LC filtering type permanent magnet motor system prediction flux linkage control method and system and medium

Abstract

The invention discloses an LC filtering type permanent magnet motor system prediction flux linkage control method and system and a medium, and belongs to the field of power electronics and power transmission. State variables of an LC filtering type permanent magnet motor system at the k moment are sampled, a discrete state-space equation of the system is established by adopting a zero-order retainer method, and a stator flux linkage vector prediction model is established; obtaining a stator flux linkage vector reference by using the electromagnetic torque reference and the parameters of the permanent magnet motor; constructing a loss function, and solving an inverter optimal control vector reference considering the system voltage constraint; park inverse transformation is referred to for the optimal control vector of the inverter, control pulses are generated through space vector modulation and act on an inverter switching tube, and LC filtering type permanent magnet motor system predictive flux linkage control is completed. According to the method, common control of the torque and the flux linkage can be realized only by controlling the stator flux linkage vector, and excellent torque flux linkage control performance can be obtained without any design parameter.

Description

Technical Field

[0001] The present invention discloses a predictive flux linkage control method, system and medium for an LC-filtered permanent magnet motor system, belonging to the field of power electronics and electric drive. Background Technique

[0002] Permanent magnet motors play an important role in the field of industrial drive due to their high efficiency, high power density and compact structure. However, in the applications of permanent magnet motor drives fed by long-distance power supply and wide-bandgap power converters, the inverter output voltage has a higher dv / dt, which in turn causes serious overvoltage problems in the permanent magnet motor, greatly reducing the motor life. For this reason, an LC filter is generally added to the output side of the frequency converter in industry to filter out the high dv / dt in the inverter output voltage, forming an LC-filtered permanent magnet motor system. Although this scheme can improve the electromagnetic compatibility, the introduced LC filter network and the motor stator inductance form a high-order coupling system, increasing the control complexity of the system.

[0003] The prior art with the publication number of CN111431460A discloses a sensorless model predictive flux linkage control method for a permanent magnet motor. First, the motor speed ω and the rotor position angle θ are observed through a sliding mode observer and a phase-locked loop based on SOGI e ; then, the given speed ω * and the speed ω pass through a speed loop SMC controller to obtain the given torque T e* ; then, from the speed ω and the d / q-axis currents i d / i q the load disturbance value is observed and the load disturbance value is fed forward and compensated to the given torque T e* ; finally, the observed speed ω, rotor position angle θ e , given torque T e* , load disturbance value, and the sampled three-phase voltages u a / u b / u c , three-phase currents i a / i b / i c etc. are substituted into the model predictive flux linkage control module for operation. This method has cumbersome prediction steps and a large amount of computation due to the lack of effective information acquisition means.

[0004] The existing control method of LC filter type permanent magnet motor system is to adopt proportional integral control, but the high-order coupling characteristics of LC filter type permanent magnet motor system make the cascade loop and control parameters of proportional integral control increase significantly, the phase lag is aggravated, and the dynamic response is difficult to meet the requirements. Model predictive control has the characteristics of intuitive physical meaning and multi-objective optimization, and is regarded as an effective solution to solve the control problem of high-order systems. The traditional multi-objective predictive control methods of LC filter type permanent magnet motor system all control the voltage and current loops, without directly controlling the torque and flux, and cannot meet the requirements of high dynamic response of torque and flux in actual engineering; secondly, the existing predictive control methods are mostly based on the finite control set predictive control architecture, which has the disadvantage of unfixed switching frequency, which will aggravate the torque and flux pulsation of the motor and is not conducive to the design of LC filter. In addition, the existing predictive control methods often need to introduce multiple weight factors to balance multiple control objectives, resulting in large workload of parameter setting and difficulty in ensuring optimal performance. Therefore, it is urgent to design a predictive control method for LC filter type permanent magnet motor system that is simple to implement and can directly optimize flux and torque. Summary of the invention

[0005] In view of the shortcomings of the prior art, a predictive flux control method for an LC filter permanent magnet motor system is provided. By establishing a stator flux prediction model for the LC filter permanent magnet motor system, a quadratic cost function based on the stator flux vector reference and the tracking error of the prediction model is designed, and the optimal control instruction that can minimize the quadratic cost function and satisfy the inverter voltage constraint is calculated, thereby achieving unified control of torque and flux. The present invention is simple to implement, does not require any design parameters, and can effectively improve the dynamic and steady-state tracking performance of torque and flux.

[0006] To achieve the above technical objectives, the present invention discloses a method for predicting flux linkage control of an LC filter type permanent magnet motor system, the steps of which are as follows:

[0007] The state variables of the LC filter type permanent magnet motor system are sampled by the sensor at time k, and the Park transformation is performed on the state variables;

[0008] The discrete state space equation of the LC filter permanent magnet motor system is constructed by using the zero-order retainer discretization method and the state complex vector after Park transformation.

[0009] Based on the discrete state space equation, the stator flux vector prediction model of the LC filter permanent magnet motor system is established;

[0010] The electromagnetic torque reference is calculated by using the proportional integral control of the error between the electrical angular velocity reference and feedback, and the stator flux vector reference is obtained by combining the permanent magnet motor information: permanent magnet flux, stator inductance and pole pair number parameters;

[0011] Construct a loss function based on the square of the two-norm of the stator flux vector prediction error by using the error between the stator flux vector reference and the stator flux vector prediction model;

[0012] Calculate the optimal control vector reference of the inverter considering the maximum voltage constraint of the inverter in the LC-filtered permanent magnet motor system by solving the loss function;

[0013] Perform an inverse Park transformation on the optimal control vector reference of the inverter, and generate pulses to control the switching tubes of the inverter through space vector modulation to achieve direct control of the torque and flux of the LC-filtered permanent magnet motor.

[0014] Furthermore, the LC-filtered permanent magnet motor system includes a three-phase inverter, an output LC filter, and a permanent magnet motor connected in series. The state variables of the LC-filtered permanent magnet motor system sampled by sensors at time k include: the three-phase filter inductor current i fabc,k , the three-phase filter capacitor voltage v sabc,k , and the three-phase stator current i sabc,k . The electrical angle θ e of the motor rotor and the electrical angular velocity ω e are also detected in real time; the speed loop uses a PI controller, and the proportional coefficient and integral coefficient involved in the PI controller are calculated and tuned through a typical type II system; the speed loop feeds back the error between the input speed command ω e * and the actual speed ω e into the internal PI regulator of the speed loop to generate a reference value T e * of the electromagnetic torque for adjusting the electromagnetic torque; use the Park transformation to transform the sampled three-phase state variables into dq-axis state complex vectors: the filter inductor current i f = i fd + ji fq , the filter capacitor voltage v s = v sd + jv sq , and the stator current i s = i sd + ji sq , where j is the imaginary unit of the complex vector, i fd , i fq are the d-axis and q-axis components of the filter inductor current, v sd , v sq are the d-axis and q-axis components of the filter capacitor voltage, i sd , i sq are the d-axis and q-axis components of the stator current.

[0015] Furthermore, Park transformation transforms the abc three-phase state variables into the dq-axis state complex vectors; Park inverse transformation converts the inverter optimal control vector reference of the dq-axis into the inverter optimal control vector reference of the αβ-axis.

[0016] Furthermore, the method for constructing the discrete state space equation of the LC-filtered permanent magnet motor system is as follows:

[0017] ;

[0018] Wherein, , , , ;

[0019] In the formula, is the state matrix composed of the filter inductor current, filter capacitor voltage and stator current at the (k + 1)-th moment, A d , B d , D d are the coefficient matrices of the discrete state space equation calculated by the zero-order hold method, is the state matrix composed of the filter inductor current, filter capacitor voltage and stator current sampled at the k-th moment, v i,k is the three-phase inverter output voltage at the k-th moment, A, B, D are the coefficient matrices of the LC-filtered permanent magnet motor system in the continuous time domain, e is the base of the natural logarithm, T s is the sampling period, represents the evolution process of the LC-filtered permanent magnet motor system from the current k-th moment state x k to the (k + 1)-th moment state x k+1 , also known as the state transition matrix; I is the third-order identity matrix, ω e is the electrical angular velocity of the motor, L f represents the filter inductor, C f represents the filter capacitor, L s represents the motor stator inductor, R s represents the motor stator resistance, ψ f represents the permanent magnet flux linkage of the motor, jω e ψ f represents the back electromotive force complex vector of the motor.

[0020] Furthermore, the stator flux linkage vector prediction model established based on the discrete state space equation is as follows:

[0021] ;

[0022] In the formula, represents the predicted value of the stator flux linkage vector composed of the d-axis and q-axis stator flux linkage components and at the (k + 1)-th moment, is the coefficient matrix, and j represents the imaginary unit of the complex vector.

[0023] Furthermore, the method for obtaining the stator flux vector reference is as follows:

[0024] ;

[0025] In the formula, represents the stator flux vector reference, and are the real and imaginary parts of the stator flux vector reference, respectively, that is, the d-axis and q-axis stator flux reference components; and are the amplitude and argument of the stator flux vector reference calculated using the permanent magnet flux ψ f , the stator inductance L s , the electromagnetic torque reference T e * and the number of pole pairs p.

[0026] Furthermore, based on the error between the stator flux vector reference and the stator flux vector prediction model, a loss function J based on the square of the two-norm of the stator flux vector prediction error is constructed:

[0027] ;

[0028] In the formula, ψ s * is the stator flux vector reference, represents the predicted value of the stator flux vector at time k + 1, represents the two-norm operation, which is obtained by first squaring and then taking the square root of the sum of the squares of the real and imaginary parts of the complex vector inside the operator, and is equivalent to the magnitude of the complex vector.

[0029] Furthermore, the specific process of solving the optimal control vector reference of the inverter in the dq-axis considering the maximum voltage constraint of the LC-filtered permanent magnet motor system through the loss function is as follows:

[0030] ;

[0031] where, v i * represents the optimal control vector reference of the inverter that can minimize the loss function J without considering the system voltage constraint, and is obtained by solving the partial derivative of the loss function J with respect to the inverter output voltage and setting the partial derivative equal to 0:

[0032] ;

[0033] In the formula, and is the real part and the imaginary part of v i * , is the two-norm of the reference of the optimal control vector of the inverter, i.e., the amplitude of is the maximum voltage constraint of the system, represents that when the amplitude of v i * is greater than the maximum voltage constraint of the inverter , v will be scaled down proportionally according to i * to obtain the reference of the optimal control vector of the inverter under the dq axis considering the maximum voltage constraint of the inverter . .

[0034] A predictive flux linkage control system for an LC-filtered permanent magnet motor system, comprising a sensor detection unit, a Park transformation unit, and a predictive flux linkage control unit connected in sequence. The predictive flux linkage control unit includes a proportional-integral unit, a stator flux linkage vector prediction model establishment unit, a stator flux linkage vector reference calculation unit, and a loss function calculation unit, an optimal control vector reference unit, a Park transformation unit, and a space vector modulation unit connected in sequence; wherein the proportional-integral unit is connected to the stator flux linkage vector reference calculation unit, and both the stator flux linkage vector reference calculation unit and the stator flux linkage vector prediction model establishment unit are connected to the loss function calculation unit;

[0035] The sensor detection unit is used to obtain the three-phase filter inductor current, the three-phase filter capacitor voltage, and the three-phase stator current, and to detect the electrical angle and electrical angular velocity of the motor rotor in real time;

[0036] The Park transformation unit is used to transform the sampled abc three-phase state variables into dq-axis state complex vectors;

[0037] The proportional-integral unit controls the speed of the permanent magnet motor and calculates the electromagnetic torque reference through the proportional-integral of the error between the electrical angular velocity reference and the feedback;

[0038] The stator flux linkage vector prediction model establishment unit is used to establish a stator flux linkage vector prediction model for the LC-filtered permanent magnet motor system;

[0039] The stator flux linkage vector reference calculation unit calculates the stator flux linkage vector reference by using the permanent magnet flux linkage, stator inductance, and number of pole pairs information of the permanent magnet motor collected by the sensor detection unit and combining with the electromagnetic torque reference;

[0040] The loss function calculation unit constructs a loss function based on the square of the two-norm of the stator flux linkage vector prediction error by using the error between the stator flux linkage vector reference and the stator flux linkage vector prediction model;

[0041] Optimal control vector reference unit, which obtains the optimal control vector reference of the dq-axis inverter considering the maximum voltage constraint of the inverter in the LC-filtered permanent magnet motor system;

[0042] Park inverse transformation unit, which is used to transform the optimal control vector reference of the dq-axis inverter into the optimal control vector reference of the αβ-axis inverter;

[0043] Space vector modulation unit, which is used to generate pulses to control the switching tubes of the inverter.

[0044] A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, and the computer program is adapted to be loaded and executed by a processor to perform the predictive flux control method for the LC-filtered permanent magnet motor system.

[0045] Compared with the prior art, the beneficial effects of the present invention are as follows: for the prior art of the LC-filtered permanent magnet motor system, most are multi-objective voltage and current predictive control, and multiple weight coefficients need to be introduced to balance the control objectives, resulting in cumbersome weight tuning and poor dynamic and steady-state performance due to the inability to directly control torque and flux; in contrast, the method provided by the present invention can achieve direct control of torque and flux by controlling the stator flux vector, and no design parameters are introduced, the implementation is simple, and the performance is not limited by parameters, so better torque and flux control performance can be obtained. In addition, the method provided by the present invention generates pulses based on space vector modulation. Compared with the existing predictive control method based on a finite control set, it can effectively reduce the steady-state ripple of torque and flux, and the switching frequency is constant, which is more convenient for the design of the LC filter. Description of the Drawings

[0046] Figure 1 It is a structural block diagram of the predictive control method for the LC-filtered permanent magnet motor system of the present invention.

[0047] Figure 2 It is a steady-state response diagram of the stator flux, electromagnetic torque, and stator current of the LC-filtered permanent magnet motor under the method of the present invention.

[0048] Figure 3 It is a steady-state response diagram of the stator flux, electromagnetic torque, and stator current of the LC-filtered permanent magnet motor under the traditional multi-objective predictive control method.

[0049] Figure 4 It is a dynamic response diagram of the stator flux, electromagnetic torque, and stator current of the LC-filtered permanent magnet motor under sudden load under the method of the invention.

[0050] Figure 5 It is a dynamic response diagram of the stator flux, electromagnetic torque, and stator current of the LC-filtered permanent magnet motor under sudden load under the traditional multi-objective predictive control method. Detailed implementation manners

[0051] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0052] Figure 1 For the LC filter type permanent magnet motor system of the present invention and the corresponding flow block diagram of the predictive control method for the LC filter type permanent magnet motor system. Among them, the DC bus voltage is converted into an AC voltage square wave signal through a three-phase voltage source inverter, and then connected to the permanent magnet motor through an output LC filter. Sampling is performed on the three-phase filter inductor current i fabc of the LC filter type permanent magnet motor system, the three-phase filter capacitor voltage u sabc and the three-phase motor stator current i sabc is performed. Figure 1 In, V dc represents the DC bus voltage; L f represents the filter inductor on the output side of the inverter, and C f represents the filter capacitor. θ e and ω e are respectively the electrical angle and electrical angular velocity of the motor rotor; the speed loop adopts a PI control method, and the proportional coefficient and integral coefficient involved in the PI controller are calculated and tuned through a typical II system; the speed loop inputs the speed command (ω e * ) and the error between the actual speed (ω e ) into the internal PI regulator of the speed loop through closed-loop feedback to generate an electromagnetic torque reference value (T e * ) for adjusting the electromagnetic torque. The speed loop dynamically converts the speed command into a torque reference command to ensure high-precision speed regulation of the motor; ψ sd * is the set reference value of the stator flux linkage on the d-axis, and T e * is the electromagnetic torque reference output by the outer speed loop; i f,k , u s,k , i s,k respectively represent the inverter current, capacitor voltage, and stator current sampled in the dq coordinate system at the kth moment; v* ic is the optimal control reference command.

[0053] The predictive flux linkage control method for the LC filter type permanent magnet motor system includes the following steps:

[0054] Step 1: Establish a continuous-time domain state space model x of the LC filter type permanent magnet motor system:

[0055] ;

[0056] In the formula, d represents the differential operator, is the state variable in the continuous-time domain of the LC filter type permanent magnet motor system, is the output voltage of the inverter. The specific expressions of matrices A, B, and D are:

[0057] , , ;

[0058] In the formula, j represents the imaginary unit, L f , C f , L s , R s and ψ f respectively represent: the value of the filter inductor, the value of the filter capacitor, the value of the stator inductor of the motor, the value of the stator resistance of the motor, and the value of the rotor magnetic flux of the motor. jω e ψ f represents the back electromotive force of the permanent magnet motor.

[0059] Step 2: Use the zero-order hold to discretize the continuous-time domain state space model to establish the stator magnetic flux prediction model ψ s,k+1 , which is specifically implemented through the following formula:

[0060] ;

[0061] In the formula, represents the predicted value of the stator magnetic flux at the future k + 1 moment. The output matrix ; is the state variable matrix composed of the filter inductor current, the filter capacitor voltage, and the stator current value of the motor sampled at the k moment, is the predicted value at the k + 1 moment obtained after discretization by the zero-order hold, , are the discrete state matrix and the discrete input matrix respectively, is the constant perturbation matrix, I is the third-order unit diagonal matrix, T s is the sampling period.

[0062] Step 3: Design the quadratic cost function J based on the stator magnetic flux reference tracking, which is implemented through the following formula:

[0063] ;

[0064] In the formula, ψ s * is the stator magnetic flux vector reference, and the specific expression is as follows:

[0065] ;

[0066] In the formula, denotes the amplitude of the stator flux vector reference, where ψ sd * is the set d-axis reference value of the stator flux, T e * is the electromagnetic torque reference output by the outer speed loop, and p is the number of pole pairs of the motor.

[0067] Step 4: Solve for the optimal control command v that minimizes the quadratic cost function J and satisfies the inverter voltage constraint ic * Designed through the following mathematical model:

[0068] First, let the partial derivative of the quadratic cost function J with respect to the inverter output voltage be equal to 0, i.e.: , then the unconstrained optimal control command v that can minimize J can be obtained i * , v i * The specific expression of is:

[0069] ;

[0070] Secondly, considering the maximum value constraint of the inverter voltage in the actual hardware, the optimal control command v that minimizes the quadratic cost function J and satisfies the inverter voltage constraint ic * is calculated by the following formula:

[0071] ;

[0072] In the formula, is the amplitude of the optimal control command at time k; the maximum inverter voltage constraint V max is one-third of the square root of the inverter DC bus voltage value V dc .

[0073] To verify the predictive flux control method for the LC-filtered permanent magnet motor system provided by the present invention, the method provided by the present invention is applied to the LC-filtered permanent magnet motor system, and the system parameters are given in Table 1:

[0074] Table 1 .

[0075] The DC bus voltage in Table 1 is a range value, the lower limit voltage corresponding to the speed is 150V, and the highest voltage is freely set within the range allowed by the hardware.

[0076] Figure 2 、 Figure 3They are respectively the comparison diagrams of the steady-state responses of the stator flux linkage, electromagnetic torque, and stator current of the LC-filtered permanent magnet motor under the method provided by the present invention and the traditional multi-objective predictive control method. By comparing and observing Figure 2 and Figure 3 it can be seen that compared with the traditional multi-objective model predictive control method, the electromagnetic torque and stator flux linkage ripples under the method of the present invention are smaller, the sinusoidality of the stator current is higher, and it has better steady-state performance.

[0077] Figure 4 、 Figure 5 They are respectively the comparison diagrams of the dynamic responses of the stator flux linkage, electromagnetic torque, and stator current of the LC-filtered permanent magnet motor under sudden load conditions under the method provided by the invention and the traditional multi-objective predictive control method. By comparing and observing Figure 4 and Figure 5 the waveforms, it can be seen that the dynamic process of the traditional multi-objective model predictive control method has large oscillations and obvious oscillation phenomena; in contrast, the method provided by the present invention has a fast dynamic response. Therefore, the dynamic performance of the method of the present invention is superior to that of the traditional multi-objective model predictive control method.

Claims

1. A method for predicting flux linkage control of a LC filter type permanent magnet motor system, characterized in that: Here are the steps: The state variables of the LC filter type permanent magnet motor system are sampled by the sensor at time k, and the Park transformation is performed on the state variables; The discrete state space equation of the LC filter permanent magnet motor system is constructed by using the zero-order retainer discretization method and the state complex vector after Park transformation. Based on the discrete state space equation, the stator flux vector prediction model of the LC filter permanent magnet motor system is established; The electromagnetic torque reference is calculated by using the proportional integral control of the error between the electrical angular velocity reference and feedback, and the stator flux vector reference is obtained by combining the permanent magnet motor information: permanent magnet flux, stator inductance and pole pair number parameters; By using the error between the stator flux vector reference and the stator flux vector prediction model, a loss function based on the square of the stator flux vector prediction error is constructed. The optimal control vector reference of the inverter considering the maximum voltage constraint of the inverter in the LC filter permanent magnet motor system is obtained by loss function calculation; The inverter optimal control vector reference is subjected to Park inverse transformation, and pulses are generated through space vector modulation to control the switching tube of the inverter, thereby realizing direct control of the torque and flux of the LC filter type permanent magnet motor.

2. The LC filter type permanent magnet motor system predictive flux control method according to claim 1, characterized in that: The LC filter type permanent magnet motor system includes a three-phase inverter, an output LC filter and a permanent magnet motor which are sequentially cascaded. The state variables of the LC filter type permanent magnet motor system at time k sampled by the sensor include: the three-phase filter inductor current i fabc,k , three-phase filter capacitor voltage v sabc,k and the three-phase stator current i sabc,k , and detect the motor rotor electrical angle θ in real time e and electrical angular velocity ω e ; The speed loop adopts PI controller, and the proportional coefficient and integral coefficient involved in the PI controller are calculated and adjusted through the typical II system; the speed loop converts the input speed command ω into e * With the actual speed ω e The error is input into the internal PI regulator of the speed loop to generate the electromagnetic torque reference value T e * Used to adjust the electromagnetic torque; use Parker transformation to transform the sampled three-phase state variables into dq axis state complex vector: filtered inductor current i f = i fd + ji fq 、Filter capacitor voltage v s = v sd + jv sq and the stator current i s = i sd +ji sq , where j is the imaginary unit of the complex vector, i fd , i fq are the d-axis and q-axis components of the filter inductor current, v sd 、v sq is the d-axis and q-axis components of the filter capacitor voltage, i sd 、i sq are the d-axis and q-axis components of the stator current.

3. The method for predicting flux linkage control of an LC filter type permanent magnet motor system according to claim 2, characterized in that: The Park transform transforms the abc three-phase state variables into the dq axis state complex vector; the Park inverse transform transforms the dq axis inverter optimal control vector reference into the αβ axis inverter optimal control vector reference.

4. The method for predicting flux linkage control of an LC filter type permanent magnet motor system according to claim 2, characterized in that: The discrete state space equation construction method of LC filter permanent magnet motor system is as follows: ； in, ， ， ， ； In the formula, is the state matrix composed of the filter inductor current, filter capacitor voltage and stator current at time k+1, A d , B d , D d is the coefficient matrix of the discrete state space equation calculated using the zero-order holder method, is the state matrix composed of the filter inductor current, filter capacitor voltage and stator current sampled at time k, v i,k is the output voltage of the three-phase inverter at time k, A, B, D are the coefficient matrices of the LC filter permanent magnet motor system in the continuous time domain, e is the base of the natural logarithm, T s is the sampling period, It means that the LC filter permanent magnet motor system is discretized from the current state x at time k k At time k+1, the state x k+1 The evolution process is also called the state transfer matrix; I is the third-order unit matrix, ω e is the electrical angular velocity of the motor, L f Indicates filter inductance, C f Indicates filter capacitor, L s Represents the motor stator inductance, R s represents the motor stator resistance, ψ f represents the permanent magnet flux of the motor, jω e ψ f Represents the motor back-electromotive force complex vector.

5. The LC filter type permanent magnet motor system predictive flux control method according to claim 4, characterized in that: The stator flux vector prediction model established based on the discrete state space equation is as follows: ； In the formula, Represents the stator flux components of the d-axis and q-axis and The predicted value of the stator flux vector at time k+1 is is the coefficient matrix, and j represents the imaginary unit of the complex vector.

6. The LC filter type permanent magnet motor system predictive flux control method according to claim 5, characterized in that: The stator flux vector reference is obtained as follows: ； In the formula, represents the stator flux vector reference, and are the real and imaginary parts of the stator flux vector reference, i.e., the d-axis and q-axis stator flux reference components, respectively; and They are respectively based on the permanent magnetic flux ψ f , stator inductance L s , electromagnetic torque reference T e * The amplitude and argument of the stator flux vector reference calculated using the pole pair number p.

7. The LC filter type permanent magnet motor system predictive flux control method according to claim 6, characterized in that: Through the error between the stator flux vector reference and the stator flux vector prediction model, a loss function J based on the square of the stator flux vector prediction error is constructed: ； In the formula, ψ s * is the stator flux vector reference, represents the predicted value of the stator flux vector at time k+1, represents the two-norm operation, which is obtained by taking the square root of the sum of the real and imaginary parts of the complex vector within the operator, and is equivalent to the magnitude of the complex vector.

8. The LC filter type permanent magnet motor system predictive flux control method according to claim 7, characterized in that: By solving the loss function, the optimal control vector reference of the inverter under the dq axis considering the maximum voltage constraint of the LC filter permanent magnet motor system is obtained. The specific process is as follows: ； Among them, v i * It represents the optimal control vector reference of the inverter that can minimize the loss function J when the system voltage constraint is not considered. By solving the loss function J, the inverter output voltage The partial derivative of , and let the partial derivative equal to 0 to obtain: ； In the formula, and Yes i * The real and imaginary parts of is the second norm of the inverter optimal control vector reference, that is, The amplitude of is the maximum voltage constraint of the system, Indicates that when v i * The amplitude Greater than the maximum voltage constraint of the inverter When v i * according to The optimal control vector reference of the inverter under the dq axis considering the maximum voltage constraint of the inverter is obtained after proportional reduction. .

9. An LC filter type permanent magnet motor system prediction flux control system, characterized in that: It includes a sensor detection unit, a Parker conversion unit and a predicted flux control unit connected in sequence, wherein the predicted flux control unit includes a proportional integral unit, a stator flux vector prediction model establishment unit, a stator flux vector reference calculation unit, and a loss function calculation unit, an optimal control vector reference unit, a Parker inverse transformation unit and a space vector modulation unit connected in sequence; The proportional integral unit is connected to the stator flux vector reference calculation unit, and the stator flux vector reference calculation unit and the stator flux vector prediction model establishment unit are both connected to the loss function calculation unit; A sensor detection unit is used to obtain the three-phase filter inductor current, the three-phase filter capacitor voltage and the three-phase stator current, and detect the motor rotor electrical angle and electrical angular velocity in real time; A Parker transformation unit is used to transform the sampled abc three-phase state variables into a dq axis state complex vector; A proportional-integral unit controls the speed of the permanent magnet motor and calculates the electromagnetic torque reference by proportionally integrating the error between the electrical angular velocity reference and the feedback; A stator flux vector prediction model building unit is used to build a stator flux vector prediction model for an LC filter type permanent magnet motor system; A stator flux vector reference calculation unit calculates the stator flux vector reference by combining the permanent magnet flux, stator inductance and pole pair number information of the permanent magnet motor collected by the sensor detection unit with the electromagnetic torque reference; The loss function calculation unit uses the error between the stator flux vector reference and the stator flux vector prediction model to construct a loss function based on the square of the stator flux vector prediction error. An optimal control vector reference unit, which obtains an optimal control vector reference of a dq-axis inverter considering a maximum voltage constraint of an inverter of an LC filter type permanent magnet motor system; A Parker inverse transformation unit, used to transform the optimal control vector reference of the dq-axis inverter into the optimal control vector reference of the αβ-axis inverter; The space vector modulation unit is used to generate pulses to control the switching tubes of the inverter.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which is suitable for being loaded by a processor and executing the LC filter type permanent magnet motor system predictive flux control method according to any one of claims 1 to 8.

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