Improved model predictive current control method and system for six-phase permanent magnet synchronous motor

Abstract

The application discloses an improved model prediction current control method and system of a six-phase permanent magnet synchronous motor, relates to the technical field of motor control, and mainly comprises the following steps: transforming stator current to a synchronous rotating coordinate system to obtain a current reference value according to phase current and rotor position at a current time, obtaining predicted current at a next time by using a current prediction model, obtaining a plane reference current by using a speed loop proportional integral controller d - q , obtaining candidate voltage vectors by using a simplified vector control set, calculating a value function corresponding to each candidate voltage vector, selecting a voltage vector with the minimum value function to obtain a selected voltage vector for controlling a two-level six-phase voltage source inverter. The method and system provided by the application can reduce the calculation complexity of the six-phase permanent magnet synchronous motor control, reduce the total harmonic distortion rate of the phase current, shorten the stable time when the load suddenly changes, enhance the system stability, avoid complex weight factor setting, and reduce electromagnetic interference.

Description

Technical Field

[0001] This invention relates to the field of motor control technology, and more specifically, to an improved model predictive current control method and system for a six-phase permanent magnet synchronous motor. Background Technology

[0002] Permanent magnet synchronous motor (PMSM) drive systems are widely used in machine tools, industrial automation, renewable energy, and transportation systems. These systems primarily consist of power electronic converters, motors, and controllers. In scenarios requiring high reliability, low voltage, high power density, and precise transmission, multiphase PMSM drive systems are widely used due to their low torque ripple and good fault tolerance. In recent years, Model Predictive Control (MPC) has gained significant attention in the PMSM control field due to its advantages such as fast dynamic response, strong multivariable constraint handling capabilities, and easily understandable algorithm structure. Among these, Finite Control Set Model Predictive Control (FCS-MPC) and Deadbeat Model Predictive Control (DB-MPC) are two mainstream implementation schemes. FCS-MPC utilizes the discrete switching characteristics of the power inverter, selecting the optimal switching state from a finite number of switching states through a preset mathematical value function. Six-phase PMSM drive systems typically use two-level voltage source inverters as the drive circuit, but this results in problems such as high computational load and high harmonic current during control, which negatively impact motor performance. A six-phase PMSM can be constructed from two sets of three-phase star windings with a spatial phase difference of 30° (labeled ABC and DEF respectively), and can be transformed and analyzed using the vector space decoupling method. Current six-phase PMSM drive control mainly employs the traditional Model Predictive Current Control (MPCC) method. The basic principle of this method is to predict the motor's operating state at future moments and select the voltage vector that minimizes the value function to be applied to the motor. The block diagram of the traditional MPCC method is shown below. Figure 2 As shown. The control flow of the prior art includes: acquiring real-time current and rotor position data through a signal acquisition unit; converting the stator current to a synchronous rotating coordinate system through a space vector decoupling (VSD) and Park transformation unit; and predicting the current using a current prediction model unit. d - q Basic plane and x - y The current in the harmonic plane; the given current is obtained through the proportional-integral (PI) controller unit of the speed loop; the optimal voltage vector is evaluated through the value function unit; the optimal voltage vector is applied through the vector control set and the six-phase voltage source inverter unit. A two-level six-phase inverter has 2... 6= 64 switching states, corresponding to 64 basic voltage vectors, including 60 non-zero voltage vectors and 4 zero voltage vectors. These voltage vectors can be categorized into large voltage vectors, medium-large voltage vectors, medium-small voltage vectors, small voltage vectors, and zero voltage vectors. However, the existing technology has the following drawbacks: 1) High computational complexity: A six-phase PMSM has 64 switching states, and a traditional MPCC needs to traverse all possible voltage vectors, resulting in a large computational burden; 2) Large harmonic current: Under the traditional method, the total harmonic distortion (THD) of the phase current is high and the harmonic loss is significant; 3) Slow dynamic response: Under sudden load changes, the response time and settling time of traditional methods are both relatively long; 4) Large current fluctuations: In traditional methods x shaft and y The shaft current fluctuates significantly. 5) The value function design is complex: it requires the introduction of weighting factors to make multi-objective trade-offs, which increases the difficulty of parameter tuning; 6) Unfixed switching frequency: This leads to prominent electromagnetic interference problems and increases the complexity of filter design. Summary of the Invention

[0003] The purpose of this invention is to provide an improved model predictive current control method and system for a six-phase permanent magnet synchronous motor, which can reduce the computational complexity of six-phase permanent magnet synchronous motor control, reduce the total harmonic distortion rate of phase current, shorten the settling time during load changes, enhance system stability, avoid complex weight factor tuning, and reduce electromagnetic interference.

[0004] This invention provides an improved model predictive current control method for a six-phase permanent magnet synchronous motor, comprising the following steps: S1: Obtain the current phase current and rotor position; S2: Based on the current phase current and rotor position, transform the stator current to the synchronous rotating coordinate system to obtain the current reference value; S3: Based on the current reference value, use the current prediction model to obtain the predicted current at the next moment; S4: Based on the current phase current and rotor position, use a speed loop proportional-integral (PI) controller to obtain... d - q Current referenced in a plane; S5: Based on the predicted current and d - q The current from the plane reference is used to obtain the candidate voltage vector using a simplified vector control set; S6: Calculate the value function corresponding to each candidate voltage vector, select the voltage vector with the smallest value function, and obtain the selected voltage vector; S7: Use the selected voltage vector to control a two-level six-phase voltage source inverter.

[0005] This invention also provides an improved model predictive current control system for a six-phase permanent magnet synchronous motor, comprising the following units: The signal acquisition unit is configured to acquire the phase current and rotor position at the current moment. The transformation unit is configured to transform the stator current to the synchronous rotating coordinate system based on the phase current and rotor position at the current moment, so as to obtain the current reference value. The current prediction model unit is configured to: obtain the predicted current at the next moment based on the current reference value using the current prediction model; The speed loop PI controller unit is configured to: obtain the current phase current and rotor position using a speed loop proportional-integral (PI) controller. d - q Planar reference current The vector control set unit is configured to: based on the predicted current and d - q The current from the plane reference is used to obtain the candidate voltage vector using a simplified vector control set; The value function unit is optimized by calculating the value function corresponding to each candidate voltage vector, selecting the voltage vector with the smallest value function, and obtaining the selected voltage vector. The six-phase voltage source inverter unit is configured to control a two-level six-phase voltage source inverter using the selected voltage vector.

[0006] The improved model predictive current control method and system for a six-phase permanent magnet synchronous motor provided by this invention has the following beneficial effects: This invention obtains a current reference value by transforming the stator current to a synchronous rotating coordinate system based on the current phase current and rotor position at the current moment. It then uses a current prediction model to obtain the predicted current for the next moment and a speed loop PI controller to achieve the desired result. d - q The current referenced in the plane is used to obtain candidate voltage vectors using a simplified vector control set. The value function corresponding to each candidate voltage vector is calculated, and the voltage vector with the smallest value function is selected. The selected voltage vector is then used to control a two-level six-phase voltage source inverter.

[0007] This invention reduces the THD of the phase current from 29.64% in the conventional method to 6.00%, significantly reducing harmonic losses and distortion. When a 10 N·m load change is applied at 0.4 s, the q-axis current response time of this invention is 25 ms, much faster than the 120 ms of the conventional method. The settling time is shortened from 25 ms to 22 ms, and the transition period is reduced from 80 ms to 45 ms. The present invention significantly improves dynamic response speed; it reduces the harmonic current amplitudes of the x-axis and y-axis from ±1.72A and ±1.71A in the traditional method to approximately ±0.5A and ±0.45A, respectively, a reduction of over 70%, which greatly reduces current fluctuations; by simplifying the vector control set, the present invention reduces computational complexity and significantly reduces the number of voltage vectors that need to be traversed, thereby improving the real-time performance of the algorithm and making it more suitable for embedded systems with limited computing resources; the improved value function of the present invention does not require the design of weight factors, reducing the difficulty of tuning control parameters and improving the robustness and adaptability of the system; the current waveform provided by the present invention is closer to an ideal sine wave, indicating a significant reduction in harmonic components, effectively improving the current waveform quality, and improving the operating efficiency and performance of the motor. In summary, the present invention reduces the computational complexity of the six-phase PMSM control system to improve real-time performance; suppresses harmonic currents, reduces the THD of phase currents, and improves power quality; accelerates dynamic response speed and shortens the settling time during load changes; reduces current fluctuations and enhances system stability; simplifies value function design and avoids complex weight factor tuning; and optimizes the switching frequency to reduce electromagnetic interference. Attached Figure Description

[0008] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart of the improved model predictive current control method for a six-phase permanent magnet synchronous motor provided by the present invention; Figure 2 This is the block diagram of a traditional model predictive current control six-phase PMSM provided by the present invention; Figure 3 This is the block diagram of the improved model predictive current control six-phase PMSM provided by the present invention; Figure 4 This is a schematic diagram of the six-phase permanent magnet synchronous motor drive system provided by the present invention; Figure 5 This is a schematic diagram of a six-phase two-level voltage source inverter provided by the present invention; Figure 6 This is a schematic diagram of the basic voltage vector control set provided by the present invention; Figure 7 This is a flowchart of the improved model predictive current control provided by the present invention; Figure 8This is a schematic diagram of the six-phase current waveform of the conventional model predictive current control method provided by the present invention; Figure 9 This is a schematic diagram of the six-phase current waveform of the improved model predictive current control method provided by the present invention; Figure 10 This is a schematic diagram of the current THD of the conventional model predictive current control method provided by the present invention; Figure 11 This is a schematic diagram of the current THD of the improved model predictive current control method provided by the present invention; Figure 12 This is a schematic diagram of the q-axis current waveform of the traditional and improved model predictive current control methods provided by this invention; Figure 13 This is a schematic diagram of the d-axis current waveform of the traditional and improved model predictive current control methods provided by this invention; Figure 14 This is a schematic diagram of the x-axis current waveform of the traditional and improved model predictive current control methods provided by this invention; Figure 15 This is a schematic diagram of the y-axis current waveform of the traditional and improved model predictive current control methods provided by this invention. Detailed Implementation

[0009] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0010] Figure 1 A schematic diagram of the improved model predictive current control method for a six-phase permanent magnet synchronous motor according to this embodiment is shown. In this embodiment, the improved model predictive current control method for a six-phase permanent magnet synchronous motor includes the following steps: S1: Obtain the current phase current and rotor position; S2: Based on the current phase current and rotor position, transform the stator current to the synchronous rotating coordinate system to obtain the current reference value; In one exemplary embodiment, the method for transforming the stator current to a synchronous rotating coordinate system is a space vector decoupling (VSD) transformation and a Park transformation; S3: Based on the current reference value, use the current prediction model to obtain the predicted current at the next moment; In one exemplary embodiment, the calculation formula for the current prediction model is:

[0011]

[0012]

[0013]

[0014] in, , , and They represent the first Each time step d axis, q axis, x shaft and y Shaft stator current components; , , and They represent the first Each time step d axis, q axis, x shaft and y Shaft stator current components; This indicates the resistance of each phase winding of the stator; Indicates the switching cycle of the inverter; express d Shaft inductance; express q Shaft inductance; express x Shaft inductance; express y Shaft inductance; Indicates electric angular velocity; Indicates the first Each time step d Shaft-stator voltage components; Indicates the first Each time step q Shaft-stator voltage components; Indicates the first Each time step x Shaft-stator voltage components; Indicates the first Each time step y Shaft-stator voltage components; This refers to the magnetic flux generated by a permanent magnet.

[0015] As an exemplary embodiment, the current prediction model can be constructed in one of the following ways: (1) Use more accurate discretization methods such as Runge-Kutta method and backward Euler method to construct the prediction model; (2) Introduce an online parameter identification algorithm to update motor parameters in real time and improve the accuracy of the prediction model; (3) Use data-driven methods to build a prediction model to adapt to the nonlinear characteristics of the system.

[0016] S4: Based on the current phase current and rotor position, use a speed loop proportional-integral (PI) controller to obtain... d - q Current referenced in a plane; S5: Based on the predicted current and d - q The current from the plane reference is used to obtain the candidate voltage vector using a simplified vector control set; In one exemplary embodiment, the selection criteria for the simplified vector control set are: Vectors with xy harmonic plane amplitude > 0.3 are excluded, and vectors with α-β fundamental plane amplitude ≥ 0.4 and uniform distribution are retained to ensure that there are at least 3 effective vectors within 120° electrical angle, and 2 zero vectors are retained for current fine adjustment; As an exemplary embodiment, the filtering of vector control sets can be simplified in one of the following ways: (1) Using virtual voltage vector combination: By allocating the time of multiple basic voltage vectors, a new virtual voltage vector is generated to further suppress harmonics; (2) Adaptive vector control set: The vector control set is dynamically adjusted according to operating parameters such as load size and speed range; (3) Selective harmonic elimination vector set: Design an optimized vector control set for specific harmonic orders, such as the 5th and 7th harmonics.

[0017] S6: Calculate the value function corresponding to each candidate voltage vector, select the voltage vector with the smallest value function, and obtain the selected voltage vector; In one exemplary embodiment, the formula for calculating the value function is:

[0018]

[0019]

[0020] in, Value function; for d Reference current of the shaft; for q Reference current of the shaft; It is a nonlinear constraint function; This represents the maximum current value. Indicates constraints; These are the switching functions of the six bridge arms of the inverter. This indicates that the upper bridge arm is open. This indicates that the lower bridge arm is open; and Indicates the first and The switching function of phase A bridge arm at each time step; and Indicates the first and The B-phase bridge arm switching function at each time step; and Indicates the first and The switching function of the C-phase bridge arm at each time step; and Indicates the first and The switching function of the D-phase bridge arm at each time step; and Indicates the first and E-phase bridge arm switching function at each time step; and Indicates the first and The switching function of the F-phase bridge arm at each time step.

[0021] As an exemplary embodiment, the value function can be designed in one of the following ways: (1) Value function based on fuzzy logic: adaptively adjust weights according to system state; (2) Multi-objective optimization value function: Incorporate indicators such as power loss, efficiency, and temperature into the value function; (3) Learning-based value function: The parameters of the value function are automatically optimized through reinforcement learning.

[0022] S7: Use the selected voltage vector to control a two-level six-phase voltage source inverter.

[0023] This embodiment provides an improved model predictive current control system for a six-phase permanent magnet synchronous motor, comprising the following units: The signal acquisition unit is configured to acquire the phase current and rotor position at the current moment. The transformation unit is configured to transform the stator current to the synchronous rotating coordinate system based on the phase current and rotor position at the current moment, so as to obtain the current reference value. The current prediction model unit is configured to: obtain the predicted current at the next moment based on the current reference value using the current prediction model; The speed loop PI controller unit is configured to: obtain the current phase current and rotor position using a speed loop proportional-integral (PI) controller. d - q Planar reference current The vector control set unit is configured to: based on the predicted current andd - q The current from the plane reference is used to obtain the candidate voltage vector using a simplified vector control set; The value function unit is optimized by calculating the value function corresponding to each candidate voltage vector, selecting the voltage vector with the smallest value function, and obtaining the selected voltage vector. The six-phase voltage source inverter unit is configured to control a two-level six-phase voltage source inverter using the selected voltage vector.

[0024] In some embodiments, the improved model predictive current control system for the six-phase permanent magnet synchronous motor described above can also be implemented in the following ways.

[0025] like Figure 3 As shown, in this embodiment, the improved model predictive current control system for the six-phase permanent magnet synchronous motor includes the following parts: Signal acquisition unit: used to sample real-time current and rotor position signals; VSD and Park transformation units: used to transform stator current to a synchronous rotating coordinate system; Current prediction model unit: used for prediction d - q shaft current; Speed ​​loop PI controller unit: used to obtain the given current; Optimization value function unit: used to evaluate the optimal voltage vector; Vector control set unit: used to reduce the voltage vectors that need to be traversed; Six-phase voltage source inverter unit: used to drive a six-phase PMSM.

[0026] In some embodiments, the improved model predictive current control method for the six-phase permanent magnet synchronous motor described above can also be implemented in the following ways.

[0027] In this embodiment, the improved model predictive current control method for a six-phase permanent magnet synchronous motor specifically includes the following steps: (1) Establish a six-phase PMSM mathematical model like Figure 4 As shown, the six-phase PMSM consists of two sets of star-connected three-phase windings (labeled ABC and DEF respectively), with a spatial phase difference of 30°. A transformation analysis is performed using the VSD method. After VSD transformation, the two sets of star-connected three-phase windings of the six-phase motor are decomposed into three independent... d - q The planes correspond to different harmonic frequency components such as the fundamental wave, the 5th harmonic, and the 7th harmonic.

[0028] In Triple d - q The voltage equation in the rotating coordinate system is:

[0029]

[0030]

[0031]

[0032]

[0033]

[0034] In the formula, and It is the first i indivual d - q In a plane d shaft and q Shaft-stator voltage components; and It is the first i indivual d - q in the plane d shaft and q Shaft stator current components; It is the resistance of each phase winding of the stator; and yes d shaft and q Shaft inductor, for surface-mount PMSM, ; It is electric angular velocity; It is a magnetic flux generated by a permanent magnet.

[0035] In Triple d - q The flux linkage equation in the rotating coordinate system is:

[0036]

[0037]

[0038]

[0039]

[0040]

[0041] In the formula, and It is the first i indivual d -q in the plane d shaft and q Shaft stator flux linkage component.

[0042] Total electromagnetic torque of a six-phase motor It equals the sum of the torques produced by three independent two-phase rectangular windings, that is:

[0043] In the formula, p It is an extreme logarithm.

[0044] (2) Space voltage vector of a two-level six-phase voltage source inverter Two-level six-phase voltage source inverter, such as Figure 5 As shown, assuming the switching state of each bridge arm is 1 or 0, the corresponding basic voltage vector is... α - β Basic plane and x - y The distribution of the harmonic plane is as follows Figure 6 As shown, and The voltage vector equation is:

[0045]

[0046] In the formula, This is the DC bus voltage; It is the switching function for the six bridge arms. This indicates that the upper bridge arm is open. This indicates that the lower bridge arm is open.

[0047] (3) Simplified vector control set A vector control set strategy is adopted to reduce the number of voltage vectors that need to be traversed. As shown in Table 1, based on the voltage vectors in... α - β Basic plane and x - y The amplitude characteristics of the harmonic plane can be analyzed by selecting appropriate large voltage vectors, medium-large voltage vectors, medium-small voltage vectors, small voltage vectors, and zero voltage vectors to form a control set, thereby suppressing harmonic components.

[0048] Table 1: Classification of Basic Voltage Vectors

[0049] 1) Control set selection criteria: Harmonic suppression takes priority: strict exclusion x - y Vectors with harmonic plane amplitude > 0.3, i.e. all small vectors and some medium-large or medium-small vectors; Fundamental wave control guarantee: Retained α - β Vectors with a basic plane amplitude ≥ 0.4 and uniform distribution, ensuring at least 3 effective vectors within a 120° electrical angle; Dynamic response requirements: Reserve two zero vectors for current fine-tuning.

[0050] 2) Final control set composition: All 12 large voltage vectors were selected and evenly distributed in 6 directions in the α-β plane, with 2 equivalent vectors in each direction; 2 zero vectors were retained; all 24 small vectors and the medium vectors with excessive amplitude in the xy plane were excluded; the control set size was reduced from 64 to 14, and the computational load was reduced by 78.1%.

[0051] 3) Harmonic suppression mechanism: Large vectors in x - y The plane amplitude is only 0.173, which is 26.9% of the small vector, and the excitation of the 5th and 7th harmonic currents generated after application is significantly reduced; the zero vector is at x - y The plane is unexcited and is used to smooth current transition.

[0052] 4) Key points for project implementation: Offline pre-computation of 14 candidate vectors α - β or x - y The planar projection values ​​are stored in a lookup table; during online control, only this simplified set is traversed, and there is no need to calculate vector classification in real time; combined with the nonlinear constraints of the improved value function, out-of-limit vectors are dynamically eliminated, further narrowing the scope of real-time calculation.

[0053] (4) Traditional current prediction model exist d - q Rotation plane and x - y The voltage equation for the harmonic plane is:

[0054]

[0055]

[0056]

[0057] In the formula, and for x shaft and y Shaft-stator voltage components; and for x shaft and y Shaft stator current components; and for x shaft and y Shaft inductance.

[0058] The difference equation for the current is established using the forward Euler method:

[0059]

[0060]

[0061]

[0062] In the formula, It is the switching cycle of the inverter; It is the first Each time step.

[0063] In traditional MPCC of surface-mount PMSM:

[0064]

[0065]

[0066]

[0067] The value function of the traditional MPCC method is defined as:

[0068] In the formula, and These are weighting coefficients used to balance the performance of fundamental current tracking and harmonic suppression. , , and They are respectively d axis, q axis, x shaft and y Reference current of the shaft.

[0069] (5) Improve the current prediction model To ensure the controller output accurately tracks reference values, such as the target current, a reasonable value function must be designed, selecting the optimal voltage vector from all possible voltage vectors based on control requirements. In traditional MPCC, each sampling cycle requires traversing all 64 switching states, calculating the predicted current for each state, and selecting the voltage vector that minimizes the value function to apply to the motor. Therefore, the design of the value function directly affects control accuracy, response speed, and computational burden.

[0070] For high-performance, low-complexity control of six-phase PMSM, the core idea of ​​the improved MPCC method is to improve control performance by simplifying the vector selection set and optimizing the value function structure, transform harmonic suppression from software parameter tuning to hardware vector screening, and integrate safety, efficiency and accuracy requirements through multi-objective value functions to achieve comprehensive optimization.

[0071] The value function is simplified to:

[0072] Only contains d shaft and q The sum of squared tracking errors of the shaft current no longer includes xy The axis term eliminates the need to adjust weight coefficients, significantly reducing computational load, improving real-time performance, and allowing for a greater focus on electromagnetic torque control.

[0073] 1) Define the nonlinear constraint function Used to limit the stator current amplitude:

[0074] In the formula, This represents the maximum current value.

[0075] When predicted or When the safe range is exceeded, an infinite penalty value is imposed. This makes it impossible for it to be selected as the optimal solution.

[0076] 2) Add constraints:

[0077] When the sampling time is short, this control strategy reduces the number of switching state changes. That is, during control, it not only pursues current tracking accuracy but also minimizes switching actions. This method embodies a hard-constraint optimization strategy: guiding controller behavior by limiting state changes, rather than relying on complex weighting parameter tuning.

[0078] 3) Improved value function: The value function of the improved MPCC method is defined as:

[0079] like Figure 7 As shown, the control flow of the improved MPCC method includes: a. Sampling k Phase current and rotor position at any given time; b. Obtain through VSD transformation and Park transformation d - q Rotation plane and x - y Current in the harmonic plane; c. Calculate using the current prediction model k Predicted current at time +1; d. Based on the speed loop PI controller, obtain d - q Current referenced in a plane; e. Traverse candidate voltage vectors within a simplified vector control set; f. Calculate the value function corresponding to each candidate voltage vector; g. Choose the voltage vector that minimizes the value function; h. Apply the selected voltage vector to the two-level six-phase voltage source inverter.

[0080] Table 2: Six-phase PMSM parameters of the embodiment

[0081] Table 3: Comparison of Indicators between Traditional and Improved MPCC Methods

[0082] It should be noted that the key to this invention lies in 1) a simplified method for constructing a vector control set: based on the voltage vector in αβ Basic plane and xy The amplitude characteristics on the harmonic plane are shown in Table 1. Intelligent selection of voltage vectors to form a control set achieves a balance between fundamental wave control and harmonic suppression; 2) Improved value function design: simplifies the traditional MPCC value function, ignoring... xy Planar constraints eliminate the need for weight factor adjustments, significantly reducing computational complexity; 3) Nonlinear current amplitude constraint mechanism: A nonlinear equation limiting the stator current amplitude is added to the design's value function, improving system safety while reducing the number of switching operations; 4) Overall control process optimization: such as... Figure 7 The complete control flow shown integrates functions such as signal acquisition, coordinate transformation, current prediction, value function evaluation, and vector selection to achieve high-performance control of a six-phase PMSM; 5) Quantitative indicators of harmonic suppression effect: In the embodiment, the phase current THD is reduced from 29.64% to 6.00%. x shaft and yThe current fluctuation of the shaft was reduced from ±1.7A to ±0.5A, and the dynamic response time was shortened from 120 ms to 25 ms.

[0083] like Figure 10 and Figure 11 As shown, this invention reduces the THD of the phase current from 29.64% using conventional methods to 6.00%, significantly reducing harmonic losses, demonstrating that this invention can significantly reduce harmonic distortion. Figure 12 As shown, when a 10 N·m load mutation is applied at 0.4 s, the present invention... q The shaft current response time is 25 ms, which is much faster than the traditional method of 120 ms. The settling time is shortened from 25 ms to 22 ms, and the transition period is reduced from 80 ms to 45 ms, indicating that the present invention can significantly improve the dynamic response speed. Figure 12 In this context, iq traditional represents the q-axis current of the traditional model, and iq improver represents the q-axis current of the improved model. Figure 13 These are schematic diagrams of the d-axis current waveforms for traditional and improved model predictive current control methods. Figure 13 In the model, `id traditional` represents the d-axis current of the traditional model, and `id improver` represents the d-axis current of the improved model. For example... Figure 14 and Figure 15 As shown, Figure 14 These are schematic diagrams of the x-axis current waveforms for traditional and improved model predictive current control methods. Figure 14 In this context, ix traditional represents the x-axis current of the traditional model, and ix improver represents the x-axis current of the improved model. Figure 15 These are schematic diagrams of the y-axis current waveforms for traditional and improved model predictive current control methods. Figure 15 In this invention, *iytraditional* represents the y-axis current of the traditional model, and *iyimprover* represents the y-axis current of the improved model; x shaft and y The harmonic current amplitudes of the shaft were reduced from ±1.72A and ±1.71A in the traditional method to approximately ±0.5A and ±0.45A, respectively, a reduction of over 70%, demonstrating that this invention can significantly reduce current fluctuations. By simplifying the vector control set, the number of voltage vectors that need to be traversed is greatly reduced, thereby improving the real-time performance of the algorithm and making it more suitable for embedded systems with limited computing resources, demonstrating that this invention can reduce computational complexity. The improved value function does not require the design of weighting factors, reducing the difficulty of tuning control parameters and improving the robustness and adaptability of the system, demonstrating that this invention can simplify parameter tuning. Figure 8 and Figure 9As shown in the comparison, the current waveform provided by the present invention is closer to an ideal sine wave, indicating a significant reduction in harmonic components, thereby improving the operating efficiency and performance of the motor, demonstrating that the present invention can improve the quality of the current waveform.

[0084] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. An improved model predictive current control method for a six-phase permanent magnet synchronous motor, characterized in that, Includes the following steps: S1: Obtain the current phase current and rotor position; S2: Based on the current phase current and rotor position, transform the stator current to the synchronous rotating coordinate system to obtain the current reference value; S3: Based on the current reference value, use the current prediction model to obtain the predicted current at the next moment; S4: Based on the current phase current and rotor position, use the speed loop proportional-integral controller to obtain... d - q Current referenced in a plane; S5: Based on the predicted current and d - q The current from the plane reference is used to obtain the candidate voltage vector using a simplified vector control set; S6: Calculate the value function corresponding to each candidate voltage vector, select the voltage vector with the smallest value function, and obtain the selected voltage vector; S7: Use the selected voltage vector to control a two-level six-phase voltage source inverter.

2. The improved model predictive current control method for a six-phase permanent magnet synchronous motor according to claim 1, characterized in that, The method for transforming the stator current to the synchronous rotating coordinate system is a space vector decoupling transformation and a Park transformation.

3. The improved model predictive current control method for a six-phase permanent magnet synchronous motor according to claim 1, characterized in that, The calculation formula for the current prediction model is as follows: in, , , and They represent the first Each time step d axis, q axis, x shaft and y Shaft stator current components; , , and They represent the first Each time step d axis, q axis, x shaft and y Shaft stator current components; This indicates the resistance of each phase winding of the stator; Indicates the switching cycle of the inverter; express d Shaft inductance; express q Shaft inductance; express x Shaft inductance; express y Shaft inductance; Indicates electric angular velocity; Indicates the first Each time step d Shaft-stator voltage components; Indicates the first Each time step q Shaft-stator voltage components; Indicates the first Each time step x Shaft-stator voltage components; Indicates the first Each time step y Shaft-stator voltage components; This refers to the magnetic flux generated by a permanent magnet.

4. The improved model predictive current control method for a six-phase permanent magnet synchronous motor according to claim 1, characterized in that, The selection criteria for the simplified vector control set are: excluding... x - y Vectors with harmonic plane amplitude > 0.3 are retained. α - β Vectors with a basic plane amplitude ≥ 0.4 and uniform distribution are used to ensure at least 3 effective vectors within a 120° electrical angle, while 2 zero vectors are reserved for current fine-tuning.

5. The improved model predictive current control method for a six-phase permanent magnet synchronous motor according to claim 1, characterized in that, The formula for calculating the value function is as follows: in, It is a value function; for d Reference current of the shaft; for q Reference current of the shaft; It is a nonlinear constraint function; This represents the maximum current value. Indicates constraints; These are the switching functions of the six bridge arms of the inverter. This indicates that the upper bridge arm is open. This indicates that the lower bridge arm is open; and Indicates the first and The switching function of phase A bridge arm at each time step; and Indicates the first and The B-phase bridge arm switching function at each time step; and Indicates the first and The switching function of the C-phase bridge arm at each time step; and Indicates the first and The switching function of the D-phase bridge arm at each time step; and Indicates the first and E-phase bridge arm switching function at each time step; and Indicates the first and The switching function of the F-phase bridge arm at each time step.

6. An improved model predictive current control system for a six-phase permanent magnet synchronous motor, characterized in that, Includes the following units: The signal acquisition unit is configured to acquire the phase current and rotor position at the current moment. The transformation unit is configured to transform the stator current to the synchronous rotating coordinate system based on the phase current and rotor position at the current moment, so as to obtain the current reference value. The current prediction model unit is configured to: obtain the predicted current at the next moment based on the current reference value using the current prediction model; The speed loop PI controller unit is configured to: obtain the current phase current and rotor position using a speed loop proportional-integral controller. d - q Planar reference current The vector control set unit is configured to: based on the predicted current and d - q The current from the plane reference is used to obtain the candidate voltage vector using a simplified vector control set; The value function unit is optimized by calculating the value function corresponding to each candidate voltage vector, selecting the voltage vector with the smallest value function, and obtaining the selected voltage vector. The six-phase voltage source inverter unit is configured to control a two-level six-phase voltage source inverter using the selected voltage vector.

7. The improved model predictive current control system for a six-phase permanent magnet synchronous motor according to claim 6, characterized in that, The method for transforming the stator current to the synchronous rotating coordinate system is a space vector decoupling transformation and a Park transformation.

8. The improved model predictive current control system for a six-phase permanent magnet synchronous motor according to claim 6, characterized in that, The calculation formula for the current prediction model is as follows: in, , , and They represent the first Each time step d axis, q axis, x shaft and y Shaft stator current components; , , and They represent the first Each time step d axis, q axis, x shaft and y Shaft stator current components; This indicates the resistance of each phase winding of the stator; Indicates the switching cycle of the inverter; express d Shaft inductance; express q Shaft inductance; express x Shaft inductance; express y Shaft inductance; Indicates electric angular velocity; Indicates the first Each time step d Shaft-stator voltage components; Indicates the first Each time step q Shaft-stator voltage components; Indicates the first Each time step x Shaft-stator voltage components; Indicates the first Each time step y Shaft-stator voltage components; This refers to the magnetic flux generated by a permanent magnet.

9. The improved model predictive current control system for a six-phase permanent magnet synchronous motor according to claim 6, characterized in that, The selection criteria for the simplified vector control set are: excluding... x - y Vectors with harmonic plane amplitude > 0.3 are retained. α - β Vectors with a basic plane amplitude ≥ 0.4 and uniform distribution are used to ensure at least 3 effective vectors within a 120° electrical angle, while 2 zero vectors are reserved for current fine-tuning.

10. The improved model predictive current control system for a six-phase permanent magnet synchronous motor according to claim 6, characterized in that, The formula for calculating the value function is as follows: in, It is a value function; for d Reference current of the shaft; for q Reference current of the shaft; It is a nonlinear constraint function; This represents the maximum current value. Indicates constraints; These are the switching functions of the six bridge arms of the inverter. This indicates that the upper bridge arm is open. This indicates that the lower bridge arm is open; and Indicates the first and The switching function of phase A bridge arm at each time step; and Indicates the first and The B-phase bridge arm switching function at each time step; and Indicates the first and The switching function of the C-phase bridge arm at each time step; and Indicates the first and The switching function of the D-phase bridge arm at each time step; and Indicates the first and E-phase bridge arm switching function at each time step; and Indicates the first and The switching function of the F-phase bridge arm at each time step.

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