CN111737872B - Margin prediction control method and system based on magnetic characteristics of passive component - Google Patents
Margin prediction control method and system based on magnetic characteristics of passive component Download PDFInfo
- Publication number
- CN111737872B CN111737872B CN202010587782.9A CN202010587782A CN111737872B CN 111737872 B CN111737872 B CN 111737872B CN 202010587782 A CN202010587782 A CN 202010587782A CN 111737872 B CN111737872 B CN 111737872B
- Authority
- CN
- China
- Prior art keywords
- current
- passive component
- voltage vector
- magnetic
- cost function
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention belongs to the field of magnetic characteristic margin prediction control, and particularly relates to a margin prediction control method and system based on the magnetic characteristic of a passive component. The margin prediction control method based on the magnetic characteristics of the passive component comprises the steps of constructing a topological circuit of a converter based on the physical characteristics of the magnetic elements of the passive component; acquiring load current, capacitance voltage, switching frequency and safety allowance of a passive component of the converter, and taking the load current, the capacitance voltage, the switching frequency and the safety allowance of the passive component as control variables of a preset cost function; mapping the magnetic constraint condition of the magnetic element working in the safe region to the current parameter of the converter topological circuit through the electromagnetic principle, and solving a voltage vector state corresponding to the minimized cost function and taking the voltage vector state as the optimal voltage vector state at the future moment; and calculating the current change track flowing through the passive component in a period of time in the future according to the optimal voltage vector state at the future moment, and then comparing the current change track with a preset current threshold value to predict the design allowance of the passive component.
Description
Technical Field
The invention belongs to the field of magnetic characteristic margin prediction control, and particularly relates to a margin prediction control method and system based on the magnetic characteristic of a passive component.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the rapid development of new energy vehicles and the continuous improvement of the intelligent level of modern power grids, the reliability of the device has higher requirements on the modularization and integration of a power electronic system, and the miniaturization and light weight of equipment become bottlenecks which restrict the further development of the equipment. The passive component generally uses magnetic core materials such as powder core and air gap ferrite. Limited by the magnetization characteristic curve of the ferromagnetic material, transient overcurrent of the ferromagnetic material can cause magnetic supersaturation and magnetic permeability reduction, and compel the reduction of inductance to cause overheating overcurrent damage of the device. A large safety margin is usually set aside during design to prevent transient overcurrent. Therefore, researching the margin control strategy of the passive component has profound significance for the design of a power electronic system.
The existing passive component margin control method is mainly based on multi-objective parameter optimization of a genetic algorithm. The inventor finds that the method has the following defects: (1) the early maturing phenomenon of the genetic algorithm causes that the optimizing capability of the system is not strong, and the optimized quantity is trapped into local optimization too early and cannot be found into global optimization. The premature phenomenon can be relieved by introducing the chaotic operator into the genetic algorithm, but repeated individuals need to be processed, the calculated amount is greatly increased, and the convergence speed is difficult to meet the requirement; (2) the algorithm relates to a plurality of parameters such as cross rate and variation rate, and the selection of the parameters is directly related to the quality of a solution, but at present, the parameters are mainly selected by depending on experience; (3) the algorithm control target only relates to design parameters and cannot dynamically restrict the condition in operation. These limitations result in a circuit design that is less than optimal in terms of actual operation.
Disclosure of Invention
In order to solve the above problems, a first aspect of the present invention provides a margin prediction control method based on the magnetic characteristics of a passive component, which can predict and control the current value passing through the passive component at a future time, and protect the circuit before the current of the passive component reaches a safe time length of an alert value, so that the passive component is strictly restricted in a safe working area, and the protection of the device is realized.
In order to achieve the purpose, the invention adopts the following technical scheme:
a margin prediction control method based on the magnetic characteristics of a passive component comprises the following steps:
constructing a topological circuit of the converter based on the physical characteristics of the passive component magnetic element;
acquiring load current, capacitance voltage, switching frequency and safety allowance of a passive component of the converter, and taking the load current, the capacitance voltage, the switching frequency and the safety allowance of the passive component as control variables of a preset cost function;
mapping the magnetic constraint condition of the magnetic element working in the safe region to the current parameter of the converter topological circuit through the electromagnetic principle, and solving a voltage vector state corresponding to the minimized cost function and taking the voltage vector state as the optimal voltage vector state at the future moment;
and calculating the current change track flowing through the passive component in a period of time in the future according to the optimal voltage vector state at the future moment, and predicting the design allowance of the passive component by comparing the current change track with a preset current threshold.
In order to solve the above problems, a second aspect of the present invention provides a margin prediction control system based on the magnetic characteristics of a passive component, which can predict and control the value of current passing through the passive component at a future time, and protect the circuit before the current of the passive component reaches a safe time length of an alert value, thereby strictly restricting the passive component in a safe working area and realizing the protection of the device.
In order to achieve the purpose, the invention adopts the following technical scheme:
a margin predictive control system based on the magnetic characteristics of passive components, comprising:
a topology circuit building module for building a topology circuit of the converter based on physical characteristics of the passive component magnetic element;
the control variable acquisition module is used for acquiring load current, capacitor voltage, switching frequency and safety margin of a passive component and taking the load current, the capacitor voltage, the switching frequency and the safety margin of the passive component as control variables of a preset cost function;
the optimal voltage vector acquisition module is used for mapping the magnetic constraint condition of the magnetic element working in the safe area to the current parameter of the converter topological circuit through the electromagnetic principle, and solving a voltage vector state corresponding to the minimized cost function and taking the voltage vector state as the optimal voltage vector state at the future moment;
and the design allowance prediction module is used for calculating a current change track flowing through the passive component in a period of time in the future according to the optimal voltage vector state at the future moment, and predicting the design allowance of the passive component by comparing the current change track with a preset current threshold.
A third aspect of the invention provides a computer-readable storage medium.
A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps of the method for margin prediction control based on magnetic characteristics of a passive component as described above.
A fourth aspect of the invention provides a computer apparatus.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method for margin prediction control based on magnetic properties of passive components as described above when executing the program.
Compared with the prior art, the invention has the beneficial effects that:
the invention takes the passive component working in a safety area as a constraint condition for optimizing the problem and gives full play to the physical curve of the magnetization characteristic based on model predictive control and the magnetic characteristic of the inductor, so that the design margin of the passive component can be reduced, the over-design of a magnetic element is avoided, the cost is reduced, the power density and the reliability of the system are improved, and the reliability and the electric energy conversion efficiency of power electronic systems such as an electric automobile, a micro-grid and a high-performance electric drive are greatly improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a schematic diagram of an NPC inversion topology according to an embodiment of the present invention;
FIG. 2 is an inverter output filter inductance model of an embodiment of the present invention;
FIG. 3 is a DC operating point of a magnetic core of an embodiment of the present invention;
FIG. 4 is a graph of the operating characteristics of the magnetic core of an embodiment of the present invention in a sinusoidal waveform;
FIG. 5 is a magnetic-to-current mapping relationship for an embodiment of the present invention;
fig. 6 is a flowchart of a margin prediction control method based on the magnetic characteristics of the passive component according to an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The core point of the invention is to combine the model prediction control with the magnetic characteristic of the passive component, and the magnetic element works in a safe area as a constraint condition, thereby achieving the purpose of controlling the margin of the passive component. The method for establishing the 3L NPC topology, predicting the state variables in the system and ensuring the passive components to work in the safe area and the protection strategy proposed by the present invention will be described below with reference to the basic principle of the magnetic components. The following describes a margin control strategy of the 3L NPC topology as an example.
Example one
The principle of the margin prediction control method based on the magnetic characteristics of the passive component in the embodiment is as follows:
constructing a topological circuit of the converter based on the physical characteristics of the passive component magnetic element;
acquiring load current, capacitor voltage, switching frequency and safety margin of a passive component of the converter and taking the load current, the capacitor voltage, the switching frequency and the safety margin of the passive component as control variables of a preset cost function;
mapping the magnetic constraint condition of the magnetic element working in the safe region to the current parameter of the converter topological circuit through the electromagnetic principle, and solving a voltage vector state corresponding to the minimized cost function and taking the voltage vector state as the optimal voltage vector state at the future moment;
and calculating the current change track flowing through the passive component in a period of time in the future according to the optimal voltage vector state at the future moment, and then comparing the current change track with a preset current threshold value to predict the design allowance of the passive component.
The working principle of the magnetic element is first analyzed based on the magnetic field theory. After the air gap is opened, the inductor can store magnetic field energy and stabilize inductance. As shown in fig. 2, the inverter output filter inductor is
In the formula: n is the number of turns of coil, mu 0 Is the magnetic permeability in vacuum, A c Is the effective sectional area, L, of the iron core e Is the average magnetic path length, mu m Effective permeability, δ air gap length; therefore, the inductor volume can be greatly reduced by reasonably configuring the inductor parameters. The task of designing an inductor is to determine the best core structure, the minimum geometric dimension, the proper number of winding turns, the cross-sectional area of a wire, the length of an air gap and the like under the condition of meeting given performance indexes. When the high-frequency loss of the inductor is not serious, the inductance reduction in the current conversion range caused by magnetic saturation is a main restriction factor for limiting the selection of the inductor, so that the inductor is not saturated when the peak current flows through, and the certain linearity is kept.
As shown in fig. 3 and 4, the dc operating point of the core shifts in the 1 and 3 quadrants of the hysteresis loop according to the sine law (50Hz) with the modulation of the sine wave. When the magnetic core is at the peak value of the sine wave, the direct current component is large, the magnetic field intensity H is large, the magnetic core is easy to reach the saturation point, and when the H is further increased at the point, the increase of the useful value of B can not be caused any more, so that the magnetic permeability of the magnetic core is reduced. As shown in fig. 5, the inductance is required to be large because of large current pulsation in the inductor, but the magnetic permeability is proportional to the inductance, and the current fluctuation is increased as the inductance decreases with the increase in the current. Considering the requirement of load variation, the inductance value is required to be as large as possible and not to vary with the load, so that the inductor current needs to be restricted within a safe area.
The 3L NPC topology is shown in fig. 1, and is widely used in many drive systems. The 3L NPC inverter has the advantages that the output line voltage and the step of the phase voltage waveform are redundant to those of the traditional two-level inverter, The Harmonic Distortion (THD) is low, and the size and the weight of passive components such as a filter and the like can be effectively reduced. Therefore, the optimization effect of the invention can be better illustrated by adopting the topology.
The model predictive control has advantages in that it can predict changes of variables at a future time using a system model, has a fast transient response, and is easy to constrain coupled variables. As shown in fig. 6, by modeling the system, the measured values x (k) measured by the measuring device can be calculated by using a prediction model:
state variables x (k +1), x (k +2).. x (k + n) at n future times;
given reference variable x * (k+1)、x * (k+2)...x * (k+n)；
Using cost functions
And calculating the state variables of the future n moments corresponding to the minimum cost function by using the relevant limiting conditions. Calculating output current value I at n time points in the future by using state variables at n time points in the future corresponding to the minimized cost function L (t) of (d). Wherein λ is n Are the weight coefficients.
The cost function achieves the following control objectives: 1. load current reference trajectory and range constraints; 2, balancing the capacitance and voltage of the DC link; 3. the switching frequency is reduced.
Let the cost function be:
wherein the first two terms are load current error under a rectangular coordinate system
Respectively the real and imaginary part of the predicted current vector,
is a vector of a reference current that is,
capacitor electricity of upper and lower bridge arms on direct current bus side respectivelyPressure, n c Representing the system switch penalty, λ dc 、λ c And the weight coefficients respectively represent the direct current side capacitor voltage and the switch penalty term. By measuring the value of the output current, it is assumed that the output current remains unchanged until the next measurement instant, since the time constant of the output current is much larger than the sampling period of the control system.
By the formula
Using resistance R, inductance L and time constant T s The output current value at n moments in the future can be calculated. Superposing the calculated current vector at the future moment and the current value at the current moment and comparing the superposed current vector with the safe current value of the inductor, if the superposed current vector is in a safe range, selecting the vector of the minimized cost function, continuing normal work, and predicting according to the reference current; if the current calculated vector causes the output current to exceed the preset proportion (for example: 90%) of the maximum peak current allowed to be borne by the inductor, a corresponding protection mechanism is started, the selection of the current vector is abandoned, and whether the next vector meets the requirement is judged until a voltage vector capable of working in a safety range is selected. And after the new measurement moment is reached, restarting the operation by using the output current value at the current moment, calculating a minimum cost function by using the output current value at the new moment, and performing current limit control on the inductor to enable the system to work in a safe area. In a word, the passive component operates in a safety zone, the method is simplified into the traditional prediction control, and the good dynamic and static performances of a controlled system can be ensured; under extreme working conditions, the passive component can be early warned to exceed a safe operation area, so that a protection mechanism is started before a fault occurs, and effective fault ride-through of the passive component is realized.
When designing a passive component, the maximum current value that the inductor can withstand is usually set to be 2 to 3 times of the rated current without imposing constraints on the passive component. And after increasing the constraint, it can ensure that the current thereof works in a safe area. At the moment when the load changes to further cause instantaneous current impact of the passive component, the invention can effectively inhibit the current overshoot phenomenon on the inductor, thereby avoiding the over-design of the safety margin of the passive component, reducing the volume of the alternating current inductor and improving the power density of the system. At the time of normal work, the circuit can keep the characteristics of rapid response and multivariable control of model predictive control.
The kind of the switch state and the calculation method are different for different topologies; for different applications, the types and the numbers of the controlled variables are different, and the requirements can be met by adjusting the weight coefficients of all terms of the cost function; any power electronic topology can be adopted for the converter corresponding to the circuit shown in FIG. 1, and the number of phases is not limited; the controlled variable involved in the above process may be a switch state, voltage or current calculated for any one of the possible operations; because a control method of multi-step length prediction can be adopted in the prediction process, the calculated amount problem of the method can be effectively solved by optimization algorithms such as spherical decoding and the like, and therefore, the detailed description is omitted.
The embodiment is oriented to application occasions such as new energy electric vehicles and intelligent micro-grids, a 3L NPC inversion topology based on model predictive control is established, currents flowing through passive components at future time are predictive controlled through a multi-step long model, a set of design method giving full play to performance parameters of the passive components is provided, physical properties of the passive components can be fully utilized, over-design problems of safety margins are avoided, and reliability and power density of a system are greatly optimized.
Example two
The margin prediction control system based on the magnetic characteristics of the passive component of the embodiment comprises:
(1) a topology circuit building module for building a topology circuit of the converter based on physical characteristics of the passive component magnetic elements;
(2) the control variable acquisition module is used for acquiring load current, capacitor voltage, switching frequency and safety margin of a passive component and taking the load current, the capacitor voltage, the switching frequency and the safety margin of the passive component as control variables of a preset cost function;
(3) the optimal voltage vector acquisition module is used for mapping the magnetic constraint condition of the magnetic element working in the safe area to the current parameter of the converter topological circuit through the electromagnetic principle, and solving a voltage vector state corresponding to the minimized cost function and taking the voltage vector state as the optimal voltage vector state at the future moment;
(4) and the design allowance prediction module is used for calculating a current change track flowing through the passive component in a period of time in the future according to the optimal voltage vector state at the future moment, and predicting the design allowance of the passive component by comparing the current change track with a preset current threshold.
As shown in fig. 6, by modeling the system, the measured values x (k) measured by the measuring device can be calculated by using a prediction model:
state variables x (k +1), x (k +2).. x (k + n) at n future times;
given reference variable x * (k+1)、x * (k+2)...x * (k+n)；
Using cost functions
And calculating the state variables of the future n moments corresponding to the minimum cost function by using the relevant limiting conditions. Wherein λ is n Are weight coefficients.
Calculating the output current value I at the future n moments by using the state variables at the future n moments corresponding to the minimized cost function L (t) of (d). The cost function achieves the following control objectives: 1. load current reference trajectory and range constraints; 2, balancing the capacitance and voltage of the DC link; 3. the switching frequency is reduced.
Let the cost function be:
wherein the first two terms are load current error under a rectangular coordinate system
Respectively the real and imaginary part of the predicted current vector,
is a reference electricityThe stream vector is a vector of the stream,
the capacitance voltages of the upper and lower bridge arms on the side of the DC bus are respectively n c Representing a system switch penalty, λ dc 、λ c And the weight coefficients respectively represent the direct current side capacitor voltage and the switch penalty term. By measuring the value of the output current, it is assumed that the output current remains unchanged until the next measurement instant, since the time constant of the output current is much larger than the sampling period of the control system.
By the formula
Using resistance R, inductance L and time constant T s The output current value at n future moments can be calculated.
Superposing the calculated current vector at the future moment and the current value at the current moment and comparing the superposed current vector with the safe current value of the inductor, if the superposed current vector is in a safe range, selecting the vector of the minimized cost function, continuing normal work, and predicting according to the reference current; if the current calculated vector causes the output current to exceed the preset proportion (for example: 90%) of the maximum peak current allowed to be borne by the inductor, a corresponding protection mechanism is started, the selection of the current vector is abandoned, and whether the next vector meets the requirement is judged until a voltage vector capable of working in a safety range is selected. And after the new measurement moment is reached, restarting the operation by using the output current value at the current moment, calculating a minimum cost function by using the output current value at the new moment, and performing current limit control on the inductor to enable the system to work in a safe area. In a word, the passive component operates in a safety area, the method is simplified into the traditional prediction control, and good dynamic and static performances of a controlled system can be ensured; under extreme working conditions, the passive component can be early warned to exceed a safe operation area, so that a protection mechanism is started before a fault occurs, and effective fault ride-through of the passive component is realized.
EXAMPLE III
The present embodiment provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements the steps in the margin prediction control method based on the magnetic characteristics of the passive component as described above.
Example four
The embodiment provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps in the margin prediction control method based on the magnetic characteristics of the passive component.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by a computer program, which may be stored in a computer readable storage medium and executed by a computer to implement the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A margin prediction control method based on the magnetic characteristics of a passive component is characterized by comprising the following steps:
constructing a topological circuit of the converter based on the physical characteristics of the passive component magnetic element;
acquiring load current, capacitance voltage, switching frequency and safety allowance of a passive component of the converter, and taking the load current, the capacitance voltage, the switching frequency and the safety allowance of the passive component as control variables of a preset cost function;
converting the magnetic constraint condition of the magnetic element working in a safe region into the safe region constraint condition of inductive current in a converter topological circuit by an electromagnetic principle, and solving a voltage vector state corresponding to a minimized cost function and taking the voltage vector state as an optimal voltage vector state at a future moment;
and calculating the current change track flowing through the passive component in a period of time in the future according to the optimal voltage vector state at the future moment, and predicting the design allowance of the passive component by comparing the current change track with a preset current threshold.
2. The margin prediction control method based on the magnetic characteristics of the passive component as claimed in claim 1, wherein the control target of the preset cost function is:
(a) load current reference trajectory and range constraints;
(b) balancing the capacitance and voltage of the direct current link;
(c) the switching frequency is reduced.
3. The method as claimed in claim 1, wherein the calculated future time current vector is added to the current time current value and compared with the safe current value of the inductor, and if the current vector is within a set safe range, the voltage vector selection for minimizing the cost function is performed, normal operation is continued, and the current flowing through the passive component is predicted according to the reference current.
4. The method as claimed in claim 3, wherein if the current calculated voltage vector causes the output current to exceed a preset proportion of the maximum peak current allowed to be borne by the inductor, the corresponding protection mechanism is started, the selection of the current vector is abandoned, and whether the next voltage vector meets the requirement is judged until a voltage vector capable of working in the safe range is selected.
5. The method as claimed in claim 1, wherein after a new measurement time is reached, a minimum cost function is calculated and current limit control is performed on the inductor by using an output current value at the current time, so that the converter operates in a safe area.
6. A margin prediction control system based on the magnetic characteristics of a passive component is characterized by comprising the following components:
a topology circuit building module for building a topology circuit of the converter based on physical characteristics of the passive component magnetic elements;
the control variable acquisition module is used for acquiring load current, capacitor voltage, switching frequency and safety margin of a passive component and taking the load current, the capacitor voltage, the switching frequency and the safety margin of the passive component as control variables of a preset cost function;
the optimal voltage vector acquisition module is used for converting the magnetic constraint condition that the magnetic element works in a safe region into the safe region constraint condition of inductive current in the converter topological circuit through the electromagnetic principle, and solving a voltage vector state corresponding to the minimized cost function and taking the voltage vector state as the optimal voltage vector state at the future moment;
and the design allowance prediction module is used for calculating a current change track flowing through the passive component in a period of time in the future according to the optimal voltage vector state at the future moment, and predicting the design allowance of the passive component by comparing the current change track with a preset current threshold.
7. The system according to claim 6, wherein in the design margin prediction module, the calculated future time current vector is superimposed on the current value at the present time and compared with the safe current value of the inductor, and if the calculated future time current vector is within a set safe range, the voltage vector selection for minimizing the cost function is performed, normal operation is continued, and the current flowing through the passive component is predicted according to the reference current.
8. The system of claim 7, wherein in the design margin prediction module, if the current calculated vector results in an output current exceeding a preset proportion of the maximum peak current allowed to be carried by the inductor, a corresponding protection mechanism is activated, the selection of the current vector is abandoned, and whether the next vector meets the requirement is judged until a voltage vector capable of operating in a safe range is selected.
9. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps of the method for margin prediction control based on the magnetic properties of a passive component according to any one of claims 1 to 5.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps in the method for margin prediction control based on magnetic properties of passive components according to any of claims 1-5 when executing the program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010587782.9A CN111737872B (en) | 2020-06-24 | 2020-06-24 | Margin prediction control method and system based on magnetic characteristics of passive component |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010587782.9A CN111737872B (en) | 2020-06-24 | 2020-06-24 | Margin prediction control method and system based on magnetic characteristics of passive component |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111737872A CN111737872A (en) | 2020-10-02 |
| CN111737872B true CN111737872B (en) | 2022-08-19 |
Family
ID=72650967
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010587782.9A Active CN111737872B (en) | 2020-06-24 | 2020-06-24 | Margin prediction control method and system based on magnetic characteristics of passive component |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111737872B (en) |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4439822A (en) * | 1982-03-26 | 1984-03-27 | California Institute Of Technology | Method and apparatus for detecting and preventing impending magnetic saturation in magnetic materials |
| EP2978122A1 (en) * | 2014-07-22 | 2016-01-27 | ABB Technology AG | Model predictive control of a modular multilevel converter |
| US10459472B2 (en) * | 2015-12-07 | 2019-10-29 | Hamilton Sundstrand Corporation | Model predictive control optimization for power electronics |
| GB2557294B (en) * | 2016-12-05 | 2022-03-30 | Itt Mfg Enterprises Llc | Matrix converter control method and system |
| CN111656673A (en) * | 2017-09-15 | 2020-09-11 | 安德烈斯·贝洛大学 | Sequential predictive control method for solving cost function first and then second cost function for two or more control objectives |
| CN108448986B (en) * | 2018-03-28 | 2021-03-12 | 天津大学 | Permanent magnet motor current control method based on adjustable bandwidth type predictive control |
| CN111224604A (en) * | 2019-11-21 | 2020-06-02 | 西安理工大学 | Simplified model prediction control method for asynchronous motor |
-
2020
- 2020-06-24 CN CN202010587782.9A patent/CN111737872B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN111737872A (en) | 2020-10-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105915091B (en) | System and method for optimizing active current sharing of parallel power converters | |
| EP3058646B1 (en) | Control method for electrical converter with lc filter | |
| Xia et al. | Robust LMI-LQR control for dual-active-bridge DC–DC converters with high parameter uncertainties | |
| CN105552959B (en) | Three-phase grid rectifier prediction direct Power Control method based on extended state observer | |
| Anzalchi et al. | Design and analysis of a higher order power filter for grid-connected renewable energy systems | |
| CN108429286A (en) | A kind of grid-connected current adjuster based on Active Disturbance Rejection Control | |
| CN112737388B (en) | Common-mode active damping resonant circulating current suppression system and method for inverter parallel system | |
| CN107070283A (en) | The improved model forecast Control Algorithm that a kind of inverter switching frequency is fixed | |
| Antoniewicz et al. | Model predictive current control method for four-leg three-level converter operating as shunt active power filter and grid connected inverter | |
| CN110212800B (en) | Modular multilevel converter universal control method based on model predictive control | |
| CN112688587A (en) | Robust prediction control method of impedance source inverter | |
| CN111737872B (en) | Margin prediction control method and system based on magnetic characteristics of passive component | |
| CN107171565A (en) | The transient current control method of the double active bridge DC converters of three-phase based on NPC | |
| Chakraborty et al. | A control method to reduce overshoots in high-frequency link current and voltages at load transients of a dual-active-bridge series-resonant converter | |
| CN107785905A (en) | A kind of self-adapting type power grid harmonic suppression device integrated system | |
| CN112202179A (en) | Flux linkage control method for restraining magnetic saturation of voltage compensator series transformer | |
| CN109390948A (en) | A kind of fuzzy model-free self-adaptation control method of low voltage control equipment | |
| Semmah et al. | Comparative study of pi and fuzzy dc voltage control for a dpc-pwm rectifier | |
| CN110688778B (en) | AC side DC bias current prediction method under asymmetric MMC bridge arm impedance | |
| Thanh et al. | A comparative study of control methods for induction motor and high performance Z-source inverter | |
| Liu et al. | LCL filter design with the inductor nonlinear behavior consideration in the three phase grid-connected inverter | |
| CN111245268A (en) | Inverter common-mode voltage suppression method based on logic switching vector optimization selection | |
| Djebbar et al. | Performance and High Robustness DPC for PWM Rectifier under Unstable Direct Voltage Bus | |
| CN115549439B (en) | MMC switching loss optimization method and equipment under low-power operation | |
| CN107994580A (en) | The three-phase four-wire system APF control methods being combined using Cycle Control and SVPWM |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |