A method for composite modeling simulation of a flow battery

Abstract

The application relates to the technical field of liquid flow batteries, and discloses a composite modeling simulation method of a liquid flow battery, which comprises the following steps: step one: establishing an electrochemical model to describe the electrochemical reaction kinetics and charge transfer process in the battery; step two: establishing a fluid dynamics model to describe the flow behavior of the electrolyte; step three: establishing a heat conduction model to describe the heat conduction behavior in the battery; step four: establishing a circuit model to describe the current and voltage relationship between the battery and the external circuit; and step five: coupling the above models to establish an overall coupling model, wherein the electrochemical model, the fluid dynamics model, the heat conduction model and the circuit model are coupled, the physical process and the interaction in the liquid flow battery are more comprehensively described, the accuracy and the reliability of the model are improved, and through the simulation and verification method, the performance and the behavior of the liquid flow battery can be researched by changing the parameters and the conditions in the model.

Description

Technical Field

[0001] The present invention relates to the technical field of liquid flow batteries, and in particular to a composite modeling and simulation method for liquid flow batteries. Background Art

[0002] Flow batteries are batteries that use liquids as electrolytes to store and release electrical energy. Unlike traditional solid-state batteries, flow batteries use liquid electrolytes to store charge, making them more flexible and scalable. A flow battery typically consists of two electrolytic cells, two electrodes, and an intermediate electrolyte. The electrolyte can be a variety of chemicals, such as sulfuric acid, lithium iron, or potassium ion solutions. The two electrolytic cells are connected by an ion exchange membrane or salt bridge. Flow batteries work by converting electrical energy into chemical energy and, when needed, converting chemical energy back into electrical energy. When the battery is charging, current flows through the electrolyte between the electrolytic cells, transferring charge to the chemicals in the electrolyte. When the energy needs to be released, the chemicals react again, releasing charge that flows back through the electrolyte to the original electrolytic cell, generating current. Flow batteries offer several advantages, including adjustable capacity, a high recharge cycle, and simplified maintenance. Furthermore, flow batteries can increase energy density by increasing the electrolyte volume, thereby achieving higher energy storage capacity. However, the performance of flow batteries still needs to be improved, such as increasing energy density, reducing costs and increasing cycle life. Currently, flow batteries have been used in some specific application areas, such as large-scale energy storage systems and electric vehicles.

[0003] Currently, the composite modeling of flow batteries involves multiple physical processes, such as electrochemical reactions, fluid dynamics, and heat conduction. These physical processes are coupled with each other, which increases the complexity of the model. Complex models require more computing resources and time, and their sensitivity to parameters also increases. At the same time, composite modeling of flow batteries requires the estimation of many parameters, such as the rate constant of the electrochemical reaction, the viscosity and conductivity of the electrolyte, etc. However, obtaining accurate parameter values ​​is often difficult because these parameters may be affected by experimental measurement errors and uncertainties. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a composite modeling and simulation method for liquid flow batteries, which solves the problem that the composite modeling of liquid flow batteries involves multiple physical processes, such as electrochemical reactions, fluid dynamics and heat conduction. These physical processes are coupled with each other, which increases the complexity of the model. Complex models require more computing resources and time, and the sensitivity to parameters will also increase.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A composite modeling and simulation method for a flow battery, comprising the following steps:

[0006] Step 1: Establish an electrochemical model to describe the electrochemical reaction kinetics and charge transfer process in the battery;

[0007] Step 2: Establish a fluid dynamics model to describe the flow behavior of the electrolyte;

[0008] Step 3: Establish a heat conduction model to describe the heat conduction behavior in the battery;

[0009] Step 4: Build a circuit model to describe the current and voltage relationship between the battery and the external circuit;

[0010] Step 5: Couple the electrochemical model, fluid dynamics model, heat conduction model, and circuit model to establish an overall coupled model;

[0011] Step 6: Perform simulation and verification to study the performance and behavior of the battery by changing parameter conditions and compare them with actual test data.

[0012] Preferably, in step 1, the electrochemical model is based on the kinetic equation and the electrochemical equilibrium equation, and the electrochemical model includes the following steps:

[0013] Focus on the kinetic parameters of exchange current density and transfer coefficient. Through linear sweep voltammetry and Tafel plot analysis, consider the influence of electrode surface microstructure and adsorption phenomena on the parameters, establish the relationship between the parameters and various influencing factors, and lay the foundation for subsequent models.

[0014] Based on the physical structural parameters of planar electrodes and porous electrodes combined with the electrolyte flow rate conditions, the calculation formula for the diffusion layer thickness was revised and improved, and a material flux equation considering convection and diffusion was established to accurately calculate the flux of materials near the electrode surface.

[0015] The electrode reaction rate based on the Butler-Volmer equation is coupled with the material flux equation, and the mutual influence between the two is considered to achieve a dynamic simulation of the electrode surface potential, current density, and material concentration distribution over time. The model is verified by comparing with the charge and discharge experimental data of the liquid flow battery, and the model parameters are optimized.

[0016] According to the electrolyte concentration, the Debye-Hückel theory and Pitzer equation are selected to calculate the activity coefficient. Considering the influence of multiphase equilibrium on the electrode potential, the effective concentration is calculated through the relevant equilibrium constant.

[0017] Preferably, in step 2, the fluid dynamics model is based on the Navier-Stokes equations and the mass conservation equation, and the fluid dynamics model includes the following steps:

[0018] The Navier-Stokes equations are expanded in a three-dimensional Cartesian coordinate system. The parameter values ​​are determined based on the flow channel shape, size, and operating conditions of the battery. No-slip boundary conditions are used for the flow channel walls, and velocity boundary conditions at the flow channel inlet and outlet are set according to the actual flow rate. Based on this, a framework for solving the equations is constructed.

[0019] The mass conservation equation is introduced. For incompressible electrolytes, its simplified form is combined with the Navier-Stokes equation to describe the flow of the electrolyte. By discretizing the equation and using the finite volume method, the flow velocity and pressure distribution of the electrolyte at different positions in the flow channel are solved.

[0020] Considering the influence of heat that may be generated during battery charging and discharging on the physical properties of the electrolyte, the changes are fed back into the Navier-Stokes equation and mass conservation equation to change the flow characteristics and analyze their impact on the overall flow behavior.

[0021] Preferably, in step 3, the heat conduction model is based on the heat conduction equation, and the heat conduction model includes the following steps:

[0022] Based on the heat conduction equation in a rectangular coordinate system, the parameters involved are clearly defined, including the density, specific heat capacity, temperature and thermal conductivity of the material, as well as the heat generation rate per unit volume;

[0023] By calculating the reaction enthalpy change and reaction rate, taking into account the specific conditions and reaction volume of each reaction, and through relevant fluid dynamics theory calculations, the heat generation source can be accurately calculated;

[0024] The boundary conditions are set according to the actual heat dissipation conditions of the battery, so that the model can accurately simulate the heat transfer between the battery and the surrounding environment.

[0025] Preferably, in step 4, the circuit model is based on Ohm's law and Kirchhoff's voltage law, and the circuit model includes the following steps:

[0026] According to Ohm's law Determine the ohmic resistance inside the flow battery using a combination of AC impedance spectroscopy and a method based on the resistivity of the material and the battery's structural dimensions.

[0027] In a loop including a flow battery and an external circuit, a voltage balance equation of the entire loop is established according to Kirchhoff's voltage law ∑V=0.

[0028] Preferably, in step five, the overall coupled model is used to simultaneously solve the equations of the electrochemical model, the fluid dynamics model, the heat conduction model, and the circuit model. The simultaneous solution method includes the following steps:

[0029] The finite element method is used to discretize the geometric model of the entire flow battery, dividing the battery components into small units. The equations of each model are approximately solved in each unit. For battery structures with complex geometries, adaptive meshing technology is used, and finer meshes are used in areas where physical quantities change dramatically to improve solution accuracy.

[0030] Given initial guesses of various physical quantities, the initial values ​​are obtained based on empirical data, simplified model calculations, or experimental measurements;

[0031] Based on the current temperature, flow rate and electrode potential information, the electrode reaction rate and substance concentration changes in the electrochemical model are solved. The flow field and pressure distribution updates in the fluid dynamics model are calculated using the current flow rate and substance concentration. Based on the reaction heat calculated by the electrochemical model and the viscous dissipation heat in the fluid dynamics model, the heat generation rate in the heat conduction model is updated, and the temperature distribution update is solved. Based on the new electrode potential, temperature and internal resistance information, the current and voltage are updated through the circuit model. After updating the physical quantities of each model, the convergence conditions are checked. The convergence conditions can be based on the rate of change of the physical quantities or the residual norm. If the convergence conditions are not met, the next iteration is continued until convergence is achieved.

[0032] For the discretized system of equations, select a linear or nonlinear equation solver, use an iterative solution method for the linear system of equations, and use the Newton-Raphson iterative method for the nonlinear system of equations.

[0033] Working Principle: First, an electrochemical model is established to describe the electrochemical reaction kinetics and charge transfer processes in the battery. Kinetic equations and electrochemical equilibrium equations are used to simulate the electrochemical reaction rates and charge transfer processes. Next, a fluid dynamics model is established to describe the flow behavior of the electrolyte. The Navier-Stokes equations and mass conservation equations are used to simulate the flow of electrolyte in the battery. Next, a heat conduction model is established to describe the heat conduction behavior in the battery. Heat conduction in the battery is simulated using the heat conduction equations. Next, a circuit model is established to describe the current and voltage relationship between the battery and the external circuit. The battery current and voltage changes are simulated using Ohm's law and Kirchhoff's voltage law. These models are coupled to establish an overall coupled model. The equations for the electrochemical, fluid dynamics, heat conduction, and circuit models are solved simultaneously, taking into account their interactions and coupling effects. Simulations and verification are performed to study the battery's performance and behavior by varying model parameters and conditions. The simulation results are compared with actual test data to verify the accuracy and reliability of the model; by simulating the interaction of electrochemical reactions, fluid flow, heat conduction and circuit behavior, battery performance can be evaluated, design and control strategies can be optimized, and battery application and development can be guided.

[0034] The present invention provides a composite modeling and simulation method for a flow battery. It has the following beneficial effects:

[0035] 1. By coupling the electrochemical model, fluid dynamics model, heat conduction model and circuit model, the present invention can comprehensively and deeply consider the complex physical processes and interactions within the liquid flow battery. The combined coupling of these four models overcomes the problem that traditional single models or simple combination models cannot fully consider the mutual influence of multiple physical processes, thereby significantly improving the accuracy and reliability of the model.

[0036] 2. The present invention can flexibly change the parameters and conditions in the model through simulation and verification methods. Parameter research can reveal the working principle of the battery under different working conditions, helping researchers and engineers to deeply understand the quantitative relationship between various physical processes inside the battery. Based on the in-depth understanding of battery performance and behavior, the design and control strategy of the battery can be further optimized. In terms of design, the impact of different electrode materials, electrolyte compositions and battery structures on battery performance can be evaluated, thereby guiding the selection of the best material and structural design. In terms of control strategy, the optimal charge and discharge control parameters can be determined based on the model simulation results to improve the performance and life of the battery.

[0037] 3. The present invention utilizes the composite modeling and simulation method to comprehensively evaluate the impact of different designs and control strategies on battery performance. At the design level, it can simulate the performance of different battery structures under various working conditions, so as to find the structural design that is most conducive to improving battery performance. In terms of material selection, it can evaluate the impact of different electrode materials, electrolyte additives, etc. on battery performance. In terms of operating strategies, it can simulate the impact of different charging and discharging strategies on battery life and performance. By analyzing the temperature changes and polarization conditions of the battery under different strategies, the optimal operating strategy can be determined, the irreversible damage of the battery can be reduced, and the overall performance and service life of the battery can be improved.

[0038] 4. Before actual manufacturing and testing, the present invention uses the composite modeling and simulation method to predict and evaluate the performance and behavior of the battery. A large number of virtual tests can be performed on different design schemes in the laboratory stage, avoiding the high cost and time consumption brought about by direct actual manufacturing and testing. At the same time, for the optimization of some key parameters, the approximate range can be determined through simulation before actual testing, which greatly reduces the number and cost of experiments, improves R&D efficiency, and accelerates the process from R&D to application of batteries.

[0039] 5. The present invention deeply analyzes the internal working mechanism of liquid flow batteries from multiple physical levels by establishing electrochemical, fluid dynamics, heat conduction and circuit models. The multi-dimensional analysis helps to reveal the complex physical principles behind battery performance and behavior. Based on a clear understanding of these mechanisms, targeted improvement and optimization suggestions can be put forward, providing a theoretical basis and directional guidance for the continuous improvement and innovation of liquid flow battery technology. DETAILED DESCRIPTION

[0040] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0041] The present invention provides a composite modeling and simulation method for liquid flow batteries. By coupling the electrochemical model, fluid dynamics model, heat conduction model, and circuit model, it can comprehensively and deeply consider the complex physical processes and interactions within the liquid flow battery, thereby improving the accuracy and reliability of the model. The following details the various steps of the method of the present invention.

[0042] Step 1: Establish an electrochemical model to describe the electrochemical reaction kinetics and charge transfer process in the battery;

[0043] In step 1, the electrochemical model is based on the kinetic equation and the electrochemical equilibrium equation. The electrochemical model includes the following steps:

[0044] Focus on the kinetic parameters of exchange current density and transfer coefficient. Through linear sweep voltammetry and Tafel plot analysis, consider the influence of electrode surface microstructure and adsorption phenomena on the parameters, establish the relationship between the parameters and various influencing factors, and lay the foundation for subsequent models.

[0045] Based on the physical structural parameters of planar electrodes and porous electrodes combined with the electrolyte flow rate conditions, the calculation formula for the diffusion layer thickness was revised and improved, and a material flux equation considering convection and diffusion was established to accurately calculate the flux of materials near the electrode surface.

[0046] The electrode reaction rate based on the Butler-Volmer equation is coupled with the material flux equation, and the mutual influence between the two is considered to achieve a dynamic simulation of the electrode surface potential, current density, and material concentration distribution over time. The model is verified by comparing with the charge and discharge experimental data of the liquid flow battery, and the model parameters are optimized.

[0047] According to the electrolyte concentration, the Debye-Hückel theory and Pitzer equation are selected to calculate the activity coefficient. Considering the influence of multiphase equilibrium on the electrode potential, the effective concentration is calculated by the relevant equilibrium constant.

[0048] Specifically, the electrochemical reaction inside the flow battery reflects its core working principle. The electrochemical model aims to accurately describe the electrochemical reaction kinetics and charge transfer process in the battery. This electrochemical model is constructed based on the kinetic equation and electrochemical equilibrium equation.

[0049] For the reaction on the electrode surface, the Butler-Volmer equation is used to describe the relationship between the electrode reaction rate and the electrode potential. According to different electrode materials and reaction types, the corresponding reaction kinetic parameters, such as the exchange current density, are determined. Taking the common all-vanadium liquid flow battery as an example, the reaction kinetic parameters of the positive and negative electrodes vary due to the different oxidation states of vanadium ions. For the positive electrode VO2 + / VO2 + Reaction, through experimental measurement and theoretical analysis to determine the exchange current density value under specific temperature and electrolyte concentration conditions, considering the effect of mass transfer on the reaction rate, introducing Fick's law to describe the diffusion process of reactants and products near the electrode surface, analyzing the effect of the ion concentration gradient in the electrolyte on the diffusion flux of the reactants, and determining parameters such as the diffusion coefficient;

[0050] The diffusion coefficients of different ions in different electrolyte systems can be measured and fitted using the rotating disk electrode method. The relationship between the electrode potential and the ion activity in the electrolyte can be described based on the Nernst equation. For each electrode reaction in the flow battery, the electrode equilibrium potential can be accurately calculated based on its stoichiometric relationship and ion activity. In electrolytes where multiple ions coexist, the Debye-Hückel theory or the more complex activity coefficient model Pitzer equation can be used to calculate the ion activity coefficient, considering the influence of ionic interactions on the activity coefficient, thereby more accurately determining the electrode equilibrium potential.

[0051] Step 2: Establish a fluid dynamics model to describe the flow behavior of the electrolyte;

[0052] In step 2, the fluid dynamics model is based on the Navier-Stokes equations and the mass conservation equation. The fluid dynamics model includes the following steps:

[0053] The Navier-Stokes equations are expanded in a three-dimensional Cartesian coordinate system. The parameter values ​​are determined based on the flow channel shape, size, and operating conditions of the battery. No-slip boundary conditions are used for the flow channel walls, and velocity boundary conditions at the flow channel inlet and outlet are set according to the actual flow rate. Based on this, a framework for solving the equations is constructed.

[0054] The mass conservation equation is introduced. For incompressible electrolytes, its simplified form is combined with the Navier-Stokes equation to describe the flow of the electrolyte. By discretizing the equation and using the finite volume method, the flow velocity and pressure distribution of the electrolyte at different positions in the flow channel are solved.

[0055] Considering the influence of heat that may be generated during battery charging and discharging on the physical properties of the electrolyte, the changes are fed back into the Navier-Stokes equation and mass conservation equation to change the flow characteristics and analyze their impact on the overall flow behavior.

[0056] Specifically, the flow behavior of the electrolyte in the flow battery has a crucial impact on the battery performance. The fluid dynamics model is based on the Navier-Stokes equation and the mass conservation equation to describe this behavior. In a three-dimensional Cartesian coordinate system, considering the flow of the electrolyte in the battery flow channel, for incompressible fluids, the Navier-Stokes equation can be expressed as:

[0057]

[0058] Among them, ρ is the electrolyte density, u is the flow velocity vector, t is time, p is pressure, μ is the dynamic viscosity, and F is the volume force. In liquid flow batteries, it is necessary to determine the various parameters in the equation based on the shape, size and flow velocity range of the battery flow channel, and the presence or absence of an external magnetic field. For the boundary conditions of the flow channel wall, a no-slip boundary condition is adopted, that is, the flow velocity of the electrolyte at the wall is zero. At the inlet and outlet of the flow channel, the corresponding flow velocity boundary conditions are set according to the actual flow rate. For example, for a given electrolyte flow rate and flow channel cross-sectional area, the average flow velocity at the inlet can be calculated and used as the inlet boundary condition.

[0059] In addition, the mass conservation equation can be expressed as:

[0060]

[0061] Combined with the Navier-Stokes equations, the conservation of mass during the electrolyte flow is ensured. During the simulation process, the finite volume method is used to solve the flow velocity and pressure distribution of the electrolyte at various positions in the flow channel by discretizing the above equations.

[0062] Step 3: Establish a heat conduction model to describe the heat conduction behavior in the battery;

[0063] In step 3, the heat conduction model is based on the heat conduction equation. The heat conduction model includes the following steps:

[0064] Based on the heat conduction equation in a rectangular coordinate system, the parameters involved are clearly defined, including the density, specific heat capacity, temperature and thermal conductivity of the material, as well as the heat generation rate per unit volume;

[0065] By calculating the reaction enthalpy change and reaction rate, taking into account the specific conditions and reaction volume of each reaction, and through relevant fluid dynamics theory calculations, the heat generation source can be accurately calculated;

[0066] The boundary conditions are set according to the actual heat dissipation conditions of the battery, so that the model can accurately simulate the heat transfer between the battery and the surrounding environment.

[0067] Specifically, the heat conduction model is used to describe the heat conduction behavior in the battery. It is based on the heat conduction equation. The flow battery generates heat during the charging and discharging process. The generation, transfer, and distribution of heat will affect the performance and safety of the battery. The heat conduction equation can be expressed in a rectangular coordinate system as follows:

[0068]

[0069] Where ρ is the material density, c p is the specific heat capacity, T is the temperature, k is the thermal conductivity, and q is the heat generation rate per unit volume. For liquid flow batteries, it is necessary to consider the thermophysical properties of different components such as electrodes, electrolytes and diaphragms, and determine their parameters such as density, specific heat capacity and thermal conductivity respectively. The heat generation rate q mainly comes from the irreversible heat of electrochemical reactions, the viscous dissipation heat of electrolyte flow, and the heat exchange between the battery and the environment. The heat generation rate is accurately calculated through the reaction heat calculation method in the electrochemical model, the viscous dissipation calculation in the fluid dynamics model, and the consideration of the heat transfer coefficient between the battery and the environment. At the boundary of the battery, the boundary temperature or heat flux boundary condition is set according to the actual heat dissipation conditions. For example, if the battery adopts air cooling, the heat flux boundary condition on the battery surface is set according to the air temperature and the convective heat transfer coefficient. If it is natural heat dissipation, the boundary condition is determined according to the ambient temperature and the radiation heat transfer characteristics of the battery surface.

[0070] Step 4: Build a circuit model to describe the current and voltage relationship between the battery and the external circuit;

[0071] In step 4, the circuit model is based on Ohm's law and Kirchhoff's voltage law. The circuit model includes the following steps:

[0072] According to Ohm's law Determine the ohmic resistance inside the flow battery using a combination of AC impedance spectroscopy and a method based on the resistivity of the material and the battery's structural dimensions.

[0073] In a loop including a flow battery and an external circuit, a voltage balance equation of the entire loop is established according to Kirchhoff's voltage law ∑V=0.

[0074] Specifically, the circuit model describes the current and voltage relationship between the battery and the external circuit, which is based on Ohm's law and Kirchhoff's voltage law. According to Ohm's law:

[0075]

[0076] In flow batteries, the internal ohmic resistance of the battery, including electrode resistance, electrolyte resistance, and contact resistance, is considered. The resistance values ​​of various parts of the battery are determined by combining AC impedance spectroscopy and theoretical calculations.

[0077] For different charge and discharge currents, the voltage drop inside the battery is calculated to obtain the relationship between the terminal voltage and current of the battery. In the loop containing the flow battery and the external circuit, according to Kirchhoff's voltage law:

[0078] ∑V=0,

[0079] Consider the battery's electromotive force, internal voltage drop, and the voltage across external circuit components to establish a voltage balance equation for the entire circuit. For example, in a simple circuit consisting of a flow battery and a resistive load, the battery electromotive force minus the voltage drop caused by the internal ohmic resistance of the battery equals the voltage across the load resistor, or E-IR. int =IR load , where E is the battery electromotive force, R int is the internal resistance of the battery, R load is the load resistance.

[0080] Step 5: Couple the electrochemical model, fluid dynamics model, heat conduction model, and circuit model to establish an overall coupled model;

[0081] In step 5, the overall coupled model is used to simultaneously solve the equations of the electrochemical model, fluid dynamics model, heat conduction model, and circuit model. The simultaneous solution method includes the following steps:

[0082] The finite element method is used to discretize the geometric model of the entire flow battery, dividing the battery components into small units. The equations of each model are approximately solved in each unit. For battery structures with complex geometries, adaptive meshing technology is used, and finer meshes are used in areas where physical quantities change dramatically to improve solution accuracy.

[0083] Given initial guesses of various physical quantities, the initial values ​​are obtained based on empirical data, simplified model calculations, or experimental measurements;

[0084] Based on the current temperature, flow rate and electrode potential information, the electrode reaction rate and substance concentration changes in the electrochemical model are solved. The flow field and pressure distribution updates in the fluid dynamics model are calculated using the current flow rate and substance concentration. Based on the reaction heat calculated by the electrochemical model and the viscous dissipation heat in the fluid dynamics model, the heat generation rate in the heat conduction model is updated, and the temperature distribution update is solved. Based on the new electrode potential, temperature and internal resistance information, the current and voltage are updated through the circuit model. After updating the physical quantities of each model, the convergence conditions are checked. The convergence conditions can be based on the rate of change of the physical quantities or the residual norm. If the convergence conditions are not met, the next iteration is continued until convergence is achieved.

[0085] For the discretized system of equations, select a linear or nonlinear equation solver, use an iterative solution method for the linear system of equations, and use the Newton-Raphson iterative method for the nonlinear system of equations.

[0086] Specifically, the overall coupling model realizes the comprehensive simulation of the multi-physical field behavior of the flow battery by jointly solving the equations of the electrochemical model, fluid dynamics model, heat conduction model and circuit model. During the coupling process, the electrode potential and reaction rate in the electrochemical model will affect the heat generation of the electrochemical reaction, thereby affecting the heat generation rate in the heat conduction model. At the same time, the temperature distribution in the heat conduction model will in turn affect the reaction kinetic parameters and physical properties of the electrolyte in the electrochemical model. The electrolyte flow rate and pressure distribution in the fluid dynamics model will affect the material transfer process on the electrode surface, thereby affecting the reaction rate in the electrochemical model. The ion consumption and generation in the electrochemical reaction process will change the concentration distribution of the electrolyte, thereby affecting the mass conservation in the fluid dynamics model and the source term in the Navier-Stokes equation.

[0087] The current and voltage in the circuit model are interrelated with the electrode potential and reaction current in the electrochemical model. At the same time, the temperature change of the battery will affect the internal resistance of the battery, and thus affect the voltage-current characteristics of the battery. A multi-physics field coupling solution algorithm, such as a multi-field coupling solver based on the finite element method, is used to discretize the geometric model of the battery and solve the equations of the above four models simultaneously on each discrete unit. During the iterative solution process, the equation coefficients and boundary conditions of the current step are updated according to the values ​​of the physical quantities calculated in the previous step until a stable solution is obtained through convergence. For example, in each time step, the reaction rate in the electrochemical model is first calculated based on the temperature, flow rate and other information of the previous time step. The heat generation rate is then updated based on the reaction rate, and the heat conduction model is solved to obtain a new temperature distribution. This process is repeated until the physical quantities no longer change within a certain error range.

[0088] Step 6: Perform simulation and verification to study the performance and behavior of the battery by changing parameter conditions and compare them with actual test data.

[0089] Specifically, the performance and behavior of the battery are studied by changing the parameter conditions and compared with the actual test data to verify the accuracy and reliability of the model. During the simulation process, multiple parameters can be changed, such as electrolyte concentration, flow rate, charge and discharge current density, and battery temperature. For example, the electrolyte flow rate is changed to observe the changes in performance indicators such as battery voltage efficiency and energy efficiency. When the flow rate increases, the material transfer of the electrolyte on the electrode surface is enhanced, which may improve the performance of the battery, but it may also increase the flow resistance and energy consumption. Through simulation, this change trend can be analyzed in detail to determine the optimal operating parameter range, change the charge and discharge current density, and study the polarization phenomenon of the battery. At high current density, the battery's ohmic polarization, activation polarization, and concentration polarization will increase. Through simulation, we can gain an in-depth understanding of different polarities. The impact of chemistry on battery voltage and performance provides a basis for the optimal design of the battery. Actual liquid flow battery charge and discharge experiments are carried out. High-precision measuring instruments are used to measure the battery voltage, current, temperature, and electrolyte flow rate parameters. These actual test data are compared with the simulation results. For example, the voltage-time curve of the battery under the same charge and discharge conditions is compared. If the simulation results and the actual test data have good consistency in both trend and value, it means that the model has high accuracy. If there is a deviation, the cause of the deviation is analyzed. It may be that the values ​​of certain parameters in the model are inaccurate, or some minor factors are ignored in the modeling process. According to the analysis results, the model is further improved and optimized to improve the accuracy of the model so that it can better reflect the actual performance and behavior of the liquid flow battery.

[0090] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the spirit of the principles and methods of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A composite modeling and simulation method for a flow battery, characterized in that: The following steps are involved: Step 1: Establish an electrochemical model to describe the electrochemical reaction kinetics and charge transfer process in the battery; The electrochemical model is based on a kinetic equation and an electrochemical equilibrium equation, and includes the following steps: Focus on the kinetic parameters of exchange current density and transfer coefficient. Through linear sweep voltammetry and Tafel plot analysis, consider the influence of electrode surface microstructure and adsorption phenomena on the parameters, establish the relationship between the parameters and various influencing factors, and lay the foundation for subsequent models. Based on the physical structural parameters of planar electrodes and porous electrodes combined with the electrolyte flow rate conditions, the calculation formula for the diffusion layer thickness was revised and improved, and a material flux equation considering convection and diffusion was established to accurately calculate the flux of materials near the electrode surface. The electrode reaction rate based on the Butler-Volmer equation is coupled with the material flux equation, and the mutual influence between the two is considered to achieve a dynamic simulation of the electrode surface potential, current density, and material concentration distribution over time. The model is verified by comparing with the charge and discharge experimental data of the liquid flow battery, and the model parameters are optimized. According to the electrolyte concentration, the Debye-Hückel theory and Pitzer equation are used to calculate the activity coefficient. The effect of multiphase equilibrium on the electrode potential is considered, and the effective concentration is calculated by the relevant equilibrium constant. Step 2: Establish a fluid dynamics model to describe the flow behavior of the electrolyte; the fluid dynamics model is based on the Navier-Stokes equations and the mass conservation equation, and the fluid dynamics model includes the following steps: The Navier-Stokes equations are expanded in a three-dimensional Cartesian coordinate system. The parameter values ​​are determined based on the shape, size, and operating conditions of the flow channel of the battery. No-slip boundary conditions are applied to the flow channel walls, and the flow velocity boundary conditions at the flow channel inlet and outlet are set according to the actual flow rate. Based on this, a framework for solving the equations is constructed. The mass conservation equation is introduced. For incompressible electrolytes, its simplified form is combined with the Navier-Stokes equation to describe the flow of the electrolyte. By discretizing the equation and using the finite volume method, the flow velocity and pressure distribution of the electrolyte at different positions in the flow channel are solved. Considering the effect of heat that may be generated during battery charging and discharging on the physical properties of the electrolyte, the changes are fed back into the Navier-Stokes equation and mass conservation equation to change the flow characteristics and analyze their impact on the overall flow behavior; Step 3: Establish a heat conduction model to describe the heat conduction behavior in the battery; Step 4: Build a circuit model to describe the current and voltage relationship between the battery and the external circuit; Step 5: Couple the electrochemical model, the fluid dynamics model, the heat conduction model, and the circuit model to establish an overall coupled model; the overall coupled model simultaneously solves the equations of the electrochemical model, the fluid dynamics model, the heat conduction model, and the circuit model, and the simultaneous solution method includes the following steps: The finite element method is used to discretize the geometric model of the entire flow battery, dividing the battery components into small units. The equations of each model are approximately solved in each unit. For battery structures with complex geometries, adaptive meshing technology is used, and finer meshes are used in areas where physical quantities change dramatically to improve solution accuracy. Given initial guesses of various physical quantities, the initial values ​​are obtained based on empirical data, simplified model calculations, or experimental measurements; Based on the current temperature, flow rate and electrode potential information, the electrode reaction rate and substance concentration changes in the electrochemical model are solved. The flow field and pressure distribution updates in the fluid dynamics model are calculated using the current flow rate and substance concentration. Based on the reaction heat calculated by the electrochemical model and the viscous dissipation heat in the fluid dynamics model, the heat generation rate in the heat conduction model is updated, and the temperature distribution update is solved. Based on the new electrode potential, temperature and internal resistance information, the current and voltage are updated through the circuit model. After updating the physical quantities of each model, the convergence conditions are checked. The convergence conditions can be based on the rate of change of the physical quantities or the residual norm. If the convergence conditions are not met, the next iteration is continued until convergence is achieved. For the discretized equation system, select linear or nonlinear equation solver, use iterative solution method for linear equation system, and use Newton-Raphson iteration method for nonlinear equation system; Step 6: Perform simulation and verification to study the performance and behavior of the battery by changing parameter conditions and compare them with actual test data.

2. The composite modeling and simulation method for a flow battery according to claim 1, characterized in that: In step 3, the heat conduction model is based on the heat conduction equation, and the heat conduction model includes the following steps: Based on the heat conduction equation in a rectangular coordinate system, the parameters involved are clearly defined, including the density, specific heat capacity, temperature and thermal conductivity of the material, as well as the heat generation rate per unit volume; By calculating the reaction enthalpy change and reaction rate, taking into account the specific conditions and reaction volume of each reaction, and through relevant fluid dynamics theory calculations, the heat generation source can be accurately calculated; The boundary conditions are set according to the actual heat dissipation conditions of the battery, so that the model can accurately simulate the heat transfer between the battery and the surrounding environment.

3. The composite modeling and simulation method for a flow battery according to claim 1, characterized in that: In step 4, the circuit model is based on Ohm's law and Kirchhoff's voltage law, and the circuit model includes the following steps: According to Ohm's law Determine the ohmic resistance inside the flow battery using a combination of AC impedance spectroscopy and a method based on the resistivity of the material and the battery's structural dimensions. In a loop including a flow battery and an external circuit, a voltage balance equation of the entire loop is established according to Kirchhoff's voltage law ∑V=0.

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