A method and device for predictive current control of a permanent magnet synchronous motor using a finite control set

Abstract

The present invention discloses a finite control set predictive current control method and control device for a permanent magnet synchronous motor. The control method includes the following steps: establishing a mathematical model of the permanent magnet synchronous motor that takes into account the nonlinear effects of the inverter; correcting the voltage vector output by the inverter based on the current polarity of the permanent magnet synchronous motor and the switching state of the inverter; using the corrected voltage vector to estimate and predict the current of the permanent magnet synchronous motor at a future time; calculating a predefined cost function based on the predicted current, selecting the voltage vector with the minimum cost function, and applying the switching state corresponding to the voltage vector with the minimum cost function to the inverter. The present invention can effectively reduce the nonlinear effects of the inverter in a permanent magnet synchronous motor drive system, achieves excellent compensation effects, reduces current harmonics and steady-state errors, and improves the tracking accuracy of the current loop.

Description

Technical Field

[0001] The present invention relates to the technical field of permanent magnet synchronous motor control, and in particular to a finite control set predictive current control method and a control device for a permanent magnet synchronous motor. Background Art

[0002] The performance of the current control loop, an inner loop, plays a crucial role in the control of a permanent magnet synchronous motor (PMSM), as it directly affects the motor's torque and speed. However, inverter nonlinearity is unavoidable in PMSM drive systems. This increases the total harmonic distortion (THD) of the PMSM current, leading to torque ripple and speed ripple. This increases parasitic iron and copper losses, motor temperature, and reduces the PMSM's tracking accuracy and service life, making high-performance current control difficult.

[0003] Currently, research on inverter nonlinearity compensation for permanent magnet synchronous motors using finite control set predictive current control often employs simple harmonic compensation methods without considering the inverter nonlinearity and overall motor modeling. Alternatively, these methods focus solely on dead-zone effects, ignoring the impact of power device voltage drops. Consequently, existing compensation techniques have limited effectiveness. Summary of the Invention

[0004] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art and provide a permanent magnet synchronous motor finite control set predictive current control method and control device, which can effectively reduce the nonlinear influence of the inverter of the permanent magnet synchronous motor drive system, have good compensation effect, can reduce current harmonics and steady-state errors, and improve the tracking accuracy of the current loop.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for predictive current control of a permanent magnet synchronous motor using a finite control set comprises the following steps:

[0007] Step S1, establishing a mathematical model of a permanent magnet synchronous motor taking into account the nonlinear effect of the inverter;

[0008] Step S2, correcting the voltage vector output by the inverter according to the current polarity of the permanent magnet synchronous motor and the switching state of the inverter;

[0009] Step S3, using the modified voltage vector to estimate and predict the current of the permanent magnet synchronous motor at a future moment;

[0010] Step S4 : calculating a predefined cost function according to the predicted current, selecting a voltage vector with the minimum cost function, and applying the switching state corresponding to the voltage vector with the minimum cost function to the inverter.

[0011] As a preferred embodiment, in step S1, the factors causing the nonlinear effect on the inverter include the inverter's dead time, device delay time, and voltage drop of the power device tube.

[0012] As a preferred embodiment, in step S1, the input of the mathematical model of the permanent magnet synchronous motor is the stator resistance, inductance, electric angular velocity, d-axis voltage, q-axis voltage, permanent magnet flux linkage, d-axis voltage change value caused by inverter nonlinearity, and q-axis voltage change value caused by inverter nonlinearity of the permanent magnet synchronous motor; the output of the mathematical model of the permanent magnet synchronous motor is the d-axis current and q-axis current of the permanent magnet synchronous motor.

[0013] As a preferred embodiment, in step S2, the voltage vector output by the inverter is corrected based on the pulse equivalence principle.

[0014] As a preferred embodiment, in step S3, the current of the permanent magnet synchronous motor at a future moment is predicted based on a single-step prediction method.

[0015] As a preferred embodiment, in step S3, the current of the permanent magnet synchronous motor at a future moment is predicted based on a multi-step prediction method.

[0016] Based on the same inventive concept, the present invention also provides a permanent magnet synchronous motor finite control set predictive current control device, which is characterized by including:

[0017] Model building unit: used to establish a mathematical model of the permanent magnet synchronous motor taking into account the nonlinear effects of the inverter;

[0018] Voltage vector correction unit: used to correct the voltage vector output by the inverter according to the current polarity of the permanent magnet synchronous motor and the switching state of the inverter;

[0019] Current prediction unit: used to estimate and predict the current of the permanent magnet synchronous motor at a future moment using a modified voltage vector;

[0020] Execution unit: used to calculate a predefined cost function based on the predicted current, select the voltage vector with the minimum cost function, and apply the switching state corresponding to the voltage vector with the minimum cost function to the inverter.

[0021] As a preferred embodiment, the permanent magnet synchronous motor is a three-phase permanent magnet synchronous motor.

[0022] Based on the same inventive concept, the present invention also provides a storage medium, which is characterized in that the storage medium stores a program file for implementing the permanent magnet synchronous motor finite control set predictive current control method.

[0023] Based on the same inventive concept, the present invention also provides a processor, which is characterized in that the processor is used to run a program, wherein the program executes the permanent magnet synchronous motor finite control set predictive current control method when running.

[0024] Compared to existing technologies, the present invention proposes a finite control set predictive current control method and device for a permanent magnet synchronous motor (PMSM) based on inverter nonlinearity compensation. This method considers the impact of the drive system's inverter nonlinearity when establishing a PMSM predictive current model. The error voltage caused by the inverter nonlinearity is then used to correct the voltage vector. This corrected voltage vector is used to predict future currents and optimize the switching state applied to the inverter. Consequently, the present invention effectively mitigates the nonlinear effects of the PMSM inverter drive system, achieving effective compensation, reducing current harmonics and steady-state errors, and improving the tracking accuracy of the current loop. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 Schematic diagram of the inverter and permanent magnet synchronous motor system structure.

[0026] Figure 2 for Figure 1 Schematic diagram of the inverter dead time effect.

[0027] Figure 3 This is a structural block diagram of the finite control set predictive current control device for a permanent magnet synchronous motor according to the present invention.

[0028] Figure 4 This is a flowchart of the current control process of the permanent magnet synchronous motor with a finite control set prediction method according to the present invention.

[0029] Figure 5 It is a schematic diagram of the operation of finite control set predictive current control under different conditions.

[0030] Figure 6 This is a comparison chart of the three-phase current response results under 1 N·m load conditions when the motor speed is 40 r / min.

[0031] Figure 7 This is a comparison chart of the three-phase current response results under the load condition of 2N·m when the motor speed is 40r / min.

[0032] Figure 8 This is a comparison chart of the three-phase current response results under the load condition of 3N·m when the motor speed is 40r / min.

[0033] Figure 9 It is the applied voltage vector sequence of the two methods in the same scenario under the load condition of 2 N·m when the motor speed is 40 r / min. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work should fall within the scope of protection of the present invention.

[0035] A first aspect of an embodiment of the present invention provides a method for predictive current control of a magnetic synchronous motor using a finite control set, comprising the following steps:

[0036] Step S1, establishing a mathematical model of a permanent magnet synchronous motor taking into account the nonlinear effect of the inverter.

[0037] The dead time of the inverter, the device delay time and the voltage drop of the power device tube are the main factors causing the nonlinearity of the inverter. In the traditional finite control set predictive current control, the prediction model used does not include these factors, resulting in current harmonics. Therefore, the method proposed in the present invention establishes a permanent magnet synchronous motor model that takes into account the influence of inverter nonlinearity, and uses this model as a prediction model to weaken the current harmonic phenomenon. Therefore, in the step S1, the factors that cause the nonlinear influence of the inverter include the dead time of the inverter, the device delay time and the voltage drop of the power device tube. Usually, the dead time set for the permanent magnet synchronous motor motor control is much longer than the device turn-on delay and turn-off delay time. Therefore, in order to simplify the analysis, the device turn-on delay and turn-off delay time are ignored. Figure 1 The schematic diagram of the inverter and permanent magnet synchronous motor system structure is shown, including two insulated gate bipolar transistors (IGBTs) and two anti-parallel freewheeling diodes. For the pulse width modulation (PWM) voltage source inverter, the upper and lower bridge arms provide complementary PWM signals to achieve voltage output. However, in order to prevent the upper and lower bridge arms in the same phase from being turned on at the same time and causing a short circuit, a dead time is usually inserted at the rising edge of the drive signal. The dead time effect diagram is shown in the figure below. Figure 2 shown.

[0038] In step S1, the inputs of the permanent magnet synchronous motor mathematical model are the stator resistance, inductance, electric angular velocity, d-axis voltage, q-axis voltage, permanent magnet flux linkage, d-axis voltage change value caused by inverter nonlinearity, and q-axis voltage change value caused by inverter nonlinearity of the permanent magnet synchronous motor; the outputs of the permanent magnet synchronous motor mathematical model are the d-axis current and q-axis current of the permanent magnet synchronous motor.

[0039] Figure 1 The schematic diagram of the inverter and permanent magnet synchronous motor system is given indc Indicates DC bus voltage; U ce Indicates the IGBT conduction voltage drop; U f Represents the voltage drop of the freewheeling diode; R s 、L s and E s They represent the stator resistance, inductance and back electromotive force of the permanent magnet synchronous motor respectively; S a 、S b and S c Represent the switching states of the three-phase bridge arms a, b, and c respectively. These three switching states can generate eight basic voltage vectors u j ,j=0,1,…,7;i a Indicates the A-phase current. Figure 2 The ideal and actual a-phase upper and lower bridge arm drive signals and a-phase voltage are shown, where T s is the current loop control period; t d is the dead time; U AN Indicates the voltage between phase a and reference ground N.

[0040] according to Figure 2 , the nonlinearity of the inverter directly affects the voltage value and action time between phase a and reference ground N, and further affects the change of dq axis voltage. Therefore, the mathematical model of the permanent magnet synchronous motor considering the nonlinearity of the inverter can be expressed as:

[0041]

[0042] Where i d and i q Represents dq axis current, u d and u q Represent the dq axis voltage, ω e represents the electrical angular velocity, ψ m represents the permanent magnet flux, Δu d and Δu q They represent the changes of d and q axis voltages caused by the nonlinearity of the inverter, which will be given in step S2.

[0043] Step S2: correcting the voltage vector output by the inverter according to the current polarity of the permanent magnet synchronous motor and the switching state of the inverter.

[0044] from Figure 2 It can be seen that the ideal voltage between phase a and reference ground N in the kth control cycle can be expressed as:

[0045] U AN (k) = S a (k)U dc (2)

[0046] Where U AN(k) and S a (k) represents the voltage between phase a and the reference ground N and the switching state of the phase a bridge arm in the kth control cycle respectively.

[0047] For continuous control set predictive current control, the average voltage error per cycle can be easily calculated because the switching frequency of SVPWM is fixed. However, for finite control set predictive current control, the switching frequency is not fixed, making it impossible to calculate and compensate for the average voltage error. Therefore, the pulse equivalence principle is used to calculate the error.

[0048] Define ΔU AN (k)=U AN (k)U′ AN (k) represents the voltage error between phase a and reference ground N caused by the nonlinearity of the inverter; U′ AN (k) represents the actual voltage considering the nonlinearity of the inverter.

[0049] When the switching state of the phase a bridge arm changes from 0 to 1, according to the pulse equivalence principle, the voltage error can be calculated as:

[0050]

[0051] Similarly, the voltage errors in other cases can also be calculated based on the pulse equivalence principle. The voltage errors under different current polarities and switch state transition conditions are given in Table 1.

[0052] Table 1 Voltage error under different current polarity and switch state transition conditions

[0053]

[0054] The eight cases in Table 1 can be expressed as follows:

[0055]

[0056] In formula (4), sgn(·) represents the sign function.

[0057] At the same time, the potential of point N' in the permanent magnet synchronous motor with three-phase winding Y-connection satisfies:

[0058] U N′N =(U AN +U BN +U CN ) / 3 (5)

[0059] Therefore, the inverter output phase voltage error caused by nonlinearity can be expressed as follows:

[0060]

[0061] Where ΔUAN′ , ΔU BN′ , ΔU CN′ The phase voltage errors of phases a, b, and c are shown respectively; ΔU BN and ΔU BN They represent the voltage errors from phases b and c to the reference ground N, respectively, and can be obtained through the same analysis.

[0062] Furthermore, the error voltage Δu on the dq axis caused by the inverter nonlinearity is d and Δu q It can be obtained by transforming the phase error voltage Clark and Park and can be expressed as:

[0063]

[0064] Therefore, the dq voltage error caused by the nonlinearity of the inverter can be derived according to the current polarity of the permanent magnet synchronous motor and the switching state of the inverter, and compensated by predictive control in step S3.

[0065] Step S3: Use the corrected voltage vector to estimate and predict the current of the permanent magnet synchronous motor at a future moment.

[0066] In step S3, according to actual needs, the current of the permanent magnet synchronous motor at a future moment can be predicted based on a single-step or multi-step prediction method.

[0067] Performing first-order forward Euler discretization on Equation (3), the predicted current expression of the motor is as follows:

[0068]

[0069] Where i d (k), i q (k) represent the dq axis currents obtained by measurement; i d (k+1)| j ,i q (k+1)| j Respectively represent the dq axis current predictions of the eight voltage vectors; [u d (k)Δu d (k)]| j and[u q (k)-Δu q (k)]| j They represent the dq axis voltages corresponding to the eight corrected inverter voltage vectors, Δu d (k) and Δu q (k) can be obtained by equations (4) and (7).

[0070] Compared with the traditional finite control set predictive current controller, the dq-axis voltage used here is the dq-axis voltage corresponding to the corrected voltage vector, which includes the prediction of the error voltage caused by the nonlinearity of the inverter. Therefore, a more accurate current prediction value will be obtained. Figure 5 A schematic diagram of the operation of the traditional finite control set predictive current control and the method proposed in the present invention is given, which can further illustrate the principle of the corrected voltage vector proposed in the present invention.

[0071] Usually, to compensate for the one-step delay in the actual system, a two-step prediction method is adopted, and the predicted current expression is rewritten as follows:

[0072]

[0073] Where i d (k+1) and i q (k+1) represents the dq axis predicted current of the (k+1)th sampling period respectively; i d (k+1)| j ,i q (k+1)| j They represent the dq axis predicted current of the (k+2)th sampling period respectively; [u d (k)-Δu d (k)] and |u q (k)-Δu q (k)] represent the dq axis voltages corresponding to the voltage vector after correction in the kth sampling period; [u d (k+1)-Δu d (k+1)]| j and[u q (k+1)Δu q (k+1)]| i They respectively represent the dq axis voltages corresponding to the corrected voltage vector in the (k+1)th sampling period.

[0074] Step S4 : calculating a predefined cost function according to the predicted current, selecting a voltage vector with the minimum cost function, and applying the switching state corresponding to the voltage vector with the minimum cost function to the inverter.

[0075] The predefined cost function is expressed as follows:

[0076]

[0077] Where Cf(j) represents the cost function; and Respectively represent the dq axis reference current; u opt Represents the optimal voltage vector.

[0078] A second aspect of the present invention further provides a finite control set predictive current control device for a permanent magnet synchronous motor, comprising:

[0079] Model building unit: used to establish a mathematical model of the permanent magnet synchronous motor taking into account the nonlinear effects of the inverter;

[0080] Voltage vector correction unit: used to correct the voltage vector output by the inverter according to the current polarity of the permanent magnet synchronous motor and the switching state of the inverter;

[0081] Current prediction unit: used to estimate and predict the current of the permanent magnet synchronous motor at a future moment using a modified voltage vector;

[0082] Execution unit: used to calculate a predefined cost function based on the predicted current, select the voltage vector with the minimum cost function, and apply the switching state corresponding to the voltage vector with the minimum cost function to the inverter.

[0083] The permanent magnet synchronous motor is preferably a three-phase permanent magnet synchronous motor.

[0084] Figure 3 This is a structural block diagram of the permanent magnet synchronous motor finite control set predictive current control device based on inverter nonlinear compensation of the present invention.

[0085] Figure 3 The system consists of a permanent magnet synchronous motor, a three-phase inverter, an encoder / position sensor, a speed loop / PI controller, a predictive current controller / current loop, and a coordinate transformation module (Park transformation and Clark transformation). The speed loop uses a PI controller to calculate the q-axis current set value based on the measured speed and the expected speed, and the d-axis current set value is set to 0. The current loop uses the finite control set predictive current controller based on inverter nonlinear compensation of the present invention to determine the optimal voltage vector and the three-phase inverter switching state based on the dq-axis current set values and the corrected voltage vector. The three-phase inverter switching state directly determines the on / off state of the inverter power devices, ultimately driving the permanent magnet synchronous motor to operate.

[0086] Figure 4 This is a flowchart of the current control process of the permanent magnet synchronous motor based on the finite control set prediction of the inverter nonlinear compensation according to the present invention.

[0087] The current loop controller first updates the new current measurement value and calculates the current-time corrected voltage vector based on the current and the switch states at the current and previous moments. It also predicts the current at the next moment. It then calculates a new corrected voltage vector based on the current at the next moment and the switch states at the current and next moments. It then uses this new corrected voltage vector and the next-moment current prediction to predict the current at time (k+2). Finally, it determines the switching state acting on the inverter using a predefined cost function.

[0088] Figure 5 It is a schematic diagram of the operation of finite control set predictive current control under different conditions.

[0089] The operation of the finite control set predictive current controller is given for different cases, where i q_0 (k), i q_1 (k), ..., i q_7 (k) represents the predicted q-axis current value of the applied 0th, 1st, ..., 7th voltage vectors respectively; i q (k) represents the q-axis current value after applying the optimal voltage vector. It can be seen that due to the nonlinearity of the inverter, there is a deviation between the q-axis current predicted based on the basic voltage vector and the q-axis current value actually obtained by applying the basic voltage vector. This will result in the selected "optimal" voltage vector being likely suboptimal, rather than optimal, which increases current tracking error and current harmonics. However, when a modified voltage vector is applied that accounts for inverter nonlinearity, the predicted current remains consistent with the current obtained by the actual applied voltage vector, ensuring the selection of the optimal voltage vector.

[0090] A third aspect of the present invention further provides a storage medium storing a program file for implementing the permanent magnet synchronous motor finite control set predictive current control method.

[0091] A fourth aspect of the present invention further provides a processor, which is used to run a program, wherein the program executes the permanent magnet synchronous motor finite control set predictive current control method when running.

[0092] To verify the effect of the present invention, the harmonic suppression capability of the finite control set predictive current control based on inverter nonlinear compensation was evaluated under the operating conditions of a permanent magnet synchronous motor at low speed (40r / min) and different applied loads.

[0093] To evaluate the harmonic suppression capability of the control method of this embodiment, the experimental results of the finite control set predictive current control without inverter nonlinear compensation and based on inverter nonlinear compensation are compared. For the sake of comparison, the speed loop of the above two methods uses a PI controller with the same parameters. dc The IGBT conduction voltage drop of the inverter is 48V. ce Set to 1.9V and the freewheeling diode voltage drop U f Set to 2.5V, dead time t d Set to 5μs, the current control period T s is 100ms.

[0094] Figure 6 、 Figure 7 、 Figure 8The three-phase current response under 1N·m, 2N·m and 3N·m load conditions when the motor speed is 40r / min, the Fourier analysis of the three-phase current and the total harmonic distortion (THD) of the three-phase current are given respectively. Figures 6-8 It can be clearly seen that the finite control set predictive current control method based on inverter nonlinear compensation (FCS-PCC+MVV) has a smaller three-phase current total harmonic distortion rate, and the harmonic amplitude caused by inverter nonlinearity is attenuated.

[0095] Figure 9 The applied voltage vector sequences of the two methods in the same scenario under the load condition of 2N·m and the motor speed is 40r / min are given. Figure 9 As can be seen in the figure, after compensating for inverter nonlinearity, the optimal voltage vector at the same time has changed. Furthermore, the FCS-PCC method does not use voltage vector u7(u0), while the FCS-PCC+MVV method does. This is because when inverter nonlinearity is not considered, voltage vectors u7 and u0 have the same effect. However, after accounting for inverter nonlinearity and correcting the voltage vector, u7 is no longer equivalent to u0.

[0096] The above results show that the finite control set predictive current control method based on inverter nonlinear compensation of the present invention can effectively reduce the influence of inverter nonlinearity of the permanent magnet synchronous motor drive system in the control, reduce current harmonics and steady-state errors, and improve the tracking accuracy of the current loop.

[0097] The above-mentioned model construction unit, voltage vector correction unit, current prediction unit, and execution unit are used to implement the above-mentioned permanent magnet synchronous motor finite control set predictive current control method.

[0098] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0099] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0100] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0101] In the embodiments provided herein, it should be understood that the disclosed methods and apparatuses may be implemented in other ways. For example, the above-described method and apparatus embodiments are merely illustrative. For example, the division of modules or units is merely a logical functional division. In actual implementation, other divisions may be used, such as combining or integrating multiple units or components into another device, or omitting or not implementing certain features.

[0102] The units described as separate components may or may not be physically separate, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0103] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0104] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0105] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for predictive current control of a permanent magnet synchronous motor with a finite control set, characterized in that: The following steps are involved: Step S1, establishing a mathematical model of a permanent magnet synchronous motor taking into account the nonlinear effect of the inverter; Step S2, correcting the voltage vector output by the inverter according to the current polarity of the permanent magnet synchronous motor and the switching state of the inverter; Step S3, using the modified voltage vector to estimate and predict the current of the permanent magnet synchronous motor at a future moment; Step S4, calculating a predefined cost function based on the predicted current, selecting a voltage vector with the minimum cost function, and applying the switching state corresponding to the voltage vector with the minimum cost function to the inverter; In the step S2, the voltage vector output by the inverter is corrected based on the pulse equivalence principle; Among them, when the switching state of the phase a bridge arm changes from 0 to 1, according to the pulse equivalence principle, the voltage error can be calculated as: Where U dc Indicates DC bus voltage; U ce Indicates the IGBT conduction voltage drop; U f Represents the voltage drop of the freewheeling diode; i a Represents the A phase current; where T s is the current loop control period; t d is the dead time; U AN Represents the voltage between phase a and reference ground N; k represents the sequence number of the control cycle, i.e. the kth control cycle; In step S3, the current of the permanent magnet synchronous motor at a future moment is predicted based on a single-step prediction method; Among them, the predicted current expression of the motor is as follows: Where R s Indicates the stator resistance of the permanent magnet synchronous motor, L s represents the stator inductance of the permanent magnet synchronous motor; i d represents the d-axis current, i q represents the q-axis current, u d represents the d-axis voltage, u q represents the q-axis voltage; ω e represents the electrical angular velocity, ψ m represents the permanent magnet flux, Δu d Indicates the change in d-axis voltage caused by the nonlinearity of the inverter, Δu q represents the change of q-axis voltage caused by the nonlinearity of the inverter; i d (k) represents the d-axis current obtained by measurement, i q (k) represents the q-axis current obtained by measurement; i d (k+1)| j represents the d-axis current prediction with eight applied voltage vectors, i q (k1)| j represents the q-axis current prediction with eight applied voltage vectors; [u d (k)-Δu d (k)]| j represents the d-axis voltage corresponding to the eight corrected inverter voltage vectors, [u q (k)-Δu q (k)]| j represents the q-axis voltage corresponding to the eight corrected inverter voltage vectors; Alternatively, the current of the permanent magnet synchronous motor at a future moment is predicted based on a multi-step prediction method; Among them, the predicted current expression is rewritten as follows: Where i d (k1) represents the d-axis predicted current of the (k+1)th sampling period, i q (k1) represents the q-axis predicted current of the (k+1)th sampling period; i d (k+2)| j represents the d-axis predicted current of the (k+2)th sampling period, i q (k2)| j represents the q-axis predicted current of the (k+2)th sampling period; [u d (k)-Δu d (k)] represents the d-axis voltage corresponding to the voltage vector after correction in the k-th sampling period, [u q (k)-Δu q (k)] represents the q-axis voltage corresponding to the voltage vector after correction in the k-th sampling period; [u d (k+1)-Δu d (k+1)]| j represents the d-axis voltage corresponding to the voltage vector after correction in the (k+1)th sampling period, [u q (k+1)-Δu q (k+1)]| j It represents the q-axis voltage corresponding to the corrected voltage vector in the (k+1)th sampling period.

2. The method for predictive current control of a permanent magnet synchronous motor using a finite control set according to claim 1, wherein: In step S1, factors causing nonlinear effects on the inverter include the inverter's dead time, device delay time, and voltage drop of power device tubes.

3. The method for predictive current control of a permanent magnet synchronous motor with a finite control set according to claim 1, wherein: In step S1, the inputs of the permanent magnet synchronous motor mathematical model are the stator resistance, inductance, electric angular velocity, d-axis voltage, q-axis voltage, permanent magnet flux linkage, d-axis voltage change value caused by inverter nonlinearity, and q-axis voltage change value caused by inverter nonlinearity of the permanent magnet synchronous motor; the outputs of the permanent magnet synchronous motor mathematical model are the d-axis current and q-axis current of the permanent magnet synchronous motor.

4. A permanent magnet synchronous motor finite control set predictive current control device, characterized in that: Executing the method for predictive current control of a permanent magnet synchronous motor with a finite control set according to any one of claims 1 to 3; the control device comprises: Model building unit: used to establish a mathematical model of the permanent magnet synchronous motor taking into account the nonlinear effects of the inverter; Voltage vector correction unit: used to correct the voltage vector output by the inverter according to the current polarity of the permanent magnet synchronous motor and the switching state of the inverter; Current prediction unit: used to estimate and predict the current of the permanent magnet synchronous motor at a future moment using a modified voltage vector; Execution unit: used to calculate a predefined cost function based on the predicted current, select the voltage vector with the minimum cost function, and apply the switching state corresponding to the voltage vector with the minimum cost function to the inverter.

5. The permanent magnet synchronous motor finite control set predictive current control device according to claim 4, characterized in that: The permanent magnet synchronous motor is a three-phase permanent magnet synchronous motor.

6. A storage medium, characterized in that The storage medium stores a program file for implementing the permanent magnet synchronous motor finite control set predictive current control method according to any one of claims 1 to 3.

7. A processor, characterized in that: The processor is used to run a program, wherein the program executes the permanent magnet synchronous motor finite control set predictive current control method according to any one of claims 1 to 3 when running.

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