Permanent magnet synchronous motor predictive current control method, device, equipment and storage medium

Abstract

The present invention discloses a method, device, equipment and storage medium for predictive current control of a permanent magnet synchronous motor, which constructs a time domain difference equation of current harmonics by performing sliding Fourier transform analysis on the sampled current value in a two-phase stationary coordinate system; then, based on the permanent magnet synchronous motor model, the current prediction value corresponding to each voltage vector is calculated according to the sampled current value and eight voltage vectors of the inverter; then, the pre-acquired current reference value is input into the time domain difference equation to calculate the current harmonic reference value, and each current prediction value is respectively input into the time domain difference equation to calculate the current harmonic prediction value corresponding to the current prediction value; the current harmonic reference value and each current harmonic prediction value are respectively used as a set of input data, and are input into a pre-constructed cost function for calculation, and then the optimal voltage vector with the smallest cost function is selected. The present invention minimizes the current harmonic amplitude, thereby selecting the optimal voltage vector of the system, and has better robustness.

Description

Technical Field

[0001] The present application relates to the technical field of servo motors, and in particular to a method, device, equipment and storage medium for predictive current control of a permanent magnet synchronous motor. Background Art

[0002] In the traditional finite set model predictive control, the selection of the optimal voltage vector is achieved by minimizing the cost function. In order to reduce the current tracking error, the cost function is usually designed as the error between the reference current and the predicted current. By traversing all the error results, the voltage vector corresponding to the smallest error is selected as the optimal voltage vector. In practical applications, although this method can appropriately and quickly select the optimal voltage vector, since the cost function is designed based on the minimization of the current tracking error in the time domain state, the harmonic components of the output current are not taken into account, so it is impossible to suppress the harmonic current of a specific order in the direct frequency domain state. At the same time, in the current harmonic analysis method, the traditional discrete Fourier transform can calculate the spectrum at a certain moment, but to calculate the spectrum at the next moment, another calculation is required. These two calculations are independent of each other and the amount of calculation is large. Summary of the invention

[0003] In view of this, the present application provides a permanent magnet synchronous motor predictive current control method, device, equipment and storage medium to solve the problem that the existing finite set model predictive control strategy cannot suppress current harmonics of specific orders in the direct frequency domain state.

[0004] In order to solve the above technical problems, a technical solution adopted by the present application is to provide a permanent magnet synchronous motor predictive current control method, which includes:

[0005] In the two-phase stationary coordinate system, the sampled current values ​​of the α and β axes are obtained, and the sampled current values ​​are subjected to sliding Fourier transform analysis to construct the time domain difference equation of the current harmonics;

[0006] Based on the pre-built permanent magnet synchronous motor model, the current prediction value corresponding to each voltage vector is calculated according to the sampled current value and the eight voltage vectors of the inverter obtained in advance;

[0007] Input the pre-acquired current reference value into the time domain difference equation to calculate the current harmonic reference value of the α and β axes, and input each current prediction value into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes;

[0008] The current harmonic reference value and each current harmonic prediction value are respectively used as a set of input data and input into a pre-constructed cost function for calculation, and then the voltage vector corresponding to the current harmonic prediction value when the cost function is minimized is selected as the optimal voltage vector.

[0009] As a further improvement of the present application, based on the pre-built permanent magnet synchronous motor model, the current prediction value corresponding to each voltage vector is calculated according to the sampled current value and the eight voltage vectors of the inverter obtained in advance, including:

[0010] Based on the pre-built permanent magnet synchronous motor model, the estimated sampling current values ​​of the α and β axes at the k+1 time are calculated by combining the input voltage values ​​and sampling current values ​​of the α and β axes in the kth control cycle;

[0011] Based on the pre-built permanent magnet synchronous motor model, the current prediction values ​​at the eight k+2 moments corresponding to the eight voltage vectors of the α and β axes are calculated according to the components of the eight voltage vectors of the inverter at the k+1 moment and the estimated value of the sampled current.

[0012] As a further improvement of the present application, the permanent magnet synchronous motor model is expressed as:

[0013]

[0014] λ α =λ β =1 / L s ;

[0015]

[0016]

[0017]

[0018] Among them, i α and i β are the stator currents of the α and β axes, λ α and λ β are the input coefficients of the α and β axes, u α and u β are the stator voltages of the α and β axes, respectively, and F α and F β is the lumped disturbance observed by the preset design observer, e α and e β are the back electromotive force of α and β axes, L s and R s are the nominal inductance and nominal resistance of the permanent magnet synchronous motor, ψ f is the flux linkage of the permanent magnet synchronous motor, θ e is the electrical angle of the permanent magnet synchronous motor, ω e is the electrical angular velocity of the permanent magnet synchronous motor;

[0019] The calculation formula of the estimated value of the sampling current is expressed as:

[0020]

[0021] Among them, i α (k+1) and i β (k+1) are the estimated current values ​​sampled by the α and β axes at time k+1, u α (k) and u β (k) are the input voltage values ​​of the α and β axes in the kth control cycle, respectively. α (k) and F β (k) are the observed values ​​of the lumped disturbance of the α and β axes at the kth moment, T s is the sampling period;

[0022] The calculation formula of the current prediction value is expressed as:

[0023]

[0024] Where j = 0, ..., 7, u j Represents the eight voltage vectors of the inverter, and They are the current prediction values ​​at eight k+2 moments corresponding to the eight voltage vectors of the α and β axes, and are the components of the eight voltage vectors of the inverter at time k+1 on the α and β axes, F α (k+1) and F β (k+1) are the observed values ​​of the lumped disturbances of the α and β axes at time k+1.

[0025] As a further improvement of the present application, the pre-acquired current reference value is input into the time domain difference equation to calculate the current harmonic reference value of the α and β axes, and each current prediction value is respectively input into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes, including:

[0026] Input the current reference value into the time domain difference equation to calculate the 1st current harmonic reference value and the mth current harmonic reference value of the α and β axes;

[0027] The current prediction values ​​at eight k+2 moments are respectively input into the time domain difference equation, and the 1st current harmonic prediction value and the mth current harmonic prediction value corresponding to each current prediction value of the α and β axes are calculated.

[0028] As a further improvement of the present application, the time domain difference equation of the current harmonics is expressed as:

[0029] X m (n) = e j2πm / N [X m(n-1)+x(n)-x(nN)];

[0030] Among them, X m (n) is the current harmonic amplitude at time n, X m (n-1) is the current harmonic amplitude at time n-1, x(n) is the sampled current value at time n, x(nN) is the sampled current value at time nN, j represents the imaginary unit, m represents the mth current harmonic, and N represents the number of samples.

[0031] As a further improvement of the present application, the calculation process of the current harmonic reference value is expressed as:

[0032]

[0033] in, and They are the mth harmonic reference values ​​of the α and β axes respectively. When m=1, it is the 1st harmonic reference value of the α and β axes. and are the current harmonic reference values ​​of the α and β axes at time k-1, and are the current reference values ​​of the α and β axes respectively, i α (kN) and i β (kN) are the sampling current values ​​of α and β axes at the time kN;

[0034] The calculation process of the current harmonic prediction value is expressed as:

[0035]

[0036] Where j = 0, ..., 7, u j are the eight voltage vectors of the inverter, and are the predicted values ​​of the mth order current harmonics of the α and β axes at time k+2, and when m=1, they are the predicted values ​​of the 1st order current harmonics of the α and β axes. and are the predicted current harmonic values ​​of the α and β axes at time k-1, and are the current prediction values ​​of the α and β axes at time k+2, corresponding to the eight voltage vectors of the inverter, i α (kN) and i β (kN) are the sampling current values ​​of α and β axes at the time kN respectively.

[0037] As a further improvement of this application, the cost function is expressed as:

[0038]

[0039] Among them, Cf j is the value of the cost function, ξ is the preset parameter, i s =[i α i β ] T , j = 0, ..., 7, u j are the eight voltage vectors of the inverter, m represents the mth current harmonic, M represents the total number of current harmonics, is the reference value of the 1st current harmonic, is the predicted value of the 1st current harmonic, is the mth current harmonic reference value, is the predicted value of the mth current harmonic.

[0040] In order to solve the above technical problems, another technical solution adopted by the present application is: to provide a permanent magnet synchronous motor predictive current control device, which includes:

[0041] A construction module is used to obtain the sampled current values ​​of the α and β axes in a two-phase stationary coordinate system, perform sliding Fourier transform analysis on the sampled current values, and construct a time domain difference equation of the current harmonics;

[0042] A first calculation module is used to calculate a current prediction value corresponding to each voltage vector based on a pre-built permanent magnet synchronous motor model and eight pre-acquired voltage vectors of the inverter according to the sampled current value;

[0043] The second calculation module is used to input the pre-acquired current reference value into the time domain difference equation to calculate the current harmonic reference value of the α and β axes, and input each current prediction value into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes;

[0044] The minimization module is used to take the current harmonic reference value and each current harmonic prediction value as a set of input data, and input them into a pre-built cost function for calculation, and then select the voltage vector corresponding to the current harmonic prediction value when the cost function is minimized as the optimal voltage vector.

[0045] To solve the above technical problems, another technical solution adopted in the present application is: to provide a computer device, which includes a processor and a memory coupled to the processor, wherein program instructions are stored in the memory, and when the program instructions are executed by the processor, the processor executes the steps of the permanent magnet synchronous motor predictive current control method as described in any one of the above items.

[0046] In order to solve the above technical problems, another technical solution adopted by the present application is: providing a storage medium storing program instructions capable of implementing any of the above permanent magnet synchronous motor predictive current control methods.

[0047] The beneficial effects of the present application are as follows: the permanent magnet synchronous motor predictive current control method of the present application introduces current harmonics in the frequency domain state into the cost function, designs a new cost function based on sliding discrete Fourier transform, and applies the new cost function to model-free predictive current control, thereby reducing the amplitude of specific order harmonics of the output current and the total harmonic distortion. By combining the new cost function based on harmonic amplitude with model-free predictive control, it is possible to not only suppress specific order harmonics and improve current tracking accuracy, but also get rid of the dependence on motor model parameters and improve the robustness of the parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 1 is a flow chart of a method for predictive current control of a permanent magnet synchronous motor according to an embodiment of the present invention;

[0049] Figure 2 is a schematic diagram of functional modules of a permanent magnet synchronous motor predictive current control device according to an embodiment of the present invention;

[0050] Figure 3 is a schematic diagram of the structure of a computer device according to an embodiment of the present invention;

[0051] Figure 4 It is a schematic diagram of the structure of the storage medium of an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0053] The terms "first", "second", "third" in this application are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined as "first", "second", "third" can expressly or implicitly include at least one of the features. In the description of this application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. In the embodiments of this application, all directional indications (such as up, down, left, right, front, back...) are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the steps or units listed, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices.

[0054] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0055] Figure 1 FIG. 1 is a flow chart of a method for predicting current control of a permanent magnet synchronous motor according to a first embodiment of the present invention. It should be noted that the method of the present invention is not limited to the method of FIG. 1 if substantially the same results are achieved. Figure 1 The process sequence shown is limited. Figure 1 As shown, the permanent magnet synchronous motor predictive current control method includes the steps of:

[0056] Step S101: in a two-phase stationary coordinate system, sampled current values ​​of the α and β axes are obtained, and sliding Fourier transform analysis is performed on the sampled current values ​​to construct a time domain difference equation of current harmonics.

[0057] In order to achieve the selection of the optimal voltage vector, this embodiment performs a sliding discrete Fourier analysis on the input current in a two-phase stationary coordinate system, and uses the analyzed high-order harmonic amplitude as a comparison object. By minimizing the high-order harmonic amplitude, the selection of the optimal voltage vector is achieved. In the traditional discrete Fourier transform, it is necessary to first collect the data in the sample and then perform spectrum analysis. Since each calculation is independent of each other, it is necessary to collect and analyze samples independently each time. Different from the traditional discrete Fourier transform, the sliding discrete Fourier transform uses the spectrum analysis results of the data sample at the previous moment based on the relationship between samples at different moments, and obtains the spectrum analysis at the next moment through corresponding recursive operations, avoiding performing a new discrete Fourier transform on the entire sample again, improving the calculation speed, and thus enabling online calculation.

[0058] Specifically, given a discrete-time signal x(n), assume that at time q, the number of samples selected by the sliding window is N. At this time, the sample sequence in the sliding window is: {x(q), x(q+1), …, x(q+N-1)}.

[0059] According to Fourier transform theory, at time q, based on the number of samples N in the sliding window, the spectrum value of the mth frequency unit is:

[0060]

[0061] Among them, X m (q) is the spectrum value of the mth frequency unit at time q, and j is an imaginary unit.

[0062] Similarly, at time q+1, in the N samples of the sliding window, the spectrum value of the mth frequency unit is:

[0063]

[0064] Among them, X m (q) is the spectrum value of the mth frequency unit at time q+1.

[0065] Let p = n + 1, formula (2) can be simplified to:

[0066]

[0067] Comparing formula (1) and formula (3), we can get the recursive expression of the sliding N-point discrete Fourier transform:

[0068] X m (q+1)=e j2πm / N [X m (q)+x(q+N)-x(q)] (4)

[0069] The generalization of formula (4) is the input sampling current value x(n) and the output current harmonic amplitude X m (q) Using the same time index n, the time domain difference equation of the current harmonics of the sliding discrete Fourier transform can be obtained:

[0070] X m (n) = e j2πm / N [X m (n-1)+x(n)-x(nN)] (5)

[0071] Among them, X m (n) is the current harmonic amplitude at time n, X m (n-1) is the current harmonic amplitude at time n-1, x(n) is the sampled current value at time n, x(nN) is the sampled current value at time nN, j represents the imaginary unit, m represents the mth current harmonic, and N represents the number of samples.

[0072] By z-transformation, formula (5) can be converted into a z-domain equation:

[0073] X m (z) = e j2πm / N [X m (z)z -1 +X(z)-X(z)z -N ] (6)

[0074] At this time, the z-domain transfer function for the mth frequency unit is:

[0075]

[0076] Step S102: Based on the pre-built permanent magnet synchronous motor model, a current prediction value corresponding to each voltage vector is calculated according to the sampled current value and eight pre-acquired voltage vectors of the inverter.

[0077] Specifically, it is necessary to first construct a permanent magnet synchronous motor model in a two-phase stationary coordinate system (α, β coordinate system). Usually, in the α, β coordinate system, the model of the permanent magnet synchronous motor is:

[0078]

[0079]

[0080] Among them, u α and u β are the stator voltages of the α and β axes of the permanent magnet synchronous motor, i α and i β are the stator currents of the α and β axes of the permanent magnet synchronous motor, e α and e βare the back electromotive force of the α and β axes of the permanent magnet synchronous motor, L s and R s are the nominal inductance and nominal resistance of the permanent magnet synchronous motor, ψ f is the flux linkage of the permanent magnet synchronous motor, θ e is the electrical angle of the permanent magnet synchronous motor, ω e is the electrical angular velocity of the permanent magnet synchronous motor. Based on formula (8) and formula (9), the permanent magnet synchronous motor model can be rewritten as:

[0081]

[0082] Among them, i α and i β are the stator currents of the α and β axes, λ α and λ β are the input coefficients of the α and β axes, u α and u β are the stator voltages of the α and β axes, respectively, and F α and F β is the lumped disturbance observed by the preset design observer, e α and e β are the back electromotive force of α and β axes, L s and R s are the nominal inductance and nominal resistance of the permanent magnet synchronous motor, ψ f is the flux linkage of the permanent magnet synchronous motor, θ e is the electrical angle of the permanent magnet synchronous motor, ω e is the electrical angular velocity of the permanent magnet synchronous motor. It should be noted that in formula (10), F α and F β It is defined as a lumped disturbance and can be observed by designing an observer, thus avoiding the direct calculation of the formula.

[0083] After the permanent magnet synchronous motor model is constructed, the current prediction value corresponding to each voltage vector is calculated based on the sampled current value and the eight voltage vectors of the inverter obtained in advance.

[0084] It should be noted that in the traditional finite set model predictive control, since the current prediction at the future moment is based on the model of the motor, it is impossible to get rid of the dependence on the motor parameters. When the parameters are mismatched, the accuracy of the current prediction at the future moment will be reduced, thereby affecting the selection of the optimal voltage vector. Therefore, in order to get rid of the dependence on the parameters, this embodiment predicts the current of the α and β axes based on the super local model. Among them, step S102 specifically includes:

[0085] 1. Based on the pre-built permanent magnet synchronous motor model, the estimated sampling current values ​​of the α and β axes at the k+1 time are calculated by combining the input voltage values ​​and sampling current values ​​of the α and β axes in the kth control cycle.

[0086] Specifically, the calculation formula of the sampling current estimation value is expressed as:

[0087]

[0088] Among them, i α (k+1) and i β (k+1) are the estimated current values ​​sampled by the α and β axes at time k+1, u α (k) and u β (k) are the input voltage values ​​of the α and β axes in the kth control cycle, respectively. α (k) and F β (k) are the observed values ​​of the lumped disturbance of the α and β axes at the kth moment, T s is the sampling period.

[0089] 2. Based on the pre-built permanent magnet synchronous motor model, according to the components of the eight voltage vectors of the inverter on the α and β axes at the k+1 moment, and the estimated value of the sampled current, the current prediction values ​​at the eight k+2 moments corresponding to the eight voltage vectors on the α and β axes are calculated.

[0090] It should be noted that due to the "one-step delay" in the hardware system, the optimal voltage vector calculated in the kth control cycle cannot be directly applied. Therefore, the "two-step prediction" is used to compensate for the "one-step delay" in the system, thereby improving the accuracy of current prediction.

[0091] Specifically, this embodiment needs to predict the current corresponding to each voltage vector at time k+2 based on the estimated value of the sampled current at time k+1. Based on formula (11), the calculation formula of the current prediction value is expressed as:

[0092]

[0093] Where j = 0, ..., 7, u j Represents the eight voltage vectors of the inverter, and They are the current prediction values ​​at eight k+2 moments corresponding to the eight voltage vectors of the α and β axes, and are the components of the eight voltage vectors of the inverter at time k+1 on the α and β axes, F α (k+1) and F β (k+1) are the observed values ​​of the lumped disturbances of the α and β axes at time k+1.

[0094] Step S103: Input the pre-acquired current reference value into the time domain difference equation to calculate α The current harmonic reference values ​​of the α and β axes are obtained, and each current prediction value is input into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes.

[0095] Wherein, step S103 specifically includes:

[0096] 1. Input the current reference value into the time domain difference equation to calculate the 1st current harmonic reference value and mth current harmonic reference value of the α and β axes.

[0097] 2. Input the current prediction values ​​at the eight k+2 moments into the time domain difference equation respectively, and calculate the 1st current harmonic prediction value and the mth current harmonic prediction value corresponding to each current prediction value of the α and β axes.

[0098] Specifically, based on formula (5), the calculation formula for the harmonic amplitude of the α-axis and β-axis currents can be derived as follows:

[0099]

[0100] Among them, i α (k) and i β (k) are the sampling current values ​​of α and β axes at time k, i α (kN) and i β (kN) are the sampling current values ​​of α and β axes at the time kN, and are the mth harmonic amplitudes of the current at time k on the α and β axes, and are the mth harmonic amplitudes of current on α and β axes at time k-1 respectively.

[0101] Based on formula (13), i α (k) and i β (k)Change to the current reference value of α and β axis and The mth harmonic reference value of the α and β axes can be derived as follows:

[0102]

[0103] in, and They are the mth harmonic reference values ​​of the α and β axes respectively. When m=1, it is the 1st harmonic reference value of the α and β axes. and are the current harmonic reference values ​​of the α and β axes at time k-1, and are the current reference values ​​of the α and β axes respectively, iα (kN) and i β (kN) are the sampling current values ​​of α and β axes at the time kN respectively.

[0104] In order to compensate for the one-step delay in the hardware system, this embodiment also needs to use "two-step prediction" to compensate for the "one-step delay" in the system, thereby improving the accuracy of current prediction. Specifically, the calculation process of the current harmonic prediction value is expressed as:

[0105]

[0106] Where j = 0, ..., 7, u j are the eight voltage vectors of the inverter, and are the predicted values ​​of the mth order current harmonics of the α and β axes at time k+2, and when m=1, they are the predicted values ​​of the 1st order current harmonics of the α and β axes. and are the predicted current harmonic values ​​of the α and β axes at time k-1, and are the current prediction values ​​of the α and β axes at time k+2, corresponding to the eight voltage vectors of the inverter, i α (kN) and i β (kN) are the sampling current values ​​of α and β axes at the time kN respectively.

[0107] Step S104: taking the current harmonic reference value and each current harmonic prediction value as a set of input data and inputting them into a pre-built cost function for calculation, and then selecting the voltage vector corresponding to the current harmonic prediction value when the cost function is minimized as the optimal voltage vector.

[0108] It should be noted that the cost function of this embodiment is based on a sliding Fourier transform, which is designed as follows:

[0109]

[0110] Among them, Cf j is the value of the cost function, ξ is the preset parameter, i s =[i α i β ] T , j = 0, ..., 7, u j are the eight voltage vectors of the inverter, m represents the mth current harmonic, M represents the total number of current harmonics, is the reference value of the 1st current harmonic, is the predicted value of the 1st current harmonic, is the mth current harmonic reference value, is the predicted value of the mth current harmonic.

[0111] Specifically, after obtaining the current harmonic reference value and eight current harmonic predicted values, the current harmonic reference value and each current harmonic predicted value are used as a set of input data to obtain eight sets of input data. Each set of input data is then input into formula (16) for calculation to obtain the cost function value corresponding to each set of input data. The current harmonic predicted value corresponding to the minimum cost function is selected, and then the voltage vector corresponding to the current harmonic predicted value is confirmed, and the voltage vector is used as the optimal voltage vector.

[0112] The permanent magnet synchronous motor predictive current control method of the embodiment of the present invention introduces current harmonics in the frequency domain state into the cost function, designs a new cost function based on sliding discrete Fourier transform, and applies the new cost function to model-free predictive current control, thereby reducing the amplitude of specific order harmonics and total harmonic distortion of the output current. By combining the new cost function based on harmonic amplitude with model-free predictive control, it is possible to not only suppress specific order harmonics and improve current tracking accuracy, but also get rid of dependence on motor model parameters and improve parameter robustness.

[0113] Figure 2 Schematic diagram of the functional modules of the permanent magnet synchronous motor predictive current control device according to an embodiment of the present invention. Figure 2 As shown, the permanent magnet synchronous motor predictive current control device 20 includes a construction module 21, a first calculation module 22, a second calculation module 23 and a minimization module 24.

[0114] A construction module 21 is used to obtain the sampled current values ​​of the α and β axes in a two-phase stationary coordinate system, and perform sliding Fourier transform analysis on the sampled current values ​​to construct a time domain difference equation of the current harmonics;

[0115] A first calculation module 22 is used to calculate a current prediction value corresponding to each voltage vector based on a pre-built permanent magnet synchronous motor model and eight pre-acquired voltage vectors of the inverter according to the sampled current value;

[0116] The second calculation module 23 is used to input the pre-acquired current reference value into the time domain difference equation to calculate the current harmonic reference value of the α and β axes, and input each current prediction value into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes;

[0117] The minimization module 24 is used to take the current harmonic reference value and each current harmonic prediction value as a set of input data, and input them into a pre-built cost function for calculation, and then select the voltage vector corresponding to the current harmonic prediction value when the cost function is minimized as the optimal voltage vector.

[0118] Optionally, the first calculation module 22 performs an operation of calculating a current prediction value corresponding to each voltage vector based on a pre-built permanent magnet synchronous motor model according to the sampled current value and eight pre-acquired voltage vectors of the inverter, specifically including:

[0119] Based on the pre-built permanent magnet synchronous motor model, the estimated sampling current values ​​of the α and β axes at the k+1 time are calculated by combining the input voltage values ​​and sampling current values ​​of the α and β axes in the kth control cycle;

[0120] Based on the pre-built permanent magnet synchronous motor model, the current prediction values ​​at the eight k+2 moments corresponding to the eight voltage vectors of the α and β axes are calculated according to the components of the eight voltage vectors of the inverter at the k+1 moment and the estimated value of the sampled current.

[0121] Alternatively, the permanent magnet synchronous motor model is expressed as:

[0122]

[0123] λ α =λ β =1 / L s ;

[0124]

[0125]

[0126]

[0127] Among them, i α and i β are the stator currents of the α and β axes, λ α and λ β are the input coefficients of the α and β axes, u α and u β are the stator voltages of the α and β axes, respectively, and F α and F β is the lumped disturbance observed by the preset design observer, e α and e β are the back electromotive force of α and β axes, L s and R s are the nominal inductance and nominal resistance of the permanent magnet synchronous motor, ψ f is the flux linkage of the permanent magnet synchronous motor, θ e is the electrical angle of the permanent magnet synchronous motor, ω e is the electrical angular velocity of the permanent magnet synchronous motor;

[0128] The calculation formula of the estimated value of the sampling current is expressed as:

[0129]

[0130] Among them, i α (k+1) and i β (k+1) are the estimated current values ​​sampled by the α and β axes at time k+1, u α (k) and u β (k) are the input voltage values ​​of the α and β axes in the kth control cycle, respectively. α (k) and F β (k) are the observed values ​​of the lumped disturbance of the α and β axes at the kth moment, T s is the sampling period;

[0131] The calculation formula of the current prediction value is expressed as:

[0132]

[0133] Where j = 0, ..., 7, u j Represents the eight voltage vectors of the inverter, and They are the current prediction values ​​at eight k+2 moments corresponding to the eight voltage vectors of the α and β axes, and are the components of the eight voltage vectors of the inverter at time k+1 on the α and β axes, F α (k+1) and F β (k+1) are the observed values ​​of the lumped disturbances of the α and β axes at time k+1.

[0134] Optionally, the second calculation module 23 performs the operation of inputting the pre-acquired current reference value into the time domain difference equation to calculate the current harmonic reference value of the α and β axes, and inputting each current prediction value into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes, specifically including:

[0135] Input the current reference value into the time domain difference equation to calculate the 1st current harmonic reference value and the mth current harmonic reference value of the α and β axes;

[0136] The current prediction values ​​at eight k+2 moments are respectively input into the time domain difference equation, and the 1st current harmonic prediction value and the mth current harmonic prediction value corresponding to each current prediction value of the α and β axes are calculated.

[0137] Alternatively, the time-domain difference equations of the current harmonics are expressed as:

[0138] X m (n) = e j2πm / N [X m (n-1)+x(n)-x(nN)];

[0139] Among them, X m (n) is the current harmonic amplitude at time n, X m (n-1) is the current harmonic amplitude at time n-1, x(n) is the sampled current value at time n, x(nN) is the sampled current value at time nN, j represents the imaginary unit, m represents the mth current harmonic, and N represents the number of samples.

[0140] Optionally, the calculation process of the current harmonic reference value is expressed as:

[0141]

[0142] in, and They are the mth harmonic reference values ​​of the α and β axes respectively. When m=1, it is the 1st harmonic reference value of the α and β axes. and are the current harmonic reference values ​​of the α and β axes at time k-1, and are the current reference values ​​of the α and β axes respectively, i α (kN) and i β (kN) are the sampling current values ​​of α and β axes at the time kN;

[0143] The calculation process of the current harmonic prediction value is expressed as:

[0144]

[0145] Where j = 0, ..., 7, u j are the eight voltage vectors of the inverter, and are the predicted values ​​of the mth order current harmonics of the α and β axes at time k+2, and when m=1, they are the predicted values ​​of the 1st order current harmonics of the α and β axes. and are the predicted current harmonic values ​​of the α and β axes at time k-1, and are the current prediction values ​​of the α and β axes at time k+2, corresponding to the eight voltage vectors of the inverter, i α (kN) and i β (kN) are the sampling current values ​​of α and β axes at the time kN respectively.

[0146] Alternatively, the cost function is expressed as:

[0147]

[0148] Among them, Cf j is the value of the cost function, ξ is the preset parameter, is =[i α i β ] T , j = 0, ..., 7, u j are the eight voltage vectors of the inverter, m represents the mth current harmonic, M represents the total number of current harmonics, is the reference value of the 1st current harmonic, is the predicted value of the 1st current harmonic, is the mth current harmonic reference value, is the predicted value of the mth current harmonic.

[0149] For other details about the technical solutions for implementing each module in the permanent magnet synchronous motor predictive current control device in the above embodiment, please refer to the description of the permanent magnet synchronous motor predictive current control method in the above embodiment, which will not be repeated here.

[0150] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0151] See also Figure 3 , Figure 3 FIG. 1 is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Figure 3 As shown, the computer device 30 includes a processor 31 and a memory 32 coupled to the processor 31, wherein the memory 32 stores program instructions. When the program instructions are executed by the processor 31, the processor 31 executes the steps of the permanent magnet synchronous motor predictive current control method described in any of the above embodiments.

[0152] The processor 31 may also be referred to as a CPU (Central Processing Unit). The processor 31 may be an integrated circuit chip having signal processing capabilities. The processor 31 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0153] See also Figure 4 , Figure 4It is a schematic diagram of the structure of the storage medium of the embodiment of the present invention. The storage medium of the embodiment of the present invention stores program instructions 41 that can implement the above-mentioned permanent magnet synchronous motor predictive current control method, wherein the program instructions 41 can be stored in the above-mentioned storage medium in the form of a software product, including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor (processor) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or a computer device such as a computer, a server, a mobile phone, or a tablet.

[0154] In the several embodiments provided in the present application, it should be understood that the disclosed computer equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0155] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional units. The above is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the contents of the specification and drawings of this application, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A method for predictive current control of a permanent magnet synchronous motor, characterized in that: It includes: In a two-phase stationary coordinate system, sampling current values ​​of the α and β axes are obtained, and sliding Fourier transform analysis is performed on the sampling current values ​​to construct a time domain difference equation of current harmonics; Based on a pre-built permanent magnet synchronous motor model, a current prediction value corresponding to each voltage vector is calculated according to the sampled current value and eight pre-acquired voltage vectors of the inverter; Inputting the pre-acquired current reference value into the time domain difference equation to calculate the current harmonic reference value of the α and β axes, and inputting each current prediction value into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes; The current harmonic reference value and each current harmonic prediction value are respectively used as a set of input data, and are input into a pre-constructed cost function for calculation, and then the voltage vector corresponding to the current harmonic prediction value with the minimum cost function is selected as the optimal voltage vector; wherein: The calculation process of current harmonic reference value is expressed as: in, and They are the mth harmonic reference values ​​of the α and β axes respectively. When m=1, it is the 1st harmonic reference value of the α and β axes. and are the current harmonic reference values ​​of the α and β axes at time k-1, and are the current reference values ​​of the α and β axes respectively, i α (kN) and i β (kN) are the sampling current values ​​of α and β axes at the time kN; The calculation process of the current harmonic prediction value is expressed as: Where j = 0,…,7,u j are the eight voltage vectors of the inverter, and are the predicted values ​​of the mth order current harmonics of the α and β axes at time k+2, and when m=1, they are the predicted values ​​of the 1st order current harmonics of the α and β axes. and are the predicted current harmonic values ​​of the α and β axes at time k-1, and are the current prediction values ​​of the α and β axes at time k+2, corresponding to the eight voltage vectors of the inverter, i α (kN) and i β (kN) are the sampled current values ​​of the α and β axes at time kN, and N represents the number of samples.

2. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, characterized in that: The method based on the pre-built permanent magnet synchronous motor model calculates the current prediction value corresponding to each voltage vector according to the sampled current value and eight pre-acquired voltage vectors of the inverter, including: Based on the pre-built permanent magnet synchronous motor model, the estimated sampled current values ​​of the α and β axes at the time k+1 are calculated by combining the input voltage values ​​of the α and β axes at the time k and the sampled current values; Based on the pre-built permanent magnet synchronous motor model, according to the components of the eight voltage vectors of the inverter at the k+1 moment on the α and β axes and the sampled current estimation value, the current prediction values ​​at the eight k+2 moments corresponding to the eight voltage vectors on the α and β axes are calculated.

3. The method for predictive current control of a permanent magnet synchronous motor according to claim 2, characterized in that: The permanent magnet synchronous motor model is expressed as: l α =λ β =1 / L s ; Among them, i α and i β are the stator currents of the α and β axes, λ α and λ β are the input coefficients of the α and β axes, u α and u β are the stator voltages of the α and β axes, respectively, and F α and F β is the lumped disturbance observed by the preset design observer, e α and e β are the back electromotive force of α and β axes, L s and R s are the nominal inductance and nominal resistance of the permanent magnet synchronous motor, ψ f is the flux linkage of the permanent magnet synchronous motor, θ e is the electrical angle of the permanent magnet synchronous motor, ω e is the electrical angular velocity of the permanent magnet synchronous motor; The calculation formula of the sampling current estimation value is expressed as: Among them, i α (k+1) and i β (k+1) are the estimated current values ​​sampled by the α and β axes at time k+1, u α (k) and u β (k) are the input voltage values ​​of α and β axes at time k, respectively. α (k) and F β (k) are the observed values ​​of the lumped disturbance of the α and β axes at time k, T s is the sampling period; The calculation formula of the current prediction value is expressed as: Where j = 0,…,7,u j Represents the eight voltage vectors of the inverter, and They are the current prediction values ​​at eight k+2 moments corresponding to the eight voltage vectors of the α and β axes, and are the components of the eight voltage vectors of the inverter at time k+1 on the α and β axes, F α (k+1) and F β (k+1) are the observed values ​​of the lumped disturbances of the α and β axes at time k+1.

4. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, characterized in that: The method of inputting the pre-acquired current reference value into the time domain difference equation to calculate the current harmonic reference value of the α and β axes, and inputting each current prediction value into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes, comprises: Inputting the current reference value into the time domain difference equation, and calculating the 1st current harmonic reference value and the mth current harmonic reference value of the α and β axes; The current prediction values ​​at eight k+2 moments are respectively input into the time domain difference equation, and the 1st current harmonic prediction value and the mth current harmonic prediction value corresponding to each current prediction value of the α and β axes are calculated.

5. The method for predictive current control of a permanent magnet synchronous motor according to claim 4, characterized in that: The time domain difference equation of the current harmonics is expressed as: X m (n)=e j2πm / N [X m (n-1)+x(n)-x(n-N)]; Among them, X m (n) is the current harmonic amplitude at time n, X m (n-1) is the current harmonic amplitude at time n-1, x(n) is the sampled current value at time n, x(nN) is the sampled current value at time nN, j represents the imaginary unit, m represents the mth current harmonic, and N represents the number of samples.

6. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, characterized in that: The cost function is expressed as: Among them, Cf j is the value of the cost function, ξ is the preset parameter, i s =[i α i β ] T ,i α and i β are the stator currents of the α and β axes, j = 0,…,7, u j are the eight voltage vectors of the inverter, m represents the mth current harmonic, M represents the total number of current harmonics, is the reference value of the 1st current harmonic, is the predicted value of the 1st current harmonic, is the mth current harmonic reference value, is the predicted value of the mth current harmonic.

7. A permanent magnet synchronous motor predictive current control device using the permanent magnet synchronous motor predictive current control method according to claim 1, characterized in that: It includes: A construction module is used to obtain the sampled current values ​​of the α and β axes in a two-phase stationary coordinate system, and to perform sliding Fourier transform analysis on the sampled current values ​​to construct a time domain difference equation of the current harmonics; A first calculation module is used to calculate a current prediction value corresponding to each voltage vector based on a pre-built permanent magnet synchronous motor model and the sampled current value and eight pre-acquired voltage vectors of the inverter; A second calculation module is used to input the pre-acquired current reference value into the time domain difference equation to calculate the current harmonic reference value of the α and β axes, and input each current prediction value into the time domain difference equation to calculate the current harmonic prediction value corresponding to each current prediction value of the α and β axes; The minimization module is used to take the current harmonic reference value and each current harmonic prediction value as a set of input data, and input them into a pre-built cost function for calculation, and then select the voltage vector corresponding to the current harmonic prediction value when the cost function is minimized as the optimal voltage vector.

8. A computer device, characterized in that: The computer device includes a processor and a memory coupled to the processor, wherein program instructions are stored in the memory, and when the program instructions are executed by the processor, the processor executes the steps of the permanent magnet synchronous motor predictive current control method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that: Program instructions capable of implementing the permanent magnet synchronous motor predictive current control method as described in any one of claims 1-6 are stored.

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