Simulation modeling method and system for electrothermal coupling of high-specific-energy lithium battery with silicon-carbon negative electrode

Abstract

The invention provides an electrothermal coupling simulation modeling method and system for a high-specific-energy lithium battery with a silicon-carbon negative electrode. The method comprises the following steps: constructing a geometric model of a battery to be simulated; establishing an electrochemical control equation set based on a porous electrode theory and a pseudo three-dimensional model and a thermal model control equation based on an energy conservation principle; materials are arranged for all the areas; setting adjustable input parameters required by the model; performing bidirectional coupling on the electrochemical control equation set and the thermal model control equation through an Arrhenius equation; after mesh generation, a transient solver is adopted for solving, iterative calculation is carried out by judging convergence, and finally simulation results of a temperature field, potential distribution and lithium ion concentration distribution are output. A high-precision virtual analysis tool is provided, the bidirectional coupling process of electrochemical and thermal behaviors in the battery can be finely simulated, and theoretical support is provided for structural design and safety evaluation of the high-specific-energy battery.

Description

Technical Field

[0001] This invention relates to the field of lithium-ion battery simulation technology, specifically to a method and system for electrothermal coupling simulation modeling of high-energy-density lithium batteries with silicon-carbon anodes. Background Technology

[0002] With the rapid development of electric vehicles and large-scale energy storage industries, the market has an urgent need for continuously increasing energy density in lithium-ion batteries. High-energy-density lithium batteries using high-capacity active materials such as high-nickel layered oxide cathodes and silicon-based anodes have become a current focus of research and industrialization. However, increasing energy density is often accompanied by more complex internal physicochemical processes and exacerbated thermal safety issues. For example, the huge volume expansion of silicon anodes during cycling, the structural instability of high-nickel cathodes at high temperatures, and the significant electrochemical polarization and uneven heat generation during high-rate charge and discharge all pose serious challenges to battery design and safety.

[0003] Computer simulation technology is widely used as an important auxiliary tool in the research and design of batteries. Many existing battery models, especially those used for state estimation in battery management systems, primarily focus on the macroscopic electrical behavior of the battery's exterior. Their model parameters are typically obtained through data fitting and do not delve into the internal electrochemical and thermal physical mechanisms of the battery. While these models are computationally simple, they cannot describe the internal processes determined by the electrode microstructure, nor can they accurately quantify the heat generation and spatial distribution from different sources such as reaction heat, polarization heat, and ohmic heat. Therefore, they cannot be used to guide the refined design of the battery's internal structure, nor can they accurately predict localized overheating or performance degradation caused by electrothermal coupling effects under high-stress conditions.

[0004] A search of patent literature revealed an invention patent with publication number CN116680938A, which discloses a modeling method and system for a lithium battery electrothermal coupling model. The method includes: constructing a dynamic model of the open-circuit voltage of a lithium battery based on measured open-circuit voltage data, using the current stored capacity of the lithium battery as the independent variable and the open-circuit voltage as the dependent variable; constructing a dynamic temperature rise model of a lithium battery using the Foster equivalent temperature rise model based on the internal resistance loss power, thermal resistance, and thermal melting of the lithium battery; constructing a lithium battery discharge internal resistance electrothermal coupling model based on the measured internal resistance value of the lithium battery under preset operating conditions, using the lithium battery temperature, charge load, and discharge rate as independent variables and the discharge internal resistance value as the dependent variable; and establishing a lithium battery electrothermal coupling model based on the lithium battery open-circuit voltage dynamic model, the lithium battery dynamic temperature rise model, and the lithium battery discharge internal resistance electrothermal coupling model. This patent does not delve into the internal electrochemical mechanism of the battery, making the modeling accuracy susceptible to problems. It lacks fine processing such as geometric modeling and mesh generation, resulting in poor simulation adaptability for special batteries such as high-energy-density batteries. Furthermore, it suffers from insufficient coupling depth and model versatility.

[0005] In summary, given the problems of the existing technologies, researching a simulation modeling method and system for electrothermal coupling of silicon-carbon anode high-energy-density lithium batteries has become a critical task that urgently needs to be addressed. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for electrothermal coupling simulation modeling of high-energy-density lithium batteries with silicon-carbon anodes.

[0007] The present invention provides a simulation modeling method for electrothermal coupling of silicon-carbon anode high-energy-density lithium batteries, comprising the following steps:

[0008] Step S1: Based on the battery parameters, construct the geometric model of the high-energy-density lithium battery to be simulated; Step S2: Add the physical field of lithium-ion battery to the geometric model to establish a set of electrochemical control equations based on porous electrode theory and pseudo-three-dimensional model. Step S3: Add a solid heat transfer physical field to the geometric model to establish the governing equations of the thermal model based on the principle of energy conservation. Step S4: Set the corresponding materials for the positive electrode region, the separator region, and the negative electrode region in the geometric model; Step S5: Set the adjustable input parameters required for the electrochemical control equation set and the thermal model control equation; Step S6: Based on the values ​​of the adjustable input parameters, the electrochemical control equation set and the thermal model control equation set are bidirectionally coupled. The coupling method is as follows: the reaction heat, polarization heat and ohmic heat calculated by the electrochemical control equation set are used as source terms to input the thermal model control equation set; the temperature field results calculated by the thermal model control equation set are used to update the parameters in the electrochemical control equation set through the Arrhenius equation. Step S7: Mesh the geometric model; Step S8: Use a transient solver to perform the calculation and determine whether the calculation result meets the preset convergence criterion. If the result does not meet the convergence criterion, generate a new set of values ​​for the adjustable input parameters and return to step S6. If the result meets the convergence criterion, output the simulation results including temperature field, potential distribution and lithium ion concentration distribution.

[0009] Preferably, in step S1, the geometric model is a two-dimensional geometric model stacked one-dimensionally in the thickness direction of the battery; the battery parameters on which the geometric model is based include: positive electrode thickness, negative electrode thickness, separator thickness, particle radius of positive and negative electrode active materials, porosity of positive electrode region, separator region and negative electrode region, maximum lithium intercalation concentration and initial lithium intercalation concentration of positive and negative electrode active materials, Arrhenius equation parameters relating the reaction rate constant of each electrode to temperature, and convective heat transfer coefficient of battery surface.

[0010] Preferably, the set of electrochemical governing equations established in step S2 includes: Solid-state mass transfer equations are used to describe the diffusion of lithium ions within active material particles:

[0011] in, They represent the negative and positive electrodes, respectively. Represents solids. This refers to the lithium concentration in the positive or negative electrode active material. The radius of the positive or negative electrode active material. It represents the diffusion coefficient of lithium ions in the active material of the positive or negative electrode. Indicates time; Transport equations in electrolytes, used to describe the migration and diffusion of lithium ions in electrolytes:

[0012] in, These represent the negative electrode, the separator, and the positive electrode, respectively. This represents the electrolyte volume fraction. The lithium-ion liquid phase diffusion coefficient; This represents the effective diffusion coefficient of liquid lithium ions in the negative electrode, separator, and positive electrode. Indicates a valid value; Indicates the lithium ion concentration in the electrolyte; This indicates the distance from the leftmost negative terminal; Indicates the specific surface area of ​​the active material; Represents the lithium-ion transference number; Indicates current density; The solid-state charge conservation equation is used to calculate the solid-state potential:

[0013] in, , representing the negative and positive electrodes respectively; Solid-state conductivity; Indicates the effective conductivity of the positive or negative electrode; This indicates the solid-phase current density at the positive or negative electrode. It is the solid-state potential; The liquid phase charge conservation equation is used to calculate the liquid phase potential:

[0014] in, The conductivity of the electrolyte. It is the correlation coefficient of electrolyte activity; These represent the negative electrode, the separator, and the positive electrode, respectively. This represents the liquid current density at the negative electrode, the diaphragm, and the positive electrode. Indicates the liquid phase; Indicates the effective conductivity of the electrolyte; Represents the ideal gas constant; Indicates temperature; Denotes Faraday's constant; Indicates liquid phase potential; Electrochemical reaction kinetic equations, based on the Butler-Volmer equations, describe the reaction rates at the electrode / electrolyte interface:

[0015]

[0016] in, The reaction rate constants are the positive and negative electrodes. The transfer coefficients for the positive and negative poles are denoted as . This is an overpotential; , representing the negative and positive electrodes respectively; Indicates the equilibrium potential; Indicates current density; This indicates the maximum lithium intercalation concentration of the active material in the positive or negative electrode. This indicates the surface lithium intercalation concentration of the positive or negative electrode active material; Indicates the negative electrode transfer coefficient; Indicates the positive electrode transfer coefficient; This indicates an overpotential at the positive or negative terminal. Preferably, the governing equations of the thermal model established in step S3 are heat conduction equations based on energy conservation:

[0017]

[0018] Total heat generation rate of battery =heat of reaction +Polarization heat +Ohm heat , Heat of reaction ; Polarization heat

[0019] Ohm's heat

[0020] in, This indicates the constant-pressure specific heat capacity of the material; Indicates the density of the material; Indicates the convective heat transfer coefficient; Indicates ambient temperature; Indicates the thermal conductivity coefficient; Indicates battery temperature; It is the local current density; It is solid-state potential. It is the liquid phase potential. It is the equilibrium potential; Indicates open-circuit voltage; Preferably, the negative electrode active component of the material set for the negative electrode region in step S4 is a silicon-carbon composite material, which contains silicon and graphite.

[0021] Preferably, the adjustable input parameters set in step S5 include material physicochemical parameters, electrical boundary conditions, thermal boundary conditions, initial temperature, initial state of charge, and the calculation time step of the transient solver.

[0022] Preferably, in step S6, the parameters in the electrochemical governing equations are updated using the Arrhenius equation, based on the following mathematical relationship:

[0023] in, Indicates the current temperature The reaction rate constant at the given time; Indicates at reference temperature The known baseline reaction rate constant of the material itself; Indicates activation energy; Preferably, in step S7, when meshing the geometric model, the mesh is refined in the electrode-diaphragm interface region and the particle surface region.

[0024] Preferably, in step S8, a new set of values ​​is generated for the adjustable input parameters, including modifying at least one of the material physicochemical parameters, electrical boundary conditions, thermal boundary conditions, initial temperature and initial state of charge, and the calculation time step of the transient solver set in step S5.

[0025] This invention also provides a simulation modeling system for electrothermal coupling of silicon-carbon anode high-energy-density lithium batteries, comprising: Module M1 constructs a geometric model of the high-energy-density lithium battery to be simulated based on battery parameters; Module M2 adds lithium-ion battery physical fields to the geometric model to establish a set of electrochemical control equations based on porous electrode theory and pseudo-three-dimensional model; Module M3 adds a solid heat transfer physical field to the geometric model to establish the governing equations of the thermal model based on the principle of energy conservation. Module M4 sets the corresponding materials for the positive electrode region, separator region, and negative electrode region in the geometric model; Module M5 allows you to set the adjustable input parameters required for the electrochemical control equation set and the thermal model control equation. Module M6, based on the adjustable input parameter values, bidirectionally couples the electrochemical control equation set with the thermal model control equation set. The coupling method is as follows: the reaction heat, polarization heat, and ohmic heat calculated by the electrochemical control equation set are used as source terms to input the thermal model control equation set; the temperature field results calculated by the thermal model control equation set are used to update the parameters in the electrochemical control equation set through the Arrhenius equation. Module M7 performs mesh generation on the geometric model; Module M8 uses a transient solver to perform the calculation and determines whether the calculation result meets the preset convergence criterion. If the result does not meet the convergence criterion, it generates a new set of values ​​for the adjustable input parameters and returns to module M6. If the result meets the convergence criterion, it outputs simulation results including temperature field, potential distribution and lithium ion concentration distribution.

[0026] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention constructs an electrochemical control equation set using a pseudo-three-dimensional model based on porous electrode theory, and combines it with a thermal model that is finely decomposed into three major sources: reaction heat, polarization heat, and ohmic heat. This enables a more realistic simulation of the complex processes such as lithium-ion diffusion, charge transfer, mass migration, and energy conversion inside high-energy-density lithium batteries from a physical mechanism perspective. It avoids treating the battery as a macroscopic empirical model that treats it as a black box. It can output microscopic physical field information such as lithium concentration on the surface of electrode active particles, local salt concentration in the electrolyte, and solid / liquid phase potential distribution. The simulation results have high fidelity and provide a powerful tool for a deeper understanding of the internal state of the battery.

[0027] 2. This invention bidirectionally couples the electrochemical governing equations with the thermal model governing equations using the Arrhenius equation. This method can dynamically capture and quantify the impact of temperature changes on electrochemical reaction kinetic parameters (such as reaction rate constant and diffusion coefficient), while simultaneously feeding back the heat generated by the electrochemical process into the thermal field calculation in real time. This tight coupling enables the model to accurately predict the temperature evolution of the battery under different operating conditions, revealing the formation mechanism of internal hotspots caused by factors such as local current density non-uniformity and ion concentration polarization, as well as the impact of temperature gradients on the spatial non-uniformity of battery performance.

[0028] 3. This invention enables rapid virtual simulation testing of different battery design schemes by adjusting adjustable input parameters. The model can quantitatively evaluate the impact of the aforementioned structural parameters on the macroscopic performance, internal state, and thermal behavior of the battery, thereby providing direct numerical basis for electrode material selection, electrode structure design and optimization, effectively reducing the number of experimental trials and shortening the R&D cycle. Attached Figure Description

[0029] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart of a simulation modeling method for electrothermal coupling of silicon-carbon anode high-energy-density lithium battery according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the meshing of the two-dimensional geometric model in an embodiment of the present invention; Figure 3 This is a simulation result diagram of the 1C rate discharge curve in an embodiment of the present invention; Figure 4 The figure shows the simulation results of the SOC change of each electrode during 1C rate discharge in the embodiment of the present invention. Figure 5 This is a simulation result diagram of the electrolyte salt concentration distribution at the end of discharge in an embodiment of the present invention; Figure 6 This is a simulation result diagram of the battery temperature distribution at the end of discharge in an embodiment of the present invention. Detailed Implementation

[0030] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0031] This application provides a method and system for electrothermal coupling simulation modeling of high-energy-density lithium batteries with silicon-carbon anodes. The method includes: constructing a geometric model of the battery to be simulated; adding lithium-ion battery physical fields and solid heat transfer physical fields to the geometric model to establish an electrochemical control equation set based on porous electrode theory and a pseudo-three-dimensional model, as well as a thermal model control equation based on the principle of energy conservation; setting materials for each region; setting adjustable input parameters required by the model; based on the adjustable input parameters, bidirectionally coupling the electrochemical control equation set and the thermal model control equation through the Arrhenius equation. The coupling method includes using the reaction heat, polarization heat, and ohmic heat calculated by the electrochemical model as heat sources input to the thermal model, and using the temperature field calculated by the thermal model to update the reaction rate constant and diffusion coefficient in the electrochemical model; after meshing, using a transient solver for solving, and performing iterative calculations by judging convergence, finally outputting the simulation results of temperature field, potential distribution, and lithium-ion concentration distribution. This application provides a high-precision virtual analysis tool that can precisely simulate the bidirectional coupling process of electrochemical and thermal behavior inside the battery, providing theoretical support for the structural design and safety assessment of high-energy-density batteries.

[0032] Example 1: Figure 1 This is a flowchart of a simulation modeling method for electrothermal coupling of a silicon-carbon anode high-energy-density lithium battery according to an embodiment of the present invention.

[0033] like Figure 1 As shown, this embodiment provides a simulation modeling method for electrothermal coupling of high-energy-density lithium batteries with silicon-carbon anodes. It is implemented using the multiphysics simulation software COMSOL Multiphysics, taking a 5.5Ah high-energy-density lithium battery (energy density 500Wh / kg) with a silicon-carbon composite anode as the simulation object. The specific steps include: Step S1: Based on the battery parameters, construct the geometric model of the high-energy-density lithium battery to be simulated.

[0034] Specifically, in step S1, the geometric model is a two-dimensional geometric model stacked one-dimensionally in the thickness direction of the battery. The battery parameters on which the geometric model is based include: positive electrode thickness, negative electrode thickness, separator thickness, particle radius of positive and negative electrode active materials, porosity of positive electrode region, separator region and negative electrode region, maximum lithium intercalation concentration and initial lithium intercalation concentration of positive and negative electrode active materials, Arrhenius equation parameters relating the reaction rate constant of each electrode to temperature, and convective heat transfer coefficient of battery surface.

[0035] Furthermore, a new two-dimensional transient study was created in COMSOL Mutiphysics software. Subsequently, the geometric model of the battery to be simulated was constructed. Specifically, based on the actual battery structure, a rectangle was drawn in the software, and the rectangle was divided along the thickness direction into the positive electrode region, the separator region, and the negative electrode region to simulate a battery cell.

[0036] In this embodiment, the specific battery parameters used are shown in Table 1: Table 1

[0037] Step S2: Add the physical field of the lithium-ion battery to the geometric model to establish a set of electrochemical control equations based on porous electrode theory and pseudo-three-dimensional model.

[0038] Specifically, the set of electrochemical governing equations established in step S2 includes: Solid-state mass transfer equations are used to describe the diffusion of lithium ions within active material particles:

[0039] in, They represent the negative and positive electrodes, respectively. Represents solids. This refers to the lithium concentration in the positive or negative electrode active material. The radius of the positive or negative electrode active material. It represents the diffusion coefficient of lithium ions in the active material of the positive or negative electrode. Indicates time; Transport equations in electrolytes, used to describe the migration and diffusion of lithium ions in electrolytes:

[0040] in, These represent the negative electrode, the separator, and the positive electrode, respectively. This represents the electrolyte volume fraction. The lithium-ion liquid phase diffusion coefficient; This represents the effective diffusion coefficient of liquid lithium ions in the negative electrode, separator, and positive electrode. Indicates a valid value; Indicates the lithium ion concentration in the electrolyte; This indicates the distance from the leftmost negative terminal; Indicates the specific surface area of ​​the active material; Represents the lithium-ion transference number; Indicates current density; The solid-state charge conservation equation is used to calculate the solid-state potential:

[0041] in, , representing the negative and positive electrodes respectively; Solid-state conductivity; Indicates the effective conductivity of the positive or negative electrode; This indicates the solid-phase current density at the positive or negative electrode. It is the solid-state potential; The liquid phase charge conservation equation is used to calculate the liquid phase potential:

[0042] in, The conductivity of the electrolyte. It is the correlation coefficient of electrolyte activity; These represent the negative electrode, the separator, and the positive electrode, respectively. This represents the liquid current density at the negative electrode, the diaphragm, and the positive electrode. Indicates the liquid phase; Indicates the effective conductivity of the electrolyte; Represents the ideal gas constant; Indicates temperature; Denotes Faraday's constant; Indicates liquid phase potential; Electrochemical reaction kinetic equations, based on the Butler-Volmer equations, describe the reaction rates at the electrode / electrolyte interface:

[0043]

[0044] in, The reaction rate constants are the positive and negative electrodes. The transfer coefficients for the positive and negative poles are denoted as . This is an overpotential; , representing the negative and positive electrodes respectively; Indicates the equilibrium potential; Indicates current density; This indicates the maximum lithium intercalation concentration of the active material in the positive or negative electrode. This indicates the surface lithium intercalation concentration of the positive or negative electrode active material; Indicates the negative electrode transfer coefficient; Indicates the positive electrode transfer coefficient; This indicates an overpotential at the positive or negative electrode.

[0045] Step S3: Add a solid heat transfer physical field to the geometric model to establish the governing equations of the thermal model based on the principle of energy conservation.

[0046] Specifically, the governing equations of the thermal model established in step S3 are heat conduction equations based on energy conservation:

[0047]

[0048] Total heat generation rate of battery =heat of reaction +Polarization heat +Ohm heat

[0049] The heat of reaction, also known as the heat of entropy change, is the heat generated by the entropy change of the electrode material; the heat of polarization is the heat generated by polarization caused by overpotential; and the heat of ohms is caused by the ohmic internal resistance. For heat dissipation, only convective heat transfer is considered.

[0050] Heat of reaction ; Polarization heat

[0051] Ohm's heat

[0052] in, This indicates the constant-pressure specific heat capacity of the material; Indicates the density of the material; Indicates the convective heat transfer coefficient; Indicates ambient temperature; Indicates the thermal conductivity coefficient; Indicates battery temperature; It is the local current density; It is solid-state potential. It is the liquid phase potential. It is the equilibrium potential; This indicates the open-circuit voltage.

[0053] Step S4: Set the corresponding materials for the positive electrode region, the separator region, and the negative electrode region in the geometric model.

[0054] Specifically, in step S4, the negative electrode active component of the material set for the negative electrode region is a silicon-carbon composite material, which contains silicon and graphite.

[0055] Step S5: Set the adjustable input parameters required for the electrochemical control equations and the thermal model control equations. These adjustable input parameters include: material physicochemical parameters; electrical boundary conditions for setting the negative electrode side boundary conditions of the geometric model to electrically ground and the positive electrode side boundary conditions to current density or voltage defined according to the charge / discharge protocol; thermal boundary conditions for applying convective heat transfer to the outer surface of the geometric model; initial temperature; initial state of charge; and the computation time step of the transient solver. The initial temperature can be set to 298.15 K, and the initial state of charge can be set to fully charged.

[0056] Step S6: Based on the values ​​of the adjustable input parameters, the electrochemical control equation set and the thermal model control equation set are bidirectionally coupled. The coupling method is as follows: the reaction heat, polarization heat and ohmic heat calculated by the electrochemical control equation set are used as source terms to input the thermal model control equation set; the temperature field results calculated by the thermal model control equation set are used to update the parameters in the electrochemical control equation set through the Arrhenius equation.

[0057] Specifically, in step S6, the parameters in the electrochemical governing equations are updated using the Arrhenius equation, based on the following mathematical relationship:

[0058] in, Indicates the current temperature The reaction rate constant at the given time; Indicates at reference temperature The known baseline reaction rate constant of the material itself; It represents the activation energy.

[0059] Step S7: Mesh the geometric model.

[0060] Figure 2 This is a schematic diagram of the meshing of the two-dimensional geometric model in an embodiment of the present invention.

[0061] like Figure 2 As shown, when meshing the geometric model, the mesh is refined in the electrode-diaphragm interface region and the particle surface region.

[0062] Step S8: Use a transient solver to perform the calculation and determine whether the calculation result meets the preset convergence criterion. If the result does not meet the convergence criterion, generate a new set of values ​​for the adjustable input parameters and return to step S6. If the result meets the convergence criterion, output the simulation results including temperature field, potential distribution and lithium ion concentration distribution.

[0063] Specifically, in step S8, a new set of values ​​is generated for the adjustable input parameters, including modifying at least one of the material physicochemical parameters, electrical boundary conditions, thermal boundary conditions, initial temperature and initial state of charge, and the calculation time step of the transient solver set in step S5.

[0064] Figure 3 This is a simulation result diagram of the 1C rate discharge curve in an embodiment of the present invention. Figure 4 This is a simulation result diagram of the SOC change of each electrode during 1C rate discharge in an embodiment of the present invention. Figure 5 This is a simulation result diagram of the electrolyte salt concentration distribution at the end of discharge in an embodiment of the present invention. Figure 6 This is a simulation result diagram of the battery temperature distribution at the end of discharge in an embodiment of the present invention.

[0065] Simulation results and analysis are as follows Figures 3 to 6 As shown, Figure 3 The simulation results show the variation curves of battery terminal voltage with depth of discharge at different discharge rates. The simulation results are in good agreement with the experimental data, verifying the accuracy of the simulation modeling method of this invention in predicting macroscopic electrical performance. Figure 4 The simulation results demonstrate the evolution of the charge state of the active materials in the negative electrode region (silicon and graphite) and the positive electrode region as the discharge process progresses. The simulation results reveal the difference in the reaction kinetics between the graphite and silicon phases in the silicon-carbon composite negative electrode material. Figure 5 and Figure 6 The key physical field distributions of the simulation results output by this invention are shown below: Figure 5The cloud map shows the concentration distribution of electrolyte salts at a certain moment, which intuitively presents the concentration polarization phenomenon caused by the limitation of ion migration and diffusion. Concentration polarization is a key factor that causes the increase of internal polarization and voltage drop in the battery. Figure 6 The cloud map of the internal temperature distribution of the battery at the corresponding moment clearly predicts the distribution of heat generation areas and potential hot spots during battery operation, providing a direct basis for the optimized design of the battery thermal management system.

[0066] Example 2: This embodiment is basically the same as the technical solution of Embodiment 1. The core modeling process, control equations and coupling solution logic are consistent. Only adaptive adjustments are made for lithium batteries with different chemical systems to verify the universality of the modeling framework of this invention.

[0067] The specific adjustments are as follows: In step S4, the positive electrode material is replaced with a high-nickel ternary material (such as NCM811), the negative electrode material is replaced with graphite, and the separator material is adapted to the system accordingly; In step S1, the geometric model size is adjusted accordingly based on the actual structure of the NCM811-graphite battery; In step S5, the physicochemical parameters of the negative and positive electrodes are replaced with the corresponding parameters of the NCM811 and graphite systems, including the equilibrium potential curve, reaction rate constant, diffusion coefficient, specific heat capacity, thermal conductivity, etc.

[0068] In this embodiment, the core process of steps S1 to S8 remains unchanged. The geometric model structure, electrochemical control equation set, thermal model control equation, bidirectional coupling method and solution criteria are all set according to Example 1. Only the above materials and parameters are adjusted to adapt to the new system, proving that the modeling method of the present invention has wide applicability.

[0069] Example 3: The present invention also provides a silicon-carbon anode high-energy-density lithium battery electrothermal coupling simulation modeling system. The silicon-carbon anode high-energy-density lithium battery electrothermal coupling simulation modeling system can be implemented by executing the process steps of the silicon-carbon anode high-energy-density lithium battery electrothermal coupling simulation modeling method. That is, those skilled in the art can understand the silicon-carbon anode high-energy-density lithium battery electrothermal coupling simulation modeling method as a preferred embodiment of the silicon-carbon anode high-energy-density lithium battery electrothermal coupling simulation modeling system.

[0070] Specifically, the electrothermal coupling simulation modeling system for high-energy-density lithium batteries with silicon-carbon anodes includes: Module M1 constructs a geometric model of the high-energy-density lithium battery to be simulated based on battery parameters; Module M2 adds lithium-ion battery physical fields to the geometric model to establish a set of electrochemical control equations based on porous electrode theory and pseudo-three-dimensional model; Module M3 adds a solid heat transfer physical field to the geometric model to establish the governing equations of the thermal model based on the principle of energy conservation. Module M4 sets the corresponding materials for the positive electrode region, separator region, and negative electrode region in the geometric model; Module M5 allows you to set the adjustable input parameters required for the electrochemical control equation set and the thermal model control equation. Module M6, based on the adjustable input parameter values, bidirectionally couples the electrochemical control equation set with the thermal model control equation set. The coupling method is as follows: the reaction heat, polarization heat, and ohmic heat calculated by the electrochemical control equation set are used as source terms to input the thermal model control equation set; the temperature field results calculated by the thermal model control equation set are used to update the parameters in the electrochemical control equation set through the Arrhenius equation. Module M7 performs mesh generation on the geometric model; Module M8 uses a transient solver to perform the calculation and determines whether the calculation result meets the preset convergence criterion. If the result does not meet the convergence criterion, it generates a new set of values ​​for the adjustable input parameters and returns to module M6. If the result meets the convergence criterion, it outputs simulation results including temperature field, potential distribution and lithium ion concentration distribution.

[0071] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0072] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A simulation modeling method for electrothermal coupling of silicon-carbon anode high-energy-density lithium batteries, characterized in that, Includes the following steps: Step S1: Based on the battery parameters, construct the geometric model of the high-energy-density lithium battery to be simulated; Step S2: Add the physical field of lithium-ion battery to the geometric model to establish a set of electrochemical control equations based on porous electrode theory and pseudo-three-dimensional model; Step S3: Add a solid heat transfer physical field to the geometric model to establish the governing equations of the thermal model based on the principle of energy conservation. Step S4: Set the corresponding materials for the positive electrode region, the separator region, and the negative electrode region in the geometric model respectively; Step S5: Set the adjustable input parameters required for the electrochemical control equation set and the thermal model control equation; Step S6: Based on the values ​​of the adjustable input parameters, the electrochemical control equation set and the thermal model control equation are bidirectionally coupled. The coupling method is as follows: the reaction heat, polarization heat, and ohmic heat calculated by the electrochemical control equation set are used as source terms to input the thermal model control equation; the temperature field results calculated by the thermal model control equation are used to update the parameters in the electrochemical control equation set through the Arrhenius equation. Step S7: Mesh the geometric model; Step S8: Use a transient solver to perform the calculation and determine whether the calculation result meets the preset convergence criterion; If the judgment result is that the convergence criterion is not met, a new set of values ​​is generated for the adjustable input parameters, and the process returns to step S6. If the judgment result is that the convergence criterion is met, the simulation results including temperature field, potential distribution and lithium ion concentration distribution are output.

2. The electrothermal coupling simulation modeling method for high-energy-density lithium batteries with silicon-carbon anodes according to claim 1, characterized in that, In step S1, the geometric model is a two-dimensional geometric model stacked one-dimensionally in the thickness direction of the battery. The battery parameters on which the geometric model is constructed include: positive electrode thickness, negative electrode thickness, separator thickness, particle radius of positive and negative electrode active materials, porosity of positive electrode region, separator region and negative electrode region, maximum lithium intercalation concentration and initial lithium intercalation concentration of positive and negative electrode active materials, Arrhenius equation parameters relating the reaction rate constant of each electrode to temperature, and convective heat transfer coefficient of battery surface.

3. The electrothermal coupling simulation modeling method for high-energy-density lithium batteries with silicon-carbon anodes according to claim 1, characterized in that, The set of electrochemical governing equations established in step S2 includes: Solid-state mass transfer equations are used to describe the diffusion of lithium ions within active material particles: in, They represent the negative and positive electrodes, respectively. Represents solids. This refers to the lithium concentration in the positive or negative electrode active material. The radius of the positive or negative electrode active material. It is the diffusion coefficient of lithium ions in the positive or negative electrode active material. Indicates time; Transport equations in electrolytes, used to describe the migration and diffusion of lithium ions in electrolytes: ； in, These represent the negative electrode, the separator, and the positive electrode, respectively. This represents the electrolyte volume fraction. The lithium-ion liquid phase diffusion coefficient; This represents the effective diffusion coefficient of liquid lithium ions in the negative electrode, separator, and positive electrode. Indicates a valid value; Indicates the lithium ion concentration in the electrolyte; Indicates the distance from the leftmost negative pole; Indicates the specific surface area of ​​the active material; Represents the lithium-ion transference number; Indicates current density; The solid-state charge conservation equation is used to calculate the solid-state potential: ； in, , representing the negative and positive electrodes respectively; Solid-state conductivity; Indicates the effective conductivity of the positive or negative electrode; This indicates the solid-phase current density at the positive or negative electrode. It is the solid-state potential; The liquid phase charge conservation equation is used to calculate the liquid phase potential: ； in, The conductivity of the electrolyte. It is the correlation coefficient of electrolyte activity; These represent the negative electrode, the separator, and the positive electrode, respectively. This represents the liquid current density at the negative electrode, the diaphragm, and the positive electrode. Indicates the liquid phase; Indicates the effective conductivity of the electrolyte; Represents the ideal gas constant; Indicates temperature; Denotes Faraday's constant; Indicates liquid phase potential; Electrochemical reaction kinetic equations, based on the Butler-Volmer equations, describe the reaction rates at the electrode / electrolyte interface: in, The reaction rate constants are the positive and negative electrodes. The transfer coefficients for the positive and negative poles are denoted as . This is an overpotential; , representing the negative and positive electrodes respectively; Indicates the equilibrium potential; Indicates current density; This indicates the maximum lithium intercalation concentration of the active material in the positive or negative electrode. This indicates the surface lithium intercalation concentration of the positive or negative electrode active material; Indicates the negative electrode transfer coefficient; Indicates the positive electrode transfer coefficient; This indicates an overpotential at the positive or negative electrode.

4. The electrothermal coupling simulation modeling method for high-energy-density lithium batteries with silicon-carbon anodes according to claim 3, characterized in that, The governing equations of the thermal model established in step S3 are heat conduction equations based on energy conservation: Total heat generation rate of battery =heat of reaction +Polarization heat +Ohm heat , The heat of reaction ; The polarization heat The ohmic heat in, This indicates the constant-pressure specific heat capacity of the material; Indicates the density of the material; Indicates the convective heat transfer coefficient; Indicates ambient temperature; Indicates the thermal conductivity coefficient; Indicates battery temperature; It is the local current density; It is solid-state potential. It is the liquid phase potential. It is the equilibrium potential; This indicates the open-circuit voltage.

5. The electrothermal coupling simulation modeling method for high-energy-density lithium batteries with silicon-carbon anodes according to claim 4, characterized in that, The negative electrode active component of the material set for the negative electrode region in step S4 is a silicon-carbon composite material, which contains silicon and graphite.

6. The electrothermal coupling simulation modeling method for high-energy-density lithium batteries with silicon-carbon anodes according to claim 5, characterized in that, The adjustable input parameters set in step S5 include material physicochemical parameters, electrical boundary conditions, thermal boundary conditions, initial temperature, initial state of charge, and the calculation time step of the transient solver.

7. The electrothermal coupling simulation modeling method for high-energy-density lithium batteries with silicon-carbon anodes according to claim 6, characterized in that, In step S6, the parameters in the electrochemical governing equation set are updated using the Arrhenius equation, based on the following mathematical relationship: in, Indicates the current temperature The reaction rate constant at the given time; Indicates at reference temperature The baseline reaction rate constant of the material itself is known. It represents the activation energy.

8. The electrothermal coupling simulation modeling method for high-energy-density lithium batteries with silicon-carbon anodes according to claim 7, characterized in that, In step S7, when meshing the geometric model, the mesh is refined in the electrode-diaphragm interface region and the particle surface region.

9. The electrothermal coupling simulation modeling method for high-energy-density lithium batteries with silicon-carbon anodes according to claim 8, characterized in that, In step S8, generating a new set of values ​​for the adjustable input parameters includes modifying at least one of the material physicochemical parameters, electrical boundary conditions, thermal boundary conditions, initial temperature and initial state of charge, and the calculation time step of the transient solver set in step S5.

10. A silicon-carbon anode high-energy-density lithium battery electrothermal coupling simulation modeling system, employing the silicon-carbon anode high-energy-density lithium battery electrothermal coupling simulation modeling method according to any one of claims 1-9, characterized in that, include: Module M1 constructs a geometric model of the high-energy-density lithium battery to be simulated based on battery parameters; Module M2 adds lithium-ion battery physical fields to the geometric model to establish a set of electrochemical control equations based on porous electrode theory and pseudo-three-dimensional model; Module M3 adds a solid heat transfer physical field to the geometric model to establish the governing equations of the thermal model based on the principle of energy conservation. Module M4 sets the corresponding materials for the positive electrode region, the separator region, and the negative electrode region in the geometric model, respectively; Module M5 sets the adjustable input parameters required for the electrochemical control equation set and the thermal model control equation; Module M6, based on the values ​​of the adjustable input parameters, bidirectionally couples the electrochemical control equation set with the thermal model control equation set. The coupling method is as follows: the reaction heat, polarization heat, and ohmic heat calculated by the electrochemical control equation set are used as source terms to input the thermal model control equation set; the temperature field results calculated by the thermal model control equation set are used to update the parameters in the electrochemical control equation set through the Arrhenius equation. Module M7 performs mesh generation on the geometric model; Module M8 uses a transient solver to perform the calculation and determines whether the calculation results meet the preset convergence criteria. If the judgment result is that the convergence criterion is not met, a new set of values ​​is generated for the adjustable input parameters and returned to module M6. If the judgment result is that the convergence criterion is met, the simulation results including temperature field, potential distribution and lithium ion concentration distribution are output.

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