Lithium ion battery mesoscopic electrochemical model structure and method based on real microstructure

Abstract

The invention relates to a lithium ion battery mesoscopic electrochemical model structure and method based on a real microstructure, a model comprises a geometric model part, an electrochemical parameter part and a partial differential equation set part of a lithium ion battery, and the geometric model part comprises electrode geometry, diaphragm geometry and current collector geometry; the electrode is geometrically a three-dimensional real microstructure image of the lithium ion battery electrode, the diaphragm is geometrically a homogenized porous medium, and the current collector is geometrically a three-dimensional entity of the current collector; the components of the geometric model part are combined to form a complete total battery unit; the partial differential equation set part is used for defining a conservation equation of the battery unit; the electrochemical parameter part is used for providing input parameters for variables of the partial differential equation set part. Compared with the prior art, the method has the advantages that the electrochemical characteristics of the battery on the active particle-pore mesoscale can be accurately expressed in a wide charge-discharge rate range, and digital twinning with higher precision and fidelity is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium-ion battery modeling, and in particular to a lithium-ion battery mesoscopic electrochemical model structure and method based on a real microstructure. Background Art

[0002] As a key representative of modern battery technology, lithium-ion batteries have become a core technology in the field of electrical energy storage due to their significant advantages, including high energy density, high efficiency, long cycle life, and low self-discharge. In a wide range of applications, including electric vehicles, renewable energy systems, and portable electronic devices, lithium-ion batteries, with their exceptional performance, provide crucial technical support for addressing global energy needs and environmental challenges. As the global transition to a low-carbon economy and sustainable development accelerates, the research and development of lithium-ion batteries has not only driven advancements in energy storage technology but also played a key role in achieving the efficient utilization of green energy and optimizing and upgrading the energy structure.

[0003] In the research and development and application of lithium-ion batteries, battery modeling plays an important role and significance. Battery modeling can help us deeply understand the physical and chemical mechanisms inside the battery, reveal key processes such as charge transfer, material transfer, and interfacial reactions, and thus provide theoretical support for battery design optimization and performance improvement. In addition, by establishing an accurate battery model, it is possible to predict the performance of the battery under different working conditions, evaluate its safety, reliability and life, and ensure its stability and efficiency in practical applications. At the same time, as the basis of the battery management system (BMS), the battery model can be used to optimize the charging and discharging strategy and extend the battery life. Therefore, battery modeling is not only a key link in promoting the research and development of new battery materials and processes, but also an important means to improve the use effect of batteries. It has important practical significance and application value for achieving high-performance, long-life and safe lithium-ion batteries.

[0004] Currently, the electrochemical model of batteries is mainly based on the traditional porous electrode theory, which is called the P2D model. For example, the invention patent with publication number CN118332872A discloses a three-dimensional electrochemical-thermal coupling modeling method for lithium-ion batteries containing a composite current collector; the invention patent with publication number CN115189047A discloses a lithium-ion battery non-lithium precipitation control method and system; and the invention patent with publication number CN117454670A discloses a lithium ion aging state prediction method and device based on an electrochemical model. According to the assumptions of the porous electrode theory, the positive and negative active particles are regarded as uniformly distributed spheres, and their electrode structure is directly determined by two geometric parameters (particle size and porosity). The P2D model has high accuracy under low-rate charge and discharge conditions and can accurately analyze the internal and external electrochemical characteristics of the battery.

[0005] However, at high rates, the complex electrode microstructure significantly limits the transport of lithium ions. At this time, the P2D model, based on the homogenization assumption, underestimates the battery polarization and thus has low accuracy. Given the current demand for higher performance at extreme rates, such as fast charge / discharge, the P2D model cannot serve as a tool for advanced battery design and management. Furthermore, the actual microstructure of the electrode, such as the size, position, and orientation of active particles and the shape of pores, significantly influences battery performance. The P2D model ignores these details at the geometric level, making it unsuitable for optimizing electrode microstructure at the mesoscopic scale. Summary of the Invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art P2D model, which underestimates the battery polarization and has low accuracy, and ignores the size, position, orientation and pore shape of the active particles at the geometric level, and provide a lithium-ion battery mesoscopic electrochemical model structure and method based on real microstructure, using advanced imaging technology to obtain the three-dimensional real microstructure of the positive and negative electrodes and generate high-precision grids based on bitmap data, and obtain the lithium-ion battery mesoscopic electrochemical model by defining the physical field and boundary conditions for different geometric domains of the battery. Compared with the traditional P2D model, the obtained mesoscopic electrochemical model can obtain high-precision simulation results within a larger charge and discharge rate range. In addition, the mapping relationship between the electrode microstructure and the macroscopic performance of the battery can also be obtained. This model is of great significance for optimizing the electrode microstructure to improve the fast charging capability of the battery and extend the cycle life.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A mesoscopic electrochemical model structure of a lithium-ion battery based on a real microstructure, characterized by comprising a geometric model portion of the lithium-ion battery, an electrochemical parameter portion, and a partial differential equation portion, wherein the geometric model portion includes electrode geometry, diaphragm geometry, and current collector geometry; the electrode geometry is a three-dimensional real microstructure image of the lithium-ion battery electrode, the diaphragm geometry is a homogenized porous medium, and the current collector geometry is a three-dimensional solid of the current collector; the various components of the geometric model portion are combined to form a complete full battery unit;

[0009] The partial differential equation group is used to define the conservation equation of the battery cell;

[0010] The electrochemical parameter part is used to provide input parameters for variables in conservation equations.

[0011] Furthermore, the electrode geometry is obtained by an imaging instrument and image post-processing technology, including the three-dimensional real microstructure of the positive electrode and the three-dimensional real microstructure of the negative electrode;

[0012] The positive electrode three-dimensional real microstructure includes a positive electrode active particle phase and a positive electrode pore phase;

[0013] The negative electrode three-dimensional real microstructure includes a negative electrode active particle phase and a negative electrode pore phase;

[0014] The current collector geometry includes the positive electrode current collector geometry and the negative electrode current collector geometry.

[0015] Furthermore, the electrochemical parameter part includes current collector parameters, active particle parameters, electrolyte parameters and reaction kinetic parameters;

[0016] The current collector parameters include the conductivity of the positive electrode current collector and the conductivity of the negative electrode current collector;

[0017] The active particle parameters include the positive and negative electrode solid phase diffusion coefficients, the positive and negative electrode solid phase initial lithium ion concentrations, the positive and negative electrode solid phase maximum lithium insertion concentrations, the positive and negative electrode solid phase conductivity and the positive and negative electrode equilibrium potentials;

[0018] The electrolyte parameters include liquid phase diffusion coefficient, liquid phase initial lithium ion concentration, liquid phase conductivity, transfer number and activity correlation;

[0019] The reaction kinetic parameters include positive and negative electrode reaction rate constants.

[0020] Furthermore, the partial differential equations include a solid-phase mass transfer conservation equation, a solid-phase charge transfer conservation equation, a liquid-phase mass transfer conservation equation, a liquid-phase charge transfer conservation equation, and a Butler-Volmer reaction kinetics equation.

[0021] The present invention also provides a modeling method for a lithium-ion battery mesoscopic electrochemical model structure based on a real microstructure as described above, comprising the following steps:

[0022] Acquire and perform three-dimensional imaging of positive and negative electrode samples to obtain three-dimensional real microstructure images of the positive and negative electrodes;

[0023] Based on the three-dimensional real microstructure images of the positive and negative electrodes, an image processing method is used to segment the positive and negative electrode active particle phases and the pore phase, and a first positive and negative electrode porosity is calculated; experiments are conducted on the positive and negative electrode samples to obtain a second positive and negative electrode porosity; the difference between the first positive and negative electrode porosity and the second positive and negative electrode porosity is compared to verify the accuracy of the three-dimensional imaging result, and the three-dimensional imaging result that passes the verification is selected;

[0024] Based on the three-dimensional real microstructure images of the positive and negative electrodes, key geometric features are determined as evaluation indicators, and a representative volume unit is selected, wherein the key geometric features of the volume unit have the same statistical characteristics as those of the complete electrode;

[0025] Based on the representative volume unit, establish the positive electrode microstructure geometry, the negative electrode microstructure geometry, the separator, the positive electrode current collector and the negative electrode current collector, and combine them to obtain a complete full battery unit and mesh each part of the battery unit based on the bitmap data;

[0026] Obtaining electrochemical parameters required for the battery cell, including current collector parameters, active particle parameters, electrolyte parameters, and reaction kinetic parameters;

[0027] Define solid-phase charge transfer conservation equations for the positive and negative current collectors and active particles in the battery cell, define solid-phase mass transfer conservation equations for the positive and negative active particles, define liquid-phase charge transfer conservation equations and liquid-phase mass transfer conservation equations for the positive and negative electrode pores and separator pores, and define a Butler-Volmer reaction kinetic equation for the positive and negative electrode solid / liquid interfaces; assign the electrochemical parameters to the variables of each equation to obtain a preliminary mesoscopic electrochemical model of a lithium-ion battery;

[0028] Discharge tests and charge tests were carried out on the positive and negative electrode samples and the preliminary lithium-ion battery mesoscopic electrochemical model respectively. The accuracy of the preliminary lithium-ion battery mesoscopic electrochemical model was verified based on the experimental terminal voltage data obtained. The verified preliminary lithium-ion battery mesoscopic electrochemical model was used as the final lithium-ion battery mesoscopic electrochemical model based on the real microstructure of the electrode.

[0029] Furthermore, the key geometric characteristics include the active particle D50 size, porosity and McMullin number in the thickness direction;

[0030] The McMullin number is the ratio of the intrinsic liquid phase conductivity of the electrolyte to the effective liquid phase conductivity of the electrode or the ratio of the intrinsic liquid phase diffusion coefficient of the electrolyte to the effective liquid phase diffusion coefficient of the electrode;

[0031] The representative volume unit selected has the characteristic that when the size continues to increase, the key geometric features of the electrode do not change significantly.

[0032] Furthermore, the current collector parameters include the conductivity of the positive electrode current collector and the conductivity of the negative electrode current collector;

[0033] The active particle parameters include the positive and negative electrode solid phase diffusion coefficients, the positive and negative electrode solid phase initial lithium ion concentrations, the positive and negative electrode solid phase maximum lithium insertion concentrations, the positive and negative electrode solid phase conductivity and the positive and negative electrode equilibrium potentials;

[0034] The electrolyte parameters include liquid phase diffusion coefficient, liquid phase initial lithium ion concentration, liquid phase conductivity, transfer number and activity correlation;

[0035] The reaction kinetic parameters include positive and negative electrode reaction rate constants.

[0036] Furthermore, the positive and negative electrode solid phase diffusion coefficients, positive and negative electrode equilibrium potentials, and positive and negative electrode reaction rate constants are obtained based on button half-cell testing;

[0037] The positive electrode collector conductivity, negative electrode collector conductivity, positive and negative electrode solid phase initial lithium ion concentration, positive and negative electrode solid phase maximum lithium insertion concentration, positive and negative electrode solid phase conductivity, liquid phase diffusion coefficient, liquid phase initial lithium ion concentration, liquid phase conductivity, transfer number and activity correlation adopt literature reference values.

[0038] Furthermore, the diaphragm pores are defined by a partial differential equation in a volume-averaged manner;

[0039] The positive and negative electrode current collectors, the positive and negative electrode active particle phases and the positive and negative electrode pore phases define partial differential equations on the corresponding real structures.

[0040] Furthermore, the expression of the solid phase charge transfer conservation equation is:

[0041] ▽·(-σ s ▽φ s )=Q s

[0042] Where, σ s is the electronic conductivity of the solid phase material, φ s is the solid phase potential, Q s is the solid phase charge source term;

[0043] The expression of the solid phase mass transfer conservation equation is:

[0044]

[0045] Where D s is the solid phase diffusion coefficient, c s is the solid phase lithium concentration, t is the time;

[0046] The expression of the liquid phase charge transfer conservation equation is:

[0047]

[0048] Where, σ l is the liquid phase electronic conductivity, φ l is the liquid phase potential, R is the ideal gas constant, T is the temperature, F is the Faraday constant, f is the activity correlation, c l is the liquid phase lithium ion concentration, t + is the liquid phase ion transfer number, Q l is the liquid phase charge source term;

[0049] The expression of the liquid phase mass transfer conservation equation is:

[0050]

[0051] Where D l is the liquid phase diffusion coefficient, i l is the local current density in the liquid phase;

[0052] The expression of the Butler-Volmer reaction kinetic equation is:

[0053]

[0054] η=φ s -φ l -E eq

[0055] Where i loc is the local current density, i0 is the exchange current density, α is the charge transfer coefficient, η is the electrode overpotential, k is the reaction rate constant, c s,max is the maximum lithium insertion concentration in the solid phase, c s,surf is the lithium ion concentration on the ion surface, c l,ref =1000mol / L is the initial lithium ion concentration in the liquid phase, φ s is the solid phase potential, φ l is the liquid phase potential, E eq is the electrode equilibrium potential.

[0056] Compared with the prior art, the present invention has the following advantages:

[0057] (1) This invention breaks the homogenization assumption of the positive and negative electrode geometric structures in the traditional P2D model. It uses advanced imaging instruments and image processing methods to obtain the three-dimensional real microstructure of the positive and negative electrodes and divide the grid based on the bitmap data. It constructs a geometric model part including the electrode geometry, diaphragm geometry and current collector geometry. By defining the physical field and inputting the corresponding electrochemical parameters, it realizes the numerical simulation of the electrochemical characteristics inside and outside the battery.

[0058] The electrode geometry is obtained by imaging instruments and image post-processing technology, established at the electrode particle and pore scale, and can be used to obtain the mapping relationship between the size and morphology of active particles and macroscopic electrochemical performance. Compared with the P2D model, it has deeper expression capabilities and more multi-dimensional optimization parameters; it can accurately express the electrochemical characteristics of the battery at the active particle-pore mesoscopic scale within a wide charge and discharge rate range, and achieve digital twins with higher precision and fidelity.

[0059] (2) The construction process of the partial differential equation group of the present invention includes: defining the solid-phase charge transfer conservation equation for the positive and negative electrode current collectors and active particles in the battery cell, defining the solid-phase mass transfer conservation equation for the positive and negative electrode active particles, defining the liquid-phase charge transfer conservation equation and the liquid-phase mass transfer conservation equation for the positive and negative electrode pores and the diaphragm pores, and defining the Butler-Volmer reaction kinetic equation for the positive and negative electrode solid / liquid interface; fully considering the influence of the heterogeneity of the electrode structure on charge transfer, ion transfer and solid / liquid interface electrochemical reaction, it can accurately express the electrochemical characteristics of lithium-ion batteries within a wider range of charge and discharge rates.

[0060] (3) The mesoscopic electrochemical model of lithium-ion batteries based on real microstructures proposed in the present invention can be further coupled with thermal, force, attenuation and other models to achieve multi-scale and multi-physics field modeling of batteries. This is of great significance for understanding the complex physical and chemical processes inside the battery and improving battery performance. It is also of great significance for designing advanced electrode structures and battery management strategies for fast charging scenarios and realizing battery systems with longer life and higher safety and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A schematic diagram of a mesoscopic electrochemical model structure of a lithium-ion battery based on a real microstructure provided in an embodiment of the present invention;

[0062] Figure 2 A schematic diagram of a three-dimensional real microstructure of a positive electrode and a negative electrode provided in an embodiment of the present invention;

[0063] Figure 3 A schematic diagram of the overall flow of a modeling method provided in an embodiment of the present invention;

[0064] Figure 4 A schematic diagram of a grid of a complete battery cell provided in an embodiment of the present invention;

[0065] Figure 5 A comparison chart of the terminal voltages of a model according to an embodiment of the present invention and a comparative model under 0.2C, 2C, and 4C discharge and 0.2C, 1C, and 2C charging conditions, as well as experimental results, is provided in an embodiment of the present invention;

[0066] Figure 6 This is a graph showing changes in electrolyte salt concentration and active particle lithium concentration in the positive electrode over time under 2C discharge in a model of an embodiment of the present invention provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0067] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0068] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0069] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0070] Example 1

[0071] This embodiment provides a mesoscopic electrochemical model structure of a lithium-ion battery based on a real microstructure, such as Figure 1 The figure shows the principle diagram of the mesoscopic electrochemical model of a lithium-ion battery according to the present invention, which includes the geometric model, electrochemical parameters, and partial differential equations of the lithium-ion battery. Unlike the P2D model based on porous electrode theory, this model is based on the actual electrode microstructure and does not make any homogenization assumptions when defining the physical field in the electrode region. Because its electrode geometry can express the actual morphology of particles and pores, this model can express the electrochemical behavior inside and outside the battery at the particle-pore scale and has higher accuracy over a wider range of charge and discharge rates.

[0072] The battery geometry model consists of electrode geometry, separator geometry, and current collector geometry. The electrode geometry is a three-dimensional real microstructure image obtained by advanced imaging instruments and image post-processing technology, including the three-dimensional real microstructure of the positive electrode and the three-dimensional real microstructure of the negative electrode. Figure 2 As shown in a and b, the three-dimensional real microstructures of the positive and negative electrodes in the embodiment of the present invention, the three-dimensional real microstructure of the positive electrode includes the positive electrode active particle phase and the positive electrode pore phase, and the three-dimensional real microstructure of the negative electrode includes the negative electrode active particle phase and the negative electrode pore phase; the diaphragm geometry is a homogenized porous medium; the current collector geometry is a three-dimensional entity, including the positive electrode current collector geometry and the negative electrode current collector geometry.

[0073] The electrochemical parameters include current collector parameters, active particle parameters, electrolyte parameters, and reaction kinetic parameters. Current collector parameters include the positive electrode current collector conductivity and the negative electrode current collector conductivity; active particle parameters include the positive and negative electrode solid phase diffusion coefficients, the positive and negative electrode solid phase initial lithium ion concentrations, the positive and negative electrode solid phase maximum lithium insertion concentrations, the positive and negative electrode solid phase conductivity, and the positive and negative electrode equilibrium potentials; electrolyte parameters include the liquid phase diffusion coefficient, the liquid phase initial lithium ion concentration, the liquid phase conductivity, the transfer number, and the activity correlation; and reaction kinetic parameters include the positive and negative electrode reaction rate constants.

[0074] The partial differential equations are used to define the conservation equations of the battery cell, including the solid-phase mass transfer conservation equation, the solid-phase charge transfer conservation equation, the liquid-phase mass transfer conservation equation, the liquid-phase charge transfer conservation equation, and the Butler-Volmer reaction kinetics equation.

[0075] like Figure 3 As shown, this embodiment also provides a modeling method for the above-mentioned lithium-ion battery mesoscopic electrochemical model structure based on the real microstructure, comprising the following steps:

[0076] A. Acquire and perform three-dimensional imaging of the positive and negative electrode samples to obtain three-dimensional real microstructure images of the positive and negative electrodes.

[0077] In this embodiment, the battery sample is a small soft-pack battery with a rated capacity of 1.2Ah, the positive electrode material is NCM523, and the negative electrode material is graphite. The battery sample is disassembled in a glove box to obtain positive and negative electrode samples. A focused ion beam-scanning electron microscope (FIB-SEM) is used to obtain a two-dimensional image test set of the positive and negative electrodes, respectively. The resolution of the two-dimensional image is 30nm×30nm, and 1300 two-dimensional images of the positive and negative electrodes are obtained, with a thickness interval of 30nm. The two-dimensional image set is imported into the three-dimensional visualization software Avizo for cropping, denoising, and then three-dimensional reconstruction is performed to obtain a three-dimensional real microstructure image of the positive and negative electrodes.

[0078] B. Based on the three-dimensional real microstructure images of the positive and negative electrodes, use imaging methods to segment the positive and negative electrode active particle phases and pore phases, and calculate the first positive and negative electrode porosity; conduct experiments on the positive and negative electrode samples to obtain the second positive and negative electrode porosity; compare the differences between the first positive and negative electrode porosity and the second positive and negative electrode porosity to verify the accuracy of the three-dimensional reconstruction results, and select the three-dimensional imaging results that have passed the verification.

[0079] In this embodiment, the imaging method used is threshold segmentation. Among them, the grayscale value range of the positive electrode active particle phase selection is 28009-65535, and the grayscale value range of the positive electrode pore phase selection is 0-28008; the grayscale value range of the negative electrode active particle phase selection is 0-25147, and the grayscale value range of the negative electrode pore phase selection is 25148-65535. Based on the image, the porosity of the positive and negative electrodes is 28.8% and 36.2%, respectively. At the same time, the positive and negative electrode samples are experimentally tested using a mercury intrusion meter, and the porosity of the positive and negative electrodes is 30.2% and 36.4%, respectively. By comparing the images and the experimental results, it is found that the errors of the positive and negative electrode porosity are 1.4% and 0.2%, respectively, proving that the three-dimensional microstructure of the positive and negative electrodes obtained by three-dimensional reconstruction is accurate and reliable.

[0080] C. Based on the obtained large-scale microstructure images, key geometric features are determined as evaluation indicators, and representative volume units are selected whose key geometric parameters have the same statistical characteristics compared with the complete geometry.

[0081] When calculating the model of the present invention, if the electrode geometry is too small, its structural characteristics will not be consistent with the actual electrode, resulting in inaccurate simulation results. If the electrode size is too large, the model will have too many meshes, resulting in excessive calculation time and serious impact on efficiency. Therefore, it is necessary to select representative volume elements whose key geometric parameters have the same statistical characteristics as the complete geometry. In this way, the electrode geometry has accurate structural characteristics while minimizing the model complexity and reducing calculation time.

[0082] In the P2D model, the input parameters of the electrode geometry are the active particle D50 size and porosity. In this embodiment, considering that the effective transport parameters of the electrode will have a great impact on the model results, the active particle D50 size, porosity and McMullin number are selected as evaluation indicators, where the McMullin number is the ratio of the intrinsic ionic conductivity of the electrolyte to the effective ionic conductivity of the electrode. The geometric dimensions of the analysis are increased along the diagonal direction of the positive and negative electrodes respectively, and the changes of the above three key geometric features with the size of the region of interest are calculated. The results show that when the positive electrode size reaches 27 microns × 27 microns × 27 microns and the negative electrode size reaches 33 microns × 33 microns × 33 microns, the active particle D50 size, porosity and McMullin number of the electrode will reach convergence and no longer change significantly with the increase of the electrode size. This size is a representative volume unit.

[0083] D. Based on representative volume cells, establish the positive electrode microstructure geometry, negative electrode microstructure geometry, separator, positive electrode current collector and negative electrode current collector, and combine them to form a complete battery cell and divide the grid of each part based on the bitmap data.

[0084] In the multi-physics simulation software COMSOL, the geometry of the positive electrode current collector, negative electrode current collector and separator is established in the form of a cuboid, with dimensions of 33 microns × 33 microns × 12 microns, 33 microns × 33 microns × 10 microns, and 33 microns × 33 microns × 25 microns, respectively. Since the representative volume unit size of the positive electrode is 27 microns × 27 microns × 27 microns, in order to match the negative electrode geometry, a structure with a size of 33 microns × 33 microns × 27 microns is cut out from the original large-scale positive electrode real microstructure geometry as the positive electrode calculation domain. The positive electrode calculation domain and the negative electrode calculation domain with a size of 33 microns × 33 microns × 33 microns are imported into the software, and are combined into a complete battery unit in the order of positive electrode current collector, positive electrode, separator, negative electrode, and negative electrode current collector. The grids of each battery unit are divided based on the bitmap data, such as Figure 4 The figure shows a complete battery cell grid diagram of an embodiment of the present invention, with a total of 631W regular tetrahedral grids.

[0085] E. Obtain the electrochemical parameters of the positive and negative electrode current collectors, positive and negative electrode active particles, and electrolyte; obtain the positive and negative electrode reaction kinetic parameters.

[0086] The electrochemical parameters of the positive and negative electrode collectors include the positive electrode collector conductivity and the negative electrode collector conductivity; the electrochemical parameters of the positive and negative electrode active particles include the positive and negative electrode solid phase diffusion coefficients, the positive and negative electrode solid phase initial lithium ion concentrations, the positive and negative electrode solid phase maximum lithium insertion concentrations, the positive and negative electrode solid phase conductivity and the positive and negative electrode equilibrium potentials; the electrochemical parameters of the electrolyte include the liquid phase diffusion coefficient, the liquid phase initial lithium ion concentration, the liquid phase conductivity, the transfer number and activity correlation; the positive and negative electrode reaction kinetic parameters include the positive and negative electrode reaction rate constants.

[0087] The positive and negative electrode solid phase diffusion coefficients, the positive and negative electrode equilibrium potentials, and the positive and negative electrode reaction rate constants are obtained based on button half-cell testing. In this embodiment, the positive and negative electrode solid phase diffusion coefficients are obtained based on the constant current intermittent titration technique (GITT), the positive and negative electrode equilibrium potentials are obtained by discharging the button half-cell at a 0.05C rate, and the positive and negative electrode reaction rate constants are obtained based on linear sweep voltammetry (LSV). The positive and negative electrode solid phase diffusion coefficients and the positive and negative electrode reaction rate constants are related to the battery state of charge (SOC). In this embodiment, GITT and LSV tests are performed every 5% SOC to obtain the functional relationship between the electrochemical parameters and SOC.

[0088] The remaining electrochemical parameters, namely, positive electrode current collector conductivity, negative electrode current collector conductivity, positive and negative electrode solid phase initial lithium ion concentration, positive and negative electrode solid phase maximum lithium insertion concentration, positive and negative electrode solid phase conductivity, liquid phase diffusion coefficient, liquid phase initial lithium ion concentration, liquid phase conductivity, transfer number and activity correlation adopt reference values ​​in the literature. Specifically, the parameters used in this embodiment are derived from the literature (CAI J, WEI X, WANG X, et al. Revealing effects of pouch Li-ion battery structure on fast charging ability through numerical simulation [J]. Applied Energy, 2025, 377:)

[0089] F. Define the solid-phase charge transfer conservation equation for the positive and negative electrode current collectors and active particles, define the solid-phase mass transfer conservation equation for the positive and negative electrode active particles, define the liquid-phase charge transfer conservation equation and liquid-phase mass transfer conservation equation for the positive and negative electrode pores and diaphragm pores, and define the Butler-Volmer reaction kinetics equation for the positive and negative electrode solid / liquid interface; assign the electrochemical parameters to the equation variables.

[0090] In COMSOL, a set of partial differential equations is defined for each computational domain. The specific equations are as follows:

[0091] In this embodiment, unless otherwise specified, the parameter subscript s represents a solid-phase related parameter, and the subscript l represents a liquid-phase related parameter.

[0092] Solid phase charge transfer conservation equation:

[0093]

[0094] Where, σ s is the electronic conductivity of the solid phase material, φ s is the solid phase potential, Q s is the solid phase charge source term.

[0095] According to the solid charge conservation equation, the battery terminal voltage (V) is defined as the difference between the positive electrode solid phase potential and the negative electrode solid phase potential.

[0096] Solid phase mass transfer conservation equation:

[0097]

[0098] Where D s is the solid phase diffusion coefficient, c s is the solid phase lithium concentration, and t is the time.

[0099] Liquid phase charge transfer conservation equation:

[0100]

[0101] Where, σ l is the liquid phase electronic conductivity, φ l is the liquid phase potential, R is the ideal gas constant, T is the temperature, F is the Faraday constant, f is the activity correlation, c l is the liquid phase lithium ion concentration, t + is the liquid phase ion transfer number, Q l is the liquid phase charge source term.

[0102] Liquid phase mass transfer conservation equation:

[0103]

[0104] Where D l is the liquid phase diffusion coefficient, c l is the liquid phase lithium ion concentration, i l is the local current density in the liquid phase, t + is the liquid phase ion transfer number, F is the Faraday constant, and t is the time.

[0105] Butler-Volmer reaction kinetic equation:

[0106]

[0107] η=φ s -φ l -E eq

[0108] Where i loc is the local current density, i0 is the exchange current density, α is the charge transfer coefficient, η is the electrode overpotential, F is the Faraday constant, R is the ideal gas constant, T is the temperature, k is the reaction rate constant, c s,max is the maximum lithium insertion concentration in the solid phase, c s,surf is the lithium ion concentration on the ion surface, c l is the liquid phase lithium ion concentration, c l,ref =1000mol / L is the initial lithium ion concentration in the liquid phase, φ s is the solid phase potential, φ l is the liquid phase potential, E eq is the electrode equilibrium potential.

[0109] The electrochemical parameters obtained in step E are assigned to the variables of the above partial differential equation.

[0110] G. Conduct discharge and charge tests on the positive and negative electrode samples and the preliminary lithium-ion battery mesoscopic electrochemical model respectively. Verify the accuracy of the preliminary lithium-ion battery mesoscopic electrochemical model based on the obtained experimental terminal voltage data. The verified preliminary lithium-ion battery mesoscopic electrochemical model is used as the final lithium-ion battery mesoscopic electrochemical model based on the real electrode microstructure.

[0111] In this embodiment, the battery samples and models were subjected to discharge tests at 0.2C, 2C and 4C rates and charge tests at 0.2C, 1C and 2C rates, respectively. The model accuracy was verified based on the experimental terminal voltage data to obtain a mesoscopic electrochemical model of lithium-ion batteries based on the real microstructure of the electrode.

[0112] like Figure 5 The green lines in the ac are the terminal voltage curves of the model in this embodiment at 0.2C, 2C and 4C discharge rates, respectively. Figure 5 The green lines in df are the terminal voltage curves of the model of this embodiment at 0.2C, 1C and 2C discharge rates. In order to verify the accuracy of the model, the terminal voltage curves of the battery sample at the above charge and discharge rates were obtained through experimental testing, as shown in Figure 2. Figure 5 The results show that the mesoscopic electrochemical model of this embodiment has high accuracy regardless of discharge or charge conditions.

[0113] The following comparative examples are compared with the above-mentioned embodiment scheme, as follows:

[0114] Compared with the embodiment, the comparative example adopts the basic P2D electrochemical model for modeling, and regards the positive and negative electrodes as homogenized porous media, and its electrochemical parameters remain the same as those of the embodiment.

[0115] Similarly, the comparative model is simulated at 0.2C, 2C, and 4C discharge rates and 0.2C, 1C, and 2C charge rates, and the terminal voltage curves are as follows: Figure 5 Shown by the blue line.

[0116] It can be seen that the comparative model is consistent with the experimental results at low rates (0.2C discharge and 0.2C charge). However, at high rates, the homogenized electrode assumption underestimates the battery liquid phase polarization, so the simulation results are very different from the experimental results and the model is inaccurate.

[0117] like Figure 6 , which is a graph showing changes in electrolyte salt concentration and active particle lithium concentration over time under 2C discharge in the model according to an embodiment of the present invention. Figure 6a in the figure is the distribution of electrolyte salt concentration in the positive electrode in the initial state. All parts remain uniform and are 1000 mol / L. As the discharge process proceeds, the lithium ions in the electrolyte are consumed in the positive electrode, so the lithium ion concentration distribution from the diaphragm to the current collector (from bottom to top) gradually decreases, as shown in the figure. Figure 6 As shown in b in Figure 6 In the c, when discharging for 300s, since lithium is first embedded in the surface of the positive electrode active particles, a large concentration gradient will appear on the surface and inside of the particles; Figure 6 In figure d, after 900 seconds of discharge, lithium ions gradually diffuse from the surface into the particle interior, and the concentration gradient continues to decrease. These results demonstrate that the model of this embodiment can analyze the heterogeneity of physical and chemical processes within the battery at the scale of real active particles and pores. However, the P2D model based on porous electrode theory lacks this expressive power and cannot optimize the electrode microstructure to improve battery performance.

[0118] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A mesoscopic electrochemical model structure of a lithium-ion battery based on a real microstructure, characterized in that: It includes a geometric model part, an electrochemical parameter part, and a partial differential equation part of a lithium-ion battery. The geometric model part includes electrode geometry, diaphragm geometry, and current collector geometry. The electrode geometry is a three-dimensional real microstructure image of the lithium-ion battery electrode, the diaphragm geometry is a homogenized porous medium, and the current collector geometry is a three-dimensional entity of the current collector. The various components of the geometric model part are combined to form a complete full battery unit. The partial differential equation group is used to define the conservation equation of the battery cell; The electrochemical parameter part is used to provide input parameters for variables in conservation equations.

2. The lithium-ion battery mesoscopic electrochemical model structure based on a real microstructure according to claim 1, characterized in that: The electrode geometry is obtained by imaging instruments and image post-processing technology, including the three-dimensional real microstructure of the positive electrode and the three-dimensional real microstructure of the negative electrode; The positive electrode three-dimensional real microstructure includes a positive electrode active particle phase and a positive electrode pore phase; The negative electrode three-dimensional real microstructure includes a negative electrode active particle phase and a negative electrode pore phase; The current collector geometry includes the positive electrode current collector geometry and the negative electrode current collector geometry.

3. The lithium-ion battery mesoscopic electrochemical model structure based on a real microstructure according to claim 1, characterized in that: The electrochemical parameters include current collector parameters, active particle parameters, electrolyte parameters and reaction kinetic parameters; The current collector parameters include the conductivity of the positive electrode current collector and the conductivity of the negative electrode current collector; The active particle parameters include the positive and negative electrode solid phase diffusion coefficients, the positive and negative electrode solid phase initial lithium ion concentrations, the positive and negative electrode solid phase maximum lithium insertion concentrations, the positive and negative electrode solid phase conductivity and the positive and negative electrode equilibrium potentials; The electrolyte parameters include liquid phase diffusion coefficient, liquid phase initial lithium ion concentration, liquid phase conductivity, transfer number and activity correlation; The reaction kinetic parameters include positive and negative electrode reaction rate constants.

4. The lithium-ion battery mesoscopic electrochemical model structure based on a real microstructure according to claim 1, characterized in that: The partial differential equation group includes a solid-phase mass transfer conservation equation, a solid-phase charge transfer conservation equation, a liquid-phase mass transfer conservation equation, a liquid-phase charge transfer conservation equation and a Butler-Volmer reaction kinetics equation.

5. A modeling method for a lithium-ion battery mesoscopic electrochemical model structure based on a real microstructure according to any one of claims 1 to 4, characterized in that: The following steps are involved: Acquire and perform three-dimensional imaging of positive and negative electrode samples to obtain three-dimensional real microstructure images of the positive and negative electrodes; Based on the three-dimensional real microstructure images of the positive and negative electrodes, an image processing method is used to segment the positive and negative electrode active particle phases and the pore phase, and a first positive and negative electrode porosity is calculated; experiments are conducted on the positive and negative electrode samples to obtain a second positive and negative electrode porosity; the difference between the first positive and negative electrode porosity and the second positive and negative electrode porosity is compared to verify the accuracy of the three-dimensional imaging result, and the three-dimensional imaging result that passes the verification is selected; Based on the three-dimensional real microstructure images of the positive and negative electrodes, key geometric features are determined as evaluation indicators, and a representative volume unit is selected, wherein the key geometric features of the volume unit have the same statistical characteristics as those of the complete electrode; Based on the representative volume unit, establish the positive electrode microstructure geometry, the negative electrode microstructure geometry, the separator, the positive electrode current collector and the negative electrode current collector, and combine them to obtain a complete full battery unit and mesh each part of the battery unit based on the bitmap data; Obtaining electrochemical parameters required for the battery cell, including current collector parameters, active particle parameters, electrolyte parameters, and reaction kinetic parameters; Define solid-phase charge transfer conservation equations for the positive and negative current collectors and active particles in the battery cell, define solid-phase mass transfer conservation equations for the positive and negative active particles, define liquid-phase charge transfer conservation equations and liquid-phase mass transfer conservation equations for the positive and negative electrode pores and separator pores, and define a Butler-Volmer reaction kinetic equation for the positive and negative electrode solid / liquid interfaces; assign the electrochemical parameters to the variables of each equation to obtain a preliminary mesoscopic electrochemical model of a lithium-ion battery; Discharge tests and charge tests were carried out on the positive and negative electrode samples and the preliminary lithium-ion battery mesoscopic electrochemical model respectively. The accuracy of the preliminary lithium-ion battery mesoscopic electrochemical model was verified based on the experimental terminal voltage data obtained. The verified preliminary lithium-ion battery mesoscopic electrochemical model was used as the final lithium-ion battery mesoscopic electrochemical model based on the real microstructure of the electrode.

6. The method according to claim 5, characterized in that The key geometric characteristics include the active particle D50 size, porosity and McMullin number in the thickness direction; The McMullin number is the ratio of the intrinsic liquid phase conductivity of the electrolyte to the effective liquid phase conductivity of the electrode or the ratio of the intrinsic liquid phase diffusion coefficient of the electrolyte to the effective liquid phase diffusion coefficient of the electrode; The representative volume unit selected has the characteristic that when the size continues to increase, the key geometric features of the electrode do not change significantly.

7. The method according to claim 5, characterized in that The current collector parameters include the conductivity of the positive electrode current collector and the conductivity of the negative electrode current collector; The active particle parameters include the positive and negative electrode solid phase diffusion coefficients, the positive and negative electrode solid phase initial lithium ion concentrations, the positive and negative electrode solid phase maximum lithium insertion concentrations, the positive and negative electrode solid phase conductivity and the positive and negative electrode equilibrium potentials; The electrolyte parameters include liquid phase diffusion coefficient, liquid phase initial lithium ion concentration, liquid phase conductivity, transfer number and activity correlation; The reaction kinetic parameters include positive and negative electrode reaction rate constants.

8. The method according to claim 7, characterized in that The positive and negative electrode solid phase diffusion coefficients, positive and negative electrode equilibrium potentials and positive and negative electrode reaction rate constants are obtained based on button half-cell testing; The positive electrode collector conductivity, negative electrode collector conductivity, positive and negative electrode solid phase initial lithium ion concentration, positive and negative electrode solid phase maximum lithium insertion concentration, positive and negative electrode solid phase conductivity, liquid phase diffusion coefficient, liquid phase initial lithium ion concentration, liquid phase conductivity, transfer number and activity correlation adopt literature reference values.

9. The method according to claim 5, characterized in that The diaphragm pores are defined by a partial differential equation in a volume-averaged manner; The positive and negative electrode current collectors, the positive and negative electrode active particle phases and the positive and negative electrode pore phases define partial differential equations on the corresponding real structures.

10. The method according to claim 5, characterized in that The expression of the solid phase charge transfer conservation equation is: Where σ s is the electronic conductivity of the solid phase material, φ s is the solid phase potential, Q s is the solid phase charge source term; The expression of the solid phase mass transfer conservation equation is: Where D s is the solid phase diffusion coefficient, c s is the solid phase lithium concentration, t is the time; The expression of the liquid phase charge transfer conservation equation is: Where σ l is the liquid phase electronic conductivity, φ l is the liquid phase potential, R is the ideal gas constant, T is the temperature, F is the Faraday constant, f is the activity correlation, c l is the liquid phase lithium ion concentration, t + is the liquid phase ion transfer number, Q l is the liquid phase charge source term; The expression of the liquid phase mass transfer conservation equation is: Where D l is the liquid phase diffusion coefficient, i l is the local current density in the liquid phase; The expression of the Butler-Volmer reaction kinetic equation is: h=φ s -f l -E eq Where i loc is the local current density, i0 is the exchange current density, α is the charge transfer coefficient, η is the electrode overpotential, k is the reaction rate constant, c s,max is the maximum lithium insertion concentration in the solid phase, c s,surf is the lithium ion concentration on the ion surface, c l,ref =1000mol / L is the initial lithium ion concentration in the liquid phase, φ s is the solid phase potential, φ l is the liquid phase potential, E eq is the electrode equilibrium potential.

Images