Permanent magnet motor model predictive current control method based on current source inverter

Abstract

The application relates to the technical field of motor control, in particular to a permanent magnet motor model predictive current control method based on a current source type inverter. The method comprises the following steps: collecting the operation state quantity of a motor system, and performing Park transformation to obtain an operation measured value; according to the operation measured value, an alternating current side parallel filter capacitor branch model and a permanent magnet synchronous motor mathematical model are established, a unified discrete prediction model is constructed, and the inverter output current vector and the capacitor current of the next period are calculated; a capacitor current steady-state reference component and a capacitor current deviation component are constructed; a cost function is constructed, the output current vector with the minimum cost function is selected as the optimal control vector of the current control period, and an inverter switching driving signal is generated to drive the CSI operation. According to the application, the stator current tracking and alternating current side oscillation suppression are simultaneously considered under the unified prediction model framework, and compared with the traditional strategy, the dynamic response speed and the steady-state waveform quality can be better considered.

Description

Technical Field

[0001] This invention relates to the field of motor control technology, and in particular to a model predictive current control method for permanent magnet motors based on a current source inverter. Background Technology

[0002] Motor drive systems are core components in electric vehicles, marine propulsion, industrial compressors, and other fields. With the increasing demand for high power density, high reliability, and high efficiency electric drive systems, motor drive solutions based on current source inverters (CSI) are receiving growing attention. Compared to traditional voltage source inverters (VSI), CSI uses DC-side inductor energy storage, offering features such as continuous DC current and strong natural short-circuit protection. Simultaneously, its parallel filter capacitor on the AC side helps improve output waveform quality and reduce the rate of change of motor terminal voltage, thereby mitigating adverse effects on the motor insulation system.

[0003] However, several control challenges remain in practical applications of CSI-driven permanent magnet synchronous motor (PMSM) systems. First, the introduction of a parallel filter capacitor on the AC side of the CSI causes the inverter output current to be split between the motor branch and the capacitor branch, resulting in more pronounced coupling characteristics. Second, under certain parameter conditions, an oscillating element can easily form between the filter capacitor and the system's equivalent inductance, leading to LC oscillations on the AC side, which in turn affects the stator current waveform quality, dynamic response performance, and system stability. Existing CSI-PMSM control methods typically employ a multi-loop cascaded control structure consisting of speed, current, and voltage loops. While this approach is mature and widely used in engineering, it still has the following drawbacks: on the one hand, the multi-loop controller parameter tuning process is complex, and parameter coupling is strong; on the other hand, limited by the cascaded structure and control bandwidth, it is difficult to simultaneously achieve both rapid response and oscillation suppression capabilities under dynamic conditions. To improve dynamic performance, finite set model predictive control has been applied because it can directly utilize the system's discrete model to predict and optimize candidate control vectors online. However, existing model predictive control schemes for CSI-PMSM systems still have room for improvement. Some schemes primarily use stator current tracking error as the optimization objective, failing to effectively suppress AC-side LC oscillations; others, while incorporating capacitor branch current into the cost function, typically penalize the capacitor current amplitude directly. Since the capacitor current contains a steady-state component determined by the coordinate rotation coupling term in the synchronously rotating dq coordinate system, directly penalizing the capacitor current amplitude can easily suppress the normal components necessary for maintaining steady-state operation, resulting in incorrect steady-state penalty and leading to stator current tracking deviation, port voltage steady-state offset, or overall control performance degradation.

[0004] Therefore, a model predictive current control method is needed for a current source inverter-driven permanent magnet synchronous motor system. This method should ensure stator current tracking performance, effectively suppress AC side LC oscillations, and avoid steady-state performance degradation caused by unreasonable capacitor current penalty mechanisms, thereby improving the overall operating performance of the system under steady-state and dynamic conditions. Summary of the Invention

[0005] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a model predictive current control method for permanent magnet motors based on a current source inverter, which simultaneously considers stator current tracking and AC side oscillation suppression within a unified predictive model framework. Compared with traditional strategies, this method can better balance dynamic response speed and steady-state waveform quality.

[0006] This invention provides a model predictive current control method for permanent magnet motors based on a current source inverter, comprising the following steps:

[0007] S1: Collect the operating status data of the motor system, transform the operating status data into the synchronous rotating coordinate system using Park transformation, and obtain the actual operating values;

[0008] S2: Based on the measured operating values, establish the AC side parallel filter capacitor branch model and the permanent magnet synchronous motor mathematical model in the synchronous rotating coordinate system, and perform discretization processing to construct a unified discrete prediction model, and calculate the output current vector and capacitor current of the next cycle.

[0009] S3: Construct a steady-state reference component for the capacitor current, and define the difference between the steady-state reference component and the capacitor current as the capacitor current deviation component;

[0010] S4: Construct a cost function, calculate the cost function based on the capacitor current deviation component, select the output current vector, and select the output current vector with the smallest cost function as the optimal control vector for the current control cycle;

[0011] S5: Generate inverter switching drive signals using the optimal control vector to drive CSI operation;

[0012] S6: Repeat steps S1 to S5 until the permanent magnet motor model predicts the current control.

[0013] According to the present invention, a model predictive current control method for permanent magnet motors based on a current source inverter is provided, wherein the operating state quantities include: three-phase stator current of the motor, motor port voltage, rotor position angle, electric angular velocity and DC bus current.

[0014] According to the present invention, a model-based predictive current control method for permanent magnet motors based on a current source inverter is provided, wherein the AC side parallel filter capacitor branch model is as follows:

[0015]

[0016] in, The components of the capacitor current vector on the d-axis. Let C be the q-component of the capacitor current vector, and C be the parallel filter capacitor. For extreme logarithms, The component of the motor port voltage on the d-axis, This represents the q-axis component of the motor port voltage. It represents the electric angular velocity.

[0017] According to the present invention, a model-based predictive current control method for permanent magnet synchronous motors based on a current source inverter is provided, wherein the mathematical model of the permanent magnet synchronous motor is:

[0018]

[0019] in, For the stator resistance of the motor, For the stator inductance of the motor, It is a permanent magnet flux linkage. The components of the stator current vector on the d-axis are... This represents the component of the stator current vector on the q-axis.

[0020] According to the present invention, a model-based predictive current control method for permanent magnet motors based on a current source inverter is provided, wherein the unified discrete prediction model formula is:

[0021]

[0022]

[0023] in, This represents the predicted component of the capacitor voltage on the d-axis. This represents the d-axis component of the actual capacitor voltage. This represents the d-axis component of the inverter output current vector prediction. The components of the predicted stator current vector on the d-axis. This represents the predicted value of the capacitor voltage as a component on the q-axis. This represents the q-axis component of the actual capacitor voltage. This represents the q-axis component of the inverter output current vector prediction. The components of the predicted stator current vector on the q-axis. This represents the q-axis component of the inverter output voltage prediction. This represents the d-axis component of the inverter output voltage prediction. The components of the actual value of the stator current vector on the d-axis. This represents the q-axis component of the stator inductance. The component of the stator inductance on the d-axis. The components of the actual stator current vector on the q-axis. The period length is denoted as .

[0024] According to the present invention, a model predictive current control method for permanent magnet motors based on a current source inverter is provided, wherein step S3 includes:

[0025] S31: The steady-state reference component of the capacitor current The construction method is as follows:

[0026]

[0027] in, This is the actual value of the electric angular velocity. The predicted value of the voltage vector is represented by the q-axis component. The predicted value of the voltage vector is represented by the component on the d-axis.

[0028] S32: The capacitor current deviation component The calculation formula is:

[0029]

[0030]

[0031] in, This is the predicted value of the capacitor current vector. This is the predicted value of the stator current vector. This is the predicted value of the inverter output current vector.

[0032] According to the present invention, a method for predicting the current control of a permanent magnet motor model based on a current source inverter provides the following formula for calculating the predicted value of the inverter output current vector:

[0033]

[0034]

[0035] in, This represents the actual value of the stator current vector. This represents the actual value of the stator voltage vector. Let be the first parameter matrix. The second parameter matrix, The third parameter matrix, The period length is denoted as .

[0036] According to the present invention, a model predictive current control method for permanent magnet motors based on a current source inverter is provided, and step S4 is as follows:

[0037] S41: Based on the deadbeat control principle, the predicted value of the motor stator current at the next moment is set to equal the reference value:

[0038] ;

[0039] S42: Calculate the inverter's expected output current vector at the next moment based on the unified discrete prediction model:

[0040]

[0041]

[0042] in, The output current vector is calculated without time-lapse. Components along the d-axis, The output current vector is calculated without time-lapse. Components on the q-axis, For the fourth parameter matrix, It is the identity matrix. x ( k ) represents the state variable of the system at this moment;

[0043] S43: If the calculated expected output current vector size exceeds the DC bus current value, the vector size needs to be constrained within the hexagonal linear modulation region by a scaling strategy. If it does not exceed the value, proceed to step S44.

[0044] S44: Based on the hexagonal linear modulation region, select the neighborhood of the corresponding sector to construct a finite number of adjacent candidate current vectors to form a candidate control set.

[0045] S45: Input the candidate current vectors in the candidate control set into the cost function to calculate the vector with the minimum cost as the optimal control vector for the current control cycle.

[0046] According to the present invention, a model predictive current control method for permanent magnet motors based on a current source inverter is provided, wherein the cost function The calculation formula is:

[0047]

[0048] in, To obtain the norm, The stator current is given a value. These are the weighting coefficients.

[0049] The above-described one or more technical solutions in the embodiments of the present invention have at least the following technical effects:

[0050] 1. The model predictive current control method proposed in this invention for electric drive systems of current source inverters can better balance dynamic response speed and steady-state waveform quality by simultaneously considering stator current tracking and AC side oscillation suppression under a unified predictive model framework, compared with traditional multi-closed-loop control strategies.

[0051] 2. This invention introduces a capacitor current deviation component suppression term into the cost function and performs consistency correction based on the steady-state component of the capacitor current in the synchronous rotating coordinate system. This avoids the steady-state mis-penalty problem caused by directly penalizing the capacitor current amplitude, effectively reduces stator current tracking deviation and port voltage steady-state offset, and improves the operating stability and control accuracy of the CSI-PMSM system under different operating conditions.

[0052] 3. This invention reduces the amount of online computation while ensuring control performance through candidate vector pre-selection and finite enumeration mechanism, making it easier to implement real-time applications on digital controller platforms.

[0053] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0055] Figure 1 The flowchart shows the predictive current control method for a permanent magnet motor model based on a current source inverter.

[0056] Figure 2 The graph shows a comparison of the steady-state performance waveforms under the three-closed-loop control strategy and the strategy of this invention.

[0057] Figure 3 The waveforms show the dynamic tracking performance under the three-closed-loop control strategy and the strategy of this invention.

[0058] Figure 4 Screening diagram for the finite control set of the current strategy.

[0059] Figure 5 This is the topology of a current source inverter system. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0061] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0062] The following is combined with Figures 1 to 5 This invention is described.

[0063] like Figure 1 As shown, this invention provides a model predictive current control method for permanent magnet motors based on a current source inverter, comprising the following steps:

[0064] S1: Collect the operating status data of the motor system, transform the operating status data into the synchronous rotating coordinate system using Park transformation, and obtain the actual operating values;

[0065] S2: Based on the measured operating values, establish the AC side parallel filter capacitor branch model and the permanent magnet synchronous motor mathematical model in the synchronous rotating coordinate system, and perform discretization processing to construct a unified discrete prediction model, and calculate the output current vector and capacitor current of the next cycle.

[0066] S3: Construct a steady-state reference component for the capacitor current, and define the difference between the steady-state reference component and the capacitor current as the capacitor current deviation component;

[0067] S4: Construct a cost function, calculate the cost function based on the capacitor current deviation component, select the output current vector, and select the output current vector with the smallest cost function as the optimal control vector for the current control cycle;

[0068] S5: Generate inverter switching drive signals using the optimal control vector to drive CSI operation;

[0069] S6: Repeat steps S1 to S5 until the permanent magnet motor model predicts the current control.

[0070] like Figure 5As shown, the controlled object of the CSI-PMSM system includes not only the motor stator current but is also significantly affected by the dynamics of the parallel capacitor branch. To provide a theoretical basis for subsequent predictive controller design, it is necessary to establish a comprehensive mathematical model of the system, including the inverter output current, filter capacitor voltage, and motor stator current. In the CSI-PMSM system, the zero filter capacitor current is not a condition for steady-state existence in the synchronous rotating coordinate system. If steady-state is assumed in the construction of the control objective or cost function... = =0, which will be inconsistent with the actual steady-state physical characteristics of the system, thus leading to a bias in the evaluation target. In particular, if the amplitude of the filter capacitor current (or its square norm) is directly used as the oscillation suppression term, this term will penalize both the steady-state component and the oscillation component of the capacitor current, which may cause steady-state mis-penalization problems, manifested as an increase in stator current tracking deviation or a shift in the steady-state operating point of the port voltage.

[0071] In summary, in the synchronously rotating dq coordinate system, the filter capacitor current in the CSI-PMSM system typically contains a non-zero steady-state component in steady state. Therefore, directly using the filter capacitor current as the evaluation quantity for oscillation suppression will lead to inconsistencies between the predicted target and the actual steady-state physical characteristics of the system. To ensure consistency between the control target and the steady-state physical process, this paper introduces a steady-state reference component and its deviation component of the capacitor current, using the latter as the basis for dynamic evaluation on the AC side.

[0072] Specifically, the operating status quantities include: motor three-phase stator current, motor port voltage, rotor position angle, electrical angular velocity, and DC bus current.

[0073] Specifically, the AC-side parallel filter capacitor branch model is as follows:

[0074]

[0075] in, The components of the capacitor current vector on the d-axis. Let C be the q-component of the capacitor current vector, and C be the parallel filter capacitor. For extreme logarithms, The component of the motor port voltage on the d-axis, This represents the q-axis component of the motor port voltage. It represents the electric angular velocity.

[0076] Specifically, the mathematical model of the permanent magnet synchronous motor is as follows:

[0077]

[0078] in, For the stator resistance of the motor, For the stator inductance of the motor, It is a permanent magnet flux linkage. The components of the stator current vector on the d-axis are... This represents the component of the stator current vector on the q-axis.

[0079] Specifically, the formula for the unified discrete prediction model is:

[0080]

[0081]

[0082] in, This represents the predicted component of the capacitor voltage on the d-axis. This represents the d-axis component of the actual capacitor voltage. This represents the d-axis component of the inverter output current vector prediction. The components of the predicted stator current vector on the d-axis. This represents the predicted value of the capacitor voltage as a component on the q-axis. This represents the q-axis component of the inverter output current vector prediction. This represents the q-axis component of the actual capacitor voltage. The components of the predicted stator current vector on the q-axis. This represents the predicted component of the capacitor voltage on the d-axis. This represents the q-axis component of the inverter output voltage prediction. This represents the d-axis component of the inverter output voltage prediction. The components of the actual value of the stator current vector on the d-axis. This represents the q-axis component of the stator inductance. The component of the stator inductance on the d-axis. This represents the component of the actual value of the stator current vector on the q-axis.

[0083] When the system reaches steady-state operation in the synchronously rotating dq coordinate system, the filter capacitor current is usually not zero, but should approach the steady-state reference component determined by the steady-state conditions of the port voltage.

[0084] Therefore, if directly using If the square norm of the capacitor current is used as a penalty term in the cost function, it will simultaneously suppress both the steady-state and dynamic components of the capacitor current, leading to a discrepancy between the control objective and the actual steady-state physical characteristics of the system. Therefore, this paper does not directly use the filter capacitor current itself, but instead uses its deviation relative to the steady-state reference component as the dynamic evaluation index for the AC side.

[0085] Specifically, step S3 includes:

[0086] S31: The steady-state reference component of the capacitor current The construction method is as follows:

[0087]

[0088] in, This is the actual value of the electric angular velocity. The predicted value of the voltage vector is represented by the q-axis component. The predicted value of the voltage vector is represented by the component on the d-axis.

[0089] S32: The capacitor current deviation component The calculation formula is:

[0090]

[0091]

[0092] in, This is the predicted value of the capacitor current vector. This is the predicted value of the stator current vector. This is the predicted value of the inverter output current vector.

[0093] Specifically, the formula for calculating the predicted value of the inverter output current vector is as follows:

[0094]

[0095]

[0096] in, This represents the actual value of the stator current vector. This represents the actual value of the stator voltage vector. Let be the first parameter matrix. The second parameter matrix, The third parameter matrix, The period length is denoted as .

[0097] Specifically, step S4 is as follows:

[0098] S41: Based on the deadbeat control principle, the predicted value of the motor stator current at the next moment is set to equal the reference value:

[0099]

[0100] S42: Calculate the inverter's expected output current vector at the next moment based on the unified discrete prediction model:

[0101]

[0102]

[0103]

[0104] in, The output current vector is calculated without time-lapse. Components along the d-axis, The output current vector is calculated without time-lapse. Components on the q-axis, For the fourth parameter matrix, It is the identity matrix. Let this be the state variable of the system at this moment. The d-axis component of the actual value of the stator current vector. The q-axis component of the actual value of the stator current vector. The actual value of the stator voltage vector is represented by its d-axis component. The actual value of the stator voltage vector is the q-axis component.

[0105] S43: If the calculated magnitude of the desired output current vector exceeds the DC bus current value, the vector magnitude needs to be constrained within the hexagonal linear modulation region using a scaling strategy. If it does not exceed the limit, proceed to step S44. The specific scaling method is as follows:

[0106]

[0107] in, To obtain the output current vector after scaling without time-lapse calculation Components along the d-axis, To obtain the output current vector after scaling without time-lapse calculation Components on the q-axis, This represents the DC bus current.

[0108] S44: Based on the hexagonal linear modulation region, select the neighborhood of the corresponding sector to construct a finite number of adjacent candidate current vectors to form a candidate control set.

[0109] Specifically, such as Figure 4 As shown, the αβ coordinate system is divided into several sectors at equal angles. In this embodiment of the invention, it is divided into six sectors, according to the red vector. The sector in question is selected from several candidate current vectors marked in blue. In this embodiment, three vectors are selected to form the current vectors belonging to the candidate set control.

[0110] S45: Input the candidate current vectors in the candidate control set into the cost function to calculate the vector with the minimum cost as the optimal control vector for the current control cycle.

[0111] Specifically, the cost function The calculation formula is:

[0112]

[0113] in, To obtain the norm, The stator current is given a value. These are the weighting coefficients.

[0114] The first item is the motor stator current tracking item, used to ensure the electromagnetic torque and field weakening control requirements during normal motor operation; the second item is the capacitor current ripple suppression item, which, through... The penalty term implements predictive active damping for the LC oscillation component; λ is a weighting coefficient used to balance current tracking performance and oscillation suppression strength.

[0115] The selection of the weighting coefficient should reflect the coordination between external tracking performance and internal dynamic suppression. A suitable increase in λ helps to reduce AC-side oscillations and improve port voltage fluctuations. However, if λ is too large, it may weaken the current tracking capability and even affect the system's dynamic response. Therefore, in practical design, priority should be given to ensuring the dominant role of stator current tracking performance, and then λ should be adjusted in combination with system parameters and operating conditions to balance current control accuracy and system steady-state quality.

[0116] At this point, the predictive control objective for the steady-state characteristics of the CSI-PMSM system has been constructed. Furthermore, to reduce the online computational burden caused by the traditional finite control set model predictive control's iterative traversal of all candidate current vectors, a local finite candidate optimization strategy suitable for real-time implementation needs to be designed based on the aforementioned predictive model and cost function.

[0117] Specifically, Figure 2 and Figure 3 These are comparative images of the present invention and the prior art. (Example) Figure 2 As shown, Figure 2 The graphs show a comparison of the steady-state performance waveforms under the three-closed-loop control strategy and the strategy of this invention. Figure 2 In the middle (a), the d-axis current is the three-closed-loop control strategy. Figure 2 In the middle (c), the q-axis current is the three-loop control strategy. Figure 2 In the middle (e), the three-phase currents of the three-closed-loop control strategy are shown. Figure 2 In (b), the current along the d-axis of the strategy of this invention is represented. Figure 2 In the middle (d), the q-axis current of the strategy of this invention is represented. Figure 2 In the figure (f), the three-phase current of the strategy of the present invention is shown. It can be clearly seen that the d-axis current waveforms are smooth and the three-phase current is a standard sine wave with almost no distortion, and the current quality is excellent. Figure 2 In the middle (g), the A-relative fundamental amplitude value of the three-phase current under the three-closed-loop control strategy is shown. Figure 2 The value of the A-relative fundamental amplitude of the three-phase current in the present invention (h) shows that the total harmonic distortion (THD) decreases from 18.15% to 2.15%, the rectification effect is significantly improved, and the harmonics are effectively suppressed.

[0118] like Figure 3 As shown, Figure 3 The waveforms show the dynamic tracking performance under the three-closed-loop control strategy and the strategy of this invention. Figure 3 In the middle (a), the dynamic tracking performance waveform under the three-closed-loop control strategy is shown. The slow torque response, large overshoot, and high steady-state ripple will lead to motor vibration, high noise, and poor accuracy. Figure 3 Figure (b) shows the dynamic tracking performance waveform under the strategy of this invention. It exhibits fast torque response, no significant overshoot, and minimal steady-state ripple, demonstrating superior dynamic tracking performance and stability. For load torque, It is electromagnetic torque.

[0119] As demonstrated by the above steps, this invention proposes a control method that constructs a unified discrete prediction model including the AC-side parallel filter capacitor branch and the permanent magnet synchronous motor branch. By introducing a capacitor current deviation component suppression term into the comprehensive cost function, predictive active damping of AC-side LC oscillations is achieved. This method avoids the steady-state mis-penalization problem caused by the traditional direct penalty of capacitor current amplitude, and can balance stator current tracking performance, steady-state waveform quality, and system operational stability under different operating conditions.

[0120] The control method proposed in this invention, by simultaneously considering stator current tracking and AC side oscillation suppression within a unified prediction model framework, can better balance dynamic response speed and steady-state waveform quality compared to traditional multi-closed-loop control strategies.

[0121] The control method proposed in this invention introduces a capacitor current deviation component suppression term into the cost function and performs consistency correction based on the steady-state component of the capacitor current in the synchronous rotating coordinate system. This avoids the steady-state mis-penalty problem caused by directly penalizing the capacitor current amplitude, effectively reduces stator current tracking deviation and port voltage steady-state offset, and improves the operating stability and control accuracy of the CSI-PMSM system under different operating conditions.

[0122] This invention reduces the amount of online computation while ensuring control performance through candidate vector pre-selection and finite enumeration mechanisms, making it easier to implement real-time applications on digital controller platforms.

[0123] Although the embodiments and drawings of the present invention have been disclosed for illustrative purposes, those skilled in the art will understand that various substitutions, variations and modifications are possible without departing from the spirit and scope of the present invention and the appended claims. Therefore, the scope of the present invention is not limited to the contents disclosed in the embodiments and drawings.

[0124] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0125] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0127] Furthermore, although the operation of the methods of this disclosure is described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Rather, the steps depicted in the flowcharts may be performed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps. It should also be noted that the features and functions of two or more devices according to this disclosure may be embodied in one device. Conversely, the features and functions of one device described above may be further divided and embodied by multiple devices.

[0128] While this disclosure has been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the specific embodiments disclosed. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A model predictive current control method for permanent magnet motors based on a current source inverter, characterized in that, Includes the following steps: S1: Collect the operating status data of the motor system, transform the operating status data into the synchronous rotating coordinate system using Park transformation, and obtain the actual operating values; S2: Based on the measured operating values, establish the AC side parallel filter capacitor branch model and the permanent magnet synchronous motor mathematical model in the synchronous rotating coordinate system, and perform discretization processing to construct a unified discrete prediction model, and calculate the output current vector and capacitor current of the next cycle. S3: Construct a steady-state reference component for the capacitor current, and define the difference between the steady-state reference component and the capacitor current as the capacitor current deviation component; S4: Construct a cost function, calculate the cost function based on the capacitor current deviation component, select the output current vector, and select the output current vector with the smallest cost function as the optimal control vector for the current control cycle; S5: Generate inverter switching drive signals using the optimal control vector to drive CSI operation; S6: Repeat steps S1 to S5 until the permanent magnet motor model predicts the current control.

2. The method for predictive current control of a permanent magnet motor model based on a current source inverter according to claim 1, characterized in that, The operating status quantities include: motor three-phase stator current, motor port voltage, rotor position angle, electric angular velocity, and DC bus current.

3. The method for predictive current control of a permanent magnet motor model based on a current source inverter according to claim 1, characterized in that, The AC-side parallel filter capacitor branch model is as follows: in, The components of the capacitor current vector on the d-axis. Let C be the q-component of the capacitor current vector, and C be the parallel filter capacitor. For extreme logarithms, The component of the motor port voltage on the d-axis, This represents the q-axis component of the motor port voltage. It represents the electric angular velocity.

4. The method for predictive current control of a permanent magnet motor model based on a current source inverter according to claim 3, characterized in that, The mathematical model of the permanent magnet synchronous motor is as follows: in, For the stator resistance of the motor, For the stator inductance of the motor, It is a permanent magnet flux chain. The components of the stator current vector on the d-axis are... This represents the component of the stator current vector on the q-axis.

5. The method for predictive current control of a permanent magnet motor model based on a current source inverter according to claim 4, characterized in that, The formula for the unified discrete prediction model is: in, This represents the predicted component of the capacitor voltage on the d-axis. This represents the d-axis component of the actual capacitor voltage. This represents the d-axis component of the inverter output current vector prediction. The components of the predicted stator current vector on the d-axis. This represents the predicted value of the capacitor voltage as a component on the q-axis. This represents the q-axis component of the actual capacitor voltage. This represents the q-axis component of the inverter output current vector prediction. The components of the predicted stator current vector on the q-axis. This represents the q-axis component of the inverter output voltage prediction. This represents the d-axis component of the inverter output voltage prediction. The components of the actual value of the stator current vector on the d-axis. This represents the q-axis component of the stator inductance. The component of the stator inductance on the d-axis. The components of the actual stator current vector on the q-axis. The period length is denoted as .

6. The method for predictive current control of a permanent magnet motor model based on a current source inverter according to claim 5, characterized in that, Step S3 includes: S31: The steady-state reference component of the capacitor current The construction method is as follows: in, This is the actual value of the electric angular velocity. The predicted value of the voltage vector is represented by the q-axis component. The predicted value of the voltage vector is represented by the component on the d-axis. S32: The capacitor current deviation component The calculation formula is: in, This is the predicted value of the capacitor current vector. This is the predicted value of the stator current vector. This is the predicted value of the inverter output current vector.

7. The method for predictive current control of a permanent magnet motor model based on a current source inverter according to claim 6, characterized in that, The formula for calculating the predicted value of the inverter output current vector is as follows: in, This represents the actual value of the stator current vector. This represents the actual value of the stator voltage vector. Let be the first parameter matrix. The second parameter matrix, The third parameter matrix, The period length is denoted as .

8. The method for predictive current control of a permanent magnet motor model based on a current source inverter according to claim 7, characterized in that, Step S4 is as follows: S41: Based on the deadbeat control principle, the predicted value of the motor stator current at the next moment is set to equal the reference value: ； S42: Calculate the inverter's expected output current vector at the next moment based on the unified discrete prediction model: in, The output current vector is calculated without time-lapse. Components along the d-axis, The output current vector is calculated without time-lapse. Components on the q-axis, For the fourth parameter matrix, It is the identity matrix. x ( k ) represents the state variable of the system at this moment; S43: If the calculated expected output current vector size exceeds the DC bus current value, the vector size needs to be constrained within the hexagonal linear modulation region by using a scaling strategy. If it does not exceed the value, proceed to step S44. S44: Based on the hexagonal linear modulation region, select the neighborhood of the corresponding sector to construct a finite number of adjacent candidate current vectors to form a candidate control set. S45: Input the candidate current vectors in the candidate control set into the cost function to calculate the vector with the minimum cost as the optimal control vector for the current control cycle.

9. The method for predictive current control of a permanent magnet motor model based on a current source inverter according to claim 8, characterized in that, The cost function The calculation formula is: in, To obtain the norm, The stator current is given a value. These are the weighting coefficients.

Images