A model predictive current control method for permanent magnet synchronous motor based on hybrid control set

Abstract

The application relates to a permanent magnet synchronous motor model prediction current control method based on a hybrid control set, which mainly comprises the following steps: a permanent magnet synchronous motor mathematical model based on Heun method discretization; selecting two adjacent effective voltage vectors and one zero voltage vector in each sector as an initial control set, calculating corresponding stator current slopes, and solving corresponding ideal action time based on a deadbeat control; obtaining different voltage vector combinations and actual action time according to different time ranges; synthesizing a desired voltage vector, and optimizing an optimal action voltage vector combination through a cost function composed of a maximum current error; and then calculating PWM three-phase duty cycles for controlling the switching state of an inverter. The hybrid control set of the method is composed of multiple initial control sets. Compared with a traditional model prediction current control method based on a single control set, the application effectively reduces dq-axis current pulsation and improves phase current output quality.

Description

Technical Field

[0001] This invention relates to the field of permanent magnet synchronous motor drive control, specifically to a model predictive current control method for permanent magnet synchronous motors based on a hybrid control set, which further optimizes the drive performance of permanent magnet synchronous motors. Background Technology

[0002] Compared to DC motors, permanent magnet synchronous motors (PMSMs) offer superior dynamic performance and lower torque ripple, leading to their widespread application in industrial sectors. Stability is a critical performance requirement for PMSMs, necessitating low-ripple flux linkage, torque, and high-quality current output. Thanks to advancements in modern microprocessors, predictive control schemes have been proposed to improve motor control performance, such as deadbeat control, trajectory prediction, and model predictive control.

[0003] Model predictive control (PMSM) technology, with its flexibility in handling multi-objective optimization problems under various nonlinear constraints, has attracted considerable attention from researchers. Among these, model predictive current control based on a finite single control set offers advantages such as simple principle and low computational cost. However, it suffers from drawbacks including variable inverter switching frequency, large current and torque ripple, and a limited number of selectable voltage vectors with fixed directions and amplitudes, resulting in poor steady-state performance. Therefore, to improve the performance of PMSM systems, it is crucial to further expand the control set of model predictive current control beyond the finite single control set, enabling the system to obtain the optimal voltage vector combination during actual operation. Summary of the Invention

[0004] To achieve the objectives of this invention, a model predictive current control method for permanent magnet synchronous motors based on a hybrid control set is proposed. This method aims to further expand the control set of model predictive current control, thereby enabling the system to achieve superior operational control performance. To achieve the above objectives, this invention implements the following technical solution.

[0005] Step 1: Obtain the nominal parameters of the permanent magnet synchronous motor, such as the stator resistance, dq-axis stator inductance, and rotor permanent magnet flux linkage. Based on the Heun method, discretize the stator current prediction equations under different voltage vectors in the dq coordinate system. The equations are as follows:

[0006]

[0007]

[0008] Among them, R s L d L q and ψ fThese are the electrical constants of a permanent magnet synchronous motor, namely the stator resistance, d-axis inductance component, q-axis inductance component, and rotor permanent magnet flux linkage amplitude. s It is the control period, k is the sampling time, and ω is the control period. e It is the electric angular velocity. d (k) and i q (k) represents the d-axis and q-axis current feedback values ​​at time k, respectively. d (k) and u q (k) represent the d-axis and q-axis voltage components at time k, respectively. dp (k+1) and i qp (k+1) represent the predicted current values ​​for the d-axis and q-axis, respectively. d (k+1) and i q (k+1) are the predicted current values ​​of the d-axis and q-axis at time (k+1).

[0009] Step 2: Select two adjacent effective voltage vectors u for each sector x u y A zero-voltage vector u0 is used as the initial control set. Each sector's initial control set contains exactly one combination of voltage vectors, and the six initial control sets constitute the hybrid control set of the method involved. During the control cycle, the current slope is calculated when the three voltage vectors corresponding to the initial control set of each sector act individually. The calculation equations are as follows:

[0010]

[0011] Where, m d0 m q0 m dx m qx m dy m qy Representing u0 and u respectively x u y The slope of the dq-axis current under the action. E d0 E q0 E dx E qx E dy E qy Representing u0 and u x u y The dq-axis current error term under the action, and and These are the dq-axis current components when u0 is applied. and They are u x u y The dq-axis current components at time k+1 during the action, where x,y∈(1,2,...,6).

[0012] Step 3: Establish the initial control set u x u y The stator current prediction equations at time k+1 under the combined action of u0 are obtained by using deadbeat control to ensure that the predicted stator current value at time k+1 remains consistent with the current reference value. The equations are as follows:

[0013]

[0014] Among them, i d (k) and i q (k) represents the current components along the dq axis at time k. d (k+1) and i q (k+1) represent the current components along the dq axis at time k+1. d_evv and m q_evv t represents the dq-axis current slope of the desired synthesized voltage vector. evv Let t represent the duration of the desired synthesized voltage vector, and t = 1 / 2. evv =t x +t y . t x t y t0 and u are respectively x u y The ideal action time corresponding to u0. and They are i d and i q Reference values.

[0015] Step 4: Solve for u using the equations mentioned above. x u y The ideal action time corresponding to u0 is calculated using the following equation:

[0016] And t x +t y +t0=T s

[0017] in, and These represent the errors between the dq-axis feedback current and the reference current at time k, respectively.

[0018] Step 5: Calculate u based on the range of the action time t0 of u0. x u y and the actual time of action of u0 d x d y The specific determination of t0 is as follows: (1) If t0 is a positive value and not greater than the control period T sThen d0 = t0, and t needs to be further determined. x and t y The range, i.e., if t x or t y If it is a negative value, then the corresponding u x or u y (2) If t0 is not within the control period T s Within the range, d0 = 0. Also consider if t... x and t y All values ​​are positive and require modulation processing; otherwise, t x or t y If it is a negative value, then only the corresponding u x or u y It takes effect and operates throughout the entire control cycle, i.e., d x or d y Equal to control period T s The equation is described as follows:

[0019]

[0020] in,

[0021] Step Six: Based on the initial control set u x u y The vector combination of u0 and u0 is used to synthesize a desired voltage vector u. evv And calculate the corresponding stator voltage components along the d-axis and q-axis. The system of equations is as follows:

[0022]

[0023] in, and Corresponding to u x and u y d-axis component, and Corresponding to u x and u y The q-axis component. u d_evv and u q_evv They represent u respectively evv The dq axis components.

[0024] Step 7: Establish a cost function composed of the maximum current error, denoted by G, and optimize the optimal voltage vector combination based on the cost function. The cost function equation is as follows:

[0025]

[0026] Among them, t on =d x +dy . This represents the maximum stator current error value within the control cycle. and Representing non-integer time t within the control period respectively on The predicted value of the stator current.

[0027] Step 8: Based on the selected optimal voltage vector combination and its corresponding actual action time, convert it into the PWM three-phase duty cycle according to the proportion of the control cycle. The equation is as follows:

[0028]

[0029] Among them, t PWM1 t PWM2 and t PWM3 These represent the duty cycle times of the three-phase PWM driving the inverter.

[0030] The present invention proposes a model predictive current control method for permanent magnet synchronous motors based on a hybrid control set. The beneficial effects are as follows: In each control cycle, the voltage vector acting on the inverter is not limited to a single vector or two vectors, but is a combination of voltage vectors corresponding to different sectors of each initial control set, thereby expanding into a hybrid control set containing multiple voltage vector combinations. Furthermore, the optimal voltage vector combination is obtained by optimization based on the cost function of the maximum current error, which effectively reduces the dq-axis current ripple of the permanent magnet synchronous motor, thereby effectively improving the output quality of the phase current and providing good control performance for the system. Attached Figure Description

[0031] Figure 1 This is a block diagram of the dual closed-loop control system of the permanent magnet synchronous motor system of the present invention;

[0032] Figure 2 This is a schematic diagram of the hybrid control set corresponding to different sectors of the present invention;

[0033] Figure 3 This is a schematic diagram of the stator current trajectory of the present invention;

[0034] Figure 4 Simulation waveforms for predictive current control using a traditional single vector model;

[0035] Figure 5 This invention relates to a simulation waveform diagram of a model predictive current control method. Detailed Implementation

[0036] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings and a classic three-phase permanent magnet synchronous motor drive system.

[0037] Figure 1This is a block diagram of the dual closed-loop control system for the permanent magnet synchronous motor system of the present invention. The dashed box describes the main implementation process of the present invention, which mainly includes calculating the actual action time of the three voltage vectors, synthesizing the desired voltage vector and optimizing the cost function, and calculating the PWM duty cycle. The specific implementation steps are as follows:

[0038] First, the nominal parameters of the permanent magnet synchronous motor, such as the stator resistance, dq-axis stator inductance, and rotor permanent magnet flux linkage, are obtained. Based on the Heun method, a set of stator current prediction equations for different voltage vectors in the dq coordinate system is discretized. The equations described are as follows:

[0039]

[0040]

[0041] Among them, R s L d L q and ψ f These are the electrical constants of a permanent magnet synchronous motor, namely the stator resistance, d-axis inductance component, q-axis inductance component, and rotor permanent magnet flux linkage amplitude. s It is the control period, k is the sampling time, and ω is the control period. e It is the electric angular velocity. d (k) and i q (k) represents the d-axis and q-axis current feedback values ​​at time k, respectively. d (k) and u q (k) represent the d-axis and q-axis voltage components at time k, respectively. dp (k+1) and i qp (k+1) represent the predicted current values ​​for the d-axis and q-axis, respectively. d (k+1) and i q (k+1) are the predicted current values ​​of the d-axis and q-axis at time (k+1).

[0042] Next, select two adjacent effective voltage vectors u for each sector. x u y A zero-voltage vector u0 is used as the initial control set. Each sector's initial control set contains exactly one combination of voltage vectors, and the six initial control sets constitute the hybrid control set of the method involved, such as... Figure 2 As shown. During the control cycle, the current slope is calculated when the three voltage vectors corresponding to the initial control set of each sector act individually. The calculation equation is as follows:

[0043]

[0044] Where, m d0 m q0 mdx m qx m dy m qy Representing u0 and u respectively x u y The slope of the dq-axis current under the action. E d0 E q0 E dx E qx E dy E qy Representing u0 and u x u y The dq-axis current error term under the action, and and These are the dq-axis current components when u0 is applied. and They are u x u y The dq-axis current components at time k+1 during the action, where x,y∈(1,2,...,6).

[0045] Establish initial control set u x u y The stator current prediction equations at time k+1 under the combined action of u0 are obtained by using deadbeat control to ensure that the predicted stator current value at time k+1 remains consistent with the current reference value. The equations are as follows:

[0046]

[0047] Among them, i d (k) and i q (k) represents the current components along the dq axis at time k. d (k+1) and i q (k+1) represent the current components along the dq axis at time k+1. d_evv and m q_evv t represents the dq-axis current slope of the desired synthesized voltage vector. evv Let t represent the duration of the desired synthesized voltage vector, and t = 1 / 2. evv =t x +t y . t x t y t0 and u are respectively x u y The ideal action time corresponding to u0. and They are i d and i q Reference values.

[0048] Secondly, based on the equations mentioned above, u can be solved jointly.x u y The ideal action time corresponding to u0 is calculated using the following equation:

[0049] And t x +t y +t0=T s

[0050] in, and These represent the errors between the dq-axis feedback current and the reference current at time k, respectively.

[0051] Then, based on the range of the action time t0 of u0, u is calculated. x u y and the actual time of action of u0 d x d y The specific determination of t0 is as follows: (1) If t0 is a positive value and not greater than the control period T s Then d0 = t0, and t needs to be further determined. x and t y The range, i.e., if t x or t y If it is a negative value, then the corresponding u x or u y (2) If t0 is not within the control period T s Within the range, d0 = 0. Also consider if t... x and t y If all values ​​are positive, modulation processing is required; otherwise, t x or t y If it is a negative value, then only the corresponding u x or u y It takes effect and operates throughout the entire control cycle, i.e., d x or d y Equal to control period T s The equation is described as follows:

[0052]

[0053] in,

[0054] Furthermore, according to the initial control set u x u y The vector combination of u0 is used to synthesize a desired voltage vector u. evv ,like Figure 2 As shown, the subscript numbers represent the desired voltage vector corresponding to each initial control set, and the stator voltage components along the d-axis and q-axis are calculated. The system of equations is as follows:

[0055]

[0056] in, and Corresponding to u x and u y d-axis component, and Corresponding to u x and u y The q-axis component. u d_evv and u q_evv They represent u respectively evv The dq axis components.

[0057] Figure 3 This is a schematic diagram of the stator current trajectory output by the system during the control cycle, showing the current trajectories corresponding to different basic voltage vectors (taking u1 and u2 as examples). and ) and desired voltage vector (u evv The corresponding current trajectory The intersection point of the predicted current trajectory corresponding to time k+1 is the maximum predicted current error of the model predicted current control method involved in this invention.

[0058] Next, a cost function, denoted by G, consisting of the maximum current error, is established, and the optimal voltage vector combination is obtained based on the cost function. The cost function equation is as follows:

[0059]

[0060] Among them, t on =d x +d y . This represents the maximum stator current error value within the control cycle. and Representing non-integer time t within the control period respectively on The predicted value of the stator current.

[0061] Finally, based on the selected optimal voltage vector combination and its corresponding actual operating time, it is converted into the PWM three-phase duty cycle according to the control cycle ratio and applied to the inverter. The equation is as follows:

[0062]

[0063] Among them, t PWM1 t PWM2 and t PWM3 These represent the duty cycle times of the three-phase PWM driving the inverter.

[0064] Figure 4 and Figure 5Simulation waveforms of traditional single-vector model predictive current control (MMDC) and the model predictive current control method of this invention, obtained based on MATLAB / SIMULINK software simulations, are shown respectively. The observed and calculated physical quantities include motor speed, output torque, stator flux linkage amplitude, dq-axis stator current, and the total harmonic distortion (THD) of the A-phase current at 300 RPM. It can be seen that, compared to the traditional single-vector model predictive current control method, the model predictive current control method of this invention achieves lower torque ripple and dq-axis current ripple, as well as more ideal phase current quality, thus effectively improving the steady-state performance of the system.

[0065] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the present invention. However, it is obvious that the described implementation solutions are only a part of the embodiments of the present invention, and not all of them.

Claims

1. A model predictive current control method for permanent magnet synchronous motors based on a hybrid control set, characterized in that, The specific steps are as follows: Step 1: Obtain the nominal parameters of the permanent magnet synchronous motor, establish the stator voltage equations of the permanent magnet synchronous motor in the dq coordinate system, and after discretization by the Heun method, obtain the stator current prediction equations under different voltage vectors in the dq coordinate system. Step 2: Select two adjacent effective voltage vectors and one zero voltage vector for each sector as the initial control set, and calculate the current slope corresponding to the individual action of the three voltage vectors in one control cycle; Step 3: Establish the initial control set when the three voltage vectors act together. The stator current prediction equations at time 1, combined with the concept of deadbeat control, enable... The predicted stator current at time t is consistent with the current reference value. Further calculations are needed to determine the ideal duration of the three voltage vectors. , , ; Step 4: Based on the duration of the zero voltage vector Within the range, the actual action time of the three voltage vectors of the initial control set is calculated. , , The specific determination is described as follows: If If it is a positive value and not greater than the control period, then And further judgment is needed. and The range, that is, if or If the value is negative, the corresponding effective voltage vector has no effect; if If it is outside the control cycle range, then At the same time, consider if and All values ​​are positive and require modulation processing; otherwise... or If the value is negative, only the corresponding effective voltage vector will take effect; Step 5: Synthesize the desired voltage vector and calculate the corresponding stator voltage components along the d-axis and q-axis; Step 6: Based on the prediction equation set, calculate the predicted stator current values ​​at non-integer times within the control cycle, construct a cost function composed of the maximum current error, and optimize to obtain the optimal voltage vector combination; Step 7: Based on the selected optimal voltage vector combination and its corresponding actual action time, convert it into the PWM three-phase duty cycle according to the control cycle ratio and apply it to the inverter; Establish a cost function consisting of the maximum current error, and use... The optimal voltage vector combination is obtained by optimization based on the cost function, which is as follows: in, , This represents the maximum stator current error value within the control cycle. and These represent the non-integer moments within the control period. The predicted value of the stator current.

2. The method for predictive current control of a permanent magnet synchronous motor model based on a hybrid control set according to claim 1, characterized in that, The nominal parameters of the permanent magnet synchronous motor are obtained, and the stator current prediction equations under different voltage vectors in the dq coordinate system are discretized based on the Heun method. The equations are as follows: in, , , and These are the electrical constants of a permanent magnet synchronous motor, namely the stator resistance, d-axis inductance component, q-axis inductance component, and rotor permanent magnet flux linkage amplitude. It is a control cycle. These are the sampling time numbers. It is electric angular velocity. and They are The d-axis and q-axis current feedback values ​​at time t. and They are Voltage components along the d-axis and q-axis at time t. and These are the predicted current values ​​for the d-axis and q-axis, respectively. and They are Predicted current values ​​for the d-axis and q-axis at time t.

3. The method for predictive current control of a permanent magnet synchronous motor based on a hybrid control set according to claim 2, characterized in that, First, select two adjacent effective voltage vectors for each sector. and a zero voltage vector As the initial control set, each sector's initial control set contains one and only one combination of voltage vectors, and the six initial control sets constitute the hybrid control set of the method involved. During the control cycle, the current slope when the three voltage vectors corresponding to the initial control set of each sector act individually is calculated, and the calculation equation is as follows: ， in, , , , , , They represent and , dq-axis current slope under action, , , , , , express and , The dq-axis current error term under the action, and and They are The dq-axis current components during operation , , and They are , The dq-axis current component during operation, and .

4. The method for predictive current control of a permanent magnet synchronous motor model based on a hybrid control set according to claim 3, characterized in that, Establish the initial control set in the current control cycle. When working together The stator current prediction equations at time 10 are used in a deadbeat control manner to make... The predicted stator current at time t is consistent with the current reference value, and the equations are as follows: ， in, and They represent The current component along the dq axis at time t. and They represent The current component along the dq axis at time t. and The dq-axis current slope represents the desired synthesized voltage vector. This represents the duration of the desired synthesized voltage vector, and has... , , , They are respectively , and The corresponding ideal action time, and These are the reference current values ​​for the dq axes, respectively.

5. The method for predictive current control of a permanent magnet synchronous motor model based on a hybrid control set according to claim 4, characterized in that, Based on the equations mentioned above, a joint solution is obtained. , and The corresponding ideal action time is calculated using the following equation: ,and in, and These represent the errors between the dq-axis feedback current and the reference current at time k, respectively.

6. The method for predictive current control of a permanent magnet synchronous motor model based on a hybrid control set according to claim 3, characterized in that, according to Duration of action The range was calculated. , and Actual action time , and The specific judgment is described as follows: (1) If It is a positive value and not greater than the control period. ,but And further judgment is needed. and The range, that is, if or If it is a negative value, then the corresponding or (2) If Not in control cycle Within the range, then At the same time, consider if and All values ​​are positive and require modulation processing; otherwise... or If it is a negative value, then only the corresponding or It works, and it works throughout the entire control cycle, that is... or equal to control period The equation is described as follows: in, .

7. The method for predictive current control of a permanent magnet synchronous motor model based on a hybrid control set according to claim 3, characterized in that, According to the initial control set The vector combinations are used to synthesize a desired voltage vector. And calculate the corresponding stator voltage components along the d-axis and q-axis. The system of equations is as follows: in, and Corresponding to and d-axis component, and Corresponding to and q-axis components and They represent The dq axis components.

8. The method for predictive current control of a permanent magnet synchronous motor model based on a hybrid control set according to claim 1, characterized in that, Based on the selected optimal voltage vector combination and its corresponding actual action time, it is converted into the PWM three-phase duty cycle according to the proportion of the control cycle, as shown in the following equation: in, , and These represent the duty cycle times of the three-phase PWM driving the inverter.

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