivation can be obtained:

[0084]

[0085] s is the integral symbol;

[0086] The transfer function of the designed sliding mode observer is:

[0087]

[0088] where, when k n > 0, the observer is stable, k m > 0, the observer is stable, k n and k m The signs should be the same, that is, both positive.

[0089] It should be noted that the transfer function of the sliding mode observer is in the form of a low-pass filter, which can eliminate the noise caused by the current differential term in the existing reference model.

[0090] b, the calculation of the calculated back electromotive force e m (t):

[0091] The calculated motor excitation current i m (t) = i 1αβ (t) + L2i 2αβ (t) / L m ; wherein i 2αβ (t) is the αβ axis secondary current of the linear induction motor at the current control period t; L2 = L m0 + L l2 , L l2 is the secondary leakage inductance;

[0092] Substitute i 1αβ (t), ω2(t) and i m (t) into the adjustable model to calculate the calculated back electromotive force e m (t); wherein the adjustable model is:

[0093]

[0094] wherein, and are the excitation inductance observation value and the corresponding secondary inductance at the last control period t-1; j is the imaginary symbol; is the secondary time constant at the last control period t-1; R2 is the secondary resistance;

[0095] c, identification of the excitation inductance observation value

[0096] Substitute and e m (t) into the adaptive rate to calculate the excitation inductance observation value ​And output as the excitation inductance identification result under the current control cycle t; where k p and k i All are positive numbers; s is the integral symbol.

[0097] It should be noted that, in the above process, the back electromotive force has already been observed using a sliding mode observer. However, it inevitably suffers from chattering caused by the sliding mode observer. Therefore, in one optional implementation, an adaptive compensation algorithm is further designed to eliminate sliding mode chattering. Specifically, the above-mentioned method for identifying the excitation inductance of a linear induction motor also includes:

[0098] The above-mentioned method for identifying the excitation inductance of a linear induction motor also includes:

[0099] After obtaining the observed value of the back electromotive force Afterwards, After filtering using n cascaded, identical low-pass filters, the result is... right To receive compensation And Updated to

[0100] in, for The result after passing through the first i-th stage low-pass filter; For the initial input i = 1, 2, ..., n, n ≥ 2.

[0101] Specifically, taking an n value of 2 as an example, the details are as follows: two cascaded low-pass filters are used; the transfer functions of the low-pass filters are:

[0102]

[0103] Where ω2 is the secondary angular velocity.

[0104] Specifically, after passing through the first-stage low-pass filter, the fundamental signal obtained after eliminating sliding mode chattering is:

[0105]

[0106] For the initial input

[0107] Therefore, ΔE can be obtained as:

[0108]

[0109] for The result after two low-pass filters.

[0110] Compensation The signal is obtained by eliminating the chattering of the back EMF observation value, and the expression is:

[0111]

[0112] In a second aspect, the present application provides a linear induction motor excitation inductance identification system, comprising: a memory and a processor, the memory stores a computer program, and the processor executes the computer program to execute the excitation inductance identification method provided in the first aspect of the present application.

[0113] The related technical solution is the same as the excitation inductance identification method provided in the first aspect of the present application, which will not be repeated here.

[0114] In an optional implementation, the linear induction motor excitation inductance identification system comprises: a reference module, an adjustable module, an adaptive module and a control module; in the current control period t:

[0115] The reference module is used for receiving the αβ-axis primary current i 1αβ (t) of the linear induction motor in the current control period t, the voltage vector u αβ (t) and the secondary angular velocity ω2(t), and substituting them into the reference model based on the sliding mode observer to calculate the observation value of the back EMF Wherein, the reference model is:

[0116]

[0117] Wherein, is the observation value of i 1αβ (t); The leakage inductance coefficient of the motor L1=L m0 +L l1 , L m0 is the excitation inductance when the motor is stationary, L l1 is the primary leakage inductance; R is the primary resistance of the motor; k m and k n are both preset gain parameters and are positive numbers; sign(·) is a sign function;

[0118] The adjustable module is used for receiving i 1αβ (t) and ω2(t), calculating the motor excitation current i m (t)=i 1αβ (t)+L2i 2αβ (t) / L m ; and i 1αβ (t), ω2(t) and i m(t) Substitute into the adjustable model for calculation to obtain the calculated value of the back electromotive force e. m (t); where i 2αβ (t) represents the αβ axis secondary current of the linear induction motor under the current control cycle t; L2 = L m0 +L l2 L l2 For secondary leakage inductance; the adjustable model is:

[0119]

[0120] in, and These are the observed values ​​of the excitation inductance and the corresponding secondary inductance under the previous control cycle t-1, respectively; j is the imaginary number sign; R1 is the secondary time constant under the previous control cycle t-1; R2 is the secondary resistance;

[0121] The adaptive module is used to... and e m (t) Substitute into the adaptive rate The calculation is performed to obtain the observed value of the excitation inductance under the current control period t. And output as the excitation inductance identification result under the current control cycle t; where k p and k i All are positive numbers; s is the integral symbol.

[0122] The related technical solutions are the same as the excitation inductance identification method provided in the first aspect of this invention, and will not be described in detail here.

[0123] Thirdly, the present invention provides a current control method for a linear induction motor, specifically a model predictive control method, such as... Figure 2 As shown, it includes:

[0124] A1. Obtain the primary current i of the αβ axis of the linear induction motor under the current control period t. 1αβ (t) and secondary angular velocity ω2(t), and voltage vector u αβ (t) After that, the excitation inductance observation value is identified using the excitation inductance identification method provided in the first aspect of the present invention. The related technical solutions are the same as the excitation inductance identification method provided in the first aspect of this invention, and will not be described in detail here;

[0125] In one alternative implementation, the αβ-axis primary current i of the linear induction motor under the current control period t is... 1αβ The methods for obtaining the secondary angular velocity ω2(t) and ωt include:

[0126] Collect the phase current i of the linear induction motor under the current control period t.1abc and convert it to the αβ axis to obtain the αβ axis primary current i 1αβ (t) ;

[0127] Collect the speed signal v2(t) of the linear induction motor at the current control period t, and according to Calculate the secondary angular velocity ω2(t) ; wherein τ represents the pole pitch of the linear induction motor.

[0128] It is easy to understand that the phase current signal i 1abc of the linear induction motor can be conveniently sampled by using a current sensor; the secondary speed signal v2(t) of the linear induction motor can be conveniently collected by using a speed sensor (or a position sensor); the voltage vector u αβ (t) at the current control period t is determined by the previous control period.

[0129] A2, the αβ axis primary current i 1αβ (t) of the linear induction motor at the current control period t, the secondary angular velocity ω2(t), the secondary flux linkage ψ 2αβ (t) and the excitation inductance observation value are substituted into the mathematical model of the linear induction motor to calculate the secondary flux linkage ψ 2αβ (t+1) at the next control period t+1.

[0130] In view of the delay caused by the calculation time of the actual control system, it is necessary to first further combine the mathematical model of the linear induction motor to make a prediction to compensate the influence of the delay, so as to improve the control accuracy of the controller. Through the sampling and observation value of the current control period t, the next control period t+1 is predicted.

[0131] The mathematical model of the linear induction motor is as follows:

[0132]

[0133] wherein, L1=L m0 +L l1 , L m0 is the excitation inductance when the motor is stationary, L l1 is the primary leakage inductance; is the secondary inductance at the current control period t; T s (t) is the time length of the current control period t; R1 and R2 are the primary resistance and the secondary resistance of the linear induction motor respectively; j represents the imaginary operator; i 2αβ (t) is the αβ axis secondary current of the linear induction motor at the current control period t.

[0134] After the secondary flux linkage is calculated, the corresponding flux linkage amplitude ||ψ2(t+1)|| and phase angle θ can be obtained. The phase angle θ can be used for coordinate transformation.

[0135] A3, PI control is performed on the difference between the secondary flux linkage ψ 2αβ (t+1) and the secondary flux linkage reference value ψ 2ref , to obtain the d-axis current reference value i dref ; PI control is performed on the difference between the secondary speed v2(t) of the linear induction motor in the current control period t and the speed reference value v ref , to obtain the q-axis current reference value i qref .

[0136] A4, the d-axis current reference value i dref and the q-axis current reference value i qref are converted to the αβ axis to obtain the αβ axis primary current reference value i 1αβref .

[0137] A5, for each voltage vector, the voltage vector is substituted into the mathematical model of the linear induction motor together with the αβ axis primary current i 1αβ (t), the secondary angular velocity ω2(t), the secondary flux linkage ψ 2αβ (t) and the excitation inductance observation value , to obtain the αβ axis primary current i 1αβ (t+1) of the next control period t+1 corresponding to the voltage vector, and the difference between the αβ axis primary current reference value i 1αβref and the αβ axis primary current i 1αβ (t+1) is calculated as a cost function.

[0138] In actual applications, the three-phase windings of the linear induction motor are respectively connected to the midpoints of the three-phase bridge arms of the inverter. In the inverter, the upper and lower ends of each phase bridge arm are respectively provided with a switching tube, S a , S b , S c respectively represent the driving signals of the upper switching tubes of the bridge arms connected to the A, B and C phase windings of the linear induction motor, 1 represents high level and 0 represents low level. It is easy to understand that the high level is the level that can make the upper switching tube of the bridge arm conduct and the lower switching tube of the bridge arm turn off, and the low level is the level that can make the upper switching tube of the bridge arm turn off and the lower switching tube of the bridge arm conduct. Therefore, according to the driving conditions of the switching tubes, there are 8 voltage vectors, and each voltage vector is shown in Table 1.

[0139] Table 1

[0140]

[0141] Each voltage vector is together with the αβ axis primary current i 1αβ (t), the secondary angular velocity ω2(t) and the secondary flux linkage ψ 2αβ(t) and the excitation inductance observation value After substituting into the mathematical model of the linear induction motor, the primary current i 1αβ (t+1) in the next control period can be solved.

[0142] g = (i 1αref -i 1α (t+1)) 2 +(i 1βref -i 1β (t+1)) 2

[0143] Wherein, g represents the cost function value; i 1αref and i 1βref are the α-axis component and the β-axis component of the primary current reference i 1αβref ; i 1α (t+1) and i 1β (t+1) are the α-axis component and the β-axis component of the primary current i 1αβ (t+1) respectively.

[0144] A6, select the voltage vector with the minimum cost function as the voltage vector u αβ (t+1) in the next control period t+1, generate the corresponding inverter switching signal, and then apply the generated switching signal to the inverter for controlling the linear induction motor in the next control period t+1.

[0145] It is easy to understand that in the next control period t+1, the bridge arm switching pulse signal of each phase is generated according to u αβ (t+1) to realize the control of the linear induction motor, and u αβ (t+1) is recorded for use in identifying the excitation inductance in the next control period.

[0146] The embodiment aims at the problems of poor parameter robustness and control performance easily affected by the change of excitation inductance when the traditional model predictive current control is applied to the linear induction motor. The identified excitation inductance is fed back to the control algorithm in real time, which greatly improves the parameter robustness of the control system.

[0147] In a fourth aspect, the present application provides a current control system of a linear induction motor, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to execute the current control method provided in the third aspect of the present application.

[0148] In one optional implementation, the current control system of the linear induction motor includes: a parameter identification module, a flux linkage observation module, a d-axis current control module, a q-axis current control module, a coordinate transformation module, a current prediction module, and an optimal vector selection module; under the current control period t:

[0149] The parameter identification module is used to obtain the αβ axis primary current i of the linear induction motor under the current control cycle t. 1αβ (t) and secondary angular velocity ω2(t), and voltage vector u αβ (t) After that, the excitation inductance observation value is identified using the excitation inductance identification method provided in the first aspect of the present invention.

[0150] The flux linkage monitoring module is used to measure the αβ axis primary current i of the linear induction motor under the current control period t. 1αβ (t), secondary angular velocity ω2(t), secondary magnetic flux ψ 2αβ (t) and observed values ​​of excitation inductance Substituting into the mathematical model of the linear induction motor, calculate the secondary flux linkage ψ in the next control cycle t+1. 2αβ (t+1);

[0151] The d-axis current control module is used to control the secondary magnetic flux ψ 2αβ (t+1) and the secondary flux reference value ψ 2ref The difference is used for PI control to obtain the d-axis current reference value i. dref ;

[0152] The q-axis current control module is used to control the secondary speed v2(t) of the linear induction motor and the speed reference value v during the current control cycle t. ref The difference is used for PI control to obtain the q-axis current reference value i. qref ;

[0153] The coordinate transformation module is used to transform the d-axis current reference value i dref and q-axis current reference value i qref Convert to the αβ axis to obtain the αβ axis primary current reference value i. 1αβref ;

[0154] The current prediction module is used to, for each selectable voltage vector, correlate it with the αβ-axis primary current i. 1αβ (t), secondary angular velocity ω2(t), secondary magnetic flux ψ 2αβ (t) and observed values ​​of excitation inductance Substituting into the mathematical model of the linear induction motor, we obtain the αβ-axis primary current i in the next control cycle t+1 corresponding to this voltage vector. 1αβ (t+1), and calculate the primary current reference value i along the αβ axis. 1αβrefthe difference between the voltage vector and the optimal voltage vector as a cost function;

[0155] The optimal vector selection module is configured to select the voltage vector with the minimum cost function as the voltage vector u αβ The inverter switching signal is generated, and the generated switching signal is applied to the inverter for controlling the linear induction motor in the next control period t+1.

[0156] The related technical solutions are the same as those of the excitation inductance identification method provided in the first aspect and the excitation inductance identification method provided in the third aspect of the present application, and thus will not be described herein.

[0157] In the fifth aspect, the present application provides a linear induction motor system, which comprises:

[0158] The linear induction motor;

[0159] The inverter, whose three-phase bridge arm midpoints are connected to the three-phase windings of the linear induction motor, respectively;

[0160] The model predictive current control system of the linear induction motor provided in the fourth aspect of the present application, which is connected to the linear induction motor and the inverter, respectively.

[0161] The related technical solutions are the same as those of the model predictive current control system of the linear induction motor provided in the fourth aspect of the present application, and thus will not be described herein.

[0162] Those skilled in the art can easily understand that the above description is only the preferred embodiments of the present application, and is not intended to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for excitation inductance identification of a linear induction motor, characterized in that, Comprising: in the current control cycle t The following operations are performed: determining whether the current control period is the last control period t The following describes a linear induction motor Shaft primary current Voltage vector And secondary angular velocity The observed value of back electromotive force is calculated by substituting the above into the reference model based on the sliding mode observer The reference model is: wherein is the observed value; ; leakage inductance coefficient of the motor ; L 1= L m0 + L l1 , L m0 is the magnetizing inductance when the motor is at rest, L l1 is the primary leakage inductance; R is the primary resistance of the motor; k m and k n are each a preset gain parameter and are each positive; is a sign function; The motor excitation current is calculated ; wherein is the current control period t The linear induction motor described below The shaft secondary current L 2= L m0 + L l2 , L l2 is the secondary leakage inductance Substitute the values of , and into the adjustable model to calculate the calculated value of back electromotive force ; the adjustable model is: wherein and are the excitation inductance observation and the corresponding secondary inductance, respectively, in the previous control cycle t -1; ; j is the imaginary unit; is the secondary time constant in the previous control cycle t -1; R 2 is the secondary resistance; Calculate in and substitute to obtain the excitation inductance observation value under the current control period t , and output as the excitation inductance identification result under the current control period ; wherein, t k p and k i are positive numbers; s is the integral symbol;​ The excitation inductance identification method further comprises: Obtaining the observed value of back electromotive force Afterwards, compensating with the observed value of back electromotive force, obtaining n After filtering processing with one cascade and same low-pass filter, obtaining , compensating , obtaining , and updating to ; wherein ; is the result after a pre i -stage low-pass filter; is the initial input ; , n ≥ 2.

2. A field inductance identification system for a linear induction motor, characterized by Comprising: A memory and a processor, the memory stores a computer program, and the processor executes the computer program to execute the excitation inductance identification method in claim 1.

3. A current control method for a linear induction motor, characterized by, Comprising: acquiring a current control period t The linear induction motor described below Shaft primary current i 1αβ ( t ) and secondary angular velocity ω 2( t ), and voltage vector After that, the excitation inductance observation value is identified by using the excitation inductance identification method in claim 1 ; the current control period t The linear induction motor described below The shaft primary current i 1αβ ( t ), secondary angular velocity ω 2( t ), secondary flux linkage and excitation inductance observation value are substituted into the mathematical model of the linear induction motor, and the secondary flux linkage t +1 in the next control period is calculated. For secondary magnetic flux With secondary flux reference value The difference is used for PI control to obtain the d-axis current reference value. For the current control cycle t The secondary speed of the linear induction motor described below v 2( t ) and speed reference value v ref The difference is used for PI control to obtain the q-axis current reference value. ; The d-axis current reference value and the q-axis current reference value are converted to the αβ-axis to obtain the αβ-axis primary current reference value ; For each of the optional voltage vectors, it is substituted into the mathematical model of the linear induction motor to obtain the next control period axial primary current i 1αβ ( t ), secondary angular velocity ω 2( t ), secondary magnetic flux and excitation inductance observation value , to obtain the next control period t +1 axial primary current i 1αβ ( t+ 1) corresponding to the voltage vector, and calculate the difference between the axial primary current reference value , as a cost function; selecting a voltage vector with the minimum cost function as the next control period t voltage vector under +1 , after generating the corresponding inverter switching signal, in the next control period t +1, the generated switching signal is applied to the inverter for controlling the linear induction motor.

4. The current control method according to claim 3, characterized by, The mathematical model of the linear induction motor is as follows: wherein, ; L 1= L m0 + L l1 , L m0 is the magnetizing inductance when the motor is at rest, L l1 is the primary leakage inductance; is the secondary inductance in the current control period t ; ; is the length of the current control period t ; R 1and R 2are the primary resistance and the secondary resistance of the linear induction motor, respectively; j denotes the imaginary unit; is the secondary current of the t axis of the linear induction motor in the current control period .

5. The current control method according to claim 3, wherein The expression of the cost function is: in, g This represents the cost function value; and They are respectively Shaft primary current reference value α-axis components and β-axis components; and They are respectively Shaft primary current i 1αβ ( t+ 1) Axial components and Axial components.

6. The current control method according to any one of claims 3 to 5, characterized by, Current control cycle t The following describes a linear induction motor Shaft primary current i 1αβ ( t ) and secondary angular velocity ω 2( t ) acquisition methods include: acquiring a current control period t the phase current of the linear induction motor i 1abc and converting it to the axis, obtaining the axis primary current i 1αβ ( t ) acquiring a current control period t the speed signal of the linear induction motor described below v 2( t ), and according to calculating the secondary angular velocity ω 2( t ); wherein, denotes the pole pitch of the linear induction motor.

7. A current control system for a linear induction motor, characterised in that, Comprising: A memory and a processor, the memory stores a computer program, and the processor executes the computer program to execute the current control method in any one of claims 3-6.

8. A linear induction motor system characterized by, Comprising: A linear induction motor; An inverter, the three-phase bridge arm midpoints of which are respectively connected to the three-phase windings of the linear induction motor; And the model predictive current control system of the linear induction motor in claim 7, which is respectively connected to the linear induction motor and the inverter.

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