Method and system for establishing a local dimension reduction simulation model of a proton exchange membrane electrolysis cell

Abstract

The application belongs to the technical field of electrolytic cells, and discloses a method and system for establishing a local dimension reduction simulation model of a proton exchange membrane electrolytic cell. The method constructs a local dimension reduction simulation model of a proton exchange membrane electrolytic cell composed of a three-dimensional calculation domain and a one-dimensional calculation domain, solves multiple physical fields in the three-dimensional calculation domain through a nonlinear partial differential equation, and obtains scalar values providing boundary conditions for the one-dimensional calculation domain; based on the scalar values, the multiple physical fields are solved in the one-dimensional calculation domain through a difference flux equation after node discretization, and the solving results are returned to the three-dimensional calculation domain in the form of source terms for iterative updating of the multiple physical fields in the three-dimensional calculation domain, and the steps are repeated until the numerical values of the calculation domain are stable, and the simulation of the multiple physical fields in the calculation domain is completed. While ensuring high-precision simulation of the real physical process, the application greatly reduces the number of grids and the calculation time, and breaks through the area limitation of the traditional model.

Description

Technical Field

[0001] This invention belongs to the field of electrolytic cell technology, and particularly relates to a method and system for establishing a local dimensionality reduction simulation model of a proton exchange membrane electrolytic cell. Background Technology

[0002] Hydrogen energy, as a green secondary energy source with high calorific value, wide availability, and zero emissions during utilization, is considered an important component in building a new clean energy system for the future. Using renewable energy sources such as wind and solar power for hydrogen production through water electrolysis not only achieves true zero carbon emissions but also effectively addresses the intermittency, volatility, and curtailment issues associated with renewable energy generation, making it an ideal approach for large-scale, long-term energy storage. Among these technologies, proton exchange membrane electrolyzers (PEMECs) are considered to have significant commercial potential and promising prospects for hydrogen production due to their high operating current density, high hydrogen purity, compact system size, and extremely fast start-up, shutdown, and load-changing response.

[0003] The PEMEC (Polymer Electrolytic Electrode Cell) involves highly coupled multiphysics fields, including gas-liquid two-phase flow, multiphase mass transfer, electrochemical reactions, proton / electron conduction, and heat transfer. Many key reactions occur within micron- to nanometer-sized porous media. Traditional experimental methods, limited by spatial resolution, struggle to achieve direct, real-time, and precise observation of microscopic physical quantities such as local reaction rates, gas phase volume fraction, and current density distribution within the electrolytic cell. Therefore, multiphysics simulation techniques based on numerical computation have become indispensable for elucidating internal hydrothermal management mechanisms and guiding the optimization of bipolar plate flow field structures and the design of operating boundary conditions.

[0004] Traditional high-precision full 3D multiphysics coupled models require extremely high-density computational grids to accurately analyze the microstructure of porous media layers and the complex mass transfer phenomena within the flow channels. However, with the commercialization and large-scale development of PEMEC technology, the effective activation area of ​​commercial single electrolytic cells is constantly increasing, typically reaching hundreds or even thousands of square centimeters. At full-scale, existing meshing strategies lead to an exponential increase in the system's degrees of freedom, and the computational cost, memory consumption, and solution time often exceed the carrying capacity limits of conventional computing clusters, making full-scale PEMEC 3D high-precision simulation impractical for real-world engineering research and development.

[0005] Based on the above analysis, the problems and defects of the existing technology are as follows: the existing technology has low simulation efficiency, cannot realize the simulation of the real physical process of full-size electrolytic cells, and cannot provide a reliable theoretical basis for the flow field design and hydrothermal management of high-power electrolytic cells. Summary of the Invention

[0006] To overcome the problems existing in related technologies, the present invention discloses a method and system for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer, specifically involving a method for establishing a full-size local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer, and particularly involving a modeling method for a full-size local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer. The purpose of this invention is to simplify the membrane electrode assembly (MEA) in one dimension by solving other components using a three-dimensional computational domain, discretizing the nodes and solving them using one-dimensional flux equations, except for the membrane electrode assembly itself. The mass conservation, momentum conservation, component conservation, energy conservation, gas pressure, gas saturation, liquid pressure, liquid water saturation, and electron potential conservation equations within the bipolar plates, flow channels, and porous transport layer of the electrolyzer are solved in the three-dimensional computational domain; the flux conservation equations related to the catalyst layer and proton exchange membrane, such as electrochemical reactions, proton conservation, electron conservation, gas pressure, liquid pressure, and energy conservation, are solved in the one-dimensional computational domain. The solution results of the three-dimensional computational domain are used as the boundary conditions of the one-dimensional computational domain, and the solution results of the one-dimensional computational domain become the source terms of the three-dimensional computational domain. This data interaction process occurs once in each iteration.

[0007] The technical solution is as follows: A method for establishing a local dimension reduction simulation model of a proton exchange membrane electrolyzer includes the following steps:

[0008] S1. Construct a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer consisting of a three-dimensional computational domain and a one-dimensional computational domain. The three-dimensional computational domain includes bipolar plates, flow channels, porous transport layers, and extension layers in the anode and cathode. The extension layers serve as data storage layers in the one-dimensional computational domain and are used to connect the anode and cathode. The catalyst layer and proton exchange membrane are simplified into a one-dimensional computational domain, which consists of internal surface nodes belonging to the anode and cathode respectively.

[0009] S2, solve the multiphysics field in the three-dimensional computational domain by nonlinear partial differential equations and obtain scalar values ​​that provide boundary conditions for the one-dimensional computational domain; based on the scalar values, solve the multiphysics field in the one-dimensional computational domain by differential flux equations after node discretization, and return the solution results to the three-dimensional computational domain in the form of source terms to perform iterative updates of the multiphysics field in the three-dimensional computational domain. Repeat the above steps until the computational domain is numerically stable, and set different boundary conditions for the computational domain to complete the multiphysics field computational simulation and performance calculation.

[0010] S3, through simulation comparison of single proton exchange membrane electrolyzers under different operating conditions and structures, optimizes rated operating conditions and structural design, and manufactures proton exchange membrane electrolyzer products.

[0011] In step S2, the multiphysics field in the three-dimensional computational domain is solved by nonlinear partial differential equations, and scalar values ​​that provide boundary conditions for the one-dimensional computational domain are obtained. These include: the fluid mass equation, fluid momentum equation, and fluid energy equation are solved for all fluid regions in the three-dimensional computational domain; the electronic potential equations of the porous transport layer and the extended layer are solved in the porous transport layer and the extended layer; the gas pressure equations of the anode porous transport layer and the extended layer are solved in the anode porous transport layer and the anode extended layer; the gas saturation equation of the anode channel is solved in the anode channel; the component equations of the cathode channel porous transport layer and the extended layer are solved in the cathode channel, the cathode porous transport layer, and the cathode extended layer; the liquid pressure conservation equation of the cathode porous transport layer and the cathode extended layer is solved in the cathode porous transport layer and the cathode extended layer; and the liquid saturation conservation equation of the cathode channel is solved in the cathode channel.

[0012] Furthermore, the fluid mass equation is:

[0013] (1)

[0014] Fluid momentum equation:

[0015] (2)

[0016] Fluid energy equation:

[0017] (3)

[0018] In the formula, Density is expressed in units of 1. ; Represents apparent velocity, in units of ; Porosity represents the porosity of porous media. Represents volume fraction. Indicates pressure, unit is ; Represents dynamic viscosity, in units of ; Specific heat capacity, unit: ; Indicates effective thermal conductivity, in units of ; Temperature is expressed in units of . ; Let each represent a source term in the above equation. The unit is , The unit is , The unit is Subscript These represent gas mixtures and liquid water, respectively.

[0019] Furthermore, the electronic potential equations for the porous transport layer and the extended layer are as follows:

[0020] (4)

[0021] The gas pressure equations for the anode porous transport layer and the extended layer are as follows:

[0022] (5)

[0023] Anode channel gas saturation equation:

[0024] (6)

[0025] The liquid pressure conservation equations for the porous transport layer and the extended layer of the cathode are as follows:

[0026] (7)

[0027] Cathode channel liquid saturation conservation equation:

[0028] (8)

[0029] Cathode flow channel, porous transport layer, and spread layer composition equations:

[0030] (9)

[0031] In the formula, Expresses electronic conductivity, in units of ; Represents electron potential, unit: ; Density is expressed in units of 1. ; Indicates relative penetration rate; Intrinsic permeability, in units of ; Represents dynamic viscosity, in units of ; Indicates pressure, unit is ; Represents apparent velocity, in units of ; Represents volume fraction. Indicates mass fraction. Represents the effective diffusion coefficient of a component, in units of 1000 m / s. ; Let each represent a source term in the above equation. The unit is , The unit is , The unit is Subscript They represent gas mixtures and liquid water, respectively; subscripts Indicates gaseous components.

[0032] In step S2, the multiphysics transmission is solved in the one-dimensional computational domain by using the differential flux equations after node discretization. The physical parameters and source term solution results required for the three-dimensional computational domain are obtained as follows: For the one-dimensional computational domain, the nonlinear partial differential equations are discretized into differential flux equations between nodes of each real component. The boundary conditions are provided by the three-dimensional computational domain, and the relevant fluxes are returned to the three-dimensional computational domain in the form of source terms. The ion potential equations, electron potential equations, and energy equations of the two-sided extended layer nodes are solved at the two-sided extended layer nodes. The gas pressure equation of the anode extended layer node is solved at the anode extended layer node. The component equations and liquid pressure equations of the cathode extended layer node are solved at the cathode extended layer node.

[0033] Furthermore, the general differential flux equation is:

[0034] (10)

[0035] In the formula, This represents the multiphysics problem to be solved. express The diffusion coefficient in the corresponding component, express The source item in the corresponding component, Indicates component thickness, subscript The values ​​0 and 1 represent the two adjacent layers of components for each computing node;

[0036] After derivation, the values ​​of each node and the source terms of the returned three-dimensional computational domain are represented as follows:

[0037] (11)

[0038] In the formula, subscripts These represent three consecutive nodes in a one-dimensional computational domain, starting from the node closest to the three-dimensional computational domain. The subscript XL indicates... and Intermediate components, subscript YL indicates and Interstitial components, with the superscript 3D indicating a three-dimensional computational domain;

[0039] Equations for the ion potentials at the nodes of the extended layers on both sides:

[0040] (12)

[0041] Electron potential equations for the nodes of the extended layers on both sides:

[0042] (13)

[0043] Energy equations for nodes in both extended layers:

[0044] (14)

[0045] Anode extension layer node gas pressure equation:

[0046] (15)

[0047] Cathode extended layer node composition equations:

[0048] (16)

[0049] Cathode extension layer node liquid pressure equation:

[0050] (17)

[0051] In the formula, Electric potential is expressed in units of 1. ; Indicates electrical conductivity, in units of ; This indicates the operating voltage, measured in volts (V). This represents reversible voltage, measured in V. Temperature is expressed in Kelvin (K). Indicates effective thermal conductivity, in units of ; This indicates pressure, expressed in Pa. This represents the diffusion coefficient in the pressure equation, expressed in seconds (s). Indicates molar concentration, in units of ; Density is expressed in units of 1. ; Indicates mass fraction. Describes molar mass, with units of 1. ; Represents the effective diffusion coefficient of a component, in units of 1000 m / s. ; This indicates the thickness of the component, in meters (m). Let each represent a source term in the equation. The unit is , The unit is Subscript These respectively represent the porous anode transport layer, the anode catalyst layer, the proton exchange membrane, the cathode catalyst layer, the porous cathode transport layer, the anode extension layer, and the cathode extension layer, indicated by subscripts. They represent ions and electrons, respectively, and are subscripts. They represent gas mixtures and liquids, respectively, and are indicated by subscripts. Indicates gaseous components.

[0052] In step S2, the relevant parameters follow the following equation:

[0053] Anode-cathode electrochemical reaction rate and Calculated using the Butler-Volmer equation:

[0054] (18)

[0055] Thermodynamic reversible voltage Determined from the Nernst equation, it can be expressed as:

[0056] (19)

[0057] in, Indicates the liquid volume fraction. These represent the anode and cathode exchange current densities, respectively, in units of... ; These represent the charge transfer coefficients of the anode and cathode, respectively. These represent the activation overpotentials of the anode and cathode catalyst layers, respectively, in V. Calculated; This represents the universal gas constant, with a value of [value missing]. ; Denotes the Faraday constant, with a value of ; Temperature is expressed in Kelvin (K). These represent the partial pressure of oxygen in the anode catalyst layer and the partial pressure of hydrogen in the cathode catalyst layer, respectively, in Pa. Thus, the electrochemical reaction rate, reversible voltage, and operating voltage of the one-dimensional node can be calculated.

[0058] In step S2, setting the corresponding boundary conditions includes:

[0059] Inlet boundary conditions: At the boundary of the anode inlet, the water velocity is set to a constant value. Under different flow conditions, the water velocity will vary with the mass flow rate. The cathode inlet is a dead end and no inlet is set.

[0060] Export boundary conditions: Pressure export boundary conditions are used for both anode and cathode.

[0061] Temperature boundary conditions: The temperature of all walls in the computational domain that are connected to the outside is set to the operating temperature;

[0062] Electric potential boundary conditions: For the boundary conditions of the electron potential, the current density flux at the anode PTL and BP contact surface under different operating conditions is given. The cathode PTL and BP contact surface are given a reference potential. ;

[0063] Pressure and saturation boundary conditions: The gas pressure distribution between the anode PTL and the flow channel is regarded as the boundary condition for solving the gas pressure equation in the porous medium, and the hydraulic pressure distribution between the cathode PTL and the flow channel is regarded as the boundary condition for solving the hydraulic pressure equation in the porous medium; the Leverett-J function is used to describe the saturation of liquid water and the capillary pressure distribution in the porous material.

[0064] Furthermore, proton exchange membrane electrolyzer products were manufactured using a method for establishing a local dimension reduction simulation model of the proton exchange membrane electrolyzer.

[0065] Another objective of this invention is to provide a system for establishing a localized dimensionality reduction simulation model of a proton exchange membrane electrolyzer. This system implements the method for establishing the localized dimensionality reduction simulation model of the proton exchange membrane electrolyzer. The system includes:

[0066] The module for constructing a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer is used to build a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer consisting of a three-dimensional computational domain and a one-dimensional computational domain. The three-dimensional computational domain includes bipolar plates, flow channels, porous transport layers, and extension layers in the anode and cathode. The extension layers serve as data storage layers in the one-dimensional computational domain and are used to connect the anode and cathode. The catalyst layer and proton exchange membrane are simplified into a one-dimensional computational domain, which is composed of internal surface nodes belonging to the anode and cathode respectively.

[0067] The computational module of the local dimensionality reduction simulation model of the proton exchange membrane electrolyzer is used to solve the multiphysics field in the three-dimensional computational domain through nonlinear partial differential equations and obtain scalar values ​​that provide boundary conditions for the one-dimensional computational domain. Based on the scalar values, the multiphysics field is solved in the one-dimensional computational domain through the differential flux equation after node discretization, and the solution results are returned to the three-dimensional computational domain in the form of source terms. The multiphysics field in the three-dimensional computational domain is iteratively updated. The steps are repeated until the numerical value of the computational domain is stable. Different boundary conditions of the computational domain are set to complete the multiphysics field computational simulation and performance calculation.

[0068] The proton exchange membrane electrolyzer manufacturing module is used to obtain the performance curves of the proton exchange membrane electrolyzer based on the calculation module, to simulate and compare single electrolyzers under different operating conditions and structures, to optimize the rated operating conditions and structural design, and to manufacture proton exchange membrane electrolyzer products.

[0069] Combining all the above technical solutions, the beneficial effects of this invention are as follows:

[0070] First, to address the issue of excessive computational resource consumption in full-size 3D models, this invention performs local dimensionality reduction on the membrane electrode assembly (MEA) of a single electrolytic cell: the extremely thin MEA assembly is simplified to one dimension, discretized into nodes, and multiphysics transmission perpendicular to the membrane direction is solved using flux-conserving difference equations; while the bipolar plates, flow channels, porous transport layer, and connecting extension layer constitute the 3D computational domain, solved using partial differential equations. The 3D computational domain provides boundary conditions for the 1D computational domain, and the calculation results from the 1D computational domain are returned to the 3D computational domain as source terms via the extension layer for iterative updates. This invention, while ensuring high-precision simulation of realistic physical processes, significantly reduces the number of meshes and computation time, breaking through the area limitations of traditional models and achieving an activation area exceeding 300 cm². 2 The high-precision simulation of full-size electrolytic cells provides an efficient and reliable solution for the flow field design and hydrothermal management of high-power electrolytic cells.

[0071] Secondly, this invention significantly reduces the number of 3D meshes in the full-size model through a local dimensionality reduction algorithm, avoiding the cumbersome numerical calculation process of traditional models. This allows enterprises to greatly reduce the consumption of hardware and software resources and simulation time costs during simulation, thereby significantly reducing R&D trial-and-error costs and hardware investment. With the commercialization and scaling up of PEMEC technology, the activation area of ​​commercial single electrolytic cells has reached hundreds or even thousands of square centimeters. This invention can achieve an activation area exceeding 300 cm². 2 The high-precision simulation of a full-scale electrolyzer provides an efficient and reliable solution for the flow field design (such as the channel-to-ridge ratio and flow field characteristic structure), thermal management, and overall performance evaluation of industrial-grade high-power electrolyzers, possessing extremely high engineering application value. Hydrogen energy is an ideal pathway for large-scale, long-term energy storage. This invention can effectively guide the exploration and structural optimization of the internal hydrothermal management mechanism of PEMEC, helping to improve the efficiency and reliability of hydrogen production through water electrolysis, thereby promoting the commercialization of renewable energy hydrogen production technology.

[0072] Third, in existing technologies, limited by computing resources, traditional simulation models are typically only applicable to small-area single cells. This invention overcomes the area limitation of traditional models, enabling simulations to be applied to activation areas exceeding 300 cm². 2 Large-scale PEMECs now enable full-size, high-precision three-dimensional macroscopic state simulation. This invention proposes to simplify the extremely thin membrane electrode assembly into one dimension and solve it using a one-dimensional flux equation, while other components retain the three-dimensional computational domain for solution. By providing boundary conditions through the three-dimensional domain and returning source terms from the one-dimensional domain for iterative updates, data interaction is ensured. This novel local dimensionality reduction algorithm achieves model dimensionality reduction while maintaining high-precision simulation of real physical processes.

[0073] Fourth, PEMEC involves highly coupled multiphysics fields, and key reactions often occur within micron- or even nanometer-scale porous media. Traditional experimental methods, limited by spatial resolution, struggle to directly, in real-time, and accurately observe internal physical quantities. This model fully considers multiple core processes, including water consumption, hydrogen generation, heat transfer, and electrochemical reaction kinetics, successfully achieving accurate simulation of real-world operating conditions. Meanwhile, the industry has long desired to analyze complex mass transfer phenomena using fully three-dimensional, high-precision multiphysics coupled models. However, this leads to an exponential increase in system degrees of freedom, with memory consumption and solution time often exceeding the limits of conventional computing clusters. This invention successfully solves this long-standing technical challenge hindering the practical application of full-scale PEMEC simulation in engineering.

[0074] Fifth, traditional high-precision simulation techniques generally believe that in order to accurately analyze the microstructure of porous media layers and complex gas-liquid two-phase flow and multiphase mass transfer phenomena inside the channels, extremely high-density three-dimensional computational grids must be used in all components. This invention breaks with this conventional wisdom. Utilizing the physical characteristics of the membrane electrode as an extremely thin sheet with low permeability, it only considers the transmission of multiphysics fields in the direction perpendicular to the membrane electrode. Simultaneously, this invention overcomes the bias that simplified models lead to decreased accuracy. By discretizing the membrane electrode into nodes and using a flux conservation difference equation that follows the principle that inflow nodes equal outflow nodes, a one-dimensional model can still accurately solve complex transport phenomena such as electrochemical reactions and electroosmotic drag. This demonstrates that under specific physical conditions (such as extremely thin-film electrodes), dimensionality reduction not only does not sacrifice key accuracy but can also greatly improve computational efficiency. Attached Figure Description

[0075] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the disclosure of this invention and, together with the description, serve to explain the principles of this disclosure;

[0076] Figure 1 This is a flowchart of the method for establishing a local dimension reduction simulation model of a proton exchange membrane electrolyzer provided in an embodiment of the present invention;

[0077] Figure 2 This is a schematic diagram of the principle of the local dimension reduction simulation model of the proton exchange membrane electrolyzer (full-size local dimension reduction simulation model of the proton exchange membrane electrolyzer) provided in the embodiment of the present invention;

[0078] Figure 3 The activation area provided in this embodiment of the invention is 535 cm². 2 Schematic diagram of the computational domain for a single electrolytic cell;

[0079] Figure 4 A schematic diagram of the boundary conditions for a local dimension reduction simulation model of a proton exchange membrane electrolyzer provided in an embodiment of the present invention;

[0080] Figure 5 This is a schematic diagram of polarization curves under different outlet back pressures provided in an embodiment of the present invention;

[0081] Figure 6 The current density distribution diagram provided for the embodiments of the present invention;

[0082] Figure 7 This is a diagram showing the oxygen volume fraction distribution of the anode catalyst layer provided in an embodiment of the present invention.

[0083] Figure 8 A hydrogen molar concentration distribution diagram of the cathode catalyst layer provided in an embodiment of the present invention;

[0084] Figure 9 A membrane temperature distribution diagram provided for an embodiment of the present invention;

[0085] Figure 10 This is a comparison chart of simulation and experimental polarization curves under different outlet back pressures provided in the embodiments of the present invention. Detailed Implementation

[0086] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0087] Example 1, such as Figure 1 As shown. The method for establishing a local dimension reduction simulation model of a proton exchange membrane electrolyzer provided in this embodiment of the invention includes:

[0088] S1, construct a locally reduced-dimensional simulation model of a proton exchange membrane electrolyzer (PEMEC single electrolyzer) consisting of a three-dimensional computational domain and a one-dimensional computational domain, such as Figure 2 As shown, the three-dimensional computational domain includes bipolar plates, flow channels, porous transport layers, and extended layers in the anode and cathode. The extended layers serve as data storage layers for the one-dimensional computational domain, connecting the anode and cathode. The catalytic layer and proton exchange membrane are simplified into a one-dimensional computational domain, composed of internal surface nodes belonging to the anode and cathode. Figure 3 The activated area is 535 cm². 2 Single electrolytic cell computational domain.

[0089] S2, solve the multiphysics field in the three-dimensional computational domain by nonlinear partial differential equations and obtain scalar values ​​that provide boundary conditions for the one-dimensional computational domain; based on the scalar values, solve the multiphysics field in the one-dimensional computational domain by differential flux equations after node discretization, and return the solution results to the three-dimensional computational domain in the form of source terms to perform iterative updates of the multiphysics field in the three-dimensional computational domain. Repeat the steps until the computational domain is numerically stable, and set different boundary conditions for the computational domain to complete the multiphysics field computational simulation and performance calculation.

[0090] S3, through simulation comparison of single proton exchange membrane electrolyzers under different operating conditions and structures, optimizes rated operating conditions and structural design, and manufactures proton exchange membrane electrolyzer products.

[0091] For example, in step S2, solving the multiphysics field in the three-dimensional computational domain using nonlinear partial differential equations and obtaining scalar values ​​that provide boundary conditions for the one-dimensional computational domain includes:

[0092] The fluid mass equation, fluid momentum equation, and fluid energy equation are solved for all fluid regions in the three-dimensional computational domain. The electronic potential equations for the porous transport layer and the extended layer are solved for the porous transport layer and the extended layer. The gas pressure equations for the anode porous transport layer and the extended layer are solved for the anode porous transport layer and the anode extended layer. The gas saturation equation for the anode channel is solved for the anode channel. The component equations for the cathode channel porous transport layer and the extended layer are solved for the cathode channel, the cathode porous transport layer, and the cathode extended layer. The liquid pressure conservation equation for the cathode porous transport layer and the cathode extended layer is solved for the cathode porous transport layer and the cathode extended layer. The liquid saturation conservation equation for the cathode channel is solved for the cathode channel.

[0093] Specifically, the fluid mass equation is:

[0094] (1)

[0095] Fluid momentum equation:

[0096] (2)

[0097] Fluid energy equation:

[0098] (3)

[0099] In the formula, Density is expressed in units of 1. ; Represents apparent velocity, in units of ; Porosity represents the porosity of porous media. Represents volume fraction. Indicates pressure, unit is ; Represents dynamic viscosity, in units of ; Specific heat capacity, unit: ; Indicates effective thermal conductivity, in units of ; Temperature is expressed in units of . ; Let each represent a source term in the above equation. The unit is , The unit is , The unit is Subscript These represent gas mixtures and liquid water, respectively.

[0100] Electron potential equations for porous transport layer and extended layer:

[0101] (4)

[0102] The gas pressure equations for the anode porous transport layer and the extended layer are as follows:

[0103] (5)

[0104] Anode channel gas saturation equation:

[0105] (6)

[0106] The liquid pressure conservation equations for the porous transport layer and the extended layer of the cathode are as follows:

[0107] (7)

[0108] Cathode channel liquid saturation conservation equation:

[0109] (8)

[0110] Cathode flow channel, porous transport layer, and spread layer composition equations:

[0111] (9)

[0112] In the formula, Expresses electronic conductivity, in units of ; Represents electron potential, unit: ; Density is expressed in units of 1. ; Indicates relative penetration rate; Intrinsic permeability, in units of ; Represents dynamic viscosity, in units of ; Indicates pressure, unit is ; Represents apparent velocity, in units of ; Represents volume fraction. Indicates mass fraction. Represents the effective diffusion coefficient of a component, in units of 1000 m / s. ; Let each represent a source term in the above equation. The unit is , The unit is , The unit is Subscript They represent gas mixtures and liquid water, respectively; subscripts Indicates gaseous components.

[0113] As can be seen, the above conservation equations are partial differential equations, which are solved using the finite volume method. First, the conservation equations are discretized using the finite volume method, dividing the entire computational domain into several control volumes (grid cells), and the corresponding conservation equations are solved within each control volume. During the solution process, the partial differential equations within the grid cells need to be transformed into linear algebraic equations, and then an iterative method is used to solve them step by step. Each iteration updates the variables in the conservation equations, such as flow velocity, pressure, temperature, and concentration, until the convergence criterion is met.

[0114] For example, in step S2, the solution of multiphysics transmission in the one-dimensional computational domain through the differential flux equation after node discretization, and the acquisition of the physical parameters required for the three-dimensional computational domain and the solution results of the source terms include:

[0115] For the one-dimensional computational domain, the nonlinear partial differential equations are discretized into differential flux equations between the nodes of each real component. Boundary conditions are provided by the three-dimensional computational domain, and relevant multiphysics fields are returned to the three-dimensional computational domain as source terms. The ion potential equations, electron potential equations, and energy equations of the two-sided extended layer nodes are solved at the two-sided extended layer nodes. The gas pressure equation of the anode extended layer node is solved at the anode extended layer node. The composition equations and liquid pressure equations of the cathode extended layer node are solved at the cathode extended layer node.

[0116] An exemplary general differential flux equation:

[0117] (10)

[0118] In the formula, This represents the multiphysics problem to be solved. express The diffusion coefficient in the corresponding component, express The source item in the corresponding component, Indicates component thickness, subscript The values ​​0 and 1 represent the two adjacent layers of components for each computing node;

[0119] After derivation, the values ​​of each node and the source terms of the returned three-dimensional computational domain are represented as follows:

[0120] (11)

[0121] In the formula, subscripts These represent three consecutive nodes in a one-dimensional computational domain, starting from the node closest to the three-dimensional computational domain. The subscript XL indicates... and Intermediate components, subscript YL indicates and Interstitial components, with the superscript 3D indicating a three-dimensional computational domain;

[0122] Equations for the ion potentials at the nodes of the extended layers on both sides:

[0123] (12)

[0124] Electron potential equations for the nodes of the extended layers on both sides:

[0125] (13)

[0126] Energy equations for nodes in both extended layers:

[0127] (14)

[0128] Anode extension layer node gas pressure equation:

[0129] (15)

[0130] Cathode extended layer node composition equations:

[0131] (16)

[0132] Cathode extension layer node liquid pressure equation:

[0133] (17)

[0134] In the formula, Electric potential is expressed in units of 1. ; Indicates electrical conductivity, in units of ; This indicates the operating voltage, measured in volts (V). This represents reversible voltage, measured in V. Temperature is expressed in Kelvin (K). Indicates effective thermal conductivity, in units of ; This indicates pressure, expressed in Pa. This represents the diffusion coefficient in the pressure equation, expressed in seconds (s). Indicates molar concentration, in units of ; Density is expressed in units of 1. ; Indicates mass fraction. Describes molar mass, with units of 1. ; Represents the effective diffusion coefficient of a component, in units of 1000 m / s. ; This indicates the thickness of the component, in meters (m). Let each represent a source term in the equation. The unit is , The unit is Subscript These respectively represent the porous anode transport layer, the anode catalyst layer, the proton exchange membrane, the cathode catalyst layer, the porous cathode transport layer, the anode extension layer, and the cathode extension layer, indicated by subscripts. They represent ions and electrons, respectively, and are subscripts. They represent gas mixtures and liquids, respectively, and are indicated by subscripts. Indicates gaseous components.

[0135] It can be seen that in the one-dimensional computational domain, the conservation equations for components, energy, gas pressure, hydraulic pressure, and electronic potential solved in the three-dimensional computational domain are transformed into flux equations for one-dimensional nodes. Additionally, equations related to the catalyst layer and proton exchange membrane, such as electrochemical reactions and ionic potentials, are also described as flux equations. In the flux equations, only diffusion effects along the thickness direction are considered. The flux equations in the one-dimensional computational domain are also solved step-by-step in each iteration using an iterative method. During computation, the scalar values ​​solved in the three-dimensional computational domain provide boundary conditions for the one-dimensional computational domain. Simultaneously, the solutions from the one-dimensional computational domain provide the necessary physical parameters and source terms for the three-dimensional computational domain. Each iteration process facilitates data exchange between the two computational domains.

[0136] For example, in step S2, the relevant parameters follow the following equation:

[0137] Anode-cathode electrochemical reaction rate and Calculated using the Butler-Volmer equation:

[0138] (18)

[0139] Thermodynamic reversible voltage Determined from the Nernst equation, it can be expressed as:

[0140] (19)

[0141] in, Indicates the liquid volume fraction. These represent the anode and cathode exchange current densities, respectively, in units of... ; These represent the charge transfer coefficients of the anode and cathode, respectively. These represent the activation overpotentials of the anode and cathode catalyst layers, respectively, in V. Calculated; This represents the universal gas constant, with values ​​ranging from 1 to 10. ; Denotes the Faraday constant, with a value of ; Temperature is expressed in Kelvin (K). These represent the partial pressure of oxygen in the anode catalyst layer and the partial pressure of hydrogen in the cathode catalyst layer, respectively, in Pa. Thus, the electrochemical reaction rate, reversible voltage, and operating voltage of the one-dimensional node can be calculated.

[0142] For example, Figure 4 This is a schematic diagram of the boundary conditions for a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer provided in an embodiment of the present invention. In step S2, setting the corresponding boundary conditions includes:

[0143] Inlet boundary conditions: In actual operation, deionized water is supplied to the reaction water by a digital peristaltic pump, and the water supply is usually controlled according to the flow rate. Therefore, at the boundary of the anode inlet, the water velocity is set to a constant value. Under different flow conditions, the water velocity will vary with the mass flow rate; in this example, it is 2.182 L min⁻¹. The cathode inlet is a dead end and no inlet is provided.

[0144] Export boundary conditions: Both anode and cathode use pressure export boundary conditions. In this example, these are 1 / 10 / 20 / 30 bar.

[0145] Temperature boundary conditions: The temperature of all walls in the computational domain that are connected to the outside is set to the operating temperature. In this example, it is 293.15 K.

[0146] Electric potential boundary conditions: For the boundary conditions of the electron potential, the current density flux at the anode PTL and BP contact surface under different operating conditions is given. The cathode PTL and BP contact surface are given a reference potential. ;

[0147] Pressure and Saturation Boundary Conditions: The gas pressure distribution between the anode PTL and the flow channel is considered as the boundary condition for solving the gas pressure equation in the porous medium (i.e., PTL and CL), while the hydraulic pressure distribution between the cathode PTL and the flow channel is considered as the boundary condition for solving the hydraulic equation in the porous medium (i.e., PTL and CL). Since the Leverett-J function is used to describe the saturation of liquid water and the capillary pressure distribution in the porous material, the coverage area of ​​the detailed two-phase flow in the flow channel on the PTL surface can be transformed into boundary conditions for the gas pressure and hydraulic equations. This helps to relate the two-phase flow in the flow channel to the gas-liquid distribution in the porous material.

[0148] As can be seen from the above embodiments, the present invention performs dimensionality reduction processing on the membrane electrode part of the three-dimensional model of the proton exchange membrane electrolyzer PEMEC single electrolyzer, making it into a three-dimensional computational domain composed of two bipolar plates, flow channels, porous transport layers, and extension layers, and a one-dimensional computational domain after the membrane electrode dimensionality reduction. The extension layers of the anode and cathode serve to connect the anode and cathode of the three-dimensional computational domain, and at the same time store the computational data of the internal nodes between the anode and cathode components in the one-dimensional computational domain.

[0149] In the three-dimensional computational domain, nonlinear partial differential equations are used to solve for mass conservation, momentum conservation, composition conservation, energy conservation, electron conservation, pressure conservation, and saturation conservation, simulating multi-physics transport phenomena such as two-phase flow, phase transition, and electron transport. In the one-dimensional computational domain, difference equations after node discretization are used to solve for mass conservation, composition conservation, energy conservation, ion conservation, electron conservation, and pressure conservation, simulating multi-physics transport phenomena such as electrochemical reactions, electroosmotic drag, and capillary pressure continuity. During simulation, the scalar values ​​solved in the three-dimensional computational domain provide boundary conditions for the one-dimensional computational domain, and the results of the one-dimensional computational domain are returned to the three-dimensional computational domain as source terms through an extension layer for iterative updates.

[0150] In summary, this invention proposes a local dimensionality reduction algorithm and, based on this, establishes a local dimensionality reduction simulation model applicable to full-size proton exchange membrane electrolyzers. In this model, since the membrane electrode (composed of the membrane and two catalytic layers and microporous layers on both sides) in a PEMEC single electrolyzer structure typically behaves as an extremely thin sheet with low permeability, it is simplified to one dimension, considering only the transmission of multiphysics fields perpendicular to the membrane. Simultaneously, the membrane electrode is divided into nodes along the perpendicular direction, and the partial differential equations used for multiphysics transmission are discretized into difference equations following the principle that the inflow node equals the outflow node. This significantly reduces the number of grids and improves the computational speed of multiphysics transmission within the membrane electrode, enabling multiphysics simulation of full-size PEMEC single electrolyzers.

[0151] The full-size, locally reduced-dimensional simulation model for proton exchange membrane electrolyzers (PEMECs) proposed in this invention fully considers core processes occurring within the PEMEC, including water consumption, hydrogen generation, heat transfer, electrochemical reaction kinetics, and water-gas conversion in the gas-liquid two-phase interaction. This ensures accurate simulation of the actual working state of the electrolyzer and guarantees the accuracy of the simulation results. This invention performs local dimensionality reduction on the MEA and discretizes it using flux conservation difference equations, avoiding redundant numerical calculations and thus greatly improving the model's computational efficiency while significantly reducing hardware and software resource consumption and simulation time costs. Based on this perfect combination of high precision and high efficiency, this invention breaks through the limitation of traditional simulation models that are only applicable to small-area single cells. The model possesses powerful large-scale spatial solution capabilities, enabling full-size, high-precision three-dimensional macroscopic state simulation of full-size PEMECs with an activated area exceeding 300 cm², providing an efficient and reliable solution for flow field design, thermal management, and performance evaluation of industrial-grade high-power electrolyzers.

[0152] Example 2: The system for establishing a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer provided in this embodiment of the invention includes:

[0153] The module for constructing a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer is used to build a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer (PEMEC single electrolyzer) consisting of a three-dimensional computational domain and a one-dimensional computational domain. The three-dimensional computational domain includes bipolar plates, flow channels, porous transport layers, and extension layers in the anode and cathode. The extension layers serve as data storage layers in the one-dimensional computational domain and connect the anode and cathode. The catalyst layer and proton exchange membrane are simplified into a one-dimensional computational domain, which consists of internal surface nodes belonging to the anode and cathode respectively.

[0154] The computational module of the local dimensionality reduction simulation model of the proton exchange membrane electrolyzer is used to solve the multiphysics field in the three-dimensional computational domain through nonlinear partial differential equations and obtain scalar values ​​that provide boundary conditions for the one-dimensional computational domain. Based on the scalar values, the multiphysics field is solved in the one-dimensional computational domain through the differential flux equation after node discretization, and the solution results are returned to the three-dimensional computational domain in the form of source terms. The multiphysics field in the three-dimensional computational domain is iteratively updated. The steps are repeated until the numerical value of the computational domain is stable. Different boundary conditions of the computational domain are set to complete the multiphysics field computational simulation and performance calculation.

[0155] The proton exchange membrane electrolyzer manufacturing module is used to obtain the performance curve of the proton exchange membrane electrolyzer based on the calculation module, to simulate and compare single proton exchange membrane electrolyzers under different operating conditions and structures, to optimize the rated operating conditions and structural design, and to manufacture proton exchange membrane electrolyzer products.

[0156] Application Example: The method for establishing a localized dimensionality-reduced simulation model of a proton exchange membrane electrolyzer provided in this invention allows for performance evaluation and hydrothermal management analysis. By setting different operating conditions, polarization curves can be simulated, and operating voltages under different current densities can be compared to evaluate the performance of the proton exchange membrane electrolyzer. Furthermore, the hydrothermal management capabilities of the electrolyzer can be comprehensively evaluated by combining key multiphysics field distribution cloud maps. Based on this, by changing the structural parameters of the electrolyzer's flow field plate, the influence of parameters such as the channel ridge ratio, flow field aspect ratio, and flow field fineness on the electrolyzer's performance, mass transfer characteristics, and hydrothermal management can be obtained.

[0157] Specifically, by setting different operating conditions, polarization curves can be simulated, and the operating voltage under different current densities can be compared to evaluate the performance of the proton exchange membrane electrolyzer. Figure 5 The polarization curves under different outlet back pressures in this example are shown. The results indicate that as the outlet back pressure increases, the operating voltage gradually increases, and the performance of the electrolyzer deteriorates. Furthermore, the hydrothermal management capability of the electrolyzer can be comprehensively evaluated by combining the key multiphysics field distribution cloud map. Figure 6 For current density distribution, Figure 7 This represents the oxygen volume fraction distribution in the anode catalyst layer. Figure 8 The molar concentration distribution of hydrogen gas in the cathode catalyst layer. Figure 9 This relates to the membrane temperature distribution. Based on this, by changing the structural parameters of the flow field plate in the electrolyzer, the influence of parameters such as the channel ridge ratio, the cross-sectional area ratio of the flow field, and the fineness of the flow field on the performance, mass transfer characteristics, and hydrothermal management of the electrolyzer can be obtained.

[0158] To illustrate the computational efficiency of the local dimensionality reduction simulation model of the proton exchange membrane electrolyzer provided by this invention, the following experiments were conducted: The activation area was sequentially set to 5 cm². 2 The single-channel computational domain has an activation area of ​​40 cm². 2 The computational domain of the small-sized flow field plate has an activation area of ​​535 cm². 2 The full-size flow field plate computational domain was simulated using both the local dimensionality reduction simulation model of the proton exchange membrane electrolyzer provided in this invention and the traditional three-dimensional model of the proton exchange membrane electrolyzer. The calculations were performed using a high-performance computer equipped with a 3.0 GHz Intel® Xeon® Gold 6248 R CPU and 64 GB of memory. The computation time differences between the two models are compared in Table 1. Experimental results show that, under the same computational domain grid number and operating conditions, the single-channel example (5 cm) achieves better computational speed. 2 The local dimensionality reduction model completes the simulation in just 10 minutes, while the traditional 3D model takes six times longer. This applies to scaling up to a small flow field plate (40 cm). 2The traditional 3D model takes 12 hours to compute, while the locally reduced-dimensional model only takes 1 hour. Furthermore, the locally reduced-dimensional model is applicable to a full-size proton exchange membrane electrolyzer (535 cm²). 2 Simulations can still be achieved on a scale of [missing information - likely a specific scale], but due to the difficulty of discretizing the computational domain and limitations in computing power, the computer cannot perform traditional three-dimensional model simulation calculations on such a large activated area. Based on the comparison of the first two methods, it is predicted that this process will take longer. The comparison of three different examples shows that the local dimensionality reduction simulation model of the proton exchange membrane electrolyzer provided by this invention significantly improves computational efficiency and is fully capable of handling large-scale simulations.

[0159] Table 1 Comparison of computation time for different models

[0160]

[0161] To demonstrate the simulation accuracy of the localized dimensionality reduction simulation model of the proton exchange membrane electrolyzer provided by this invention, the following experiments were conducted: Simulations were performed using the localized dimensionality reduction simulation model of the proton exchange membrane electrolyzer provided by this invention under the conditions of an inlet water flow rate of 2.182 L min⁻¹, an operating temperature of 293.15 K, and outlet back pressures of 1 bar and 10 bar, respectively, and the simulation results were compared with experimental data. Figure 10 For the comparison of polarization curves, specific data are shown in Table 2. Experimental results show that, under the same model parameters, the local dimensionality reduction simulation model of the proton exchange membrane electrolyzer provided by this invention can calibrate experimental data under different operating conditions, with a maximum error of only -0.68%, demonstrating good simulation accuracy.

[0162] Table 2 Comparison of simulation and experimental polarization curves under different operating conditions

[0163]

[0164] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention and within the spirit and principles of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer, characterized in that, The method includes the following steps: S1. Construct a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer consisting of a three-dimensional computational domain and a one-dimensional computational domain. The three-dimensional computational domain includes bipolar plates, flow channels, porous transport layers, and extension layers in the anode and cathode. The extension layers serve as data storage layers in the one-dimensional computational domain and are used to connect the anode and cathode. The catalyst layer and proton exchange membrane are simplified into a one-dimensional computational domain, which consists of internal surface nodes belonging to the anode and cathode respectively. S2, solve the multiphysics field in the three-dimensional computational domain by nonlinear partial differential equations and obtain scalar values ​​that provide boundary conditions for the one-dimensional computational domain; based on the scalar values, solve the multiphysics field in the one-dimensional computational domain by differential flux equations after node discretization, and return the solution results to the three-dimensional computational domain in the form of source terms to perform iterative updates of the multiphysics field in the three-dimensional computational domain. Repeat the above steps until the computational domain is numerically stable, and set different boundary conditions for the computational domain to complete the multiphysics field computational simulation and performance calculation. S3, through simulation comparison of single proton exchange membrane electrolyzers under different operating conditions and structures, optimizes rated operating conditions and structural design, and manufactures proton exchange membrane electrolyzer products.

2. The method for establishing a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer according to claim 1, characterized in that, In step S2, the multiphysics field in the three-dimensional computational domain is solved by nonlinear partial differential equations, and scalar values ​​that provide boundary conditions for the one-dimensional computational domain are obtained. These include: the fluid mass equation, fluid momentum equation, and fluid energy equation are solved for all fluid regions in the three-dimensional computational domain; the electronic potential equations of the porous transport layer and the extended layer are solved in the porous transport layer and the extended layer; the gas pressure equations of the anode porous transport layer and the extended layer are solved in the anode porous transport layer and the anode extended layer; the gas saturation equation of the anode channel is solved in the anode channel; the component equations of the cathode channel porous transport layer and the extended layer are solved in the cathode channel, the cathode porous transport layer, and the cathode extended layer; the liquid pressure conservation equation of the cathode porous transport layer and the cathode extended layer is solved in the cathode porous transport layer and the cathode extended layer; and the liquid saturation conservation equation of the cathode channel is solved in the cathode channel.

3. The method for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer according to claim 2, characterized in that, The fluid mass equation is: （1） Fluid momentum equation: （2） Fluid energy equation: （3） In the formula, Density is expressed in units of 1. ; Represents apparent velocity, in units of ; Porosity represents the porosity of porous media. Represents volume fraction. Indicates pressure, unit is ; Represents dynamic viscosity, in units of ; Specific heat capacity, unit: ; Indicates effective thermal conductivity, in units of ; Temperature is expressed in units of . ; Let each represent a source term in the above equation. The unit is , The unit is , The unit is Subscript These represent gas mixtures and liquid water, respectively.

4. The method for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer according to claim 2, characterized in that, Electron potential equations for porous transport layer and extended layer: （4） The gas pressure equations for the anode porous transport layer and the extended layer are as follows: （5） Anode channel gas saturation equation: （6） The liquid pressure conservation equations for the porous transport layer and the extended layer of the cathode are as follows: （7） Cathode channel liquid saturation conservation equation: （8） Cathode flow channel, porous transport layer, and spread layer composition equations: （9） In the formula, Expresses electronic conductivity, in units of ; Represents electron potential, unit: ; Density is expressed in units of 1. ; Indicates relative penetration rate; Intrinsic permeability, in units of ; Represents dynamic viscosity, in units of ; Indicates pressure, unit is ; Represents apparent velocity, in units of ; Represents volume fraction. Indicates mass fraction. Represents the effective diffusion coefficient of a component, in units of 1000 m / s. ; Let each represent a source term in the above equation. The unit is , The unit is , The unit is Subscript They represent gas mixtures and liquid water, respectively; subscripts Indicates gaseous components.

5. The method for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer according to claim 1, characterized in that, In step S2, the multiphysics transmission is solved in the one-dimensional computational domain by using the differential flux equations after node discretization. The physical parameters and source term solution results required for the three-dimensional computational domain are obtained as follows: For the one-dimensional computational domain, the nonlinear partial differential equations are discretized into differential flux equations between nodes of each real component. The boundary conditions are provided by the three-dimensional computational domain, and the relevant fluxes are returned to the three-dimensional computational domain in the form of source terms. The ion potential equations, electron potential equations, and energy equations of the two-sided extended layer nodes are solved at the two-sided extended layer nodes. The gas pressure equation of the anode extended layer node is solved at the anode extended layer node. The component equations and liquid pressure equations of the cathode extended layer node are solved at the cathode extended layer node.

6. The method for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer according to claim 5, characterized in that, General differential flux equation: （10） In the formula, This represents the multiphysics problem to be solved. express The diffusion coefficient in the corresponding component, express The source item in the corresponding component, Indicates component thickness, subscript The values ​​0 and 1 represent the two adjacent layers of components for each computing node; After derivation, the values ​​of each node and the source terms of the returned three-dimensional computational domain are represented as follows: （11） In the formula, subscripts These represent three consecutive nodes in a one-dimensional computational domain, starting from the node closest to the three-dimensional computational domain. The subscript XL indicates... and Intermediate components, subscript YL indicates and Interstitial components, with the superscript 3D indicating a three-dimensional computational domain; Equations for the ion potentials at the nodes of the extended layers on both sides: （12） Electron potential equations for the nodes of the extended layers on both sides: （13） Energy equations for nodes in both extended layers: （14） Anode extension layer node gas pressure equation: （15） Cathode extended layer node composition equations: （16） Cathode extension layer node liquid pressure equation: （17） In the formula, Electric potential is expressed in units of 1. ; Indicates electrical conductivity, in units of ; This indicates the operating voltage, measured in volts (V). This represents reversible voltage, measured in V. Temperature is expressed in Kelvin (K). Indicates effective thermal conductivity, in units of ; This indicates pressure, expressed in Pa. This represents the diffusion coefficient in the pressure equation, expressed in seconds (s). Indicates molar concentration, in units of ; Density is expressed in units of 1. ; Indicates mass fraction. Describes molar mass, with units of 1. ; Represents the effective diffusion coefficient of a component, in units of 1000 m / s. ; This indicates the thickness of the component, in meters (m). Let each represent a source term in the equation. The unit is , The unit is Subscript These respectively represent the porous anode transport layer, the anode catalyst layer, the proton exchange membrane, the cathode catalyst layer, the porous cathode transport layer, the anode extension layer, and the cathode extension layer, indicated by subscripts. They represent ions and electrons, respectively, and are subscripts. They represent gas mixtures and liquids, respectively, and are indicated by subscripts. Indicates gaseous components.

7. The method for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer according to claim 1, characterized in that, In step S2, the relevant parameters follow the following equation: Anode-cathode electrochemical reaction rate and Calculated using the Butler-Volmer equation: （18） Thermodynamic reversible voltage Determined from the Nernst equation, it can be expressed as: （19） in, Indicates the liquid volume fraction. These represent the anode and cathode exchange current densities, respectively, in units of... ; These represent the charge transfer coefficients of the anode and cathode, respectively. These represent the activation overpotentials of the anode and cathode catalyst layers, respectively, in V. Calculated; This represents the universal gas constant, with values ​​ranging from 1 to 10. ; Denotes the Faraday constant, with a value of ; Temperature is expressed in Kelvin (K). These represent the partial pressure of oxygen in the anode catalyst layer and the partial pressure of hydrogen in the cathode catalyst layer, respectively, in Pa. Thus, the electrochemical reaction rate, reversible voltage, and operating voltage of the one-dimensional node can be calculated.

8. The method for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer according to claim 1, characterized in that, In step S2, setting the corresponding boundary conditions includes: Inlet boundary conditions: At the boundary of the anode inlet, the water velocity is set to a constant value. Under different flow conditions, the water velocity will vary with the mass flow rate. The cathode inlet is a dead end and no inlet is set. Export boundary conditions: Pressure export boundary conditions are used for both anode and cathode. Temperature boundary conditions: The temperature of all walls in the computational domain that are connected to the outside is set to the operating temperature; Electric potential boundary conditions: For the boundary conditions of the electron potential, the current density flux at the anode PTL and BP contact surface under different operating conditions is given. The cathode PTL and BP contact surface are given a reference potential. ; Pressure and saturation boundary conditions: The gas pressure distribution between the anode PTL and the flow channel is regarded as the boundary condition for solving the gas pressure equation in the porous medium, and the hydraulic pressure distribution between the cathode PTL and the flow channel is regarded as the boundary condition for solving the hydraulic pressure equation in the porous medium; the Leverett-J function is used to describe the saturation of liquid water and the capillary pressure distribution in the porous material.

9. The method for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer according to claim 1, characterized in that, A proton exchange membrane electrolyzer product was fabricated using a method for establishing a local dimension reduction simulation model of the proton exchange membrane electrolyzer.

10. A system for establishing a local dimensionality-reduced simulation model of a proton exchange membrane electrolyzer, characterized in that, This system implements the method for establishing a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer as described in any one of claims 1-9, and the system includes: The module for constructing a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer is used to build a local dimensionality reduction simulation model of a proton exchange membrane electrolyzer consisting of a three-dimensional computational domain and a one-dimensional computational domain. The three-dimensional computational domain includes bipolar plates, flow channels, porous transport layers, and extension layers in the anode and cathode. The extension layers serve as data storage layers in the one-dimensional computational domain and are used to connect the anode and cathode. The catalyst layer and proton exchange membrane are simplified into a one-dimensional computational domain, which is composed of internal surface nodes belonging to the anode and cathode respectively. The computational module of the local dimensionality reduction simulation model of the proton exchange membrane electrolyzer is used to solve the multiphysics field in the three-dimensional computational domain through nonlinear partial differential equations and obtain scalar values ​​that provide boundary conditions for the one-dimensional computational domain. Based on the scalar values, the multiphysics field is solved in the one-dimensional computational domain through the differential flux equation after node discretization, and the solution results are returned to the three-dimensional computational domain in the form of source terms. The multiphysics field in the three-dimensional computational domain is iteratively updated. The steps are repeated until the numerical value of the computational domain is stable. Different boundary conditions of the computational domain are set to complete the multiphysics field computational simulation and performance calculation. The proton exchange membrane electrolyzer manufacturing module is used to obtain the performance curve of the proton exchange membrane electrolyzer based on the calculation module, to simulate and compare single proton exchange membrane electrolyzers under different operating conditions and structures, to optimize the rated operating conditions and structural design, and to manufacture proton exchange membrane electrolyzer products.

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