Solid oxide fuel cell gradient hole anode modeling calculation method

Abstract

The invention provides a solid oxide fuel cell gradient hole anode modeling calculation method which specifically comprises the following steps: performing three-dimensional scanning on a prepared solid oxide fuel cell gradient anode sample, and extracting a real microstructure; performing three-dimensional reconstruction and segmentation on the three-dimensional scanning image; constructing a two-dimensional axisymmetric single battery model; setting a control equation of the multi-physics field coupling model; setting boundary conditions of the multi-physics field coupling model, dividing grids of the SOFC single battery and performing numerical simulation calculation, and verifying the effectiveness of the multi-physics field coupling model by using grid independence; the gradient hole anode design parameters of the solid oxide fuel cell are obtained by calculating the temperature field, the material distribution field and the electrochemical power density of the cell under different anode structure parameters. According to the technical scheme, the problem that the material transmission performance and the electrochemical performance of the battery anode are not considered in a modeling calculation method in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of solid oxide fuel cell, in particular to a solid oxide fuel cell gradient pore anode modeling calculation method. BACKGROUND

[0002] Solid oxide fuel cell (SOFC) is a fuel cell composed of all-solid components, which directly converts chemical energy between fuel and oxidant into electrical energy.

[0003] Among many configurations, the flat plate type SOFC has a unique "sandwich" type single cell unit (Positive electrode-Electrolyte-Negative electrode, PEN structure) due to its modular stacking characteristics, and is also the most common structure in SOFC battery systems, with advantages such as low cost, easy assembly, short current path and high output power. The anode of the solid oxide fuel cell (SOFC) as the core component needs to bear three functions at the same time: fuel oxidation reaction, charge transmission channel and mechanical support structure. Its performance is closely related to the microstructure characteristics, for example, porosity determines the gas diffusion efficiency, and the three-phase interface length directly affects the electrochemical reaction active area. The random and uniform pore structure of the traditional anode is difficult to achieve effective material transmission, which causes the fuel molecules to be unable to fully reach the active reaction sites, ultimately resulting in slow electrochemical reaction kinetics and overall performance degradation of the battery. Research has shown that changing the microstructure of the anode from random pores to vertical microchannels is an effective way to accelerate gas diffusion and avoid concentration loss. In addition to the improved straight microchannel structure, further research on the anode channel structure is also very little. Chinese patent (CN202311576422.9) A solid oxide fuel cell gradient pore anode mechanical property calculation method only considers the mechanical property calculation of the solid oxide fuel cell gradient anode, and does not consider the material transport performance and electrochemical performance of the battery anode.

[0004] Therefore, there is a need for a solid oxide fuel cell gradient pore anode modeling calculation method that considers the material transport performance and electrochemical performance of the battery anode. SUMMARY

[0005] The main purpose of the present application is to provide a solid oxide fuel cell gradient pore anode modeling calculation method to solve the problem that the modeling calculation method in the prior art does not consider the material transport performance and electrochemical performance of the battery anode.

[0006] To achieve the above purpose, the present application provides a solid oxide fuel cell gradient pore anode modeling calculation method, which specifically comprises the following steps:

[0007] S1, three-dimensional scanning is performed on the prepared solid oxide fuel cell gradient anode sample to extract the real microstructure.

[0008] S2, three-dimensional reconstruction and segmentation are performed on the three-dimensional scanning image.

[0009] S3, a two-dimensional axisymmetric single cell model is constructed based on the COMSOL Multiphysics multi-physics simulation platform.

[0010] S4, the control equations of the multi-physics coupling model are set, including: electrochemical model, gas flow transfer model, material diffusion model and heat transfer model.

[0011] S5, the boundary conditions of the multi-physics coupling model are set, the grid of the SOFC single cell is divided and numerical simulation calculation is performed, and the effectiveness of the multi-physics coupling model is verified by using grid independence.

[0012] S6, the design parameters of the solid oxide fuel cell gradient pore anode are obtained by calculating the temperature field, material distribution field and electrochemical power density of the cell under different anode structure parameters.

[0013] Further, step S1 is specifically:

[0014] The industrial-grade nano-CT is used to scan the solid oxide fuel cell gradient anode sample along the x-y, x-z and y-z axes with a scanning interval of 5 μm; the CT images of the top view TOP, front view FRONT and right view RIGHT are obtained.

[0015] Further, step S2 is specifically:

[0016] The CT images are reconstructed in three dimensions by Avizo software;

[0017] The pore phase and matrix phase are separated, the porosity, tortuosity and average pore size are calculated, and the CT images are analyzed layer by layer, the pore distribution in different cross-sectional layers is counted, and the gradient homogeneity is verified.

[0018] Further, step S3 specifically includes the following steps:

[0019] S3.1, the two-dimensional axisymmetric single cell model includes: anode support layer, electrolyte, cathode and gas flow channel.

[0020] S3.2, the porosity, tortuosity and average pore size extracted in step S2 are imported into the material setting module of the multi-physics simulation platform.

[0021] Further, the electrochemical model construction in step S4 includes the following steps:

[0022] S4.1, the open circuit voltage of SOFC is caused by the concentration difference of hydrogen and oxygen between cathode and anode:

[0023]

[0024] wherein, E is the open circuit voltage of SOFC; E0 is the theoretical electrode potential of the battery; R is the ideal gas molar constant, which is 8.314 J·mol -1 ·K -1 , T is, F is the Faraday constant, which is 9.6485 C·mol -1 , P is the partial pressure of gas component, unit Pa.

[0025] S4.2, the working voltage V cell of SOFC is calculated by the following formula:

[0026]

[0027] wherein, V act is the activation polarization loss; V con is the concentration polarization loss, V ohm is the ohmic polarization loss.

[0028] S4.3, the Butler-Volmer equation is used to describe the current density:

[0029]

[0030] wherein, J is the working current density, A·m -2 ; J0 is the exchange current density, A·m -2 ; α is the electron transfer coefficient; n is the number of electrons transferred per electrochemical reaction; η act is the activation overpotential, exp is the exponential function.

[0031] Considering the influence of temperature, J0 is expressed by the following formula:

[0032]

[0033] wherein, γ is the exponential pre-factor, A·m -2 ; E act is the activation energy, J·mol -1 .

[0034] Further, the gas flow transmission model in step S4 includes the following steps:

[0035] S4.4, the internal reaction of SOFC battery follows the law of conservation of mass, and the control equation is expressed as:

[0036]

[0037] where, is the divergence operator, ε is the porosity, ρ is the gas density, v is the velocity vector, S m is the mass source.

[0038] S4.5, Navier-Stokes equation describes the momentum transfer mechanism in open channels, and the compressible Navier-Stokes equation is used to model in the gas flow channel:

[0039]

[0040] where, p is the pressure of the gas, Pa; I represents the unit tensor, τ is the viscous stress tensor, F is the volume force vector.

[0041] S4.6, seepage phenomenon will occur in the porous electrode, considering the influence of porosity and permeability, Brinkman equation is used to describe, expressed as:

[0042]

[0043] where, ξ is the permeability, μ is the dynamic viscosity of the gas.

[0044] Further, the material diffusion model in step S4 includes the following steps:

[0045] S4.7, the Stefan-Maxwell model based on Fick model is used to describe the gas diffusion in the electrode, and the Knudsen diffusion is considered:

[0046]

[0047] where, w i is the mass fraction of gas i, is the thermal diffusion coefficient of gas i m 2 / s, Q i is the mass source term of gas i, unit kg / (m3·s), to is the inverse of tortuosity factor, D ij is the bulk diffusion coefficient of gas i and j, unit m 2 / s, D ij,eff is the effective binary diffusion coefficient, unit m 2 ·s -1 , x j is the mole fraction of gas j.

[0048] S4.8, the dust gas model is used to describe the diffusion of the mixture in the porous medium, as shown in the following formula:

[0049]

[0050] In the formula, Pi represents the partial pressure of gas i; N i is the molar flux of gas i; is the effective Knudsen diffusion coefficient.

[0051] Further, the heat transfer model in step S4 is specifically constructed as follows:

[0052]

[0053] wherein C p is the specific heat capacity of the component, k eff is the thermal conductivity of each component; and Q is the heat source term.

[0054] Further, step S5 specifically includes the following steps:

[0055] S5.1, setting the boundary conditions of the multi-physics coupling model: fuel inlet volume ratio: H2 / H2O = 0.97:0.03, flow rate 1 m / s; air inlet volume ratio: O2 / N2 = 0.21:0.79, flow rate 2 m / s; electrochemical boundary: anode ground 0V, cathode set working voltage 0.6-0.8V.

[0056] S5.2, dividing the grid of the SOFC single cell and performing numerical simulation calculation, the grid adopts regular hexahedron unit, the total number of the grid of the SOFC single cell is 73500, and the electrode-electrolyte interface region is encrypted.

[0057] S5.3, the multi-physics coupling model is calculated by adopting different grid numbers, and the grid independence is verified.

[0058] Further, step S6 specifically includes the following steps:

[0059] S6.1, calculating the electrochemical performance, temperature field and substance distribution field of the cell.

[0060] S6.2, calculating the temperature field, substance distribution field and electrochemical power density of the cell under different anode structure parameters, and obtaining the optimal solid oxide fuel cell gradient pore anode design parameter.

[0061] The present application has the following beneficial effects:

[0062] The coupling model integrates electrochemistry (Butler-Volmer), mass transfer (DGM model), heat transfer (LTNE equation) and mechanics (thermal stress), and the performance prediction deviation of the single physical field model is reduced. The parameterized gradient control of the gradient anode structure of the solid oxide fuel cell is proposed, the quantitative analysis of the gradient slope and the anode thickness is carried out, the optimization interval is determined, the power density of the cell is improved, the long service life and high reliability operation of the cell are provided, and the optimization design of the gradient anode material of the solid oxide fuel cell has guiding significance. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor. In the drawings:

[0064] Figure 1 A three-dimensional reconstruction result diagram is shown.

[0065] Figure 2 A sample 50th layer scanning surface porosity of 37.2% is shown.

[0066] Figure 3 A sample 100th layer scanning surface porosity of 37.8% is shown.

[0067] Figure 4 A sample 150th layer scanning surface porosity of 38.4% is shown.

[0068] Figure 5 An Avizo three-dimensional reconstruction diagram is shown.

[0069] Figure 6 A pressure distribution diagram in the pore channel is shown.

[0070] Figure 7 A SOFC model structure diagram is shown.

[0071] Figure 8 A local enlarged view of the power density curve of the cell with different gradient structures is shown.

[0072] Figure 9 A hydrogen molar mass distribution diagram of the cell with different gradient structures is shown.

[0073] Figure 10 A temperature distribution diagram of the cell with different gradient structures is shown. DETAILED DESCRIPTION

[0074] The technical solutions of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the protection scope of the present application.

[0075] As shown in a solid oxide fuel cell gradient pore anode modeling calculation method, specifically comprising the following steps: Figure 1

[0076] S1, the prepared solid oxide fuel cell gradient anode sample is three-dimensionally scanned, and the real microstructure is extracted.

[0077] S2, the three-dimensional scanning image is three-dimensionally reconstructed and segmented.

[0078] S3, based on the COMSOL Multiphysics multi-physical field simulation platform, a two-dimensional axisymmetric single cell model is constructed.

[0079] S4, setting the control equations of the multi-physical field coupling model, including: electrochemical model, gas flow transfer model, substance diffusion model and heat transfer model.

[0080] S5, setting the boundary conditions of the multi-physical field coupling model, dividing the grid of the SOFC single cell and carrying out numerical simulation calculation, and verifying the effectiveness of the multi-physical field coupling model by using the grid independence.

[0081] S6, by calculating the temperature field, substance distribution field and electrochemical power density of the cell under different anode structure parameters, the design parameters of the solid oxide fuel cell gradient pore anode are obtained.

[0082] Specifically, step S1 is specifically:

[0083] The industrial-grade nano-CT is used to scan the solid oxide fuel cell gradient anode sample along the x-y, x-z and y-z axes, and the scanning interval is 5 μm; the CT images of the top view TOP, the front view FRONT and the right view RIGHT are obtained.

[0084] Specifically, step S2 is specifically:

[0085] As shown in the three-dimensional reconstruction of the CT image by the Avizo software. Figure 1

[0086] The pore phase and the matrix phase are separated, the porosity, the tortuosity and the average pore diameter are calculated, and the CT image is analyzed layer by layer, the porosity distribution in different cross-sectional layers is counted, and the gradient homogeneity is verified. The porosity calculation distribution graph under different heights is as shown in Figure 2 、 Figure 3 and​​Figure 4 As shown, Figure 5 For solid phase part three-dimensional reconstruction map, pore channel pressure distribution map is Figure 6 .

[0087] Specifically, step S3 specifically includes the following steps:

[0088] S3.1, as Figure 7 shown, the two-dimensional axisymmetric single cell model includes: anode support layer, electrolyte, cathode and gas flow channel, wherein Hano is the overall height of the anode support, d is the width of the sponge phase away from the gas channel, and l is the increase value of the sponge phase width for controlling the gradient structure.

[0089] S3.2, the porosity, tortuosity and average pore size extracted in step S2 are introduced into the material setting module of the multi-physical field simulation platform.

[0090] Specifically, the electrochemical model construction in step S4 includes the following steps:

[0091] S4.1, the open circuit voltage of SOFC is caused by the concentration difference of hydrogen and oxygen between the cathode and the anode:

[0092]

[0093] Wherein, E is the open circuit voltage of SOFC; E0 is the theoretical electrode potential of the battery; R is the ideal gas molar constant, which is 8.314 J·mol -1 ·K -1 , T is, F is the Faraday constant, which is 9.6485 C·mol -1 , P is the partial pressure of gas components, unit Pa.

[0094] S4.2, the working voltage V cell of SOFC is calculated by the formula:

[0095]

[0096] Wherein, V act is the activation polarization loss; V con is the concentration polarization loss, V ohm is the ohmic polarization loss.

[0097] S4.3, the Butler-Volmer equation is used to describe the current density:

[0098]

[0099] Wherein, J is the working current density, A·m -2 ; J0 is the exchange current density, A·m -2; a is the electron transfer coefficient; n is the number of electrons transferred per electrochemical reaction; η act is the activation overpotential, and exp is the exponential function.

[0100] Considering the effect of temperature, J0 is expressed by the following formula:

[0101]

[0102] wherein γ is the pre-exponential factor, A·m -2 ; E act is the activation energy, J·mol -1 .

[0103] Specifically, the gas flow transfer model in step S4 includes the following steps:

[0104] S4.4, the internal reaction of the SOFC cell follows the law of conservation of mass, and the control equation is expressed as:

[0105]

[0106] wherein, is the divergence operator, ε is the porosity, ρ is the gas density, v is the velocity vector, S m is the mass source.

[0107] S4.5, the Navier-Stokes equation describes the momentum transfer mechanism in the open channel, and the compressible Navier-Stokes equation is used to model in the gas flow channel:

[0108]

[0109] wherein p is the pressure of the gas, Pa; I represents the unit tensor, τ is the viscous stress tensor, and F is the volume force vector.

[0110] S4.6, seepage phenomenon will occur in the porous electrode, considering the influence of porosity and permeability, Brinkman equation is used to describe, expressed as:

[0111]

[0112] wherein ξ is the permeability, which depends on the geometric shape of the porous medium, and μ is the dynamic viscosity of the gas.

[0113] Specifically, the material diffusion model in step S4 includes the following steps:

[0114] S4.7, the Stefan-Maxwell model based on the Fick model is used to describe the gas diffusion in the electrode, and the Knudsen diffusion is considered:

[0115]

[0116] where w i is the mass fraction of gas i, is the thermal diffusion coefficient of gas i m 2 / s, Q i is the mass source term of gas i, with the unit of kg / (m3·s), to is the inverse of tortuosity factor, D ij is the bulk diffusion coefficient of gas i and j, with the unit of m 2 / s, D ij,eff is the effective binary diffusion coefficient, with the unit of m 2 ·s -1 , x j is the mole fraction of gas j.

[0117] S4.8, the diffusion of the mixture in the porous medium is described using a dust gas model, as shown in the following formula:

[0118]

[0119] In the formula, P i represents the partial pressure of gas i; N i is the molar flux of gas i; is the effective Knudsen diffusion coefficient.

[0120] Specifically, the heat transfer model in step S4 is specifically constructed as:

[0121]

[0122] where C p is the specific heat capacity of the component, k eff is the thermal conductivity of each component; and Q is the heat source term.

[0123] Specifically, step S5 specifically includes the following steps:

[0124] S5.1, setting the boundary conditions of the multi-physical field coupling model: the volume ratio of fuel inlet: H2 / H2O = 0.97:0.03, the flow rate is 1 m / s; the volume ratio of air inlet: O2 / N2 = 0.21:0.79, the flow rate is 2 m / s; the electrochemical boundary: the anode is grounded at 0 V, and the cathode is set to work at a voltage of 0.6-0.8 V.

[0125] S5.2, dividing the grid of the SOFC single cell and performing numerical simulation calculation, the grid adopts regular hexahedron unit, the total number of the grid of the SOFC single cell is 73500, and the grid in the electrode-electrolyte interface area is encrypted by dividing smaller grid.

[0126] S5.3, the multi-physical field coupling model is calculated by taking different grid numbers of different sizes respectively, the grid independence of the multi-physical field coupling model is verified, and the temperature distribution error is less than 0.5% through four groups of grids (22, 330 to 60, 650 units).

[0127] Specifically, step S6 specifically comprises the following steps:

[0128] S6.1, calculate the electrochemical performance, temperature field and substance distribution field of the battery.

[0129] S6.2, calculate the temperature field, substance distribution field and electrochemical power density of the battery under different anode structure parameters, and obtain the optimal solid oxide fuel cell gradient hole anode design parameter.

[0130] Parameterize the structure parameters, and compare the hydrogen distribution (molar mass difference <0.001 mol·m -3 ), temperature gradient (axial temperature rise rate 0.4K·mm -1 ) and power density (peak 0.86W·cm -2 ) under l=0, 5, 10 and 15μm. Anode thickness (Hano) optimization: determine 850-900μm as the optimal interval, balance the activation polarization and concentration polarization. The power density curve of the battery with different gradient structures is shown in Figure 8 , the hydrogen molar mass distribution of the battery with different gradient structures is shown in Figure 9 , and the temperature distribution of the battery with different gradient structures is shown in Figure 10 .

[0131] Of course, the above description is not a limitation of the present application, and the present application is not limited to the above examples. Changes, modifications, additions or substitutions made by those skilled in the art within the scope of the present application should also be within the protection scope of the present application.

Claims

1. A solid oxide fuel cell gradient pore anode modeling calculation method, characterized in that: The specific steps include: S1, perform 3D scanning on the prepared solid oxide fuel cell gradient anode sample to extract the real microstructure; S2, 3D reconstruction and segmentation of the 3D scanned image; S3, based on the COMSOL Multiphysics multi-physics simulation platform, builds a two-dimensional axisymmetric single battery model; S4, setting the control equations of the multi-physics coupling model, including: electrochemical model, air flow transfer model, material diffusion model and heat transfer model; S5, setting the boundary conditions of the multi-physics coupling model, dividing the grid of the SOFC single cell and performing numerical simulation calculations, and using the grid independence to verify the effectiveness of the multi-physics coupling model; S6, obtain the design parameters of the gradient pore anode of the solid oxide fuel cell by calculating the temperature field, material distribution field and electrochemical power density of the battery under different anode structural parameters.

2. A solid oxide fuel cell gradient pore anode modeling calculation method according to claim 1, characterized in that: Step S1 is specifically as follows: An industrial-grade nano-CT was used to scan the solid oxide fuel cell gradient anode sample along the xy, xz, and yz axes with a scanning interval of 5 μm; CT images of the top view TOP, front view FRONT, and right view RIGHT were obtained.

3. The solid oxide fuel cell gradient pore anode modeling calculation method according to claim 1, characterized in that: Step S2 is specifically as follows: CT images were three-dimensionally reconstructed using Avizo software; The pore phase and the matrix phase were separated, the porosity, tortuosity and average pore size were calculated, and the CT images were analyzed layer by layer. The porosity distribution in different sections was statistically analyzed to verify the gradient homogeneity.

4. The solid oxide fuel cell gradient pore anode modeling calculation method according to claim 1, characterized in that: Step S3 specifically includes the following steps: S3.1, a two-dimensional axisymmetric single cell model including: anode support layer, electrolyte, cathode and gas flow channel; S3.2, import the porosity, tortuosity and average pore size extracted in step S2 into the material setting module of the multi-physics simulation platform.

5. The solid oxide fuel cell gradient pore anode modeling calculation method according to claim 1, characterized in that: The electrochemical model construction in step S4 includes the following steps: S4.1, SOFC open circuit voltage is caused by the difference in hydrogen and oxygen concentrations between the cathode and anode: Where E is the open circuit voltage of SOFC; E0 is the theoretical electrode potential of the battery; R is the ideal gas molar constant, which is 8.314 J·mol -1 ·K -1 , T is temperature, unit K, F is Faraday constant, value is 9.6485C·mol -1 , P is the partial pressure of the gas component, unit is Pa; S4.2, SOFC operating voltage V cell The calculation formula is: Among them, V act is the activation polarization loss; V con is the concentration polarization loss, V ohm is the ohmic polarization loss; S4.3, use the Butler-Volmer equation to describe the current density: Where J is the working current density, A·m -2 ; J0 is the exchange current density, A·m -2 ; α is the electron transfer coefficient; n is the number of electrons transferred in each electrochemical reaction; η act is the activation overpotential, exp is the exponential function; Taking into account the influence of temperature, J0 is expressed as follows: Where γ is the pre-exponential factor, A·m -2 ;E act is the activation energy, J·mol -1 .

6. A solid oxide fuel cell gradient pore anode modeling calculation method according to claim 5, characterized in that: The airflow transfer model construction in step S4 includes the following steps: S4.4, the internal reaction of SOFC cell follows the law of conservation of mass, and the governing equation is expressed as: in, is the divergence operator, ε is the porosity, ρ is the gas density, v is the velocity vector, S m For the quality source; S4.5, the Navier-Stokes equations describe the momentum transfer mechanism in open channels. The compressible Navier-Stokes equations are used for modeling in gas flow channels: Where p is the pressure of the gas, Pa; I represents the unit tensor, τ is the viscous stress tensor, and F, is the body force vector; S4.6, seepage occurs in porous electrodes. Considering the influence of porosity and permeability, the Brinkman equation is used to describe it, which is expressed as: Where ξ is the permeability and μ is the gas dynamic viscosity.

7. A solid oxide fuel cell gradient pore anode modeling calculation method according to claim 6, characterized in that: The material diffusion model construction in step S4 includes the following steps: S4.7, use the Stefan-Maxwell model based on the Fick model to describe the gas diffusion in the electrode, and consider Knudsen diffusion: Among them, w i is the mass fraction of gas i, is the thermal diffusion coefficient m of gas i 2 / s,Q i is the mass source term of gas i, in kg / (m3·s), to is the inverse of the tortuosity factor, D ij is the bulk diffusion coefficient of gases i and j, in m 2 / s,D ij,eff is the effective binary diffusion coefficient, in m 2 ·s -1 , x j is the mole fraction of gas j; S4.8, use the dust-gas model to describe the diffusion of the mixture in the porous medium as described by the following equation: Where, P i represents the partial pressure of gas i; N i is the molar flux of gas i; is the effective Kunsen diffusion coefficient.

8. A solid oxide fuel cell gradient pore anode modeling calculation method according to claim 7, characterized in that: The heat transfer model in step S4 is constructed as follows: Among them, C p is the specific heat capacity of the component, k eff is the thermal conductivity of each component; Q is the heat source term.

9. The solid oxide fuel cell gradient pore anode modeling calculation method according to claim 1, characterized in that: Step S5 specifically includes the following steps: S5.

1. Set the boundary conditions for the multiphysics coupling model: fuel inlet volume ratio: H2 / H2O = 0.97:0.03, flow rate 1 m / s; air inlet volume ratio: O2 / N2 = 0.21:0.79, flow rate 2 m / s; electrochemical boundaries: anode grounded at 0 V, cathode set to an operating voltage of 0.6-0.8 V; S5.

2. Grid the SOFC cell using hexahedral elements. The total number of cells in the SOFC cell is 73,500. The electrode-electrolyte interface region is denser. S5.3, calculate the multi-physics field coupling model separately using different grid sizes, and use grid independence to verify the effectiveness of the multi-physics field coupling model.

10. The solid oxide fuel cell gradient pore anode modeling calculation method according to claim 1, characterized in that: Step S6 specifically includes the following steps: S6.1, calculate the electrochemical performance, temperature field, and material distribution field of the battery; S6.2, calculate the temperature field, material distribution field and electrochemical power density of the battery under different anode structural parameters to obtain the optimal solid oxide fuel cell gradient pore anode design parameters.

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