Method for establishing performance prediction simulation model of direct ammonia fuel cell

Abstract

The invention discloses a method for establishing a performance prediction simulation model of a direct ammonia fuel cell. The method comprises the following steps: establishing a three-dimensional two-phase geometric model of the direct ammonia fuel cell, setting physical property parameters in the model, carrying out three-dimensional model grid division, respectively setting an air inlet mass flow rate and a working temperature according to boundary conditions, and establishing a solving model of the direct ammonia fuel cell. The modeling method provided by the invention accurately describes the electrochemical process and mass transfer characteristics involved in the fuel cell, accurately analyzes electrochemical reaction kinetics through multi-physics field coupling, and clarifies the two-phase transport characteristics and ammonia transmembrane transport mechanism in the anode. The diffusion flux of ammonia molecules caused by the concentration difference and the electroosmosis flux caused by electroosmosis dragging are quantified, so that the regulation and control rule of the current density on ammonia osmosis is obtained, the analysis of multi-physical field distribution characteristics and the influence rule of the multi-physical field distribution characteristics on the battery performance is facilitated, and the method has great significance in optimizing hydrothermal management and low-permeability composite membrane design. The method has guiding significance in reducing ammonia permeation loss.

Description

Technical Field

[0001] The present invention belongs to the technical field of fuel cells, and in particular relates to a three-dimensional simulation modeling method that directly adopts two-phase flow of an ammonia fuel cell. Background Art

[0002] The development of efficient and low-carbon fuel cell technology is the key to building a clean energy system. Ammonia fuel cells use ammonia as fuel, with its high energy density, mature storage and transportation system, and carbon neutrality, providing a new approach to solving bottleneck problems such as high costs of hydrogen storage and transportation and an imperfect industrial chain. As an innovative technology to solve the problem of hydrogen storage and transportation, direct ammonia fuel cells have shown significant technical advantages and industrialization potential in recent years with the in-depth development of polymer electrolyte membrane materials and in-depth research on AOR (ammonia oxidation reaction) related catalysts. However, direct ammonia fuel cells (DAFCs) are complex nonlinear systems involving multi-component reactions, multi-dimensional transport, and multi-physical fields. It is difficult to characterize their internal transport phenomena and multi-physical field distribution characteristics by relying solely on experiments. For the internal transport and reaction processes of DAFCs, the study of the transmembrane transport mechanism and characteristic laws of ammonia is a forward-looking science and technology.

[0003] Establishing a simulation model that couples internal transport and electrochemical reactions within a DAFC full cell is a highly effective research approach. This approach couples multiple physical fields, including electrochemical reactions, fluid flow within porous media, and concentrated species diffusion, to simulate the flow field and ammonia-nitrogen transport processes within porous electrodes. This helps clarify the two-phase transport characteristics within the cell anode and the ammonia transmembrane transport mechanism, quantifying the ammonia transmembrane permeation flux and the resulting parasitic current density. The proposed ammonia fuel cell performance prediction simulation model can reveal the ammonia / water / gas transport kinetics under multi-physics coupling, analyze the multi-physics distribution characteristics and their impact on cell performance, and provide methodological guidance for further developing hydrothermal management and control strategies to improve cell performance. Summary of the Invention

[0004] The purpose of the present invention is to propose a method for establishing a performance prediction simulation model for a direct ammonia fuel cell, to achieve performance prediction under different operating conditions, and to obtain polarization curves and internal multi-physical field distributions under multiple sets of operating condition combinations.

[0005] The method steps for constructing the model of the present invention are as follows:

[0006] (1) Establish a three-dimensional two-phase geometric model of a direct ammonia fuel cell, including: finite element model of cathode and anode flow channels, cathode and anode diffusion layers, cathode and anode catalyst layers, and anion exchange membrane.

[0007] (2) Set the physical parameters of the 7 parts of the finite element model, namely, the cathode and anode flow channels, the cathode and anode diffusion layers, the cathode and anode catalyst layers, and the anion exchange membrane, including: the permeability and intrinsic conductivity of the anion exchange membrane, the permeability, conductivity and porosity of the cathode and anode catalyst layers and diffusion layers, and the gas phase and liquid phase density and dynamic viscosity.

[0008] (3) Use meshing software to mesh the three-dimensional model, and perform additional mesh encryption on the membrane and catalyst layer; set velocity inlet boundary conditions and pressure outlet boundary conditions at the corresponding inlet and outlet positions respectively.

[0009] (4) Set the intake mass flow rate and operating temperature according to the boundary conditions in step (3).

[0010] (5) A solution model for a direct ammonia fuel cell is established. The fluid domains of the anode and cathode of the model include: flow channels, diffusion layers, and catalytic layers; the porous electrodes of the anode and cathode include: diffusion layers, catalytic layers; and the electron transport part includes: catalytic layers and diffusion layers.

[0011] Furthermore, the governing equations of the three-dimensional model include: the continuity equation, the momentum conservation equation, the porous media momentum conservation equation, the material transport equation, the liquid water transport equation (under steady-state operating conditions), the liquid water volume fraction solved using the Leverett-J equation, the charge conservation equation, and the electrochemical reaction rate solved using the modified Butler-Volmer equation.

[0012] By using the established simulation model, simulation calculations are performed to simulate its performance, outputting polarization curves and internal multi-physics fields under different combinations of operating temperature and speed conditions. The ammonia permeation flux driven by diffusion and electroosmotic drag, as well as the resulting parasitic current density, are calculated according to formula (13).

[0013] The increase in current density reduces the net permeation flux of ammonia through a dual mechanism: on the one hand, the current consumes anode ammonia, narrows the concentration gradient, and inhibits the diffusion flux; on the other hand, the ion migration is enhanced, strengthening the offsetting effect of electroosmosis on diffusion. By calculating the change law of ammonia permeation flux with current density, the regulation law of current density on ammonia permeation can be obtained, which provides a quantitative basis for optimizing hydrothermal management and inhibiting ammonia leakage.

[0014] This simulation model realizes the fully coupled dynamic simulation of electrochemistry, two-phase flow, and transmembrane transport. It can analyze the multi-physical field distribution characteristics inside the DAFC and its impact on battery performance, and effectively predict battery performance under different operating conditions. This reduces the time and economic costs consumed by the experiment, and helps to explore the hydrothermal management and control methods for improving heat and mass transfer under operating conditions and battery design, thereby improving DAFC performance.

[0015] The characteristics and benefits of the present invention are as follows: (1) The proposed modeling method comprehensively considers the electrochemical processes and mass transfer characteristics involved in direct ammonia fuel cells, including processes such as gas-liquid two-phase transport in porous media. Through multi-physics field coupling, the electrochemical reaction kinetics are accurately analyzed, and the two-phase transport characteristics in the anode and the ammonia transmembrane permeation mechanism are clarified. (2) The synergistic effect of ammonia oxidation at the anode and oxygen reduction at the cathode are simulated by combining the modified Butler-Volmer equation. (3) The diffusion flux of ammonia molecules caused by concentration difference and the electroosmotic flux caused by electroosmotic drag are quantified, which has guiding significance for the design of low-permeability composite membranes and the reduction of ammonia permeation losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a geometric diagram of the three-dimensional model established in the example of the present invention.

[0017] Figure 2 This is a diagram of ammonia permeation flux according to an example of the present invention.

[0018] Figure 3 This is a parasitic current density diagram of an example of the present invention.

[0019] Figure 4 This is the ammonia concentration cloud map output by the example of the present invention.

[0020] Figure 5 This is the nitrogen concentration cloud map output by the example of the present invention. DETAILED DESCRIPTION

[0021] The method steps of the present invention are further described below with reference to the accompanying drawings and through specific calculation examples. It should be noted that this embodiment is descriptive rather than restrictive and does not limit the scope of protection of the present invention.

[0022] 1. The steps of establishing the performance prediction simulation model of direct ammonia fuel cells are as follows:

[0023] (1) Establish a three-dimensional two-phase geometric model of a direct ammonia fuel cell, including: finite element model of cathode and anode flow channels, cathode and anode diffusion layers, cathode and anode catalyst layers, and anion exchange membrane.

[0024] (2) Set the physical parameters of the 7 parts of the finite element model, namely, the cathode and anode flow channels, the cathode and anode diffusion layers, the cathode and anode catalyst layers, and the anion exchange membrane, including: the permeability and intrinsic conductivity of the anion exchange membrane, the permeability, conductivity and porosity of the cathode and anode catalyst layers and diffusion layers, and the gas phase and liquid phase density and dynamic viscosity.

[0025] (3) Use meshing software to mesh the three-dimensional model, and perform additional mesh encryption on the membrane and catalyst layer; set velocity inlet boundary conditions and pressure outlet boundary conditions at the corresponding inlet and outlet positions respectively.

[0026] (4) Set the intake mass flow rate and operating temperature according to the boundary conditions in step (3).

[0027] (5) A three-dimensional two-phase solution model of a direct ammonia fuel cell is established. The fluid domains of the anode and cathode of the model include: flow channels, diffusion layers and catalyst layers; the porous electrodes of the anode and cathode include: diffusion layers and catalyst layers; and the electron transport part includes: catalyst layers and diffusion layers.

[0028] The governing equations of the specific three-dimensional model include:

[0029] (1) Continuity equation:

[0030]

[0031] where ρ - Density kg m -3 , u - velocity vector ms -1 .

[0032] (2) Momentum conservation equation

[0033]

[0034] Where p-pressure Pa, μ - Dynamic viscosity of the mixture kg m -1 s -1 , I-unit tensor, u-velocity vector, -Velocity vector gradient.

[0035] (3) Conservation equation of momentum in porous media (Brinkman equation):

[0036]

[0037] Where ε is the porosity of the porous medium, κ is - Permeability of porous media (m 2 ), β-Ergun parameters.

[0038] (4) Material transport equation:

[0039]

[0040] where ω j -mass fraction, x j - mole fraction, - mole fraction gradient, R i -reaction source term, D ij eff is the effective diffusion coefficient m of substance i relative to substance j 2 s -1 , the effective diffusion coefficient Dij eff Need to add reference diffusion coefficient D ij m 2 s -1 , porosity and liquid water volume fraction corrections:

[0041]

[0042] Where s is the liquid water volume fraction and ε is the porosity.

[0043] (5) The liquid water transport equation under steady-state operating conditions is:

[0044]

[0045] Where κ is the intrinsic permeability of porous media m 2 , κ l -Relative permeability of liquid water m 2 , μ l -Liquid water dynamic viscosity kgm -1 s -1 , p l -Liquid pressure Pa, S l -source term kg m -3 s -1 .

[0046] (6) Use the Leverett-J equation to solve the liquid water volume fraction:

[0047]

[0048] Among them, P c -capillary pressure Pa, θ-porous medium contact angle °, σ-liquid water surface tension N m -1 .

[0049] (7)) Charge conservation equation:

[0050]

[0051] where σ e -Effective ionic conductivity Sm -1 , σ ion -Effective electronic conductivity Sm -1 .

[0052] (8) Solve the electrochemical reaction rate using the modified Butler-Volmer equation:

[0053]

[0054] in - anodic reference exchange current density, - cathode reference exchange current density, - ammonia concentration molm -3 、 -Oxygen concentration mol m -3 、 -water concentration mol m -3 , - Ammonia reference concentration mol m -3 , - oxygen reference concentration mol m -3 , -water reference concentration mol m -3 , γ, δ, ε are the reaction orders, α a -Anode charge transfer coefficient, α c - Charge transfer coefficient at cathode, R - Universal gas constant 8.314 J mol -1 K -1 , η act,a - activation overpotential V of the anode, η act,c - Activation overpotential V of the cathode.

[0055] The simulation models established above were used to simulate their performance. The polarization curves and internal multi-physics fields under different operating conditions (operating temperature and speed) were output, and the ammonia permeation flux driven by diffusion and electroosmotic drag, as well as the resulting parasitic current density, were calculated according to the following formula (13):

[0056]

[0057] I crossover =3F·Ammonia crossover (14)

[0058] in -Diffusion coefficient m of liquid ammonia in the membrane 2 s -1 , n d - electroosmotic drag coefficient, - mole fraction of ammonia, K mem -Permeability of anion exchange membrane m 2 ,Δp-pressure difference on both sides of the membrane Pa,δ mem - thickness of the film m, - ammonia concentration mol m -3 , and the ammonia permeation flux and parasitic current density are calculated.

[0059] The model parameters designed in this embodiment are given in the specific calculation process.

[0060] (1) Establish a three-dimensional two-phase geometric model of a direct ammonia fuel cell (see attached) Figure 1The model includes finite element models of cathode and anode flow channels, cathode and anode diffusion layers, cathode and anode catalyst layers, and anion exchange membrane.

[0061] In this step, the geometric parameters of each component are determined, such as Figure 2 As shown in the cross-sectional view, the channel inlet and outlet sections are 0.4mm wide and 0.4mm high, the cathode / anode diffusion layer thickness is 0.33mm, the anode / cathode catalyst layer thickness is 0.04mm, and the membrane thickness is 0.015mm.

[0062] (2) Set the material properties of each component. Anion exchange membrane permeability K mem 1.0×10 -18 m 2 , the static contact angles θ of the anode diffusion layer and the catalyst layer are both 110°. The intrinsic permeability K of the cathode and anode diffusion layers gdl 5.0×10 -11 m 2 , the intrinsic permeability of the catalytic layer K cl 2.0×10 -11 m 2 The intrinsic conductivity σ of the anode and cathode diffusion layer, catalytic layer and membrane gdl , σ cl , σ mem 200s·m -1 , 200s·m -1 and 1s·m -1 The porosity of the anode and cathode diffusion layers and the catalyst layer ε gdl , ε cl The surface tension coefficient σ is 0.0625N·m -1 , transfer coefficient α a , α c They are 0.46 and 1 respectively, and the constant voltage V cell =0.6V input.

[0063] (3) Use meshing software to mesh the three-dimensional model and perform additional mesh encryption on the membrane and catalyst layer.

[0064] (4) Set the boundary conditions and working conditions, and set the velocity inlet boundary conditions and pressure outlet boundary conditions at the corresponding inlet and outlet positions. The inlet velocity is 0.26m·s -1 The cathode and anode outlet pressures are both 1.0 atm, and the temperature boundary conditions are set, and the battery operating temperature T is 80 °C.

[0065] From the formula, we can see that the ammonia permeation flux is mainly caused by three mechanisms: the diffusion term caused by concentration difference, the electroosmotic term caused by electric drag, and the convection term caused by pressure gradient. So far, the ammonia permeation flux diagram and parasitic current density diagram have been obtained through calculation, as shown in the attached figure. Figure 2 、 3 shown.

[0066] Figure 2 The law of ammonia permeation flux in direct ammonia fuel cells changing with current density is presented in the figure: the diffusion flux is driven by the anode-cathode ammonia concentration gradient. When the current density increases, the ammonia in the anode is consumed by the electrochemical reaction, the concentration gradient decreases, and the diffusion driving force is weakened. The calculated ammonia diffusion flux decreases monotonically with increasing current density; while the electroosmotic flux is determined by the direction in which ion migration "drags" ammonia molecules. The direction of ion migration is opposite to the direction of ammonia diffusion, which manifests as "inhibition" of diffusion. Its intensity first increases with current density, and then tends to equilibrium due to the decrease in ammonia concentration in the membrane. In the figure, 300-400mA / cm 2 The electroosmotic flux peaked in the first half of the 20th century, then declined slightly and stabilized. The "first rise and then stability" of the electroosmotic flux reflects the dynamic equilibrium between ammonia transport and ion migration within the membrane: initially, the ion migration rate is dominated by the electroosmotic intensity, while later, the ammonia concentration within the membrane becomes the limiting factor.

[0067] Figure 3 It shows how the parasitic current generated by the electrochemical reaction after ammonia penetrates into the cathode changes with the working current density. The intensity of the parasitic current is directly related to the ammonia permeation flux, and it decreases monotonically with the increase of the battery working current density. The downward curve in the figure shows that increasing the battery working current density can inhibit ammonia permeation and reduce side reaction losses.

[0068] In addition, the simulation model can also give a cloud diagram of ammonia concentration distribution, as shown in the attached figure. Figure 4 This is a pseudo-color cloud map showing the concentration gradient. The flow channel represents a high-concentration ammonia "transport zone," while the vicinity of the catalyst layer represents a low-concentration ammonia "consumption-equilibrium zone." Along the flow channel, the ammonia concentration near the catalyst layer exhibits a gradient characteristic of "low on the left and high on the right," due to "strong consumption at the inlet and decreasing consumption along the flow path."

[0069] At the same time, the simulation model gives the nitrogen concentration distribution cloud map, as shown in the attached figure. Figure 5 The figure clearly illustrates the coupled process of "reaction generation-diffusion-transport." The spatial gradient of color intuitively reflects the chain logic of "ammonia consumption → reaction rate reduction → nitrogen generation reduction → mass transfer and transport attenuation," providing a visual representation of the "reactant consumption-product evolution" of the anode of a direct ammonia fuel cell.

Claims

1. A method for establishing a performance prediction simulation model for a direct ammonia fuel cell, characterized by: The steps for building the model are as follows: (1) Establish a three-dimensional two-phase geometric model of a direct ammonia fuel cell, including: finite element model of cathode and anode flow channels, cathode and anode diffusion layers, cathode and anode catalyst layers, and anion exchange membrane; (2) Setting the physical parameters of the 7 parts of the finite element model: cathode and anode flow channels, cathode and anode diffusion layers, cathode and anode catalyst layers, and anion exchange membrane, including: anion exchange membrane permeability, intrinsic conductivity, cathode and anode catalyst layers, diffusion layer permeability, conductivity and porosity, gas phase, liquid phase density and dynamic viscosity; (3) Use meshing software to mesh the three-dimensional model, and perform additional mesh encryption on the membrane and catalyst layer; set velocity inlet boundary conditions and pressure outlet boundary conditions at the corresponding inlet and outlet positions respectively; (4) setting the intake mass flow rate and operating temperature according to the boundary conditions in step (3); (5) Then, a three-dimensional two-phase geometric solution model of a direct ammonia fuel cell is established. The fluid domains of the anode and cathode of the model include: flow channels, diffusion layers and catalyst layers; the porous electrodes of the anode and cathode include: diffusion layers and catalyst layers; and the electron transport part includes: catalyst layers and diffusion layers.

2. The method for establishing a performance prediction simulation model for a direct ammonia fuel cell according to claim 1, characterized in that: The governing equations of the three-dimensional two-phase model include: (1) Continuity equation: ▽(ρu)=0 (1) Where ρ is the density and u is the velocity vector; (2) Momentum conservation equation ρ(u·▽)u=▽·[-pI+μ(▽u+(▽u) T )] (2) Where p is the pressure, μ is the mixture dynamic viscosity, I is the unit tensor, u is the velocity vector, ▽u is the velocity vector gradient, (3) Momentum conservation equation for porous media: Where ε is the porosity of the porous medium, κ is the permeability of the porous medium, and β is the Ergun parameter; (4) Material transport equation: where ω j is the mass fraction, x j is the mole fraction, ▽x j is the mole fraction gradient, R i is the reaction source term, D ij eff is the effective diffusion coefficient of substance i relative to substance j, the effective diffusion coefficient D ij eff Need to add reference diffusion coefficient D ij , porosity and liquid water volume fraction corrections: D ij eff =D ij [(1-s)ε] 1.5 (6) Where s is the liquid water volume fraction and ε is the porosity; (5) The liquid water transport equation under steady-state operating conditions is: where κ is the intrinsic permeability of the porous medium, l is the relative permeability of liquid water, μ l is the dynamic viscosity of liquid water, p l is the liquid pressure, S l is the source term; (6) Use the Leverett-J equation to solve the liquid water volume fraction: Among them, P c is the capillary pressure, θ is the contact angle of the porous medium, and σ is the surface tension of liquid water; (7)) Charge conservation equation: ▽·(s e ▽φ e )=0 (10) ▽·(s ion ▽φ ion )=0 (11) where σ e is the effective ionic conductivity, σ ion is the effective electronic conductivity; (8) Solve the electrochemical reaction rate using the modified Butler-Volmer equation: in is the anodic reference exchange current density, is the cathode reference exchange current density, is the ammonia concentration, is the oxygen concentration, is the water concentration, is the ammonia reference concentration, is the oxygen reference concentration, is the water reference concentration, γ, δ, ε are the reaction orders, α a is the anode charge transfer coefficient, α c is the cathode charge transfer coefficient, R is the universal gas constant, η act,a is the activation overpotential of the anode, η act,c is the activation overpotential of the cathode.

3. The method for establishing a performance prediction simulation model for a direct ammonia fuel cell according to claim 1 or 2, characterized in that: The simulation model established in claim 2 is used to simulate its performance, output polarization curves and internal multi-physical fields under different combinations of operating temperature and speed conditions, and calculate the ammonia permeation flux driven by diffusion and electroosmotic drag and the resulting parasitic current density according to the following formula (13): I crossover =3F·Ammonia crossover (14) in is the diffusion coefficient of liquid ammonia in the membrane, n d is the electroosmotic drag coefficient, is the mole fraction of ammonia, K mem is the permeability of the anion exchange membrane, Δp is the pressure difference across the membrane, δ mem is the membrane thickness, is the ammonia concentration, and the ammonia permeation flux and parasitic current density are calculated.

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