Converter and control method thereof

Abstract

The invention discloses a converter control method and a converter. The converter control method comprises the following steps: acquiring an output current; performing Clarke conversion on the output current to obtain a current value under an alpha-beta two-phase static coordinate system; obtaining an output voltage estimated value and a lumped disturbance estimated value through a high-order expansion observer; decomposing the output voltage estimated value and the lumped disturbance estimated value in a natural coordinate system to obtain a normal component; based on the normal components of the output voltage estimation value and the lumped disturbance estimation value, obtaining the input gain of the high-order expansion observer through a fast gradient algorithm; substituting the input gain into the high-order expansion observer to update the observer, and performing output voltage estimation based on the updated high-order expansion observer to obtain an output voltage reference value; and generating a switching state based on the output voltage reference value and controlling the converter based on the switching state. According to the invention, the dependence of the control system on accurate inductance parameters can be eliminated, and the control precision and robustness of the converter system are improved.

Description

Technical Field

[0001] This application relates to the technical field of converter control, and particularly to a converter and its control method. Background Art

[0002] Traditional model predictive current control is widely used in converter systems due to its clear concept, fast dynamic response, etc. However, traditional model predictive current control highly depends on the accuracy of motor parameters (such as stator resistance, inductance, permanent magnet flux, etc.). When the parameters are mismatched due to factors such as temperature change and aging, the current tracking error increases, the total harmonic distortion significantly rises, and even the converter system becomes unstable. For example, parameter mismatch will lead to the degradation of the steady-state and dynamic performance of traditional model predictive current control, the current will have a steady-state error and increase the operating noise. Summary of the Invention

[0003] To solve the deficiencies of the prior art, the following technical solutions are adopted in this application: In a first aspect, a control method for a converter provided by this application, the control method includes the following steps: Obtain the output current of the converter system; Perform Clarke transformation on the output current to obtain αβ The current value in the two-phase stationary coordinate system; Based on the αβ Current value in the two-phase stationary coordinate system, obtain the output voltage estimation value and the lumped disturbance estimation value through an initialized high-order extended observer; Decompose the output voltage estimation value and the lumped disturbance estimation value in the natural coordinate system respectively to obtain the normal components of the output voltage estimation value and the lumped disturbance estimation value; Based on the normal components of the output voltage estimation value and the lumped disturbance estimation value, obtain the input gain of the high-order extended observer through the fast gradient algorithm; Substitute the input gain into the high-order extended observer to update the observer, and based on the updated high-order extended observer, re-perform output voltage estimation to obtain the output voltage reference value; Based on the output voltage reference value, generate the switching state of the converter and control the converter based on the switching state.

[0004] In summary, for the control method of a converter provided in the embodiments of the present application, a high-order extended observer is used to obtain the estimated value of the output voltage and the estimated value of the lumped disturbance of the converter system. The normal vectors of the estimated value of the output voltage and the estimated value of the lumped disturbance are obtained by the method of current decomposition, and thus the input gain of the high-order extended observer is obtained based on the fast gradient algorithm. By combining the high-order extended observer with the fast gradient algorithm, the online adjustment of the input gain of the high-order extended observer is realized, the parameter error is dynamically compensated, the debugging workload is reduced, so that the high-order extended observer can automatically optimize the parameters according to the operating state of the converter system, complete the estimation of the output voltage of the converter system, improve the control accuracy and robustness of the converter system; and by the way of current decomposition, the dependence of the control system on the accurate inductance parameters is eliminated, the performance degradation caused by parameter mismatch in the traditional control method is avoided, and the performance of the converter system is further improved.

[0005] Further, the high-order extended observer is configured to: at the discrete time scale, based on the actual output current at the k-th moment and the estimated value of the output current at the k-th moment calculate the estimation error at the k-th moment , and by constructing the linear feedback term, quadratic feedback term and cubic feedback term of the estimation error , obtain the estimated value of the output current at the (k + 1)-th moment , the estimated value of the lumped disturbance of the converter system at the (k + 1)-th moment and the estimated value of the lumped disturbance change rate in the iterative update, so as to realize the real-time compensation and state tracking of the uncertainty of the converter system.

[0006] Further, the linear feedback term of the error is configured to amplify the estimation error by three times the bandwidth, and the estimated value of the output current at the (k + 1)-th moment is obtained in the following way: based on the estimated value of the output current at the k-th moment , the product of the sampling period and the current estimation correction term is superimposed, and the current estimation correction term is configured to satisfy: the estimated value of the lumped disturbance of the converter system at the k-th moment , the output voltage at the k-th moment modulated by the input gain of the high-order extended observer, and the sum of the linear feedback term of the error ; The quadratic feedback term of the estimation error is configured to: the square of the estimation error is modulated by three times the bandwidth square; the estimated value of the lumped disturbance of the converter system at the (k + 1)-th moment Obtained by the following method: relying on the estimated value of the lumped disturbance of the converter system at time k , adding the product of the sampling period and the correction term of the lumped disturbance estimation, and the correction term of the lumped disturbance estimation is configured to satisfy: the estimation of the disturbance derivative and the estimation error of the sum of the quadratic feedback terms; The cubic feedback term of the estimation error is configured as: the cube of the estimation error is obtained by amplifying the bandwidth cube; the estimated value of the change rate of the lumped disturbance is obtained by the following method: based on the estimation of the disturbance derivative , adding the product of the sampling period and the cubic feedback term of the estimation error .

[0007] Furthermore, the fast gradient algorithm is represented by the following formula: ; In the formula, is gradient, and the input gain is obtained by the following formula : ; In the formula, and are two parameters for adjusting the step size, and the discrete form is as follows: ; In the formula, represents the tangential component of the lumped disturbance at time k, represents the tangential component of the output voltage at time k, represents the estimated value of the iteration step coefficient at time k + 1, represents the estimated value of the input gain at time k + 1, represents the selected step coefficient.

[0008] Furthermore, generating the switching state of the converter based on the output voltage reference value includes: Traversing the switching state to obtain the optimal switching state with the minimum cost function as the goal, and the cost function is a function related to the output voltage reference value.

[0009] Furthermore, the cost function is configured as: the sum of the first parameter, the second parameter, and the third parameter, where the first parameter is the component of the reference voltage at time k in direction and the first iThe component of a voltage vector in the direction, the square of the deviation of the reference voltage at the k-th moment in the direction, and the i component of the -th voltage vector in the direction. The third parameter is the product of the square of the midpoint voltage and the weight.

[0010] Further, the control method further includes calculating the midpoint voltage through the following steps: Multiply the absolute value of the switching state of the i -th voltage vector by the three-phase phase current respectively and sum them to obtain the midpoint current; Divide the midpoint current by twice the DC-side capacitor, multiply the result by the sampling period and superimpose the product result on the midpoint voltage at the current moment to reflect the charging and discharging effect of the midpoint current on the capacitor through discrete integration, so as to obtain the midpoint voltage at the next moment.

[0011] In a second aspect, the present application further provides a converter, and the converter includes: A neutral-point clamped three-phase inverter circuit for converting direct current into alternating current; a sampling module for sampling the output current of the neutral-point clamped three-phase inverter circuit; a processing module, and the processing module includes: A first coordinate transformation unit for performing Clarke transformation on the output current to obtain αβ the current value in the two-phase stationary coordinate system; A high-order extended observer for obtaining an output voltage estimation value and a lumped disturbance estimation value based on the αβ current value in the two-phase stationary coordinate system; A second coordinate transformation unit for respectively decomposing the output voltage estimation value and the lumped disturbance estimation value in the natural coordinate system to obtain the normal components of the output voltage estimation value and the lumped disturbance estimation value; A fast gradient processing unit for obtaining the input gain of the high-order extended observer through a fast gradient algorithm according to the normal components of the output voltage estimation value and the lumped disturbance estimation value; The processing module substitutes the input gain into the high-order extended observer to update the observer, based on the updated high-order extended observer, re-performs output voltage estimation to obtain an output voltage reference value, and based on the output voltage reference value, generates the switching state of the converter and controls the converter based on the switching state.

[0012] Furthermore, the high-order extended observer is configured to: on a discrete time scale, based on the actual output current at the k-th moment and the estimated value of the output current at the k-th moment calculate the estimation error at the k-th moment , and by constructing the linear feedback term, quadratic feedback term, and cubic feedback term of the estimation error , obtain the estimated value of the output current at the (k + 1)-th moment, the estimated value of the lumped disturbance of the converter system at the (k + 1)-th moment and the estimated value of the lumped disturbance change rate in iterative updates, so as to achieve real-time compensation for the uncertainty of the converter system and state tracking.

[0013] Furthermore, the fast gradient algorithm is represented by the following formula: ; In the formula, is the gradient of, and the input gain is obtained through the following formula : ; In the formula, and are two parameters for adjusting the step size, and the discrete form is as follows: ; In the formula, represents the tangential component of the lumped disturbance at the k-th moment, represents the tangential component of the output voltage at the k-th moment, represents the estimated value of the iteration step size coefficient at the (k + 1)-th moment, represents the estimated value of the input gain at the (k + 1)-th moment, represents the selected step size coefficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a flowchart of the steps of a control method for a converter provided by an embodiment of the present application; Figure 2 is a schematic diagram of coordinate decomposition in a natural coordinate system in a control method for a converter provided by an embodiment of the present application; Figure 3 is a control block diagram of applying a control method for a converter provided by an embodiment of the present application to a converter system; Figure 4 is a schematic diagram of the topology of a converter in a simulation experiment of a control method for a converter provided by an embodiment of the present application; Figure 5aSchematic diagram of the simulation results of the steady-state performance of the traditional FCS-MPC method provided by a comparative example of this application under the condition of system parameter matching; Figure 5b Schematic diagram of the simulation results of the steady-state performance of the ESO-based FCS-MPC method provided by a comparative example of this application under the condition of system parameter matching; Figure 5c Schematic diagram of the simulation results of the steady-state performance of the control method of the converter provided by an embodiment of this application under the condition of system parameter matching; Figure 6a Schematic diagram of the simulation results of the steady-state performance of the traditional FCS-MPC method provided by a comparative example of this application under the condition of system parameter mismatch; Figure 6b Schematic diagram of the simulation results of the steady-state performance of the ESO-based FCS-MPC method provided by a comparative example of this application under the condition of system parameter mismatch; Figure 6c Schematic diagram of the simulation results of the steady-state performance of the control method of the converter provided by an embodiment of this application under the condition of system parameter mismatch; Figure 7a Schematic diagram of the experimental results of the steady-state performance of the traditional FCS-MPC method provided by a comparative example of this application under the condition of system parameter matching; Figure 7b Schematic diagram of the experimental results of the steady-state performance of the ESO-based FCS-MPC method provided by a comparative example of this application under the condition of system parameter matching; Figure 7c Schematic diagram of the experimental results of the steady-state performance of the control method of the converter provided by an embodiment of this application under the condition of system parameter matching; Figure 8a Schematic diagram of the experimental results of the steady-state performance of the traditional FCS-MPC method provided by a comparative example of this application under the condition of system parameter mismatch; Figure 8b Schematic diagram of the experimental results of the steady-state performance of the ESO-based FCS-MPC method provided by a comparative example of this application under the condition of system parameter mismatch; Figure 8c Schematic diagram of the experimental results of the steady-state performance of the control method of the converter provided by an embodiment of this application under the condition of system parameter mismatch. Detailed implementation manners

[0015] The following will describe this application in detail in conjunction with the specific implementation manners shown in the drawings. However, these implementation manners do not limit this application, and any structural, method, or functional transformation made by those of ordinary skill in the art based on these implementation manners is included within the protection scope of this application.

[0016] To solve the deficiencies of the prior art, in a first aspect, embodiments of the present application provide a control method for a converter, as Figure 1 shown, the control method includes the following steps: Step S101: Obtain the output current of the converter system, perform Clarke transformation on the output current to obtain the current values in the αβ two-phase stationary coordinate system.

[0017] Step S102: Based on the current values in the αβ two-phase stationary coordinate system, obtain the output voltage estimation value and the lumped disturbance estimation value through an initialized high-order extended observer.

[0018] Step S103: Decompose the output voltage estimation value and the lumped disturbance estimation value in the natural coordinate system respectively to obtain the normal components of the output voltage estimation value and the lumped disturbance estimation value.

[0019] Step S104: Based on the normal components of the output voltage estimation value and the lumped disturbance estimation value, obtain the input gain of the high-order extended observer through the fast gradient algorithm.

[0020] Step S105: Substitute the input gain into the high-order extended observer to update the observer, and based on the updated high-order extended observer, re-perform the output voltage estimation to obtain the output voltage reference value.

[0021] Step S106: Based on the output voltage reference value, generate the switching state of the converter and control the converter based on the switching state.

[0022] Specifically, collect and obtain the output current of the converter system. The output current data can reflect the actual load state of the converter system during operation. Exemplarily, taking a three-level neutral-point clamped converter as an example, its output current is a three-phase alternating current i a 、 i b 、 i c , and the output current can be expressed by the following formula: ; In the formula, i represents the output current, u represents the output voltage, R represents the load resistance, and L represents the load inductance.

[0023] Perform Clarke transformation on the obtained output current to convert the current in the three-phase stationary coordinate system into αβ the current values in the two-phase stationary coordinate system, eliminate the redundancy of the three-phase system through linear algebraic operations, simplify the mathematical model to reduce the computational complexity, decouple the complex coupling problem of the three-phase system into two independent orthogonal components, so as to use the high-order extended observer for state estimation.

[0024] Based on the converted αβ Under the two-phase stationary coordinate system, the current value, in step S102, initializes the high-order extended observer, integrates the disturbances during the operation of the converter system into the lumped disturbance, estimates the lumped disturbance and the state of the converter system through the high-order extended observer, and obtains the estimated output voltage value and the estimated lumped disturbance value of the converter system. The high-order extended observer observes and evaluates the lumped disturbance, accurately estimates the system state without relying on an accurate motor model, effectively compensates for the errors caused by parameter mismatch, and improves the robustness of the control strategy.

[0025] Optionally, in the embodiments of the present application, according to the principle of the high-order extended observer, the mathematical model of the second-order extended observer can be expressed by the following formula: ; In the formula, e represents the estimation error; represents the estimated value of the output current i, represents the first derivative of; represents the bandwidth of the high-order extended observer; represents the lumped disturbance, and ; is the derivative of, represents the estimated value of, represents the first derivative of; represents the input gain of the high-order extended observer, and .

[0026] The output current i of the converter system can be decomposed into a tangential component and a normal component in the natural coordinate system. The output current vector i is in the same direction as the normal component of the natural coordinate system, and the output current vector i is perpendicular to the tangential component of the natural coordinate system. The direction of the output current vector is always in the same direction as the normal component of the natural coordinate system, ensuring that the current i n is always zero. As Figure 2 shown, the obtained estimated output voltage value and the estimated lumped disturbance value are respectively decomposed in the natural coordinate system. In the figure, f t represents the tangential component of the estimated lumped disturbance value, f n represents the normal component of the estimated lumped disturbance value, u t represents the tangential component of the estimated output voltage value, u n represents the normal component of the estimated output voltage value.

[0027] Based on the obtained estimated output voltage and the normal component of the lumped disturbance estimate, there is the following quantitative relationship: ; In the formula, f n represents the normal component of the lumped disturbance estimate, u n represents the normal component of the estimated output voltage, L represents the load inductance value of the converter system at the current moment, represents the load inductance value of the converter system at the initial moment.

[0028] According to the above analysis, in step 104, taking the normal component error as the objective function, the input gain of the high-order extended observer is calculated using the fast gradient algorithm, and the high-order extended observer is adaptively adjusted through the input gain to avoid the problem of insufficient robustness caused by fixed parameters in the traditional control method and eliminate the influence of parameter mismatch on the control system. In the embodiment of the present application, the objective function can be expressed by the following formula: ; In the formula, represents the input gain of the high-order extended observer, represents the objective function value.

[0029] 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 to update the parameters in the high-order extended observer 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 corrected and updated through the input gain, and then the state of the converter system 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, so as to control the converter based on the switching state to maintain the stable operation of the converter and the balance of the midpoint potential.

[0030] According to the above description, a control method for a converter provided by an embodiment of the present application uses a high-order extended observer to obtain an estimated value of the output voltage and an estimated value of the lumped disturbance of the converter system, obtains the normal vector of the estimated value of the output voltage and the estimated value of the lumped disturbance through a current decomposition method, thereby obtains the input gain of the high-order extended observer based on the fast gradient algorithm, and realizes the online adjustment of the input gain of the high-order extended observer by combining the high-order extended observer with the fast gradient algorithm, dynamically compensates for parameter errors and reduces 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 estimation of the output voltage of the converter system, improve the control accuracy and robustness of the converter system; and by means of current decomposition, eliminates the dependence of the control system on accurate inductance parameters, avoids the performance degradation caused by parameter mismatch of traditional control methods, and further improves the performance of the converter system.

[0031] As an alternative implementation, in step S102, based on the current values in the αβ two-phase stationary coordinate system, an estimated value of the output voltage and an estimated value of the lumped disturbance are obtained through an initialized high-order extended observer. The high-order extended observer is configured to: at the discrete time scale, based on the actual output current at the k-th moment and the estimated value of the output current at the k-th moment calculate the estimation error at the k-th moment , and by constructing the linear feedback term, quadratic feedback term, and cubic feedback term of the estimation error , obtain the estimated value of the output current at the (k + 1)-th moment , the estimated value of the lumped disturbance of the converter system at the (k + 1)-th moment and the estimated value of the lumped disturbance change rate in the iterative update, so as to realize the real-time compensation and state tracking of the uncertainty of the converter system.

[0032] Furthermore, in the high-order extended observer, the linear feedback term of the error is configured to amplify the estimation error by three times the bandwidth. The estimated value of the output current at the (k + 1)-th moment is obtained in the following way: based on the estimated value of the output current at the k-th moment , superimpose the product of the sampling period and the current estimation correction term. The current estimation correction term is configured to satisfy: the estimated value of the lumped disturbance of the converter system at the k-th moment , the output voltage at the k-th moment and the product of the input gain of the high-order extended observer, and the sum of the linear feedback term of the error .

[0033] Furthermore, in the high-order extended observer, the estimation error The quadratic feedback term is configured as: the estimated error obtained by modulating the square of the estimated error by three times the square of the bandwidth. The estimated value of the lumped disturbance of the converter system at the (k + 1)-th moment is obtained by relying on the estimated value of the lumped disturbance of the converter system at the k-th moment , adding the product of the sampling period and the correction term of the lumped disturbance estimation, and the correction term of the lumped disturbance estimation is configured to satisfy: the sum of the estimated value of the disturbance derivative and the quadratic feedback term of the estimated error .

[0034] Furthermore, in the high-order extended observer, the cubic feedback term of the estimated error is configured as: the cube of the estimated error amplified by the cube of the bandwidth; the estimated value of the change rate of the lumped disturbance is obtained by taking the estimated value of the disturbance derivative as the basis, and adding the product of the sampling period and the cubic feedback term of the estimated error .

[0035] In one embodiment, the high-order extended observer can be expressed by the following formula: ; wherein, represents the sampling time, k represents the moment, represents the actual output current at the k-th moment, represents the estimated value of the output current at the k-th moment, represents the estimated error at the k-th moment, represents the input gain of the high-order extended observer, represents the lumped disturbance of the converter system at the k-th moment, represents the estimated value of the lumped disturbance of the converter system at the k-th moment, represents the output voltage at the k-th moment, represents the bandwidth of the high-order extended observer; is the derivative of, represents the change rate of the lumped disturbance of the converter system; represents the estimated value of the change rate of the lumped disturbance of the converter system.

[0036] After obtaining the estimated output voltage value and the estimated lumped disturbance value, the estimated output voltage value and the estimated lumped disturbance value are respectively decomposed in the natural coordinate system, so as to obtain the normal components of the estimated output voltage value and the estimated lumped disturbance value. Further, in step S104, based on the normal components of the estimated output voltage value and the estimated lumped disturbance value, the input gain of the high-order extended observer is obtained through the fast gradient algorithm. As an optional implementation, the fast gradient algorithm can be expressed by the following formula: ; In the formula, is The gradient of, and the input gain of the high-order extended observer is obtained through the following formula : ; In the formula, represents the estimated value of the input gain , and are two parameters for adjusting the step size, represents the learning rate, represents the iteration step size coefficient, and The discrete forms of are as follows: ; In the formula, represents the tangential component of the lumped disturbance at the k-th moment, represents the tangential component of the output voltage at the k-th moment, represents the estimated value of the iteration step size coefficient at the (k + 1)-th moment, represents the estimated value of the input gain at the (k + 1)-th moment, represents the selected step size coefficient.

[0037] Further, 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 estimated again to obtain the output voltage reference value. As an optional implementation, the high-order extended observer estimates the output voltage of the converter system by predicting the output current of the converter system and based on the predicted output current through the following formula: ; In the formula, u ( k ) * represents the output voltage reference value, i ref is the reference value of the current, i ( k ) is the output current at the k-th moment.

[0038] As an alternative implementation, the control method provided by the embodiments of the present application further includes: Step S106, generating the switching state of the converter based on the obtained output voltage reference value, traversing all the switching states, obtaining the optimal switching state with the minimum cost function as the goal, and controlling the converter based on the optimal switching state. Exemplarily, in the embodiments of the present application, the three-level neutral-point clamped converter has 27 possible switching states, thus having 27 possible voltage vectors. By traversing all the switching states, comparing the cost function values of all the switching states, and selecting the switching state that makes the cost function minimum as the optimal switching state, the converter is controlled based on the optimal switching state to ensure the stable operation of the converter and the balance of the neutral-point voltage.

[0039] Further, the cost function is configured as the sum of a first parameter, a second parameter, and a third parameter, where the first parameter is the component of the reference voltage at the k-th moment in the direction and the i -th voltage vector in the direction of the square of the deviation, the second parameter is the component of the reference voltage at the k-th moment in the direction and the i -th voltage vector in the direction of the square of the deviation, and the third parameter is the product of the square of the neutral-point voltage and the weight.

[0040] 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 deviations of the component of the reference voltage at the current moment in the direction are calculated respectively, the two deviation values are squared and added, and then the product of the square of the neutral-point voltage and the weight is superimposed. By integrating the constraints of the voltage tracking error and the neutral-point voltage fluctuation, a quantitative index is provided for the optimal selection of the voltage vector. Further, the cost function can be expressed by the following formula: ; In the formula, is the first parameter, and respectively represent the components of the reference voltage at the k-th moment in the direction; is the second parameter, and respectively represent the components of the -th voltage vector in the direction; is the third parameter, represents the neutral-point voltage, Indicates the weight of the midpoint voltage in the cost function.

[0041] As an alternative implementation, the control method further includes calculating the midpoint voltage through the following steps: Multiply the absolute value of the switching state of the i ith voltage vector by the three-phase phase current respectively and sum them to obtain the midpoint current; Divide the midpoint current by twice the DC-side capacitor and multiply it by the sampling period and add the product result to 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.

[0042] Among them, the midpoint current can be calculated through the following formula: ; In the formula, i a , i b , i c represent the currents of each phase of the converter, represents the absolute value of the switching state of the ith voltage vector.

[0043] The midpoint voltage at the next moment can be calculated through the following formula: ; In the formula, i n ( k ) represents the midpoint current at the current moment, v n ( k ) represents the midpoint voltage at the current moment, represents the midpoint voltage at the next moment, represents the sampling time, C dc represents the bus capacitor on the DC side.

[0044] 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 as Figure 3 shown. First, the control system performs a Clarke transformation on the output current i abc of the converter system to obtain the current value i αβ in the αβ two-phase stationary coordinate system; Based on the current value i αβ in the αβ two-phase stationary coordinate system, the output voltage estimated value u αβ and the lumped disturbance estimated value f αβ; based on the current value in the αβ two-phase stationary coordinate system i αβ , the estimated output voltage u αβ and the estimated lumped disturbance f αβ , decompose the estimated output voltage u αβ and the estimated lumped disturbance f αβ in the natural coordinate system to obtain the normal component of the estimated output voltage u n and the estimated lumped disturbance f n ; and based on the normal component of the estimated output voltage u n and the estimated lumped disturbance f n , calculate the input gain α of the high-order extended observer through the fast gradient algorithm; then, substitute the input gain α into the high-order extended observer for observer update, and based on the updated high-order extended observer, re-estimate the output voltage to obtain the output voltage reference value v αβ ; and based on the output voltage reference value v αβ , traverse all switching states through the cost function to minimize the cost function as the goal to obtain the optimal switching state S abc , control the converter based on the switching state S abc to achieve the control goal of the converter system.

[0045] To further illustrate a control method for a converter provided by an embodiment of the present application, the following is a simulation test and an experimental test. By comparing 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 by the embodiment of the present application, the effectiveness of the control method provided by the embodiment of the present application is verified. As Figure 4As shown, in the simulation experiment, the converter uses a neutral-point 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. Among them, the control period of the digital signal processor is 100 μs; the resistance value of the RL load is set to 1 Ω, and the inductance value L is 10 mH; to verify the situation of parameter mismatch, the inductance value is set to 8 mH in the experiment. In terms of the software module, for the initialization of the inductance parameter, the bandwidth of the high-order extended observer is set from 500 to 3000, and the learning rate is equal to 1, and the iteration step coefficient is 0.03.

[0046] First of all, the steady-state performances of the above three control methods are simulated and compared. Under the condition of system parameter matching (inductance value L = 10 mH), the steady-state performance simulation results of the traditional FCS-MPC method are as Figure 5a shown. Under the control of the traditional FCS-MPC method, the THD (Total Harmonic Distortion) of the output current of the inverter is 1.12%; the steady-state performance simulation results of the FCS-MPC method based on ESO are as Figure 5b shown. Under the control of the FCS-MPC method based on ESO, the THD of the output current of the inverter is 1.03%; the steady-state performance simulation results of the control method provided by the embodiment of the present application are as Figure 5c shown. Under the control of this control method, the THD of the output current of the inverter is 0.97%. Compared with the traditional control method, the relative reduction of THD of the control method provided by the embodiment of the present application reaches 13.4%; compared with the FCS-MPC method based on ESO, the relative reduction of THD of the control method provided by the embodiment of the present application reaches 5.93%. It can be concluded that under the condition of system parameter matching, the control method provided by the embodiment of the present application has better harmonic suppression ability than the previous two control methods.

[0047] Under the condition of system parameter mismatch (inductance value L = 8 mH), the steady-state performance simulation results of the traditional FCS-MPC method are as Figure 6a shown. Under the control of the traditional FCS-MPC method, the THD of the output current of the inverter is 1.28%; the steady-state performance simulation results of the FCS-MPC method based on ESO are as Figure 6b shown. Under the control of the FCS-MPC method based on ESO, the THD of the output current of the inverter is 1.22%; the steady-state performance simulation results of the control method provided by the embodiment of the present application are as Figure 6cAs shown, the THD of the output current of the inverter under the control of this control method is 1.21%. Compared with the traditional control method, the relative reduction of THD of the control method provided by the embodiment of the present application reaches 5.5%; compared with the FCS-MPC method based on ESO, the relative reduction of THD of the control method provided by the embodiment of the present application reaches 0.8%. It can be concluded that even under the condition of system parameter mismatch, the control method provided by the embodiment of the present application still has better harmonic suppression ability than the former two control methods.

[0048] Furthermore, the steady-state performances of the above three control methods are experimentally compared. Under the condition of system parameter matching (inductance value L = 10 mH), the experimental results of the steady-state performance of the traditional FCS-MPC method are as Figure 7a shown. The THD of the output current of the inverter under the control of the traditional FCS-MPC method is 2.47%; the experimental results of the steady-state performance of the FCS-MPC method based on ESO are as Figure 7b shown. The THD of the output current of the inverter under the control of the FCS-MPC method based on ESO is 1.24%; the experimental results of the steady-state performance of the control method provided by the embodiment of the present application are as Figure 7c shown. The THD of the output current of the inverter under the control of this control method is 0.97%. It can be seen from the experimental waveforms that the current distortion of the inverter 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 relative reduction of THD of the control method provided by the embodiment of the present application reaches 21.8%. It can be concluded that under the condition of system parameter matching, the control method provided by the embodiment of the present application has better harmonic suppression ability than the former two control methods.

[0049] Under the condition of system parameter mismatch (inductance value L = 8 mH), the experimental results of the steady-state performance of the traditional FCS-MPC method are as Figure 8a shown. The THD of the output current of the inverter under the control of the traditional FCS-MPC method is 4.23%; the experimental results of the steady-state performance of the FCS-MPC method based on ESO are as Figure 8b shown. The THD of the output current of the inverter under the control of the FCS-MPC method based on ESO is 1.83%; the experimental results of the steady-state performance of the control method provided by the embodiment of the present application are as Figure 8cAs shown, the THD of the output current of the inverter under the control of this control method is 1.41%. It can be seen from the experimental waveforms that under the control method provided in the embodiments of this application, the current distortion of the inverter is significantly reduced. Compared with the traditional control method, the relative reduction of THD of the control method provided in the embodiments of this application reaches 66.7%; compared with the FCS-MPC method based on ESO, the relative reduction of THD of the control method provided in the embodiments of this application reaches 22.9%. It can be concluded that even under the condition of system parameter mismatch, the control method provided in the embodiments of this application still has better harmonic suppression ability than the former two control methods, can ensure the stable operation of the system, and effectively improve the anti-interference ability of the system.

[0050] The comparative analysis of the implementation results shows that under the traditional control method and the FCS-MPC method based on ESO, the current quality of the inverter has a significant dependence on the controller parameter matching degree, and its THD index shows an obvious deterioration trend with the increase of the parameter adaptation degree. The control method provided in the embodiments of this application can effectively overcome the defect of parameter sensitivity, making the control method have stronger robustness and engineering applicability, and is more suitable for application scenarios with parameter changes or measurement errors.

[0051] According to the above description, a control method for a converter provided in the embodiments of this application uses a high-order extended observer to obtain the estimated value of the output voltage and the estimated value of the lumped disturbance of the converter system, obtains the normal vectors of the estimated value of the output voltage and the estimated value of the lumped disturbance through the method of current decomposition, and thus obtains the input gain of the high-order extended observer based on the fast gradient algorithm. Through the combination of the high-order extended observer and the fast gradient algorithm, the online adjustment of the input gain of the high-order extended observer is realized, the parameter error is dynamically compensated to reduce the debugging workload, so that the high-order extended observer can automatically optimize the parameters according to the operating state of the converter system, complete the estimation of the output voltage of the converter system, improve the control accuracy and robustness of the converter system; through the calculation of the cost function, select the switching state that makes the cost function the smallest to control the converter system, realize the precise control of the converter system, ensure the stable operation of the converter system and the balance of the midpoint voltage; and through the method of current decomposition, eliminate the dependence of the control system on the precise inductance parameters, avoid the performance degradation caused by parameter mismatch in the traditional control method, and further improve the performance of the converter system.

[0052] Second aspect, based on the same inventive concept, an embodiment of the present application further provides an inverter, which includes a neutral-point clamped three-phase inverter circuit, a sampling module, and a processing module. The neutral-point clamped three-phase inverter circuit is used to convert direct current into alternating current; the sampling module is used to collect the output current of the neutral-point clamped three-phase inverter circuit. The processing module includes a first coordinate transformation unit, a high-order extended observer, a second coordinate transformation unit, and a fast gradient processing unit. Among them, the first coordinate transformation unit is used to perform Clarke transformation on the output current to obtain the current value in the αβ two-phase stationary coordinate system; the high-order extended observer is used to obtain the estimated output voltage value and the lumped disturbance estimated value based on the current value in the αβ two-phase stationary coordinate system; the second coordinate transformation unit is used to decompose the estimated output voltage value and the lumped disturbance estimated value in the natural coordinate system respectively to obtain the normal components of the estimated output voltage value and the lumped disturbance estimated value; the fast gradient unit is used to obtain the input gain of the high-order extended observer through the fast gradient algorithm according to the normal components of the estimated output voltage value and the lumped disturbance estimated value.

[0053] The processing module substitutes the input gain into the high-order extended observer to update the observer. Based on the updated high-order extended observer, the output voltage is estimated again to obtain the output voltage reference value, and based on the output voltage reference value, the switching state of the inverter is generated and the inverter is controlled based on the switching state.

[0054] As an optional implementation manner, in the processing module, based on the current value in the αβ two-phase stationary coordinate system, the estimated output voltage value and the lumped disturbance estimated value are obtained through a high-order extended observer. The high-order extended observer is configured to: on a discrete time scale, based on the actual output current at the k-th moment and the estimated value of the output current at the k-th moment calculate the estimation error at the k-th moment , and by constructing the linear feedback term, quadratic feedback term, and cubic feedback term of the estimation error , obtain the estimated value of the output current at the (k + 1)-th moment , the estimated value of the lumped disturbance of the inverter system at the (k + 1)-th moment and the estimated value of the change rate of the lumped disturbance in the iterative update, so as to realize the real-time compensation and state tracking of the uncertainty of the inverter system.

[0055] In one embodiment, the high-order extended observer can be expressed by the following formula: ; In the formula, represents the sampling time, k represents the moment, represents the output current at the k-th moment, represents the estimation error of the output current at the k-th moment, denotes the estimation error at the k-th moment, represents the input gain of the high-order extended observer, denotes the lumped disturbance of the converter system at the k-th moment, represents the estimated value of the lumped disturbance of the converter system at the k-th moment, denotes the output voltage at the k-th moment, represents the bandwidth of the high-order extended observer; is the derivative of, denotes the change rate of the lumped disturbance of the converter system; represents the estimated value of the change rate of the lumped disturbance of the converter system.

[0056] The high-order extended observer is configured to predict the output current, and based on the predicted output current, estimate the output voltage of the converter system through the following formula: ; wherein, u ( k ) * represents the output voltage reference value, i ref represents the reference value of the current, i ( k ) is the output current at the k-th moment.

[0057] As an alternative implementation, in the processing module, the fast gradient unit obtains the input gain of the high-order extended observer through the fast gradient algorithm, and the fast gradient algorithm can be expressed by the following formula: ; wherein, is the gradient of, f n is f the normal component of, u n is u the normal component of. Further, the input gain is obtained through the following formula

[0058] ; wherein, and are two parameters for adjusting the step size, and the discrete form is as follows: ; wherein, denotes the tangential component of the lumped disturbance at the k-th moment, denotes the tangential component of the output voltage at the k-th moment, represents the estimated value of the iteration step coefficient at the (k + 1)-th moment, represents the estimated value of the input gain at the (k + 1)-th moment, represents the selected step coefficient.

[0059] As an alternative implementation, in the processing module, based on the output voltage reference value, generating the switching state of the converter includes: traversing the switching states to obtain the optimal switching state with the goal of minimizing the cost function. Among them, 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: ; In the formula, and respectively represent the components of the reference voltage at the k-th moment in the direction, and respectively represent the components of the -th voltage vector in the direction, represents the midpoint voltage, represents the weight of the midpoint voltage in the cost function.

[0060] represents the midpoint voltage, and the midpoint voltage can be calculated by the following formula: ; ; In the formula, i n ( k ) represents the midpoint current, i a , i b , i c represent the phase currents of the converter, v n ( k ) represents the midpoint voltage, represents the sampling time, represents the absolute value of the switching state of the

[0061] According to the above description, a converter provided by an embodiment of the present application uses a high-order extended observer to obtain an estimated value of the output voltage and an estimated value of the lumped disturbance of the converter system, obtains the normal vectors of the estimated value of the output voltage and the estimated value of the lumped disturbance through a current decomposition method, and thus obtains the input gain of the high-order extended observer based on the fast gradient algorithm. By combining the high-order extended observer with the fast gradient algorithm, the online adjustment of the input gain of the high-order extended observer is realized, the dynamic compensation of parameter errors reduces the debugging workload, enables the high-order extended observer to automatically optimize parameters according to the operating state of the converter system, completes the estimation of the output voltage of the converter system, and improves the control accuracy and robustness of the converter system; through cost function calculation, the switching state that minimizes the cost function is selected to control the converter system, realizes the precise control of the converter system, and ensures the stable operation and midpoint voltage balance of the converter system; and through the current decomposition method, the dependence of the control system on the precise inductor parameters is eliminated, avoiding the performance degradation caused by parameter mismatch in the traditional control method, and further improving the performance of the converter system.

[0062] It can be understood that the term "exemplary" used herein means "serving as an example, instance, or illustration". Any embodiment described as "exemplary" is not necessarily preferred over or superior to other embodiments and / or does not exclude combining the features of other embodiments. It should be understood that certain features of the present application described in the context of separate embodiments can also be provided in combination in a single embodiment for clarity. Conversely, the various features of the present application described in the context of a single embodiment can also be provided separately or in any suitable combination or as any other described embodiment of the present application.

[0063] In the description of the present application, unless otherwise specified, " / " means "or". For example, A / B can represent A or B. The "and / or" herein is merely a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, "at least one" means one or more, and "a plurality" means two or more. The terms "first", "second", etc. do not limit the quantity and execution order, and the terms "first", "second", etc. do not necessarily limit being different.

[0064] The above-disclosed are only the preferred embodiments of the present application, but they are not intended to limit the scope of the rights of the present application. Those of ordinary skill in the art can understand that within 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 covered by the invention.

Claims

1. A control method for an inverter, characterized in that The control method includes the following steps: Obtain the output current of the converter system; Perform Clarke transformation on the output current to obtain αβ the current value in the two-phase stationary coordinate system; Based on the αβ current values in the two-phase stationary coordinate system, the output voltage estimation value and the lumped disturbance estimation value are obtained through the initialized high-order extended observer; Decompose the output voltage estimate and the lumped disturbance estimate in the natural coordinate system respectively to obtain the normal components of the output voltage estimate and the lumped disturbance estimate; Based on the normal components of the output voltage estimate and the lumped disturbance estimate, obtain the input gain of the high-order extended observer through the fast gradient algorithm; Substitute the input gain into the high-order extended observer to update the observer. Based on the updated high-order extended observer, re-estimate the output voltage to obtain the output voltage reference value; Based on the output voltage reference value, generate the switching state of the converter and control the converter based on the switching state.

2. The control method of the converter according to claim 1, wherein The high-order extended observer is configured to: at the discrete time scale, based on the actual output current at the k-th moment and the estimated value of the output current at the k-th moment calculate the estimation error at the k-th moment , and by constructing the linear feedback term, quadratic feedback term and cubic feedback term of the said estimation error , obtain the estimated value of the output current at the (k + 1)-th moment , the estimated value of the lumped disturbance of the converter system at the (k + 1)-th moment and the estimated value of the change rate of the lumped disturbance in the iterative update, so as to realize the real-time compensation and state tracking of the uncertainty of the said converter system.

3. The control method of the converter according to claim 2, wherein The error 's linear feedback term is configured to amplify the estimated error by three times the bandwidth, and the estimated value of the output current at the (k + 1)-th moment is obtained as follows: based on the estimated value of the output current at the k-th moment , the product of the sampling period and the current estimation correction term is superimposed. The current estimation correction term is configured to satisfy: the estimated value of the lumped disturbance of the converter system at the k-th moment , the output voltage at the k-th moment modulated by the input gain of the high-order extended observer feedforward term, and the sum of the linear feedback term of the error ; The estimation error The quadratic feedback term of is configured such that: the square of the estimation error is obtained through triple bandwidth squared modulation; the estimated value of the lumped disturbance of the converter system at the (k + 1)-th moment is obtained in the following manner: relying on the estimated value of the lumped disturbance of the converter system at the k-th moment , and adding the product of the sampling period and the correction term of the lumped disturbance estimation, where the correction term of the lumped disturbance estimation is configured to satisfy: the sum of the estimated value of the disturbance derivative and the quadratic feedback term of the estimation error ; The estimated error The cubic feedback term of which is configured such that the cube of the estimated error is obtained by amplifying the bandwidth cube; the estimated value of the lumped disturbance change rate is obtained by the following method: based on the estimation of the disturbance derivative , the product of the sampling period and the cubic feedback term of the estimated error is superimposed and obtained.

4. The control method of the converter according to claim 1, wherein The fast gradient algorithm is represented by the following formula: ； In the formula, is the gradient of, and the input gain is obtained through the following formula : ； In the formula, and are two parameters for adjusting the step size, and the discrete form is as follows: ； wherein, represents the tangential component of the lumped disturbance at the k-th moment, represents the tangential component of the output voltage at the k-th moment, represents the estimated value of the iteration step coefficient at the (k + 1)-th moment, represents the estimated value of the input gain at the (k + 1)-th moment, represents the iteration step coefficient.

5. The control method of the converter according to claim 1, wherein Generating the switching state of the converter based on the output voltage reference value includes: Traverse the switching states to obtain the optimal switching state with the minimum cost function as the goal, and the cost function is a function related to the output voltage reference value.

6. The control method of the converter according to claim 5, wherein The cost function is configured as the sum of a first parameter, a second parameter, and a third parameter, where the first parameter is the component of the reference voltage at the k-th moment in the direction and the component of the i th voltage vector in the direction The square of the deviation, the second parameter is the component of the reference voltage at the k-th moment in the direction and the component of the i th voltage vector in the direction The square of the deviation, and the third parameter is the product of the square of the midpoint voltage and the weight.

7. The control method of the converter according to claim 6, characterized in that The control method further includes calculating the midpoint voltage through the following steps: Multiply the absolute value of the switching state of the i th voltage vector by the three-phase phase current respectively and sum them to obtain the neutral point current; Divide the midpoint current by twice the DC-side capacitance and multiply the result by the sampling period and add the product to the midpoint voltage at the current moment to reflect the charging and discharging effect of the midpoint current on the capacitance through discrete integration, thereby obtaining the midpoint voltage at the next moment.

8. A current converter, characterized in that, The converter includes: A neutral-point clamped three-phase inverter circuit for converting direct current into alternating current; A sampling module for collecting the output current of the neutral-point clamped three-phase inverter circuit; A processing module, and the processing module includes: The first coordinate transformation unit is configured to perform Clarke transformation on the output current to obtain αβ the current value in the two-phase stationary coordinate system; High-order extended observer, which is used to obtain an estimated output voltage value and an estimated lumped disturbance value based on the αβ current value in the two-phase stationary coordinate system; A second coordinate transformation unit for decomposing the output voltage estimate and the lumped disturbance estimate in the natural coordinate system respectively to obtain the normal components of the output voltage estimate and the lumped disturbance estimate; A fast gradient processing unit for obtaining the input gain of the high-order extended observer through the fast gradient algorithm according to the normal components of the output voltage estimate and the lumped disturbance estimate; The processing module substitutes the input gain into the high-order extended observer to update the observer. Based on the updated high-order extended observer, re-estimate the output voltage to obtain the output voltage reference value, and based on the output voltage reference value, generate the switching state of the converter and control the converter based on the switching state.

9. The converter according to claim 8, characterized in that, The high-order extended observer is configured to: on a discrete time scale, based on the actual output current at the k-th moment and the estimated value of the output current at the k-th moment calculate the estimation error at the k-th moment , and by constructing the linear feedback term, quadratic feedback term, and cubic feedback term of the estimation error , obtain the estimated value of the output current at the (k + 1)-th moment , the estimated value of the lumped disturbance of the converter system at the (k + 1)-th moment and the estimated value of the change rate of the lumped disturbance in the iterative update, so as to achieve real-time compensation for the uncertainty of the converter system and state tracking.

10. The converter according to claim 8, wherein The fast gradient algorithm is represented by the following formula: ； In the formula, is 's gradient, and the input gain is obtained through the following formula : ； In the formula, and are two parameters for adjusting the step size, and the discrete form is as follows: ； wherein, represents the tangential component of the lumped disturbance at the k-th moment, represents the tangential component of the output voltage at the k-th moment, represents the estimated value of the iteration step coefficient at the (k + 1)-th moment, represents the estimated value of the input gain at the (k + 1)-th moment, represents the iteration step coefficient.

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