CN105891698B - A kind of Boost circuit multi-parameter on-line identification method - Google Patents
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M3/00—Conversion of dc power input into dc power output
- H02M3/02—Conversion of dc power input into dc power output without intermediate conversion into ac
- H02M3/04—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters
- H02M3/10—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
- H02M3/145—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal
- H02M3/155—Conversion of dc power input into dc power output without intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only
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Abstract
The invention discloses a kind of Boost circuit multi-parameter discrimination method, which includes constant pressure source E, inductance and inductance equivalent series resistance, filter capacitor and filter capacitor equivalent series resistance, device for power switching S1, diode S2And load resistance, this method comprises: establishing S respectively according to Boost circuit structure1And S2State equation under different conditions；By the equations of state synthetic state space equation group under different conditions, unified Boost circuit model is obtained；The sampling period is set, by state space equation group discretization, and defines observing matrix and parameter matrix；Sample the switching signal of inductive current, output voltage and switching tube；The least-squares estimation value of parameter matrix is obtained, the device parameter values recognized needed for being calculated with the parameter matrix that above-mentioned estimated value obtains.Using method provided by the invention, the accurate identification of Boost circuit parameter under perfect switch state may be implemented.
Description
Technical Field
The invention relates to a method for identifying circuit fault characteristic parameters, in particular to a method for identifying multiple parameters of a Boost circuit on line.
Background
System fault Prediction and Health Management (PHM) is a comprehensive fault detection, isolation and prediction and Health Management technique. The self health condition of the system is estimated by monitoring the fault characteristic parameters of the system and by means of various reasoning algorithms, the fault of the system can be monitored as early as possible before the fault of the system occurs, the degraded or fault part can be effectively predicted, the degraded or fault part can be accurately positioned, and a maintenance plan is given by combining various information resources, so that the situation-based maintenance and the autonomous guarantee of the system are realized, and the system has very important significance for reducing the maintenance cost, guaranteeing the reliability and the safety of the system, and improving the readiness and success rate of tasks. The PHM mainly comprises two parts of fault prediction and health management, wherein the fault prediction is the basis for realizing the system health management.
The application of power electronic technology can greatly improve the power density of the electric energy conversion device and reduce the volume and the weight. With the development of multi-electric and all-electric airplanes, the electricity consumption of airplanes is continuously increased, and the number of airborne power electronic devices is increased, so that higher requirements on the reliability, maintainability and testability of an airborne power electronic conversion device are provided, and the importance of the PHM of a power electronic system is increased.
Faults of power electronic conversion circuits can be mainly classified into structural faults and parametric faults according to different fault properties. The structural fault refers to a fault that a circuit topology changes due to short circuit or open circuit of a circuit device. Parametric faults refer to soft faults due to degradation of device parameters of the power electronic system. The parametric fault usually does not immediately lead to the system shutdown, but can cause the change of the output characteristic, so that the working performance and the reliability of the system are reduced; if the parametric fault can be predicted in time, the system can be prevented from developing into a worse system structural fault and from being seriously influenced by the structural fault, and the system reliability is greatly improved. Therefore, the key to realize the fault prediction is the accurate extraction of the characteristic parameters.
After the concept of discrete event dynamic system was proposed in the 80 s of the 20 th century, the hybrid system theory became a research hotspot in the field of control theory in recent years through years of research. A hybrid system refers to a system with continuous dynamic behavior and discrete event-driven behavior and the interaction of these two behaviors. Power electronic circuits, as switching power converters, are typically a hybrid dynamic system. The Matthew Senesky is based on the theory of a hybrid automaton, and provides a modeling method of a power electronic circuit based on a hybrid system.
The method comprises the steps that on the basis of the research of hybrid modeling in Zhejiang university, a hybrid system model of the power electronic circuit is constructed by utilizing a switching signal, inductive current and output voltage, and on the basis, the method for identifying the parameters of the power electronic circuit is obtained through a least square algorithm. However, the Boost circuit model thereof can cause the problems that the filter capacitor, the equivalent resistance thereof and the output resistance are difficult to identify in practical application.
Disclosure of Invention
The method takes the Boost circuit as an object, modifies the existing Boost hybrid model, and realizes the online identification of the multiple parameters of the Boost circuit, thereby providing a research basis for the fault prediction of the power electronic circuit.
The invention adopts the following technical scheme for solving the technical problems:
a Boost circuit multi-parameter online identification method is characterized by comprising the following steps:
the method comprises the steps of firstly, determining state variables of a Boost circuit, establishing state equations of the determined state variables in different switch tubular states according to the structure of the Boost circuit, and combining the established state equations into a Boost circuit space state equation set so as to obtain a Boost circuit model;
secondly, discretizing the Boost circuit model obtained in the first step, and then defining an observation matrix phi (t) and a parameter matrix thetanWherein n is 1, 2;
thirdly, sampling the determined state variable and a switching signal of a switching tube to form an observation matrix phi (t);
and fourthly, obtaining a least square estimation value of the parameter matrix through a recursion algorithm, and calculating the parameter value of the element to be identified by using the parameter matrix obtained by the estimation value.
Further, the Boost circuit may equivalently include a constant voltage source E, an inductor and inductor equivalent series resistor, a filter capacitor and filter capacitor equivalent series resistor, and a power switch device S1Diode S2And a load resistor, wherein the negative electrode of the constant voltage source E is grounded, the positive electrode of the constant voltage source E is connected with one end of an inductor, the other end of the inductor is connected with one end of an inductor equivalent series resistor, and the other end of the inductor equivalent series resistor is simultaneously connected with the power switch device S1And diode S2Anode of (2), power switching device S1Is grounded, diode S2The cathode of the filter capacitor is connected with the equivalent series resistor of the filter capacitor and the load resistor at the same time, the other end of the equivalent series resistor of the filter capacitor is connected with the filter capacitor, the other end of the filter capacitor is grounded, and the other end of the load resistor is grounded.
Further, in a first step, the output voltage u across the load resistor is adjustedoAnd an inductor current i flowing through the inductorLfDetermining the state variable as the state variable of the Boost circuit, and establishing the state variable u according to the structure of the Boost circuitoAnd iLfAt the switch tube S1And a diode S2Equation of state in different states:
state 1: switch tube S1Conducting, diode S2Turn off, note: s1＝1，s2When the voltage and current in the state are 0, the system of differential equations of the voltage and the current in the state is as follows:
state 2: switch tube S1Turn-off, diode S2Open, record as: s1＝0，s2The differential equation of the voltage and current in this state is 1:
state 3: switch tube S1Turn-off, diode S2Turn off, note: s1＝0，s2When the voltage and current in the state are 0, the system of differential equations of the voltage and the current in the state is as follows:
using switching signals s1、s2Writing the obtained equations under different switch tubular states into a uniform form:
combining the obtained state equations into a state equation set to obtain a Boost circuit model as follows:
wherein u iso、iLfRespectively output voltage and inductive current;differential quantities of the output voltage and the inductive current are respectively; s1、s2Separately switching tube S1Diode S2Switch signal quantity of, switch tube S1At the time of conduction s11, switching tube S1At turn-off time s10, diode S2At the time of conduction s21, diode S2At turn-off time s2＝0；Lf、Cf、RL、RC、RoRespectively an inductance value and a filter in the Boost circuitA wave capacitance value, an inductance equivalent series resistance value, a filter capacitance equivalent series resistance value and a load resistance value;
in the second step, a sampling period T is set, and the Boost circuit model obtained in the second step is subjected to discretization treatment to obtain:
defining an observation matrix as:
defining a parameter matrix as:
wherein u iso、iLfRespectively an output voltage value and an inductance current value; l isf、Cf、RL、RC、RoRespectively obtaining an inductance value, a filter capacitance value, an inductance equivalent series resistance value, a filter capacitance equivalent series resistance value and a load resistance value in the Boost circuit;
in the third step, the inductive current i at the t-1 moment is obtained according to the set sampling frequencyLf(t-1), output voltage uo(t-1) switching tube switching signal s1(t-1), diode switch signal s2(t-1) obtaining a switching signal s of the diode at the time of t-22(t-2) forming an observation matrix phi (t); obtaining the inductive current i at the moment tLf(t) output voltage uo(t)；
In the fourth step, a parameter matrix theta is obtained through a recurrence algorithmnLeast squares estimate of (d):
wherein n is 1, 2, x1＝iLf(t)，x2＝uo(t)，θnThe estimated values of (c) are:
wherein,are each theta1、θ2An estimated value of (d); a is11、a12、a13、a14、a15、a16、a17Is composed ofOf matrix coefficients, i.e. theta1Each matrix coefficient estimate of a21、a22、a23、a24、a25、a26、a27Is composed ofOf matrix coefficients, i.e. theta2The estimated value of each matrix coefficient;
calculating the element parameter values to be identified according to the relationship between the parameter matrix obtained by estimation and the system parameters:
wherein L isf、RL、Ro、Cf、RCThe inductance value, the equivalent series resistance value of the inductor, the load resistance value, the filter capacitance value and the equivalent series resistance value of the filter capacitor in the Boost circuit are respectively.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
the online identification method provided by the invention has simple circuit, and improves the identification precision on the basis of not increasing electronic components;
after the scheme is adopted, the current detection point is subjected to inductive current and output voltage acquisition, the switching signals of the switching tube and the diode are switched on and off, and the filtering capacitance value C in the circuit can be realized on line by utilizing a recursion algorithm on the basis of a newly established Boost circuit modelfAnd its equivalent series resistance RCFilter inductance value LfAnd its equivalent series resistance RLAnd a load resistance value RoLeast squares estimation of (d);
the multi-parameter online identification method of the Boost circuit has the advantages that the switch switching of the diode is considered, and the filter capacitance C in the circuit is consideredfAnd its equivalent series resistance RCResistance value R of loadoAnd (4) due to the identification influence, the established model is simultaneously suitable for modes of CCM and DCM.
Drawings
FIG. 1 is a schematic diagram of a Boost circuit structure in the method of the present invention;
FIG. 2 is a flow chart of the method of the present invention;
FIG. 3 is a circuit diagram of the present invention.
Detailed Description
The invention provides a Boost circuit multi-parameter online identification method, which aims to make the purpose, technical scheme and effect of the invention clearer and further describes the invention in detail by referring to the attached drawings and taking examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
A Boost circuit multi-parameter online identification method comprises the following steps:
first, determining the output voltage uoAnd the inductor current iLfAnd respectively establishing state equations of the state variables under different switch tubular states according to the Boost circuit structure for the state variables:
state 1: switch tube S1Conducting, diode S2Turn off, note: s1＝1，s2The system of differential equations for voltage and current in this state is listed as 0:
state 2: switch tube S1Turn-off, diode S2Open, record as: s1＝0，s2The system of differential equations for voltage and current in this state is listed as 1:
state 3: switch tube S1Turn-off, diode S2Turn off, note: s1＝0，s2The system of differential equations for voltage and current in this state is listed as 0:
second, using the switching signal s1、s2Writing the equations in different states obtained in the first step into a uniform form:
and further arranging the data into a matrix form to obtain a model of the Boost circuit:
and the third step specifically comprises the steps of setting the sampling period as T, and carrying out discretization treatment on the Boost circuit model obtained in the second step:
defining an observation matrix:
defining a parameter matrix:
fourthly, obtaining the inductive current i at the t-1 moment according to the set sampling frequencyLf(t-1), output voltage uo(t-1) switching tube switching signal s1(t-1), diode switch signal s2(t-1) obtaining a switching signal s of the diode at the time of t-22(t-2) forming an observation matrix phi (t); obtaining the inductive current i at the moment tLf(t) output voltage uo(t)。
Fifthly, obtaining a parameter matrix theta through a recursion algorithmnLeast squares estimate of (d):
wherein n is 1 or 2; x is the number of1＝iLf(t)，x2＝uo(t)；θnThe estimated values of (c) are:
calculating the element parameter values to be identified according to the relationship between the parameter matrix obtained by estimation and the system parameters:
the Boost circuit mentioned herein has a schematic structure as shown in fig. 1, and includes a constant voltage source E and an inductor LfAnd its equivalent series resistance RLFilter capacitor CfAnd its equivalent series resistance RCDiode S2Power switch device S1And a load resistance Ro(ii) a Wherein the negative electrode of the constant voltage source E is groundedThe positive pole of the constant voltage source E is connected with an inductor LfOne end; inductor LfThe other end is connected with an equivalent series resistance R of an inductorLOne end of (a); inductance equivalent series resistance RLThe other end of the first and second switches is connected with a power switch device S1And diode S2The anode of (1); power switch device S1The source of (2) is grounded; diode S2The cathode of the filter capacitor is simultaneously connected with an equivalent series resistor R of the filter capacitorCAnd a load resistor Ro(ii) a Equivalent series resistance R of filter capacitorCThe other end is connected with a filter capacitor Cf(ii) a Filter capacitor CfThe other end of the first and second electrodes is grounded; load resistance RoThe other end is grounded; wherein, the power switch device S1May be a MOSFET or an IGBT.
The simulation circuit diagram of the Boost circuit multi-parameter online identification method provided by the invention is shown in fig. 3, and the simulation conditions, namely the converter parameters, are shown in table 1, wherein the constant voltage source E is 24V, and the inductance L isfInductance equivalent series resistance R of 0.24mHL0.4 Ω, capacitance Cf120 muF, filter capacitance equivalent series resistance RC0.1 Ω, load resistance Ro15 Ω, switching frequency fs50kHz, sampling frequency fc5MHz, duty cycle D is 0.5. Firstly, circuit operation simulation is carried out, after the operation is stopped, signals of inductance current, output voltage and diode voltage are led into the works space of MATLAB, least square estimation is carried out through a recursion algorithm, the result is shown in Table 2, and inductance L isfEstimated value is 0.24019mH, and inductance equivalent series resistance RLIs 0.3954 omega, capacitance CfEstimated value is 120.05 mu F, and filter capacitor equivalent series resistance RCEstimated value of 0.1009 omega, load resistance RoThe estimated value is 14.9964 omega, and the errors of the five are respectively 0.079%, 1.15%, 0.42%, 0.9% and 0.024%, so that the Boost circuit multi-parameter online identification method provided by the invention has high accuracy.
TABLE 1
| E/V | Lf/mH | Cf/μF | Ro/Ω | RL/Ω | RC/Ω | fs/kHz | fc/MHz | D |
| 24 | 0.24 | 120 | 15 | 0.4 | 0.1 | 50 | 5 | 0.5 |
TABLE 2
| Lf/mH | RL/Ω | Cf/μF | RC/Ω | Ro/Ω | |
| Actual value | 0.24 | 0.4 | 120 | 0.1 | 15 |
| Estimated value | 0.24019 | 0.3954 | 120.05 | 0.1009 | 14.9964 |
| Error/%) | 0.079 | 1.15 | 0.042 | 0.9 | 0.024 |
The Boost circuit multi-parameter online identification method has the advantages thatFilter capacitance value C in switch switching pair circuit considering diodefAnd its equivalent series resistance RCResistance value R of loadoAnd (4) due to the identification influence, the established model is simultaneously suitable for modes of CCM and DCM. The model established in the method is more accurate and has higher identification precision than the model proposed by Zhejiang university.
It should be understood that equivalents and modifications of the technical solution and inventive concept thereof may occur to those skilled in the art, and all such modifications and alterations should fall within the scope of the appended claims.
Claims (2)
1. A Boost circuit multi-parameter online identification method is characterized by comprising the following steps:
A. determining state variables of a Boost circuit, establishing state equations of the determined state variables in different switch tubular states according to the structure of the Boost circuit, and combining the established state equations into a Boost circuit space state equation set so as to obtain a Boost circuit model; the Boost circuit model comprises a constant voltage source E, an inductor and an inductor equivalent series resistor, a filter capacitor and a filter capacitor equivalent series resistor, and a power switch device S1Diode S2And a load resistor, wherein the negative electrode of the constant voltage source E is grounded, the positive electrode of the constant voltage source E is connected with one end of an inductor, the other end of the inductor is connected with one end of an inductor equivalent series resistor, and the other end of the inductor equivalent series resistor is simultaneously connected with the power switch device S1And diode S2Anode of (2), power switching device S1Is grounded, diode S2The cathode of the filter capacitor is simultaneously connected with the equivalent series resistor of the filter capacitor and the load resistor, the other end of the equivalent series resistor of the filter capacitor is connected with the filter capacitor, the other end of the filter capacitor is grounded, and the other end of the load resistor is grounded;
B. carrying out discretization treatment on the Boost circuit model obtained in the step A, and then defining an observation matrixAnd a parameter matrix thetanWherein n is 1, 2;
C. sampling the determined state variables and the switching signals of the switching tubes to form an observation matrix
D. And obtaining a least square estimation value of the parameter matrix through a recursion algorithm, and calculating the element parameter value to be identified by using the parameter matrix obtained by the estimation value.
2. The method of claim 1, wherein the method comprises the steps of:
in step A, the output voltage value u at two ends of the load resistor is measuredoAnd the value of the inductor current i flowing through the inductorLfDetermining the state variable as the state variable of the Boost circuit, and establishing the state variable u according to the structure of the Boost circuitoAnd iLfAt the switch tube S1And a diode S2Combining the obtained state equations into a state equation set under different states to obtain a Boost circuit model as follows:
wherein u iso、iLfRespectively an output voltage value and an inductance current value;differential quantities of the output voltage value and the inductance current value are respectively; s1、s2Separately switching tube S1Diode S2Switch signal quantity of, switch tube S1At the time of conduction s11, switching tube S1At turn-off time s10, diode S2At the time of conduction s21, diode S2At turn-off time s2＝0；Lf、Cf、RL、RC、RoRespectively obtaining an inductance value, a filter capacitance value, an inductance equivalent series resistance value, a filter capacitance equivalent series resistance value and a load resistance value in the Boost circuit;
in the step B, a sampling period T is set, and the Boost circuit model obtained in the step A is subjected to discretization treatment to obtain:
defining an observation matrix as:
defining a parameter matrix as:
wherein u iso、iLfAre respectively the output voltageValue, inductance current value; l isf、Cf、RL、RC、RoRespectively obtaining an inductance value, a filter capacitance value, an inductance equivalent series resistance value, a filter capacitance equivalent series resistance value and a load resistance value in the Boost circuit;
in step C, acquiring an inductance current value i at the t-1 moment according to the set sampling frequencyLf(t-1), output voltage value uo(t-1) switching tube switching signal s1(t-1), diode switch signal s2(t-1) obtaining a switching signal s of the diode at the time of t-22(t-2) forming an observation matrixObtaining the value i of the inductance current at the moment tLf(t) output voltage value uo(t)；
In step D, a parameter matrix theta is obtained through a recursion algorithmnLeast squares estimate of (d):
wherein n is 1, 2, x1＝iLf(t)，x2＝uo(t)，θnThe estimated values of (c) are:
wherein,are each theta1、θ2An estimated value of (d); a is11、a12、a13、a14、a15、a16、a17Is composed ofOf matrix coefficients, i.e. theta1Each matrix coefficient estimate of a21、a22、a23、a24、a25、a26、a27Is composed ofOf matrix coefficients, i.e. theta2The estimated value of each matrix coefficient;
calculating the element parameter values to be identified according to the relationship between the parameter matrix obtained by estimation and the system parameters:
wherein L isf、RL、Ro、Cf、RCThe inductance value, the equivalent series resistance value of the inductor, the load resistance value, the filter capacitance value and the equivalent series resistance value of the filter capacitor in the Boost circuit are respectively.
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| US11846668B2 (en) | 2019-03-12 | 2023-12-19 | Schneider Electric Power Drives Gmbh | Method for assessing the thermal loading of a converter |
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| CN106908666A (en) * | 2017-02-23 | 2017-06-30 | 南京航空航天大学 | A kind of Boost circuit and its output capacitance ESR monitoring methods |
| CN110658414B (en) * | 2019-11-08 | 2022-07-12 | 上海科技大学 | Power electronic parametric fault detection method based on model |
| CN111398787B (en) * | 2020-04-17 | 2022-09-16 | 安徽理工大学 | Fault diagnosis method for three-phase voltage type PWM (pulse-width modulation) rectification circuit under complex working condition |
| CN112782633A (en) * | 2020-12-24 | 2021-05-11 | 深圳市优优绿能电气有限公司 | Inductive current sampling calibration method, system and computer readable storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103472381A (en) * | 2013-09-27 | 2013-12-25 | 南京航空航天大学 | Power switch tube fault characteristic parameter extracting method |
| CN103675524A (en) * | 2013-11-14 | 2014-03-26 | 国家电网公司 | Photovoltaic power generation system model parameter identification test method |
| CN104750915A (en) * | 2015-03-06 | 2015-07-01 | 南京航空航天大学 | Buck circuit multiparameter on-line identification method |
-
2016
- 2016-03-31 CN CN201610196539.8A patent/CN105891698B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103472381A (en) * | 2013-09-27 | 2013-12-25 | 南京航空航天大学 | Power switch tube fault characteristic parameter extracting method |
| CN103675524A (en) * | 2013-11-14 | 2014-03-26 | 国家电网公司 | Photovoltaic power generation system model parameter identification test method |
| CN104750915A (en) * | 2015-03-06 | 2015-07-01 | 南京航空航天大学 | Buck circuit multiparameter on-line identification method |
Non-Patent Citations (2)
| Title |
|---|
| 兼顾电感电流连续导通和断续运行模式的DC/DC电路建模和参数辨识;马皓等;《中国电机工程学报》;20100331;第26卷(第5期);64-69 |
| 基于混杂系统模型的电力电子电路故障诊断;刘佳;《中国优秀硕士学位论文全文数据库 信息科技辑（月刊 ）》;20120315(第03期);I135-200 正文第14-17、34-35页 |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11846668B2 (en) | 2019-03-12 | 2023-12-19 | Schneider Electric Power Drives Gmbh | Method for assessing the thermal loading of a converter |
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