CN113884928B - Multi-stack distributed control method based on fuel cell health degree correction - Google Patents
Multi-stack distributed control method based on fuel cell health degree correction Download PDFInfo
- Publication number
- CN113884928B CN113884928B CN202111111502.8A CN202111111502A CN113884928B CN 113884928 B CN113884928 B CN 113884928B CN 202111111502 A CN202111111502 A CN 202111111502A CN 113884928 B CN113884928 B CN 113884928B
- Authority
- CN
- China
- Prior art keywords
- fuel cell
- current
- voltage
- real
- rated
- 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
- 239000000446 fuel Substances 0.000 title claims abstract description 177
- 230000036541 health Effects 0.000 title claims abstract description 51
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000012937 correction Methods 0.000 title claims abstract description 21
- 238000004364 calculation method Methods 0.000 claims abstract description 15
- 230000008859 change Effects 0.000 claims abstract description 9
- 238000002474 experimental method Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 abstract description 5
- 238000004891 communication Methods 0.000 abstract description 3
- 238000011161 development Methods 0.000 description 3
- 230000018109 developmental process Effects 0.000 description 3
- 238000005457 optimization Methods 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 229910052739 hydrogen Inorganic materials 0.000 description 2
- 239000001257 hydrogen Substances 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000003487 electrochemical reaction Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/374—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] with means for correcting the measurement for temperature or ageing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/389—Measuring internal impedance, internal conductance or related variables
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Fuel Cell (AREA)
Abstract
The invention discloses a multi-stack distributed control method based on fuel cell health degree correction, which comprises the steps of collecting voltage and current signals at the output end of a fuel cell, collecting voltage and current signals at the output end of a unidirectional converter, and collecting voltage and current signals at a demand side; evaluating the real-time operation performance of the fuel cell through the acquired output end voltage, current and power of the fuel cell, and quantifying the health degree of each fuel cell; calculating real-time self-setting factors related to the current performance state of each fuel cell by combining the circuit and current-carrying characteristics of a direct current power supply network according to the calculation result of the health degree of the fuel cells; and finally, completing the self-adaptive adjustment of the output power of the fuel cell through the rapid correction of the voltage outer ring and the current inner ring under the change of the real-time self-setting factor, and realizing the distributed control among the fuel cells of multiple stacks. The invention is beneficial to any galvanic pile access system or fault galvanic pile exit system, reduces communication fault, enhances system stability and is beneficial to system capacity expansion.
Description
Technical Field
The invention belongs to the technical field of fuel cells, and particularly relates to a power distribution management and control method of a fuel cell cluster.
Background
With the rapid development of world science and technology, energy which pollutes the serious environment urgently needs new environment-friendly energy to replace, energy conservation and emission reduction become directions of continuous efforts of scientific research institutes of all countries, in the application of numerous new energy, hydrogen energy is taken as a new energy which is efficient, safe, clean and sustainable, and is regarded as the development direction of clean energy and strategic energy of human beings with the most development potential in the 21 st century, and a fuel cell is a device which converts hydrogen energy into electric energy through electrochemical reaction, and has the advantages of no restriction of Carnot cycle, high energy conversion efficiency, low working temperature, high starting speed, low operation noise and the like.
Although the fuel cell has many advantages, the fuel cell has the defects of limited power grade, insufficient durability and the like of a single set of power generation system, so that the fuel cell cannot be put into use on a large scale in a large-power energy market. Therefore, more and more researchers are building multi-stack fuel cell systems to solve the above problems by coordinating a plurality of individual fuel cells. However, most of the current research on multi-stack fuel cell systems are composed of single-stack fuel cells with the same power generation parameters, and no intensive research has been conducted on a method for coordinating and controlling multi-stack fuel cell systems. In addition, most of the existing control strategies are based on an ideal situation, the fuel cell is regarded as a static power generation system, and the influence caused by the change of the operation performance of the electric pile is not considered on the assumption that the operation performance of the electric pile does not change. In practical applications, the fuel cell is greatly influenced by environmental factors such as temperature, pressure, humidity, etc., and the operation state of the electric pile needs to be evaluated in real time, and a proper control method is timely and effectively implemented according to the respective health degrees of the electric pile, so that the normal and stable operation of a multi-pile fuel cell system is ensured.
Disclosure of Invention
In order to solve the problems, the invention provides a multi-stack distributed control method based on fuel cell health degree correction, which is used for adaptively adjusting the stack output power of a multi-stack fuel cell according to the real-time running performance of each stack so as to improve the system running performance. Considering that a certain electric pile in a multi-pile system can suddenly quit due to a fault, and meanwhile, in order to realize a plug and play function, a control method based on self-setting factor adjustment is adopted, and an adjustment factor self-adaptive adjustment setting coefficient is designed according to the real-time operation performance of each electric pile to realize the distribution of reference power.
In order to achieve the purpose, the invention adopts the technical scheme that: a multi-stack distributed control method based on fuel cell health correction, comprising the steps of:
s100, collecting voltage and current signals of the output end of the fuel cell, collecting voltage and current signals of the output end of the unidirectional DC/DC converter, and collecting voltage and current signals of a demand side;
s200, evaluating the real-time operation performance of the fuel cell through the acquired output end voltage, current and power of the fuel cell, and quantifying the health degree of each fuel cell;
s300, calculating real-time self-setting factors related to the current performance state of each fuel cell by combining the circuit and current-carrying characteristics of a direct current power supply network according to the calculation result of the health degree of the fuel cell;
and S400, finally, completing the self-adaptive adjustment of the output power of the fuel cell through the rapid correction of the voltage outer ring and the current inner ring under the change of the real-time self-setting factor, and realizing the distributed control among the fuel cells of multiple stacks.
Furthermore, the multi-stack fuel cell system comprises a plurality of fuel cells which supply power to the bus in a full parallel connection mode, and all the fuel cells are connected to the direct current bus through respective one-way DC/DC converters, so that the stability of the voltage of the output power fluctuation load side is ensured, and the power supply quality is improved.
Further, when the health degree of the real-time operation performance of the fuel cell is calculated in step S200, the rated voltage of the fuel cell at the time of the optimal performance of the corresponding stack is calculated according to the real-time output current of the fuel cell, and the health degree is calculated according to the maximum voltage drop allowed at the time of the rated current.
Further, the calculation formula of the health degree of the real-time operation performance of the fuel cell in the step S200 is as follows:
the health degree considering the performance of the fuel cell is HFCAnd has the formula:
in the formula,. DELTA.VratedThe voltage drop of the pile when the pile outputs rated current under the current performance is shown, and further the voltage drop is shown as rated voltage V when the pile performance is optimalrated,initWith current performance stateRated voltage Vrated,degradedThe difference between the two; Δ Vrated,maxThe maximum voltage drop allowed at the rated current is 10% of the rated voltage.
Furthermore, the rated voltage V when the corresponding electric pile performance is optimal under the real-time output current of the fuel cellrated,initThe acquisition process comprises the following steps:
carrying out test experiments on the fuel cell with good performance to obtain experimental data of current and voltage running under different power levels;
through the analysis of experimental data of voltage and current, the relation between the ideal output voltage and the operating current of the fuel cell is reversely deduced;
method for identifying ideal output voltage and operating current coefficient a of fuel cell by adopting complex nonlinear least square algorithm0、a1、…、anN is the order determined by experiment to obtain the rated voltage V when the corresponding electric pile performance is optimal under the real-time output current of the fuel cellrated,init。
Further, the method adopts a complex nonlinear least square algorithm to identify the coefficients of ideal output voltage and operation current of the fuel cell, and specifically comprises the following steps:
for a fuel cell system: y ═ f (x, θ);
wherein y is the ideal voltage value of the fuel cell; x is the measured current when the fuel cell is working; θ is the parameter vector to be identified:
and has the following components:
where N is the number of frequency samples, wk is the residual weight, S is the residual weighted sum of the measured value and the fitted value, and ΔlFor error accuracy, Δ is when θ (k +1) and θ (k) are infinitely closelWill be very smallThe recognition result tends to be stable.
Further, in step S300, the output power of each fuel cell is calculated according to the calculation result of the health degree of the fuel cell, and the real-time self-tuning factor related to the current performance state of each fuel cell is calculated according to the output power of the fuel cell and by combining the circuit and the current-carrying characteristics of the dc power supply network.
Further, the method for calculating the output power of each fuel cell based on the calculation result of the health degree of the fuel cell includes the steps of:
estimating the health ratio of each fuel cell in operation in real time according to the measured voltage change;
and calculating the output power of each fuel cell in the multi-stack fuel cell system according to the health ratio.
Further, the method is characterized in that a real-time self-setting factor related to the current performance state of each fuel cell is calculated according to the output power of the fuel cell and by combining the circuit and current-carrying characteristics of a direct current power supply network, and comprises the following steps:
the self-setting factor of the output end of the unidirectional DC/DC converter configured for each fuel cell is considered to be KdroopAiming at a direct current power supply system with a parallel structure, an equation set can be constructed according to kirchhoff voltage and current laws;
and calculating the real-time value of the corresponding self-setting factor under the output power of each fuel cell according to the constructed equation set and the circuit and current-carrying characteristics of the direct-current power supply network.
Further, in the step S400, a corresponding self-setting factor is added to the power at the output end of the unidirectional DC/DC converter configured for each fuel cell, the unidirectional DC/DC converter can be controlled to output corresponding power by changing the size of the self-setting factor, and the self-adaptive adjustment of the output power of the fuel cell is completed by the rapid correction of the voltage outer ring and the current inner ring, so as to implement the distributed control among the fuel cells in multiple stacks.
The beneficial effects of the technical scheme are as follows:
the method comprises the steps of firstly, respectively acquiring voltage and current signals of the input end of a fuel cell and the output end of a unidirectional DC/DC converter and voltage and current of a load demand side in real time by means of a high-precision sensor, storing the voltage and current signals and the voltage and current of the load demand side into a controller, then, evaluating the real-time operation performance condition of the fuel cell according to the measured voltage, current and power, quantizing the health degree of each fuel cell for the first time, finally, calculating a real-time self-setting factor related to the current health degree of each fuel cell by combining the circuit and current-carrying characteristics of a direct-current power supply network, and completing self-adaptive adjustment of the output power of each fuel cell through a voltage outer ring and a current inner ring, thereby realizing the distributed control among multiple fuel cells. The invention is beneficial to any galvanic pile access system or fault galvanic pile exit system, reduces communication fault, enhances system stability, and is beneficial to system capacity expansion.
The invention adopts the real-time operation performance of each galvanic pile to adaptively adjust the output power of the galvanic pile, thereby improving the operation performance of the system. Meanwhile, a droop control method based on health degree setting is adopted, and adjustment factors are designed according to the real-time running performance of each electric pile to adaptively adjust droop coefficients to realize the distribution of reference power, so that the possibility of system faults is reduced, the fault-tolerant capability and the power supply reliability of the system are improved, and the plug-and-play function is realized. The multi-stack fuel cell system adopts distributed control to ensure that each stack can self-adaptively adjust the output power according to the performance quality and the health degree relationship, thereby not only improving the consistency of the system, but also improving the reliability of the power supply of the system and the fault tolerance of the system.
The invention provides a calculation formula for real-time operation performance evaluation, and quantifies the operation aging degree of the fuel cell to provide a control basis for power distribution of a multi-stack fuel cell system.
The invention adopts the complex nonlinear least square algorithm to fit the relation between the ideal voltage and the output current of the fuel cell in real time, and determines the coupling coefficient a of the fuel cell0、a1、…、anCompared with other methods, the iterative solution of the complex nonlinear least square algorithm is adopted, the amount of the utilized measurement data is small, the fitting error can be reduced, and the engineering practicability is high.
The invention simplifies the quantitative relation between the output power of the fuel cell and the added self-setting factor by analyzing the basic circuit of the parallel direct current power supply system, directly couples the performance of the fuel cell with the control variable, reduces the communication relation between the galvanic pile, enhances the stability of the system and promotes the expansion ductility of the system.
Drawings
FIG. 1 is a schematic flow chart of a multi-stack distributed control method based on fuel cell health correction according to the present invention;
FIG. 2 is a schematic structural diagram of a multi-stack fuel cell system with setting factors according to an embodiment of the invention;
fig. 3 is a simplified equivalent circuit diagram of the output of the unidirectional DC/DC converter in the multi-stack fuel cell system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described with reference to the accompanying drawings.
In this embodiment, referring to fig. 1, the present invention provides a multi-stack distributed control method based on fuel cell health correction, comprising the steps of:
s100, collecting voltage and current signals of the output end of the fuel cell, collecting voltage and current signals of the output end of the unidirectional DC/DC converter, and collecting voltage and current signals of a demand side;
s200, evaluating the real-time operation performance of the fuel cell through the acquired output end voltage, current and power of the fuel cell, and quantifying the health degree of each fuel cell;
s300, calculating real-time self-setting factors related to the current performance state of each fuel cell by combining the circuit and current-carrying characteristics of a direct current power supply network according to the calculation result of the health degree of the fuel cell;
and S400, finally, completing the self-adaptive adjustment of the output power of the fuel cell through the rapid correction of the voltage outer ring and the current inner ring under the change of the real-time self-setting factor, and realizing the distributed control among the fuel cells of multiple stacks.
The multi-stack fuel cell system comprises a plurality of fuel cells which supply power to a bus in a full parallel mode, and all the fuel cells are connected to a direct current bus through respective one-way DC/DC converters, so that the stability of the voltage of an output power fluctuation load side is ensured, and the power supply quality is improved.
As an optimization scheme of the foregoing embodiment, when the health degree of the real-time operation performance of the fuel cell is calculated in step S200, the rated voltage when the performance of the corresponding stack is optimal is calculated according to the real-time output current of the fuel cell, and the health degree is calculated according to the maximum voltage drop allowed at the rated current.
The calculation formula of the health degree of the real-time operation performance of the fuel cell is as follows:
the health degree considering the performance of the fuel cell is HFCAnd has the formula:
in the formula,. DELTA.VratedThe voltage drop of the pile when the pile outputs rated current under the current performance is shown, and further the voltage drop is shown as rated voltage V when the pile performance is optimalrated,initRated voltage V corresponding to current performance staterated,degradedThe difference between the two; Δ Vrated,maxThe maximum voltage drop allowed at the rated current is 10% of the rated voltage.
Furthermore, the rated voltage V when the corresponding electric pile performance is optimal under the real-time output current of the fuel cellrated,initThe acquisition process comprises the following steps:
carrying out test experiments on the fuel cell with good performance to obtain experimental data of current and voltage running under different power levels;
through the analysis of experimental data of voltage and current, the relation between the ideal output voltage and the operating current of the fuel cell is reversely deduced;
method for identifying ideal output voltage and operating current coefficient a of fuel cell by adopting complex nonlinear least square algorithm0、a1、…、anN is the order determined experimentally, is obtainedObtaining the rated voltage V when the corresponding electric pile performance is optimal under the real-time output current of the fuel cellrated,init。
The method comprises the following steps of identifying coefficients of ideal output voltage and operation current of the fuel cell by adopting a complex nonlinear least square algorithm, and specifically comprising the following steps of:
for a fuel cell system: y ═ f (x, θ);
wherein y is the ideal voltage value of the fuel cell; x is the measured current when the fuel cell is working; θ is the parameter vector to be identified:
and has the following components:
wherein N is the number of frequency sampling points, wk is the residual weight, S is the residual weighted sum of the measured value and the fitting value, and deltalFor error accuracy, Δ is when θ (k +1) and θ (k) are infinitely closelWill be very small and the recognition result will tend to be stable.
As an optimization solution of the above embodiment, in step S300, the output power of each fuel cell is calculated according to the calculation result of the health degree of the fuel cell, and the real-time self-tuning factor related to the current performance state of each fuel cell is calculated according to the output power of the fuel cell and by combining the circuit and the current-carrying characteristics of the dc power supply network.
Wherein, according to the health degree calculation result to the fuel cell, calculate each fuel cell output power, comprising the step:
and estimating the health ratio of each fuel cell in operation in real time according to the measured voltage change:
in the formula, LijRepresenting the ratio of the output power fluctuation quantity of the ith branch circuit converter to the output power fluctuation quantity of the jth branch circuit converter;
calculating the output power of each fuel cell in the multi-stack fuel cell system according to the health ratio:
in the formula,. DELTA.PdciRepresenting the amount of output power fluctuation, P, of the i-th branch converterdci(0) And the initial output power of the ith branch converter is shown.
As shown in fig. 2 and 3, calculating a real-time self-tuning factor related to the current performance state of each fuel cell according to the output power of the fuel cell and combining the circuit and current-carrying characteristics of the direct-current power supply network includes the steps of:
considering that the self-setting factor of the output end of the unidirectional DC/DC converter configured for each fuel cell is KdroopAiming at the direct-current power supply system with the parallel structure, an equation set can be constructed according to kirchhoff voltage and current law:
in the formula Idci、VdciAnd RliRespectively representing the output current, voltage and line impedance of the ith branch converter of the system, wherein the line impedance RliUsually very small and, if necessary, negligible, RloadRepresenting the load resistance, KdroopiSelf-tuning factor, V, representing the addition of the ith branchbusIs a dc bus voltage;
and (3) calculating the real-time value of the self-setting factor corresponding to each fuel cell under the output power according to the established equation set and the circuit and current-carrying characteristics of the direct-current power supply network:
wherein,
as an optimization scheme of the above embodiment, in the step S400, a corresponding self-setting factor is added to the power at the output end of the unidirectional DC/DC converter configured for each fuel cell, the unidirectional DC/DC converter can be controlled to output corresponding power by changing the size of the self-setting factor, and the self-adaptive adjustment of the output power of the fuel cell is completed by the rapid correction of the voltage outer loop and the current inner loop, so as to implement distributed control among multiple fuel cells.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. A multi-stack distributed control method based on fuel cell health correction, comprising the steps of:
s100, collecting voltage and current signals of the output end of the fuel cell, collecting voltage and current signals of the output end of the unidirectional DC/DC converter, and collecting voltage and current signals of a demand side;
s200, evaluating the real-time operation performance of the fuel cell through the acquired output end voltage, current and power of the fuel cell, and quantifying the health degree of each fuel cell; during the calculation of the health degree of the real-time operation performance of the fuel cell in the step S200, the rated voltage of the fuel cell corresponding to the fuel cell when the performance of the fuel cell is optimal is calculated according to the real-time output current of the fuel cell, and the health degree is calculated according to the maximum voltage drop allowed by the fuel cell when the rated current is adopted;
the calculation formula of the health degree of the real-time operation performance of the fuel cell in the step S200 is as follows:
the health degree considering the performance of the fuel cell is HFCAnd has the formula:
in the formula,. DELTA.VratedThe voltage drop of the galvanic pile when the galvanic pile outputs rated current under the current performance is expressed, and further expressed as rated voltage V when the galvanic pile performance is optimalrated_initRated voltage V corresponding to current performance staterated_DThe difference between the two; Δ Vrated_maxThe maximum voltage drop allowed in rated current is represented, and the value is 10% of the rated voltage;
s300, calculating real-time self-setting factors related to the current performance state of each fuel cell by combining the circuit and current-carrying characteristics of a direct current power supply network according to the calculation result of the health degree of the fuel cell;
s400, finally, completing the self-adaptive adjustment of the output power of the fuel cell through the rapid correction of the voltage outer ring and the current inner ring under the change of the real-time self-setting factor, and realizing the distributed control among the fuel cells of multiple stacks;
in the step S400, a corresponding self-setting factor is added to the power at the output end of the unidirectional DC/DC converter configured for each fuel cell, the magnitude of the self-setting factor is changed through the set of equations, so as to control the unidirectional DC/DC converter to output the corresponding power, and the self-adaptive adjustment of the output power of the fuel cells is completed through the fast correction of the voltage outer ring and the current inner ring, thereby implementing the distributed control among the fuel cells.
2. The multi-stack distributed control method based on fuel cell health correction according to claim 1, wherein the multi-stack fuel cell system comprises a plurality of fuel cells which supply power to the bus in a full parallel manner, and all the fuel cells are connected to the direct current bus through respective unidirectional DC/DC converters.
3. The fuel cell health correction-based multi-stack distributed control method according to claim 1, wherein the rated voltage V at which the corresponding stack performance is optimal under the real-time output current of the fuel cell is the rated voltage Vrated_initThe acquisition process comprises the following steps:
carrying out test experiments on the fuel cell with good performance to obtain experimental data of current and voltage running under different power levels;
through the analysis of experimental data of voltage and current, the relation between the ideal output voltage and the operating current of the fuel cell is reversely deduced;
method for identifying ideal output voltage and operating current coefficient a of fuel cell by adopting complex nonlinear least square algorithm0、a1、…、anN is the order determined by experiment to obtain the rated voltage V when the corresponding electric pile performance is optimal under the real-time output current of the fuel cellrated_init。
4. The multi-stack distributed control method based on fuel cell health correction according to claim 3, characterized in that coefficients for identifying ideal output voltage and operating current of the fuel cell based on a complex nonlinear least squares algorithm are adopted, specifically:
for a fuel cell system: y ═ f (x, θ);
wherein y is the ideal voltage value of the fuel cell; x is the measured current when the fuel cell is working; θ is the parameter vector to be identified:
and has the following components:
where N is the number of frequency samples, wk is the residual weight, S is the residual weighted sum of the measured value and the fitted value, and ΔlFor error accuracy, Δ is when θ (k +1) and θ (k) are infinitely closelIt will be very small and the recognition result will tend to be stable.
5. The multi-stack distributed control method based on fuel cell health correction according to claim 1, wherein in step S300, the output power of each fuel cell is calculated according to the calculation result of the health of the fuel cell, and the real-time self-tuning factor related to the current performance state of each fuel cell is calculated according to the output power of the fuel cell and the circuit and current-carrying characteristics of the direct current power supply network.
6. The multi-stack distributed control method based on fuel cell health correction according to claim 5, wherein the output power of each fuel cell is calculated based on the calculation result of the health of the fuel cell, comprising the steps of:
estimating the health ratio of each fuel cell in operation in real time according to the measured voltage change;
and calculating the output power of each fuel cell in the multi-stack fuel cell system according to the health ratio.
7. The multi-stack distributed control method based on the fuel cell health correction according to claim 5, wherein the real-time self-tuning factor related to the current performance state of each fuel cell is calculated according to the output power of the fuel cell and the circuit and current-carrying characteristics of the direct current power supply network, and the method comprises the following steps:
taking into account the unidirectional configuration of each fuel cellThe self-tuning factor of the output end of the DC/DC converter is KdroopAiming at a direct-current power supply system with a parallel structure, an equation set can be constructed according to kirchhoff voltage and current laws;
and calculating the real-time value of the corresponding self-setting factor under the output power of each fuel cell according to the constructed circuit combined with the direct current power supply network and the current-carrying characteristics.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111111502.8A CN113884928B (en) | 2021-09-23 | 2021-09-23 | Multi-stack distributed control method based on fuel cell health degree correction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111111502.8A CN113884928B (en) | 2021-09-23 | 2021-09-23 | Multi-stack distributed control method based on fuel cell health degree correction |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113884928A CN113884928A (en) | 2022-01-04 |
| CN113884928B true CN113884928B (en) | 2022-06-21 |
Family
ID=79009954
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111111502.8A Active CN113884928B (en) | 2021-09-23 | 2021-09-23 | Multi-stack distributed control method based on fuel cell health degree correction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113884928B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114384423A (en) * | 2022-01-07 | 2022-04-22 | 重庆大学 | Fuel cell health state identification method based on typical operation parameters |
| CN114662900A (en) * | 2022-03-21 | 2022-06-24 | 山东氢探新能源科技有限公司 | Energy management method and system for multiple fuel cell nodes |
| CN116341395B (en) * | 2023-05-29 | 2023-08-01 | 西北工业大学 | Energy management method, system, equipment and terminal for multi-stack fuel cell aircraft |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102340152A (en) * | 2010-07-15 | 2012-02-01 | 中兴电工机械股份有限公司 | System for connecting multiple groups of fuel battery converters in parallel and control method thereof |
| CN112366678A (en) * | 2020-11-13 | 2021-02-12 | 株洲国创轨道科技有限公司 | Power distribution method and system for parallel fuel cell power system |
| CN113043917A (en) * | 2021-04-15 | 2021-06-29 | 西南交通大学 | Layered control method for multi-stack fuel cell hybrid power system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6387556B1 (en) * | 1997-11-20 | 2002-05-14 | Avista Laboratories, Inc. | Fuel cell power systems and methods of controlling a fuel cell power system |
| US7362073B2 (en) * | 2003-11-21 | 2008-04-22 | Mti Microfuel Cells, Inc. | Dynamic fuel cell system management controller |
| US8963369B2 (en) * | 2007-12-04 | 2015-02-24 | Solaredge Technologies Ltd. | Distributed power harvesting systems using DC power sources |
-
2021
- 2021-09-23 CN CN202111111502.8A patent/CN113884928B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102340152A (en) * | 2010-07-15 | 2012-02-01 | 中兴电工机械股份有限公司 | System for connecting multiple groups of fuel battery converters in parallel and control method thereof |
| CN112366678A (en) * | 2020-11-13 | 2021-02-12 | 株洲国创轨道科技有限公司 | Power distribution method and system for parallel fuel cell power system |
| CN113043917A (en) * | 2021-04-15 | 2021-06-29 | 西南交通大学 | Layered control method for multi-stack fuel cell hybrid power system |
Non-Patent Citations (3)
| Title |
|---|
| On Maximizing the Steady-State Efficiency of a Multi-Stack Fuel Cell System;Neigel Marx 等;《2018 IEEE Vehicle Power and Propulsion Conference (VPPC)》;20181231;第1-6页 * |
| 基于功率自适应分配的多堆燃料电池系统效率协调优化控制;朱亚男 等;《中国电机工程学报》;20190320;第39卷(第6期);第1714-1722页 * |
| 多模块燃料电池混合动力系统功率分配研究;尹章文 等;《电源技术》;20181231;第42卷(第12期);第1857-1868页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113884928A (en) | 2022-01-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113884928B (en) | Multi-stack distributed control method based on fuel cell health degree correction | |
| Kim et al. | State-of-health diagnosis based on hamming neural network using output voltage pattern recognition for a PEM fuel cell | |
| CN108241128B (en) | A kind of proton exchange film fuel battery system method for estimating state | |
| Ramos-Paja et al. | Mathematical analysis of hybrid topologies efficiency for PEM fuel cell power systems design | |
| CN107169170B (en) | A kind of prediction technique of battery remaining power | |
| CN112630659A (en) | Lithium battery SOC estimation method based on improved BP-EKF algorithm | |
| CN110212551B (en) | Micro-grid reactive power automatic control method based on convolutional neural network | |
| She et al. | Multiobjective control of PEM fuel cell system with improved durability | |
| CN110137547A (en) | Control method, device and the electronic equipment of fuel cell system with reformer | |
| CN118336885B (en) | Hybrid power electric energy supply method and system based on super-capacity energy storage | |
| CN113459902B (en) | Power distribution method for realizing maximum efficiency operation of fuel cell array | |
| CN111327048A (en) | Robust operation optimization method for power distribution network containing three-terminal SNOP | |
| CN117895613A (en) | Energy management method of flow battery-lithium battery hybrid energy storage system | |
| CN110994686B (en) | Discrete power generation, energy storage and power supply system cooperative control method | |
| CN110011424B (en) | Safety and stability control method for distributed cloud energy storage system of intelligent micro-grid | |
| CN114825402B (en) | Self-adaptive collaborative terminal sliding mode control method, medium, electronic equipment and system | |
| Li et al. | A wind power prediction model based on optimized N-BEATS network with multivariate inputs | |
| CN109449968B (en) | Power electronic transformer and AC/DC source network load multi-current equipment integration method | |
| CN113241793A (en) | Prevention control method for power system with IPFC (intelligent power flow controller) considering wind power scene | |
| CN117767369B (en) | Energy storage site selection and hierarchical configuration method considering medium-long term planning | |
| CN114844052B (en) | Voltage reactive power optimization control method based on active power distribution network | |
| Guo et al. | Voltage stability control method based on comprehensive principal component analysis and improved neural network | |
| Zhang et al. | Research on Output Characteristics of the Proton Exchange Membrane Fuel Cell Based on Model Reference Adaptive Control | |
| CN118707363A (en) | Self-adaptive fusion filtering SOC estimation method for marine battery system | |
| Huajun et al. | Multi-objective reinforcement learning algorithm and its application in drive system |
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 |