CN114491947A - Modeling method and simulation method of fuel cell - Google Patents
Modeling method and simulation method of fuel cell Download PDFInfo
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- 239000000446 fuel Substances 0.000 title claims abstract description 290
- 238000000034 method Methods 0.000 title claims abstract description 39
- 238000004088 simulation Methods 0.000 title claims description 30
- 239000007789 gas Substances 0.000 claims abstract description 52
- 239000001257 hydrogen Substances 0.000 claims abstract description 42
- 229910052739 hydrogen Inorganic materials 0.000 claims abstract description 42
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 claims abstract description 39
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 25
- 239000001301 oxygen Substances 0.000 claims abstract description 25
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 25
- 238000001816 cooling Methods 0.000 claims abstract description 19
- 238000006243 chemical reaction Methods 0.000 claims abstract description 12
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 12
- 239000003792 electrolyte Substances 0.000 claims abstract description 10
- 239000012528 membrane Substances 0.000 claims abstract description 7
- 230000010287 polarization Effects 0.000 claims description 29
- 239000003990 capacitor Substances 0.000 claims description 20
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 claims description 9
- 230000004913 activation Effects 0.000 claims description 6
- 239000003054 catalyst Substances 0.000 claims description 4
- 239000000126 substance Substances 0.000 claims description 4
- 239000013543 active substance Substances 0.000 claims 1
- 230000008859 change Effects 0.000 abstract description 9
- 238000004590 computer program Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 5
- 239000000463 material Substances 0.000 description 5
- 238000012546 transfer Methods 0.000 description 5
- 150000002500 ions Chemical class 0.000 description 4
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical group C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 4
- 239000005518 polymer electrolyte Substances 0.000 description 4
- 238000005094 computer simulation Methods 0.000 description 3
- 239000004065 semiconductor Substances 0.000 description 3
- NBIIXXVUZAFLBC-UHFFFAOYSA-N Phosphoric acid Chemical compound OP(O)(O)=O NBIIXXVUZAFLBC-UHFFFAOYSA-N 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 239000008151 electrolyte solution Substances 0.000 description 2
- 238000001704 evaporation Methods 0.000 description 2
- 230000008020 evaporation Effects 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- BVKZGUZCCUSVTD-UHFFFAOYSA-L Carbonate Chemical compound [O-]C([O-])=O BVKZGUZCCUSVTD-UHFFFAOYSA-L 0.000 description 1
- 229910000147 aluminium phosphate Inorganic materials 0.000 description 1
- 239000000969 carrier Substances 0.000 description 1
- 239000004020 conductor Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000005684 electric field Effects 0.000 description 1
- 150000002431 hydrogen Chemical class 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- POFWRMVFWIJXHP-UHFFFAOYSA-N n-benzyl-9-(oxan-2-yl)purin-6-amine Chemical compound C=1C=CC=CC=1CNC(C=1N=C2)=NC=NC=1N2C1CCCCO1 POFWRMVFWIJXHP-UHFFFAOYSA-N 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
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- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/30—Hydrogen technology
- Y02E60/50—Fuel cells
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Abstract
The embodiment of the invention discloses a modeling method of a fuel cell. The method comprises the following steps: determining parameters of the fuel cell stack, wherein the parameters at least comprise hydrogen partial pressure, oxygen partial pressure, temperature of the fuel cell and water content of an electrolyte membrane, and constructing a fuel cell stack model according to the parameters of the fuel cell stack; constructing a feed tube model based on the gas volume of the feed tube being the sum of the difference of the inlet gas minus the exhaust gas and the gas consumed in the anode channel or cathode channel reactions, and the ratio of the outlet gas rate to the internal gas partial pressure being a constant value; constructing a fuel processor model from the hydrogen producing fuel; a cooling system model is constructed based on the difference between the actual voltage and the maximum voltage of the fuel cell stack representing the energy that is not converted to electrical energy and released in the form of heat. By the method, each part of the fuel cell is independently modeled, and the influence of the temperature change of the fuel cell on the model parameters is considered when the fuel cell stack model is constructed, so that the accuracy of the model is improved.
Description
Technical Field
The invention relates to the field of fuel cells, in particular to a modeling method of a fuel cell, a simulation method and a simulation device.
Background
A fuel cell is an electrochemical cell that generates electrical energy and is comprised of two conductors, referred to as electrodes, and a conductive membrane between the electrodes, referred to as an electrolyte. Among them, fuel cells are classified into the following types according to the type of electrolyte used: polymer electrolyte fuel cells, alkaline fuel cells, battery phosphoric acid fuel, molten carbonate fuel cells, and battery solid oxide fuel. Polymer electrolyte fuel cells are more suitable for use in hydrogen-fueled vehicles due to low temperature, low operating pressure, and high power density compared to other types of fuel cells. In the prior art, modeling of fuel cells is generally divided into two categories: a theoretical model based on physical rules, a quasi-experimental model obtained through actual experiments based on the previously proposed model. The two modeling methods do not consider the influences of temperature change, mass transfer loss, double-layer load and the like during operation, and further the accuracy of the model is low.
In summary, how to effectively model the fuel cell and improve the accuracy of the model is a problem to be solved at present.
Disclosure of Invention
In view of this, embodiments of the present invention provide a modeling method for a fuel cell, and a method and an apparatus for simulation, which can perform individual modeling on each part of the fuel cell, and take into account the influence of the temperature change of the fuel cell on the model parameters when constructing a fuel cell stack model, thereby improving the accuracy of the model.
In a first aspect, an embodiment of the present invention provides a modeling method for a fuel cell, including: determining parameters of a fuel cell stack, wherein the parameters at least comprise hydrogen partial pressure, oxygen partial pressure, temperature of a fuel cell and water content of an electrolyte membrane, and constructing a fuel cell stack model according to the parameters of the fuel cell stack; constructing a feed tube model based on the gas volume of the feed tube being the sum of the difference of the inlet gas minus the exhaust gas and the gas consumed in the anode channel or cathode channel reactions, and the ratio of the outlet gas rate to the internal gas partial pressure being a constant value; constructing a fuel processor model from the hydrogen producing fuel; a cooling system model is constructed based on the difference between the actual voltage and the maximum voltage of the fuel cell stack representing the energy that is not converted to electrical energy and released in the form of heat.
Optionally, the constructing a fuel cell stack model includes: obtaining a polarization curve representation of a single fuel cell according to parameters of a fuel cell stack and an electrochemical thermodynamic principle; obtaining a polarization curve representation of the fuel cell stack from the polarization curve representation of the single fuel cell; and constructing a fuel cell stack model according to the polarization curve representation of the fuel cell stack.
Optionally, the step of constructing a fuel cell stack model includes: a fuel cell stack model is constructed from the parameters of the fuel cell stack and from the capacitors.
Optionally, according to parameters of the fuel cell stack and an electrochemical thermodynamic principle, obtaining a polarization curve representation of a single fuel cell:
VFC＝Enernst-Vohmic-Vact-Vconc
wherein, VFCIs the voltage of a single fuel cell;
Enernstis a lossless open-circuit voltage in a single fuel cell;
Vohmicis a significant voltage drop due to resistance to electron and ion movement in a single fuel cell;
Vactis the activation voltage drop at the anode and cathode in a single fuel cell;
Vconcis the pressure drop due to the decrease in active concentration.
Optionally, obtaining a polarization curve representation of the fuel cell stack according to the polarization curve representation of the single fuel cell:
VFC，Stack＝n*VFC
wherein, VFC，StackThe voltage of the fuel cell stack is the voltage of the fuel cell stack, and the fuel cell stack is composed of n single fuel cells, wherein n is a positive integer.
Alternatively, E is determined by the following formulanernst：
Wherein, PH2And PO2Hydrogen partial pressure and oxygen partial pressure, respectively; t is the temperature of the fuel cell;
v is determined by the following set of equationsohmic：
Vohmic＝＝iFC*(RM+RC)
Wherein R isCA fixed resistance for passing electrons from the electrode pair; rhoMIs the resistivity of the conductive film; a is the effective area of the conductive film; l is the thickness of the conductive film; jn is the current density of fuel consumption during idling; r is a global constant; f is the Faraday constant;
v is determined by the following set of equationsact：
Wherein iFCCurrent for a single fuel cell; zeta1、ζ2、ζ3、ζ4Is a model parameter;
is the oxygen concentration at the catalyst surface;
v is determined by the following formulaconc：
Where J is the current density of the fuel consumption.
Optionally, constructing a fuel cell stack model according to the parameters of the fuel cell stack and according to the capacitors, includes:
VFC＝Enernst-υC-Vohmic
wherein τ is the time constant resulting from the activation voltage and concentration drop; and C is the capacitance of the capacitor.
Optionally, the constructing a feeding tube model comprises:
using the ideal gas law, the partial pressure of hydrogen and the partial pressure of oxygen are obtained:
wherein the content of the first and second substances,
and
ratios of outlet hydrogen rate, oxygen rate and internal gas partial pressure, respectively;
and
respectively the rate of hydrogen input to the anode, the rate of oxygen input to the anode, VanIs the anode volume.
Optionally, the constructing a fuel processor model comprises:
based on the hydrogen-producing fuel being methanol, determining a fuel processor model as:
wherein the CV value is obtained based on a type of fuel input to the fuel processor,
is the hydrogen reaction rate at the anode.
In a second aspect, an embodiment of the present invention provides a modeling apparatus for a fuel cell, the apparatus including: the fuel cell stack modeling module is used for determining parameters of the fuel cell stack, wherein the parameters at least comprise hydrogen partial pressure, oxygen partial pressure, temperature of the fuel cell and water content of an electrolyte membrane, and a fuel cell stack model is constructed according to the parameters of the fuel cell stack; a feed tube modeling module for constructing a feed tube model based on the gas volume of the feed tube being the sum of the difference of the inlet gas minus the exhaust gas and the gas consumed in the anode channel or cathode channel reactions, and the ratio of the outlet gas rate to the internal gas partial pressure being a constant value; a fuel processor modeling module for constructing a fuel processor model based on the hydrogen producing fuel; and a cooling system modeling module for constructing a cooling system model based on a difference between an actual voltage and a maximum voltage of the fuel cell stack representing energy that is not converted into electric energy and is released in the form of heat.
Optionally, the fuel cell stack modeling module is further configured to obtain a polarization curve representation of a single fuel cell according to parameters of the fuel cell stack and an electrochemical thermodynamic principle; obtaining a polarization curve representation of the fuel cell stack from the polarization curve representation of the single fuel cell; and the polarization curve of the fuel cell stack represents and constructs a fuel cell stack model.
Optionally, the fuel cell stack modeling module is further configured to construct a fuel cell stack model according to the parameters of the fuel cell stack and according to the capacitor.
In a third aspect, an embodiment of the present invention provides a simulation method for a fuel cell, including: a fuel cell stack model, a feed pipe model, a fuel processor model, a cooling system model constructed as described in any of the above were simulated based on two modes, constant temperature and variable temperature, and from no load to full load.
In a fourth aspect, embodiments of the present invention provide computer program instructions, which when executed by a processor, implement a method as set forth in any one of the possibilities of the first aspect, the third aspect or the first aspect.
In a fifth aspect, the present invention provides a computer-readable storage medium on which computer program instructions are stored, the computer program instructions, when executed by a processor, implementing the method according to the first aspect or any one of the possibilities of the first aspect and the third aspect.
According to the embodiment of the invention, each part of the fuel cell is independently modeled, and the influence of the temperature change of the fuel cell on the model parameters is considered when the fuel cell stack model is constructed, so that the accuracy of the model is improved.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:
FIG. 1 is a schematic view of a fuel cell system in an embodiment of the invention;
FIG. 2 is a schematic diagram of a modeling method of a fuel cell in an embodiment of the invention;
FIG. 3 is a schematic diagram of an embodiment of the present invention with a capacitor placed due to a double layer load;
FIG. 4 is an exemplary graph of the results of a fuel cell simulation performed by an embodiment of the present invention;
FIG. 5 is an exemplary graph of the results of a fuel cell simulation performed without a double layer capacitor;
FIG. 6 is an exemplary graph of the results of a fuel cell simulation performed by an embodiment of the present invention;
FIG. 7 is an exemplary graph of the results of a fuel cell simulation performed without the double layer capacitor;
FIG. 8 is an exemplary graph of the results of a fuel cell simulation performed by an embodiment of the present invention;
fig. 9 is an exemplary diagram of the results of a fuel cell simulation performed by the embodiment of the present invention.
Detailed Description
The present disclosure is described below based on examples, but the present disclosure is not limited to only these examples. In the following detailed description of the present disclosure, certain specific details are set forth. It will be apparent to those skilled in the art that the present disclosure may be practiced without these specific details. Well-known methods, procedures, components and circuits have not been described in detail so as not to obscure the present disclosure.
Further, those of ordinary skill in the art will appreciate that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.
Unless the context clearly requires otherwise, throughout this specification, the words "comprise", "comprising", and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, what is meant is "including, but not limited to".
In the description of the present disclosure, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present disclosure, "a plurality" means two or more unless otherwise specified.
Fig. 1 is a schematic view of a fuel cell system in an embodiment of the present invention, and as shown in fig. 1, a polymer electrolyte fuel cell includes: a fuel cell stack 110, a supply pipe part 120, a reformer or a fuel processor 130, and a cooling system 140, wherein the supply pipe part 120 includes a hydrogen supply pipe 121 and an air supply pipe 122. Specifically, fuel enters a reformer or fuel processor 130 and a cooling system 140 with fans is used to blow air into the cells of the fuel cell stack 110.
Fig. 2 is a schematic diagram of a modeling method of a fuel cell in an embodiment of the present invention, and as shown in fig. 2, the embodiment of the present invention provides a modeling method of a fuel cell, the method mainly including:
s201: determining parameters of a fuel cell stack, wherein the parameters at least comprise hydrogen partial pressure, oxygen partial pressure, temperature of a fuel cell and water content of an electrolyte membrane, and constructing a fuel cell stack model according to the parameters of the fuel cell stack;
s202: constructing a feed tube model based on the gas volume of the feed tube being the sum of the difference of the inlet gas minus the exhaust gas and the gas consumed in the anode channel or cathode channel reactions, and the ratio of the outlet gas rate to the internal gas partial pressure being a constant value;
s203: constructing a fuel processor model from the hydrogen producing fuel;
s204: a cooling system model is constructed based on the difference between the actual voltage and the maximum voltage of the fuel cell stack representing the energy that is not converted to electrical energy and released in the form of heat.
According to the embodiment of the invention, a theoretical model is adopted in the construction of the fuel cell stack model, and a quasi-experimental model is adopted in the supply pipe model modeling. Further, by modeling the fuel cell temperature, the effect of temperature changes from start-up to full load may also be considered in the model.
In an optional embodiment, for the implementation of S201, the method specifically includes: and obtaining the polarization curve representation of the single fuel cell according to the parameters of the fuel cell stack and the electrochemical thermodynamic principle. And obtaining a polarization curve representation of the fuel cell stack according to the polarization curve representation of the single fuel cell. And constructing a fuel cell stack model according to the polarization curve representation of the fuel cell stack. In an alternative embodiment, the step of constructing a fuel cell stack model includes constructing a fuel cell stack model based on parameters of the fuel cell stack and based on a capacitor.
In an alternative embodiment, a polarization curve representation of a single fuel cell is obtained based on parameters of the fuel cell stack and electrochemical thermodynamic principles:
VFC＝Enernst-Vohmic-Vact-Vconc
wherein, VFCIs the voltage of a single fuel cell;
Enernstis a lossless open-circuit voltage in a single fuel cell;
Vohmicis a significant voltage drop due to resistance to electron and ion movement in a single fuel cell;
Vactis the activation voltage drop at the anode and cathode in a single fuel cell;
Vconcis the pressure drop due to the decrease in active concentration.
In an alternative embodiment, the polarization curve representation of the fuel cell stack is derived from the polarization curve representation of the single fuel cell:
VFC，Stack＝n*VFC
wherein, VFC，StackThe voltage of the fuel cell stack is defined as the voltage of the fuel cell stack, and the fuel cell stack is composed of n single fuel cells, wherein n is a positive integer.
In particular, EnernstIs a lossless open-circuit voltage in a single fuel cell, then
Where Δ G explains the change in Gibbs free energy in joules/mole (j/mol) in the above formula and Δ S is the change in entropy in joules/mole (j/mol). F is the Faraday constant and is the value of,
and
respectively, hydrogen partial pressure and oxygen partial pressure in units of atmospheric air. R is the universal constant for gases; t is the fuel cell temperature, TrefIs a reference temperature (25 ℃) expressed in kelvin.
In an alternative embodiment, using standard pressure and temperature Δ S, Δ G value is obtained, and E is determined based on the above formula and by the following formulanernst：
Wherein, PH2And PO2Hydrogen partial pressure and oxygen partial pressure, respectively; t is the temperature of the fuel cell;
v is determined by the following set of equationsohmic：
Vohmic＝＝iFC*(RM+RC)
Wherein R isCA fixed resistance for the passage of electrons by the electrode pair; rhoMIs the resistivity of the conductive film; a is the effective area of the conductive film and has a unit of square centimeter (cm)2) (ii) a l is the thickness of the conductive film in centimeters (cm); jn is the current density of fuel consumption during idling; r is allLocal constants; f is the Faraday constant. And determining the resistivity ρ of the conductive film by the following formulaM：
V is determined by the following set of equationsact：
Wherein iFCCurrent for a single fuel cell; ζ represents a unit1、ζ2、ζ3、ζ4Is a model parameter;
is the oxygen concentration at the catalyst surface;
v is determined by the following formulaconc：
Where J is the current density of the fuel consumption.
Although fuel cell d electrolyte has been chosen to conduct ions, it always has too much electron capacity and in the fuel cell operating state, similar to the minority carriers in semiconductors, a large number of hydrogen molecules will penetrate the cathode through the anolyte and react directly with oxygen due to the presence of the catalyst without current flowing through the external circuit. This small amount of hydrogen is referred to as fuel loss and migrates through the electrolyte. By JnRepresenting a current density equal to the amount of fuel consumed at no load, the fuel cell current used in the model is:
there is a phenomenon known as an electric double layer in the fuel cell. If two different materials with uncharged loads are in contact with each other, charge is transferred from one material to the other and the carrying area between the two materials is empty, thereby creating a potential difference between the two materials. For example, electrons penetrate from the N region to the P region, and holes penetrate from the P region to the N region, resulting in void regions at bond sites in the semiconductor material; this in turn creates an electric field in this region, which creates a potential difference at the key surface, preventing further penetration of electrons and holes. In an electrochemical system, an electric double layer like a semiconductor element is formed because electrons move from an electrode to an electrolytic solution, and ions move from the electrolytic solution to the electrode when a capacitor is operated. Therefore, the voltage generated by the electric double layer cannot immediately follow the current change, and a significant voltage drop follows the current change. To model a double layer, as shown in FIG. 3, embodiments of the present invention may model it using capacitors.
In an alternative embodiment, constructing a fuel cell stack model based on parameters of the fuel cell stack and based on capacitors comprises:
VFC＝Enernst-υC-Vohmic
wherein τ is the time constant resulting from the activation voltage and concentration drop; and C is the capacitance of the capacitor.
For example, for a nominal power of 5kW and a cross-sectional area of 232cm2The Ballard Mark V fuel cell of which the capacitance value determined by the above formula is 3 farads。
In an alternative embodiment, the building feed tube model comprises:
using the ideal gas law, the hydrogen partial pressure and the oxygen partial pressure are obtained:
wherein the content of the first and second substances,
and
ratios of outlet hydrogen rate, oxygen rate and internal gas partial pressure, respectively;
and with
Respectively the rate of hydrogen input to the anode, the rate of oxygen input to the anode, VanIs the anode volume.
Specifically, assuming that the gas volume of the supply tube is the sum of the difference between the inlet gas minus the exhaust gas and the gas consumed in the anode channel or cathode channel reaction, using the ideal gas law, the hydrogen partial pressure is derived:
wherein the content of the first and second substances,
the rate of hydrogen input to the anode is given in mol · s-1；
The rate of hydrogen output to the anode is given in mol · s-1；
Is the hydrogen reaction rate at the anode in mol · s-1；VanIs the volume of the anode in m3. As above, can calculate
Then:
on the other hand, assuming that the difference between the inlet and outlet pressures is such that the orifice ruptures to simulate the output flow of oxygen and hydrogen, the ratio of the outlet gas velocity to the internal gas partial pressure is a constant value:
then, according to the above formula, one can obtain:
the partial pressures of hydrogen and oxygen were obtained by laplace transformation of the above two equations and arranged:
in an alternative embodiment, the constructing the fuel processor model comprises:
based on the hydrogen-producing fuel being methanol, determining a fuel processor model as:
wherein the CV value is obtained based on a type of fuel input to the fuel processor,
is the hydrogen reaction rate at the anode.
If the fuel input to the fuel processor is methane gas, 2 molecules of hydrogen gas are obtained and produced for each molecule of methane gas input to the fuel processor. Thus, in this case, the CV value would be equal to 2, and the input hydrogen flow and the rate of reacting hydrogen in the fuel cell would be:
If all of the energy released in the fuel cell chemical reaction is converted to electrical energy, i.e., no losses in the system, the open circuit voltage of the cell is equal to 48.1 volts. The difference between the actual cell voltage and the maximum voltage represents the energy that is not converted into electrical energy and released as heat, so if the water produced is a liquid, the total heat Q released in a fuel stack containing n single cellsgeneratedEqual to:
Qgenerated＝(Emax-Vcell_real)*I*ncell
and, the heat generated in the fuel cell is returned to the environment in three ways, respectively: convective heat losses, radiative losses, surface evaporation of water produced by the cathode. Wherein, three heat losses are respectively expressed as follows:
Qcow＝n*Acell*hstack*(Tstack-Troom)
Qrad＝σ*Aexterior*(Tstack 4-Troom 4)
wherein h isstackIs the convective heat transfer coefficient and has the unit of W (m)2·K)-1(ii) a n is the number of batteries; a. thecellIs the effective surface of the fuel cell and has a unit of m2；AexteriorIs the outer surface of the fuel cell stack and has the unit of m2(ii) a σ is the Stefan-Boltzmann constant, (5.67 x 10-8) W (m2.K)-1；
Is the molar mass of water in grams; i isevapIs the latent heat of water evaporation, in units of j.g-1(ii) a Beta is the ratio of evaporated water to total water yield.
In an alternative embodiment, the convective heat transfer coefficient h is selected to provide forced convection in an air flow modestackThe value range of (1) is 25-250; for natural convection of air flow, the convective heat transfer coefficient hstackThe value range of (A) is 5-50. In an alternative embodiment, a cooling system with a fan is used to blow air into the cells of the stack, the fan speed being proportional to the fuel cell output current, where the convective heat transfer coefficient is scaled from 25 to 250W (m)2·K)-1And (4) changing. And calculating the temperature of the fuel cell by the following formula:
wherein M isFCThe unit is kg for the total mass of the fuel cell; cFCIs the specific heat capacity of the fuel cell and has the unit of J (kg. K)-1。
The embodiment of the invention provides a modeling device of a fuel cell, which comprises: the fuel cell stack modeling module is used for determining parameters of the fuel cell stack, wherein the parameters at least comprise hydrogen partial pressure, oxygen partial pressure, temperature of the fuel cell and water content of an electrolyte membrane, and a fuel cell stack model is constructed according to the parameters of the fuel cell stack; a feed tube modeling module for constructing a feed tube model based on the gas volume of the feed tube being the sum of the difference of the inlet gas minus the exhaust gas and the gas consumed in the anode channel or cathode channel reactions, and the ratio of the outlet gas rate to the internal gas partial pressure being a constant value; a fuel processor modeling module for constructing a fuel processor model based on the hydrogen producing fuel; and a cooling system modeling module for constructing a cooling system model based on a difference between an actual voltage and a maximum voltage of the fuel cell stack representing energy that is not converted into electrical energy and is released in the form of heat.
In an alternative embodiment, the fuel cell stack modeling module is further configured to obtain a polarization curve representation of the single fuel cell according to parameters of the fuel cell stack and an electrochemical thermodynamic principle; obtaining a polarization curve representation of the fuel cell stack from the polarization curve representation of the single fuel cell; and the polarization curve of the fuel cell stack represents and constructs a fuel cell stack model.
In an alternative embodiment, the fuel cell stack modeling module is further configured to construct a fuel cell stack model based on parameters of the fuel cell stack and based on capacitors.
The embodiment of the invention provides a fuel cell simulation method, which comprises the following steps: a fuel cell stack model, a feed pipe model, a fuel processor model, a cooling system model constructed as described in any of the above were simulated based on two modes, constant temperature and variable temperature, and from no load to full load.
To evaluate the constructed fuel cell model, all parts of the above constructed fuel cell stack model, supply tube model, fuel processor model, cooling system model were implemented in Simulink/Matlab software.
FIG. 4 is an exemplary graph of the results of a fuel cell simulation performed by an embodiment of the present invention; FIG. 5 is an exemplary graph of the results of a fuel cell simulation performed without a double layer capacitor; FIG. 6 is an exemplary graph of the results of a fuel cell simulation performed by an embodiment of the present invention; FIG. 7 is an exemplary graph of the results of a fuel cell simulation performed without the double layer capacitor; FIG. 8 is an exemplary graph of the results of a fuel cell simulation performed by an embodiment of the present invention; fig. 9 is an exemplary diagram of the results of a fuel cell simulation performed by the embodiment of the present invention.
In one embodiment, a fuel cell is simulated, specifically, based on the fuel cell stack model, supply tube model, fuel processor model, cooling system model constructed as described above, a load is applied to the fuel cell every 0.5 seconds, a 4 ohm resistor is inserted in the form of a bridge, and then removed. As shown in fig. 4, varying the power of the fuel cell during this simulation test, the effect of the double layer capacitor can be seen in less than a tenth of a second. Again, the above test was repeated without the double layer capacitor, and as can be seen from fig. 5, there was a sudden jump in the voltage of the fuel cell.
In one embodiment, a simulation of the fuel cell, specifically, based on the fuel cell stack model, supply pipe model, fuel processor model, cooling system model constructed as described above, applies a load to the fuel cell every 20 seconds, with the load being input and removed as a bridge. As shown in fig. 6, 7, the time constant for temperature is much greater than 20 seconds, where the observed dynamics are related to the fuel processor unit and the fuel and air supply pipes of the fuel cell.
In one embodiment, the simulation of the fuel cell, specifically, the load is added in the form of a bridge based on the fuel cell stack model, the supply pipe model, the fuel processor model, and the cooling system model constructed as described above until the temperature reaches a steady state, and it is determined that the temperature of the fuel cell has a time constant of several hundred seconds.
In one embodiment, the simulation of the fuel cell, specifically, based on the fuel cell stack model, the supply pipe model, the fuel processor model, and the cooling system model constructed as described above, is performed in both constant temperature and variable temperature modes, from no-load to full-load, and from full-load to no-load. The temperature value in the constant temperature mode is assumed to be 65 degrees (nominal value) and the initial temperature, and the temperature of the fuel cell is assumed to be 27 degrees celsius. As shown in fig. 8 and 9, the temperature of the fuel cell tends to the nominal value from the initial value as the load increases. And, during the first 200 seconds of the simulation, since the actual temperature of the fuel cell was below the nominal value. This difference reaches zero when the temperature reaches its nominal value. When the load drops at 530 seconds, the temperature starts to drop, but the difference between the two waveforms is small due to the dynamic change of the temperature, and the difference between the two voltage waveforms is significant 60 seconds after the start of the load shedding.
And, in the above fuel cell simulation, a 5kW fuel cell may be used. Further, the same experiment can be performed for cells of different capacities by changing the number of cells, changing the weight parameters and the size of the fuel cell. If 5kw polymer electrolyte fuel cells are modeled and simulated, the fuel cells can be classified into three categories according to the dynamic simulation result: short term, medium term and long term. The short term dynamics of the fuel cell is due to the presence of a phenomenon known as double layer, whose time constant is about one tenth of a second. Another dynamic factor, the medium-term dynamics of the fuel cell, is its time constant of tens of seconds due to the dynamics of the fuel processor unit and the fuel and air supply pipes of the fuel cell. Finally, the long-term dynamics of fuel cells are due to the thermodynamic properties of fuel cells, with time constants in the range of hundreds of seconds.
According to the embodiment of the invention, the influence of the temperature on the performance of the fuel cell can be reflected through the simulation of the fuel cell in two modes of constant temperature and variable temperature. And simulation results based on Simulink/Matlab software show that for a 5kW sample fuel cell, the power is less than the nominal power of the cell in more than 60 seconds or under initial load conditions, and temperature modeling of the fuel cell has a considerable impact on improving model accuracy.
In an embodiment of the present invention, there is further provided a computer program instruction, which when executed by a processor, implements the method of any one of the above embodiments.
In an embodiment of the present invention, there is also provided a computer-readable storage medium on which computer program instructions are stored, which when executed by a processor implement the method of any one of the above embodiments.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, various aspects of embodiments of the invention may take the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit," module "or" system. Furthermore, various aspects of embodiments of the invention may take the form of: the computer program product is embodied in one or more computer readable media having computer readable program code embodied thereon.
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 to the present invention 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 method of modeling a fuel cell, the method comprising:
determining parameters of a fuel cell stack, wherein the parameters at least comprise hydrogen partial pressure, oxygen partial pressure, temperature of a fuel cell and water content of an electrolyte membrane, and constructing a fuel cell stack model according to the parameters of the fuel cell stack;
constructing a feed tube model based on the gas volume of the feed tube being the sum of the difference of the inlet gas minus the exhaust gas and the gas consumed in the anode channel or cathode channel reactions, and the ratio of the outlet gas rate to the internal gas partial pressure being a constant value;
constructing a fuel processor model from the hydrogen producing fuel;
a cooling system model is constructed based on the difference between the actual voltage and the maximum voltage of the fuel cell stack representing the energy that is not converted to electrical energy and released in the form of heat.
2. The method of claim 1, wherein constructing a fuel cell stack model comprises:
obtaining a polarization curve representation of a single fuel cell according to parameters of a fuel cell stack and an electrochemical thermodynamic principle;
obtaining a polarization curve representation of the fuel cell stack from the polarization curve representation of the single fuel cell;
and constructing a fuel cell stack model according to the polarization curve representation of the fuel cell stack.
3. The method of claim 1 or 2, wherein constructing a fuel cell stack model comprises:
a fuel cell stack model is constructed from the parameters of the fuel cell stack and from the capacitors.
4. The method of claim 2, wherein the polarization curve representation of the single fuel cell is obtained based on parameters of the fuel cell stack and electrochemical thermodynamic principles:
VFC＝Enernst-Vohmic-Vact-Vconc
wherein, VFCIs the voltage of a single fuel cell;
Enernstis a lossless open-circuit voltage in a single fuel cell;
Vohmicis a significant voltage drop due to resistance to electron and ion movement in a single fuel cell;
Vactis the activation voltage drop at the anode and cathode in a single fuel cell;
Vconcis the pressure drop due to the decrease in the concentration of the active substance.
5. The method of claim 4, wherein the polarization curve representation for the fuel cell stack is derived from the polarization curve representation for the single fuel cell by:
VFC，Stack＝n*VFC
wherein, VFC，StackIs the voltage of a fuel cell stack consisting of nA single fuel cell composition, wherein n is a positive integer.
6. The method of claim 4,
e is determined by the following formulanernst：
Wherein, PH2And PO2Hydrogen partial pressure and oxygen partial pressure, respectively; t is the temperature of the fuel cell;
v is determined by the following set of equationsohmic：
Vohmic＝＝iFC*(RM+RC)
Wherein R isCA fixed resistance for the passage of electrons by the electrode pair; rhoMIs the resistivity of the conductive film; a is the effective area of the conductive film; l is the thickness of the conductive film; jn is the current density of fuel consumption during idling; r is a global constant; f is the Faraday constant;
v is determined by the following set of equationsact：
Wherein iFCIs single fuel electricityThe current of the cell; zeta1、ζ2、ζ3、ζ4Is a model parameter;
is the oxygen concentration at the catalyst surface;
v is determined by the following formulaconc：
Where J is the current density of the fuel consumption.
7. The method of claim 4, wherein constructing a fuel cell stack model from parameters of the fuel cell stack and from capacitors comprises:
VFC＝Enernst-υC-Vohmic
wherein τ is the time constant resulting from the activation voltage and concentration drop; and C is the capacitance of the capacitor.
8. The method of claim 1, wherein the constructing a feed tube model comprises:
using the ideal gas law, the partial pressure of hydrogen and the partial pressure of oxygen are obtained:
wherein the content of the first and second substances,
and with
Ratios of outlet hydrogen rate, oxygen rate and internal gas partial pressure, respectively;
and
respectively the rate of hydrogen input to the anode, the rate of oxygen input to the anode, VanIs the anode volume.
9. The method of claim 8, wherein the constructing a fuel processor model comprises:
based on the hydrogen-producing fuel being methanol, determining a fuel processor model as:
wherein the CV value is obtained based on a type of fuel input to the fuel processor,
is the hydrogen reaction rate at the anode.
10. A simulation method of a fuel cell, characterized in that the simulation method comprises:
a simulation of a fuel cell stack model, a supply tube model, a fuel processor model, a cooling system model constructed as described in any one of claims 1-9, based on both constant temperature and variable temperature modes, and from empty to full load.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110086286A1 (en) * | 2009-10-09 | 2011-04-14 | Gm Global Technology Operations, Inc. | Method to perform adaptive voltage suppression of a fuel cell stack based on stack parameters |
| US20140322625A1 (en) * | 2013-04-24 | 2014-10-30 | GM Global Technology Operations LLC | Systems and methods to monitor and control a flow of air within a fuel cell stack |
| CN109657348A (en) * | 2018-12-18 | 2019-04-19 | 安徽江淮汽车集团股份有限公司 | One proton exchanging film fuel battery modeling method |
| CN113097542A (en) * | 2021-03-30 | 2021-07-09 | 新源动力股份有限公司 | Fuel cell air system modeling simulation method based on Amesim |
| CN113488680A (en) * | 2021-06-28 | 2021-10-08 | 同济大学 | SIMULINK-based cold start modeling simulation test method for fuel cell stack |
-
2021
- 2021-12-24 CN CN202111600786.7A patent/CN114491947B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110086286A1 (en) * | 2009-10-09 | 2011-04-14 | Gm Global Technology Operations, Inc. | Method to perform adaptive voltage suppression of a fuel cell stack based on stack parameters |
| US20140322625A1 (en) * | 2013-04-24 | 2014-10-30 | GM Global Technology Operations LLC | Systems and methods to monitor and control a flow of air within a fuel cell stack |
| CN109657348A (en) * | 2018-12-18 | 2019-04-19 | 安徽江淮汽车集团股份有限公司 | One proton exchanging film fuel battery modeling method |
| CN113097542A (en) * | 2021-03-30 | 2021-07-09 | 新源动力股份有限公司 | Fuel cell air system modeling simulation method based on Amesim |
| CN113488680A (en) * | 2021-06-28 | 2021-10-08 | 同济大学 | SIMULINK-based cold start modeling simulation test method for fuel cell stack |
Non-Patent Citations (1)
| Title |
|---|
| 曹蕾等: "燃料电池发动机低温冷启动热平衡建模与实验研究", 东方电气评论, vol. 35, no. 138, pages 21 - 24 * |
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