Model predictive control method and device for improved quasi-y source dc-dc converter

Abstract

The application discloses a model prediction control method and device for an improved quasi-Y source DC-DC converter, and relates to the technical field of DC-DC converters. The method solves the problems of poor output voltage stability of the converter and inflexible duty ratio regulation. The method comprises the following steps: obtaining a state equation of an improved quasi-Y source DC-DC converter system and an input / output voltage relationship; discretizing the state equation by taking an inductor current and a capacitor voltage as control variables to obtain a voltage prediction model; combining a moving discrete control set model prediction control algorithm with the voltage prediction model to predict an output voltage; and selecting a suitable cost function to measure the output performance of the prediction control and control the output voltage. The application is applied to the field of industrial automation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of DC-DC converter, and particularly relates to a model prediction control method of an improved quasi-Y-source DC-DC converter. BACKGROUND

[0002] The design of a boost DC-DC converter with continuous input current and wide voltage gain range is one of the most challenging requirements for many distributed generation and regulation systems, especially when using intermittent power sources such as fuel cells, photovoltaic panels and wind turbines. In order to meet this challenging requirement, various impedance networks have been developed to achieve the goal of wide range voltage gain, high power conversion efficiency.

[0003] The Y-source impedance network uses three-end coupled inductors for energy transfer, and the turn ratio design is very flexible, and the turn ratio and total turn of the coupled inductor can be kept in a relatively small range. The improved quasi-Y-source DC-DC converter realizes the effects of high voltage gain, high transmission efficiency, continuous input current, suppression of starting impulse current and low DC link voltage peak by adjusting the conduction duty ratio of the switch tube and the turn ratio of the coupled inductor.

[0004] For the existing Y-source control mode, a fixed duty ratio switch control signal is usually given from the outside to make the converter output voltage reach the reference value, and the duty ratio of the switch cannot be automatically adjusted according to the difference between the output voltage and the reference value, resulting in poor anti-interference of the converter and significantly reducing the stability and flexibility.

[0005] Therefore, how to overcome the poor stability of the converter output voltage and the inflexible duty ratio adjustment on the basis of the improved quasi-Y-source DC-DC converter control is a technical problem that has not been solved in the art. SUMMARY

[0006] The present application proposes a model prediction control method of an improved quasi-Y-source DC-DC converter to overcome the poor stability of the converter output voltage and the inflexible duty ratio adjustment, and the specific scheme is as follows:

[0007] A model prediction control method based on an improved quasi-Y-source DC-DC converter, the method comprising:

[0008] S1: obtaining the state equation of the improved quasi-Y-source DC-DC converter system and the input / output voltage relationship;

[0009] S2: discretizing the state equation by taking the inductor current and the capacitor voltage as control variables to obtain a voltage prediction model;

[0010] S3: combining the moving discrete control set model predictive control algorithm with the voltage prediction model to predict the output voltage;

[0011] S4: selecting a suitable cost function to measure the output performance of the prediction control and controlling the output voltage.

[0012] Further, an improved quasi-Y source DC-DC converter system is provided, and the state equation and the input / output voltage relationship in step S1 are specifically as follows:

[0013]

[0014] wherein U0 is the output voltage of the converter, U in is the output current of the converter, I C5 is the current flowing through the capacitor C5, R is the output circuit load, K is the winding factor of the improved quasi-Y source converter, D is the through duty ratio, and t is time.

[0015] Further, an improved quasi-Y source converter winding factor K is provided, and the winding factor K is determined by the turns ratio N1:N2:N3 of the three-winding coupled inductance of the improved quasi-Y source converter, and the calculation formula is as follows:

[0016]

[0017] Further, the step S2 includes:

[0018] The output voltage and the output current are taken as control variables, the state equation of the improved quasi-Y source DC-DC converter system is discretized by the forward Euler method, and the discrete formula of the output voltage is obtained:

[0019]

[0020] wherein k is a certain control instant, T is a switching period, U0(k) is the output voltage at time k, U0(k+1) is the output voltage at time k+1, and I0(k) is the output current at time k.

[0021] Further, the step S3 includes:

[0022] The moving discrete control set model predictive control algorithm is used to calculate the value function in each control period, and the optimal control compensation from the sampling time to the prediction time is applied to the converter;

[0023] At the control time k, the initial value of the duty ratio D is defined as d, and in the control interval k~k+1, the moving discrete control calculation formula of D(k+1) is as follows:

[0024] D(k+1) = D(k) + AD(k) = d + {-4AD, -3AD, -2AD, -AD, 0, AD, 2AD, 3AD, 4AD}

[0025] Wherein, D(k+1) is the value of the duty ratio D at k+1 time, D(k) is the value of the duty ratio D at k time, AD(k) is the change of the duty ratio in k~k+1 control interval, AD is the discrete accuracy.

[0026] Further, an optimal mode is further provided, and the rolling number of the moving discrete control set model predictive control algorithm in each control period is 9.

[0027] Further, an optimal mode is further provided, and the step S4 comprises:

[0028] J = (U0(k+1) - U ref ) 2

[0029] Wherein, J is a cost function, U ref is an output voltage reference value.

[0030] Based on the same inventive concept, the application further provides a model predictive control device based on the improved quasi-Y source DC-DC converter, and the device comprises:

[0031] A state acquisition unit acquires a state equation of the improved quasi-Y source DC-DC converter system and an input / output voltage relationship;

[0032] A voltage prediction model construction unit is used to discretize the state equation by taking the inductor current and the capacitor voltage as control variables, so as to obtain a voltage prediction model;

[0033] A prediction unit is used to combine the moving discrete control set model predictive control algorithm with the voltage prediction model to predict the output voltage;

[0034] A control unit is used to select a suitable cost function to measure the output performance of the predictive control and control the output voltage.

[0035] Based on the same inventive concept, the application further provides a computer device comprising a memory and a processor, and the memory stores a computer program, when the processor runs the computer program stored in the memory, the processor executes the model predictive control method based on the improved quasi-Y source DC-DC converter according to any one of the above.

[0036] Based on the same inventive concept, the application further provides a computer readable storage medium for storing a computer program for executing the model predictive control method based on the improved quasi-Y source DC-DC converter.

[0037] The application has the advantages that:

[0038] The model predictive control method based on the improved quasi-Y source DC-DC converter can significantly improve the anti-interference of the improved quasi-Y source DC-DC converter, improve the dynamic performance of the improved quasi-Y source DC-DC converter, avoid frequent manual adjustment of the duty cycle, shorten the response time of the converter output voltage, and widen the application range of the improved quasi-Y source DC-DC converter.

[0039] The model predictive control method based on the improved quasi-Y source DC-DC converter can accurately describe the dynamic characteristics of the system, including important variables such as inductor current and capacitor voltage, by obtaining the state equation and input / output voltage relationship of the improved quasi-Y source DC-DC converter system. The voltage prediction model obtained by discretizing the state equation can accurately predict the future voltage trend of the system. This prediction ability can effectively cope with load changes and input voltage fluctuations, thereby realizing more stable output voltage control. The combination of the moving discrete control set model predictive control algorithm and the voltage prediction model enables the controller to dynamically adjust the duty cycle of the switching tube based on the real-time predicted voltage trend. This method not only provides accurate voltage control in steady state, but also maintains stability in transient response. By designing a suitable cost function to measure the output performance of the predictive control, the converter output voltage responds quickly.

[0040] The model predictive control method based on the improved quasi-Y source DC-DC converter can combine the system dynamic model and real-time prediction to achieve accurate control of the output voltage, thereby significantly improving the stability and response speed of the system. Compared with traditional open-loop or simple feedback control, this method performs better when dealing with complex loads and environmental condition changes. By dynamically adjusting the duty cycle, model predictive control enables the system to adapt to different working conditions, improving the flexibility and adaptability of the system. This flexibility is particularly important for industrial automation and power electronics applications, effectively coping with variable working environments and load requirements. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1A flow chart of a model predictive control method based on the improved quasi-Y source DC-DC converter according to the first embodiment;

[0042] Figure 2 An improved quasi-Y source DC-DC converter circuit structure schematic diagram according to the second embodiment;

[0043] Figure 3 Two working state schematic diagrams of the improved quasi-Y source DC-DC converter according to the eleventh embodiment

[0044] Figure 4 A principle diagram of the moving discrete control set model predictive control according to the eleventh embodiment;

[0045] Figure 5 A flow chart of the model predictive control strategy of the improved quasi-Y source DC-DC converter according to the eleventh embodiment;

[0046] Figure 6 An output voltage simulation diagram when the load is suddenly changed according to the eleventh embodiment;

[0047] Figure 7 A load current and output voltage experimental diagram when the load is suddenly changed according to the eleventh embodiment. DETAILED DESCRIPTION

[0048] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in connection with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application.

[0049] The first embodiment is described as follows. Figure 1 The model predictive control method based on the improved quasi-Y source DC-DC converter according to the present embodiment comprises the following steps.

[0050] S1: obtaining the state equation of the improved quasi-Y source DC-DC converter system and the input / output voltage relationship formula;

[0051] S2: discretizing the state equation by taking the inductor current and the capacitor voltage as the control variables to obtain a voltage prediction model;

[0052] S3: combining the moving discrete control set model predictive control algorithm with the voltage prediction model to predict the output voltage;

[0053] S4: selecting a suitable cost function to measure the output performance of the predictive control and controlling the output voltage.

[0054] The embodiment can accurately describe the dynamic characteristics of the system, including important variables such as inductor current and capacitor voltage, by obtaining the state equation and input / output voltage relationship of the improved quasi-Y source DC-DC converter system. The voltage prediction model obtained after discretizing the state equation can accurately predict the future voltage trend of the system. This prediction ability can effectively cope with load changes and input voltage fluctuations, thereby achieving more stable output voltage control. The combination of the moving discrete control set model predictive control algorithm and the voltage prediction model enables the controller to dynamically adjust the duty cycle of the switching tube based on the real-time predicted voltage trend. This method not only provides accurate voltage control in steady state, but also maintains stability in transient response. By designing a suitable cost function to measure the output performance of the predictive control, the converter output voltage responds quickly.

[0055] The embodiment based on the model predictive control method can combine the system dynamic model and real-time prediction to achieve accurate control of the output voltage, thereby significantly improving the stability and response speed of the system. Compared with traditional open-loop or simple feedback control, this method performs better when dealing with complex loads and environmental condition changes. By dynamically adjusting the duty cycle, model predictive control enables the system to adapt to different working conditions, improving the flexibility and adaptability of the system. This flexibility is particularly important for industrial automation and power electronics applications, effectively coping with changing working environments and load requirements.

[0056] Embodiment two, see Figure 2 The embodiment is a further limitation of the model predictive control method based on the improved quasi-Y source DC-DC converter described in embodiment one. The state equation and input / output voltage relationship of the improved quasi-Y source DC-DC converter system in step S1 are as follows:

[0057]

[0058] where U0 is the output voltage of the converter, U in is the output current of the converter, I C5 is the current flowing through the capacitor C5, R is the output circuit load, K is the winding factor of the improved quasi-Y source converter, D is the through duty cycle, and t is the time.

[0059] The high-gain improved quasi-Y source DC-DC converter in this embodiment is a high-gain improved quasi-Y source DC-DC converter with the patent number 202410887983.9. The specific structure includes a DC voltage source, power electronic switches, a high-gain quasi-Y source impedance network, a passive circuit with a switching inductor, a DC load Rload, and a controller for the power electronic switches. The power electronic switches are composed of two IGBT modules. The high-gain quasi-Y source bidirectional impedance network is composed of inductors L1, L4, capacitors C1, C2, C5, two groups of power electronic switches SW1 and SW1' and SW3 and SW3', and a three-winding coupled inductor with a turn ratio of N1:N2:N3. The switching inductor is composed of inductors L2, L3, diodes D4, D5, and D6. The passive circuit with a switching inductor is composed of a group of power electronic switches SW2 and SW2', capacitors C3 and C4, and a switching inductor. The DC load Rload has a bidirectional converter output DC voltage across it. The controller for the power electronic switches sends switching control signals to the three groups of power electronic switches.

[0060] Embodiment three, this embodiment is a further limitation of the model predictive control method based on the improved quasi-Y source DC-DC converter described in embodiment one. The winding factor K of the improved quasi-Y source converter is determined by the turn ratio N1:N2:N3 of the three-winding coupled inductor of the improved quasi-Y source converter, and the calculation formula is:

[0061]

[0062] In this embodiment, the winding factor K of the improved quasi-Y source converter is determined by the turn ratio N1:N2:N3 of the coupled inductor, which means that the characteristics of voltage transmission can be accurately controlled during the design phase. The model predictive control method utilizes this determinism to more accurately establish a voltage prediction model, and combines a moving discrete control set model predictive control algorithm to achieve high-precision control of the output voltage. This accuracy helps to stabilize the power system and improve its reliability.

[0063] The turn ratio N1:N2:N3 of the coupled inductor determines the winding factor K, and this design flexibility allows the voltage gain and efficiency of the converter to be adjusted according to specific requirements. The model predictive control method is suitable for various converter designs and can achieve optimal control strategies under different turn ratio settings, thereby fully exploiting the performance potential of the system.

[0064] Embodiment four, this embodiment is a further limitation of the model predictive control method based on the improved quasi-Y source DC-DC converter described in embodiment one. Step S2 includes:

[0065] The state equation of the improved quasi-Y source DC-DC converter system is discretized by forward Euler method with output voltage and output current as control variables, and the discrete formula of output voltage is obtained:

[0066]

[0067] where k is a certain control instant, T is the switching period, U0(k) is the output voltage at time k, U0(k+1) is the output voltage at time k+1, and I0(k) is the output current at time k.

[0068] By discretizing the state equation, the output voltage of the system at the next control instant can be accurately predicted. This accuracy helps to reduce the transition process in the response process of the system and improves the stability and reliability of the output voltage. The model predictive control method can adjust the output voltage in real time according to the current system state and control variables, so it can quickly respond to changes in external environment and changes in load demand. This real-time performance is one of the advantages that traditional control methods do not have. By optimizing the control of output voltage and output current as control variables, the energy efficiency and power conversion efficiency of the system can be effectively improved. This optimization helps to reduce energy waste and improve the overall performance of the system.

[0069] Embodiment five, this embodiment is a further limitation of the model predictive control method based on the improved quasi-Y source DC-DC converter of embodiment one, step S3 comprises:

[0070] The moving discrete control set model predictive control algorithm is used to calculate the value function in each control period, and the optimal control compensation from the sampling time to the prediction time is selected to act on the converter;

[0071] At control time k, the initial value of duty ratio D is defined as d, and in the control interval of k~k+1, the moving discrete control calculation formula of D(k+1) is:

[0072] D(k+1)=D(k)+ΔD(k)=d+(-4Δd,-3Δd,-2Δd,-Δd,0,Δd,2Δd,3Δd,4Δd}

[0073] where D(k+1) is the value of duty ratio D at time k+1, D(k) is the value of duty ratio D at time k, ΔD(k) is the change of duty ratio in the control interval of k~k+1, and Δd is the discrete precision.

[0074] The embodiment can dynamically evaluate and select the optimal control strategy from the current time to the predicted time by rolling the value function in each control period. This dynamic optimization ensures the selection of the most suitable control compensation strategy under different operating conditions to achieve optimal output voltage stability and efficiency.

[0075] The calculation formula of the control duty cycle D(k+1) combines the prediction error and the control compensation. By optimizing these parameters, the duty cycle of the switching tube can be effectively adjusted to achieve precise control of the output voltage. This precision is particularly important when facing load changes and grid fluctuations, ensuring system stability and the reliability of the output voltage.

[0076] In each control interval, the control duty cycle D(k+1) is dynamically adjusted based on real-time state feedback and prediction error. This real-time feedback mechanism and dynamic adjustment enable the converter to respond more quickly to changes in the external environment, such as load surges or grid disturbances, thereby improving the response speed and stability of the converter.

[0077] Embodiment six, the embodiment is a further limitation of the model predictive control method based on the improved quasi-Y source DC-DC converter of embodiment one, the rolling number of the moving discrete control set model predictive control algorithm in each control period is set to 9.

[0078] Embodiment seven, the embodiment is a further limitation of the model predictive control method based on the improved quasi-Y source DC-DC converter of embodiment four, step S4 includes:

[0079] J = (U0(k+1) - U ref ) 2

[0080] where J is the cost function used to measure the output performance of the predictive control, U ref is the output voltage reference value.

[0081] Embodiment eight, the model predictive control device based on the improved quasi-Y source DC-DC converter of the embodiment, the device includes:

[0082] a state acquisition unit that acquires the state equation of the improved quasi-Y source DC-DC converter system and the input / output voltage relationship;

[0083] a voltage prediction model construction unit for discretizing the state equation with inductor current and capacitor voltage as control variables to obtain a voltage prediction model;

[0084] a prediction unit for combining the moving discrete control set model predictive control algorithm with the voltage prediction model to predict the output voltage;

[0085] a control unit for selecting a suitable cost function to measure the output performance of the predictive control and controlling the output voltage.

[0086] Embodiment Nine, the computer device of the embodiment, comprising a memory and a processor, the memory stores a computer program, when the processor runs the computer program stored in the memory, the processor executes the model predictive control method based on the improved quasi-Y source DC-DC converter according to any one of the embodiments one to seven.

[0087] Embodiment Ten, the computer readable storage medium of the embodiment, the computer readable storage medium is used to store a computer program, the computer program executes the model predictive control method based on the improved quasi-Y source DC-DC converter according to any one of the embodiments one to seven.

[0088] Embodiment Eleven, see Figures 3 to 7 This embodiment is described. The embodiment is a specific embodiment of the model predictive control method based on the improved quasi-Y source DC-DC converter according to the embodiment one, and also used to explain the embodiments two to seven, specifically:

[0089] A model predictive control method of an improved quasi-Y source DC-DC converter, comprising:

[0090] S1, obtaining the state equation of the improved quasi-Y source DC-DC converter system and the input / output voltage relationship;

[0091] S2, selecting the inductor current and the capacitor voltage as the control variable to discretize the state equation to obtain a voltage prediction model;

[0092] S3, combining the moving discrete control set model predictive control algorithm with the voltage prediction model to predict the output voltage;

[0093] S4, selecting a suitable cost function to measure the output performance of the predictive control and controlling the output voltage;

[0094] The structure diagram of the improved quasi-Y source DC-DC converter involved is shown in Figure 2 .

[0095] Specifically, in steps S1-S2, first, analyze two working states of the improved quasi-Y source DC-DC converter respectively, then obtain the input / output voltage relationship of the improved quasi-Y source DC-DC converter system by using the volt-second balance principle, and then summarize the state equation shared in the two working states to obtain the state equation of the converter;

[0096] The two working state diagrams of the improved quasi-Y source DC-DC converter are shown in Figures 1 and 2. Figure 3

[0097]

[0098] wherein U in is the DC input voltage; U0 is the output DC voltage; U L1 , U L2 , U L3 , U L4 , U C1 , U C2 , U C3 and U C4 are the voltages across the inductors L1, L2, L3, L4 and the capacitors C1, C2, C3 and C4 in the improved quasi-Y source DC-DC converter in the pass-through mode; U L is the voltage across the coupled inductor N1; N1, N2, N3 are the number of turns of the three-winding coupled inductor.

[0099] The non-pass-through state is represented by the following formula:

[0100]

[0101] wherein U in is the DC input voltage; U0 is the output DC voltage; U' L1 , U' L2 , U' L3 , U' L4 , U C1 , U C2 , U C3 and U C4 are the voltages across the inductors L1, L2, L3, L4 and the capacitors C1, C2, C3 and C4 in the improved quasi-Y source DC-DC converter in the non-pass-through mode; U' L is the voltage across the coupled inductor N1; N1, N2, N3 are the number of turns of the three-winding coupled inductor.

[0102] From the volt-second balance principle, the voltage across the inductor is zero in a period in the steady state. The relationship between the current in the pass-through state and the current in the non-pass-through state of the inductors L1, L2, L3, L4 and the coupled inductor is represented by the following formula:

[0103]

[0104] In combination with the above relationship, the relationship between the output voltage and the input voltage of the improved quasi-Y source DC-DC converter is represented by the following formula: ​

[0105]

[0106] Wherein: D is the through duty ratio, if the switching period of the converter is defined as T, the on time is recorded as T on , the off time is recorded as T off , and T=T on +T off , then the through duty ratio D=T on / T off .

[0107] The state equation of the improved quasi-Y source DC-DC converter system and the input / output voltage relationship are summarized by the following formula:

[0108]

[0109] Wherein: I0 is the output current of the converter, I C5 is the current flowing through the capacitor C5, R is the output circuit load, K is the winding factor of the improved quasi-Y source converter, which is determined by the turns ratio N1:N2:N3 of the three-winding coupled inductor of the improved quasi-Y source converter, and the calculation formula is

[0110] In step S2, the voltage of the capacitor C5, i.e. the output voltage, and the current of the inductor L4, i.e. the output current, are selected as control variables, and the state equation of the improved quasi-Y source DC-DC converter system is discretized by forward Euler method to obtain the discrete formula of the output voltage.

[0111] The discrete formula of the output voltage is represented as:

[0112]

[0113] Wherein: k is a certain control instant, T is the switching period, U0(k), U0(k+1) are the output voltages at k time and k+1 time, and I0(k) is the output current at k time.

[0114] In step S3, the moving discrete control set model predictive control algorithm is combined with the voltage prediction model to predict the output voltage.

[0115] The moving discrete control set model predictive control algorithm calculates the value function in each control period, so as to select the optimal control compensation from the sampling time to the prediction time to act on the converter, and the optimization period is pushed forward step by step. Figure 4The diagram shows the principle of moving discrete control set model predictive control, the rolling number of control algorithm is set to 9, the initial value of duty cycle D is defined as d, since the output voltage of the converter has a direct relationship with the duty cycle, let the duty cycle D(k+1) = D(k) + ΔD(k). In the control interval of k ~ k+1, the moving discrete control calculation formula of D(k+1) is:

[0116] D(k+1) = D(k) + ΔD(k) = d + (-4Δd, -3Δd, -2Δd, -Δd, 0, Δd, 2Δd, 3Δd, 4Δd}

[0117] Where: Δd is the discrete accuracy, the value is determined by the control period.

[0118] In step S4, a suitable cost function is selected to measure the output performance of the predictive control and control the output voltage, which is expressed by the following formula:

[0119] J = (U0(k+1) - U ref ) 2

[0120] Where: U ref is the output voltage reference value.

[0121] Figure 5 The flow chart of the improved quasi-Y source DC-DC converter model predictive control strategy is shown. By deriving the prediction model of the output voltage, the value of the predicted output voltage U0 at k+1 is obtained, and the difference between the reference value is obtained. The error is adjusted by the moving discrete set to adjust the duty cycle feedback to the output voltage end, further reduce the error, seek the optimal duty cycle, avoid the artificial frequent adjustment of the duty cycle, at the same time, it can quickly respond to the change of the output voltage, so that the output voltage can reach the reference value around the reference value.

[0122] Figure 6 The simulation results of the output voltage of the improved quasi-Y source DC-DC converter when the output resistance suddenly changes from 1000Ω to 500Ω at 1.0s are given. The output voltage reference value is 700V, when the output resistance is 1000Ω, the converter reaches the voltage reference value at about 0.6s under the moving discrete control set model predictive control algorithm. When t = 1.0s, the load suddenly changes from 1000Ω to 500Ω, the output voltage oscillates, the maximum oscillation amplitude is about 20V, and it reaches the reference value again after 0.6s. It can be seen that the moving discrete control set model predictive control algorithm can obviously improve the dynamic response of the improved quasi-Y source DC-DC converter and improve the anti-interference of the improved quasi-Y source DC-DC converter.

[0123] Figure 7The experimental results of the output voltage and the load current of the improved quasi-Y source DC-DC converter when the output resistance suddenly changes from 1000 Ω to 500 Ω at t=1.0 s are given. When t=1.0 s, the load suddenly changes from 1000 Ω to 500 Ω, the output voltage oscillates, and after 0.6 s, it reaches the reference value again and stabilizes, and the output current becomes twice the original. It can be found from the experimental results that the improved quasi-Y source DC-DC converter model predictive control method adopted in the application has the same simulation effect as the simulation effect, can realize fast response to output voltage change and high efficiency of output voltage control, improve the dynamic response capability of the system, and improve the anti-interference performance of the system.

[0124] Although the preferred embodiments of the present disclosure have been described, those skilled in the art can make additional changes and modifications to the embodiments once they know the basic inventive concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present disclosure. Obviously, those skilled in the art can make various modifications and changes to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and changes of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and changes.

[0125] Those skilled in the art should understand that the embodiments of the present disclosure can be provided as a method, a system or a computer program product. Therefore, the present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present disclosure can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0126] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each flow and / or block in the flowcharts and / or block diagrams and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing apparatus to produce a machine, so that the instructions executed by the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one flow or multiple flows and / or blocks Figure 1 The functions specified in one flow or multiple flows and / or blocks These computer program instructions can also be stored in a computer-readable memory that can cause the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction devices that implement the functions specified in the flowcharts and / or block diagrams.Figure 1 one or more blocks and / or steps in a flowchart Figure 1 one or more blocks and / or steps in a flowchart These computer program instructions can also be loaded into computer or other programmable data processing devices, so that a series of operation steps are performed on the computer or other programmable data processing devices to generate computer-implemented processes, so that the instructions executed on the computer or other programmable data processing devices provide steps for implementing the function specified in the flowchart Figure 1 one or more blocks and / or steps in a flowchart Figure 1 one or more blocks and / or steps in a flowchart

[0127] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present disclosure, but not to limit the scope of protection, although the present disclosure is described in detail with reference to the above examples, those skilled in the art should understand: after reading the present disclosure, the person skilled in the art can make various changes, modifications or equivalent replacements to the specific embodiments of the application, but these changes, modifications or equivalent replacements are all within the protection scope of the disclosed claims.

Claims

1. A model predictive control method based on an improved quasi-Y source DC-DC converter, characterized in that, The method comprises: S1: obtaining the state equation and input / output voltage relationship of the improved quasi-Y source DC-DC converter system; S2: discretizing the state equation by taking the inductor current and capacitor voltage as control variables to obtain a voltage prediction model; S3: combining the moving discrete control set model prediction control algorithm with the voltage prediction model to predict the output voltage; S4: selecting a suitable cost function to measure the output performance of the prediction control and controlling the output voltage; The state equation and input / output voltage relationship of the improved quasi-Y source DC-DC converter system in step S1 are specifically as follows: where U0 is the output voltage of the converter, U in is the output voltage of the converter, I0 is the output current of the converter, I C5 is the current flowing through the capacitor C5, R is the load of the output circuit, K is the winding factor of the improved quasi-Y source converter, D is the shoot-through duty cycle, and t is time. The improved quasi-Y source DC-DC converter comprises a DC voltage source, power electronic switches SW1, SW2 and SW3, a high-gain quasi-Y source impedance network, a passive circuit with a switching inductor and a DC load R load The power electronic switch SW1 is composed of two IGBT modules; the high-gain quasi-Y source impedance network is composed of inductors L1 and L4, capacitors C1, C2 and C5, the power electronic switches SW1 and SW3 and a three-winding coupled inductor with a winding ratio of N1:N2:N3; the switching inductor is composed of inductors L2 and L3 and diodes D4, D5 and D6; the passive circuit with the switching inductor is composed of a group of power electronic switches SW2, capacitors C3 and C4 and the switching inductor; and the DC load R load The two-terminal voltage is a bidirectional converter output DC voltage; and the controller of the power electronic switches sends switch control signals to the power electronic switches SW1, SW2 and SW3 respectively. The two IGBT modules of the power electronic switch SW1 are reversely connected, and the internal anti-parallel diode of each IGBT switch tube is connected; The diode D4 is connected with the inductor L3 to form a branch, and the connection point is marked as M point, and the direction of M point is the positive transmission direction of diode D4; The inductor L2 is connected with the diode D6 to form a branch, and the connection point is marked as N point, and the positive transmission direction of diode D6 is away from N point; the diode D5 is connected between M point and N point, and the positive transmission direction is from N point to M point, and the three diodes form a Z shape in the circuit topology structure; The passive circuit with switching inductor is in T shape, wherein the power electronic switch SW2 is connected with the switching inductor, and the connection point is marked as O point, the capacitor C3 is connected in parallel with the branch composed of the power electronic switch and the switching inductor, and the capacitor C4 is connected with O point; The positive pole of the direct current voltage source is connected with the inductor L1, and then connected with the power electronic switch SW1 and the same name end of the middle winding N1 of the three-winding coupled inductor, wherein the connection point of the inductor L1 and the power electronic switch SW1 is recorded as point P, the non-same name end of the N2 of the three-winding coupled inductor is connected with the capacitor C2 in series, and then connected with the negative pole of the direct current voltage source and the negative pole of the direct output voltage, the non-same name end of the N3 of the three-winding coupled inductor is connected with the port of one side of the bidirectional switch in the passive circuit, the inductor L4 is connected with the capacitor C5 and the direct current load R load in series, the power electronic switch SW3 and the branch composed of the inductor L4, the capacitor C5 and the direct current load R load are connected in parallel, one side of the capacitor C1 is connected with the point P, and the other side is connected with the connection point of the power electronic switch SW3 and the inductor L4.

2. The model predictive control method for an improved quasi-Y source DC-DC converter according to claim 1, wherein The winding factor K of the improved quasi-Y source converter is determined by the turn ratio N1:N2:N3 of the three-winding coupled inductor of the improved quasi-Y source converter, and the calculation formula is: 。 3. The model predictive control method for an improved quasi-Y source DC-DC converter according to claim 1, wherein The step S2 comprises: The output voltage and output current are taken as control variables, the state equation of the improved quasi-Y source DC-DC converter system is discretized by the forward Euler method, and the discrete formula of the output voltage is obtained: wherein k is a certain control instant selected, T is a switching period, is the output voltage at k time, is the output voltage at k+1 time, is the output current at k time.

4. The model predictive control method for an improved quasi-Y source DC-DC converter according to claim 1, wherein, The step S3 comprises: In each control period, the moving discrete control set model prediction control algorithm is used to calculate the value function, and the optimal control compensation from the sampling time to the prediction time is applied to the converter; At the control time k, the initial value of the duty cycle D is defined as d, and in the control interval k~k+1, the moving discrete control calculation formula of D(k+1) is: wherein, is a value of the duty ratio D at the k+1th instant, is a value of the duty ratio D at the kth instant, is a variation amount of the duty ratio in the k~k+1 control interval, is a discrete precision.

5. The model predictive control method for an improved quasi-Y source DC-DC converter according to claim 1, wherein, The rolling number of the moving discrete control set model prediction control algorithm in each control period is set to 9.

6. The model predictive control method for an improved quasi-Y source DC-DC converter according to claim 3, wherein, Step S4 comprises: wherein, is a cost function, is an output voltage reference value.

7. A model predictive control apparatus for an improved quasi-Y-source DC-DC converter, characterized by, The device comprises: A state acquisition unit acquires the state equation and input / output voltage relationship of the improved quasi-Y source DC-DC converter system; the state equation and input / output voltage relationship of the improved quasi-Y source DC-DC converter system are specifically as follows: where U0 is the output voltage of the converter, U in is the output voltage of the converter, I0 is the output current of the converter, I C5 is the current flowing through the capacitor C5, R is the load of the output circuit, K is the winding factor of the improved quasi-Y source converter, D is the shoot-through duty cycle, and t is time. A voltage prediction model construction unit is configured to discretize the state equation by taking the inductor current and capacitor voltage as control variables to obtain a voltage prediction model; A prediction unit is configured to combine the moving discrete control set model prediction control algorithm with the voltage prediction model to predict the output voltage; A control unit is configured to select a suitable cost function to measure the output performance of the prediction control and control the output voltage; The improved quasi-Y source DC-DC converter comprises a DC voltage source, power electronic switches SW1, SW2 and SW3, a high-gain quasi-Y source impedance network, a passive circuit with a switching inductor and a DC load R load The power electronic switch SW1 is composed of two IGBT modules; the high-gain quasi-Y source impedance network is composed of inductors L1 and L4, capacitors C1, C2 and C5, the power electronic switches SW1 and SW3 and a three-winding coupled inductor with a winding ratio of N1:N2:N3; the switching inductor is composed of inductors L2 and L3 and diodes D4, D5 and D6; the passive circuit with the switching inductor is composed of a group of power electronic switches SW2, capacitors C3 and C4 and the switching inductor; and the DC load R load The two-terminal voltage is a bidirectional converter output DC voltage; and the controller of the power electronic switches sends switch control signals to the power electronic switches SW1, SW2 and SW3, respectively. Two IGBT modules of the power electronic switch SW1 are reversely connected, and each IGBT switch tube has an internal anti-parallel diode; The diode D4 and the inductor L3 form a branch, and the connection point is marked as M point. The direction of the M point is the positive transmission direction of the diode D4; The inductor L2 and the diode D6 form a branch, and the connection point is marked as N point. The positive transmission direction of the diode D6 is away from the N point. The diode D5 is connected between the M point and the N point, and the positive transmission direction is from the N point to the M point. The three diodes form a Z-shaped structure in the circuit topology; The passive circuit with a switching inductor is in a T shape. The power electronic switch SW2 and the switching inductor are connected, and the connection point is marked as O point. The capacitor C3 is connected in parallel with the branch formed by the power electronic switch and the switching inductor. The capacitor C4 is connected to the O point. The positive pole of the direct current voltage source is connected with the inductor L1, and then connected with the power electronic switch SW1 and the same name end of the middle winding N1 of the three-winding coupled inductor, wherein the connection point of the inductor L1 and the power electronic switch SW1 is recorded as point P, the non-same name end of the N2 of the three-winding coupled inductor is connected with the capacitor C2 in series, and then connected with the negative pole of the direct current voltage source and the negative pole of the direct output voltage, the non-same name end of the N3 of the three-winding coupled inductor is connected with the port of one side of the bidirectional switch in the passive circuit, the inductor L4 is connected with the capacitor C5 and the direct current load R load in series, the power electronic switch SW3 and the branch composed of the inductor L4, the capacitor C5 and the direct current load R load are connected in parallel, one side of the capacitor C1 is connected with the point P, and the other side is connected with the connection point of the power electronic switch SW3 and the inductor L4.

8. A computer device, comprising: The computer readable storage medium is used to store a computer program, and the computer program executes the model predictive control method based on the improved quasi-Y source DC-DC converter according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium is used to store a computer program, and the computer program executes the model predictive control method based on the improved quasi-Y source DC-DC converter according to any one of claims 1-6.

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