Electrochemical simulation methods, equipment, storage media, and software products for lithium-air batteries

Abstract

This application discloses a lithium-air battery electrochemical simulation method, device, storage medium, and program product. This application relates to the field of battery simulation technology. The lithium-air battery electrochemical simulation method includes: obtaining the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity; solving a set of coupled equations based on the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity as model inputs, wherein the coupled equations are coupled according to the air layer, current collector layer, and cathode layer; mapping the solution results of the coupled equations to the battery geometric model corresponding to the model mesh to determine the battery rate performance. This achieves precise simulation of the battery's internal microstructure characteristics down to the battery electrode, improving the simulation efficiency of the influence of electrode microstructure on performance during cell design.

Description

Technical Field

[0001] This application relates to the field of battery simulation technology, and in particular to a lithium-air battery electrochemical simulation method, device, storage medium and program product. Background Technology

[0002] The relevant technologies mainly consider the diffusion process of lithium ions in the electrolyte, the diffusion process of lithium ions from the interior to the surface and from the surface to the interior of the active material, the potential distribution of the electrolyte, the potential distribution of the active material, the reaction process of lithium ion insertion and extraction, and the distribution state of the active material in two-dimensional space. The lithium ion exchange between solid and liquid is refined to the boundary conditions, and lithium ion exchange is set to occur at the solid-liquid interface, thereby simulating the performance of the battery under different conditions.

[0003] However, current simulation methods cannot accurately simulate the microstructure characteristics inside the battery electrodes, resulting in poor simulation results for lithium-air batteries. Summary of the Invention

[0004] The main purpose of this application is to provide a lithium-air battery electrochemical simulation method, device, storage medium and program product, which aims to solve the technical problem that current simulation methods cannot accurately simulate the microstructure characteristics inside the battery electrode, resulting in poor simulation effect of lithium-air batteries.

[0005] Firstly, this application provides an electrochemical simulation method for lithium-air batteries, the method comprising:

[0006] Obtain the positive electrode thickness, positive electrode tortuosity, positive electrode porosity, and current collector porosity;

[0007] The coupled equations are solved using the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity as model inputs. The coupled equations are coupled based on the air layer, current collector layer, and cathode layer.

[0008] The solution results of the coupled equations are mapped to the battery geometry model corresponding to the model mesh to determine the battery rate performance.

[0009] This application simulates the ion migration, electron conduction, and dissolved gas diffusion processes, as well as reaction kinetics, by inputting electrode structure parameters, including but not limited to porosity and tortuosity, and then processing them through a set of physicochemical coupling equations. Finally, it outputs the battery rate performance indicators under specific temperature and different rate conditions, thereby achieving precise simulation of battery simulation down to the internal microstructure characteristics of the battery electrode, improving the simulation accuracy of lithium-air batteries, and increasing the simulation efficiency of the impact of electrode microstructure on performance during cell design.

[0010] In some embodiments, the step of solving the coupled equations based on the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity as model inputs includes:

[0011] The coupled equations are discretized using the model mesh of the battery geometric model to obtain an algebraic equation system.

[0012] The algebraic equations are solved based on the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity to obtain a single-step solution set.

[0013] If the calculation cutoff condition is met, the single-step solution set is output as the solution result.

[0014] This application achieves battery simulation based on the fine structure of the electrode by discretizing and solving the coupled equations, and taking the battery structure parameters as the main input, thereby improving the simulation accuracy.

[0015] In some embodiments, the step of solving the system of algebraic equations based on the positive electrode thickness, the positive electrode tortuosity, the positive electrode porosity, and the current collector porosity to obtain a single-step solution set includes:

[0016] Substituting the air velocity into the first equation at the interface between the air layer and the current collector layer, and substituting the positive electrode porosity and the current collector porosity into the second equation at the interface between the current collector layer and the positive electrode layer, and using the positive electrode thickness, the positive electrode tortuosity, and the current collector thickness as boundary constraints, the single-step solution set is obtained.

[0017] By focusing on the coupling of the air layer, current collector layer, and cathode layer, this application enables a more targeted analysis of the impact of these key regions on battery performance.

[0018] In some embodiments, the battery geometric model includes an air layer, a current collector layer, a positive electrode layer, a separator layer, and a negative electrode layer. After substituting the positive electrode porosity and the current collector porosity into the second equation at the interface between the current collector layer and the positive electrode layer, the model further includes:

[0019] Substituting the porosity, the first interface reaction rate, and the electrolyte dissolved gas concentration into the third equation of the diffusion of matter between the positive electrode layer and the separator layer, and substituting the electrolyte dissolved gas concentration and the second interface reaction rate into the fourth equation of the interface between the separator layer and the negative electrode layer, and using the positive electrode thickness, the positive electrode tortuosity, the negative electrode thickness, the separator thickness, and the current collector thickness as boundary constraints, the single-step solution set is obtained.

[0020] This application introduces key parameters such as the reaction rate at the first interface, the reaction rate at the second interface, and the concentration of dissolved gases in the electrolyte, enabling a more precise description of the mass exchange and chemical reactions between the layers. This makes the simulation results closer to the actual operation of the battery.

[0021] In some embodiments, after substituting the electrolyte dissolved gas concentration and the second interface reaction rate into the fourth equation at the interface between the separator layer and the negative electrode layer, the method further includes:

[0022] Substituting the porosity, the first interface reaction rate, and the electrolyte lithium-ion concentration into the fifth equation for lithium-ion diffusion in the positive electrode layer and the separator layer, and using the positive electrode thickness, the positive electrode tortuosity, the negative electrode thickness, the separator thickness, and the current collector thickness as boundary constraints, the single-step solution set is obtained.

[0023] This application improves the electrochemical simulation model of lithium-air batteries by further considering lithium-ion diffusion, thereby enhancing the simulation accuracy.

[0024] In some embodiments, the negative electrode layer includes a first negative electrode layer and a negative electrode current collector layer. After substituting the porosity, the first interfacial reaction rate, and the electrolyte lithium ion concentration into the fifth equation for lithium ion diffusion in the positive electrode layer and the separator layer, the equation further includes:

[0025] Substituting the thickness of the positive electrode, the thickness of the current collector, the thickness of the first negative electrode, and the thickness of the negative electrode current collector into the sixth equation of the current collector layer, the positive electrode layer, the first negative electrode layer, and the negative electrode current collector layer, and using the thickness of the positive electrode, the tortuosity of the positive electrode, the thickness of the negative electrode, the thickness of the separator, the thickness of the current collector, the thickness of the first negative electrode, and the thickness of the negative electrode current collector as boundary constraints, the single-step solution set is obtained.

[0026] This application, by substituting the key thickness parameters of each layer into the sixth equation and setting boundary constraints, can more accurately describe the interactions and material-energy transfer between the battery layers, further reducing errors caused by model simplification.

[0027] In some embodiments, after mapping the solution results of the coupled equation system to the battery geometric model corresponding to the model mesh, the method further includes:

[0028] In response to the received simulation time value, determine the dissolved gas distribution corresponding to the simulation time value;

[0029] Based on the dissolved gas distribution corresponding to each of the simulation time values, oxygen utilization evaluation indicators and gas pressure evaluation indicators are determined.

[0030] This application obtains the distribution of dissolved gases through user operation, enabling in-depth analysis of the distribution of dissolved gases inside the battery and the utilization efficiency of oxygen.

[0031] In some embodiments, after determining the oxygen utilization evaluation index and the gas pressure evaluation index based on the dissolved gas distribution corresponding to each of the simulation time values, the steps include:

[0032] Based on the oxygen utilization evaluation index, update the cathode thickness and cathode tortuosity in the battery geometry information, and update the current collector porosity and cathode porosity in the battery material parameters to update the gas flow channel of the battery or increase the input gas pressure.

[0033] Based on the analysis results of oxygen utilization evaluation indicators, this application suggests optimizing the battery structure design, such as increasing the porosity of the positive electrode to improve oxygen diffusion efficiency, or improving the electrolyte formulation to enhance oxygen solubility and transport performance, thereby improving the overall battery performance.

[0034] Secondly, this application provides a lithium-air battery electrochemical simulation device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the lithium-air battery electrochemical simulation method described above.

[0035] Thirdly, this application provides a storage medium, which is a computer-readable storage medium, on which a program for implementing a lithium-air battery electrochemical simulation method is stored. The program for implementing the lithium-air battery electrochemical simulation method is executed by a processor to implement the steps of the lithium-air battery electrochemical simulation method as described above.

[0036] Thirdly, this application provides a computer program product, including a computer program that is executed by a processor to implement the steps of the lithium-air battery electrochemical simulation method as described above.

[0037] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0038] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0039] Figure 1 This is a flowchart illustrating steps S10-S30 in one embodiment of the lithium-air battery electrochemical simulation method of this application.

[0040] Figure 2 This is a flowchart illustrating step S221 in another embodiment of the lithium-air battery electrochemical simulation method of this application;

[0041] Figure 3 This is a schematic diagram of the battery geometric model in another embodiment of the lithium-air battery electrochemical simulation method of this application;

[0042] Figure 4 This is a flowchart illustrating step S222 in another embodiment of the lithium-air battery electrochemical simulation method of this application;

[0043] Figure 5 This is a schematic diagram of the overall process in another embodiment of the lithium-air battery electrochemical simulation method of this application;

[0044] Figure 6 This is a schematic diagram illustrating the positive electrode blockage situation in another embodiment of the lithium-air battery electrochemical simulation method of this application;

[0045] Figure 7 This is a schematic diagram of the hardware structure involved in the embodiment of the lithium-air battery electrochemical simulation equipment of this application.

[0046] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0047] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by one of ordinary skill in the art to which this application belongs; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this application; the terms “comprising” and “having” and any variations thereof in the specification, claims and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0049] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0050] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0051] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0052] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0053] In the description of the embodiments of this application, the technical terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of this application and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application.

[0054] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0055] Currently, related technologies consider lithium-ion diffusion, potential distribution, lithium-ion insertion / extraction reactions, and two-dimensional distribution of active materials when simulating battery performance. They also refine lithium-ion exchange at the solid-liquid interface to boundary conditions to simulate battery performance under different conditions. However, current simulation methods cannot accurately simulate the microstructural characteristics inside the battery electrodes, resulting in poor simulation results for lithium-air batteries.

[0056] The main solution of this application is as follows: First, obtain key parameters such as cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity. These parameters are crucial for accurately describing the internal structure and lithium-ion transport characteristics of the battery. For example, cathode porosity affects the diffusion path and velocity of lithium ions in the cathode material. The obtained parameters are used as model inputs and solved in a coupled equation set based on the coupling of the air layer, current collector layer, and cathode layer. By coupling these different layers, the interactions and influences between different regions inside the battery can be considered more comprehensively, such as the relationship between oxygen supply in the air layer and lithium-ion reaction in the cathode layer. The solution results of the coupled equation set are mapped onto the battery geometry model corresponding to the model mesh to finally determine the battery's rate performance. This step combines the numerical calculation results with the actual battery geometry, intuitively obtaining the battery's performance at different rates, thereby achieving effective simulation of the lithium-air battery performance.

[0057] Firstly, one embodiment of this application proposes an electrochemical simulation method for lithium-air batteries; please refer to [reference needed]. Figure 1 In this embodiment, the electrochemical simulation method for lithium-air batteries includes the following steps:

[0058] Step S10: Obtain the positive electrode thickness, positive electrode tortuosity, positive electrode porosity, and current collector porosity.

[0059] In this embodiment, the positive electrode thickness refers to the thickness of the positive electrode material layer in a lithium-air battery, which affects the transport distance of lithium ions and the size of the reaction region within the positive electrode. The positive electrode tortuosity is a parameter reflecting the influence of the internal pore structure of the positive electrode on the ion diffusion path; the greater the tortuosity, the more complex the ion diffusion path. The positive electrode porosity is the proportion of pore volume to the total volume in the positive electrode material, affecting electrolyte wetting and lithium ion diffusion. The current collector porosity is the proportion of pore volume to the total volume in the current collector, affecting the transport of air and lithium ions.

[0060] To obtain all parameters, the user inputs initial battery parameters, including battery geometry, battery material parameters, and charging conditions. Battery geometry includes, but is not limited to, positive electrode thickness and positive electrode tortuosity. Battery material parameters include, but are not limited to, positive electrode porosity and current collector porosity. Charging conditions include, but are not limited to, the charging / discharging process and ambient temperature. The charging / discharging process includes charging and discharging.

[0061] To refine the simulation to the microstructure of the electrode, at least the following parameters are required: cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity. These parameters are then used to determine the airflow channels formed by the current collector and cathode. Users input initial battery parameters through the simulation software's interface, including battery geometry (such as cathode thickness and tortuosity), battery material parameters (such as cathode porosity and current collector porosity), and charging conditions (such as charge / discharge process and ambient temperature). After receiving these parameters, the software extracts the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity for subsequent simulation calculations.

[0062] Step S20: Solve the coupled equation set based on the positive electrode thickness, positive electrode tortuosity, positive electrode porosity and current collector porosity as model inputs. The coupled equation set is coupled according to the air layer, current collector layer and positive electrode layer.

[0063] In this embodiment, model input refers to the initial values ​​of the parameters required for the first solution of the coupled equations. Model mesh: Divides the battery's geometric model into several small grid cells for numerical calculations. Coupled equations: Contains multiple interrelated equations describing the coupling relationships between different physicochemical processes within the battery, such as mass transport and chemical reactions between the air layer, current collector layer, and cathode layer. Air layer: The part of the battery in contact with external air, providing oxygen for the battery reaction. Current collector layer: The part that collects and conducts current, made of metallic materials. Cathode layer: The part of the battery where the positive electrode reaction occurs, the main region for lithium-ion insertion and extraction.

[0064] To improve the accuracy of the model solution, a battery geometric model was constructed based on the battery geometry and material parameters. This model describes the three-dimensional structure of the battery to be simulated, including the arrangement of each layer and the airflow channel formed by the current collector and the positive electrode. In a lithium-air battery, air enters the current collector from the outside, then diffuses to the positive electrode, and then diffuses to the separator. In other words, air enters the separator from the outside through the airflow channel formed by the current collector and the positive electrode to react. First, a battery geometric model was constructed based on the acquired battery geometry and material parameters. This model describes the three-dimensional structure of the battery, including the arrangement of each layer and the airflow channel formed by the current collector and the positive electrode. Then, the positive electrode thickness, positive electrode tortuosity, positive electrode porosity, and current collector porosity were used as model inputs and substituted into the equations obtained by coupling the air layer, current collector layer, and positive electrode layer. Numerical calculation methods (such as the finite element method and the finite difference method) were used to iteratively solve the coupled equations on the model mesh until the convergence condition was met.

[0065] To further improve simulation accuracy, the coupled equation set can also include a P2D model. In this case, the model input is determined based on user input; if the user input does not include a model input, a preset value is used instead. The user input also includes ambient temperature. Specifically, the user input includes the dimensions of various components such as the battery electrode GDL thickness, CNT thickness, separator thickness, and lithium metal thickness, as well as the electrode tortuosity. Material properties include the porosity of the positive electrode, the porosity of the current collector, the concentration of dissolved gases CO2 / O2 / H2O in the electrolyte, the main reaction interface rate, and the charging conditions including the charging and discharging process and ambient temperature. This outputs the battery rate performance indicators under specific temperature and different rate conditions.

[0066] Step S30: Map the solution results of the coupled equation set to the battery geometric model corresponding to the model mesh to determine the battery rate performance.

[0067] In this embodiment, the solution results are the numerical values ​​of various physical quantities obtained through iterative solutions to the coupled equations, such as lithium-ion concentration and potential distribution. Battery geometric model: A three-dimensional model describing the actual structure of the battery. Battery rate performance: The battery's performance at different charge / discharge rates, such as capacity and charge / discharge efficiency.

[0068] To visually demonstrate the impact of electrode structure on battery rate performance, the solution results of the coupled equations (such as lithium-ion concentration and potential distribution) are mapped onto the battery geometric model corresponding to the model mesh. By analyzing the distribution of physical quantities in each part of the model, the battery performance indicators, such as battery capacity and charge / discharge efficiency, are calculated at different charge / discharge rates, thereby determining the battery rate performance.

[0069] For ease of understanding, the following example is provided, but it does not limit this application. As an example, the user opens the simulation software and inputs the initial battery parameters in the input interface: Battery geometry: positive electrode thickness is 100 μm, positive electrode tortuosity is 2.5. Battery material parameters: positive electrode porosity is 0.4, current collector porosity is 0.3. Charging conditions: constant current charging to 4.2V, ambient temperature is 25℃. The software extracts the positive electrode thickness, positive electrode tortuosity, positive electrode porosity, and current collector porosity as the basic parameters for subsequent calculations. The software constructs a battery geometric model based on the input battery geometry and battery material parameters. This model clearly shows the three-dimensional structure of the battery, including the arrangement of the air layer, current collector layer, positive electrode layer, and the air flow channel composed of the current collector and positive electrode. The positive electrode thickness, positive electrode tortuosity, positive electrode porosity, and current collector porosity are used as model inputs and substituted into the coupled equation system. The finite element method (FEM) was used to iteratively solve the coupled equations on the model mesh. After multiple iterations, the solution to the equations converged. The solution results of the coupled equations (such as lithium-ion concentration distribution and potential distribution) were mapped onto the battery geometric model. The distribution of physical quantities in each part of the model was analyzed, and the battery capacity at a 1C charging rate was calculated to be 20Ah, with a charge-discharge efficiency of 90%. By changing the charge-discharge rate and repeating the above steps, the battery performance indicators at different rates were obtained, thus comprehensively evaluating the battery's rate performance.

[0070] This application simulates the ion migration, electron conduction, and reaction kinetics during the electrochemical reaction process by inputting electrode structure parameters, including but not limited to porosity and tortuosity, and then processing them through a set of physicochemical coupling equations. Finally, it outputs the battery rate performance index under specific temperature and different rate conditions, thereby realizing the precise simulation of battery simulation down to the internal microstructure characteristics of the battery electrode and improving the simulation accuracy of lithium-air batteries.

[0071] In some embodiments, refer to Figure 2 In this embodiment, before step S20, the following steps are included:

[0072] Step A10: Establish a battery geometric model based on the positive electrode thickness, positive electrode tortuosity, positive electrode porosity, current collector thickness, separator thickness, current collector porosity, and electrolyte dissolved gas concentration.

[0073] In this embodiment, the thickness of the current collector layer (used to collect and conduct current) affects the battery's internal resistance and current distribution. The separator thickness, located between the positive and negative electrodes, prevents direct short-circuiting while allowing lithium ions to pass through; its thickness affects the lithium ion transport rate. The concentration of dissolved gases in the electrolyte (such as oxygen) affects the chemical reactions and performance within the battery.

[0074] To visually demonstrate the simulation results, parameters such as positive electrode thickness, positive electrode tortuosity, positive electrode porosity, current collector thickness, separator thickness, current collector porosity, and electrolyte dissolved gas concentration were collected. Using professional modeling software (such as COMSOL Multiphysics and ANSYS), a precise battery geometric model was constructed based on these parameters, clearly showing the spatial layout of the air layer, current collector layer, positive electrode layer, separator layer, and negative electrode layer. The electrolyte dissolved gas concentration includes the concentrations of carbon dioxide (CO2), oxygen (O2), and water vapor (H2O) that can dissolve in the electrolyte.

[0075] Step A20: Determine the first grid density of the battery surface in the battery geometry model and the second grid density of the gas flow channel in the battery geometry model.

[0076] In this embodiment, the first mesh density refers to the density of the mesh on the battery surface. A suitable mesh density can improve computational efficiency while ensuring computational accuracy, affecting the accuracy of calculations of physical quantities on the battery surface (such as potential and current density). The second mesh density refers to the density of the mesh in the battery gas flow channels. These channels are responsible for gas transport, and their mesh density is crucial to the accuracy of gas diffusion and reaction simulations. The model mesh divides the battery geometric model into many small units (mesh) for numerical calculations and solving physical equations.

[0077] To ensure the accuracy of the model mesh, the mesh density is determined by comprehensively considering the physical characteristics of the battery and the simulation requirements. For the battery surface, a higher first mesh density can be set if accurate simulation of the electrochemical processes on the surface is required; for the gas flow channel, a second mesh density is determined based on the complexity of gas diffusion and the required simulation accuracy.

[0078] To improve processing efficiency, the first grid density of the battery surface in the preset battery geometry model and the second grid density of the gas flow channel in the preset battery geometry model are obtained.

[0079] Step A30: Construct the model mesh based on the first mesh density and the second mesh density.

[0080] In this embodiment, the battery geometric model is meshed in the modeling software according to a predetermined first and second mesh density. The software divides the battery geometric model into numerous small mesh units according to specified density rules, forming a model mesh.

[0081] For ease of understanding, the following examples are provided, but are not intended to limit this application. As an example, parameters were collected: parameters were obtained through experimental measurements or by referring to battery design data. The positive electrode thickness was 80 μm, the positive electrode tortuosity was 2.2, the positive electrode porosity was 0.38, the current collector thickness was 20 μm, the separator thickness was 15 μm, the current collector porosity was 0.25, and the electrolyte dissolved gas concentration was 0.05 mol / L. Using COMSOL Multiphysics software, the dimensions and positional relationships of the air layer, current collector layer, positive electrode layer, separator layer, and negative electrode layer were defined sequentially according to these parameters to construct the battery geometric model. For the battery surface, due to the need for accurate simulation of the surface electrochemical reaction, the first grid density was set to 20 grid cells per millimeter. For the gas flow channel, considering the complexity of gas diffusion, the second grid density was set to 15 grid cells per millimeter. In COMSOL Multiphysics software, the mesh generation function was selected, and the battery geometric model was meshed according to the determined first and second grid densities. The software automatically divides the battery geometry model into numerous small mesh units, forming a model mesh for subsequent simulation calculations.

[0082] This application constructs a battery geometric model by using battery geometric information, and then considers the mesh density of the battery surface and the internal airflow channels to construct a model mesh, thereby improving simulation accuracy.

[0083] In some embodiments, step S20 includes:

[0084] Step S21: Discretize the coupled equation set using the model mesh of the battery geometric model to obtain an algebraic equation set.

[0085] In this embodiment, the coupled equations are a set of equations describing the interrelationships of multiple physicochemical processes in a lithium-air battery. For example, they might include equations related to lithium-ion diffusion, electrode reactions, and gas transport. These processes influence each other and need to be solved simultaneously. Discretization is the process of transforming the continuous mathematical model (coupled equations) into a discrete set of algebraic equations. On the model mesh, numerical methods (such as finite difference methods or finite element methods) are applied to each mesh cell to represent continuous physical quantities as discrete values ​​at the mesh nodes. The algebraic equations are a set of algebraic equations obtained from discretization, where the unknowns are the physical quantity values ​​at the mesh nodes. Solving the algebraic equations yields the distribution of these physical quantities throughout the battery model.

[0086] To improve computational accuracy, numerical methods (such as the finite element method) are used to process the coupled equations. Taking the finite element method as an example, the geometric region of the battery is divided into multiple small elements according to the model mesh. Within each element, it is assumed that physical quantities (such as lithium-ion concentration, electric potential, etc.) have a certain distribution form (polynomial). By integrating and approximating the coupled equations over each element, the continuous equations are transformed into an algebraic equation system with the physical quantities at the mesh nodes as unknowns.

[0087] Step S22: Solve the algebraic equations based on the positive electrode thickness, the positive electrode tortuosity, the positive electrode porosity, and the current collector porosity to obtain a single-step solution set.

[0088] In this embodiment, the single-step solution set is the set of solutions for all physical quantities at all grid nodes obtained during the process of solving the algebraic equation system once, such as the values ​​of physical quantities like lithium ion concentration and electric potential at each grid node.

[0089] To improve computational accuracy, the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity are used as model inputs and substituted into a system of algebraic equations. A suitable numerical solution algorithm (such as the Newton-Raphson method) is employed to solve the system of algebraic equations. During the solution process, the values ​​of the unknowns are iteratively updated until certain convergence conditions are met, resulting in a single-step solution set.

[0090] Step S23: If the calculation cutoff condition is met, output the single-step solution set as the solution result.

[0091] In this embodiment, the calculation cutoff condition is a pre-set condition for determining whether the solution process has ended, including reaching an upper limit on the number of iterations, the change in physical quantities being less than a certain threshold, and reaching a set solution time. The solution result is the single-step solution set obtained after satisfying the calculation cutoff condition; it represents the physicochemical state of the battery under the current operating conditions and can be used to analyze battery performance.

[0092] To ensure the stability of the simulation results, after each step of solving the algebraic equations and obtaining the solution set, it is checked whether the computational cutoff condition is met. If the condition is met (e.g., the number of iterations reaches 100 or the maximum change of the physical quantity between two adjacent iterations is less than 10), the simulation results are considered complete. -6 If the current single-step solution set is obtained, then the current solution set will be output as the final solution result; otherwise, the next iteration will continue.

[0093] To ensure the timeliness of simulation results, a solution time is set. If the current solution time reaches the set time, the solution of the algebraic equations is stopped, and the last single-step solution set is obtained as the solution result.

[0094] For ease of understanding, the following example is provided, but it does not limit this application. As an example, a model mesh has been constructed based on the battery's structure and parameters. The coupled equations describing lithium-ion diffusion, electrode reactions, and gas transport in the battery are discretized using finite element software (such as COMSOL Multiphysics). The software automatically transforms the coupled equations into a set of algebraic equations with the lithium-ion concentration, potential, etc., at the mesh nodes as unknowns. The measured values ​​are: positive electrode thickness 120 μm, positive electrode tortuosity 2.3, positive electrode porosity 0.4, and current collector porosity 0.28. These values ​​are substituted into the algebraic equations as model input. The Newton-Raphson method is used for solving, updating the values ​​of the unknowns in each iteration. After multiple iterations until the convergence condition is met, a single-step solution set is obtained, containing the lithium-ion concentration and potential values ​​at each mesh node. The calculation cutoff condition is set to 80 iterations or the maximum change in lithium-ion concentration between two adjacent iterations being less than 10. -5 During the iteration process, the condition was continuously checked to ensure it was met. When the 65th iteration was reached, the maximum change in lithium-ion concentration was less than 10. -5 If the computation deadline is met, the current single-step solution set will be output as the solution result.

[0095] In this embodiment, the coupled equations are discretized into a set of algebraic equations, which can then be solved using mature numerical algorithms. These algorithms are computationally efficient when dealing with algebraic equations, avoiding the complexity of directly solving continuous equations and thus reducing computation time and resource consumption. Discretization on the model mesh allows for a more accurate description of the physicochemical processes inside the battery. By appropriately selecting the mesh density and discretization method, numerical errors can be reduced to some extent, improving the accuracy of the calculation results. The cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity are used as model inputs for the solution, and computational cutoff conditions are set, making the solution process iterative and controllable. The model inputs and computational cutoff conditions can be adjusted according to actual needs to obtain solution results that better reflect the actual situation.

[0096] In summary, this embodiment effectively improves the computational efficiency and accuracy of lithium-air battery electrochemical simulation through steps such as discretization, iterative solution, and cutoff condition judgment, providing a reliable basis for battery design and optimization.

[0097] In some embodiments, refer to Figure 2 Step S22 includes:

[0098] Step S221: Substitute the air velocity into the first equation at the interface between the air layer and the current collector layer, and substitute the positive electrode porosity and the current collector porosity into the second equation at the interface between the current collector layer and the positive electrode layer. Use the positive electrode thickness, the positive electrode tortuosity, and the current collector thickness as boundary constraints to obtain the single-step solution set.

[0099] In this embodiment, air velocity refers to the speed at which air flows within the battery's air layer. It affects the rate at which oxygen is transported into the battery, thus influencing the battery's electrochemical reactions. The first equation describes the physicochemical processes at the interface between the air layer and the current collector layer, including parameters such as air velocity, and is used to simulate the mass exchange and energy transfer between them. The second equation describes the physicochemical processes at the interface between the current collector layer and the cathode layer, involving parameters such as cathode porosity and current collector porosity, and is used to simulate lithium-ion transport and chemical reactions between them. Boundary constraints are the restrictions imposed on the values ​​or variations of physical quantities at the boundaries when solving the algebraic equations. Here, cathode thickness, cathode tortuosity, and current collector thickness are used as boundary constraints to determine the physical boundaries of different regions within the battery.

[0100] To refine the microstructure of the electrode, parameters such as air velocity, positive electrode porosity, current collector porosity, positive electrode thickness, positive electrode tortuosity, and current collector thickness are determined based on user input. The specific forms of the first and second equations are defined; these equations are based on physicochemical principles, such as the law of conservation of mass and the law of conservation of charge. Substituting the air velocity into the first equation, which describes the physicochemical processes at the interface between the air layer and the current collector layer, allows us to determine the oxygen transport and reaction at this interface. Substituting the positive electrode porosity and current collector porosity into the second equation, which describes the physicochemical processes at the interface between the current collector layer and the positive electrode layer, allows us to determine how lithium ions are transported and reacted between these two layers. Simultaneously, the positive electrode thickness, positive electrode tortuosity, and current collector thickness are used as boundary constraints to limit the solutions of the algebraic equations to a reasonable physical range. Then, a suitable numerical solution method (such as the Newton-Raphson method) is used to solve the algebraic equations after parameter substitution and boundary condition constraints, resulting in a single-step solution set. For the separator and negative electrode layers, conventional coupling equations are used. These equations are based on the diffusion of lithium ions in the separator and the electrochemical reaction at the negative electrode. When solving the algebraic equation system, the equations for the separator and negative electrode layers are solved simultaneously with equations considering the coupling of the air layer, current collector layer, and positive electrode layer to obtain the physicochemical state of the entire battery.

[0101] This embodiment uses conventional coupling equations for the separator and negative electrode layers, focusing on the coupling of the air layer, current collector layer, and positive electrode layer. This allows for a more targeted analysis of the impact of these key regions on battery performance. In practical applications, the design and optimization of these regions are crucial for improving battery performance. This simulation method can provide more valuable references for battery design and improvement. While ensuring simulation accuracy, it avoids complex coupling analyses of all layers, reducing computational load and improving computational efficiency. Compared to comprehensive and complex coupling simulations of the entire battery, it can obtain more accurate results in a shorter time, meeting the needs of practical engineering.

[0102] In some embodiments, after step S221, the following is included:

[0103] Step S222: Substitute the porosity, the first interface reaction rate, and the electrolyte dissolved gas concentration into the third equation of the diffusion of matter between the positive electrode layer and the membrane layer; substitute the electrolyte dissolved gas concentration and the second interface reaction rate into the fourth equation of the interface between the membrane layer and the negative electrode layer; and use the positive electrode thickness, the positive electrode tortuosity, the negative electrode thickness, the membrane thickness, and the current collector thickness as boundary constraints to obtain the single-step solution set.

[0104] In this embodiment, the first interface reaction rate is the rate of chemical reaction at the interface between the positive electrode layer and the separator layer, which affects the exchange and transformation of substances between these two layers. The electrolyte dissolved gas concentration is the concentration of dissolved gases (such as oxygen) in the electrolyte, which has a significant impact on the electrochemical reactions within the battery. The second interface reaction rate is the rate of chemical reaction at the interface between the separator layer and the negative electrode layer, which determines the exchange of substances between these two layers. The third equation describes the diffusion process of substances between the positive electrode layer and the separator layer, including parameters such as porosity, the first interface reaction rate, and the electrolyte dissolved gas concentration. The fourth equation describes the physicochemical processes at the interface between the separator layer and the negative electrode layer, involving the electrolyte dissolved gas concentration and the second interface reaction rate.

[0105] To further consider the separator and negative electrode layers and improve the accuracy of battery simulation, parameters such as porosity, first interface reaction rate, electrolyte dissolved gas concentration, second interface reaction rate, positive electrode thickness, positive electrode tortuosity, negative electrode thickness, separator thickness, and current collector thickness are determined based on user input. The specific forms of the third and fourth equations are defined; these equations are established based on physicochemical principles (such as diffusion laws and reaction kinetics). After substituting the positive electrode porosity and current collector porosity into the second equation at the interface between the current collector layer and the positive electrode layer, porosity, the first interface reaction rate, and the electrolyte dissolved gas concentration are further substituted into the third equation, which simulates the diffusion and reaction processes between the positive electrode layer and the separator layer. The electrolyte dissolved gas concentration and the second interface reaction rate are substituted into the fourth equation, which describes the physicochemical processes at the interface between the separator and the negative electrode layer. The positive electrode thickness, positive electrode tortuosity, negative electrode thickness, separator thickness, and current collector thickness are used as boundary constraints. Using appropriate numerical methods, the system of algebraic equations after parameter substitution and boundary condition constraints is solved, ultimately yielding a set of single-step solutions. (Refer to...) Figure 3 , Figure 3 The diagram provides an example of a battery geometry model. From top to bottom, it consists of an air layer, a current collector layer, a positive electrode layer, a separator layer, and a negative electrode layer. The air layer is the interface between the current collector layer and the air, and is not shown in the diagram. The GDL (Gas Diffusion Layer) is the current collector layer. The CNT (Carbon Nanotube Oxygen Precipitation Main Reaction Layer) is the positive electrode layer. The negative electrode layer includes a first negative electrode layer composed of lithium metal and a negative electrode current collector layer composed of copper.

[0106] This embodiment, by introducing key parameters such as the reaction rate at the first interface, the reaction rate at the second interface, and the concentration of dissolved gases in the electrolyte, enables a more precise description of the mass exchange and chemical reactions between the layers. This makes the simulation results closer to the actual operation of the battery, providing a more reliable basis for battery design and optimization. In summary, this embodiment improves the completeness and accuracy of the electrochemical simulation of lithium-air batteries by comprehensively considering each layer of the battery, reasonably substituting parameters, and setting boundary constraints.

[0107] In some embodiments, refer to Figure 3 After step S222, the following steps are also included:

[0108] Step S223: Substitute the porosity, the first interface reaction rate, and the electrolyte lithium ion concentration into the fifth equation for lithium ion diffusion in the positive electrode layer and the separator layer, and use the positive electrode thickness, the positive electrode tortuosity, the negative electrode thickness, the separator thickness, and the current collector thickness as boundary constraints to obtain the single-step solution set.

[0109] In this embodiment, the electrolyte lithium-ion concentration refers to the amount of lithium ions in the electrolyte, which is a crucial factor affecting the diffusion of lithium ions between battery layers and the electrochemical reactions of the battery. The fifth equation specifically describes the lithium-ion diffusion process between the positive electrode layer and the separator layer, and includes parameters such as porosity, the first interface reaction rate, and the electrolyte lithium-ion concentration. The meanings of other parameters and equations are consistent with the explanations in the previous embodiments.

[0110] To further improve simulation accuracy, parameters such as porosity, first interface reaction rate, electrolyte lithium-ion concentration, positive electrode thickness, positive electrode tortuosity, negative electrode thickness, separator thickness, and current collector thickness were determined based on user input. The specific form of the fifth equation was defined; this equation is based on the physical laws of lithium-ion diffusion and incorporates factors such as interfacial reactions. After substituting the electrolyte dissolved gas concentration and the second interface reaction rate into the fourth equation at the interface between the separator and negative electrode layers, porosity, the first interface reaction rate, and the electrolyte lithium-ion concentration were then substituted into the fifth equation. This process aims to accurately describe the diffusion of lithium ions between the positive electrode and separator layers, considering the influence of pore structure, interfacial reactions, and the lithium-ion content in the electrolyte on diffusion. The positive electrode thickness, positive electrode tortuosity, negative electrode thickness, separator thickness, and current collector thickness were used as boundary constraints. The numerical solution method is used to solve the algebraic equations after parameter substitution and boundary condition constraints. After multiple iterations, a single-step solution set is obtained, which contains the values ​​of physical quantities such as lithium ion concentration and electric potential at each grid node.

[0111] This embodiment, building upon the previous consideration of diffusion from the positive electrode to the separator layer, further considers lithium-ion diffusion, substituting relevant parameters into the fifth equation to make the simulation model more complete. The lithium-ion diffusion process plays a crucial role in the battery's charging and discharging process; accurately simulating lithium-ion diffusion helps in a more comprehensive understanding of the battery's internal physicochemical processes. By further considering lithium-ion diffusion, the electrochemical simulation model of the lithium-air battery is improved, enhancing simulation accuracy.

[0112] In some embodiments, after step S223, the method further includes:

[0113] Step S224: Substitute the positive electrode thickness, the current collector thickness, the first negative electrode thickness, and the negative electrode current collector thickness into the sixth equation of the current collector layer, the positive electrode layer, the first negative electrode layer, and the negative electrode current collector layer, and use the positive electrode thickness, the positive electrode tortuosity, the negative electrode thickness, the membrane thickness, the current collector thickness, the first negative electrode thickness, and the negative electrode current collector thickness as boundary constraints to obtain the single-step solution set.

[0114] In this embodiment, the thickness of the first negative electrode layer (lithium metal layer) affects the reactivity of lithium metal, the lithium-ion insertion / extraction process, and the battery's capacity. The thickness of the negative electrode current collector layer (copper layer) primarily functions as a current collector, and its thickness influences the battery's internal resistance and current distribution. The sixth equation describes the physicochemical coupling relationship between the current collector layer, positive electrode layer, first negative electrode layer, and negative electrode current collector layer. This equation includes parameters such as the positive electrode thickness, current collector thickness, first negative electrode thickness, and negative electrode current collector thickness, and is used to comprehensively consider the interactions between the layers. The meanings of other parameters and equations are consistent with the preceding text.

[0115] To further improve simulation accuracy, parameters such as positive electrode thickness, current collector thickness, first negative electrode thickness, negative electrode current collector thickness, positive electrode tortuosity, negative electrode thickness (the sum of the first negative electrode thickness and the negative electrode current collector thickness), and separator thickness are determined based on user input. The specific form of the sixth equation is determined, which is based on the physicochemical properties of each battery layer, such as the principles of charge conservation and mass conservation. After substituting porosity, the first interface reaction rate, and the electrolyte lithium-ion concentration into the fifth equation for lithium-ion diffusion between the positive electrode layer and the separator layer, the positive electrode thickness, current collector thickness, first negative electrode thickness, and negative electrode current collector thickness are then substituted into the sixth equation. This step aims to accurately describe the interaction and mass-energy transfer process between the current collector layer, positive electrode layer, first negative electrode layer, and negative electrode current collector layer using these key geometric parameters. The positive electrode thickness, positive electrode tortuosity, negative electrode thickness, separator thickness, current collector thickness, first negative electrode thickness, and negative electrode current collector thickness are used as boundary constraints. A suitable numerical solution method is used to solve the system of algebraic equations after parameter substitution and boundary condition constraints. During the solution process, the values ​​of the unknowns are continuously updated iteratively until the convergence condition is met, thus obtaining a single-step solution set, which contains the distribution of physical quantities such as lithium-ion concentration and potential at various locations in the battery.

[0116] This embodiment, by substituting the key thickness parameters of each layer into the sixth equation and setting boundary constraints, can more accurately describe the interactions and material-energy transfer between the battery layers. This further reduces errors introduced by the simplified model, making the simulation results closer to the actual operation of the battery.

[0117] For ease of understanding, the following example is provided, but it does not limit this application. As an example, the battery geometric model can be arbitrarily modified and is not necessarily a regular rectangular geometry; that is, the battery geometric model is determined based on the input battery geometric information and battery material parameters. The battery geometric model consists of an air layer, a current collector layer, a positive electrode layer, a separator layer, and a negative electrode layer, wherein the air layer is the interface between the current collector layer and the air, and the negative electrode includes a first negative electrode layer and a negative electrode current collector layer. The first negative electrode layer is lithium metal, and the negative electrode current collector layer is copper. The first equation is the Navier-Stokes equation, the second equation is based on Henry's law, the third equation is based on Fick's law, the fourth equation is the Butler-Volmar equation, the fifth equation is based on the Nerst-Planck equation for dilute solutions or Newman's theory of concentrated solutions, and the sixth equation is based on Ohm's law. Among them, the Navier-Stokes equation is a fundamental equation in fluid mechanics, which describes how a gas or liquid flows under the action of an external force (such as a pressure gradient). These equations characterize the fluid's motion through factors such as viscosity, inertia, and compressibility, and are key to understanding the flow behavior of gas in current collectors. Here, the top GDL layer (current collector layer) is not immersed in electrolyte; air enters from the top, hence this equation describes it. Henry's Law states that at a given temperature, the solubility of a gas in a liquid is proportional to the partial pressure applied to the liquid surface. It explains the dissolution and release of gases (such as CO2, oxygen, water vapor, and nitrogen) in the electrolyte, corresponding to the release / fixation of oxygen through the gas-liquid interface during the charging / discharging of a lithium-air battery. Figure 1 The process involves the non-wetting interface of the GDL and the wetting interface of the CNT (positive electrode layer). During discharge, oxygen enters the GDL from the outside, dissolves at the GDL / CNT gas-liquid interface, enters the CNT, and finally reacts with lithium ions and electrons on the carbon nanotube surface to form lithium peroxide. The charging process follows the reverse path. Other gases also follow this process, but with different operating voltages, mainly reflected in the difference in the η overpotential in the BV equation. Figure 3 The model only lists one main reaction; other gas components such as carbon dioxide and water vapor follow the same pattern. Figure 3 The equations differ in parameters. Ohm's law describes that current in a conductor is directly proportional to voltage and inversely proportional to resistance. In porous cathodes (CNTs), porous current collectors (GDLs), and lithium metal anodes of batteries, Ohm's law helps us understand how electrons are conducted and how the potential is distributed. Fick's law is one of the fundamental theories of mass transport phenomena, used to describe the diffusion process of matter (such as neutral gas molecules) in an electrolyte driven by a concentration gradient. It emphasizes the proportionality of diffusion flux to the concentration gradient. In the electrolyte of lithium-ion batteries, the migration of lithium ions is affected not only by the concentration gradient but also by the electric field. John Newman's concentrated solution theory correction takes these factors into account, including diffusion, electromigration, and activity corrections to the liquid phase potential in concentrated solutions.

[0118] The electrochemical physics model in this embodiment depicts the complex physical processes within a lithium-air battery. The core of the model lies in its multi-scale, multi-field coupling characteristics, enabling a comprehensive analysis of the battery's operating mechanism from the microscopic to the macroscopic levels. At the microscopic level, it traces the migration paths of lithium ions and oxygen in the electrode materials, considers the reaction kinetics of lithium ions and oxygen on carbon surfaces, and describes the diffusion and transport characteristics of these substances within the porous structure. Furthermore, the model simulates the adsorption, dissociation, and recombination of oxygen on the catalyst surface, revealing the impact of these fundamental reaction steps on overall battery performance. Utilizing porous media theory, the model deeply analyzes the complex fluid dynamics within the electrode. This includes the flow behavior of the electrolyte in the electrode pores, the diffusion and collection efficiency of gases (oxygen and potential byproducts) in the porous structure, and how these transport processes are affected by variations in porosity and tortuosity. Through fine mesh generation and the finite element method, the model can accurately predict the mass transport efficiency and reactant distribution state within the battery under different structural parameters. On a macroscopic level, the model comprehensively considers the thermodynamic and kinetic responses of the battery under different operating conditions (such as temperature variations and charge / discharge rates). This includes the coupled effects of multiple factors such as electrochemical reaction heat, ohmic heat, and convective and radiative heat dissipation, thereby accurately assessing the battery's thermal management requirements and safety. Simultaneously, the model can also simulate the impact of electrode porosity utilization. This model not only theoretically explores the working principle of lithium-air batteries but also provides specific guidance for practical battery design. By simulating the influence of different electrode structural parameters (such as porosity distribution and interlayer interface characteristics) on battery performance, it addresses issues such as how to balance porosity to promote mass transport while maintaining sufficient active material loading, and how to design electrode hierarchical structures to improve electronic conductivity and mechanical strength.

[0119] In some embodiments, after mapping the solution results of the coupled equation system to the battery geometric model corresponding to the model mesh, the method further includes:

[0120] Step S40: In response to the received simulation time value, determine the dissolved gas distribution corresponding to the simulation time value.

[0121] In this embodiment, the simulation time value refers to the time point set by the user during battery simulation to simulate the battery's operating state. Since battery performance changes over time, different simulation time values ​​correspond to the battery's operating state at different moments. Dissolved gas distribution, in lithium-air batteries, mainly refers to the distribution of oxygen dissolved in the electrolyte. Oxygen is a key reactant in the battery reaction, and its uneven distribution in the electrolyte will affect the battery's reaction rate and performance.

[0122] To investigate the oxygen conductivity of the electrolyte, the system receives user-input simulation time values. After solving the coupled equations to obtain results at different time steps, it determines the target result corresponding to each simulation time value. Then, it extracts physical quantities related to dissolved gases (mainly oxygen), such as dissolved oxygen concentration, from the target result. Based on the extracted physical quantities and the positional information of each grid cell in the battery geometric model, it determines the distribution of dissolved gases inside the battery at each simulation time value. For example, different colored regions can be drawn on the geometric model to represent the distribution of dissolved gases at different concentrations, with darker colors indicating higher concentrations.

[0123] Step S50: Determine the oxygen utilization evaluation index based on the dissolved gas distribution corresponding to each of the simulation time values.

[0124] In this embodiment, the oxygen utilization evaluation index is a quantitative indicator used to measure the efficiency and effectiveness of the battery's oxygen utilization during operation. Evaluation indicators include oxygen utilization rate, oxygen consumption rate, and effective diffusion distance of oxygen within the battery.

[0125] To evaluate the battery's performance under current structural and temperature parameters, for each simulation time value, the total amount of oxygen participating in the reaction inside the battery is calculated by integration, which can be derived from the dissolved gas distribution and reaction kinetic equations. This is then divided by the total amount of oxygen entering the battery from the outside, assuming known air intake conditions, to obtain the oxygen utilization rate at that moment. For example, at a certain simulation time value, if the calculated amount of oxygen participating in the reaction is n1 and the total amount of oxygen entering the battery is n0, then the oxygen utilization rate is equal to n1 divided by n0 and multiplied by 100%. Based on the dissolved gas distribution at different simulation time values, the change in oxygen concentration between adjacent time steps is calculated and then divided by the time interval to obtain the oxygen consumption rate. For example, at times t1 and t2 (t2 minus t1 equals the time interval), the oxygen concentration at a certain location is C1 and C2 respectively; then the oxygen consumption rate at that location is equal to C1 minus C2 and then divided by the time interval. Integrating or statistically averaging over the entire battery geometric model yields the overall oxygen consumption rate of the battery. Analyze the effective diffusion distance of oxygen within the battery: Observe the changes in dissolved gas distribution at different simulation time values ​​to determine the diffusion range within the battery where oxygen can effectively participate in the reaction. A concentration threshold can be defined; when the dissolved oxygen concentration is below this threshold, the reactivity of oxygen in that region is considered low, thus determining the effective diffusion distance of oxygen within the battery.

[0126] For ease of understanding, the following example is provided, but it does not limit the scope of this application. As an example, simulation software is used to establish a three-dimensional battery geometric model based on battery design parameters, including the positive electrode layer, current collector layer, air layer, and electrolyte region. The model is meshed to ensure mesh fineness and accurately simulate the internal physical processes of the battery. Battery material parameters are input, such as the porosity and tortuosity of the positive electrode material, the conductivity and diffusion coefficient of the electrolyte, and battery geometric dimensions, such as the thickness of the positive electrode and the thickness of the current collector layer. A set of coupled equations is established, including ion transport equations, electron conduction equations, oxygen diffusion equations, and electrochemical reaction kinetic equations, as described in the previous embodiments, and will not be repeated here. The simulation time range is set to 0 to 3600 seconds, i.e., 1 hour, and a series of simulation time values ​​are defined, such as taking a time point every 100 seconds, for a total of 36 time points. Numerical calculation methods are used to solve the set of coupled equations to obtain the distribution of various physical quantities inside the battery at different time steps, including lithium ion concentration, potential distribution, and dissolved gas distribution. The solution results are mapped to the battery geometric model, and visualization tools in the software are used to display the distribution of physical quantities inside the battery at different time points. For example, color mapping is used to show the distribution of lithium-ion concentration in the positive electrode layer and the distribution of dissolved oxygen concentration in the electrolyte. For each simulation time value, the oxygen utilization evaluation index is calculated according to the above implementation steps. For example, at 1000 seconds, the calculated amount of oxygen participating in the reaction is 0.05 moles, and the total amount of oxygen entering the battery is 0.1 moles, so the oxygen utilization rate at this time is 50%. At the same time, the overall oxygen consumption rate of the battery is calculated to be 5 x 10^-5 moles per second. By analyzing the distribution of dissolved gas at different time points, it is found that the effective diffusion distance of oxygen inside the battery is large at the beginning and gradually decreases as the reaction proceeds. This indicates that the utilization of oxygen in the battery is gradually limited during operation, possibly due to the decrease in oxygen concentration in the electrolyte and the accumulation of reaction products.

[0127] Through the above examples, it can be seen that this simulation method can not only output the rate performance of the battery, but also provide in-depth analysis of the distribution of dissolved gases inside the battery and the oxygen utilization efficiency, providing important reference for battery optimization design. For example, based on the analysis results of oxygen utilization evaluation indicators, the battery structure design can be optimized, such as increasing the porosity of the positive electrode to improve oxygen diffusion efficiency, or improving the electrolyte formulation to enhance oxygen solubility and transport performance, thereby improving the overall battery performance.

[0128] Further, after step S50, the following steps are included:

[0129] Step S60: Update the positive electrode thickness and positive electrode tortuosity in the battery geometry information based on the oxygen utilization evaluation index, and update the current collector porosity and positive electrode porosity in the battery material parameters to update the gas flow channel of the battery.

[0130] In this embodiment, the gas flow channel of the battery, in a lithium-air battery, is the channel through which air enters the battery to participate in the reaction, and is mainly composed of the current collector and the positive electrode. The structure and characteristics of the gas flow channel, such as porosity and tortuosity, are also considered.

[0131] To optimize the battery structure design, a comprehensive and in-depth analysis of the calculated oxygen utilization evaluation indicators was conducted. The reasons for low oxygen utilization were investigated, including potential obstacles to oxygen transport, preventing it from fully reaching the reaction area; a slow oxygen consumption rate, possibly indicating insufficient reactive sites; and a short effective diffusion distance, possibly due to an unreasonable pore structure. Based on the analysis results, targeted adjustments to the battery geometry and material parameters were determined. If oxygen diffusion within the cathode was found to be difficult, increasing the cathode porosity and reducing its tortuosity could be considered to optimize the ion diffusion path. If oxygen transport was obstructed in the current collector layer, increasing its porosity could be attempted. If low oxygen utilization was due to insufficient reaction area, the cathode thickness could be appropriately adjusted to expand the reaction area. Following the determined adjustment directions, specific values ​​for the cathode thickness and tortuosity in the battery geometry, and the current collector porosity and cathode porosity in the battery material parameters were updated. For example, the positive electrode porosity is increased from 30% to 35%, the current collector porosity is increased from 20% to 25%, the positive electrode tortuosity is reduced from 1.5 to 1.3, and the positive electrode thickness is fine-tuned according to specific circumstances. Based on the updated parameters, the gas flow channel model of the battery is reconstructed. The new parameters will change the structure and characteristics of the gas flow channel, such as the size and distribution of pores and the degree of channel tortuosity. The gas transport in the new flow channel is recalculated and simulated using simulation software to ensure that the updated gas flow channel can effectively improve the oxygen transport efficiency and utilization.

[0132] For ease of understanding, the following example is provided, but it does not limit this application. As an example, a three-dimensional geometric model of a lithium-air battery is constructed based on initial design parameters, defining the positive electrode layer, current collector layer, air layer, separator layer, and negative electrode layer, and dividing them into a fine mesh. Initial battery geometry information is input: the positive electrode thickness is 0.5 mm, and the positive electrode tortuosity is 1.8; battery material parameters are: current collector porosity is 18%, and positive electrode porosity is 28%. Simultaneously, a coupled equation set including equations for ion transport, electron conduction, oxygen diffusion, and electrochemical reaction kinetics is established. The simulation time range is set to 0 to 7200 seconds (2 hours), with a simulation time value taken every 200 seconds. The coupled equation set is solved using numerical calculation methods to obtain the distribution of various physical quantities inside the battery at different time steps, including the dissolved gas distribution. Based on the dissolved gas distribution corresponding to different simulation time values, an oxygen utilization evaluation index is calculated. The results show that the average oxygen utilization rate is only 40%, the oxygen consumption rate is slow, and the effective diffusion distance of oxygen within the battery is short, only 0.2 mm. The R&D team analyzed the evaluation indicators and concluded that the low oxygen utilization rate was mainly due to the large tortuosity of the positive electrode, which hindered oxygen diffusion. Simultaneously, the relatively low porosity of the current collector and the positive electrode limited the transport of air and lithium ions. The team decided to increase the current collector porosity to 25%, increase the positive electrode porosity to 35%, reduce the positive electrode tortuosity to 1.4, and appropriately increase the positive electrode thickness to 0.6 mm. The battery geometry and material parameters were updated in the simulation software, and the battery's gas flow channel model was reconstructed. Simulation calculations were performed again, setting the same simulation time range and time values. Based on the new simulation results, the oxygen utilization evaluation indicators were recalculated. This time, the average oxygen utilization rate increased to 60%, the oxygen consumption rate significantly accelerated, and the effective diffusion distance of oxygen within the battery increased to 0.35 mm. By comparing the oxygen utilization evaluation indicators before and after optimization, the R&D team confirmed that the parameter update and gas flow channel optimization effectively improved the battery's oxygen utilization efficiency. This indicates that the optimized battery design can theoretically improve the driving range of electric vehicles, providing a strong theoretical basis for subsequent actual battery manufacturing and testing.

[0133] In this embodiment, the solution results are mapped to the battery geometric model, and the output results include, but are not limited to, battery rate performance, spatial and temporal distribution of current density, reaction rate, lithium-ion concentration distribution, dissolved gas concentration distribution, and current-voltage curves. Figure 6 , Figure 6To demonstrate the pore blockage situation, the predicted porous cathode pore blockage situation, current density distribution, product distribution during charging and discharging, and oxygen diffusion are then displayed in the battery geometry model. The system can also compare the solution results under various user inputs, outputting the predicted electrochemical performance of the material and cell performance under several parameter combinations, such as oxygen diffusion under different materials, oxygen dissolution capacity of different electrolytes, oxygen concentration changes with time in the thickness direction, and comparisons of results under different parameter combinations.

[0134] For ease of understanding, examples are given below, but these are not intended to limit the scope of this application. As an example, see [reference to...]. Figure 5The system receives user input and determines battery geometry, material parameters, and charging conditions. Battery geometry includes dimensions of various components such as the cathode thickness, current collector thickness, separator thickness, and lithium metal thickness, as well as electrode tortuosity. Material properties include cathode porosity, current collector porosity, electrolyte dissolved gas CO2 / O2 / H2O concentration, and main reaction interface rate. Charging conditions include the charge / discharge process and ambient temperature. A battery geometric model is established based on the battery geometry and material parameters. Then, advanced mesh generation technology is used to mesh the cell, ensuring high mesh density in key areas such as the electrode surface and gas channels. Subsequently, using numerical solutions based on the finite element method or finite volume method, the partial differential equations describing the complex reactions and transport processes inside the lithium-air battery are discretized and converted into a set of algebraic equations solvable by a computer. By solving these discretized equations, the method can simulate and predict the electrochemical performance of the battery under different charge / discharge rates and ambient temperatures, specifically outputting key performance indicators such as battery capacity, voltage efficiency, and cycle stability. Crucially, the model can assess the distribution of oxygen inside the battery under various operating conditions, which is essential for understanding the reaction mechanism of lithium-air batteries and optimizing gas utilization efficiency. Based on the performance data output by the model, especially the distribution of oxygen inside the battery, this invention provides a set of evaluation criteria to determine whether the current design can effectively promote oxygen transport and utilization while avoiding performance degradation caused by local overheating or excessive local deposition of lithium peroxide. By iteratively iterating the design parameters and rerunning the model, the optimal design of the battery electrodes and gas flow channels is ultimately achieved, ensuring that the battery exhibits the best lifespan and performance in practical applications. The model depicts the entire process of air entering the open cell from the atmosphere, dissolving at the gas-liquid interface to reach the electrolyte, and then diffusing through the electrolyte to the carbon surface to undergo a reduction reaction with lithium ions and electrons, fixing them into lithium peroxide. It also describes the process of lithium ions detaching from the lithium metal anode surface and being transported to the porous cathode surface for reaction under the combined forces of electromigration and diffusion using concentrated solution theory and the BV equation. While increasing electrolyte volume or electrode thickness might intuitively seem to improve battery energy storage capacity during model testing, this practice actually significantly deteriorates the electrochemical kinetics within the battery. Excessive electrolyte or electrode thickness lengthens the transport paths for lithium ions and oxygen, increasing transport resistance and thus slowing down the electrochemical reaction rate, reducing the battery's power output and charge / discharge efficiency. Furthermore, to meet the stringent requirements of practical applications, particularly for high power output and long cycle life, the battery's oxygen dissolution and diffusion capabilities need to be improved by orders of magnitude.This requires us not only to develop novel electrode materials and electrolyte systems with higher oxygen affinity and faster ion conduction speeds at the materials level, but also to innovate in battery structure design. This includes optimizing the porous structure of the electrodes to increase the effective contact area and transport channels for oxygen, and improving the electrolyte flow pattern to accelerate the transport of reactants to the electrode surface and the removal of products. Simultaneously, improving oxygen utilization efficiency is also a key research focus. This involves the design and optimization of catalysts, requiring the development of bifunctional catalysts that can efficiently promote both the oxygen reduction reaction (ORR) and the oxygen generation reaction (OER) to reduce reaction overpotential and improve battery charge-discharge efficiency and cycle stability.

[0135] This embodiment describes a method for updating battery parameters and gas flow channels based on oxygen utilization evaluation indicators, which can effectively optimize the performance of lithium-air batteries.

[0136] Secondly, embodiments of this application provide a lithium-air battery electrochemical simulation device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the lithium-air battery electrochemical simulation method in Embodiment 1 above.

[0137] The following is for reference. Figure 7 The diagram illustrates a structural schematic suitable for implementing the lithium-air battery electrochemical simulation device of the embodiments of this application. The lithium-air battery electrochemical simulation device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 7 The lithium-air battery electrochemical simulation device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0138] like Figure 7As shown, the lithium-air battery electrochemical simulation device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the lithium-air battery electrochemical simulation device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. The following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the lithium-air battery electrochemical simulation equipment to communicate wirelessly or wiredly with other devices to exchange data. Although a lithium-air battery electrochemical simulation equipment with various systems is shown in the figure, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0139] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0140] The lithium-air battery electrochemical simulation equipment provided in this application employs the lithium-air battery electrochemical simulation method described in the above embodiments. This solves the technical problem that current simulation methods cannot accurately simulate the microstructural characteristics within the battery electrodes, resulting in poor simulation performance. Compared with the prior art, the beneficial effects of the lithium-air battery electrochemical simulation equipment provided in this application are the same as those of the lithium-air battery electrochemical simulation equipment provided in the above embodiments. Furthermore, other technical features of this lithium-air battery electrochemical simulation equipment are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0141] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0142] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0143] Thirdly, embodiments of this application provide a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the lithium-air battery electrochemical simulation method in the above embodiments.

[0144] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0145] The aforementioned computer-readable storage medium may be included in the lithium-air battery electrochemical simulation device; or it may exist independently and not assembled into the lithium-air battery electrochemical simulation device.

[0146] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by a lithium-air battery electrochemical simulation device, the lithium-air battery electrochemical simulation device: acquires the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity; solves a set of coupled equations based on the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity as model inputs, wherein the coupled equations are coupled according to the air layer, current collector layer, and cathode layer; and maps the solution results of the coupled equations to the battery geometric model corresponding to the model mesh to determine the battery rate performance.

[0147] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0148] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0149] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0150] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described lithium-air battery electrochemical simulation method. This solves the technical problem that current simulation methods cannot accurately simulate the microstructure characteristics inside the battery electrodes, resulting in poor simulation effects for lithium-air batteries. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the lithium-air battery electrochemical simulation method provided in the above embodiments, and will not be repeated here.

[0151] Fourthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the lithium-air battery electrochemical simulation method described above.

[0152] The computer program product provided in this application can solve the technical problem that current simulation methods cannot accurately simulate the microstructure characteristics inside the battery electrodes, resulting in poor simulation effects for lithium-air batteries. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the lithium-air battery electrochemical simulation method provided in the above embodiments, and will not be repeated here.

[0153] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A method for electrochemical simulation of lithium-air batteries, characterized in that, The lithium-air battery electrochemical simulation method includes: Obtain the positive electrode thickness, positive electrode tortuosity, positive electrode porosity, and current collector porosity; The coupled equations are solved using the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity as model inputs. The coupled equations are coupled based on the air layer, current collector layer, and cathode layer. The solution results of the coupled equations are mapped to the battery geometry model corresponding to the model mesh to determine the battery rate performance.

2. The lithium-air battery electrochemical simulation method as described in claim 1, characterized in that, The step of solving the coupled equations based on the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity as model inputs includes: The coupled equations are discretized using the model mesh of the battery geometric model to obtain an algebraic equation system. Solve the algebraic equations based on the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity to obtain a single-step solution set; If the calculation cutoff condition is met, the single-step solution set is output as the solution result.

3. The lithium-air battery electrochemical simulation method as described in claim 2, characterized in that, The step of solving the system of algebraic equations based on the cathode thickness, cathode tortuosity, cathode porosity, and current collector porosity to obtain a single-step solution set includes: Substituting the air velocity into the first equation at the interface between the air layer and the current collector layer, and substituting the positive electrode porosity and the current collector porosity into the second equation at the interface between the current collector layer and the positive electrode layer, and using the positive electrode thickness, the positive electrode tortuosity, and the current collector thickness as boundary constraints, the single-step solution set is obtained.

4. The lithium-air battery electrochemical simulation method as described in claim 3, characterized in that, The battery geometric model includes an air layer, a current collector layer, a positive electrode layer, a separator layer, and a negative electrode layer. After substituting the positive electrode porosity and the current collector porosity into the second equation at the interface between the current collector layer and the positive electrode layer, the model further includes: Substituting the porosity, the first interface reaction rate, and the electrolyte dissolved gas concentration into the third equation of the diffusion of matter between the positive electrode layer and the separator layer, and substituting the electrolyte dissolved gas concentration and the second interface reaction rate into the fourth equation of the interface between the separator layer and the negative electrode layer, and using the positive electrode thickness, the positive electrode tortuosity, the negative electrode thickness, the separator thickness, and the current collector thickness as boundary constraints, the single-step solution set is obtained.

5. The lithium-air battery electrochemical simulation method as described in claim 4, characterized in that, After substituting the electrolyte dissolved gas concentration and the second interface reaction rate into the fourth equation at the interface between the membrane layer and the negative electrode layer, the method further includes: Substituting the porosity, the first interface reaction rate, and the electrolyte lithium-ion concentration into the fifth equation for lithium-ion diffusion in the positive electrode layer and the separator layer, and using the positive electrode thickness, the positive electrode tortuosity, the negative electrode thickness, the separator thickness, and the current collector thickness as boundary constraints, the single-step solution set is obtained.

6. The lithium-air battery electrochemical simulation method as described in claim 5, characterized in that, The negative electrode layer includes a first negative electrode layer and a negative electrode current collector layer. Substituting the porosity, the first interfacial reaction rate, and the electrolyte lithium-ion concentration into the fifth equation for lithium-ion diffusion in the positive electrode layer and the separator layer, the equation further includes: Substituting the thickness of the positive electrode, the thickness of the current collector, the thickness of the first negative electrode, and the thickness of the negative electrode current collector into the sixth equation of the current collector layer, the positive electrode layer, the first negative electrode layer, and the negative electrode current collector layer, and using the thickness of the positive electrode, the tortuosity of the positive electrode, the thickness of the negative electrode, the thickness of the separator, the thickness of the current collector, the thickness of the first negative electrode, and the thickness of the negative electrode current collector as boundary constraints, the single-step solution set is obtained.

7. The lithium-air battery electrochemical simulation method as described in claim 1, characterized in that, After mapping the solution results of the coupled equation set to the battery geometric model corresponding to the model mesh, the method further includes: In response to the received simulation time value, determine the dissolved gas distribution corresponding to the simulation time value; Based on the dissolved gas distribution corresponding to each of the simulation time values, oxygen utilization evaluation indicators and gas pressure evaluation indicators are determined.

8. The lithium-air battery electrochemical simulation method as described in claim 7, characterized in that, After determining the oxygen utilization evaluation index and the gas pressure evaluation index based on the dissolved gas distribution corresponding to each of the simulation time values, the following steps are included: Based on the oxygen utilization evaluation index, update the cathode thickness and cathode tortuosity in the battery geometry information, and update the current collector porosity and cathode porosity in the battery material parameters to update the gas flow channel of the battery or increase the input gas pressure.

9. A lithium-air battery electrochemical simulation device, characterized in that, The lithium-air battery electrochemical simulation device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the lithium-air battery electrochemical simulation method as described in any one of claims 1 to 8.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the lithium-air battery electrochemical simulation method as described in any one of claims 1 to 8.

11. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the steps of the lithium-air battery electrochemical simulation method as described in any one of claims 1 to 8.

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