Method and apparatus for determining flow battery electrolyte concentration

Abstract

The application provides a method and device for determining the concentration of electrolyte of a flow battery. The relationship between the viscosity of the electrolyte and the concentration of the active substance is fitted to determine the hydrodynamic radius of the active substance; the ionic conductivity of the active substance is determined based on the inverse relationship between the self-diffusion coefficient of the active substance and the viscosity of the electrolyte and the hydrodynamic radius; a model for the change of the concentration of the active substance in the electrolyte of the positive and negative electrodes of the flow battery with time is established based on the law of conservation of mass and the ionic conductivity; the current and energy efficiency parameters of the battery are determined based on the concentration of the active substance to determine the target concentration through the energy efficiency parameters. The scheme establishes a dynamic model for the change of the concentration of the active substance in the charging and discharging process, monitors the battery state in real time according to the model, optimizes the electrolyte formula through performance evaluation, determines the optimal concentration of the active substance of the electrolyte, improves the efficiency of the electrolyte formula design and performance evaluation, and reduces the research and production cost.

Description

[0001] This application is a divisional application of the invention patent application with the application number of 202411209851.7, the application date of 2024-08-30, and the invention name of "A method and device for determining the concentration of electrolyte of flow battery". TECHNICAL FIELD

[0002] The present application relates to the field of flow battery, in particular, to a method and device for determining the concentration of electrolyte of flow battery. BACKGROUND

[0003] The concentration of active substances in the electrolyte of the flow battery is an important factor affecting the energy density, system efficiency and electrolyte utilization rate: when the concentration is too low, the active substances carried in the unit volume of electrolyte are less, and the energy density of the flow battery is lower. When the concentration of active substances is high, the energy density is improved, however, high concentration of active substances will significantly increase the viscosity of electrolyte, increase the pump power loss, and thus reduce the system efficiency; too high concentration of active substances will also reduce the ionic conductivity of electrolyte, increase the ohmic resistance of battery, cause high ohmic polarization of battery, and affect the efficiency of battery and the utilization rate of electrolyte.

[0004] On the other hand, the concentration of supporting electrolyte salt ions in the electrolyte of the flow battery will also significantly affect the energy efficiency and system efficiency of the battery. When the concentration of supporting electrolyte salt ions is too low, the viscosity of electrolyte is low, the pump power loss is low, and the system efficiency is high, but the ionic conductivity is low, and the ohmic polarization of battery is large, and the energy efficiency is low; higher salt concentration can improve the ionic conductivity of electrolyte, thereby improving the energy efficiency, but high concentration will cause the viscosity of electrolyte to increase, resulting in large pump power loss and reducing the system efficiency.

[0005] Therefore, in order to comprehensively consider the energy density, energy efficiency, system efficiency and electrolyte utilization rate of the flow battery, it is necessary to optimize the electrolyte formula. In practice, people often rely on experiments to design and find the optimal electrolyte formula, however, there are many choices of active substances and supporting electrolytes in the electrolyte, and the combination of formula is extremely complex, the experiment is extremely time-consuming and material-consuming, and the optimal formula obtained by experiment is only suitable for specific battery and experimental conditions. When the battery structure or temperature conditions change, experiments need to be optimized again to determine the electrolyte concentration that can meet the requirements or has the optimal performance.

[0006] However, this way often requires high time cost and material cost, and the low experimental reaction efficiency will affect the progress of the whole research and production. Therefore, there is a problem in the prior art that the performance evaluation of the electrolyte of the flow battery is not accurate and efficient enough, and it is difficult to determine the optimal electrolyte concentration at low cost and high efficiency in the research and production of the flow battery. SUMMARY

[0007] Embodiments of the present application provide a method and device for determining the concentration of electrolyte of a flow battery, thereby at least partially solving the problem of inaccurate and inefficient performance evaluation of electrolyte of a flow battery.

[0008] Other features and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.

[0009] According to an aspect of the present application, a method for determining the concentration of electrolyte of a flow battery is provided, comprising:

[0010] fitting the relationship between the viscosity of the electrolyte and the concentration of the active substance to determine the hydrodynamic radius of the active substance; determining the ionic conductivity of the active substance in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, and the hydrodynamic radius; establishing a model of the change of the concentration of the active substance over time during the charging and discharging process of the positive and negative electrolyte of the flow battery based on the conservation of mass theory and the ionic conductivity, and obtaining the concentration of the active substance corresponding to the current time according to the change model; determining the current battery voltage based on the concentration of the active substance; and determining the energy efficiency parameter of the battery based on the battery voltage, so as to determine the target concentration of the active substance through the energy efficiency parameter.

[0011] In the present application, based on the foregoing scheme, the determination of the energy efficiency parameter of the battery based on the battery voltage comprises: determining the pressure difference of the electrolyte flowing through the porous electrode based on the permeability of the porous electrode, the cross-sectional area of the electrode, and the height of the electrode, as one of the energy efficiency parameters.

[0012] In the present application, based on the foregoing scheme, after the determination of the energy efficiency parameter of the battery based on the battery voltage, it further comprises: determining the utilization rate of the electrolyte based on the discharge current corresponding to the current time, the concentration of the active substance, and the volume of the electrolyte.

[0013] In the present application, based on the foregoing scheme, the fitting of the relationship between the viscosity of the electrolyte and the concentration of the active substance to determine the hydrodynamic radius of the active substance comprises: Higgin's equation fitting of the relationship between the viscosity of the electrolyte and the concentration of the active substance to determine the hydrodynamic radius of the active substance.

[0014] In the present application, based on the foregoing scheme, the ion conductivity of the active substance in the electrolyte is determined based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, and the hydrodynamic radius, comprising: determining the self-diffusion coefficient of the active substance based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, and the absolute temperature, the hydrodynamic radius of the active substance; determining the ion conductivity of the electrolyte by the Nernst-Einstein equation based on the self-diffusion coefficient, and the number of cations and anions in the active substance and the number of charges they carry.

[0015] In the present application, based on the foregoing scheme, the concentration of the active substance in the electrolyte of the positive and negative electrodes of the flow battery changes with time during the charging and discharging process is established based on the mass conservation theory and the ion conductivity, and the concentration of the active substance corresponding to the current time is obtained according to the change model, comprising: generating a change equation based on the mass conservation theory, the concentration of the active substance in the electrolyte of the positive and negative electrodes of the flow battery during the charging and discharging process, the volume of the electrolyte and the volume flow rate, as the change model; determining the concentration of the active substance in the electrode and the liquid storage tank based on the change equation.

[0016] In the present application, based on the foregoing scheme, the current battery voltage is determined based on the concentration of the active substance, comprising: determining the overpotential of the battery at the current time based on the battery parameters; determining the open circuit voltage of the battery based on the concentration of the active substance and the equilibrium potential of the battery under standard conditions; determining the battery voltage based on the overpotential and the open circuit voltage.

[0017] According to one aspect of the present application, a device for determining the concentration of electrolyte of a flow battery is provided, comprising:

[0018] The fitting unit is configured to fit the relationship between the viscosity of the electrolyte and the concentration of the active substance, and determine the hydrodynamic radius of the active substance.

[0019] The conductive unit is configured to determine the ion conductivity of the active substance in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, and the hydrodynamic radius.

[0020] The model unit is configured to establish a change model of the concentration of the active substance with time during the charging and discharging process of the electrolyte of the positive and negative electrodes of the flow battery based on the mass conservation theory and the ion conductivity, and obtain the concentration of the active substance corresponding to the current time according to the change model.

[0021] The voltage unit is configured to determine the current battery voltage based on the concentration of the active substance.

[0022] A parameter unit is configured to determine an energy efficiency parameter of the battery based on the battery voltage, so as to determine a target concentration of the active material through the energy efficiency parameter.

[0023] According to an aspect of the present application, a computer readable medium is provided, which stores a computer program. The computer program is executed by a processor to implement the method for determining the concentration of the electrolyte of the flow battery as described in the above embodiments.

[0024] According to an aspect of the present application, an electronic device is provided, which comprises one or more processors, and a storage device configured to store one or more programs. The one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method for determining the concentration of the electrolyte of the flow battery as described in the above embodiments.

[0025] According to an aspect of the present application, a computer program product or a computer program is provided, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and executes the computer instructions, so that the computer device performs the method for determining the concentration of the electrolyte of the flow battery as provided in the various optional implementation manners.

[0026] In the technical solution of the present application, the relationship between the viscosity of the electrolyte and the concentration of the active material is fitted to determine the hydrodynamic radius of the active material; the inverse relationship between the self-diffusion coefficient of the active material in the electrolyte and the viscosity of the electrolyte is used to determine the ionic conductivity of the electrolyte based on the hydrodynamic radius; the concentration of the active material in the electrolyte of the positive and negative electrodes of the flow battery changes with time during the charging and discharging process is modeled based on the mass conservation theory and the ionic conductivity, and the concentration of the active material corresponding to the current time is obtained according to the change model; the current battery voltage is determined based on the concentration of the active material; the energy efficiency parameter of the battery is determined based on the battery voltage, so as to determine the target concentration of the active material through the energy efficiency parameter. The technical solution of the present application evaluates the ionic conductivity based on the relationship between the viscosity and the self-diffusion coefficient, improves the accuracy of the performance prediction of the battery, establishes a dynamic model of the change of the concentration of the active material during the charging and discharging process, monitors the state of the battery in real time, calculates the battery voltage and the energy efficiency parameter in real time according to the model, optimizes the electrolyte formula through performance evaluation, determines the optimal concentration of the active material of the electrolyte, and improves the efficiency of the design and performance evaluation of the electrolyte formula, provides a reliable data basis for the subsequent production of the battery, and reduces the cost of research and development and production.

[0027] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0028] The accompanying drawings, which are incorporated herein and constitute part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the application. It is to be expressly understood, however, that the drawings are included herein for illustrative purposes only and that they are subject to interpretation, modification and / or change, without departing from the scope and spirit of the present application.

[0029] Figure 1 A flow chart schematically illustrates a method for determining the concentration of electrolyte of a flow battery in an embodiment of the present application.

[0030] Figure 2 A graph schematically illustrates the effect of the viscosity, ion diffusion coefficient and ion conductivity of electrolyte with the change of the concentration of VOSO4 in an embodiment of the present application.

[0031] Figure 3 A graph schematically illustrates the comparison between the experimental results and the model results in an embodiment of the present application.

[0032] Figure 4 A graph schematically illustrates the effect of the energy density, energy efficiency, system efficiency and electrolyte utilization of a flow battery with the change of the concentration of VOSO4 in an embodiment of the present application.

[0033] Figure 5 A graph schematically illustrates the multi-objective optimization for finding the optimal concentration of active material of electrolyte in an embodiment of the present application.

[0034] Figure 6 A graph schematically illustrates the effect of the concentration of H2SO4 supporting electrolyte on the viscosity and ion conductivity of electrolyte in an embodiment of the present application.

[0035] Figure 7 A graph schematically illustrates the effect of the concentration on the viscosity and ion conductivity of electrolyte in an embodiment of the present application.

[0036] Figure 8 A schematic diagram schematically illustrates a device for determining the concentration of electrolyte of a flow battery in an embodiment of the present application.

[0037] Figure 9 A structural schematic diagram of a computer system of an electronic device suitable for implementing embodiments of the present application is shown. DETAILED DESCRIPTION

[0038] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations can be implemented in any

[0039] Moreover, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the

[0040] The block diagrams in the drawings show only the functionality of the examples and do not imply any particular physical or architectural arrangement of the examples. For example, functions shown as discrete blocks in the block diagrams, can be provided in one or more modules, components, or integrated circuits. Similarly, the functions shown as single blocks can be implemented

[0041] The flow diagrams shown in the drawings are examples only and are not necessarily to be construed as having any special order of execution. For example, some operations / steps can be performed in a different order, or can be combined or partially combined, and the actual order can be changed as appropriate.

[0042] The implementation details of the technical solutions of the present application are described below in detail:

[0043] Figure 1 A flow chart of a method for determining a concentration of a flow battery electrolyte is shown according to an embodiment of the present application. Referring to Figure 1 As shown, the method for determining a concentration of a flow battery electrolyte includes at least steps S110 to S150, which are described in detail as follows:

[0044] In step S110, the relationship between the electrolyte viscosity and the active material concentration is fitted to determine the hydrodynamic radius of the active material.

[0045] In an embodiment of the present application, fitting the relationship between the electrolyte viscosity and the active material concentration to determine the hydrodynamic radius of the active material includes: fitting the relationship between the electrolyte viscosity and the active material concentration by the Huggins equation to determine the hydrodynamic radius of the active material.

[0046] In this embodiment, it is assumed that the solute in the electrolyte can be simplified as electrically neutral, rigid and inelastic spheres with no interaction. When the electrolyte is in the dilute electrolyte, the real-time viscosity μ increases linearly with the increase of the concentration c (moles per unit volume). After entering the semi-dilute electrolyte, the viscosity increases rapidly. This phenomenon can be described by the Huggins equation:

[0047]

[0048] where μ0 is the viscosity of the solvent itself, and [η] is called the intrinsic viscosity, which is related to the hydrodynamic radius r of the spherical solute active substance H .

[0049]

[0050] where N A is the Avogadro constant, and k H is the Huggins coefficient, which quantitatively describes the interaction between particles.

[0051] For example, when only considering hydrodynamic interaction and steric effect, k H = 0.992. Therefore, by fitting equation (1.1), the hydrodynamic radius of vanadyl sulfate VOSO4 can be calculated.

[0052] In this way, the hydrodynamic radius of the active substance can be obtained by fitting the equation under the condition of a certain concentration and real-time viscosity, thereby improving the accuracy of active substance detection and evaluation. Through experiments and theoretical calculations, the above process accurately characterizes the viscosity, hydrodynamic radius and other physicochemical parameters of the electrolyte under different active substance concentrations. These parameters are the basis for understanding the properties of the electrolyte, optimizing the formulation, and predicting the performance of the battery.

[0053] In step S120, based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, and the hydrodynamic radius, the ionic conductivity of the active substance in the electrolyte is determined.

[0054] In one embodiment of the present application, based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, and the hydrodynamic radius, the ionic conductivity of the active substance in the electrolyte is determined, comprising:

[0055] Based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, and the absolute temperature, the hydrodynamic radius of the active substance, the self-diffusion coefficient of the active substance is determined;

[0056] Based on the self-diffusion coefficient, and the number of cations and anions in the active substance and the number of charges they carry, the ionic conductivity of the active substance in the electrolyte is determined by the Nernst-Einstein equation.

[0057] In this embodiment, the self-diffusion coefficient of ions in the electrolyte is inversely proportional to the viscosity of the electrolyte, because the migration rate of ions is slowed down under greater viscous resistance. The Stokes-Einstein equation can be used to predict the VO 2+ and SO4 2 The self-diffusion coefficient of ions is:

[0058]

[0059] where D + and D - are the self-diffusion coefficients of VO 2+ and SO4 2- ions, k is the Boltzmann constant, T is the absolute temperature, r + and r - are the hydrodynamic radii of VO 2+ and SO4 2 ions, respectively.

[0060] Based on the measured viscosity and the inferred hydrodynamic radii, the self-diffusion coefficients of VO 2+ and SO4 2 ions at different concentrations can be predicted.

[0061] The ionic conductivity of the electrolyte can be estimated from the self-diffusion coefficient (ionic mobility) of the charged species and the Nernst-Einstein equation, i.e.:

[0062]

[0063] where e is the elementary charge, n + and n - are the number of cations and anions in each active substance, and z+ and z- are the number of charges carried by the cations and anions, respectively.

[0064] The above process successfully predicts the ionic conductivity of the active substance in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, as well as the known hydrodynamic radii. The ionic conductivity is one of the key parameters for evaluating the electrochemical performance of the battery, and its accurate prediction helps to improve the scientificity and effectiveness of battery design.

[0065] In step S130, based on the conservation of mass theory and the ionic conductivity, a model of the concentration of active substance in the electrolyte of the positive and negative electrodes of the flow battery over time during charging and discharging is established, and the concentration of active substance corresponding to the current time is obtained according to the change model.

[0066] In one embodiment of the present application, based on the mass conservation theory and the ion conductivity, a model of the concentration of active substances of the positive and negative electrolytes of the flow battery in the charging and discharging process is established, and the concentration of active substances corresponding to the current time is obtained according to the change model, comprising:

[0067] Based on the mass conservation theory, a change equation of the concentration of active substances, the electrolyte volume and the volume flow rate of the positive and negative electrolytes of the flow battery in the charging and discharging process is generated as the change model;

[0068] Based on the change equation, the concentration of active substances in the electrode and the liquid storage tank is determined.

[0069] In order to maintain generality, it is assumed that in the charging process, the redox active substance A obtains an electron e - on the negative electrode to obtain negative ion A - , and the above process is represented as:

[0070]

[0071] At the same time, the substance C loses an electron e - on the positive electrode to obtain positive ion C + , and the above process is represented as:

[0072]

[0073] Where k n and k p are the reaction rate constants of the negative and positive reactions, respectively. The valence of active molecules A and C and their reduced and oxidized states can be adjusted according to different redox reactions.

[0074] It is assumed that the positive and negative electrodes are symmetrical, and the electrolyte volume V r stored in the storage tank and the volume flow rate Q on both sides are the same; the viscosity μ and the ion conductivity σ of the electrolyte on both sides are also the same, that is:

[0075]

[0076] Where the subscript neg represents the parameters of the negative electrode, and the subscript pos represents the parameters of the positive electrode.

[0077] It is assumed that the active substance does not diffuse across the membrane, and there is no degradation of active material and other side reactions in the reaction process, and according to the mass conservation, the following equation can be written:

[0078]

[0079] Where Q is the volume flow rate, F is the Faraday constant, and cA and c A res are the concentrations of species A in the electrode and reservoir, respectively. A- and c A- res are the concentrations of species A in the electrode and reservoir, respectively. e is the volume of electrolyte in the electrode, V r is the volume of electrolyte, I is the current. The above set of equations (1.8) has a theoretical solution, i.e.:

[0080]

[0081] where:

[0082] c A,0 , c A-,0 are the initial concentrations of A and A - in the electrode and reservoir;

[0083] t is the charge / discharge time;

[0084] w e is the thickness of the electrode;

[0085] i is the current density, defined as i = I / A, A is the cross-sectional area of the electrode and current collector;

[0086] δ is the ratio of the volume of the reservoir to the volume of the electrode, i.e. δ = Vr / Ve. For high efficiency operation of the flow battery, the volume of the reservoir is generally much larger than the volume of the electrode.

[0087] Due to the symmetry of the positive and negative electrodes, the concentrations of species C and C + are the same as the concentrations of species A and A - .

[0088] The above process establishes a model of the change of the concentrations of active species in the electrolyte of the positive and negative electrodes of the flow battery over time during the charge and discharge process by combining the conservation of mass theory and the predicted ion conductivity. This model can dynamically reflect the change of the concentrations of active species in the battery, and provides a powerful tool for real-time monitoring and optimization of the performance of the battery.

[0089] In step S140, a current battery voltage is determined based on the concentrations of the active species.

[0090] In an embodiment of the present application, determining a current battery voltage based on the concentrations of the active species comprises:

[0091] determining a current overpotential of the battery based on battery parameters;

[0092] determining an open circuit voltage of the battery based on the concentrations of the active species and the equilibrium potential of the battery under standard conditions;

[0093] determining a battery voltage based on the overpotential and the open circuit voltage.

[0094] In this embodiment, the battery overpotential is linked to the concentration of the species, and the battery voltage during charging and discharging can be calculated. The open circuit voltage E OCV which can be calculated by the Nernst equation:

[0095]

[0096] R is the gas constant, T is the thermodynamic temperature, and E 0 pos and E 0 neg is the equilibrium potential under standard conditions, n is the electrochemical equivalent, and F is the Faraday constant. c A- is the concentration of species A in the electrode, c A is the concentration of species A in the electrode, is the concentration of species C + in the electrode, and c C is the concentration of species C in the electrode.

[0097] During charging and discharging, the voltage of the battery is determined by the open circuit voltage and the overpotential, and the charging voltage and discharging voltage are obtained as:

[0098]

[0099] where η R , η A , and η C are the ohmic overpotential, the activation overpotential, and the concentration overpotential (also called ohmic, activation, and concentration polarization), respectively.

[0100] In the above process, in a flow battery, the ohmic overpotential is related to the ohmic resistance of the battery, including the internal resistance of the electrolyte, porous electrode, and membrane (the resistance of the current collector is much lower than other components, so it is ignored in this model). The ohmic overpotential can be calculated by the following formula:

[0101]

[0102] where w m and σ m are the thickness and conductivity of the membrane, w e is the thickness of the electrode; σ e is the apparent conductivity of the porous electrode, and σ is the conductivity of the electrolyte. It is worth noting that the conductivities of the membrane and the electrolyte are related to the concentration of the electrolyte, because the concentration not only affects the ion transport in the electrolyte, but also affects the ion transport across the membrane.

[0103] The activation overpotential ηA is caused by the charge transfer at the electrode-electrolyte interface, which is related to the reaction rate constant, as follows:

[0104]

[0105] where R is the gas constant, T is the absolute temperature, F is the Faraday constant, and k n and k p are the reaction rate constants for the negative and positive reactions, respectively.

[0106] The concentration overpotential η C is caused by the mass transfer from the electrolyte to the electrode surface, which can be written as follows:

[0107]

[0108] where S is the surface area of the electrode, k m is the mass transfer coefficient, which depends on the self-diffusion coefficient of the transferred ion, the viscosity of the electrolyte, and the flow rate U, and is expressed as:

[0109]

[0110] where D is the self-diffusion coefficient, d f is the diameter of the carbon fiber in the porous electrode, p is the density of the electrolyte, U is the flow rate, and m is the viscosity.

[0111] Based on the active material concentration obtained from the dynamic simulation, the current battery voltage can be calculated in real time. Furthermore, based on the battery voltage, key performance parameters such as the energy density, energy efficiency, and system efficiency of the battery can be further determined. This real-time evaluation capability helps to timely detect abnormal battery performance, prevent faults, and optimize the operation strategy of the battery.

[0112] In step S150, based on the battery voltage, the energy efficiency parameters of the battery are determined to determine the target concentration of the active material through the energy efficiency parameters.

[0113] In an embodiment of the present application, through the above calculation, the charge-discharge curve of the flow battery can be obtained, and the performance parameters of the battery can be calculated through the charge-discharge curve.

[0114] The energy efficiency parameters in the present embodiment include the energy density, energy efficiency, and system efficiency.

[0115] For a flow battery storing a certain volume of electrolyte, the energy density (ED) can be obtained by integrating the discharge curve:

[0116]

[0117] where I is the current, E is the battery voltage, V is the volume of electrolyte, and t is the discharge time from the start of discharge (disch, start) to the end of discharge (disch, end). cell r is the battery voltage during the discharge process, V is the volume of electrolyte, and t is the discharge time from the start of discharge (disch, start) to the end of discharge (disch, end). The energy density of the electrolyte is an important consideration when evaluating the cost of the battery. Increasing the energy density of the electrolyte can significantly reduce the system volume and footprint, and reduce manufacturing costs.

[0118] In addition, the energy efficiency (EE) of the battery is also an important parameter to be evaluated, which is defined as:

[0119]

[0120] The energy efficiency evaluates the utilization rate of input energy by the battery during the charging and discharging process.

[0121] In the system-level evaluation, the system efficiency (SE) takes into account the power loss of the pump, and is defined as:

[0122]

[0123] where φ represents the pump efficiency, Q is the volumetric flow rate, and ΔP is the pressure difference of the electrolyte flowing through the porous electrode. pump

[0124] In an embodiment of the present application, based on the battery voltage, the energy efficiency parameter of the battery is determined, including: based on the permeability of the porous electrode, the cross-sectional area of the electrode, and the height of the electrode, the pressure difference of the electrolyte flowing through the porous electrode is determined as one of the energy efficiency parameters.

[0125] Specifically, the pressure difference of the electrolyte flowing through the porous electrode can be calculated by the permeability of the electrode:

[0126]

[0127] where K is the permeability of the porous electrode, Q is the volumetric flow rate, A is the cross-sectional area of the electrode, and H is the height of the electrode.

[0128] In an embodiment of the present application, after determining the energy efficiency parameter of the battery based on the battery voltage, the method further includes:

[0129] Based on the discharge current corresponding to the current time, the active material concentration, and the electrolyte volume, the utilization rate of the electrolyte is determined.

[0130] ​​Specifically, another parameter that greatly affects the cost of flow batteries is the electrolyte utilization (EU), which represents the ratio of the discharge capacity to the theoretical capacity, specifically defined as:

[0131]

[0132] where V is the volume of the electrolyte, and I is the current. r

[0133] The above parameters collectively form a multi-dimensional and multi-performance evaluation system for evaluating the performance of flow batteries, helping us to optimize the concentration of electrolyte, and to determine the target concentration of electrolyte active material with optimal utility based on numerous evaluation parameters corresponding to various electrolytes.

[0134] In addition, the above process can further determine the energy density, energy efficiency, and system efficiency of the battery based on the battery voltage. This real-time evaluation capability helps to timely detect abnormal battery performance, prevent faults, and optimize the operation strategy of the battery. By comparing the performance parameters of the battery under different conditions, the formulation of the electrolyte can be optimized, and the charging and discharging strategy can be adjusted, so as to improve the overall performance and economic benefits of the battery based on the lowest cost and highest efficiency in production and research.

[0135] It should be noted that this optimization strategy based on experimental data and theoretical models is scientific, practical, and universal, and the above process is generally applicable to electrolytes of various active materials, which helps to further develop flow battery technology.

[0136] Example 1:

[0137] For example, the optimal VOSO4 concentration of a single-stage all-vanadium flow battery with an active area of 20 mm x 20 mm, an electrolyte volume of 10 mL x 2, and an electrolyte flow rate of 46 mL min -1 The specific embodiment of the present application is introduced in detail.

[0138] The specific steps are as follows:

[0139] (1) Measure the viscosity of electrolyte with different vanadium ion concentrations, and predict the ion diffusion coefficient and conductivity of electrolyte with different concentrations. By measuring the viscosity of electrolyte, the size of internal friction resistance of electrolyte can be understood, which is an important factor affecting the efficiency of ion transmission. Low-viscosity electrolyte usually provides a more efficient ion transmission channel. Conductivity is an important indicator to measure the conductivity of electrolyte, which is closely related to ion concentration, ion mobility, etc. Accurate prediction of conductivity helps to evaluate the conductivity performance of electrolyte and its influence on battery performance.

[0140] ​(2) Using a zero-dimensional mass transfer coupled electrochemical reaction dynamic model, the charge-discharge curves for various electrolyte concentrations were calculated. Through model simulation, the voltage changes during the charge-discharge process for electrolytes with different vanadium ion concentrations can be predicted, i.e., the charge-discharge curves. This curve reflects the energy conversion efficiency and stability of the battery.

[0141] (3) Using the charge-discharge curves, calculate the battery performance parameters under various electrolyte concentrations. By comparing the performance parameters under different electrolyte concentrations, the specific impact of electrolyte concentration on battery performance can be quantified, providing data support for optimizing the electrolyte formulation.

[0142] (4) Compare various performance parameters and select the optimal electrolyte concentration. By comprehensively comparing the battery performance parameters under different electrolyte concentrations, it is possible to determine which concentrations exhibit better performance in which aspects. Ultimately, the optimal electrolyte concentration that meets both performance requirements and is cost-effective is selected. Optimizing electrolyte concentration can significantly improve key performance indicators such as battery energy density, cycle stability, and safety, thereby promoting the further development of battery technology.

[0143] Example 2:

[0144] Taking VOSO4 aqueous electrolyte without sulfuric acid as an example, the change of electrolyte viscosity with VOSO4 concentration was measured, and the hydrodynamic radius of VOSO4 in the aqueous electrolyte was calculated by fitting the Higgins equation. Based on the viscosity and hydrodynamic radius, the changes of ion diffusion coefficient and ionic conductivity of VOSO4 aqueous electrolyte at different concentrations were predicted.

[0145] like Figure 2 As shown, Figure 2 In (a), the viscosity of the electrolyte first increases linearly with concentration, and then increases nonlinearly and rapidly. By fitting the Higgins formula, the hydrodynamic radius of VOSO4 can be obtained. Figure 2 (b) Predicting the change of ion diffusion coefficient with concentration through viscosity; Figure 2 (c) Predict the concentration-dependent change in ionic conductivity using viscosity.

[0146] like Figure 2 As shown in the figure, the viscosity of VOSO4 (vanadium oxysulfate, also known as vanadium yl sulfate) aqueous electrolyte is experimentally measured as a function of VOSO4 concentration. As the concentration increases, the viscosity first increases linearly, and then increases significantly and rapidly. The data are fitted using the Higgins formula, where the coefficient of the first-order term is related to the hydrodynamic radius of the solute VOSO4. The hydrodynamic radius of VOSO4 can be calculated to be 0.42nm using the formula. Based on the measured electrolyte viscosity and hydrodynamic radius, the ion diffusion coefficient and ion conductivity at different concentrations can be predicted, where ν + =ν - =1,z + =z -=2. The calculated VO 2+ and SO4 2- The ion diffusion coefficient and ionic conductivity of VOSO4 water electrolyte change with VOSO4 concentration as shown in Figure 2 As shown in Figure 2, the diffusion coefficient decreases with increasing concentration, while the ionic conductivity first increases and then decreases with increasing concentration.

[0147] Example 3:

[0148] like Figure 3 As shown, Figure 3 The following is an example of the flow battery performance parameters calculated based on this model, namely energy density, energy efficiency, system efficiency and electrolyte utilization rate as a function of concentration. The vanadium ion concentration is 1 mol / L, the sulfuric acid concentration is 3 mol / L, and the current density is 200 mA cm -2 , volume flow rate is 46 mL min -1 For example, we calculated the charge and discharge curves of a flow battery and compared them with experimental data to verify the accuracy of the model. As shown in the figure, the average relative error of the model predictions compared with the experimental data is within 0.2%.

[0149] In the all-vanadium flow battery, the electrochemical reactions at the positive and negative electrodes are as follows:

[0150]

[0151] Among them, V 3+ and V 2+ represent trivalent vanadium ions and divalent vanadium ions, VO 2+ It is the vanadium oxide ion H + is a hydrogen ion. n and k p are the reaction rate constants of the negative and positive electrode reactions, respectively. The electrochemical reaction rate constants of the positive and negative electrodes include: k n =6.8×10 -7 ms -1 and k p =1.7×10 -7 ms -1 The selection of other parameters, such as electrode thickness, membrane thickness, etc., is determined by the geometric parameters of the specific battery.

[0152] Compared with the experimental data, the average relative error of the model prediction is within 0.2%. It can be seen that the model in this application can fully simulate the actual experimental data and has high accuracy.

[0153] Example 4:

[0154] like Figure 4 As shown, it shows the influence of electrolyte concentration on various aspects of battery status, including: Figure 4(a) Energy density, Figure 4 (b) Energy efficiency, Figure 4 (c) System efficiency and Figure 4 (d) Variation of electrolyte utilization with VOSO4 concentration.

[0155] The steps of Example 3 were repeated to calculate the charge-discharge curves of electrolytes with different vanadium ion concentrations and the battery performance parameters, including energy density, energy efficiency, system efficiency, and electrolyte utilization.

[0156] Example 5:

[0157] like Figure 5 As shown, Figure 5 This diagram illustrates a multi-objective optimization method for finding the optimal electrolyte active material concentration, as provided in this application. Multi-objective optimization was used to optimize the electrolyte vanadium ion concentration and find the optimal concentration. The multi-objective optimization of vanadium ion concentration in an all-vanadium redox flow battery electrolyte, while simultaneously considering the battery's energy density, system efficiency, and electrolyte utilization, yielded an optimal electrolyte concentration of approximately 1.25 mol / L.

[0158] Example 6:

[0159] like Figure 6 As shown, Figure 6 This chart shows the effect of sulfuric acid concentration on electrolyte viscosity and ionic conductivity. Taking H2SO4 in an all-vanadium flow battery electrolyte as an example, the concentration of the supporting electrolyte in the electrolyte is optimized. A higher supporting electrolyte concentration increases electrolyte viscosity and ionic conductivity. The method for optimizing the supporting electrolyte salt ion concentration is similar to that for the active material, and the specific steps are as follows:

[0160] (1) Measure the viscosity of electrolytes with different sulfuric acid concentrations and predict how the ion diffusion coefficient and conductivity of electrolytes of different concentrations change with sulfuric acid concentration.

[0161] (2) Using the zero-dimensional mass transfer coupled electrochemical reaction dynamic model, the charge and discharge curves of electrolytes of various concentrations were calculated.

[0162] (3) Using the charge and discharge curves, calculate the battery performance parameters under various electrolyte concentrations.

[0163] (4) Compare various performance parameters and select the optimal sulfuric acid concentration.

[0164] The above process achieves dynamic simulation and real-time monitoring of the battery state by establishing a model of the change in active material concentration over time in the positive and negative electrolytes of the flow battery during the charge and discharge process. By obtaining the active material concentration in real time and calculating the battery voltage, key performance parameters such as the battery's energy density, energy efficiency, and system efficiency are further evaluated. This provides a scientific basis for optimizing battery performance.

[0165] Example 7:

[0166] As an example, the viscosity and ionic conductivity of the organic active material Dex-Vi in 1 mol / L sodium chloride (NaCl) aqueous electrolyte were measured as a function of active material concentration. The concentration of Dex-Vi was optimized as follows:

[0167] (1) As shown in FIG. 1, the viscosity of VOSO4 aqueous electrolyte was measured as a function of VOSO4 concentration. The viscosity increased linearly at first, and then increased significantly faster as the concentration increased. The Huggins equation was used to fit the data, where the coefficient of the first term is related to the hydrodynamic radius of the solute Dex-Vi. The hydrodynamic radius of Dex-Vi was calculated to be 0.72 nm using the formula. Based on the viscosity and hydrodynamic radius, the changes in ion diffusion coefficient and ionic conductivity of the electrolyte at different concentrations were predicted. The ionic conductivity increased first, and then decreased as the concentration increased. Figure 7

[0168] (2) A zero-dimensional mass transfer coupled with electrochemical reaction dynamic model was used to calculate the charge and discharge curves of the electrolyte at different Dex-Vi concentrations.

[0169] (3) Based on the charge and discharge curves, the battery performance parameters at each concentration were calculated.

[0170] (4) By comparing the performance parameters, the optimal Dex-Vi concentration was selected.

[0171] The above process measured the viscosity of VOSO4 aqueous electrolyte as a function of VOSO4 concentration through experiments, and found that it had a nonlinear growth trend. The Huggins equation was successfully used to fit the data, which not only revealed the complex relationship between viscosity and concentration, but also calculated the hydrodynamic radius of the solute Dex-Vi, providing an important parameter for understanding the behavior of the solute in the electrolyte. Based on the information of viscosity and hydrodynamic radius, combined with the theoretical model, the change trend of ion diffusion coefficient and ionic conductivity of the electrolyte at different concentrations was successfully predicted. This prediction ability is crucial for understanding the electrochemical processes inside the battery, optimizing the battery design, and improving the battery performance. Based on the charge and discharge curves, the battery performance parameters at each concentration were calculated, such as energy density, energy efficiency, power output, etc. The comprehensive evaluation of these parameters provides a scientific basis for selecting the optimal Dex-Vi concentration, which helps to maximize the performance of the battery.

[0172] ​In the technical solution of the present application, the relationship between the electrolyte viscosity and the active material concentration is fitted to determine the hydrodynamic radius of the active material; based on the inverse relationship between the self-diffusion coefficient of the active material in the electrolyte and the electrolyte viscosity and the hydrodynamic radius, the ionic conductivity of the active material in the electrolyte is determined; based on the substance conservation theory and the ionic conductivity, a model of the change of the concentration of the active material in the electrolyte of the positive and negative electrodes of the flow battery over time during the charging and discharging process is established, and the active material concentration corresponding to the current time is obtained according to the change model; the current battery voltage is determined based on the active material concentration; and based on the battery voltage, the energy efficiency parameter of the battery is determined to determine the target concentration of the active material through the energy efficiency parameter. The technical solution of the present application evaluates the ionic conductivity based on the relationship between the viscosity and the self-diffusion coefficient, improves the accuracy of the battery performance prediction, establishes a dynamic model of the change of the active material concentration during the charging and discharging process, monitors the battery state in real time, calculates the battery voltage in real time according to the model, and determines the performance parameters such as the energy density, the energy efficiency, the system efficiency and the electrolyte utilization rate, optimizes the electrolyte formula through performance evaluation, determines the optimal electrolyte active material concentration, improves the efficiency of the electrolyte formula design and performance evaluation, provides a reliable data basis for the subsequent battery production, and reduces the research and production cost.

[0173] The device embodiment of the present application is introduced below, which can be used to execute the method for determining the electrolyte concentration of the flow battery in the above-mentioned embodiments of the present application. It can be understood that the device can be a computer program (including program code) running in a computer device, for example, the device is an application software; the device can be used to execute the corresponding steps in the method provided by the embodiments of the present application. For details not disclosed in the device embodiment of the present application, please refer to the above-mentioned embodiments of the method for determining the electrolyte concentration of the flow battery.

[0174] Figure 8 A block diagram of the device for determining the electrolyte concentration of the flow battery according to an embodiment of the present application is shown.

[0175] Referring to Figure 8 The device for determining the electrolyte concentration of the flow battery according to an embodiment of the present application includes:

[0176] The fitting unit 310 is configured to fit the relationship between the electrolyte viscosity and the active material concentration to determine the hydrodynamic radius of the active material;

[0177] The conductive unit 320 is configured to determine the ionic conductivity of the active material in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active material in the electrolyte and the electrolyte viscosity and the hydrodynamic radius;

[0178] The model unit 330 is configured to establish a model of changes of the concentration of the active substance of the electrolyte of the positive and negative electrodes of the flow battery over time in the charging and discharging process based on the mass conservation theory and the ion conductivity, and obtain the concentration of the active substance corresponding to the current time according to the change model.

[0179] The voltage unit 340 is configured to determine the current battery voltage based on the concentration of the active substance.

[0180] The parameter unit 350 is configured to determine an energy efficiency parameter of the battery based on the battery voltage, so as to determine the target concentration of the active substance through the energy efficiency parameter.

[0181] In the present application, based on the foregoing scheme, the determination of the energy efficiency parameter of the battery based on the battery voltage comprises: determining the pressure difference of the electrolyte flowing through the porous electrode as one of the energy efficiency parameters based on the permeability of the porous electrode, the cross-sectional area of the electrode, and the height of the electrode.

[0182] In the present application, based on the foregoing scheme, after the determination of the energy efficiency parameter of the battery based on the battery voltage, the method further comprises: determining the utilization rate of the electrolyte based on the discharge current corresponding to the current time, the concentration of the active substance, and the volume of the electrolyte.

[0183] In the present application, based on the foregoing scheme, the fitting of the relationship between the viscosity of the electrolyte and the concentration of the active substance to determine the hydrodynamic radius of the active substance comprises: performing Huggins equation fitting on the relationship between the viscosity of the electrolyte and the concentration of the active substance to determine the hydrodynamic radius of the active substance.

[0184] In the present application, based on the foregoing scheme, the determination of the ion conductivity of the active substance in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte and the hydrodynamic radius comprises: determining the self-diffusion coefficient of the active substance based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte and the absolute temperature and the hydrodynamic radius of the active substance; determining the ion conductivity of the active substance in the electrolyte through the Nernst-Einstein equation based on the self-diffusion coefficient and the number of cations and anions in the active substance and the number of charges carried by the cations and anions.

[0185] In the present application, based on the foregoing scheme, the establishment of the change model of the concentration of the active substance of the electrolyte of the positive and negative electrodes of the flow battery over time in the charging and discharging process based on the mass conservation theory and the ion conductivity, and the obtaining of the concentration of the active substance corresponding to the current time according to the change model comprise: generating a change equation of the concentration of the active substance, the volume of the electrolyte, and the volume flow rate of the electrolyte of the positive and negative electrodes of the flow battery in the charging and discharging process as the change model based on the mass conservation theory; and determining the concentration of the active substance in the electrode and the liquid storage tank based on the change equation.

[0186] In the present application, based on the foregoing scheme, the determining the current battery voltage based on the active material concentration comprises: determining the current overpotential of the battery based on battery parameters; determining the open circuit voltage of the battery based on the active material concentration and the equilibrium potential of the battery under standard conditions; determining the battery voltage based on the overpotential and the open circuit voltage.

[0187] In the technical scheme of the present application, the relationship between the electrolyte viscosity and the active material concentration is fitted to determine the hydrodynamic radius of the active material; the ion conductivity of the active material in the electrolyte is determined based on the inverse relationship between the self-diffusion coefficient of the active material in the electrolyte and the viscosity of the electrolyte, and the hydrodynamic radius; the concentration change model of the active material in the electrolyte of the flow battery positive and negative electrode during the charging and discharging process is established based on the conservation of mass theory and the ion conductivity, and the corresponding active material concentration at the current time is obtained according to the change model; the current battery voltage is determined based on the active material concentration; the energy efficiency parameter of the battery is determined based on the battery voltage, so as to determine the target concentration of the active material through the energy efficiency parameter. The technical scheme of the present application evaluates the ion conductivity based on the relationship between the viscosity and the self-diffusion coefficient, improves the accuracy of battery performance prediction, establishes a dynamic model of the concentration change of the active material during the charging and discharging process, monitors the battery state in real time, calculates the battery voltage and performance parameters such as energy density and efficiency in real time according to the model, optimizes the electrolyte formula through performance evaluation, determines the optimal electrolyte active material concentration, improves the efficiency of electrolyte formula design and performance evaluation, provides reliable data basis for subsequent battery production, and reduces research and production cost.

[0188] Figure 9 The structural schematic diagram of the computer system of the electronic device suitable for realizing the embodiments of the present application is shown.

[0189] It should be noted that the computer system 400 of the electronic device shown in the figure is only an example, and should not bring any limitation to the function and use range of the embodiments of the present application.

[0190] Among them, the computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage portion 408 to the random access memory (RAM) 403, such as performing the method described in the above embodiments. In the RAM 403, various programs and data required for system operation are also stored. The CPU 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0191] The following components are connected to the I / O interface 405: an input portion 406 including a keyboard, a mouse, and the like; an output portion 407 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), and the like, and a speaker, and the like; a storage portion 408 including a hard disk, and the like; and a communication portion 409 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication portion 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is mounted on the drive 410 as needed, so that a computer program read therefrom is installed in the storage portion 408 as needed.

[0192] In particular, according to the embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, the embodiments of the present application include a computer program product including a computer program carried on a computer-readable medium, the computer program containing a computer program for executing the method shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network by the communication portion 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the system of the present application are performed.

[0193] It should be noted that the computer-readable medium in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination thereof. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In the present application, the computer-readable signal medium can include a data signal carrying computer-readable computer programs in a baseband or as a part of a carrier wave. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, which can send, propagate or transmit programs for use by or in conjunction with an instruction execution system, device or apparatus. The computer programs contained in the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, or the like, or any suitable combination thereof.

[0194] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In the flowcharts or block diagrams, each block can represent a module, a program segment or a part 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 noted in the blocks can occur in different orders than that shown in the drawings. For example, two blocks represented in succession can actually be executed substantially in parallel, and sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams or flowcharts, and the combination of blocks in the block diagrams or flowcharts, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0195] The units described in the embodiments of the present application can be implemented by software, or by hardware, or by a combination of software and hardware. The units described can also be located in a single processor. In some cases, the names of the units do not limit the units themselves.

[0196] According to an aspect of the present application, a computer program product or computer program is provided, which includes computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device performs the method provided in the various optional implementation manners described above.

[0197] As another aspect, the present application also provides a computer readable medium, which can be included in the electronic device described in the above embodiments, or can exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the method described in the above embodiments.

[0198] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, the division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into several modules or units.

[0199] From the above description of the embodiments, those skilled in the art will readily appreciate that the example embodiments described herein can be implemented by software and / or by hardware. Accordingly, the technical solutions of the embodiments of the present application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, or the like) or on a network, and includes a number of instructions for causing a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to perform the methods according to the embodiments of the present application.

[0200] Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the application following the general principles thereof and including such departures from the present disclosure as come within known use or custom in the art.

[0201] It is to be understood that the application is not limited to the precise construction herein described and as shown in the drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims

1. A method for determining the concentration of a flow battery electrolyte, characterized in that: include: Fit the relationship between electrolyte viscosity and active material concentration to determine the hydrodynamic radius of the active material; determining the ionic conductivity of the active material in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active material in the electrolyte and the viscosity of the electrolyte, and the hydrodynamic radius; Based on the theory of conservation of matter and the ionic conductivity, a model for the change in the concentration of active substances in the positive and negative electrolytes of the flow battery over time during the charge and discharge process is established, and the active substance concentration corresponding to the current moment is obtained according to the change model; determining a current battery voltage based on the active material concentration; An energy efficiency parameter of the battery is determined based on the battery voltage, so as to determine a target concentration of the active material through the energy efficiency parameter.

2. The method according to claim 1, characterized in that Fit the relationship between electrolyte viscosity and active material concentration to determine the hydrodynamic radius of the active material, including: The relationship between electrolyte viscosity and active material concentration was fitted with the Higgins equation to determine the hydrodynamic radius of the active material.

3. The method according to claim 1, characterized in that Determining the ionic conductivity of the active material in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active material in the electrolyte and the viscosity of the electrolyte, as well as the hydrodynamic radius, includes: Determining the self-diffusion coefficient of the active substance in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active substance in the electrolyte and the viscosity of the electrolyte, as well as the absolute temperature and the hydrodynamic radius of the active substance; Based on the self-diffusion coefficient, the number of cations and anions in the active material and the number of charges carried by them, the ionic conductivity of the electrolyte is determined by the Nernst-Einstein equation.

4. The method according to claim 1, wherein Based on the theory of conservation of matter and the ionic conductivity, a model for the change of the concentration of active substances in the positive and negative electrolytes of the flow battery over time during the charge and discharge process is established, and the active substance concentration corresponding to the current moment is obtained according to the change model, including: Based on the theory of conservation of matter, a change equation is generated for the concentration of active substances in the positive and negative electrolytes of the flow battery during the charge and discharge process, the electrolyte volume, and the volume flow rate, which serves as the change model; Based on the transformation equation, the concentration of the active material in the electrode and the reservoir is determined.

5. The method according to claim 1, characterized in that Determining a current battery voltage based on the active material concentration includes: Based on the battery parameters, determine the current overpotential of the battery; determining an open circuit voltage of the battery based on the concentration of the active material and the equilibrium potential of the battery under standard conditions; A battery voltage is determined based on the overpotential and the open circuit voltage.

6. A device for determining the concentration of a flow battery electrolyte, characterized in that: include: A fitting unit is used to fit the relationship between electrolyte viscosity and active material concentration to determine the hydrodynamic radius of the active material; a conductive unit for determining the ionic conductivity of the active material in the electrolyte based on the inverse relationship between the self-diffusion coefficient of the active material in the electrolyte and the viscosity of the electrolyte, and the hydrodynamic radius; A model unit is used to establish a time-varying model of the concentration of active substances in the positive and negative electrolytes of the flow battery during the charge and discharge process based on the theory of conservation of matter and the ionic conductivity, and to obtain the active substance concentration corresponding to the current moment according to the change model; a voltage unit, configured to determine a current battery voltage based on the active material concentration; A parameter unit is used to determine an energy efficiency parameter of the battery based on the battery voltage, so as to determine a target concentration of the active material through the energy efficiency parameter.

7. A computer-readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining the concentration of an electrolyte in a flow battery according to any one of claims 1 to 5 is implemented.

8. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the method for determining the concentration of a flow battery electrolyte as described in any one of claims 1 to 5.

Images