Battery performance prediction method based on carbon corrosion of the catalytic layer

Abstract

The present invention discloses a battery performance prediction method based on carbon corrosion of the catalytic layer. In the battery performance prediction method based on carbon corrosion of the catalytic layer, a dual-site carbon corrosion kinetic reaction equation group is adopted, and the carbon-based mass loss under different operating voltage cycle conditions is calculated based on the Newton method. The carbon mass is converted into the evolution of the carbon particle diameter in the agglomerate model according to the conservation of carbon mass within each time step, and then the change of the microstructure of the catalytic layer is deduced, and the catalytic layer thickness, ionomer volume fraction, catalyst volume fraction and porosity are updated. The average radius of the Pt particles is predicted using a Pt aging radius model. According to the structural parameters of the catalytic layer after aging, the gas diffusion coefficient, proton conductivity and local mass transfer resistance and other parameters in the battery model are updated. By iteratively solving the battery model, the battery performance after carbon corrosion of the catalytic layer is predicted.

Description

Technical Field

[0001] The invention belongs to the technical field of fuel cells, and in particular to a method for predicting battery performance based on carbon corrosion of a catalytic layer. Background Art

[0002] Proton exchange membrane fuel cells (PEMFCs) have considerable potential to replace traditional internal combustion engines due to their high energy density, high efficiency, and theoretically zero emissions. Furthermore, PEMFCs are more reliable than lithium-ion batteries, despite numerous safety concerns. However, widespread adoption of PEM fuel cells in automobiles currently faces two major challenges: cost and longevity.

[0003] One of the factors limiting fuel cell durability is corrosion of the carbon supporting the Pt catalyst in the catalyst layer, particularly on the cathode membrane electrode. Frequent start-up and shutdown cycles are inevitable during the fuel cell's service life. This process causes local overpotentials in the catalyst layer to reach 1.5V, accelerating internal cell aging and significantly impacting battery life. Carbon corrosion during start-stop cycling can significantly age the catalyst layer, disrupting the connectivity of the carbon framework, leading to collapse of the internal solid structure, altering the wetting properties of the porous medium, increasing catalyst particle size, and severely reducing cell output performance. Current estimates of battery life and the impact of catalyst layer aging on battery performance are primarily conducted experimentally. However, these experiments are time-consuming and incur high technical and operational costs, making the use of mathematical models a viable alternative. Many existing carbon corrosion models either completely ignore the complex structural changes caused by carbon corrosion or rely solely on empirical equations for electrode mass loss. These models perform poorly in predicting mass loss and catalyst layer structural changes under varying aging conditions. There is an urgent need for more realistic physicochemical models to describe the various phenomena caused by carbon support corrosion and predict battery performance loss.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the Invention

[0005] In response to the problems existing in the prior art, the present invention proposes a battery performance prediction method based on catalytic layer carbon corrosion. The purpose of the present invention is to achieve this through the following technical solutions. A battery performance prediction method based on catalytic layer carbon corrosion includes:

[0006] Step 1: Establish a one-dimensional battery model. The calculation area of ​​the battery model is composed of the anode plate, anode gas diffusion layer, anode microporous layer, anode catalyst layer, proton exchange membrane, cathode catalyst layer, cathode microporous layer, cathode gas diffusion layer and cathode plate in the thickness direction. The model parameters of the one-dimensional battery model include the diffusion coefficient of each material component, the electrical conductivity of protons and electrons, the local mass transfer resistance of the gas, and the porosity, wetting angle, and average pore diameter physical properties of the porous medium; establish a one-dimensional carbon corrosion model of the catalyst layer, perform aging simulation on the catalyst layer of the battery, divide the catalyst layer into N control bodies along the thickness direction, set the initial structural parameters of the catalyst layer according to the carbon loading, platinum loading, ionomer-to-carbon mass ratio and porosity parameters of the simulated proton exchange membrane fuel cell catalyst layer, that is, the initial porosity, ionomer volume fraction, carbon particle radius, number and platinum particle radius of each control body, and update them in the subsequent carbon corrosion process;

[0007] Step 2: Establish and run the dual-site carbon corrosion model, input the test voltage cycle curve to simulate the catalytic layer aging process under the battery start-stop cycle conditions, where the dual-site carbon corrosion model includes:

[0008] C#+H2O→C#OH+H + +e - (1)

[0009]

[0010] Where f is the Frankin coefficient, c is the proportion of a certain reaction product in the total reaction sites on the carbon surface, the subscripts va and co represent the type of reaction product, the symbols # or * represent the types of two reaction sites on the carbon surface, F is the Faraday constant, R is the universal gas constant, T is the catalyst layer temperature during the reaction, V is the catalyst layer overpotential, and other parameters are fitting parameters of the electrochemical reaction kinetics. This parameter description is also applicable to the subsequent formulas.

[0011]

[0012]

[0013] Where p0 is the water vapor partial pressure, is the reference value of water vapor partial pressure,

[0014]

[0015]

[0016] where h + is the proton concentration in the ionomer of the catalytic layer, is the reference value of the proton concentration in the ionomer,

[0017] 2C#OH+C#+H2O→C3#O3+4H + +4e - (7)

[0018]

[0019] C3#O+C*O→C3#O2+C* (9)

[0020]

[0021] 2C#OH+C#+H2O+C3#O2→C3#O2+C3#O3+4H + +4e - (11)

[0022]

[0023]

[0024]

[0025] Formulas (1)-(14) are the electrochemical reaction process and the corresponding kinetic equation expressions in the dual-site carbon corrosion model, where formulas (3) and (4) are the electrochemical reaction equations and kinetic equations for carbon oxidation to generate carbon dioxide.

[0026]

[0027]

[0028]

[0029]

[0030]

[0031]

[0032] Formulas (15)-(20) are the governing equations of the dual-site carbon corrosion model, where N # and N * are the molar numbers of # and * sites per unit carbon surface area, respectively. They are solved under the start-stop cycle conditions to simulate the carbon corrosion process of the catalytic layer under the start-stop state of the battery. The carbon corrosion reaction rate, the generation and consumption rate of oxides and intermediates, and the coverage of each control body are obtained by iterative calculation using the Newton method.

[0033]

[0034]

[0035] Formulas (21)-(22) are the carbon mass conservation and water vapor conservation control equations of the catalyst layer, which simulate the overall carbon corrosion and water vapor consumption and transportation process inside the catalyst layer. Substituting the carbon corrosion rate calculated by the carbon corrosion model into the equations and solving them, the carbon residual amount of each control body and the water vapor concentration distribution in the catalyst layer at the current time step can be obtained. C，i is the residual molar amount of carbon per unit cross-sectional area of ​​each control volume, ε is the porosity, S b is the specific surface area of ​​carbon particles, M is the molar mass of carbon, Rate2 is the reaction rate of carbon oxidation to produce carbon dioxide, D is the diffusion coefficient of water vapor in the catalytic layer, is the water vapor concentration, is the source term of water vapor consumption caused by carbon corrosion, and the subscript i represents the number of the control body;

[0036] Step 3: Based on the evolution control equation, simulate the compression process of the catalytic layer structure, update the catalytic layer structural parameters, and predict the average radius of the Pt particles according to the catalytic layer Pt aging radius prediction equation, where:

[0037]

[0038]

[0039]

[0040]

[0041]

[0042]

[0043] ε(i)=1-ε C (i)-ε i (i)-ε Pt (i) (29)

[0044] Formulas (23)-(29) are the evolution control equations of the catalyst layer structural parameters. They simulate the structural compression process of the catalyst layer under the action of preload after carbon corrosion. The C C，i Substitute into the equations and solve to obtain the remaining thickness, porosity, ionomer volume fraction, and carbon particle diameter of each control body of the catalyst layer after carbon corrosion in the current time step, where d i is the carbon particle diameter, ε i (i), ε C (i), ε Pt(i) and ε(i) are the volume fractions and porosity of ionomer, carbon matrix and metal platinum, respectively; dx(i) is the size of the control body; (I / C) is the mass ratio of ionomer to carbon matrix; num i To control the amount of carbon particles in the body, A is the cross-sectional area of ​​the catalytic layer, V M is the molar volume of carbon, ρ Pt is the density of metallic platinum, ρ C is the density of carbon, ρ ion is the density of the ionomer, L CL is the initial thickness of the catalytic layer, m Pt is the platinum loading of the catalytic layer,

[0045]

[0046]

[0047] Formulas (30)-(31) are the prediction equations for the aging radius of Pt in the catalyst layer. They simulate the dissolution and reprecipitation process of Pt particles in the carbon matrix under start-stop cycle conditions. By iteratively calculating and solving them, the average radius of Pt particles at any time in the start-stop cycle test can be obtained. t，Pt , where r0 is the initial radius of the platinum particle, δ is the surface energy density of platinum, Pt 2+ The equilibrium concentration in the ionomer, Pt 2+ Diffusion coefficient in ionomer, V a is the average voltage, E rev is the reversible potential of platinum dissolution reaction, V Pt is the molar volume of platinum;

[0048] Step 4: Update the battery model parameters according to the updated catalyst layer structure parameters, where:

[0049]

[0050]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056]

[0057]

[0058] Formulas (32)-(40) are the local mass transfer resistance, the equivalent diffusion resistance R1 in the ionomer, the equivalent interface transport resistance R2 of Pt, the equivalent interface transport resistance R3 of the ionomer, and the effective diffusion coefficient Electrochemical specific surface area ECSA of Pt, thickness δ of ionomer membrane ion , mass ratio of platinum to carbon Pt / C, Pt active volume surface area a Pt and carbon active volume surface area a C The relationship between the carbon particle radius r calculated above and the catalytic layer structure parameters is C , ionomer volume fraction ε ion , I / C, porosity ratio and other parameters are substituted into the calculation to update the structural parameters, so that the local structural changes after carbon corrosion of the catalyst layer can be reflected in the calculation of the overall performance of the battery;

[0059] Step 5: Predict battery performance based on the updated battery model parameters, where:

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066] Formulas (41)-(46) are the governing equations of the one-dimensional battery model, where C i is the gas component concentration, is the effective diffusion coefficient of the gas component, s lq is the liquid water saturation, D l is the effective diffusion coefficient of liquid water, ρ1 is the density of liquid water, λ is the membrane water content, D m is the effective diffusion coefficient of membrane water, ρ MEM is the membrane density, EW is the equivalent weight of the membrane, φ e is the electron potential, is the effective conductivity of electrons, φ i is the proton potential, is the effective conductivity of protons, T is the temperature, k effThe effective thermal conductivity is calculated by inputting the cathode and anode inlet pressures, hydrogen and oxygen concentrations, temperature, relative humidity, and battery output voltage boundary condition parameters into the one-dimensional battery model. Formulas (41)-(46) are then coupled and iteratively solved to obtain the concentrations of the various material components within the battery, the distribution of the proton overpotential, electron overpotential, and temperature within the battery, as well as the corresponding output current density of the battery at this output voltage. Substituting the updated battery model parameters, the output current density at an output voltage of 0.1-1.0V is calculated to obtain the battery polarization curve, completing the prediction of battery performance after start-stop cycle aging.

[0067] In the battery performance prediction method based on catalytic layer carbon corrosion, the material components inside the battery include hydrogen, oxygen, nitrogen, water vapor, membrane water, and liquid water.

[0068] In the battery performance prediction method based on carbon corrosion of the catalytic layer, the catalytic layer is a cathode catalytic layer.

[0069] In the battery performance prediction method based on carbon corrosion of the catalytic layer, the test voltage cycle curve is a triangular electric wave or a rectangular electric wave or a constant voltage.

[0070] Compared with the prior art, the present invention has the following advantages: the battery performance prediction method based on carbon corrosion of the catalytic layer described in the present invention adopts a dual-site carbon corrosion kinetic reaction equation group, calculates the carbon-based mass loss under different operating voltage cycling conditions based on the Newton method, and converts it into the evolution of the carbon particle diameter in the agglomerate model according to the conservation of carbon mass in each time step, and then deduces the changes in the microstructure of the catalytic layer (updating the catalytic layer thickness, ionomer volume fraction, catalyst volume fraction and porosity, etc., and the average radius of the Pt particles is predicted using the Pt aging radius model). According to the structural parameters of the catalytic layer after aging, the gas diffusion coefficient, proton conductivity and local mass transfer resistance and other parameters in the battery model are updated, and the battery model is iteratively solved to achieve the prediction of the battery performance after carbon corrosion of the catalytic layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Various other advantages and benefits of the present invention will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are intended only to illustrate preferred embodiments and are not to be construed as limiting the present invention. It should be understood that the drawings described below are merely examples of the present invention, and that those skilled in the art will be able to derive other drawings from these drawings without inventive effort. Throughout the drawings, identical reference numerals are used to denote identical components.

[0072] In the attached figure:

[0073] Figure 1is a flow chart of a method for predicting battery performance based on carbon corrosion of the catalytic layer according to one embodiment of the present invention;

[0074] Figure 2 1 is a schematic diagram comparing fuel cell polarization curve results and experimental measurement results of a method for predicting battery performance based on carbon corrosion of a catalytic layer according to an embodiment of the present invention;

[0075] Figure 3 This is a schematic diagram of the triangular radio wave used to simulate the battery start-stop cycle conditions during the experimental measurement and model verification process in the above example.

[0076] The present invention will be further explained below with reference to the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0077] The following will refer to the attached Figures 1 to 3 Specific embodiments of the present invention will now be described in greater detail. Although specific embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention may be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to facilitate a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0078] It should be noted that certain words are used in the specification and claims to refer to specific components. Those skilled in the art should understand that technicians may use different nouns to refer to the same component. This specification and claims do not use the difference in nouns as a way to distinguish components, but use the difference in the functions of the components as the criterion for distinction. As mentioned throughout the specification and claims, "including" or "comprising" is an open term, so it should be interpreted as "including but not limited to". The subsequent description of the specification is a preferred embodiment of the present invention, but the description is based on the general principles of the specification and is not intended to limit the scope of the invention. The scope of protection of the present invention shall be as defined in the attached claims.

[0079] To facilitate understanding of the embodiments of the present invention, further explanation will be given below using specific embodiments as examples in conjunction with the accompanying drawings, and the accompanying drawings do not constitute a limitation on the embodiments of the present invention.

[0080] For better understanding, Figures 1 to 3 As shown, the battery performance prediction methods based on carbon corrosion of the catalytic layer include:

[0081] The dual-site carbon corrosion kinetic reaction equations are used to calculate the carbon-based mass loss under different operating voltage cycling conditions based on the Newton method. The carbon mass conservation law is converted into the evolution of the carbon particle diameter in the agglomerate model within each time step, and then the changes in the microstructure of the catalytic layer are deduced (the catalytic layer thickness, ionomer volume fraction, catalyst volume fraction and porosity are updated, and the average radius of the Pt particles is predicted using the Pt aging radius model). According to the structural parameters of the catalytic layer after aging, the gas diffusion coefficient, proton conductivity and local mass transfer resistance in the battery model are updated. By iteratively solving the battery model, the battery performance after carbon corrosion of the catalytic layer is predicted.

[0082] In one embodiment, testing the voltage cycling profile includes a start-stop voltage cycling test.

[0083] In one embodiment, the method is divided into three submodules, namely a one-dimensional catalytic layer carbon corrosion prediction module, a full battery model parameter update module, and a battery overall performance prediction module.

[0084] ① One-dimensional catalyst layer carbon corrosion prediction module:

[0085] The cathode catalyst layer is divided into N control bodies along the thickness direction of the battery. The initial porosity, ionomer volume fraction, carbon particle radius, platinum particle radius, etc. of each control body are set according to the carbon loading, platinum loading, I / C and other parameters of the simulated proton exchange membrane fuel cell.

[0086] C#+H2O→C#OH+H + +e - (1)

[0087]

[0088]

[0089]

[0090]

[0091]

[0092] 2C#OH+C#+H2O→C3#O3+4H + +4e - (7)

[0093]

[0094] C3#O+C*O→C3#O2+C* (9)

[0095]

[0096] 2C#OH+C#+H2O+C3#O2→C3#O2+C3#O3+4H + +4e - (11)

[0097]

[0098]

[0099]

[0100] Formulas (1)-(14) are the electrochemical reaction processes and corresponding kinetic equations in the dual-site carbon corrosion model, where formulas (3) and (4) are the electrochemical reaction equations and kinetic equations for carbon oxidation to generate carbon dioxide.

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] Formulas (15)-(20) are the control equations of the carbon corrosion model. Solving them under the start-stop cycle conditions can simulate the carbon corrosion process of the catalyst layer under the start-stop state of the battery. The Newton method is used to iteratively calculate the carbon corrosion reaction rate, generation and consumption rate of oxides and intermediate products, and coverage of each control body.

[0108]

[0109]

[0110] Formulas (21)-(22) are the carbon mass conservation and water vapor conservation control equations of the catalyst layer, which simulate the overall carbon corrosion and water vapor consumption and transportation process inside the catalyst layer. Substituting the carbon corrosion rate calculated by the carbon corrosion model into the equations and solving them, the carbon residual amount of each control body and the water vapor concentration distribution in the catalyst layer at the current time step can be obtained. C，i is the residual molar amount of carbon per unit cross-sectional area of ​​each control volume, ε is the porosity, S b is the specific surface area of ​​the carbon particles, M is the molar mass of carbon, and Rate2 is the reaction rate of carbon oxidation to produce carbon dioxide.

[0111]

[0112]

[0113]

[0114]

[0115]

[0116]

[0117] ε(i)=1-ε C (i)-ε i (i)-ε Pt (i) (29)

[0118] Formulas (23)-(29) are the evolution control equations of the catalyst layer structural parameters. They simulate the structural compression process of the catalyst layer under the action of preload after carbon corrosion. The C C，i Substituting into the equations and solving them, we can obtain the remaining thickness, porosity, ionomer volume fraction, carbon particle diameter and other parameters of each control body of the catalyst layer after carbon corrosion in the current time step. i is the carbon particle diameter, ε i (i), ε C (i), ε Pt (i) and ε(i) are the volume fractions and porosity of ionomer, carbon matrix and metallic platinum, respectively, dx(i) is the control body size, and (I / C) is the mass ratio of ionomer to carbon matrix.

[0119]

[0120]

[0121] Formulas (30)-(31) are the prediction equations for the aging radius of Pt in the catalytic layer, which simulate the dissolution and reprecipitation process of Pt particles in the carbon matrix under start-stop cycle conditions. The average radius of Pt particles at any time in the start-stop cycle test can be obtained by iterative calculation.

[0122] ②Full battery model parameter update module:

[0123]

[0124]

[0125]

[0126]

[0127]

[0128]

[0129]

[0130]

[0131]

[0132] The changes in the structural parameters of the catalytic layer caused by carbon corrosion will affect the mass transfer and electrochemical reaction inside the battery. Formulas (32)-(40) are the relationships between the local mass transfer resistance, diffusion coefficient, electrochemical reaction area, etc. and the structural parameters of the catalytic layer. Substituting the carbon particle radius, ionomer volume fraction, I / C, porosity and other parameters calculated above into the updated structural parameters, the local structural changes of the catalytic layer after carbon corrosion can be reflected in the overall performance calculation of the battery.

[0133] ③Battery overall performance prediction module (x is the battery thickness direction):

[0134]

[0135]

[0136]

[0137]

[0138]

[0139]

[0140] Formulas (41)-(46) are the control equations of the one-dimensional battery model. Substituting the updated battery model parameters mentioned above, the polarization curve of the battery is obtained by calculating the output current density at an output voltage of 0.1-1.0 V, and the battery performance after start-stop cycle aging is predicted. At the same time, the distribution of various physical fields inside the battery can be output, and the influence of carbon corrosion in the catalyst layer on the heat transfer and mass transfer inside the battery can be more intuitively analyzed, so as to provide a more comprehensive theoretical reference for the optimization design of fuel cells.

[0141] Although the embodiments of the present invention have been described above with reference to the accompanying drawings, the present invention is not limited to the above-mentioned specific embodiments and application fields. The above-mentioned specific embodiments are merely illustrative and instructive, and are not restrictive. A person skilled in the art, guided by this specification and without departing from the scope of protection of the claims of the present invention, may also devise various forms, all of which fall within the scope of protection of the present invention.

Claims

1. A battery performance prediction method based on carbon corrosion of the catalytic layer, characterized in that: It includes the following steps, Step 1: Establish a one-dimensional battery model. The calculation area of ​​the battery model is composed of the anode plate, anode gas diffusion layer, anode microporous layer, anode catalyst layer, proton exchange membrane, cathode catalyst layer, cathode microporous layer, cathode gas diffusion layer and cathode plate in the thickness direction. The model parameters of the one-dimensional battery model include the diffusion coefficient of each material component, the electrical conductivity of protons and electrons, the local mass transfer resistance of the gas, and the porosity, wetting angle, and average pore diameter physical properties of the porous medium; establish a one-dimensional carbon corrosion model of the catalyst layer, perform aging simulation on the catalyst layer of the battery, divide the catalyst layer into N control bodies along the thickness direction, set the initial structural parameters of the catalyst layer according to the carbon loading, platinum loading, ionomer-to-carbon mass ratio and porosity parameters of the simulated proton exchange membrane fuel cell catalyst layer, that is, the initial porosity, ionomer volume fraction, carbon particle radius, number and platinum particle radius of each control body, and update them in the subsequent carbon corrosion process; Step 2: Establish and run the dual-site carbon corrosion model, input the test voltage cycle curve to simulate the catalytic layer aging process under the battery start-stop cycle conditions, where the dual-site carbon corrosion model includes: （1） （2） in is the Franchin coefficient, is the proportion of a certain reaction product in the total reaction sites on the carbon surface, and its subscript and Represents the type of reaction product, symbol and Represent the two types of reaction sites on the carbon surface, is the Faraday constant, is the universal gas constant, is the temperature of the catalyst layer during the reaction, is the overpotential of the catalytic layer, and the other parameters are the fitting parameters of the electrochemical reaction kinetics. This parameter description is also applicable to the subsequent formulas. （3） （4） in is the water vapor partial pressure, is the reference value of water vapor partial pressure, （5） （6） in is the proton concentration in the ionomer of the catalytic layer, is the reference value of the proton concentration in the ionomer, （7） （8） （9） （10） （11） （12） （13） （14） Formulas (1)-(14) are the electrochemical reaction process and the corresponding kinetic equation expressions in the dual-site carbon corrosion model, where formulas (3) and (4) are the electrochemical reaction equations and kinetic equations for carbon oxidation to generate carbon dioxide. （15） （16） （17） （18） （19） （20） Formulas (15)-(20) are the governing equations of the dual-site carbon corrosion model, where and They are and The molar number of sites per unit carbon surface area is solved under the start-stop cycle voltage condition to simulate the carbon corrosion process of the catalytic layer under the start-stop state of the battery. The carbon corrosion reaction rate, the generation and consumption rate of oxides and intermediate products, and the coverage of each control body are obtained by iterative calculation using the Newton method. （21） （22） Formulas (21)-(22) are the carbon mass conservation and water vapor conservation control equations of the catalyst layer, which simulate the overall carbon corrosion and water vapor consumption and transportation process inside the catalyst layer. Substituting the carbon corrosion rate calculated by the carbon corrosion model into the equations and solving them, the carbon residual amount of each control body and the water vapor concentration distribution in the catalyst layer at the current time step can be obtained. is the remaining molar amount of carbon per unit cross-sectional area of ​​each control volume, is the porosity, is the specific surface area of ​​carbon particles, is the molar mass of carbon, is the reaction rate of carbon oxidation to produce carbon dioxide, is the diffusion coefficient of water vapor in the catalyst layer, is the water vapor concentration, is the source term for water vapor consumption caused by carbon corrosion, and the subscript i represents the number of the control body; Step 3: Based on the evolution control equation, simulate the compression process of the catalytic layer structure, update the catalytic layer structural parameters, and predict the average radius of the Pt particles according to the catalytic layer Pt aging radius prediction equation, where: （23） （24） （25） （26） （27） （28） （29） Formulas (23)-(29) are the evolution control equations of the catalyst layer structural parameters. They simulate the structural compression process of the catalyst layer under the action of preload after carbon corrosion. Substitute the equations and solve them to obtain the remaining thickness, porosity, ionomer volume fraction, and carbon particle diameter of each control body in the catalyst layer after carbon corrosion in the current time step, where is the carbon particle diameter, 、 、 、 are the volume fractions and porosity of ionomer, carbon matrix and metallic platinum, respectively. To control the size of the body, is the mass ratio of ionomer to carbon base, To control the amount of carbon particles in the body, is the cross-sectional area of ​​the catalytic layer, is the molar volume of carbon, is the density of metallic platinum, is the density of carbon, is the density of the ionomer, is the initial thickness of the catalytic layer, is the platinum loading of the catalytic layer; （30） （31） Formulas (30)-(31) are the prediction equations for the aging radius of Pt in the catalyst layer. They simulate the dissolution and reprecipitation process of Pt particles in the carbon matrix under start-stop cycle conditions. The average radius of Pt particles at any time in the start-stop cycle test can be obtained by iterative calculation. ,in is the initial radius of the platinum particle, is the surface energy density of platinum, Pt 2+ The equilibrium concentration in the ionomer, Pt 2+ The diffusion coefficient in the ionomer, is the average voltage, is the reversible potential of the platinum dissolution reaction, is the molar volume of platinum; Step 4: Update the battery model parameters according to the updated catalyst layer structure parameters, where: （32） （33） （34） （35） （36） （37） （38） （39） （40） Formulas (32)-(40) are the local mass transfer resistance, and the equivalent diffusion resistance in the ionomer is , the equivalent interfacial transport resistance of Pt , ionomer interface resistance coefficient k1, Pt surface interface resistance coefficient k2, ionomer equivalent interface transport resistance , effective diffusion coefficient , electrochemical specific surface area of ​​Pt , the thickness of the ionomer membrane , mass ratio of platinum to carbon , Pt active volume surface area and carbon active volume surface area The relationship between the carbon particle radius calculated above and the catalytic layer structure parameters is , ionomer volume fraction , I / C, porosity Substitute the other parameters and update the structural parameters to reflect the local structural changes after carbon corrosion in the catalytic layer in the overall performance calculation of the battery. Step 5: Predict battery performance based on the updated battery model parameters, where: （41） （42） （43） （44） （45） （46） Formulas (41)-(46) are the governing equations of the one-dimensional battery model, where is the gas component concentration, is the effective diffusion coefficient of the gas component, is the liquid water saturation, is the effective diffusion coefficient of liquid water, is the density of liquid water, is the membrane water content, is the effective diffusion coefficient of membrane water, is the film density, is the equivalent weight of the membrane, is the electron potential, is the effective conductivity of electrons, is the proton potential, is the effective conductivity of protons, is the temperature, For the effective thermal conductivity, the cathode and anode inlet pressures, hydrogen and oxygen concentrations, temperature, relative humidity and battery output voltage boundary condition parameters are input into the one-dimensional battery model; Formulas (41)-(46) are coupled and iteratively solved to obtain the concentration of each material component inside the battery, the distribution of proton overpotential, electron overpotential and temperature inside the battery, and the output current density corresponding to the battery under the output voltage state; Substituting the updated battery model parameters, the polarization curve of the battery is obtained by calculating the output current density at an output voltage of 0.1-1.0 V, and the prediction of the battery performance after start-stop cycle aging is completed.

2. The battery performance prediction method based on catalyst layer carbon corrosion according to claim 1, wherein: The material components inside the battery include hydrogen, oxygen, nitrogen, water vapor, membrane water, and liquid water.

3. The battery performance prediction method based on catalyst layer carbon corrosion according to claim 1, wherein: The catalytic layer is a cathode catalytic layer.

4. The battery performance prediction method based on catalyst layer carbon corrosion according to claim 1, wherein: The test voltage cycle curve is a triangular wave or a rectangular wave or a constant voltage.

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