Modeling method and device of lithium ion battery multi-physical field aging coupling model

Abstract

The invention relates to a modeling method and device for a lithium ion battery multi-physics field aging coupling model, and relates to the technical field of lithium ion batteries. The method comprises the following steps: obtaining a pre-constructed equivalent circuit model, and obtaining a pre-constructed evolution model of solid electrolyte interfacial film growth; the equivalent circuit model is coupled with the evolution model of solid electrolyte interfacial film growth, and a lithium ion battery multi-physical field aging coupling model is constructed; and on the basis of the test data corresponding to the lithium ion battery, calibrating various parameters in the lithium ion battery multi-physics field aging coupling model to obtain a calibrated aging coupling model. By adopting the method, the simulation and prediction effects of the aging model of the battery in a simulation experiment can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of lithium-ion batteries, and in particular to a modeling method and device for a multi-physical field aging coupling model of lithium-ion batteries. Background Art

[0002] Energy storage is an important part of new energy technology, and electrochemical energy storage is one of the most important energy storage methods. Lithium-ion batteries are significantly superior to other batteries in terms of energy, power, cycle life, etc., and are an important carrier of electrochemical energy storage. Lithium-ion batteries are inevitably accompanied by aging during use, which leads to a decrease in battery power and capacity, and also poses safety hazards. In order to better understand the battery aging process and conduct battery research more efficiently, it is necessary to build an aging model for lithium-ion batteries to simulate and predict the battery aging process and electrochemical performance. Battery aging modeling involves multiple physical fields such as electricity, heat, and force, which makes battery aging modeling challenging.

[0003] However, the current battery aging model takes a long time to calculate, has inaccurate parameter calibration, and has poor simulation accuracy, resulting in poor simulation and prediction effects of the battery aging model in simulation experiments. Summary of the invention

[0004] Based on this, it is necessary to provide a modeling method, device, computer equipment, computer-readable storage medium and computer program product for a lithium-ion battery multi-physical field aging coupling model that can improve the simulation and prediction effects of the battery aging model in simulation experiments in response to the above-mentioned technical problems.

[0005] In a first aspect, an embodiment of the present application provides a modeling method for a multi-physics field aging coupling model of a lithium-ion battery. The method comprises:

[0006] Obtaining a pre-constructed equivalent circuit model and a pre-constructed solid electrolyte interface film growth evolution model; the equivalent circuit model is a model for equivalent lithium-ion batteries, and the solid electrolyte interface film growth evolution model is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery;

[0007] The equivalent circuit model is coupled with the evolution model of the solid electrolyte interface film growth to construct a multi-physical field aging coupling model of lithium-ion batteries;

[0008] Based on the test data corresponding to the lithium-ion battery, various parameters in the multi-physical field aging coupling model of the lithium-ion battery are calibrated to obtain a calibrated aging coupling model; the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of the lithium-ion battery.

[0009] In one embodiment, after the step of calibrating various parameters in the multi-physics field aging coupling model of the lithium-ion battery to obtain the calibrated aging coupling model, the method further includes:

[0010] Using the calibrated aging coupling model, a finite element modeling method is used to divide the grid; the grid is used to carry the decomposed elements;

[0011] Simulating the lithium-ion battery corresponding to the calibrated aging coupling model based on the grid to obtain a battery simulation result;

[0012] The battery simulation results include battery aging simulation results, thermal simulation results and mechanical simulation results.

[0013] In one embodiment, the step of obtaining a pre-constructed evolution model of solid electrolyte interface film growth comprises:

[0014] Determine the side reaction overpotential based on the main reaction overpotential and equilibrium potential corresponding to the solid electrolyte interface film growth process;

[0015] Determine the current density of the main reaction based on the Tafel equation and the main reaction overpotential, and determine the current density of the side reaction based on the Butler-Wolmer equation and the side reaction overpotential;

[0016] An evolution model of the growth of the solid electrolyte interface film is determined according to the current density of the main reaction, the current density of the side reaction, the main reaction overpotential and the side reaction overpotential.

[0017] In one embodiment, coupling the equivalent circuit model with the evolution model of the solid electrolyte interface film growth includes:

[0018] Integrating the current density in the side reaction corresponding to the evolution model of the solid electrolyte interface film growth to obtain an integral result, and using the integral result as an input of the negative electrode in the equivalent circuit model;

[0019] The negative electrode open circuit voltage and total current density of the equivalent circuit model are used as an input in the evolution model of solid electrolyte interface film growth.

[0020] In one embodiment, the method further comprises:

[0021] Disassembling and measuring the lithium-ion battery to obtain a measurement result;

[0022] Conducting a half-cell open circuit potential test on the positive electrode and the negative electrode of the lithium-ion battery to obtain a curve of the potential of a single electrode as a function of the lithium insertion state of the electrode;

[0023] Carrying out charge and discharge tests on the monomers of the lithium-ion battery, and obtaining thermodynamic parameters according to input and output characteristics corresponding to the charge and discharge tests;

[0024] Conducting a dynamic working condition test on the monomer of the lithium-ion battery, and obtaining thermodynamic parameters, kinetic parameters and diffusion parameters according to the input-output characteristics corresponding to the dynamic working condition test;

[0025] Carry out aging tests on lithium-ion battery cells to determine the capacity attenuation test data of battery aging;

[0026] The measurement results, the curve of the change of the potential with the lithium insertion state of the electrode, the thermodynamic parameters, the kinetic parameters, the diffusion parameters, and the capacity attenuation test data of the battery aging are used as the test data corresponding to the lithium ion battery.

[0027] In one embodiment, the equivalent circuit model corresponding to the equivalent circuit equation is a one-dimensional model for distinguishing the positive and negative electrode charge states, the positive and negative electrode open circuit potentials, the liquid phase overpotential, and the ohmic lumped overpotential, and the equivalent circuit model is used to simulate the dynamic characteristics of the battery through electronic components.

[0028] In a second aspect, the present application also provides a modeling device for a multi-physics field aging coupling model of a lithium-ion battery. The device comprises:

[0029] An equation acquisition module is used to acquire a pre-constructed equivalent circuit model and a pre-constructed evolution model of solid electrolyte interface film growth; the equivalent circuit model is a model for equivalent lithium-ion batteries, and the evolution model of solid electrolyte interface film growth is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery;

[0030] A model coupling module, used to couple the equivalent circuit model with the evolution model of the solid electrolyte interface film growth to construct a multi-physical field aging coupling model of lithium-ion batteries;

[0031] A model parameter calibration module is used to calibrate various parameters in the multi-physical field aging coupling model of the lithium-ion battery based on the test data corresponding to the lithium-ion battery to obtain a calibrated aging coupling model; the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of the lithium-ion battery.

[0032] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0033] Obtaining a pre-constructed equivalent circuit model and a pre-constructed solid electrolyte interface film growth evolution model; the equivalent circuit model is a model for equivalent lithium-ion batteries, and the solid electrolyte interface film growth evolution model is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery;

[0034] The equivalent circuit model is coupled with the evolution model of the solid electrolyte interface film growth to construct a multi-physical field aging coupling model of lithium-ion batteries;

[0035] Based on the test data corresponding to the lithium-ion battery, various parameters in the multi-physical field aging coupling model of the lithium-ion battery are calibrated to obtain a calibrated aging coupling model; the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of the lithium-ion battery.

[0036] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0037] Obtaining a pre-constructed equivalent circuit model and a pre-constructed solid electrolyte interface film growth evolution model; the equivalent circuit model is a model for equivalent lithium-ion batteries, and the solid electrolyte interface film growth evolution model is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery;

[0038] The equivalent circuit model is coupled with the evolution model of the solid electrolyte interface film growth to construct a multi-physical field aging coupling model of lithium-ion batteries;

[0039] Based on the test data corresponding to the lithium-ion battery, various parameters in the multi-physical field aging coupling model of the lithium-ion battery are calibrated to obtain a calibrated aging coupling model; the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of the lithium-ion battery.

[0040] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0041] Obtaining a pre-constructed equivalent circuit model and a pre-constructed solid electrolyte interface film growth evolution model; the equivalent circuit model is a model for equivalent lithium-ion batteries, and the solid electrolyte interface film growth evolution model is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery;

[0042] The equivalent circuit model is coupled with the evolution model of the solid electrolyte interface film growth to construct a multi-physical field aging coupling model of lithium-ion batteries;

[0043] Based on the test data corresponding to the lithium-ion battery, various parameters in the multi-physical field aging coupling model of the lithium-ion battery are calibrated to obtain a calibrated aging coupling model; the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of the lithium-ion battery.

[0044] The modeling method, device, computer equipment, storage medium and computer program product of the multi-physics field aging coupling model of lithium-ion batteries are constructed by obtaining the pre-constructed equivalent circuit equation and the evolution equation of solid electrolyte interface film growth, combining the characteristics of the two, and constructing the multi-physics field aging coupling model of lithium-ion batteries. First, the equivalent circuit equation is coupled with the film growth evolution equation to form a simplified model that comprehensively reflects the electrochemical, thermodynamic and mechanical properties; then, based on the corresponding experimental data, the various parameters in the model are calibrated to obtain a usable aging coupling model; this scheme effectively improves the understanding and prediction capabilities of lithium-ion battery aging behavior, provides a scientific basis for battery design and optimization, simplifies the electrochemical part of the coupling model through the equivalent circuit model, and couples it with the aging mechanism model of solid electrolyte interface film growth, while being able to obtain reliable battery aging simulation results, greatly reducing the time and computing power required for calculation, and improving the simulation and prediction effects of the battery aging model in simulation experiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] FIG1 is an application environment diagram of a modeling method for a multi-physics field aging coupling model of a lithium-ion battery in one embodiment;

[0047] Figure 2 A schematic diagram of a flow chart of a method for modeling a multi-physics field aging coupling model for a lithium-ion battery in one embodiment;

[0048] Figure 3 A schematic diagram of a flow chart of a modeling method for a multi-physics field aging coupling model of a lithium-ion battery in another embodiment;

[0049] Figure 4Schematic diagram of the equivalent circuit model and SEI film growth side reaction model;

[0050] Figure 5 It is a curve diagram of voltage and time during the cycle aging process of lithium-ion batteries;

[0051] Figure 6 This is a graph showing the temperature and stress changes during the cycle aging process of lithium-ion batteries;

[0052] Figure 7 A structural block diagram of a modeling device for a multi-physics field aging coupling model of a lithium-ion battery in one embodiment;

[0053] FIG. 8 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0055] The modeling method of the multi-physics field aging coupling model of lithium-ion batteries provided in the embodiment of the present application can be applied in the application environment shown in Figure 1. The terminal 102 communicates with the server 104 through a network.

[0056] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0057] In one embodiment, Figure 2 As shown, a modeling method for a multi-physics field aging coupling model of a lithium-ion battery is provided, and the method is applied to the terminal 102 in FIG. 1 as an example for explanation, including the following steps:

[0058] S201, obtaining a pre-built equivalent circuit model, and obtaining a pre-built solid electrolyte interface film growth evolution model.

[0059] It should be noted that the equations in this application are equations used to construct a model. The construction of the equations is the construction of the model, and the coupling of the equations is the coupling of the model. In general, the usage of equations and models can be interchangeable, and the meanings expressed are the same. For example, the equivalent circuit equation is the equivalent circuit model.

[0060] Among them, the equivalent circuit model is a model used to perform equivalent analysis on lithium-ion batteries, and the evolution model of solid electrolyte interface film growth is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery.

[0061] For example, an equivalent circuit model (ECM) is a model that uses circuit elements such as a voltage source, a resistor, and a capacitor to simulate the dynamic characteristics of a lithium-ion battery.

[0062] S202, coupling the equivalent circuit model with the evolution model of solid electrolyte interface film growth to construct a multi-physical field aging coupling model of lithium-ion batteries.

[0063] Among them, the multi-physics field aging coupling model of lithium-ion batteries is the model obtained after coupling, which is also called a simplified electrochemical-thermal-mechanical-aging coupling model of lithium-ion batteries.

[0064] Exemplarily, the equivalent circuit model is coupled with the SEI film growth equation to construct a lithium-ion battery aging model.

[0065] S203, based on the test data corresponding to the lithium-ion battery, calibrate various parameters in the multi-physical field aging coupling model of the lithium-ion battery to obtain a calibrated aging coupling model.

[0066] Among them, the test data corresponding to lithium-ion batteries include measurement results, curves of potential change with the lithium insertion state of the electrode, thermodynamic parameters, kinetic parameters, diffusion parameters, and capacity attenuation test data of battery aging.

[0067] The concept of calibration refers to adjusting the parameters in the model by comparing the experimental data with the model calculation results so that it can more accurately reflect the behavior of the actual system, thereby improving the accuracy and reliability of the model.

[0068] Among them, the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of lithium-ion batteries.

[0069] In the modeling method of the multi-physics field aging coupling model of lithium-ion batteries mentioned above, the multi-physics field aging coupling model of lithium-ion batteries is constructed by obtaining the pre-constructed equivalent circuit equation and the evolution equation of solid electrolyte interface film growth, combining the characteristics of the two. First, the equivalent circuit equation is coupled with the film growth evolution equation to form a simplified model that comprehensively reflects the electrochemical, thermodynamic and mechanical properties; then, based on the corresponding experimental data, the various parameters in the model are calibrated to obtain a usable aging coupling model; this scheme effectively improves the understanding and prediction capabilities of lithium-ion battery aging behavior, and provides a scientific basis for battery design and optimization. The electrochemical part of the coupling model is simplified through the equivalent circuit model, and coupled with the aging mechanism model of solid electrolyte interface film growth. While being able to obtain reliable battery aging simulation results, it greatly reduces the time and computing power required for calculation, and improves the simulation and prediction effects of the battery aging model in simulation experiments.

[0070] In one embodiment, after calibrating various parameters in the multi-physics field aging coupling model of the lithium-ion battery to obtain the calibrated aging coupling model, the method also includes: using the calibrated aging coupling model to divide the grid using a finite element modeling method; simulating the lithium-ion battery corresponding to the calibrated aging coupling model based on the grid to obtain a battery simulation result.

[0071] Among them, the grid is used to carry the decomposed elements; the battery simulation results include battery aging simulation results, thermal simulation results and mechanical simulation results.

[0072] For example, the aging mechanism model of lithium-ion batteries with calibrated parameters is used to build a model using the finite element method, divide the grid, and perform lithium-ion battery aging simulation and thermal and mechanical simulation. Specifically, the calibrated parameters are substituted into the finite element model, and the model can be used to predict the aging of the battery and the performance changes and thermal and mechanical changes of the battery after aging.

[0073] In this embodiment, the various parameters in the multi-physics field aging coupling model of lithium-ion batteries are first calibrated to obtain a calibrated aging coupling model; then, the model is used to perform meshing using the finite element method so that the complex geometric structure can be decomposed into simpler elements for calculation; based on the divided mesh, the calibrated aging coupling model is simulated to obtain comprehensive information including battery aging simulation results, thermal simulation results, and mechanical simulation results. This technical solution effectively improves the understanding of the aging mechanism and performance prediction capabilities of lithium-ion batteries, and provides important theoretical support and technical basis for battery design optimization, life assessment, and safety improvement.

[0074] In one embodiment, a pre-constructed evolution model of solid electrolyte interface film growth is obtained, including: determining the side reaction overpotential according to the main reaction overpotential corresponding to the solid electrolyte interface film growth process and the equilibrium potential; determining the current density of the main reaction based on the Tafel equation and the main reaction overpotential, and determining the current density of the side reaction based on the Butler-Wolmer equation and the side reaction overpotential; determining the evolution model of solid electrolyte interface film growth according to the current density of the main reaction, the current density of the side reaction, the main reaction overpotential and the side reaction overpotential.

[0075] Among them, Tafel equation is Tafel equation, Butler-Volmer equation is Butler-Volmer equation.

[0076] Among them, the evolution equation of solid electrolyte interface film growth includes the equation of SEI film growth rate and battery internal state, as well as the relationship between SEI film thickness change and reaction rate.

[0077] For example, according to the reaction chemical equation of the SEI film side reaction, the reaction occurs at the interface between the solid phase material and the SEI film. According to the Tafel equation, the current density of the side reaction is The overpotential of the side reaction In the equivalent circuit model used, there is no concept of liquid phase potential and solid phase potential, but the main reaction overpotential Calculation shows that there are two equilibrium potentials between the two, namely the equilibrium potential of the negative electrode OCP and the SEI side reaction. The former is solved directly through the equivalent circuit model, and the latter is an undetermined constant, which can be regarded as a parameter to be identified.

[0078] At the same time, the main reaction overpotential According to the current density And Butler-Volmer equation calculated.

[0079] at last, and The sum of is the current density brought by the external current, which can be achieved by dividing the battery current by the battery electrode area divided by the battery negative electrode thickness.

[0080] In summary, the reduced-order model is , , , The relationship between the two sets of parameters is established under the simplified model Equation (also known as the equation of SEI film growth rate and battery internal state):

[0081]

[0082] The relationship between SEI film thickness change and reaction rate. The change of film thickness and film resistance satisfies:

[0083]

[0084] In the formula is the molar mass of the SEI film, is the density of the SEI film.

[0085] In this embodiment, first, the side reaction overpotential is determined based on the relationship between the main reaction overpotential and the equilibrium potential; then, the current density of the main reaction is calculated based on the Tafel equation, and the current density of the side reaction is determined based on the Butler-Wolmer equation; by comprehensively considering the main reaction current density, the side reaction current density, the main reaction overpotential and the side reaction overpotential, the evolution equation of the solid electrolyte interface film growth is finally derived to describe the relationship between the film growth rate and the internal state of the battery and the relationship between the film thickness change and the reaction rate; the application of this technical solution makes it possible to effectively simulate the SEI film growth dynamics, provide a clearer understanding and model support, and help optimize battery performance and improve battery life and safety.

[0086] In one embodiment, the equivalent circuit model is coupled with the evolution model of solid electrolyte interface film growth, including: integrating the current volume density in the side reaction corresponding to the evolution equation of solid electrolyte interface film growth to obtain an integral result, and using the integral result as an input of the negative electrode in the equivalent circuit model; using the negative electrode open circuit voltage and total current density of the equivalent circuit model as an input in the evolution model of solid electrolyte interface film growth.

[0087] Among them, the evolution model of solid electrolyte interface film growth is also called the solid electrolyte interface film thickening side reaction model.

[0088] Exemplarily, the coupling method is that the current density in the SEI film thickening side reaction is integrated as an input of the negative electrode of the equivalent circuit model, and the negative electrode OCP and total current density of the equivalent circuit model are used as an input of the SEI film thickening side reaction model. Specifically, the formula expression of the coupling method can be:

[0089]

[0090]

[0091] At this point, the equation construction of the simplified model of lithium-ion battery aging mechanism considering SEI film growth has been completed.

[0092] In this embodiment, a simplified model of the aging mechanism of lithium-ion batteries is established by coupling the equivalent circuit equation with the evolution equation of the growth of the solid electrolyte interface film. In the specific implementation process, the current volume density in the thickening side reaction of the solid electrolyte interface film is first integrated to obtain the integral result, and the result is used as an input of the negative electrode in the equivalent circuit model. In addition, the negative electrode open circuit voltage and total current density of the equivalent circuit model are also used as input variables in the solid electrolyte interface film thickening side reaction model. Through this coupling method, the film growth process is closely combined with the current characteristics of the battery, so that the model can more accurately reflect the changes in the film thickness of the battery during the charging and discharging process and its impact on the battery performance, improve the understanding of the aging mechanism of lithium-ion batteries, promote the optimization of battery performance, and provide a scientific basis for battery design and life prediction.

[0093] In one embodiment, the method further includes: disassembling and measuring the lithium-ion battery to obtain measurement results; performing a half-cell open-circuit potential test on the positive and negative electrodes of the lithium-ion battery to obtain a curve of the potential of a single electrode changing with the lithium insertion state of the electrode; performing a charge and discharge test on the monomer of the lithium-ion battery to obtain thermodynamic parameters according to the input and output characteristics corresponding to the charge and discharge test; performing a dynamic working condition test on the monomer of the lithium-ion battery to obtain thermodynamic parameters, kinetic parameters and diffusion parameters according to the input and output characteristics corresponding to the dynamic working condition test; performing an aging test on the monomer of the lithium-ion battery to determine the capacity attenuation test data of the battery aging; and using the measurement results, the curve of the potential changing with the lithium insertion state of the electrode, the thermodynamic parameters, the kinetic parameters, the diffusion parameters, and the capacity attenuation test data of the battery aging as the test data corresponding to the lithium-ion battery.

[0094] Exemplarily, the current and voltage data during the test are used to calibrate the parameters of the lithium-ion battery aging mechanism model; the tests corresponding to the test data include: charge and discharge characteristic test, aging test, half-cell open circuit potential test and geometric parameter test.

[0095] More specifically, the lithium-ion battery is disassembled; measurement results are obtained, and the lithium-ion battery aging mechanism model is updated using the measurement results; the measurement results include: positive electrode, negative electrode, diaphragm thickness and electrode area; a half-cell open circuit potential test is carried out on the positive electrode and the negative electrode to obtain a curve of the potential of a single electrode changing with the lithium insertion state of the electrode; and the lithium-ion battery aging mechanism model is updated twice using the change curve; a charge and discharge test at a rate of less than 1 / 10C is carried out on the single cell of the lithium-ion battery; thermodynamic parameters are obtained based on the comparison results of the input-output characteristics of the lithium-ion battery aging mechanism model with the current and voltage data measured experimentally; and the thermodynamic parameters are updated using the thermodynamic parameters. The parameters of the lithium-ion battery aging mechanism model are updated three times; the dynamic working condition test is carried out on the lithium-ion battery monomer; the kinetic parameters and diffusion parameters are obtained based on the comparison results of the input-output characteristics of the lithium-ion battery aging mechanism model with the experimentally measured current and voltage data; the lithium-ion battery aging mechanism model is updated four times using the kinetic parameters and diffusion parameters; an aging test is carried out on the lithium-ion battery monomer, and charge and discharge cycles are performed under standard cycle conditions, and the aging test is suspended after a fixed number of charge and discharge cycles, and a capacity test test is carried out; the parameters of the SEI film side reaction model are calibrated according to the capacity decay test data of battery aging.

[0096] In this embodiment, a lithium-ion battery aging mechanism model is constructed through a series of tests and analyses. First, the battery is disassembled and measured to obtain the measurement results of the positive electrode, negative electrode, diaphragm thickness and electrode area, and the aging mechanism model is updated using these data; then, a half-cell open circuit potential test is performed to obtain the curve of the change of each single electrode potential with the lithium insertion state, and the model is updated again; then, a charge and discharge test with a C rate less than one-tenth is carried out, and the thermodynamic parameters are obtained by comparing the experimental current and voltage data with the model input and output characteristics, and the model is updated; further dynamic operating condition tests are carried out to obtain kinetic parameters and diffusion parameters, and the fourth model update is carried out; finally, an aging test is carried out, charging and discharging are carried out under standard cycle conditions, and the capacity decay is tested regularly to calibrate the parameters of the SEI membrane side reaction model; this technical solution realizes the accurate modeling of the lithium-ion battery aging mechanism through multiple rounds of iterative updates, and improves the scientificity and reliability of battery performance improvement and life prediction.

[0097] In one embodiment, the equivalent circuit model corresponding to the equivalent circuit equation is a one-dimensional model used to distinguish the positive and negative electrode charge states, the positive and negative electrode open circuit potentials, the liquid phase overpotential, and the ohmic lumped overpotential. The equivalent circuit model is used to simulate the dynamic characteristics of the battery through electronic components.

[0098] Among them, SOC (State of Charge) refers to the ratio between the current charge of the battery and its maximum charge, usually expressed as a percentage; OCP (Open Circuit Potential) is the potential difference between the two electrodes when the battery is not powered.

[0099] In another embodiment, Figure 3 As shown, a modeling method for a multi-physics field aging coupling model of a lithium-ion battery is provided, comprising the following steps:

[0100] S301, obtaining a pre-built equivalent circuit model; determining a side reaction overpotential according to a main reaction overpotential and an equilibrium potential corresponding to a solid electrolyte interface film growth process.

[0101] S302, determining the current density of the main reaction based on the Tafel equation and the main reaction overpotential, and determining the current density of the side reaction based on the Butler-Wolmer equation and the side reaction overpotential.

[0102] S303, determining an evolution model of solid electrolyte interface film growth according to the current density of the main reaction, the current density of the side reaction, the main reaction overpotential and the side reaction overpotential.

[0103] S304, integrating the current density in the side reaction corresponding to the evolution model of the solid electrolyte interface film growth to obtain an integral result, and using the integral result as an input of the negative electrode in the equivalent circuit model.

[0104] S305, using the negative electrode open circuit voltage and total current density of the equivalent circuit model as an input in the evolution model of solid electrolyte interface film growth, and constructing a multi-physics field aging coupling model of lithium-ion batteries.

[0105] S306, based on the test data corresponding to the lithium-ion battery, calibrate various parameters in the multi-physics field aging coupling model of the lithium-ion battery to obtain a calibrated aging coupling model.

[0106] S307, using the calibrated aging coupling model, adopting a finite element modeling method to divide the grid; the grid is used to carry the decomposed elements.

[0107] S308, simulating the lithium-ion battery corresponding to the calibrated aging coupling model based on the grid to obtain a battery simulation result.

[0108] It should be noted that the specific limitations of the above steps can be found in the specific limitations of the modeling method of a multi-physical field aging coupling model of a lithium-ion battery mentioned above, which will not be repeated here.

[0109] The research on battery aging models mainly includes empirical models, data-driven models, and mechanism models. Among them, empirical models and data-driven models have the disadvantages of poor interpretability and large amounts of data required for model calibration. The construction of mechanism models is based on the description of the main chemical reactions occurring inside the battery, coupling the battery electrochemical model with the dominant aging reaction model, and calibrating the model parameters through experimental data, which has higher application value.

[0110] In the study of aging mechanism models, the quasi-two-dimensional model is one of the widely used battery electrochemical models. The quasi-two-dimensional model accurately describes the chemical reactions occurring inside the battery in the form of partial differential equations, and can obtain better battery simulation results. However, in actual application, the quasi-two-dimensional model requires a large amount of calculation, and the model structure is complex, there are many internal parameters, and some equations need to be solved by finite element method, which makes the model calculation time-consuming, parameter calibration inaccurate, and simulation accuracy poor.

[0111] Based on this, the present application embodiment provides a modeling method for a multi-physics field aging coupling model of a lithium-ion battery, also known as a modeling method for an electrochemical-thermal-mechanical-aging coupling model of a lithium-ion battery. Figures 4 to 6 , a modeling method of a multi-physics field aging coupling model of a lithium-ion battery is described in detail with a specific embodiment. It is worth noting that the following description is only an exemplary description and not a specific limitation of the application.

[0112] The modeling method of the multi-physics field aging coupling model of lithium-ion batteries provided in the present application uses an equivalent circuit model to reduce the order of a quasi-two-dimensional model, which can obtain reliable battery aging simulation results while reducing the time and computing power required for calculation; specifically, the electrochemical part of the coupling model is simplified through an equivalent circuit model, and coupled with an aging mechanism model of SEI (Solid Electrolyte Interphase) film growth, which can greatly reduce the time and computing power required for calculation while obtaining reliable battery aging simulation results.

[0113] The modeling method of the multi-physical field aging coupling model of lithium-ion batteries provided in the present application includes: constructing a simplified electrochemical equation of the battery; constructing an equation for the growth rate of the battery SEI film and the internal state of the battery during the growth of the SEI film; calibrating the parameters of the multi-physical field aging coupling model of the lithium-ion battery using the current and voltage data in the experimental process; the experiments include: charge and discharge characteristic experiments, aging experiments, pulse characteristic experiments, half-cell open circuit potential tests, and geometric parameter tests; using the lithium-ion battery aging coupling model with calibrated parameters, adopting the finite element method to model, divide the grid, and perform lithium-ion battery aging simulation.

[0114] Specifically, it can include the following five steps:

[0115] Step 1: Construct an equivalent circuit model of the battery based on the characteristic curve of the lithium-ion battery.

[0116] Among them, the electrochemical equation is the equivalent circuit model; the equivalent circuit model (ECM) is a model that uses circuit elements such as voltage source, resistor, capacitor, etc. to simulate the dynamic characteristics of lithium-ion batteries. This model can be used to predict battery characteristics such as voltage, current, temperature and capacity.

[0117] The equivalent circuit model is a one-dimensional model that simulates the dynamic characteristics of the battery through electronic components such as resistors and capacitors. The equivalent circuit model used is a model that distinguishes positive and negative electrode SOC, positive and negative electrode OCP, liquid phase overpotential, and ohmic lumped overpotential. There are three first-order inertia links that describe the dynamic processes of the positive electrode solid phase, negative electrode solid phase, and liquid phase, respectively.

[0118] Step 2: Construct the evolution equation of the battery state during the growth of SEI film.

[0119] The side reactions of SEI growth include lithium ion consumption, electrolyte consumption, and solid matter generation. The current flow density of the side reactions of SEI film aging is modeled through the Tafel equation, Butler-Volmer equation, and other equations.

[0120] Construct a SEI membrane side reaction rate model. According to the reaction chemical equation of the SEI membrane side reaction, the reaction occurs at the interface between the solid phase material and the SEI membrane. According to the Tafel equation, the current density of the side reaction is The overpotential of the side reaction In the equivalent circuit model used, there is no concept of liquid phase potential and solid phase potential, but the main reaction overpotential Calculation shows that there are two equilibrium potentials between the two, namely the equilibrium potential of the negative electrode OCP and the SEI side reaction. The former is solved directly through the equivalent circuit model, and the latter is an undetermined constant, which can be regarded as a parameter to be identified.

[0121] At the same time, the main reaction overpotential According to the current density And Butler-Volmer equation calculated.

[0122] at last, and The sum of is the current density brought by the external current, which can be achieved by dividing the battery current by the battery electrode area divided by the battery negative electrode thickness.

[0123] In summary, the reduced-order model is , , , The relationship between the two sets of parameters is established under the simplified model Equation (also known as the equation of SEI film growth rate and battery internal state):

[0124]

[0125] The relationship between SEI film thickness change and reaction rate. The change of film thickness and film resistance satisfies:

[0126]

[0127] In the formula is the molar mass of the SEI film, is the density of the SEI film.

[0128] Step 3: Couple the equivalent circuit model with the SEI film growth equation to construct a lithium-ion battery aging model.

[0129] The coupling method is that the current density in the SEI film thickening side reaction is integrated as an input of the negative electrode of the equivalent circuit model, and the negative electrode OCP and total current density of the equivalent circuit model are used as an input of the SEI film thickening side reaction model.

[0130]

[0131]

[0132] The coupling relationship between the two models is shown in the attached figure. Figure 2 As shown. So far, the equation construction of the simplified model of lithium-ion battery aging mechanism considering SEI film growth has been completed.

[0133] Step 4: Use the current and voltage data during the test to calibrate the parameters of the lithium-ion battery aging mechanism model; the test includes: charge and discharge characteristic test, aging test, half-cell open circuit potential test and geometric parameter test.

[0134] The lithium-ion battery is disassembled; measurement results are obtained, and the lithium-ion battery aging mechanism model is updated using the measurement results; the measurement results include: positive electrode, negative electrode, diaphragm thickness and electrode area.

[0135] Half-cell open-circuit potential tests were carried out on the positive and negative electrodes to obtain a curve of the potential of a single electrode changing with the lithium insertion state of the electrode; and the change curve was used to update the lithium-ion battery aging mechanism model for a second time.

[0136] The single lithium-ion battery cells were subjected to charge and discharge tests at a rate less than 1 / 10C. The thermodynamic parameters were obtained based on the comparison results of the input-output characteristics of the lithium-ion battery aging mechanism model with the experimentally measured current and voltage data. The lithium-ion battery aging mechanism model was updated three times using the thermodynamic parameters.

[0137] Conduct dynamic operating condition tests on lithium-ion battery cells; obtain kinetic parameters and diffusion parameters based on the comparison results of the input-output characteristics of the lithium-ion battery aging mechanism model with the experimentally measured current and voltage data; and update the lithium-ion battery aging mechanism model four times using the kinetic parameters and diffusion parameters.

[0138] An aging test is carried out on the single cells of the lithium-ion battery. Charge and discharge cycles are carried out under standard cycle conditions. The aging test is suspended after a fixed number of charge and discharge cycles, and a capacity test is carried out. The parameters of the SEI film side reaction model are calibrated based on the capacity decay test data of battery aging.

[0139] The following is described by specific examples:

[0140] First, disassemble the lithium-ion battery under study, measure the thickness of its positive electrode, negative electrode, and separator, and measure its electrode area. If conditions permit, a scanning electron microscope can also be used to measure the particle radius of the positive and negative electrode active materials. , the measurement results of the geometric parameters are substituted into the aging mechanism model.

[0141] Next, a half-cell open circuit potential test was carried out on the disassembled positive and negative electrodes to obtain the curve of the potential of a single electrode changing with the lithium insertion state of the electrode, that is, the change of the positive and negative electrode materials , and substitute it into the aging mechanism model.

[0142] Then, the lithium-ion battery under study was subjected to 1 / 20C charge and discharge test at 25°C. By comparing the input and output characteristics of the model with the current and voltage data measured experimentally, the thermodynamic parameters in the model were calibrated using heuristic search algorithms such as genetic algorithms, including , Etc., and substitute into the aging mechanism model.

[0143] Then, the HPPC test was carried out on the lithium-ion battery under study at 25°C. By comparing the input-output characteristics of the model with the current-voltage data measured experimentally, the kinetic parameters and diffusion parameters in the model were calibrated through heuristic search algorithms such as genetic algorithms, including , Etc., and substitute into the aging mechanism model.

[0144] Finally, an aging test was carried out on the battery under study at 25°C, and charge and discharge cycles were performed under standard cycle conditions. The aging test was paused every 100 charge and discharge cycles, and a 1 / 3C charge and discharge characteristic test was carried out to test the capacity change. Based on the capacity decay test data of battery aging, the parameters of the SEI film side reaction model were calibrated.

[0145] Step 5: Use the calibrated lithium-ion battery aging mechanism model, adopt the finite element method to build a model, divide the grid, and perform lithium-ion battery aging simulation and thermal and mechanical simulation.

[0146] Substituting the calibrated parameters into the finite element model, the model can be used to predict the aging of the battery and the performance changes, thermal and mechanical changes of the battery after aging. Figure 3 The simulation results of the aging mechanism model for the response voltage of a lithium-ion battery with 1C charge and 1C discharge cycles are given. Figure 4 The simulation results of the aging model on the temperature and stress changes during the battery aging process are given.

[0147] This application targets SEI film formation, a common and important aging mechanism in the aging process of lithium-ion batteries. This application comprehensively considers the consumption of available lithium ions, electrolyte consumption, and SEI film formation process associated with this side reaction process, and combines the battery equivalent circuit model with the SEI film formation side reaction model, thereby comprehensively and accurately modeling the battery aging process coupled with the SEI film formation side reaction. Based on the method described in this patent, it is expected to achieve more accurate prediction of battery aging and electrochemical performance of aged batteries based on a small amount of battery test data.

[0148] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0149] Based on the same inventive concept, the embodiment of the present application also provides a modeling device for a lithium-ion battery multi-physics field aging coupling model for implementing the modeling method of the lithium-ion battery multi-physics field aging coupling model involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the modeling device for one or more lithium-ion battery multi-physics field aging coupling models provided below can be referred to the limitations of the modeling method of the lithium-ion battery multi-physics field aging coupling model above, and will not be repeated here.

[0150] In one embodiment, Figure 7 As shown, a modeling device for a multi-physical field aging coupling model of a lithium-ion battery is provided, comprising: an equation acquisition module 701, a model coupling module 702, and a model parameter calibration module 703, wherein:

[0151] The equation acquisition module 701 is used to acquire a pre-built equivalent circuit model and a pre-built evolution model of solid electrolyte interface film growth; the equivalent circuit model is a model for equivalent lithium-ion batteries, and the evolution model of solid electrolyte interface film growth is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery;

[0152] A model coupling module 702 is used to couple the equivalent circuit model with the evolution model of the solid electrolyte interface film growth to construct a multi-physics field aging coupling model of the lithium-ion battery;

[0153] The model parameter calibration module 703 is used to calibrate various parameters in the multi-physics field aging coupling model of the lithium-ion battery based on the test data corresponding to the lithium-ion battery to obtain a calibrated aging coupling model; the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of the lithium-ion battery.

[0154] Each module in the modeling device of the multi-physics field aging coupling model of lithium-ion batteries can be implemented in whole or in part by software, hardware and a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module above.

[0155] In addition, the present application also provides a lithium-ion battery aging simulation system corresponding to a modeling method of a lithium-ion battery multi-physical field aging coupling model, including: an equivalent circuit equation construction module, used to construct an equivalent circuit equation of the battery; an evolution equation construction module, used to construct an evolution equation for SEI film growth; a lithium-ion battery aging mechanism model construction module, used to couple the equivalent circuit equation with the evolution equation to construct a lithium-ion battery aging mechanism model; a parameter calibration module, used to calibrate the parameters of the lithium-ion battery aging mechanism model using current and voltage data during the test; the tests include: charge and discharge characteristic tests, aging tests, half-cell open circuit potential tests, and geometric parameter tests; an aging simulation module, used to use the lithium-ion battery aging mechanism model with calibrated parameters, adopt the finite element method to model, divide the grid, and perform lithium-ion battery aging simulation.

[0156] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in the figure. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a modeling method for a multi-physical field aging coupling model of a lithium-ion battery is realized. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0157] Those skilled in the art will understand that the structure shown in FIG. 8 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0158] In one embodiment, a computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps in the above method embodiments are implemented.

[0159] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0160] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0161] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0162] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0163] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A modeling method for a multi-physics field aging coupling model of a lithium-ion battery, characterized in that: The method comprises: Obtaining a pre-constructed equivalent circuit model and a pre-constructed solid electrolyte interface film growth evolution model; the equivalent circuit model is a model for equivalent lithium-ion batteries, and the solid electrolyte interface film growth evolution model is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery; The equivalent circuit model is coupled with the evolution model of the solid electrolyte interface film growth to construct a multi-physical field aging coupling model of lithium-ion batteries; Based on the test data corresponding to the lithium-ion battery, various parameters in the multi-physical field aging coupling model of the lithium-ion battery are calibrated to obtain a calibrated aging coupling model; the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of the lithium-ion battery.

2. The method according to claim 1, characterized in that After the step of calibrating various parameters in the multi-physical field aging coupling model of the lithium-ion battery to obtain the calibrated aging coupling model, the method further includes: Using the calibrated aging coupling model, a finite element modeling method is used to divide the grid; the grid is used to carry the decomposed elements; Simulating the lithium-ion battery corresponding to the calibrated aging coupling model based on the grid to obtain a battery simulation result; The battery simulation results include battery aging simulation results, thermal simulation results and mechanical simulation results.

3. The method according to claim 1, characterized in that The step of obtaining a pre-constructed evolution model of solid electrolyte interface film growth comprises: Determine the side reaction overpotential based on the main reaction overpotential and equilibrium potential corresponding to the solid electrolyte interface film growth process; Determine the current density of the main reaction based on the Tafel equation and the main reaction overpotential, and determine the current density of the side reaction based on the Butler-Wolmer equation and the side reaction overpotential; An evolution model of the growth of the solid electrolyte interface film is determined according to the current density of the main reaction, the current density of the side reaction, the main reaction overpotential and the side reaction overpotential.

4. The method according to claim 1, characterized in that: The coupling of the equivalent circuit model with the evolution model of the solid electrolyte interface film growth comprises: Integrating the current density in the side reaction corresponding to the evolution model of the solid electrolyte interface film growth to obtain an integral result, and using the integral result as an input of the negative electrode in the equivalent circuit model; The negative electrode open circuit voltage and total current density of the equivalent circuit model are used as an input in the evolution model of solid electrolyte interface film growth.

5. The method according to claim 1, characterized in that The method further comprises: Disassembling and measuring the lithium-ion battery to obtain a measurement result; Conducting a half-cell open circuit potential test on the positive electrode and the negative electrode of the lithium-ion battery to obtain a curve of the potential of a single electrode as a function of the lithium insertion state of the electrode; Carrying out charge and discharge tests on the monomers of the lithium-ion battery, and obtaining thermodynamic parameters according to input and output characteristics corresponding to the charge and discharge tests; Conducting a dynamic working condition test on the monomer of the lithium-ion battery, and obtaining thermodynamic parameters, kinetic parameters and diffusion parameters according to the input-output characteristics corresponding to the dynamic working condition test; Carry out aging tests on lithium-ion battery cells to determine the capacity attenuation test data of battery aging; The measurement results, the curve of the change of the potential with the lithium insertion state of the electrode, the thermodynamic parameters, the kinetic parameters, the diffusion parameters, and the capacity attenuation test data of the battery aging are used as the test data corresponding to the lithium ion battery.

6. The method according to claim 1, characterized in that The equivalent circuit model is a one-dimensional model used to distinguish the positive and negative electrode charge states, the positive and negative electrode open circuit potentials, the liquid phase overpotential, and the ohmic lumped overpotential. The equivalent circuit model is used to simulate the dynamic characteristics of the battery through electronic components.

7. A modeling device for a multi-physics field aging coupling model of a lithium-ion battery, characterized in that: The device comprises: An equation acquisition module is used to acquire a pre-constructed equivalent circuit model and a pre-constructed evolution model of solid electrolyte interface film growth; the equivalent circuit model is a model for equivalent lithium-ion batteries, and the evolution model of solid electrolyte interface film growth is a model that characterizes the growth rate of the solid electrolyte interface film of the lithium-ion battery and the internal state of the lithium-ion battery; A model coupling module, used to couple the equivalent circuit model with the evolution model of the solid electrolyte interface film growth to construct a multi-physical field aging coupling model of lithium-ion batteries; A model parameter calibration module is used to calibrate various parameters in the multi-physical field aging coupling model of the lithium-ion battery based on the test data corresponding to the lithium-ion battery to obtain a calibrated aging coupling model; the calibrated aging coupling model is used to simulate and predict the aging process and electrochemical performance of the lithium-ion battery.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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