A converter and a control method thereof

Abstract

The present application discloses a control method for a converter and a converter, comprising: obtaining an output current; performing Clarke transformation on the output current to obtain αβ Current value in a two-phase stationary coordinate system; obtaining an output voltage estimate and a lumped disturbance estimate through a high-order extended observer; decomposing the output voltage estimate and the lumped disturbance estimate in a natural coordinate system to obtain a normal component; obtaining the input gain of the high-order extended observer through a fast gradient algorithm based on the normal component of the output voltage estimate and the lumped disturbance estimate; substituting the input gain into the high-order extended observer to update the observer, and performing output voltage estimation based on the updated high-order extended observer to obtain an output voltage reference value; generating a switch state based on the output voltage reference value and controlling the converter based on the switch state. This application can eliminate the control system's dependence on precise inductance parameters and improve the control accuracy and robustness of the converter system.

Description

Technical Field

[0001] The present application relates to the technical field of converter control, and in particular to a converter and a control method thereof. Background Art

[0002] Traditional model-based predictive current control (MPC) is widely used in converter systems due to its clear concepts and fast dynamic response. However, it relies heavily on the accuracy of motor parameters (such as stator resistance, inductance, and permanent magnet flux). When these parameters mismatch due to factors such as temperature fluctuations and aging, current tracking errors increase, total harmonic distortion (THD) significantly rises, and even leads to converter system instability. For example, parameter mismatch can degrade the steady-state and dynamic performance of MPC, leading to steady-state current errors and increased operating noise. Summary of the Invention

[0003] In order to solve the deficiencies of the prior art, this application adopts the following technical solutions:

[0004] In a first aspect, the present application provides a method for controlling a converter, the method comprising the following steps:

[0005] Obtaining the output current of the converter system;

[0006] The output current is subjected to Clarke transformation to obtain αβ Current value in the two-phase stationary coordinate system;

[0007] Based on the αβ The current values ​​in the two-phase stationary coordinate system are initialized to obtain the output voltage estimation value and the lumped disturbance estimation value;

[0008] Decomposing the output voltage estimate and the lumped disturbance estimate in a natural coordinate system to obtain normal components of the output voltage estimate and the lumped disturbance estimate;

[0009] obtaining an input gain of the high-order extended observer by a fast gradient algorithm based on the output voltage estimate and the normal component of the lumped disturbance estimate;

[0010] Substituting the input gain into the high-order extended observer to update the observer, and re-estimating the output voltage based on the updated high-order extended observer to obtain an output voltage reference value;

[0011] Based on the output voltage reference value, a switching state of the converter is generated and the converter is controlled based on the switching state.

[0012] In summary, an embodiment of the present application provides a control method for a converter, which adopts a high-order expanded observer to obtain the output voltage estimate and the lumped disturbance estimate of the converter system, and obtains the normal vector of the output voltage estimate and the lumped disturbance estimate by a current decomposition method, thereby obtaining the input gain of the high-order expanded observer based on a fast gradient algorithm. By combining the high-order expanded observer with the fast gradient algorithm, online adjustment of the input gain of the high-order expanded observer is achieved, and parameter errors are dynamically compensated to reduce the debugging workload, so that the high-order expanded observer can automatically optimize parameters according to the operating status of the converter system, complete the output voltage estimation of the converter system, and improve the control accuracy and robustness of the converter system; and through current decomposition, the control system's dependence on precise inductance parameters is eliminated, avoiding the performance degradation of traditional control methods due to parameter mismatch, and further improving the performance of the converter system.

[0013] Furthermore, the high-order extended observer is configured to: in a discrete time scale, based on the actual output current at the kth moment and the estimated value of the output current at the kth moment Calculate the estimation error at the kth moment and construct the estimated error by The linear feedback term, the quadratic feedback term and the cubic feedback term are used to obtain the output current estimate at the k+1th moment in the iterative update. , the estimated value of the total disturbance of the converter system at time k+1 and an estimate of the rate of change of the aggregate disturbance , in order to achieve real-time compensation and state tracking of the converter system uncertainty.

[0014] Furthermore, the error The linear feedback term is configured to triple the bandwidth to amplify the estimation error, and the output current estimation value at the k+1th moment is Obtained by: taking the estimated value of the output current at the kth moment Based on the superposition sampling period The product of the current estimation correction term is obtained, and the current estimation correction term is configured to satisfy: the estimated value of the total disturbance of the converter system at the kth moment is , output voltage at moment k Input gain after high-order expanded observer modulated feedforward term, and the error The sum of the linear feedback terms;

[0015] The estimated error The secondary feedback term is configured as follows: the estimated error The square of is obtained by triple bandwidth square modulation; the estimated value of the total disturbance of the converter system at the k+1th moment is Obtained by: Based on the estimated value of the total disturbance of the converter system at time k , superimposed sampling period The product of the lumped disturbance estimate correction term is obtained, and the lumped disturbance estimate correction term is configured to satisfy: the estimate of the disturbance derivative The estimated error The sum of the secondary feedback terms of ;

[0016] The estimated error The cubic feedback term is configured as follows: the estimated error The cube of is obtained by bandwidth cube amplification; the estimated value of the rate of change of the aggregate disturbance is It is obtained as follows: using the estimate of the perturbation derivative Based on the superposition sampling period The estimated error The product of the three feedback terms is obtained.

[0017] Furthermore, the fast gradient algorithm is expressed by the following formula:

[0018] ;

[0019] Where, yes The gradient of , the input gain is obtained by the following formula :

[0020] ;

[0021] Where, and There are two parameters used to adjust the step size, and the discrete form is as follows:

[0022] ;

[0023] Where, represents the tangential component of the lumped disturbance at the kth moment, represents the tangential component of the output voltage at the kth moment, represents the estimated value of the iteration step coefficient at the k+1th moment, represents the estimated value of the input gain at the k+1th moment, Represents the step size coefficient of the selection.

[0024] Furthermore, generating the switching state of the converter based on the output voltage reference value includes:

[0025] The switch states are traversed to obtain the optimal switch state with the goal of minimizing a cost function, wherein the cost function is a function related to the output voltage reference value.

[0026] Furthermore, the cost function is configured as: the sum of the first parameter, the second parameter and the third parameter, wherein the first parameter is the reference voltage at the kth moment Directional component With the i The voltage vector Directional component The second parameter is the square of the deviation of the reference voltage at the kth moment. Directional component With the i The voltage vector Directional component The third parameter is the product of the square of the midpoint voltage and the weight.

[0027] Furthermore, the control method further comprises calculating the midpoint voltage by the following steps:

[0028] The first i The absolute values ​​of the switching states of the voltage vectors are multiplied by the three-phase currents and then summed to obtain the midpoint current;

[0029] The midpoint current is divided by twice the DC link capacitance and the sampling period Multiply them, and superimpose the product result with the midpoint voltage at the current moment, and reflect the charging and discharging effect of the midpoint current on the capacitor through discrete integration to obtain the midpoint voltage at the next moment.

[0030] In a second aspect, the present application further provides a converter, comprising:

[0031] A midpoint-clamped three-phase inverter circuit for converting direct current into alternating current; a sampling module for collecting the output current of the midpoint-clamped three-phase inverter circuit; and a processing module comprising:

[0032] A first coordinate transformation unit is used to perform Clarke transformation on the output current to obtain αβ Current value in the two-phase stationary coordinate system;

[0033] A high-order dilated observer is used to αβ The current values ​​in the two-phase stationary coordinate system are used to obtain the output voltage estimation value and the lumped disturbance estimation value;

[0034] a second coordinate transformation unit, configured to decompose the output voltage estimate and the lumped disturbance estimate in a natural coordinate system to obtain normal components of the output voltage estimate and the lumped disturbance estimate;

[0035] a fast gradient processing unit, the fast gradient unit being configured to obtain an input gain of the high-order extended observer by a fast gradient algorithm according to the output voltage estimate and the normal component of the lumped disturbance estimate;

[0036] The processing module substitutes the input gain into the high-order extended observer to update the observer, and re-estimates the output voltage based on the updated high-order extended observer to obtain an output voltage reference value. Based on the output voltage reference value, the processing module generates a switching state of the converter and controls the converter based on the switching state.

[0037] Furthermore, the high-order extended observer is configured to: in a discrete time scale, based on the actual output current at the kth moment and the estimated value of the output current at the kth moment Calculate the estimation error at the kth moment and construct the estimated error by The linear feedback term, the quadratic feedback term and the cubic feedback term are used to obtain the output current estimate at the k+1th moment in the iterative update. , the estimated value of the total disturbance of the converter system at time k+1 and an estimate of the rate of change of the aggregate disturbance , in order to achieve real-time compensation and state tracking of the converter system uncertainty.

[0038] Furthermore, the fast gradient algorithm is expressed by the following formula:

[0039] ;

[0040] Where, yes The gradient of , the input gain is obtained by the following formula :

[0041] ;

[0042] Where, and There are two parameters used to adjust the step size, and the discrete form is as follows:

[0043] ;

[0044] Where, represents the tangential component of the lumped disturbance at the kth moment, represents the tangential component of the output voltage at the kth moment, represents the estimated value of the iteration step coefficient at the k+1th moment, represents the estimated value of the input gain at the k+1th moment, Represents the step size coefficient of the selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A flowchart of a method for controlling a converter according to an embodiment of the present application;

[0046] Figure 2 A schematic diagram of coordinate decomposition in a natural coordinate system in a method for controlling a converter provided by an embodiment of the present application;

[0047] Figure 3 A control block diagram of a converter system in which a converter control method provided by an embodiment of the present application is applied;

[0048] Figure 4 A schematic diagram of a converter topology in a simulation experiment of a converter control method provided by an embodiment of the present application;

[0049] Figure 5a A schematic diagram of simulation results of steady-state performance of a traditional FCS-MPC method under system parameter matching conditions provided as a comparative example of this application;

[0050] Figure 5b A schematic diagram of simulation results of the steady-state performance of the ESO-based FCS-MPC method under system parameter matching conditions provided as a comparative example of the present application;

[0051] Figure 5c A schematic diagram of simulation results of steady-state performance of a converter control method provided by an embodiment of the present application under system parameter matching conditions;

[0052] Figure 6a A schematic diagram of simulation results of the steady-state performance of the traditional FCS-MPC method under system parameter mismatch conditions provided as a comparative example of this application;

[0053] Figure 6b A schematic diagram of simulation results of the steady-state performance of the ESO-based FCS-MPC method under system parameter mismatch conditions provided as a comparative example of the present application;

[0054] Figure 6c A schematic diagram of simulation results of steady-state performance of a converter control method provided by an embodiment of the present application under system parameter mismatch conditions;

[0055] Figure 7aA schematic diagram of the experimental results of the steady-state performance of the traditional FCS-MPC method under the system parameter matching condition provided as a comparative example of this application;

[0056] Figure 7b A schematic diagram of the experimental results of the steady-state performance of the ESO-based FCS-MPC method under system parameter matching conditions provided as a comparative example of the present application;

[0057] Figure 7c A schematic diagram of experimental results of steady-state performance of a converter control method provided by an embodiment of the present application under system parameter matching conditions;

[0058] Figure 8a A schematic diagram of the experimental results of the steady-state performance of the traditional FCS-MPC method under system parameter mismatch conditions provided as a comparative example of this application;

[0059] Figure 8b A schematic diagram of the experimental results of the steady-state performance of the ESO-based FCS-MPC method under system parameter mismatch conditions provided as a comparative example of the present application;

[0060] Figure 8c A schematic diagram of experimental results of steady-state performance of a converter control method provided by an embodiment of the present application under system parameter mismatch conditions. DETAILED DESCRIPTION

[0061] The present application will be described in detail below in conjunction with the specific embodiments shown in the accompanying drawings, but these embodiments do not limit the present application. Structural, methodological, or functional changes made by ordinary technicians in this field based on these embodiments are included in the scope of protection of the present application.

[0062] In order to solve the deficiencies of the prior art, in a first aspect, the present invention provides a control method for a converter, such as Figure 1 As shown, the control method includes the following steps:

[0063] Step S101 : obtaining the output current of the converter system, performing Clarke transformation on the output current, and obtaining the current value in the αβ two-phase stationary coordinate system.

[0064] Step S102 : Based on the current values ​​in the αβ two-phase stationary coordinate system, an output voltage estimation value and a lumped disturbance estimation value are obtained through an initialized high-order extended observer.

[0065] Step S103 : Decompose the output voltage estimate and the lumped disturbance estimate in a natural coordinate system to obtain normal components of the output voltage estimate and the lumped disturbance estimate.

[0066] Step S104 : obtaining the input gain of the high-order extended observer by a fast gradient algorithm based on the output voltage estimate and the normal component of the lumped disturbance estimate.

[0067] In step S105 , the input gain is substituted into the high-order extended observer to update the observer, and the output voltage is re-estimated based on the updated high-order extended observer to obtain an output voltage reference value.

[0068] Step S106 : generating a switching state of the converter based on the output voltage reference value and controlling the converter based on the switching state.

[0069] Specifically, the output current of the converter system is collected and obtained, and the output current data can reflect the actual load state of the converter system during operation. For example, taking a three-level neutral point clamped converter as an example, its output current is a three-phase AC current. i a 、 i b 、 i c , the output current can be expressed by the following formula:

[0070] ;

[0071] Where i represents the output current, u represents the output voltage, R represents the load resistance, and L represents the load inductance.

[0072] The obtained output current is transformed by Clarke, and the current in the three-phase stationary coordinate system is converted into αβ The current values ​​in the two-phase stationary coordinate system are obtained by eliminating the redundancy of the three-phase system through linear algebra operations, simplifying the mathematical model to reduce the computational complexity, and decoupling the complex coupling problem of the three-phase system into two independent orthogonal components so that state estimation can be performed using a high-order extended observer.

[0073] Based on the conversion αβ The current values ​​in the two-phase stationary coordinate system are calculated. In step S102, a high-order extended observer is initialized to integrate the disturbances during the converter system operation into a lumped disturbance. The high-order extended observer estimates the lumped disturbance and the converter system state, obtaining an estimated output voltage and lumped disturbance of the converter system. This high-order extended observer observes and evaluates the lumped disturbance, accurately estimating the system state without relying on a precise motor model, effectively compensating for errors caused by parameter mismatch, and improving the robustness of the control strategy.

[0074] Optionally, in an embodiment of the present application, according to the principle of a high-order extended observer, the mathematical model of a second-order extended observer can be expressed by the following formula:

[0075] ;

[0076] Where, e represents the estimation error; represents the estimated value of the output current i, express The first derivative of ; represents the bandwidth of the high-order dilated observer; represents the lumped disturbance, and ; for The derivative of express The estimated value of express The first derivative of ; represents the input gain of the high-order extended observer, and .

[0077] The output current i of the converter system can be decomposed into tangential component and normal component in the natural coordinate system. The direction of the output current vector i is consistent with the direction of the normal component in the natural coordinate system, and the output current vector i is perpendicular to the direction of the tangential component in the natural coordinate system. The direction of the output current vector is always consistent with the direction of the normal component in the natural coordinate system, ensuring that the current of the normal component is i n Always zero. Figure 2 As shown in the figure, the obtained output voltage estimate and lumped disturbance estimate are decomposed in the natural coordinate system respectively. f t represents the tangential component of the lumped disturbance estimate, f n represents the normal component of the lumped disturbance estimate, u t represents the tangential component of the output voltage estimate, u n Represents the normal component of the output voltage estimate.

[0078] Based on the obtained output voltage estimate and the normal component of the lumped disturbance estimate, the following quantitative relationship exists:

[0079] ;

[0080] Where, f n represents the normal component of the lumped disturbance estimate, u n represents the normal component of the output voltage estimate, L represents the load inductance value of the converter system at the current moment, Indicates the load inductance value at the initial moment of the converter system.

[0081] Based on the above analysis, in step 104, the normal component error is used as the objective function, and the fast gradient algorithm is used to calculate the input gain of the high-order extended observer. The high-order extended observer is adaptively adjusted based on the input gain to avoid the lack of robustness caused by parameter fixation in traditional control methods and eliminate the impact of parameter mismatch on the control system. In this embodiment of the present application, the objective function can be expressed as follows:

[0082] ;

[0083] Where, represents the input gain of the high-order extended observer, Represents the objective function value.

[0084] After obtaining the input gain of the high-order extended observer, in step S105, the input gain is substituted into the state equation of the high-order extended observer, and the parameters in the high-order extended observer are updated in real time. Based on the updated high-order extended observer, the state variables are recalculated, the output voltage of the converter system is re-estimated, and the output voltage reference value of the converter system is obtained. The high-order extended observer is updated and corrected by the input gain, and the converter system state is re-evaluated using the corrected and updated high-order extended observer to achieve dynamic tracking of the time-varying characteristics of the parameters. Based on the output voltage reference value of the converter system, all switching states of the converter are traversed, and the voltage vector corresponding to the converter in each switching state is calculated. The converter is then controlled based on the switching state to maintain converter operation stability and midpoint potential balance.

[0085] According to the above description, an embodiment of the present application provides a control method for a converter, which adopts a high-order expanded observer to obtain the output voltage estimate and the lumped disturbance estimate of the converter system, and obtains the normal vector of the output voltage estimate and the lumped disturbance estimate by a current decomposition method, thereby obtaining the input gain of the high-order expanded observer based on the fast gradient algorithm. By combining the high-order expanded observer with the fast gradient algorithm, online adjustment of the input gain of the high-order expanded observer is achieved, and parameter errors are dynamically compensated to reduce the debugging workload, so that the high-order expanded observer can automatically optimize parameters according to the operating status of the converter system, complete the output voltage estimation of the converter system, and improve the control accuracy and robustness of the converter system; and through current decomposition, the control system's dependence on precise inductance parameters is eliminated, avoiding the performance degradation of traditional control methods due to parameter mismatch, and further improving the performance of the converter system.

[0086] As an optional implementation, in step S102, based on the current values ​​in the αβ two-phase stationary coordinate system, the output voltage estimation value and the lumped disturbance estimation value are obtained by initializing the high-order extended observer. The high-order extended observer is configured to: in a discrete time scale, based on the actual output current at the kth moment and the estimated value of the output current at the kth moment Calculate the estimation error at the kth moment and estimate the error by constructing The linear feedback term, the quadratic feedback term and the cubic feedback term are used to obtain the output current estimate at the k+1th moment in the iterative update. , the estimated value of the total disturbance of the converter system at time k+1 and an estimate of the rate of change of the aggregate disturbance , in order to achieve real-time compensation and state tracking of converter system uncertainty.

[0087] Furthermore, in the high-order extended observer, the error The linear feedback term is configured to triple the bandwidth to amplify the estimation error. The output current estimate at time k+1 is Obtained by: taking the estimated value of the output current at the kth moment Based on the superposition sampling period The current estimation correction term is configured to satisfy: the estimated value of the total disturbance of the converter system at the kth moment is , output voltage at moment k and the input gain of the high-order extended observer The product of, and the error The sum of the linear feedback terms.

[0088] Furthermore, in the high-order dilated observer, the estimation error The secondary feedback term is configured as follows: Estimation error The square of is obtained by triple bandwidth square modulation. The estimated value of the total disturbance of the converter system at time k+1 is Obtained by: Based on the estimated value of the total disturbance of the converter system at time k , superimposed sampling period The product of the lumped disturbance estimate correction term is obtained, and the lumped disturbance estimate correction term is configured to satisfy: the estimate of the disturbance derivative and estimation error The sum of the quadratic feedback terms.

[0089] Furthermore, in the high-order dilated observer, the estimation error The three feedback terms are configured as follows: Estimation error The cube of is obtained by amplifying the bandwidth cube; the estimated value of the rate of change of the aggregate disturbance is It is obtained as follows: using the estimate of the perturbation derivative Based on the superposition sampling period and estimation error The product of the three feedback terms is obtained.

[0090] In one embodiment, the high-order dilated observer can be expressed as follows:

[0091] ;

[0092] Where, represents the sampling time, k represents the moment, represents the actual output current at the kth moment, represents the estimated value of the output current at the kth moment, represents the estimation error at the kth moment, represents the input gain of the high-order extended observer, represents the lumped disturbance of the converter system at the kth moment, represents the estimated value of the lumped disturbance of the converter system at the kth moment, represents the output voltage at the kth moment, represents the bandwidth of the high-order dilated observer; for The derivative of represents the rate of change of the lumped disturbance of the converter system; Represents the estimated value of the rate of change of the lumped disturbance of the converter system.

[0093] After obtaining the output voltage estimate and the lumped disturbance estimate, the output voltage estimate and the lumped disturbance estimate are decomposed in a natural coordinate system to obtain normal components of the output voltage estimate and the lumped disturbance estimate. Furthermore, in step S104, based on the normal components of the output voltage estimate and the lumped disturbance estimate, the input gain of the high-order dilated observer is obtained using a fast gradient algorithm. As an optional implementation, the fast gradient algorithm can be expressed as follows:

[0094] ;

[0095] Where, yes The gradient of the high-order dilated observer is obtained by the following formula :

[0096] ;

[0097] Where, Indicates input gain The estimated value of and There are two parameters used to adjust the step size. represents the learning rate, represents the iteration step coefficient, and The discrete form of is as follows:

[0098] ;

[0099] Where, represents the tangential component of the lumped disturbance at the kth moment, represents the tangential component of the output voltage at the kth moment, represents the estimated value of the iteration step coefficient at the k+1th moment, represents the estimated value of the input gain at the k+1th moment, Represents the step size coefficient of the selection.

[0100] Furthermore, after obtaining the input gain of the high-order extended observer, in step S105, the input gain is substituted into the high-order extended observer to update the observer. Based on the updated high-order extended observer, the output voltage is re-estimated to obtain an output voltage reference value. As an optional implementation, the high-order extended observer predicts the output current of the converter system and estimates the output voltage of the converter system based on the predicted output current using the following formula:

[0101] ;

[0102] Where, u ( k ) * Indicates the output voltage reference value, i ref is the reference value of the current, i ( k ) is the output current at the kth moment.

[0103] As an optional implementation, the control method provided in an embodiment of the present application further includes: step S106, generating a switching state of the converter based on the output voltage reference value obtained above, traversing all switching states, obtaining an optimal switching state with the goal of minimizing the cost function, and controlling the converter based on the optimal switching state. For example, in an embodiment of the present application, a three-level neutral-point clamped converter shares 27 possible switching states, thereby having 27 possible voltage vectors. By traversing all switching states and comparing the cost function values ​​of all switching states, the switching state that minimizes the cost function is selected as the optimal switching state, and the converter is controlled based on the optimal switching state to ensure stable operation of the converter and midpoint voltage balance.

[0104] Furthermore, the cost function is configured as: the sum of the first parameter, the second parameter and the third parameter, wherein the first parameter is the reference voltage at the kth moment Directional component With the i The voltage vector Directional component The second parameter is the square of the deviation of the reference voltage at the kth moment. Directional component With the i The voltage vector Directional component The third parameter is the product of the square of the midpoint voltage and the weight.

[0105] In one embodiment, the cost function is a function related to the output voltage reference value of the converter. When constructing the cost function, the current reference voltage is calculated. The deviation of the direction component is calculated by square-adding the two deviation values, and then adding them together. The product of the square of the midpoint voltage and the weight is superimposed. By integrating the constraints of voltage tracking error and midpoint voltage fluctuation, a quantitative indicator is provided for the optimal selection of the voltage vector. Furthermore, the cost function can be expressed by the following formula:

[0106] ;

[0107] Where, is the first parameter, and Respectively represent the reference voltage at the kth moment Directional component; is the second parameter, and Respectively represent The voltage vector Directional component; is the third parameter, Indicates the midpoint voltage, Represents the weight of the midpoint voltage in the cost function.

[0108] As an optional implementation, the control method further includes calculating the midpoint voltage by the following steps: i The absolute value of the switching state of each voltage vector is multiplied by the three-phase current and then summed to obtain the midpoint current; the midpoint current is divided by twice the DC side capacitance and then summed with the sampling period Multiply them, and superimpose the product result with the midpoint voltage at the current moment, and reflect the charging and discharging effect of the midpoint current on the capacitor through discrete integration to obtain the midpoint voltage at the next moment.

[0109] The midpoint current can be calculated using the following formula:

[0110] ;

[0111] Where, i a 、i b 、 i c Indicates the current of each phase of the converter, Represents the absolute value of the switching state of the i-th voltage vector.

[0112] The midpoint voltage at the next moment can be calculated using the following formula:

[0113] ;

[0114] Where, i n ( k ) represents the midpoint current at the current moment, v n ( k ) represents the midpoint voltage at the current moment, Indicates the midpoint voltage at the next moment, represents the sampling time, C dc Indicates the bus capacitance on the DC side.

[0115] In summary, based on a control method for a converter provided in an embodiment of the present application, the control system is applied to a converter system such as Figure 3 As shown, first, the control system controls the output current of the converter system i abc Perform Clarke transformation to obtain the current value of the αβ two-phase stationary coordinate system i αβ ; Based on the current value in the αβ two-phase stationary coordinate system i αβ , the output voltage estimate is obtained by a high-order extended observer u αβ and the lumped disturbance estimate f αβ ; Based on the current value in the αβ two-phase stationary coordinate system i αβ , output voltage estimate u αβ and the lumped disturbance estimate f αβ , the output voltage estimate u αβ and the lumped disturbance estimate f αβ Decompose in the natural coordinate system to obtain the output voltage estimate u n and the lumped disturbance estimate f n The normal component of u n and the lumped disturbance estimatef n The normal component of the high-order expanded observer is calculated by the fast gradient algorithm to obtain the input gain α of the high-order expanded observer; then, the input gain α is substituted into the high-order expanded observer for observer update, and based on the updated high-order expanded observer, the output voltage is re-estimated to obtain the output voltage reference value v αβ ; and based on the output voltage reference value v αβ , through the cost function to traverse all the switch states, with the goal of minimizing the cost function, to obtain the optimal switch state S abc , based on the switch state S abc The converter is controlled to achieve the control goal of the converter system.

[0116] To further illustrate the control method of a converter provided in an embodiment of the present application, simulation tests and experimental tests are conducted below to compare the traditional FCS-MPC (Finite Control-Set Model Predictive Control) method, the FCS-MPC method based on ESO (Extended State Observer), and the control method provided in an embodiment of the present application to verify the effectiveness of the control method provided in an embodiment of the present application. Figure 4 As shown in the figure, in the simulation experiment, the converter adopts a midpoint clamped three-level inverter. The hardware platform in the simulation experiment consists of a 3L-NPC converter, a digital signal processor, and an RL load. The control cycle of the digital signal processor is 100μs; the resistance value of the RL load is set to 1Ω, and the inductance value L is 10mH. To verify the parameter mismatch, the inductance value is set to 8mH in the experiment. In terms of the software module, for the initialization of the inductor parameters, the bandwidth of the high-order extended observer is set to 500 to 3000, and the learning rate is set to Equal to 1, iterative step coefficient is 0.03.

[0117] First, the steady-state performance of the three control methods mentioned above is simulated and compared. Under the condition of system parameter matching (inductance value L=10mH), the steady-state performance simulation results of the traditional FCS-MPC method are as follows: Figure 5a As shown in Figure 2, the output current THD (Total Harmonic Distortion) of the inverter under the traditional FCS-MPC method is 1.12%; the steady-state performance simulation results of the FCS-MPC method based on ESO are shown in Figure 2. Figure 5bAs shown in FIG, the output current THD of the inverter under the control of the FCS-MPC method based on ESO is 1.03%; the steady-state performance simulation results of the control method provided in the embodiment of the present application are shown in FIG. Figure 5c As shown in the figure, the output current THD of the inverter under the control of this control method is 0.97%. Compared with the traditional control method, the control method provided by the embodiment of the present application has a relative reduction of THD of 13.4%; compared with the FCS-MPC method based on ESO, the control method provided by the embodiment of the present application has a relative reduction of THD of 5.93%. It can be concluded that under the working condition of matching system parameters, the control method provided by the embodiment of the present application has better harmonic suppression capability than the previous two control methods.

[0118] Under the condition of system parameter mismatch (inductance value L=8mH), the steady-state performance simulation results of the traditional FCS-MPC method are as follows: Figure 6a As shown in Figure 2, the output current THD of the inverter under the traditional FCS-MPC method is 1.28%; the steady-state performance simulation results of the FCS-MPC method based on ESO are shown in Figure 2. Figure 6b As shown in FIG1 , the output current THD of the inverter under the control of the FCS-MPC method based on ESO is 1.22%; the steady-state performance simulation results of the control method provided in the embodiment of the present application are shown in FIG1 . Figure 6c As shown in the figure, the output current THD of the inverter under the control of this control method is 1.21%. Compared with the traditional control method, the control method provided by the embodiment of the present application has a relative reduction of THD of 5.5%; compared with the FCS-MPC method based on ESO, the control method provided by the embodiment of the present application has a relative reduction of THD of 0.8%. It can be concluded that even under the working condition of system parameter mismatch, the control method provided by the embodiment of the present application still has better harmonic suppression capability than the previous two control methods.

[0119] Furthermore, the steady-state performance of the three control methods mentioned above is experimentally compared. Under the condition of system parameter matching (inductance value L=10mH), the steady-state performance experimental results of the traditional FCS-MPC method are as follows: Figure 7a As shown in Figure 2, the output current THD of the inverter under the traditional FCS-MPC method is 2.47%; the steady-state performance experimental results of the FCS-MPC method based on ESO are shown in Figure 2. Figure 7b As shown in FIG1 , the output current THD of the inverter under the control of the FCS-MPC method based on ESO is 1.24%; the steady-state performance experimental results of the control method provided in the embodiment of the present application are shown in FIG1 . Figure 7cAs shown in the figure, the output current THD of the inverter under the control of this control method is 0.97%. From the experimental waveform, it can be seen that the inverter current distortion is significantly reduced under the control method provided by the embodiment of the present application. Compared with the traditional control method, the relative reduction of its THD reaches 60.7%; compared with the FCS-MPC method based on ESO, the control method provided by the embodiment of the present application has a relative reduction of THD of 21.8%. It can be concluded that under the working condition of matching system parameters, the control method provided by the embodiment of the present application has better harmonic suppression capability than the previous two control methods.

[0120] Under the condition of system parameter mismatch (inductance value L=8mH), the steady-state performance experimental results of the traditional FCS-MPC method are as follows: Figure 8a As shown in Figure 2, the output current THD of the inverter under the traditional FCS-MPC method is 4.23%; the steady-state performance experimental results of the FCS-MPC method based on ESO are shown in Figure 2. Figure 8b As shown in FIG, the output current THD of the inverter under the control of the FCS-MPC method based on ESO is 1.83%; the steady-state performance experimental results of the control method provided in the embodiment of the present application are shown in FIG. Figure 8c As shown in the figure, under the control of this control method, the output current THD of the inverter is 1.41%. From the experimental waveform, it can be seen that the inverter current distortion is significantly reduced under the control method provided in the embodiment of the present application. Compared with the traditional control method, the control method provided in the embodiment of the present application has a relative reduction of THD of 66.7%; compared with the FCS-MPC method based on ESO, the control method provided in the embodiment of the present application has a relative reduction of THD of 22.9%. It can be concluded that even under the working condition of system parameter mismatch, the control method provided in the embodiment of the present application still has better harmonic suppression capability than the previous two control methods, can ensure the stable operation of the system, and effectively improve the anti-interference ability of the system.

[0121] Comparative analysis of the implementation results shows that the inverter current quality is significantly dependent on the controller parameter matching under traditional control methods and the ESO-based FCS-MPC method, and its THD index shows a significant deterioration trend with increasing parameter adaptation. The control method provided by the embodiment of the application can effectively overcome the parameter sensitivity drawback, making the control method more robust and engineering applicable, and more suitable for application scenarios with parameter changes or measurement errors.

[0122] According to the above description, an embodiment of the present application provides a control method for a converter. A high-order extended observer is used to obtain an output voltage estimate and a lumped disturbance estimate of a converter system. The normal vectors of the output voltage estimate and the lumped disturbance estimate are obtained by current decomposition. The input gain of the high-order extended observer is then obtained based on a fast gradient algorithm. By combining the high-order extended observer with the fast gradient algorithm, online adjustment of the input gain of the high-order extended observer is achieved, and parameter errors are dynamically compensated to reduce the debugging workload. The high-order extended observer can automatically optimize parameters according to the operating state of the converter system, complete the output voltage estimate of the converter system, and improve the control accuracy and robustness of the converter system. By calculating a cost function, the switching state that minimizes the cost function is selected to control the converter system, thereby achieving precise control of the converter system and ensuring stable operation and midpoint voltage balance of the converter system. By current decomposition, the control system eliminates the control system's dependence on precise inductance parameters, avoiding the performance degradation of traditional control methods due to parameter mismatch, and further improving the performance of the converter system.

[0123] In a second aspect, based on the same inventive concept, an embodiment of the present application further provides a converter, comprising a midpoint-clamped three-phase inverter circuit, a sampling module, and a processing module. The midpoint-clamped three-phase inverter circuit is configured to convert direct current into alternating current; the sampling module is configured to collect the output current of the midpoint-clamped three-phase inverter circuit. The processing module comprises a first coordinate transformation unit, a high-order extended observer, a second coordinate transformation unit, and a fast gradient processing unit. The first coordinate transformation unit is configured to perform a Clarke transform on the output current to obtain a current value in an αβ two-phase stationary coordinate system; the high-order extended observer is configured to obtain an output voltage estimate and a lumped disturbance estimate based on the current value in the αβ two-phase stationary coordinate system; the second coordinate transformation unit is configured to decompose the output voltage estimate and the lumped disturbance estimate in a natural coordinate system to obtain normal components of the output voltage estimate and the lumped disturbance estimate; and the fast gradient unit is configured to obtain an input gain of the high-order extended observer using a fast gradient algorithm based on the normal components of the output voltage estimate and the lumped disturbance estimate.

[0124] The processing module substitutes the input gain into the high-order extended observer to update the observer, and re-estimates the output voltage based on the updated high-order extended observer to obtain an output voltage reference value. Based on the output voltage reference value, the switching state of the converter is generated and the converter is controlled based on the switching state.

[0125] As an optional implementation, in the processing module, based on the current values ​​in the αβ two-phase stationary coordinate system, the output voltage estimate and the lumped disturbance estimate are obtained through a high-order extended observer. The high-order extended observer is configured to: based on the actual output current at the kth moment in a discrete time scale and the estimated value of the output current at the kth moment Calculate the estimation error at the kth moment and estimate the error by constructing The linear feedback term, the quadratic feedback term and the cubic feedback term are used to obtain the output current estimate at the k+1th moment in the iterative update. , the estimated value of the total disturbance of the converter system at time k+1 and an estimate of the rate of change of the aggregate disturbance , in order to achieve real-time compensation and state tracking of converter system uncertainty.

[0126] In one embodiment, the high-order dilated observer can be expressed as follows:

[0127] ;

[0128] Where, represents the sampling time, k represents the moment, represents the output current at the kth moment, represents the estimated error of the output current at the kth moment, represents the estimation error at the kth moment, represents the input gain of the high-order extended observer, represents the lumped disturbance of the converter system at the kth moment, represents the estimated value of the lumped disturbance of the converter system at the kth moment, represents the output voltage at the kth moment, represents the bandwidth of the high-order dilated observer; for The derivative of represents the rate of change of the lumped disturbance of the converter system; Represents the estimated value of the rate of change of the lumped disturbance of the converter system.

[0129] The high-order extended observer is configured to predict the output current and estimate the output voltage of the converter system based on the predicted output current using the following formula:

[0130] ;

[0131] Where, u ( k ) * Indicates the output voltage reference value, i ref Indicates the reference value of the current, i ( k ) is the output current at the kth moment.

[0132] As an optional implementation, in the processing module, the fast gradient unit obtains the input gain of the high-order dilated observer through a fast gradient algorithm. The fast gradient algorithm can be expressed by the following formula:

[0133] ;

[0134] Where, for The gradient, f n for f The Dharma component, u n for u The normal phase component of . Further, the input gain is obtained by the following formula

[0135] ;

[0136] Where, and There are two parameters used to adjust the step size, and the discrete form is as follows:

[0137] ;

[0138] Where, represents the tangential component of the lumped disturbance at the kth moment, represents the tangential component of the output voltage at the kth moment, represents the estimated value of the iteration step coefficient at the k+1th moment, represents the estimated value of the input gain at the k+1th moment, Represents the step size coefficient of the selection.

[0139] As an optional implementation, in the processing module, generating the switching state of the converter based on the output voltage reference value includes: traversing the switching states to obtain the optimal switching state with the goal of minimizing a cost function. The cost function is a function related to the output voltage reference value of the converter, and the cost function can be expressed by the following formula:

[0140] ;

[0141] Where, and Respectively represent the reference voltage at the kth moment The direction component, and Respectively represent The voltage vector The direction component, represents the midpoint voltage, Represents the weight of the midpoint voltage in the cost function.

[0142] Represents the midpoint voltage, which can be calculated using the following formula:

[0143] ;

[0144] ;

[0145] Where, i n ( k ) represents the midpoint current, i a 、 i b 、 i c Indicates the current of each phase of the converter, v n ( k ) represents the midpoint voltage, represents the sampling time, Represents the absolute value of the switching state of the i-th voltage vector.

[0146] According to the above description, an embodiment of the present application provides a converter that uses a high-order extended observer to obtain an output voltage estimate and a lumped disturbance estimate of the converter system, obtains the normal vectors of the output voltage estimate and the lumped disturbance estimate through a current decomposition method, and thereby obtains the input gain of the high-order extended observer based on a fast gradient algorithm. By combining the high-order extended observer with the fast gradient algorithm, online adjustment of the input gain of the high-order extended observer is achieved, and parameter errors are dynamically compensated to reduce the debugging workload, so that the high-order extended observer can automatically optimize parameters according to the operating state of the converter system, complete the output voltage estimate of the converter system, and improve the control accuracy and robustness of the converter system. By calculating the cost function, the switching state that minimizes the cost function is selected to control the converter system, thereby achieving precise control of the converter system and ensuring stable operation and midpoint voltage balance of the converter system. By using current decomposition, the control system eliminates the control system's dependence on precise inductance parameters, avoids the performance degradation of traditional control methods caused by parameter mismatch, and further improves the performance of the converter system.

[0147] It will be understood that the word "exemplary" as used herein means "serving as an example, instance, or illustration." Any embodiment described as "exemplary" is not necessarily preferred or advantageous over other embodiments and / or does not exclude the ability to combine features of other embodiments. It will be understood that certain features of the present application, which are described in the context of separate embodiments for the sake of clarity, may also be provided in combination in a single embodiment. Conversely, various features of the present application, which are described in the context of a single embodiment for the sake of clarity, may also be provided separately or in any suitable combination or as any other described embodiment of the present application.

[0148] In the description of this application, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" means one or more, and "a plurality" means two or more. Words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not limit them to be necessarily different.

[0149] The above disclosure is only a preferred embodiment of the present application, but it is not intended to limit the scope of rights of the present application. A person skilled in the art can understand that without departing from the spirit and scope of the present application and the appended claims, changes, modifications, substitutions, combinations, and simplifications should all be equivalent replacement methods and still fall within the scope of the invention.

Claims

1. A method for controlling a converter, characterized in that: The control method comprises the following steps: Obtaining the output current of the converter system; The output current is subjected to Clarke transformation to obtain αβ Current value in the two-phase stationary coordinate system; Based on the αβ The current values ​​in the two-phase stationary coordinate system are initialized to obtain the output voltage estimation value and the lumped disturbance estimation value; Decomposing the output voltage estimate and the lumped disturbance estimate in a natural coordinate system to obtain normal components of the output voltage estimate and the lumped disturbance estimate; obtaining an input gain of the high-order extended observer by a fast gradient algorithm based on the output voltage estimate and the normal component of the lumped disturbance estimate; Substituting the input gain into the high-order extended observer to update the observer, and re-estimating the output voltage based on the updated high-order extended observer to obtain an output voltage reference value; generating a switching state of the converter based on the output voltage reference value and controlling the converter based on the switching state; The high-order extended observer is configured to: based on the actual output current at the kth moment in a discrete time scale and the estimated value of the output current at the kth moment Calculate the estimation error at the kth moment and construct the estimated error by The linear feedback term, the quadratic feedback term and the cubic feedback term are used to obtain the output current estimate at the k+1th moment in the iterative update. , the estimated value of the total disturbance of the converter system at time k+1 and an estimate of the rate of change of the aggregate disturbance , so as to achieve real-time compensation and state tracking of the uncertainty of the converter system; The fast gradient algorithm is expressed by the following formula: ； Where, yes The gradient of , the input gain is obtained by the following formula : ； Where, and There are two parameters used to adjust the step size, and the discrete form is as follows: ； Where, represents the tangential component of the lumped disturbance at the kth moment, represents the tangential component of the output voltage at the kth moment, represents the estimated value of the iteration step coefficient at the k+1th moment, represents the estimated value of the input gain at the k+1th moment, Represents the iteration step coefficient.

2. The control method of the converter according to claim 1, characterized in that: The error The linear feedback term is configured to triple the bandwidth to amplify the estimation error, and the output current estimation value at the k+1th moment is Obtained by: taking the estimated value of the output current at the kth moment Based on the superposition sampling period The product of the current estimation correction term is obtained, and the current estimation correction term is configured to satisfy: the estimated value of the total disturbance of the converter system at the kth moment is , output voltage at moment k Input gain after high-order expanded observer modulated feedforward term, and the error The sum of the linear feedback terms; The estimated error The secondary feedback term is configured as follows: the estimated error The square of is obtained by triple bandwidth square modulation; the estimated value of the total disturbance of the converter system at the k+1th moment is Obtained by: Based on the estimated value of the total disturbance of the converter system at time k , superimposed sampling period The product of the lumped disturbance estimate correction term is obtained, and the lumped disturbance estimate correction term is configured to satisfy: the estimate of the disturbance derivative The estimated error The sum of the secondary feedback terms of ; The estimated error The cubic feedback term is configured as follows: the estimated error The cube of is obtained by bandwidth cube amplification; the estimated value of the rate of change of the aggregate disturbance is It is obtained as follows: using the estimate of the perturbation derivative Based on the superposition sampling period The estimated error The product of the three feedback terms is obtained.

3. The control method of the converter according to claim 1, characterized in that: Generating the switching state of the converter based on the output voltage reference value includes: The switch states are traversed to obtain the optimal switch state with the goal of minimizing a cost function, wherein the cost function is a function related to the output voltage reference value.

4. The control method of the converter according to claim 3, characterized in that: The cost function is configured as: the sum of a first parameter, a second parameter and a third parameter, wherein the first parameter is the reference voltage at the kth moment Directional component With the i The voltage vector Directional component The second parameter is the square of the deviation of the reference voltage at the kth moment. Directional component With the i The voltage vector Directional component The third parameter is the product of the square of the midpoint voltage and the weight.

5. The control method of the converter according to claim 4, characterized in that: The control method further comprises calculating the midpoint voltage by the following steps: The first i The absolute values ​​of the switching states of the voltage vectors are multiplied by the three-phase currents and then summed to obtain the midpoint current; The midpoint current is divided by twice the DC link capacitance and the sampling period Multiply them, and superimpose the product result with the midpoint voltage at the current moment, and reflect the charging and discharging effect of the midpoint current on the capacitor through discrete integration to obtain the midpoint voltage at the next moment.

6. A converter, characterized in that: The converter comprises: A neutral point clamped three-phase inverter circuit is used to convert DC power into AC power; A sampling module, used for collecting the output current of the midpoint clamped three-phase inverter circuit; A processing module, the processing module comprising: A first coordinate transformation unit is used to perform Clarke transformation on the output current to obtain αβ Current value in the two-phase stationary coordinate system; A high-order dilated observer is used to αβ The current values ​​in the two-phase stationary coordinate system are used to obtain the output voltage estimation value and the lumped disturbance estimation value; a second coordinate transformation unit, configured to decompose the output voltage estimate and the lumped disturbance estimate in a natural coordinate system to obtain normal components of the output voltage estimate and the lumped disturbance estimate; a fast gradient processing unit, configured to obtain an input gain of the high-order extended observer by a fast gradient algorithm according to the output voltage estimate and the normal component of the lumped disturbance estimate; The processing module substitutes the input gain into the high-order extended observer to update the observer, re-estimates the output voltage based on the updated high-order extended observer to obtain an output voltage reference value, generates a switching state of the converter based on the output voltage reference value, and controls the converter based on the switching state; The high-order extended observer is configured to: based on the actual output current at the kth moment in a discrete time scale and the estimated value of the output current at the kth moment Calculate the estimation error at the kth moment and construct the estimated error by The linear feedback term, the quadratic feedback term and the cubic feedback term are used to obtain the output current estimate at the k+1th moment in the iterative update. , the estimated value of the total disturbance of the converter system at time k+1 and an estimate of the rate of change of the aggregate disturbance , so as to achieve real-time compensation and state tracking of the uncertainty of the converter system; The fast gradient algorithm is expressed by the following formula: ； Where, yes The gradient of , the input gain is obtained by the following formula : ； Where, and There are two parameters used to adjust the step size, and the discrete form is as follows: ； Where, represents the tangential component of the lumped disturbance at the kth moment, represents the tangential component of the output voltage at the kth moment, represents the estimated value of the iteration step coefficient at the k+1th moment, represents the estimated value of the input gain at the k+1th moment, Represents the iteration step coefficient.

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