4L-NNPC inverter control method and device based on improved finite control set model

Abstract

This invention provides a control method and apparatus for a 4L-NNPC inverter based on an improved finite control set model. The method includes: real-time acquisition of the current three-phase grid voltage, current flying capacitor voltage, and current output three-phase current; calculation of the static reference current and a preliminary evaluation function; determination of a candidate switch state set through an output level screening mechanism, combining the preliminary evaluation function and the static reference current; for each candidate switch state, prediction of the corresponding state flying capacitor voltage and state output three-phase current at the next moment based on the current output three-phase current; calculation of the current tracking cost function and the balancing flying capacitor voltage cost function using a multi-objective cost function based on sliding mode control theory, generating an overall cost function; and selection of the candidate switch state that minimizes the overall cost function as the optimal control output for the 4L-NNPC inverter control. This invention significantly reduces computational complexity while improving system dynamic performance and steady-state accuracy.

Description

Technical Field

[0001] This invention relates to the field of power electronic converter control technology, and in particular to a control method and device for a 4L-NNPC inverter based on an improved finite control set model. Background Technology

[0002] Multilevel inverters, as key equipment for medium- and high-voltage high-power power conversion, have significant advantages in reducing harmonic distortion and switching losses in fields such as new energy power generation grid connection and industrial motor drive. However, with the increase in the number of levels, traditional finite control set model predictive control strategies face the problem of an explosive growth in switching state combinations, leading to a sharp increase in computational burden. The 4L-NNPC (Four-Level Neutral-Point-Clamped with Flying–Capacitor) inverter, with up to 218 effective switching states, causes the single control cycle time of traditional methods to exceed 70 microseconds, failing to meet high-frequency control requirements. This results in system dynamic response lag, excessive output current harmonic distortion rate, and flying capacitor voltage imbalance, severely restricting the application of multilevel inverters in high-precision grid connection scenarios.

[0003] Currently, methods to alleviate computational pressure typically involve simplifying prediction models or limiting the state search range, but this sacrifices control accuracy and dynamic performance; while relying on high-performance processors to forcibly accelerate computation significantly increases system costs. Existing technologies consistently struggle to balance the triple objectives of real-time performance, control accuracy, and economy, and are prone to instability risks under transient conditions such as sudden changes in grid voltage. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, this invention provides a 4L-NNPC inverter control method and device based on an improved finite control set model, which significantly reduces computational complexity while improving system dynamic performance and steady-state accuracy.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] In a first aspect, the present invention provides a control method for a 4L-NNPC inverter based on an improved finite control set model, comprising:

[0007] Step S1: Real-time acquisition of current three-phase grid voltage, current flying capacitor voltage, and current output three-phase current;

[0008] Step S2: Using a simplified prediction model, obtain the stationary reference current in the stationary coordinate system at the next moment based on the current three-phase voltage of the power grid, and calculate the preliminary evaluation function of the flying capacitor voltage based on the current flying capacitor voltage.

[0009] Step S3: Combining the preliminary evaluation function and the static reference current, determine the set of candidate switch states through the output level screening mechanism;

[0010] Step S4: For each candidate switch state in the candidate switch state set, predict the state fly-through capacitor voltage and state output three-phase current at the next moment based on the current output three-phase current.

[0011] Step S5: Using a multi-objective cost function based on sliding mode control theory, with the static reference current as the reference, and combining the state flying capacitor voltage and the state output three-phase current, the current tracking cost function and the balanced flying capacitor voltage cost function are calculated to generate the overall cost function.

[0012] Step S6: Select the candidate switch state that minimizes the overall cost function as the optimal control output for the 4L-NNPC inverter control.

[0013] The beneficial effects of this invention are as follows: by combining a simplified prediction model and an output level filtering mechanism, the total number of switching states is rapidly reduced; at the same time, the dynamic performance and steady-state accuracy of the system are improved by using a multi-objective cost function based on sliding mode control theory, thereby significantly reducing computational complexity while improving the dynamic performance and steady-state accuracy of the system.

[0014] Optionally, the expression for the overall cost function in step S5 is:

[0015] ;

[0016] ;

[0017] ;

[0018] In the formula, g is the total cost function, g i Let g be the current tracking cost function, λ be the weighting coefficient, and g be the weighting coefficient. c To balance the cost function of the flying capacitor voltage, a, b, and c are three phases, i x The output three-phase current is i. xref As the static reference current, v xn e represents the output voltage corresponding to the candidate switch state. x V represents the current three-phase voltage of the power grid. cx1 and V cx2 The two states of the flying capacitor voltage of the 4L-NNPC inverter.

[0019] Optionally, step S3 includes:

[0020] Using the static reference current as the target, select the switching states whose actual output current is close to the static reference current from all switching states as the first set of switching states;

[0021] Based on the preliminary evaluation function, the switch states in which the capacitor voltage deviation affected by the charging and discharging of the flying capacitor converges toward the reference value are taken as the second set of switch states.

[0022] The intersection of the first set of switch states and the second set of switch states is used to obtain the candidate set of switch states.

[0023] Optionally, the expression for filtering based on the static reference current in step S3 is:

[0024] ;

[0025] In the formula, i xref (k+1) is the resting reference current at the next moment, T s For the control cycle, L is the filter inductance, and V... x (k) represents the effective voltage output of phase x of the inverter at the current time k, e x (k) represents the current three-phase voltage of the power grid, R is the filter resistor, and i x (k) represents the current output three-phase current.

[0026] Optionally, the expression for filtering based on the preliminary evaluation function in step S3 is:

[0027] ;

[0028] In the formula, L X Let L3 and L be the set of candidate switch states. 2A L 2B L 1A L 1B L0 is the output level, V dc V is the DC bus voltage. x This is the effective voltage output of phase x of the inverter.

[0029] Optionally, step S2 includes:

[0030] Step S21: The phase-locked loop tracks and obtains the grid voltage phase angle based on the current grid three-phase voltage, and calculates the rotating reference current in the rotating coordinate system based on the grid voltage phase angle and the given reference current;

[0031] Step S22: Using a simplified prediction model, predict the reference current in the rotating coordinate system at the next moment based on the rotating reference current, and transform it into the stationary reference current in the stationary coordinate system.

[0032] Step S23: Predict the global flying capacitor voltage at the next moment and compare it with the reference value of the flying capacitor voltage to calculate the preliminary evaluation function of the global flying capacitor voltage.

[0033] Optionally, the simplified prediction model construction expression in step S2 is:

[0034] ;

[0035] In the formula, σ x For current-controlled sliding surfaces, σ x ' is the derivative of the current-controlled sliding mode surface, i x 'i represents the current output three-phase current.' xref ' is the rotating reference current, v xn ' represents the output voltage corresponding to the current switching state, e x R is the current three-phase voltage of the power grid. x For the filter resistor, L x This is a filter inductor.

[0036] In a second aspect, the present invention provides a 4L-NNPC inverter control device based on an improved finite control set model, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the 4L-NNPC inverter control method based on the improved finite control set model of the first aspect.

[0037] The technical effects of the 4L-NNPC inverter control device based on the improved finite control set model provided in the second aspect are described in the relevant description of the 4L-NNPC inverter control method based on the improved finite control set model provided in the first aspect. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the main flow of the 4L-NNPC inverter control method based on the improved finite control set model according to an embodiment of the present invention.

[0039] Figure 2 This is a topological schematic diagram of the improved finite control set model involved in the embodiments of the present invention.

[0040] Figure 3 This is a schematic diagram of the overall process of the 4L-NNPC inverter control method based on the improved finite control set model involved in the embodiments of the present invention.

[0041] Figure 4 This is a waveform diagram of the output current involved in an embodiment of the present invention.

[0042] Figure 5This is a THD diagram of the output current involved in an embodiment of the present invention.

[0043] Figure 6 This is a diagram showing the voltage variation of the flying capacitor in an embodiment of the present invention.

[0044] Figure 7 This is a comparison chart of control calculation time involved in an embodiment of the present invention.

[0045] Figure 8 This is a schematic diagram of the structure of the 4L-NNPC inverter control device based on the improved finite control set model according to an embodiment of the present invention.

[0046] Explanation of reference numerals in the attached figures:

[0047] 1: A control device for a 4L-NNPC inverter based on an improved finite control set model;

[0048] 2: Processor;

[0049] 3: Memory. Detailed Implementation

[0050] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present invention can be understood more clearly and thoroughly, and that the scope of the present invention can be fully conveyed to those skilled in the art.

[0051] Example 1

[0052] In existing technologies, the control methods for 4L-NNPC inverters consistently struggle to simultaneously achieve the triple objectives of real-time performance, control accuracy, and economy, and are prone to instability risks under transient conditions such as sudden changes in grid voltage. This embodiment addresses this by reconstructing the cost function using sliding mode control theory, combined with a simplified prediction model and a level filtering mechanism, significantly reducing computational complexity while improving system dynamic performance and steady-state accuracy. Details are discussed below.

[0053] Please refer to Figures 1 to 7 A control method for 4L-NNPC inverters based on an improved finite control set model includes:

[0054] Step S1: Real-time acquisition of the current three-phase voltage of the power grid, the current voltage of the flying capacitor, and the current output three-phase current.

[0055] Step S2: Using a simplified prediction model, obtain the static reference current in the static coordinate system at the next moment based on the current three-phase voltage of the power grid, and calculate the preliminary evaluation function of the flying capacitor voltage based on the current flying capacitor voltage.

[0056] In this embodiment, step S2 includes:

[0057] Step S21: The phase-locked loop tracks and obtains the grid voltage phase angle based on the current three-phase grid voltage, and calculates the rotating reference current in the rotating coordinate system based on the grid voltage phase angle and the given reference current.

[0058] like Figure 2 and Figure 3 As shown, in step S1, the current three-phase voltage e of the power grid is collected in real time. abc (k) Current flying capacitor voltage V cx (k) and the current output three-phase current i abc (k), based on the current three-phase voltage e of the power grid by the phase-locked loop. abc (k) is used to track and obtain the grid voltage phase angle θ, combined with a given reference current I. ref Calculate the rotating reference current i in the rotating coordinate system, i.e., the αβ coordinate system. αβref (k).

[0059] Step S22: Using a simplified prediction model, predict the reference current in the rotating coordinate system at the next moment based on the rotating reference current, and transform it into the stationary reference current in the stationary coordinate system.

[0060] In this embodiment, the simplified prediction model construction expression in step S22 is:

[0061] ;

[0062] In the formula, σ x For current-controlled sliding surfaces, σ x ' is the derivative of the current-controlled sliding mode surface, i x 'i represents the current output three-phase current.' xref ' is the rotating reference current, v xn ' represents the output voltage corresponding to the current switching state, e x R is the current three-phase voltage of the power grid. x For the filter resistor, L x This is a filter inductor.

[0063] Therefore, this embodiment first defines a sliding surface based on the rotating reference current and the current actual current to reflect the deviation between the two; then, combining circuit parameters and real-time acquired voltage data, it calculates the derivative of the sliding surface to reflect the trend of deviation change; and then, based on this trend, it predicts the rotating reference current i at the next moment. αβref (k+1), and finally, through coordinate transformation, i.e., from the αβ coordinate system to the abc coordinate system, it is transformed into the stationary reference current i. abcref (k) provides a current target for subsequent screening.

[0064] Step S23: Predict the global flying capacitor voltage at the next moment and compare it with the reference value of the flying capacitor voltage to calculate the preliminary evaluation function of the global flying capacitor voltage.

[0065] In this embodiment, based on the difference between the global flying capacitor voltage and the reference value of the flying capacitor voltage at the next moment, a preliminary evaluation function is constructed and calculated to measure the deviation and convergence trend of the flying capacitor voltage. This provides a basis for subsequent screening of switching states that can make the voltage converge toward the reference value, so as to achieve balanced control of the flying capacitor voltage.

[0066] Step S3: Combining the preliminary evaluation function and the static reference current, determine the set of candidate switch states through the output level screening mechanism.

[0067] In this embodiment, step S3 includes:

[0068] Step S31: Using the static reference current as the target, select the switching states from all switching states whose actual output current is close to the static reference current as the first set of switching states.

[0069] In this embodiment, the expression for filtering based on the static reference current in step S31 is:

[0070] ;

[0071] In the formula, i xref (k+1) is the resting reference current at the next moment, T s For the control cycle, L is the filter inductance, and V... x (k) represents the effective voltage output of phase x of the inverter at the current time k, e x (k) represents the current three-phase voltage of the power grid, R is the filter resistor, and i x (k) represents the current output three-phase current.

[0072] In this embodiment, step S31 compares the actual output current change trend corresponding to the full-scale switching state with the predicted current i. αβref (k+1) comparison, filtering out those whose actual output current can approximate i xref The switching states of (k+1) form the first set of switching states to ensure current tracking accuracy.

[0073] Step S32: Based on the preliminary evaluation function, select the switch states in which the capacitor voltage deviation affected by the charging and discharging of the flying capacitor converges to the reference value as the second set of switch states.

[0074] In this embodiment, the expression for screening based on the preliminary evaluation function in step S32 is:

[0075] ;

[0076] In the formula, L X Let L3 and L be the set of candidate switch states. 2A L 2B L 1A L 1B L0 is the output level, V dc V is the DC bus voltage. x This is the effective voltage output of phase x of the inverter.

[0077] In this embodiment, the voltage deviation of the flying capacitor is divided into high, normal, and low ranges based on the relationship between the voltage deviation of the flying capacitor and the DC bus voltage. It determines which switching states in different ranges can make the voltage deviation converge toward the reference value. For example, in this embodiment, the discharge state is selected when the voltage deviation is high and the charging state is selected when the voltage deviation is low. The switching states that meet the voltage balance requirements are selected to form a second set of switching states to solve the problem of voltage imbalance of the flying capacitor.

[0078] Step S33: Take the intersection of the first switch state set and the second switch state set to obtain the candidate switch state set.

[0079] Therefore, by taking the intersection of the two sets, we obtain the set of candidate switch states.

[0080] Step S4: For each candidate switch state in the candidate switch state set, predict the state flyover capacitor voltage and state output three-phase current at the next moment based on the current output three-phase current.

[0081] Specifically, for each candidate switch state in the selected set of candidate switch states, the current output three-phase current, combined with inverter topology, circuit parameters such as inductor and capacitor characteristics, and the mapping relationship between switch states and electrical quantities, is used to predict the state at the next moment, specifically the fly-through capacitor voltage V. Cx (k+1) and the state output three-phase current i abc (k+1).

[0082] Step S5: Using a multi-objective cost function based on sliding mode control theory, with the static reference current as the benchmark, and combining the state flyover capacitor voltage and the state output three-phase current, the current tracking cost function and the balance flyover capacitor voltage cost function are calculated, and the overall cost function is generated.

[0083] In this embodiment, the expression for the overall cost function in step S5 is:

[0084] ;

[0085] ;

[0086] ;

[0087] In the formula, g is the total cost function, g i Let g be the current tracking cost function, λ be the weighting coefficient, and g be the weighting coefficient. c To balance the cost function of the flying capacitor voltage, a, b, and c are three phases, i x The output three-phase current is i. xref As the static reference current, v xn e represents the output voltage corresponding to the candidate switch state. x V represents the current three-phase voltage of the power grid. cx1 and V cx2 The two states of the flying capacitor voltage of the 4L-NNPC inverter.

[0088] In step S5 of this embodiment, the three-phase current output in the state is compared with the static reference current. Combined with the candidate state output voltage and the grid voltage, the current tracking deviation is quantified. At the same time, the absolute value of the voltage deviation of the flying capacitor is calculated to measure the degree of voltage balance. Finally, the two objectives are balanced by weighting coefficients, and the two are weighted and summed to obtain the overall cost function. The control effect of the candidate switching state is comprehensively evaluated, providing a basis for selecting the optimal switching state.

[0089] Step S6: Select the candidate switching state that minimizes the overall cost function as the optimal control output for the 4L-NNPC inverter control.

[0090] Therefore, in this embodiment, the candidate switching state with the minimum overall cost function is selected for control output, thereby achieving coordinated control of accurate current tracking and voltage balance.

[0091] like Figure 4 , Figure 5 as well as Figure 6 As shown, after applying the method of this embodiment, simulation analysis is performed using Matlab. Figure 4 As shown in the figure, at 0.05s, the curves from top to bottom are i. b i a i c The method in this embodiment has an output current waveform with a response time of 1.15ms after a sudden current change under rated operating conditions and dynamic step operating conditions. Furthermore, the current ripple amplitude is significantly reduced by about 35% under steady-state operating conditions, and the waveform smoothness is significantly improved. This verifies the optimization effect of the sliding mode cost function on the dynamic process.

[0092] like Figure 5 As shown, harmonic spectrum analysis reveals that the method in this embodiment reduces THD to 1.29%, attenuates the amplitude of high-frequency harmonics above 3kHz by more than 40%, completely eliminates the 5th and 7th characteristic harmonics, and shifts harmonic energy to the >10kHz ultra-high frequency band, highlighting the optimization effect of the level screening mechanism on the switching sequence.

[0093] like Figure 6 As shown, based on its position at 0.05s, the curves from top to bottom are V. Ca1 V Cb2 V Cc2 V Cb1 V Cc1 and V Ca2 Therefore, according to Figure 6 The voltage fluctuation characteristics of the flying capacitor show that the voltage extreme value is reduced by 15%, effectively avoiding the overvoltage risk of power devices, proving the effectiveness of the strategy of the level screening mechanism to prioritize the switching state in the voltage convergence direction.

[0094] like Figure 7 As shown, the improved finite control set model in this embodiment is Sliding Mode Control-Model Predictive Control (SMC-MPC). The order of its rows is parameter acquisition, level filtering, prediction, and cost function calculation. Actual test data from the DSP28379D platform shows that the traditional FCS-MPC (Finite Control Set Model Predictive Control) takes 78.43 μs to traverse 216 states. The SMC-MPC in this embodiment compresses the number of states through level filtering and, combined with a simplified design of the sliding mode cost function, requires only 23.59 μs per cycle, a reduction of 70%. The freed-up computational margin allows for an increase in sampling frequency to 50 μs or the use of a low-cost processor, providing hardware feasibility support for high-frequency control.

[0095] In summary, this embodiment can significantly reduce computational complexity while improving the system's dynamic performance and steady-state accuracy.

[0096] Example 2

[0097] Please refer to Figure 8 The 4L-NNPC inverter control device 1 based on the improved finite control set model includes a memory 3, a processor 2, and a computer program stored in the memory 3 and run on the processor 2. When the processor 2 executes the computer program, it implements the steps in the above embodiment 1.

[0098] Since the systems / devices described in the above embodiments of the present invention are systems / devices used to implement the methods of the above embodiments of the present invention, those skilled in the art can understand the specific structure and modifications of the systems / devices based on the methods described in the above embodiments of the present invention, and therefore will not be repeated here. All systems / devices used in the methods of the above embodiments of the present invention fall within the scope of protection of the present invention.

[0099] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions.

[0101] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.

[0102] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "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. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, 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.

[0103] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0104] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, then this invention should also include these modifications and variations.

Claims

1. A control method for a 4L-NNPC inverter based on an improved finite control set model, characterized in that, include: Step S1: Real-time acquisition of current three-phase grid voltage, current flying capacitor voltage, and current output three-phase current; Step S2: Using a simplified prediction model, obtain the stationary reference current in the stationary coordinate system at the next moment based on the current three-phase voltage of the power grid, and calculate the preliminary evaluation function of the flying capacitor voltage based on the current flying capacitor voltage. Step S3: Combining the preliminary evaluation function and the static reference current, determine the set of candidate switch states through the output level screening mechanism; Step S4: For each candidate switch state in the candidate switch state set, predict the state fly-through capacitor voltage and state output three-phase current at the next moment based on the current output three-phase current. Step S5: Using a multi-objective cost function based on sliding mode control theory, with the static reference current as the reference, and combining the state flying capacitor voltage and the state output three-phase current, the current tracking cost function and the balanced flying capacitor voltage cost function are calculated to generate the overall cost function. Step S6: Select the candidate switching state that minimizes the overall cost function as the optimal control output for the 4L-NNPC inverter control; Step S2 includes: Step S21: The phase-locked loop tracks and obtains the grid voltage phase angle based on the current grid three-phase voltage, and calculates the rotating reference current in the rotating coordinate system based on the grid voltage phase angle and the given reference current; Step S22: Using a simplified prediction model, predict the reference current in the rotating coordinate system at the next moment based on the rotating reference current, and transform it into the stationary reference current in the stationary coordinate system. Step S23: Predict the global flying capacitor voltage at the next moment and compare it with the flying capacitor voltage reference value to calculate the preliminary evaluation function of the global flying capacitor voltage; The simplified prediction model construction expression in step S2 is as follows: ； In the formula, σ x For current-controlled sliding surfaces, σ x ' is the derivative of the current-controlled sliding mode surface, i x 'i represents the current output three-phase current.' xref ' is the rotating reference current, v xn ' represents the output voltage corresponding to the current switching state, e x R is the current three-phase voltage of the power grid. x For the filter resistor, L x For filtering inductors; Step S3 includes: Using the static reference current as the target, select the switching states whose actual output current is close to the static reference current from all switching states as the first set of switching states; Based on the preliminary evaluation function, the switch states in which the capacitor voltage deviation affected by the charging and discharging of the flying capacitor converges toward the reference value are taken as the second set of switch states. The intersection of the first set of switch states and the second set of switch states is used to obtain the candidate set of switch states. The expression for the overall cost function in step S5 is: ； ； ； In the formula, g is the total cost function, g i Let g be the current tracking cost function, λ be the weighting coefficient, and g be the weighting coefficient. c To balance the cost function of the flying capacitor voltage, a, b, and c are three phases, i x i is the current output three-phase current. xref As the static reference current, v xn e represents the output voltage corresponding to the candidate switch state. x V represents the current three-phase voltage of the power grid. cx1 and V cx2 The two states of the flying capacitor voltage of the 4L-NNPC inverter.

2. The 4L-NNPC inverter control method based on the improved finite control set model according to claim 1, characterized in that, The expression for filtering based on the static reference current in step S3 is as follows: ； In the formula, i xref (k+1) is the resting reference current at the next moment, T s For the control cycle, L is the filter inductance, and V... x (k) represents the effective voltage output of phase x of the inverter at the current time k, e x (k) represents the current three-phase voltage of the power grid, R is the filter resistor, and i x (k) represents the current output three-phase current.

3. The 4L-NNPC inverter control method based on the improved finite control set model according to claim 1, characterized in that, The expression for screening based on the preliminary evaluation function in step S3 is as follows: ； In the formula, L X Let L3 and L be the set of candidate switch states. 2A L 2B L 1A L 1B L0 is the output level, V dc V is the DC bus voltage. x This is the effective voltage output of phase x of the inverter.

4. A 4L-NNPC inverter control device based on an improved finite control set model, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the 4L-NNPC inverter control method based on the improved finite control set model as described in any one of claims 1 to 3.

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