WO2022242653A1 - 确定电芯充放电性能的方法、装置、存储介质及电子设备 - Google Patents

确定电芯充放电性能的方法、装置、存储介质及电子设备 Download PDF

Info

Publication number
WO2022242653A1
WO2022242653A1 PCT/CN2022/093382 CN2022093382W WO2022242653A1 WO 2022242653 A1 WO2022242653 A1 WO 2022242653A1 CN 2022093382 W CN2022093382 W CN 2022093382W WO 2022242653 A1 WO2022242653 A1 WO 2022242653A1
Authority
WO
WIPO (PCT)
Prior art keywords
target
model
target cell
cell
preset
Prior art date
Application number
PCT/CN2022/093382
Other languages
English (en)
French (fr)
Inventor
王连旭
杨红新
骆兆军
高飞
何见超
于奥
李峰宇
陈思
Original Assignee
蜂巢能源科技股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 蜂巢能源科技股份有限公司 filed Critical 蜂巢能源科技股份有限公司
Publication of WO2022242653A1 publication Critical patent/WO2022242653A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/3865—Arrangements for measuring battery or accumulator variables related to manufacture, e.g. testing after manufacture
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

Definitions

  • the present application relates to the field of battery performance detection, in particular, to a method, device, storage medium and electronic equipment for determining the charging and discharging performance of a battery.
  • a positive pole piece with a double-layer coating structure is proposed in related technologies. It improves the compatibility between coatings, avoids the dissolution of the internal coating by double-layer coating, improves the flatness of the surface of the pole piece, effectively improves the safety performance of lithium-ion batteries, and also has a positive effect on the rate performance and cycle performance of the battery.
  • the electrochemical performance measurement process requires a lot of human and material resources, and the time cost is high, which in turn affects the iteration speed of the cell.
  • the purpose of this application is to provide a method, device, storage medium and electronic equipment for determining the charging and discharging performance of a battery cell.
  • a method for determining the charging and discharging performance of a battery comprising: obtaining a preset target battery model, the target battery model is used to charge the target battery at a preset ambient temperature
  • the discharge performance is simulated, the target cell includes a cell made of at least two layers of coated electrodes; the target cell is subjected to a first preset at the preset ambient temperature through the target cell model
  • the process of carrying out constant current rate charging or constant current rate discharge is simulated; according to the simulation results, the target performance parameters of the target cell are determined, and the target performance parameters include performing constant current on the target cell at the preset ambient temperature
  • the target performance parameters include lithium ion concentration distribution and potential distribution on the target cell;
  • the simulation results include lithium ion concentrations at different positions of the target cell obtained at multiple preset times , the solid-phase potential at different positions and the liquid-phase potential at different positions;
  • the determination of the target performance parameters of the target cell according to the simulation results includes: Lithium at different positions of the target cell respectively obtained according to a plurality of preset times The ion concentration determines the lithium ion concentration distribution of the target cell at the target moment; the solid-phase potential at different positions of the target cell and the liquid at different positions respectively obtained according to a plurality of preset times The phase potential determines the potential distribution of the target cell at the target moment.
  • the target cell model includes a one-dimensional cell model, a two-dimensional cell model or a three-dimensional cell model, wherein the one-dimensional cell model is used to preset the thickness direction of the target cell Simulate the lithium ion concentration distribution and the potential distribution of the target battery; the two-dimensional battery model is used to calculate the lithium ion concentration distribution and the lithium ion concentration distribution in the preset thickness direction and preset height direction of the target battery cell.
  • the electric potential distribution is simulated; the three-dimensional battery model is used to simulate the lithium ion concentration distribution and the electric potential distribution in the preset thickness direction, preset height direction and preset length direction of the target battery cell .
  • the target performance parameters include the capacity and energy corresponding to the target battery cell
  • the simulation results include charging or discharging the target battery cell at a constant current rate according to the first preset current
  • the target time and the cell simulation voltage measured at different preset times, the target time includes the charging cut-off time or discharge cut-off time;
  • the determination of the target performance parameters of the target cell according to the simulation results includes: according to the target time
  • the energy corresponding to the target battery is determined from the simulation voltage of the battery cell measured at different preset times, and the capacity corresponding to the target battery is determined according to the target time.
  • the target performance parameter includes a target cell temperature at at least one specified location on the target cell
  • the simulation result includes cell temperatures collected by temperature sensing devices set at different preset locations, and the specified The location includes any of the preset locations
  • the determination of the target performance parameters of the target cell according to the simulation results includes: taking the cell temperature collected by the temperature sensing device set at the specified position as the target cell temperature .
  • the target battery model includes an electrochemical model and a solid heat transfer model; the electrochemical model is used to simulate the electrochemical performance of the target battery during charging and discharging, and the solid heat transfer model The model is used to simulate the temperature transfer of the target cell during charging and discharging.
  • the target cell model is pre-established in the following manner:
  • the preset model parameters include custom parameters, cell design parameters, electrochemical parameters and thermodynamic parameters; establish the finite element electrochemical geometry model and finite element solid heat transfer geometry corresponding to the target cell model, and set the material properties of each region in the finite element electrochemical geometric model and the finite element solid heat transfer geometric model according to the user's trigger operation; obtain user-defined model input parameters and model output parameters; according to the The target cell model is established based on the preset model parameters, the model input parameters, the model output parameters, the finite element electrochemical geometric model with set material properties, and the finite element solid heat transfer geometric model with set material properties.
  • a device for determining the charging and discharging performance of a battery comprising:
  • the obtaining module is used to obtain a preset target cell model, the target cell model is used to simulate the charging and discharging performance of the target cell at a preset ambient temperature, and the target cell includes at least two layers of coating A cell made of cloth electrodes; a simulation module for performing constant current rate charging or constant current rate discharge on the target cell at the preset ambient temperature according to the first preset current through the target cell model The process is simulated; the determination module is used to determine the target performance parameters of the target battery according to the simulation results, and the target performance parameters include charging performance when the target battery is charged at a constant current rate at the preset ambient temperature parameters, or include discharge performance parameters when the target cell is discharged at a constant current rate at the preset ambient temperature.
  • the target performance parameters include lithium ion concentration distribution and potential distribution on the target cell;
  • the simulation results include lithium ion concentrations at different positions of the target cell obtained at multiple preset times , solid-phase potentials at different positions and liquid-phase potentials at different positions;
  • the determining module is configured to determine the target battery cell according to lithium ion concentrations at different positions of the target battery cell obtained at multiple preset times The lithium ion concentration distribution at the target moment; determining the target cell according to the solid-phase potential at different positions of the target cell and the liquid-phase potential at different positions respectively obtained at a plurality of preset moments The potential distribution at the target instant.
  • the target cell model includes a one-dimensional cell model, a two-dimensional cell model or a three-dimensional cell model, wherein the one-dimensional cell model is used to preset the thickness direction of the target cell Simulate the lithium ion concentration distribution and the potential distribution of the target battery; the two-dimensional battery model is used to calculate the lithium ion concentration distribution and the lithium ion concentration distribution in the preset thickness direction and preset height direction of the target battery cell.
  • the electric potential distribution is simulated; the three-dimensional battery model is used to simulate the lithium ion concentration distribution and the electric potential distribution in the preset thickness direction, preset height direction and preset length direction of the target battery cell .
  • the target performance parameters include the capacity and energy corresponding to the target battery cell
  • the simulation results include charging or discharging the target battery cell at a constant current rate according to the first preset current
  • the target time and the battery simulation voltage measured at different preset times, the target time includes the charging cut-off time or the discharge cut-off time; the determination module is used to measure according to the target time and different preset times
  • the energy corresponding to the target battery cell is determined according to the simulation voltage of the battery cell; the capacity corresponding to the target battery cell is determined according to the target time.
  • the target performance parameter includes a target cell temperature at at least one specified location on the target cell
  • the simulation result includes cell temperatures collected by temperature sensing devices set at different preset locations
  • the specified The location includes any of the preset locations
  • the determination module is configured to use the cell temperature collected by the temperature sensing device arranged at the designated location as the target cell temperature.
  • the target battery model includes an electrochemical model and a solid heat transfer model; the electrochemical model is used to simulate the electrochemical performance of the target battery during charging and discharging, and the solid heat transfer model The model is used to simulate the temperature transfer of the target cell during charging and discharging.
  • the target cell model is pre-established in the following manner:
  • the preset model parameters include custom parameters, cell design parameters, electrochemical parameters and thermodynamic parameters; establish the finite element electrochemical geometry model and finite element solid heat transfer geometry corresponding to the target cell model, and set the material properties of each region in the finite element electrochemical geometric model and the finite element solid heat transfer geometric model according to the user's trigger operation; obtain user-defined model input parameters and model output parameters; according to the The target cell model is established based on the preset model parameters, the model input parameters, the model output parameters, the finite element electrochemical geometric model with set material properties, and the finite element solid heat transfer geometric model with set material properties.
  • a non-transitory computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the method described in the first aspect of the present application are implemented.
  • an electronic device including: a memory, on which a computer program is stored; and a processor, configured to execute the computer program in the memory, so as to implement the steps of the method described in the first aspect of the present application.
  • a preset target cell model is obtained, the target cell model is used to simulate the charging and discharging performance of the target cell at a preset ambient temperature, and the target cell includes at least two layers of coating A cell made of cloth electrodes; using the target cell model to simulate the process of the target cell being charged at a constant current rate or discharged at a constant current rate at the preset ambient temperature according to a first preset current; Determine the target performance parameters of the target battery according to the simulation results, the target performance parameters include the charging performance parameters when the target battery is charged at a constant current rate at the preset ambient temperature, or include charging performance parameters at the preset ambient temperature The discharge performance parameters when the target cell is discharged at a constant current rate, so that the charging and discharging performance of the cell made of at least two layers of coated electrodes can be determined through simulation, so that the obtained value can be obtained according to the simulation.
  • the target performance parameters optimize the cell design without the need for actual measurement and a large number of experimental optimizations, which speeds up the R&D process, shortens the R&D cycle, reduces labor costs, time costs, and cell manufacturing costs, and realizes rapid product iteration of cell design.
  • Fig. 1 is a flow chart of a method for determining the charging and discharging performance of a cell according to an exemplary embodiment
  • Fig. 2 is a schematic diagram showing the relationship between an electrochemical model and a solid heat transfer model according to an exemplary embodiment
  • Fig. 3 is a schematic structural diagram of a one-dimensional cell model shown according to an exemplary embodiment
  • Fig. 4 is a schematic structural diagram of a two-dimensional cell model shown according to an exemplary embodiment
  • Fig. 5 is a schematic structural diagram of a three-dimensional cell model shown according to an exemplary embodiment
  • Fig. 6 is a flowchart of a method for establishing a target cell model according to an exemplary embodiment
  • Fig. 7 is a block diagram of a device for determining the charging and discharging performance of a cell according to an exemplary embodiment
  • Fig. 8 is a structural block diagram of an electronic device according to an exemplary embodiment.
  • This application is mainly used in the scenario of testing the charge and discharge performance of the target cell made of multi-layer coated electrodes in the process of cell design and development, wherein the target cell is Refers to a cell made of at least two layers of coated electrodes, and the positive or negative electrode of the cell can be made of multiple coatings.
  • the present application provides a method, device, storage medium and electronic equipment for the charge and discharge performance of the battery cell, which can determine the charge and discharge performance of the battery cell made of at least two layers of coated electrodes by means of simulation , so that the battery design can be optimized according to the target performance parameters obtained by simulation, without the need for actual measurement and a large number of experimental optimizations, which speeds up the research and development process, shortens the research and development cycle, reduces labor costs, time costs and battery production costs, and realizes Rapid product iteration of cell design.
  • Fig. 1 is a flowchart of a method for determining the charging and discharging performance of a cell according to an exemplary embodiment. As shown in Fig. 1, the method includes the following steps:
  • step S101 a preset target cell model is obtained, the target cell model is used to simulate the charge and discharge performance of the target cell at a preset ambient temperature, the target cell includes at least two layers of coated electrodes manufactured batteries.
  • the target cell model includes an electrochemical model and a solid heat transfer model
  • the electrochemical model is used to simulate the electrochemical performance of the target cell during charging and discharging
  • the solid heat transfer model is used to The temperature transfer of the battery cell during charging and discharging is simulated;
  • the preset ambient temperature includes but not limited to any of the following temperatures: -30°C, -10°C, 0°C, 25°C, 45°C, 60°C.
  • Fig. 2 is a schematic diagram showing the interaction between an electrochemical model and a solid heat transfer model according to an exemplary embodiment.
  • the solid heat transfer model To the solid heat transfer model, it is converted into the temperature change of the battery core, and then the temperature is coupled to the electrochemical model.
  • the sensitive parameters about the temperature in the electrochemical model will change with the change of temperature, thus realizing the electrochemical and solid heat transfer. Interaction.
  • the electrochemical model may include a finite element electrochemical geometric model
  • the solid heat transfer model may include a finite element solid heat transfer geometric model.
  • users generally refer to cell designers
  • Use COMSOL Mutiphysics software to pre-establish the target cell model (the specific model establishment process will be described below).
  • step S102 the process of performing constant current rate charging or constant current rate discharge on the target cell at the preset ambient temperature according to the first preset current is simulated through the target cell model.
  • the first preset current may be a cell charging current or a cell discharging current arbitrarily set by a cell designer according to current testing requirements.
  • a preset magnification can be selected from a plurality of preset magnifications as the current magnification, and the current magnification, the preset ambient temperature and the first preset current are used as the target cell model
  • the terminal can use the target cell model in the COMSOL Mutiphysics software to operate the target cell at the preset ambient temperature according to the first preset environment temperature.
  • the target time when a preset current is charged at a constant current rate or discharged at a constant current rate includes the charge cut-off time or discharge cut-off time
  • the cell simulation voltage at different preset times includes the different preset times
  • Performance parameters such as the simulated temperature of the cell at different preset positions of the cell.
  • the results of charge and discharge simulation tests of the target cell at multiple preset ambient temperatures and multiple preset magnifications can be obtained.
  • the simulation curves corresponding to multiple preset rates at the preset ambient temperature can be obtained by simulation, so as to determine the target performance parameters of the target cell when charging and discharging with different charge and discharge rates at the same ambient temperature, and also The target performance parameters of the target cell at the same charge and discharge rate and corresponding to different ambient temperatures can be determined.
  • the target performance parameters of the target cell are determined according to the simulation results, the target performance parameters include the charging performance parameters when the target cell is charged at a constant current rate at the preset ambient temperature, or are included in the preset ambient temperature. Set the discharge performance parameters when the target cell is discharged at a constant current rate at the ambient temperature.
  • the target performance parameter may include but not limited to one or more parameters in the following parameters: the capacity corresponding to the target cell, energy, lithium ion concentration distribution on the target cell, potential distribution, and The target cell temperature of at least one specified location
  • the simulation results may include but not limited to one or more of the following results: Lithium ion concentrations at different locations of the target cell obtained at multiple preset times, and at multiple The solid-phase potential at different positions and the liquid-phase potential at different positions respectively obtained at the preset time, and the target time for the target cell to be charged at a constant current rate or discharged at a constant current rate according to the first preset current (the target time can be Including charge cut-off time or discharge cut-off time), the simulated voltage of the cell measured at different preset times, and the temperature of the cell collected by the temperature sensing device set at different preset positions, and the temperature sensing device may include a temperature probe.
  • the underlying mass conservation equation and charge conservation equation can be built into the target cell model in advance, so that when simulating the charging or discharging process of the target cell based on the target cell model, the The mass conservation equation and the initial value of the lithium ion concentration are calculated by the model to obtain the lithium ion concentration of the target cell at different preset times, and the charge conservation equation and the initial value of the solid phase potential are calculated by the model to obtain the target cell at different
  • the solid-phase potential at the preset moment, through the charge conservation equation and the initial value of the liquid-phase potential, the liquid-phase potential of the target cell at different preset moments is calculated by the model; in addition, it can also be defined at different positions of the target cell Temperature probe, through which the temperature changes at different positions of the battery core can be observed.
  • the different positions can include the positive pole pole, the negative pole pole pole, the center of the large surface, the center of the pole group and other positions of the battery core. This is just an example It should be noted that this application is not limited to this.
  • the lithium ion concentration of the target cell at the target time can be determined according to the lithium ion concentrations at different positions of the target cell obtained at a plurality of preset times.
  • Concentration distribution, wherein the target time may be any time among multiple preset times, or any time between any two adjacent preset times specified by the user.
  • an implementation method may be to obtain the lithium ion concentration of the target battery at different positions simulated at the target moment, and then use the electrochemical geometric model
  • the position of the negative electrode current collector is the origin of the coordinates
  • the distance from the origin of the coordinates is the abscissa
  • the lithium ion concentration is the ordinate to draw a graph to obtain the lithium ion concentration distribution of the target cell, so that the user can
  • the distribution of the lithium ion concentration displayed can be used to understand the lithium ion movement of the target cell during charging or discharging in a timely manner, and then optimize the design of the cell based on this.
  • the lithium ions of the target cell at different positions respectively corresponding to the two adjacent preset moments can be obtained.
  • the target cell can be determined according to the solid-phase potential at different positions of the target cell and the liquid-phase potential at different positions respectively obtained at a plurality of preset times
  • the potential of the cell is equal to the difference between the solid-phase potential and the liquid-phase potential.
  • the position where the fluid is located) is the origin of the coordinates
  • the distance from the preset position is the horizontal axis
  • the difference between the solid phase potential and the liquid phase potential of each position at different positions is plotted on the vertical axis to determine the target The potential distribution of the cell.
  • the energy corresponding to the target cell can be determined according to the target time in the simulation results and the cell simulation voltage measured at different preset times;
  • the target time determines the capacity corresponding to the target cell.
  • the capacity and energy of the target cell can be calculated by writing the following global ordinary differential and differential algebraic equations in the target cell model:
  • W represents the energy of the target cell
  • Q represents the capacity of the target cell
  • I represents the constant charge and discharge current (ie the first preset current)
  • E cell represents the cell emulation voltage of the target cell.
  • the target performance parameter also includes the target cell temperature of at least one designated position on the target cell, and the designated position can be any preset position.
  • the target cell temperature of the target cell is determined according to the simulation result During the process, the cell temperature collected by the temperature sensing device arranged at the specified position can be used as the target cell temperature.
  • the target cell before producing the target cell, it is possible to simulate the charging and discharging process of the target cell at a constant current rate at different preset ambient temperatures, and to know the performance of the target cell according to the simulation results , so as to optimize the battery design according to the determined performance of the target battery, for example, the rated capacity of the target battery is 84Ah (Ah), the determined actual capacity (or It is called the actual play capacity) is 78Ah.
  • the battery design can be optimized by appropriately reducing the thickness of the pole piece, increasing the conductive agent, increasing the porosity of the porous electrode, and reducing the particle size of the positive/negative active material, so that the optimized
  • the target battery cell meets the performance requirements of charging and discharging, thereby speeding up the research and development process, shortening the research and development cycle, reducing labor costs, time costs and battery manufacturing costs, and realizing rapid product iteration of battery cell design.
  • a one-dimensional battery model, A two-dimensional cell model and a three-dimensional cell model may include a one-dimensional cell model, a two-dimensional cell model, or a three-dimensional cell model, wherein the one-dimensional cell model is used for The lithium ion concentration distribution and the potential distribution in the preset thickness direction of the target cell are simulated; the two-dimensional cell model is used for the lithium ion in the preset thickness direction and preset height direction of the target cell The concentration distribution and the potential distribution are simulated; the three-dimensional cell model is used to simulate the lithium ion concentration distribution and the potential distribution of the target cell in all directions.
  • Fig. 3 is a schematic structural view of a one-dimensional cell model according to an exemplary embodiment
  • Fig. 4 is a schematic structural view of a two-dimensional cell model according to an exemplary embodiment
  • Fig. 5 is a schematic structural view of a two-dimensional cell model according to an exemplary embodiment
  • the positive electrode of the target battery includes two coated Layer as an example, as shown in Figure 3, the geometric structure of the one-dimensional cell model from left to right is negative current collector, negative porous electrode, separator, positive porous electrode coating 2, positive porous electrode coating 1, positive electrode Collector, like this, assume that lithium ions only move in the preset thickness direction of the cell, based on the one-dimensional cell model, it can be known that the target cell is in the preset thickness direction (in the cell geometry as shown in Figure 3 Lithium ion concentration distribution and potential distribution in the direction from left to right;
  • Concentration distribution and potential distribution as shown in Figure 5, it is the three-dimensional cell model of the target cell.
  • the three-dimensional cell model is the same as the actual cell structure. Based on the three-dimensional cell model, it can be known that the target cell is in all
  • the lithium ion concentration distribution and potential distribution in the direction the above examples are only for illustration, and the present application is not limited thereto.
  • the model can automatically After the operation, the corresponding target performance parameters can be retrieved to draw a visual map, for example, the voltage-time curve, voltage-capacity curve, capacity-power curve, battery temperature-time curve, etc. can be drawn, and the charging or discharging of the battery can also be drawn Lithium ion concentration changes in the solid or liquid phase during the process.
  • the temperature distribution cloud map, the potential distribution of the porous electrode, the current density distribution, and the lithium ion concentration distribution cloud map in the solid or liquid phase can also be obtained. Therefore, the charging and discharging performance of the target cell can be displayed to the user more intuitively.
  • the charge and discharge performance of the cell made of at least two layers of coated electrodes can be determined by simulation, so that the cell design can be optimized according to the target performance parameters obtained by simulation, without the need for actual measurement and a large number of experimental optimizations , to speed up the R&D process, shorten the R&D cycle, reduce labor costs, time costs and cell production costs, and realize rapid product iteration of cell design.
  • the lithium ion concentration distribution or potential distribution of the battery in different dimensional directions can also be determined according to the battery model of different dimensions, so as to provide reference data of different dimensions for the research and development of the battery.
  • Fig. 6 is a flowchart of a method for establishing a target cell model according to an exemplary embodiment. As shown in Fig. 6, the method includes the following steps:
  • step S601 preset model parameters are obtained, and the preset model parameters include user-defined parameters, cell design parameters, electrochemical parameters, and thermodynamic parameters.
  • the user-defined parameter may include a user-defined charge and discharge rate and a preset ambient temperature
  • the cell design parameter may include the design size of the target cell
  • the electrochemical parameter may include the parameters shown in Table 1 and the target cell.
  • the maximum state of charge of the porous positive electrode of the core, the minimum state of charge of the porous positive electrode, the maximum state of charge of the porous negative electrode, the minimum state of charge of the porous negative electrode, the initial electrolyte salt concentration, Brugman coefficient and other parameters, thermodynamic parameters can include convective heat transfer coefficient and the temperature derivative of the equilibrium potential of the positive and negative electrode materials.
  • the electrochemical parameters of the target cell can be determined by consulting the literature or testing according to the commonly used electrochemical equations (such as Fick's second law, Butler-Volmer equation, Nernst-Plank equation). Collect the design parameters of the cell to obtain the initial value of the preset model parameters.
  • electrochemical equations such as Fick's second law, Butler-Volmer equation, Nernst-Plank equation.
  • step S602 the finite element electrochemical geometric model and the finite element solid heat transfer geometric model corresponding to the target cell are established, and the finite element electrochemical geometric model and the finite element solid heat transfer geometric model are set according to the user's trigger operation Material properties for each region in .
  • the target cell whose positive electrode is made of two coatings first draw the three-dimensional finite element electrochemical geometric model of the target cell with a six-layer structure, as shown in Figure 5, the six-layer structure is sequentially the positive electrode Current collector, positive electrode porous electrode coating 1, positive electrode porous electrode coating 2, separator, negative electrode porous electrode, negative electrode current collector, and then give different regions corresponding regional properties and material properties, where the regional properties can include positive and negative active materials, Electrolyte, diaphragm, current collector, for example, you can embed the corresponding area attributes in the "Area Attributes" interface in the model interface, and then select the corresponding electrolyte material domain in the corresponding defined geometric area in the "Lithium-ion Battery” interface Or positive and negative active materials.
  • the material properties corresponding to different regions can also be set, wherein the material properties of the positive and negative electrodes include conductivity, solid phase diffusion coefficient, equilibrium potential, temperature derivative of equilibrium potential, reference concentration, maximum and minimum state of charge of the electrode, etc. Since the pores of the diaphragm entity are filled with the electrolyte, it is necessary to assign the properties of the electrolyte to the diaphragm, including liquid phase diffusion coefficient, electrolyte conductivity, transfer number, activity correlation, etc., and assign properties of aluminum or copper to the positive or negative current collector , including electrical conductivity, the above is only for illustration, and the present application is not limited thereto.
  • the pre-establishment process of the target cell model will be described below.
  • the properties of the negative porous electrode can be defined, and the properties of the negative electrode material set by the user can be obtained according to the user’s trigger operation, and the temperature, active material volume fraction, porosity, effective electrolyte conductivity and effective solid phase diffusion coefficient of the porous electrode can be further determined , define the porous electrode reaction temperature, the electrode kinetic expression, define the particle intercalation temperature, the initial lithium ion concentration, and select the lithium ion concentration transfer model.
  • the diffusion of lithium generally adopts Fick’s second The law defines and defines the particle size of the particles.
  • the active material of the negative electrode includes but is not limited to: graphite, silicon oxide, lithium metal, etc.
  • the coating 1 and coating 2 of the positive electrode can be the same positive electrode material It can also be different positive electrode materials, wherein the positive electrode materials include but are not limited to: lithium cobalt oxide, lithium iron phosphate, lithium manganese oxide, nickel cobalt lithium manganese oxide, etc.
  • the thickness and porosity of coating 1 and coating 2 can be determined according to actual conditions.
  • the porosity of the coating near the current collector can be set to be lower than that of the coating near the diaphragm. layer porosity.
  • the diaphragm, positive and negative current collectors, electrical grounding and electrode current, initial battery charge distribution can be defined in turn, and grid division can be performed to perform finite element calculations based on the divided finite number of small cells.
  • the solid heat transfer geometric model of the target cell can be established.
  • a simplified geometric model or a real geometric model consistent with the actual cell structure can be used.
  • the simplified geometric model can be a cuboid with the same size as the actual cell, or it can be a simple geometric model that simplifies some structural parts.
  • the solid heat transfer geometric model can be The material properties (such as constant pressure heat capacity, density, thermal conductivity, etc.)
  • the heat transfer model sets the model, including setting the temperature of the solid (depolarization group), and selecting the corresponding material properties, defining the external temperature of the battery cell, defining the equivalent thermal conductivity in different directions, defining the heat source, and selecting the pole group domain
  • couple the heat generation in the electrochemical model to the solid heat transfer model define the heat exchange (or heat flux) between the cell and the external environment, and define the convective heat transfer coefficient (usually 10-20W* m-2*K-1), and set the external temperature, that is, the ambient temperature of the battery cell.
  • step S603 user-defined model input parameters and model output parameters are acquired.
  • the input parameters of the model may include current density
  • the output parameters of the model may include battery voltage, cell temperature, charging cut-off time or discharge cut-off time when the simulation stop condition is met
  • the stop condition may be set as the upper limit of the cell voltage or The lower limit may also be set as the upper limit of the battery cell temperature, which is not limited in this application.
  • step S604 the target electrochemical model is established according to the preset model parameters, the model input parameters, the model output parameters, the finite element electrochemical geometric model with the material properties set, and the finite element solid heat transfer geometric model with the material properties set. core model.
  • the target cell model corresponding to the target cell is established, and different preset ambient temperatures correspond to different target cell models.
  • the basic properties include: the solid phase diffusion coefficient of the positive and negative materials , conductivity, the maximum lithium ion concentration, the equilibrium potential of the material and the temperature derivative of the equilibrium potential, etc.
  • Fig. 7 is a device for determining the charging and discharging performance of a cell according to an exemplary embodiment. As shown in Fig. 7, the device includes:
  • the obtaining module 701 is used to obtain a preset target cell model, the target cell model is used to simulate the charging and discharging performance of the target cell at a preset ambient temperature, and the target cell includes at least two layers of coating Cells made of electrodes;
  • the simulation module 702 is used to simulate the process of performing constant current rate charging or constant current rate discharge of the target cell at the preset ambient temperature according to the first preset current through the target cell model;
  • the determination module 703 is used to determine the target performance parameters of the target battery cell according to the simulation results, and the target performance parameters include charging performance parameters when the target battery cell is charged at a constant current rate at the preset ambient temperature, or included in the preset ambient temperature.
  • the target performance parameters include lithium ion concentration distribution and potential distribution on the target battery cell;
  • the simulation results include the lithium ion concentration at different positions of the target battery cell, the Solid phase potential and liquid phase potential at different positions;
  • the determination module 703 is used to determine the lithium ion concentration distribution of the target battery at the target time according to the lithium ion concentrations at different positions of the target battery obtained at the multiple preset times; The obtained solid phase potentials at different positions of the target cell and the liquid phase potentials at different positions determine the potential distribution of the target cell at the target moment.
  • the target cell model includes a one-dimensional cell model, a two-dimensional cell model or a three-dimensional cell model, wherein the one-dimensional cell model is used to preset the lithium battery in the thickness direction of the target cell
  • the ion concentration distribution and the potential distribution are simulated
  • the two-dimensional cell model is used to simulate the lithium ion concentration distribution and the potential distribution in the preset thickness direction and preset height direction of the target cell
  • the core model is used to simulate the lithium ion concentration distribution and the potential distribution in the preset thickness direction, preset height direction and preset length direction of the target cell.
  • the target performance parameter includes the capacity and energy corresponding to the target battery cell
  • the simulation result includes the target time and the difference between the target battery cell being charged at a constant current rate or discharged at a constant current rate according to the first preset current.
  • the battery simulation voltage measured at the preset time, the target time includes the charging cut-off time or discharge cut-off time;
  • the determining module 703 is configured to determine the energy corresponding to the target battery according to the target time and the battery simulation voltage measured at different preset times; determine the capacity corresponding to the target battery according to the target time.
  • the target performance parameter includes a target cell temperature at at least one specified location on the target cell;
  • the simulation result includes cell temperatures collected by temperature sensing devices arranged at different preset positions;
  • the determining module 603 is configured to use the cell temperature collected by the temperature sensing device arranged at the designated position as the target cell temperature.
  • the target cell model includes an electrochemical model and a solid heat transfer model; the electrochemical model is used to simulate the electrochemical performance of the target cell during charging and discharging, and the solid heat transfer model is used to The temperature transfer of the target cell during charging and discharging is simulated.
  • the target cell model is pre-established in the following ways:
  • Obtain preset model parameters which include custom parameters, cell design parameters, electrochemical parameters, and thermodynamic parameters; establish a finite element electrochemical geometric model and a finite element solid heat transfer geometric model corresponding to the target cell, And set the material properties of each region in the finite element electrochemical geometric model and the finite element solid heat transfer geometric model according to the user's trigger operation; obtain user-defined model input parameters and model output parameters; according to the preset model parameters , the model input parameters, the model output parameters, the finite element electrochemical geometric model with set material properties, and the finite element solid heat transfer geometric model with set material properties to establish the target cell model.
  • the charge and discharge performance of the cell made of at least two layers of coated electrodes can be determined by simulation, so that the cell design can be optimized according to the target performance parameters obtained by simulation, without the need for actual measurement and a large number of experimental optimizations , to speed up the R&D process, shorten the R&D cycle, reduce labor costs, time costs and cell production costs, and realize rapid product iteration of cell design.
  • Fig. 8 is a block diagram of an electronic device 800 according to an exemplary embodiment.
  • the electronic device 800 may include: a processor 801 and a memory 802 .
  • the electronic device 800 may also include one or more of a multimedia component 803 , an input/output (I/O) interface 804 , and a communication component 805 .
  • I/O input/output
  • the processor 801 is used to control the overall operation of the electronic device 800 to complete all or part of the steps in the above-mentioned method for determining the charging and discharging performance of the battery cell.
  • the memory 802 is used to store various types of data to support the operation of the electronic device 800, for example, these data may include instructions for any application or method operating on the electronic device 800, and application-related data, Such as contact data, sent and received messages, pictures, audio, video, etc.
  • the memory 802 can be implemented by any type of volatile or non-volatile storage device or their combination, such as Static Random Access Memory (Static Random Access Memory, referred to as SRAM), Electrically Erasable Programmable Read-Only Memory (EPROM) Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), Erasable Programmable Read-Only Memory (Erasable Programmable Read-Only Memory, referred to as EPROM), Programmable Read-Only Memory (Programmable Read-Only Memory, referred to as PROM), read-only Memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk.
  • Multimedia components 803 may include screen and audio components.
  • the screen can be, for example, a touch screen, and the audio component is used for outputting and/or inputting audio signals.
  • an audio component may include a microphone for receiving external audio signals.
  • the received audio signal may be further stored in the memory 802 or sent through the communication component 805 .
  • the audio component also includes at least one speaker for outputting audio signals.
  • the I/O interface 804 provides an interface between the processor 801 and other interface modules, which may be a keyboard, a mouse, buttons, and the like. These buttons can be virtual buttons or physical buttons.
  • the communication component 805 is used for wired or wireless communication between the electronic device 800 and other devices.
  • the corresponding communication component 805 may include: a Wi-Fi module, a Bluetooth module, an NFC module and the like.
  • the electronic device 800 may be implemented by one or more application-specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), digital signal processors (Digital Signal Processor, DSP for short), digital signal processing equipment (Digital Signal Processing Device, referred to as DSPD), programmable logic device (Programmable Logic Device, referred to as PLD), field programmable gate array (Field Programmable Gate Array, referred to as FPGA), controller, microcontroller, microprocessor or other electronic components
  • ASIC Application Specific Integrated Circuit
  • DSP Digital Signal Processor
  • DSPD Digital Signal Processing Device
  • PLD programmable logic device
  • FPGA Field Programmable Gate Array
  • controller microcontroller
  • microprocessor or other electronic components The implementation is used to implement the above-mentioned method for determining the charging and discharging performance of the battery cell.
  • a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned method for determining the charging and discharging performance of a battery are implemented.
  • the computer-readable storage medium may be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions can be executed by the processor 801 of the electronic device 800 to complete the above-mentioned method for determining the charging and discharging performance of a battery cell.
  • a computer program product comprising a computer program executable by a programmable device, the computer program having a function for performing the above-mentioned The code portion of the method for determining the charge and discharge performance of a cell.

Landscapes

  • Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Secondary Cells (AREA)

Abstract

一种确定电芯充放电性能的方法、装置、存储介质及电子设备，方法包括：获取预先设置的目标电芯模型，目标电芯模型用于对目标电芯在预设环境温度下的充放电性能进行仿真，目标电芯包括由至少两层涂布电极制成的电芯（S101）；通过目标电芯模型对目标电芯在预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电的过程进行仿真（S102）；根据仿真结果确定目标电芯的目标性能参数，目标性能参数包括在该预设环境温度下对目标电芯进行恒流倍率充电时的充电性能参数，或者包括在该预设环境温度下对目标电芯进行恒流倍率放电时的放电性能参数（S103）。

Description

确定电芯充放电性能的方法、装置、存储介质及电子设备
本申请要求在2021年05月17日提交中国专利局、申请号为202110535290.X、发明名称为“确定电芯充放电性能的方法、装置、存储介质及电子设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及电芯性能检测领域，具体地，涉及一种确定电芯充放电性能的方法、装置、存储介质及电子设备。
背景技术
随着市场对新能源汽车的迫切需求，动力电池企业也要加快电芯迭代速度，缩短研发周期，为了改善电芯的性能，相关技术中提出了一种双层涂覆结构的正极极片，改善了涂层间的兼容性，同时避免双层涂布对内部涂层的溶解问题，提高了极片表面的平整度，有效提高锂离子电池的安全性能，对电池的倍率性能、循环性能也有一定的提高，但基于多层结构的极片制作出的电芯性能具体提高了多少，一般需要通过实测才能知道，并且需要大量的实验优化出多层结构的最佳厚度，但实验及电芯电化学性能实测过程需要大量的人力物力资源，且时间成本较高，进而影响电芯的迭代速度。
发明内容
本申请的目的是提供一种确定电芯充放电性能的方法、装置、存储介质及电子设备。
第一方面，提供一种确定电芯充放电性能的方法，所述方法包括：获取预先设置的目标电芯模型，所述目标电芯模型用于对目标电芯在预设环境温度下的充放电性能进行仿真，所述目标电芯包括由至少两层涂布电极制成的电芯；通过所述目标电芯模型对所述目标电芯在所述预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电的过程进行仿真；根据仿真结果确定目标电芯的目标性能参数，所述目标性能参数包括在该预设环境温度下对所述目标电芯进行恒流倍率充电时的充电性能参数，或者包括在该预设环境温度下对所述目标电芯进行恒流倍率放电时的放电性能参数。
可选地，所述目标性能参数包括所述目标电芯上的锂离子浓度分布和电势分布；所述仿真结果包括在多个预设时刻分别得到的所述目标电芯不同位置的锂离子浓度、不同位置的固相电势和不同位置的液相电势；所述根据仿真结果确定目标电芯的目标性能参数包括：根据多个所述预设时刻分别得到的所述目标电芯不同位置的锂离子浓度确定所述目标电芯在目标时刻的所述锂离子浓度分布；根据多个所述预设时刻分别得到的所述目标电芯不同位置的所述固相电势和不同位置的所述液相电势确定所述目标电芯在所述目标时刻的所述电势分布。
可选地，所述目标电芯模型包括一维电芯模型、二维电芯模型或者三维电芯模型，其中，所述一维电芯模型用于对所述目标电芯预设厚度方向上的所述锂离子浓度分布和所述电势分布进行仿真；所述二维电芯模型用于对所述目标电芯的预设厚度方向和预设高度方向上的 所述锂离子浓度分布和所述电势分布进行仿真；所述三维电芯模型用于对所述目标电芯的预设厚度方向、预设高度方向以及预设长度方向上的所述锂离子浓度分布和所述电势分布进行仿真。
可选地，所述目标性能参数包括所述目标电芯对应的容量和能量，所述仿真结果包括对所述目标电芯按照所述第一预设电流进行恒流倍率充电或者恒流倍率放电的目标时间和不同预设时刻分别测得的电芯仿真电压，所述目标时间包括充电截止时间或者放电截止时间；所述根据仿真结果确定目标电芯的目标性能参数包括：根据所述目标时间和不同预设时刻分别测得的所述电芯仿真电压确定所述目标电芯对应的所述能量；根据所述目标时间确定所述目标电芯对应的所述容量。
可选地，所述目标性能参数包括所述目标电芯上至少一个指定位置的目标电芯温度，所述仿真结果包括设置在不同预设位置的温度感应装置采集的电芯温度，所述指定位置包括任一所述预设位置；所述根据仿真结果确定目标电芯的目标性能参数包括：将设置在所述指定位置的温度感应装置采集的所述电芯温度作为所述目标电芯温度。
可选地，所述目标电芯模型包括电化学模型和固体传热模型；所述电化学模型用于对所述目标电芯在充放电过程中的电化学性能进行仿真，所述固体传热模型用于对所述目标电芯在充放电过程中的温度传递进行仿真。
可选地，所述目标电芯模型通过以下方式预先建立：
获取预设模型参数，所述预设模型参数包括自定义参数、电芯设计参数、电化学参数以及热力学参数；建立所述目标电芯对应的有限元电化学几何模型和有限元固体传热几何模型，并根据用户的触发操作设置所述有限元电化学几何模型和所述有限元固体传热几何模型中每个区域的材料属性；获取用户自定义的模型输入参数和模型输出参数；根据所述预设模型参数、所述模型输入参数、所述模型输出参数、被设置材料属性的有限元电化学几何模型以及被设置材料属性的有限元固体传热几何模型建立所述目标电芯模型。
第二方面，提供一种确定电芯充放电性能的装置，所述装置包括：
获取模块，用于获取预先设置的目标电芯模型，所述目标电芯模型用于对目标电芯在预设环境温度下的充放电性能进行仿真，所述目标电芯包括由至少两层涂布电极制成的电芯；仿真模块，用于通过所述目标电芯模型对所述目标电芯在所述预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电的过程进行仿真；确定模块，用于根据仿真结果确定目标电芯的目标性能参数，所述目标性能参数包括在该预设环境温度下对所述目标电芯进行恒流倍率充电时的充电性能参数，或者包括在该预设环境温度下对所述目标电芯进行恒流倍率放电时的放电性能参数。
可选地，所述目标性能参数包括所述目标电芯上的锂离子浓度分布和电势分布；所述仿真结果包括在多个预设时刻分别得到的所述目标电芯不同位置的锂离子浓度、不同位置的固相电势和不同位置的液相电势；所述确定模块，用于根据多个所述预设时刻分别得到的所述目标电芯不同位置的锂离子浓度确定所述目标电芯在目标时刻的所述锂离子浓度分布；根据多个所述预设时刻分别得到的所述目标电芯不同位置的所述固相电势和不同位置的所述液相电势确定所述目标电芯在所述目标时刻的所述电势分布。
可选地，所述目标电芯模型包括一维电芯模型、二维电芯模型或者三维电芯模型，其中，所述一维电芯模型用于对所述目标电芯预设厚度方向上的所述锂离子浓度分布和所述电势分布进行仿真；所述二维电芯模型用于对所述目标电芯的预设厚度方向和预设高度方向上的 所述锂离子浓度分布和所述电势分布进行仿真；所述三维电芯模型用于对所述目标电芯的预设厚度方向、预设高度方向以及预设长度方向上的所述锂离子浓度分布和所述电势分布进行仿真。
可选地，所述目标性能参数包括所述目标电芯对应的容量和能量，所述仿真结果包括对所述目标电芯按照所述第一预设电流进行恒流倍率充电或者恒流倍率放电的目标时间和不同预设时刻分别测得的电芯仿真电压，所述目标时间包括充电截止时间或者放电截止时间；所述确定模块，用于根据所述目标时间和不同预设时刻分别测得的所述电芯仿真电压确定所述目标电芯对应的所述能量；根据所述目标时间确定所述目标电芯对应的所述容量。
可选地，所述目标性能参数包括所述目标电芯上至少一个指定位置的目标电芯温度，所述仿真结果包括设置在不同预设位置的温度感应装置采集的电芯温度，所述指定位置包括任一所述预设位置；所述确定模块，用于将设置在所述指定位置的温度感应装置采集的所述电芯温度作为所述目标电芯温度。
可选地，所述目标电芯模型包括电化学模型和固体传热模型；所述电化学模型用于对所述目标电芯在充放电过程中的电化学性能进行仿真，所述固体传热模型用于对所述目标电芯在充放电过程中的温度传递进行仿真。
可选地，所述目标电芯模型通过以下方式预先建立：
获取预设模型参数，所述预设模型参数包括自定义参数、电芯设计参数、电化学参数以及热力学参数；建立所述目标电芯对应的有限元电化学几何模型和有限元固体传热几何模型，并根据用户的触发操作设置所述有限元电化学几何模型和所述有限元固体传热几何模型中每个区域的材料属性；获取用户自定义的模型输入参数和模型输出参数；根据所述预设模型参数、所述模型输入参数、所述模型输出参数、被设置材料属性的有限元电化学几何模型以及被设置材料属性的有限元固体传热几何模型建立所述目标电芯模型。
第三方面，提供一种非临时性计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现本申请第一方面所述方法的步骤。
第四方面，提供一种电子设备，包括：存储器，其上存储有计算机程序；处理器，用于执行所述存储器中的所述计算机程序，以实现本申请第一方面所述方法的步骤。
通过上述技术方案，获取预先设置的目标电芯模型，所述目标电芯模型用于对目标电芯在预设环境温度下的充放电性能进行仿真，所述目标电芯包括由至少两层涂布电极制成的电芯；通过所述目标电芯模型对所述目标电芯在所述预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电的过程进行仿真；根据仿真结果确定目标电芯的目标性能参数，所述目标性能参数包括在该预设环境温度下对所述目标电芯进行恒流倍率充电时的充电性能参数，或者包括在该预设环境温度下对所述目标电芯进行恒流倍率放电时的放电性能参数，这样，可以通过仿真的方式确定由至少两层涂布电极制成的电芯的充放电性能，从而可以根据仿真得到的该目标性能参数优化电芯设计，无需进行实测以及大量的实验优化，加快了研发进程，缩短了研发周期，减少了人工成本、时间成本与电芯制作成本，实现了电芯设计的快速产品迭代。
本申请的其他特征和优点将在随后的具体实施方式部分予以详细说明。
附图说明
附图是用来提供对本申请的进一步理解，并且构成说明书的一部分，与下面的具体实施 方式一起用于解释本申请，但并不构成对本申请的限制。在附图中：
图1是根据一示例性实施例示出的一种确定电芯充放电性能的方法的流程图；
图2是根据一示例性实施例示出的一种电化学模型和固体传热模型相互作用的关系示意图；
图3是根据一示例性实施例示出的一种一维电芯模型的结构示意图；
图4是根据一示例性实施例示出的一种二维电芯模型的结构示意图；
图5是根据一示例性实施例示出的一种三维电芯模型的结构示意图；
图6是根据一示例性实施例示出的一种建立目标电芯模型的方法的流程图；
图7是根据一示例性实施例示出的一种确定电芯充放电性能的装置的框图；
图8是根据一示例性实施例示出的一种电子设备的结构框图。
具体实施方式
以下结合附图对本申请的具体实施方式进行详细说明。应当理解的是，此处所描述的具体实施方式仅用于说明和解释本申请，并不用于限制本申请。
首先，对本申请的应用场景进行介绍，本申请主要应用于电芯设计研发过程中对经过多层涂布电极制成的目标电芯进行充放电性能测试的场景中，其中，该目标电芯是指至少由两层涂布电极制成的电芯，并且电芯的正极或者负极均可以由多个涂层制成。
为了确定由多层涂布电极制成的电芯的性能，现有技术中一般需要通过实测才能知道，并且需要大量的实验优化出多层结构的最佳厚度，但实验及电芯电化学性能实测过程需要大量的人力物力资源，且时间成本较高，进而影响电芯的迭代速度。
为了解决上述存在的问题，本申请提供一种电芯充放电性能的方法、装置、存储介质及电子设备，可以通过仿真的方式确定由至少两层涂布电极制成的电芯的充放电性能，从而可以根据仿真得到的该目标性能参数优化电芯设计，无需进行实测以及大量的实验优化，加快了研发进程，缩短了研发周期，减少了人工成本、时间成本与电芯制作成本，实现了电芯设计的快速产品迭代。
下面结合附图对本申请的具体实施方式进行详细说明。
图1是根据一示例性实施例示出的一种确定电芯充放电性能的方法的流程图，如图1所示，该方法包括以下步骤：
在步骤S101中，获取预先设置的目标电芯模型，该目标电芯模型用于对目标电芯在预设环境温度下的充放电性能进行仿真，该目标电芯包括由至少两层涂布电极制成的电芯。
其中，该目标电芯模型包括电化学模型和固体传热模型，该电化学模型用于对该目标电芯在充放电过程中的电化学性能进行仿真，该固体传热模型用于对该目标电芯在充放电过程中的温度传递进行仿真；该预设环境温度包括但不限于以下温度中的任一温度：-30℃、-10℃、0℃、25℃、45℃、60℃。
图2是根据一示例性实施例示出的一种电化学模型和固体传热模型相互作用的关系示意图，如图2所示，利用电化学模型可以计算由于电化学反应产生的热量，将热量耦合到固体传热模型，转化成电芯的温度变化，再将温度耦合到电化学模型，电化学模型中关于温度的敏感参数会随着温度的变化而变化，从而实现了电化学与固体传热的相互作用。
另外，该电化学模型可以包括有限元电化学几何模型，该固体传热模型可以包括有限元固体传热几何模型，在一种可能的实现方式中，用户(一般指电芯设计人员)可以通过运用 COMSOL Mutiphysics软件预先建立该目标电芯模型(具体模型建立过程会在下文中描述)。
在步骤S102中，通过该目标电芯模型对该目标电芯在该预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电的过程进行仿真。
其中，该第一预设电流可以为由电芯设计人员根据当前的测试需求任意设置的电芯充电电流或者电芯放电电流。
在一种可能的实现方式中，可以从多个预设倍率中选择一个预设倍率作为当前倍率，并将该当前倍率、该预设环境温度以及该第一预设电流作为该目标电芯模型中自定义参数的变量值，这样，用户在触发充电或者放电仿真指令后，终端可以在该COMSOL Mutiphysics软件中通过该目标电芯模型对该目标电芯在该预设环境温度下按照第一预设电流进行恒流倍率(即该当前倍率，如0.33C，1C，2C等)充电或者恒流倍率放电的过程进行仿真，进而得到模型输出的该目标电芯在该预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电时的目标时间(该目标时间包括充电截止时间或者放电截止时间)、电芯在不同预设时刻的电芯仿真电压、以及不同预设时刻电芯不同预设位置的电芯仿真温度等性能参数。
需要说明的是，基于上述的仿真方法，可以得到该目标电芯在多个预设环境温度、多个预设倍率下分别进行充放电仿真测试的结果，具体的，针对每个预设环境温度，可以仿真得到该预设环境温度下多个预设倍率分别对应的仿真曲线，从而确定出该目标电芯在同一环境温度下，采用不同的充放电倍率进行充放电时的目标性能参数，也可以确定出该目标电芯在同一充放电倍率下，对应不同的环境温度时的该目标性能参数。
在步骤S103中，根据仿真结果确定目标电芯的目标性能参数，该目标性能参数包括在该预设环境温度下对该目标电芯进行恒流倍率充电时的充电性能参数，或者包括在该预设环境温度下对该目标电芯进行恒流倍率放电时的放电性能参数。
其中，该目标性能参数可以包括但不限于以下参数中的一个或者多个参数：该目标电芯对应的容量、能量、该目标电芯上的锂离子浓度分布、电势分布以及该目标电芯上至少一个指定位置的目标电芯温度，该仿真结果可以包括但不限于以下结果中的一个或者多个：在多个预设时刻分别得到的该目标电芯不同位置的锂离子浓度、在多个预设时刻分别得到的不同位置的固相电势和不同位置的液相电势、对该目标电芯按照该第一预设电流进行恒流倍率充电或者恒流倍率放电的目标时间(该目标时间可以包括充电截止时间或者放电截止时间)、在不同预设时刻分别测得的电芯仿真电压以及设置在不同预设位置的温度感应装置采集的电芯温度，该温度感应装置可以包括温度探针。
需要说明的是，可以预先为该目标电芯模型内置底层的质量守恒方程以及电荷守恒方程，这样，在基于该目标电芯模型对该目标电芯的充电或者放电过程进行仿真时，可以通过该质量守恒方程和锂离子浓度的初始值由模型计算得到该目标电芯在不同预设时刻的该锂离子浓度，通过该电荷守恒方程和固相电势的初始值由模型计算得到目标电芯在不同预设时刻的固相电势，通过该电荷守恒方程和液相电势的初始值由模型计算得到目标电芯在不同预设时刻的液相电势；另外，还可以通过在目标电芯的不同位置定义温度探针，通过该温度探针观测到电芯不同位置的温度变化，该不同位置可以包括电芯的正极极柱、负极极柱、大面中心、极组中心等位置，此处仅是举例说明，本申请对此不作限定。
下面对上述不同的目标性能参数的确定过程分别进行说明。
在根据仿真结果确定目标电芯的锂离子浓度分布的过程中，可以根据多个该预设时刻分 别得到的该目标电芯不同位置的锂离子浓度确定该目标电芯在目标时刻的该锂离子浓度分布，其中，该目标时刻可以为多个该预设时刻中的任一时刻，也可以为用户指定的任意两个相邻的预设时刻之间的任一时刻。
若该目标时刻为多个该预设时刻中的任一时刻，一种实现方式可以是获取该目标时刻仿真得到的该目标电芯在不同位置的锂离子浓度，然后以该电化学几何模型中的负极集流体所在的位置为坐标原点，以与该坐标原点的距离为横坐标，以该锂离子浓度为纵坐标画图，得到该目标电芯的锂离子浓度分布，使得用户可以根据坐标图中展示的该锂离子浓度分布情况及时了解该目标电芯在充电或者放电过程中的锂离子移动情况，进而基于此进行电芯的优化设计。
若该目标时刻为任意两个相邻的预设时刻之间的任一时刻，一种实现方式中可以获取该相邻的两个预设时刻分别对应的该目标电芯在不同位置的锂离子浓度，然后针对每个位置的锂离子浓度，根据该位置上相邻的两个预设时刻分别仿真得到的该锂离子浓度，采用插值的方式计算出该目标时刻在该位置的锂离子浓度，之后可以按照与上一段中所述的类似的方式作图，得到在该目标时刻目标电芯在不同位置的锂离子浓度分布情况。
在根据仿真结果确定目标电芯的电势分布的过程中，可以根据多个该预设时刻分别得到的该目标电芯不同位置的该固相电势和不同位置的该液相电势确定该目标电芯在该目标时刻的该电势分布，电芯的电势等于固相电势与液相电势的差值，在本申请一种可能的实现方式中，也可以该目标电芯的预先设置位置(如负极集流体所在的位置)为坐标原点，以与该预先设置位置的距离为横轴，以不同位置上，每一位置的固相电势与液相电势的差值为纵轴作图，确定出该目标电芯的电势分布。
在根据仿真结果确定目标电芯的容量和能量的过程中，可以根据仿真结果中的该目标时间和不同预设时刻分别测得的该电芯仿真电压确定该目标电芯对应的该能量；根据该目标时间确定该目标电芯对应的该容量。
具体地，可以通过在该目标电芯模型中写入如下所示的全局常微分和微分代数方程计算得到该目标电芯的容量和能量：
Figure PCTCN2022093382-appb-000001
Figure PCTCN2022093382-appb-000002
其中，W表示该目标电芯的能量，Q表示目标电芯的容量，I表示恒流充放电电流(即该第一预设电流)，E cell表示目标电芯的电芯仿真电压。
另外，该目标性能参数还包括该目标电芯上至少一个指定位置的目标电芯温度，该指定位置可以为任一预设位置，在根据该仿真结果确定目标电芯的该目标电芯温度的过程中，可以将设置在该指定位置的温度感应装置采集的该电芯温度作为该目标电芯温度。
基于上述的实施步骤，在生产该目标电芯之前，可以根据对目标电芯在不同的预设环境温度下的恒流倍率充放电过程进行仿真，根据仿真结果得知此款目标电芯的性能，从而根据确定出的目标电芯的性能优化电芯设计，例如，该目标电芯的额定容量为84Ah(安时)，确定出的该目标电芯在进行恒流充电时的实际容量(或称之为实际发挥容量)为78Ah，此时可以通过适当降低极片厚度、增加导电剂、增加多孔电极的孔隙率、降低正极/负极活性材料的颗粒尺寸等措施优化电芯设计，使得优化后的目标电芯满足充放电的性能要求，从而加 快了研发进程，缩短了研发周期，减少了人工成本、时间成本与电芯制作成本，实现了电芯设计的快速产品迭代。
为使得在电芯设计研发阶段，用户可以及时获知目标电芯在充电过程或者放电过程中在不同维度上的锂离子浓度分布和电势分布，在本申请中，可以预先建立一维电芯模型、二维电芯模型以及三维电芯模型，也就是说，该目标电芯模型可以包括一维电芯模型、二维电芯模型或者三维电芯模型，其中，该一维电芯模型用于对该目标电芯预设厚度方向上的该锂离子浓度分布和该电势分布进行仿真；该二维电芯模型用于对该目标电芯的预设厚度方向和预设高度方向上的该锂离子浓度分布和该电势分布进行仿真；该三维电芯模型用于对该目标电芯在所有方向上的该锂离子浓度分布和该电势分布进行仿真。
示例地，图3是根据一示例性实施例示出的一种一维电芯模型的结构示意图，图4是根据一示例性实施例示出的一种二维电芯模型的结构示意图，图5是根据一示例性实施例示出的一种三维电芯模型的结构示意图，图3、图4和图5中所示的目标电芯的几何模型结构中，均以目标电芯的正极包括两个涂层为例，如图3所示，该一维电芯模型的几何结构从左到右依次为负极集流体、负极多孔电极、隔膜、正极多孔电极涂层二、正极多孔电极涂层一、正极集流体，这样，假定锂离子仅在电芯的预设厚度方向进行移动，基于该一维电芯模型可以获知该目标电芯在预设厚度方向(如图3所示的电芯几何结构中从左到右的方向)上的锂离子浓度分布和电势分布；如图4所示，该二维电芯模型即为对该一维电芯模型在预设高度方向上进行拉伸后得到的，这样，假定锂离子仅在电芯的预设厚度方向和预设高度方向进行移动，基于该二维电芯模型可以获知该目标电芯在预设厚度方向和预设高度方向上的锂离子浓度分布和电势分布；如图5所示，为该目标电芯的三维电芯模型，该三维电芯模型与实际的电芯结构相同，基于该三维电芯模型可以获知该目标电芯在所有方向上的锂离子浓度分布和电势分布，上述示例仅是举例说明，本申请对此不作限定。
需要说明的是，在根据该目标电芯模型仿真得到该目标电芯的充放电性能参数的过程中，用户触发目标按钮(如“开始仿真”或者“模型计算”等)后，模型即可自行运算，在运算结束后，可以调取相应地目标性能参数绘制可视化图谱，例如，可以绘制电压时间曲线、电压容量曲线、容量功率曲线、电芯温度时间曲线等，还可以绘制电芯充电或者放电过程中的固相或液相的锂离子浓度变化，基于三维电芯模型还可以调取温度分布云图，多孔电极的电势分布、电流密度分布及固相或液相的锂离子浓度分布云图等，从而可以更直观地向用户展示该目标电芯的充放电性能。
采用上述方法，可以通过仿真的方式确定由至少两层涂布电极制成的电芯的充放电性能，从而可以根据仿真得到的该目标性能参数优化电芯设计，无需进行实测以及大量的实验优化，加快了研发进程，缩短了研发周期，减少了人工成本、时间成本与电芯制作成本，实现了电芯设计的快速产品迭代。
另外，还可以根据不同维度的电芯模型确定电芯在不同维度方向上的锂离子浓度分布或者电势分布，从而为电芯的研发设计提供不同维度的参考数据。
图6是根据一示例性实施例示出的一种建立目标电芯模型的方法的流程图，如图6所示，该方法包括以下步骤：
在步骤S601中，获取预设模型参数，该预设模型参数包括自定义参数、电芯设计参数、电化学参数以及热力学参数。
其中，该自定义参数可以包括自定义的充放电倍率以及预设环境温度，该电芯设计参数 可以包括目标电芯的设计尺寸，该电化学参数可以包括如表1所示的参数以及目标电芯的多孔正极最大荷电状态、多孔正极最小荷电状态、多孔负极最大荷电状态、多孔负极最小荷电状态、初始电解质盐浓度、布鲁格曼系数等参数，热力学参数可以包括对流换热系数和正负极材料的平衡电位温度导数。
Figure PCTCN2022093382-appb-000003
表1
在一种可能的实现方式中，可以根据常用的电化学方程(如Fick第二定律、Butler-Volmer方程、Nernst-Plank方程)通过查阅文献或进行测试两种途径对目标电芯的电化学参数与电芯设计参数进行收集，得到该预设模型参数的初始值。
在步骤S602中，建立该目标电芯对应的有限元电化学几何模型和有限元固体传热几何模型，并根据用户的触发操作设置该有限元电化学几何模型和该有限元固体传热几何模型中每个区域的材料属性。
示例地，以正极由两个涂层制成的目标电芯为例，首先绘制六层结构的目标电芯的三维有限元电化学几何模型，如图5所示，该六层结构依次为正极集流体、正极多孔电极涂层1、 正极多孔电极涂层2、隔膜、负极多孔电极、负极集流体，然后赋予不同区域对应的区域属性和材料属性，其中区域属性可以包括正负极活性物质、电解液、隔膜、集流体，例如，可以在模型界面中的“区域属性”接口嵌入相应的区域属性，然后在“锂离子电池”接口中对应定义的几何区域中，选择相应的电解液材料域或者正负极活性材料。进一步地，还可以设置不同区域对应的材料属性，其中，正负极的材料属性包括电导率、固相扩散系数、平衡电位、平衡电位温度导数、参考浓度、电极最大及最小荷电状态等，由于隔膜实体的孔隙由电解液填充，因此需要给隔膜赋予电解液的属性，包括液相扩散系数、电解质电导率、传递数、活性相关性等，给正极或负极集流体赋予铝或者铜的属性，包括电导率，上述仅为举例说明，本申请对此不作限定。
下面以该目标电芯为正极由两个涂层制成的锂离子电池为例，对该目标电芯模型的预先建立过程进行说明。
首先，可以定义负极多孔电极的属性，根据用户的触发操作，获取用户设置的负极材料属性，并进一步确定多孔电极的温度、活性物质体积分数、孔隙率及有效电解质电导率与有效固相扩散系数，定义多孔电极反应温度、电极动力学表达式，定义颗粒插层的温度、初始锂离子浓度，选择锂离子浓度传递模型，在锂离子电池固相颗粒内，锂的扩散一般采用菲克第二定律定义，并且定义颗粒的粒径，另外，负极的活性材料包括但不限于：石墨，氧化亚硅，锂金属等。
其次，定义正极多孔电极涂层1和2的属性，该过程与定义负极多孔电极的属性的过程类似，在此不再赘述，其中，正极的涂层1与涂层2可以是同一种正极材料也可以是不同的正极材料，其中正极材料包含但不限于：钴酸锂，磷酸铁锂，锰酸锂，镍钴锰酸锂等，涂层1与涂层2的厚度及孔隙率可以根据实际情况设置，另外，考虑到两个涂层的活性材料的体积分数与孔隙率可能不一样，因此，在设计电芯时可以设置靠近集流体侧的涂层的孔隙率低于靠近隔膜侧的涂层的孔隙率。
之后，可以依次定义隔膜、正负极集流体、电接地与电极电流、初始电池电荷分布，并进行网格划分，以便根据划分后的有限个小的单元进行有限元计算。
在建立好上述的电化学几何模型后，可以建立该目标电芯的固体传热几何模型，根据不同仿真需求可以采用简化几何模型或者采用与实际电芯结构一致的真实几何模型，例如，简化几何模型可以是与实际电芯尺寸一致的长方体，也可以是简化部分结构件的简单几何模型，在此对简化几何模型与真实几何模型的模型结构不作限定，之后可以对该固体传热几何模型中各区域的材料属性(如恒压热容、密度、导热系数等)进行定义，具体地，可以由用户根据电芯各个结构材料种类分别导入相应材料的理论值或实验测值，之后对该固体传热模型进行模型设置，包括设置固体(除极组)的温度，并选择对应的材料属性，定义电芯所处的外部温度，定义不同方向的等效导热系数，定义热源，选择极组域为热源，将电化学模型中的产热耦合到固体传热模型，定义电芯与外部环境的热交换(或者称之为热通量)，通过定义对流换热系数(一般为10-20W*m-2*K-1)，并设置外部温度，即电芯所处的环境温度。
至此即建立了该目标电芯对应的电化学几何模型和固体传热几何模型。
在步骤S603中，获取用户自定义的模型输入参数和模型输出参数。
其中，该模型输入参数可以包括电流密度，该模型输出参数可以包括电池电压、电芯温度、满足仿真停止条件时的充电截止时间或者放电截止时间，该停止条件可以设置为电芯电压的上限或者下限，也可以设置为电芯的温度上限，本申请对此不作限定。
在步骤S604中，根据该预设模型参数、该模型输入参数、该模型输出参数、被设置材料属性的有限元电化学几何模型以及被设置材料属性的有限元固体传热几何模型建立该目标电芯模型。
至此即建立该目标电芯对应的该目标电芯模型，并且不同的预设环境温度对应不同的该目标电芯模型。
还需说明的是，在模型构建过程中，涂覆的层数和每层涂覆的活性材料的基本属性均可以根据实际情况灵活调整，其中基本属性包括：正负极材料的固相扩散系数、电导率、最大锂离子浓度、材料的平衡电位及平衡电位温度导数等。
图7是根据一示例性实施例示出的一种确定电芯充放电性能的装置，如图7所示，该装置包括：
获取模块701，用于获取预先设置的目标电芯模型，该目标电芯模型用于对目标电芯在预设环境温度下的充放电性能进行仿真，该目标电芯包括由至少两层涂布电极制成的电芯；
仿真模块702，用于通过该目标电芯模型对该目标电芯在该预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电的过程进行仿真；
确定模块703，用于根据仿真结果确定目标电芯的目标性能参数，该目标性能参数包括在该预设环境温度下对该目标电芯进行恒流倍率充电时的充电性能参数，或者包括在该预设环境温度下对该目标电芯进行恒流倍率放电时的放电性能参数。
可选地，该目标性能参数包括该目标电芯上的锂离子浓度分布和电势分布；该仿真结果包括在多个预设时刻分别得到的该目标电芯不同位置的锂离子浓度、不同位置的固相电势和不同位置的液相电势；
该确定模块703，用于根据多个该预设时刻分别得到的该目标电芯不同位置的锂离子浓度确定该目标电芯在目标时刻的该锂离子浓度分布；根据多个该预设时刻分别得到的该目标电芯不同位置的该固相电势和不同位置的该液相电势确定该目标电芯在该目标时刻的该电势分布。
可选地，该目标电芯模型包括一维电芯模型、二维电芯模型或者三维电芯模型，其中，该一维电芯模型用于对该目标电芯预设厚度方向上的该锂离子浓度分布和该电势分布进行仿真；该二维电芯模型用于对该目标电芯的预设厚度方向和预设高度方向上的该锂离子浓度分布和该电势分布进行仿真；该三维电芯模型用于对该目标电芯的预设厚度方向、预设高度方向以及预设长度方向上的该锂离子浓度分布和该电势分布进行仿真。
可选地，该目标性能参数包括该目标电芯对应的容量和能量，该仿真结果包括对该目标电芯按照该第一预设电流进行恒流倍率充电或者恒流倍率放电的目标时间和不同预设时刻分别测得的电芯仿真电压，该目标时间包括充电截止时间或者放电截止时间；
该确定模块703，用于根据该目标时间和不同预设时刻分别测得的该电芯仿真电压确定该目标电芯对应的该能量；根据该目标时间确定该目标电芯对应的该容量。
可选地，该目标性能参数包括该目标电芯上至少一个指定位置的目标电芯温度；该仿真结果包括设置在不同预设位置的温度感应装置采集的电芯温度；
该确定模块603，用于将设置在该指定位置的温度感应装置采集的该电芯温度作为该目标电芯温度。
可选地，该目标电芯模型包括电化学模型和固体传热模型；该电化学模型用于对该目标电芯在充放电过程中的电化学性能进行仿真，该固体传热模型用于对该目标电芯在充放电过 程中的温度传递进行仿真。
可选地，该目标电芯模型通过以下方式预先建立：
获取预设模型参数，该预设模型参数包括自定义参数、电芯设计参数、电化学参数以及热力学参数；建立该目标电芯对应的有限元电化学几何模型和有限元固体传热几何模型，并根据用户的触发操作设置该有限元电化学几何模型和该有限元固体传热几何模型中每个区域的材料属性；获取用户自定义的模型输入参数和模型输出参数；根据该预设模型参数、该模型输入参数、该模型输出参数、被设置材料属性的有限元电化学几何模型以及被设置材料属性的有限元固体传热几何模型建立该目标电芯模型。
关于上述实施例中的装置，其中各个模块执行操作的具体方式已经在有关该方法的实施例中进行了详细描述，此处将不做详细阐述说明。
采用上述装置，可以通过仿真的方式确定由至少两层涂布电极制成的电芯的充放电性能，从而可以根据仿真得到的该目标性能参数优化电芯设计，无需进行实测以及大量的实验优化，加快了研发进程，缩短了研发周期，减少了人工成本、时间成本与电芯制作成本，实现了电芯设计的快速产品迭代。
图8是根据一示例性实施例示出的一种电子设备800的框图。如图8所示，该电子设备800可以包括：处理器801，存储器802。该电子设备800还可以包括多媒体组件803，输入/输出(I/O)接口804，以及通信组件805中的一者或多者。
其中，处理器801用于控制该电子设备800的整体操作，以完成上述的确定电芯充放电性能的方法中的全部或部分步骤。存储器802用于存储各种类型的数据以支持在该电子设备800的操作，这些数据例如可以包括用于在该电子设备800上操作的任何应用程序或方法的指令，以及应用程序相关的数据，例如联系人数据、收发的消息、图片、音频、视频等等。该存储器802可以由任何类型的易失性或非易失性存储设备或者它们的组合实现，例如静态随机存取存储器(Static Random Access Memory，简称SRAM)，电可擦除可编程只读存储器(Electrically Erasable Programmable Read-Only Memory，简称EEPROM)，可擦除可编程只读存储器(Erasable Programmable Read-Only Memory，简称EPROM)，可编程只读存储器(Programmable Read-Only Memory，简称PROM)，只读存储器(Read-Only Memory，简称ROM)，磁存储器，快闪存储器，磁盘或光盘。多媒体组件803可以包括屏幕和音频组件。其中屏幕例如可以是触摸屏，音频组件用于输出和/或输入音频信号。例如，音频组件可以包括一个麦克风，麦克风用于接收外部音频信号。所接收的音频信号可以被进一步存储在存储器802或通过通信组件805发送。音频组件还包括至少一个扬声器，用于输出音频信号。I/O接口804为处理器801和其他接口模块之间提供接口，上述其他接口模块可以是键盘，鼠标，按钮等。这些按钮可以是虚拟按钮或者实体按钮。通信组件805用于该电子设备800与其他设备之间进行有线或无线通信。无线通信，例如Wi-Fi，蓝牙，近场通信(Near Field Communication，简称NFC)，2G、3G、4G、NB-IOT、eMTC、或其他5G等等，或它们中的一种或几种的组合，在此不做限定。因此相应的该通信组件805可以包括：Wi-Fi模块，蓝牙模块，NFC模块等等。
在一示例性实施例中，电子设备800可以被一个或多个应用专用集成电路(Application Specific Integrated Circuit，简称ASIC)、数字信号处理器(Digital Signal Processor，简称DSP)、数字信号处理设备(Digital Signal Processing Device，简称DSPD)、可编程逻辑器件(Programmable Logic Device，简称PLD)、现场可编程门阵列(Field Programmable Gate  Array，简称FPGA)、控制器、微控制器、微处理器或其他电子元件实现，用于执行上述的确定电芯充放电性能的方法。
在另一示例性实施例中，还提供了一种包括程序指令的计算机可读存储介质，该程序指令被处理器执行时实现上述的确定电芯充放电性能的方法的步骤。例如，该计算机可读存储介质可以为上述包括程序指令的存储器802，上述程序指令可由电子设备800的处理器801执行以完成上述的确定电芯充放电性能的方法。
在另一示例性实施例中，还提供一种计算机程序产品，该计算机程序产品包含能够由可编程的装置执行的计算机程序，该计算机程序具有当由该可编程的装置执行时用于执行上述的确定电芯充放电性能的方法的代码部分。
以上结合附图详细描述了本申请的可选实施方式，但是，本申请并不限于上述实施方式中的具体细节，在本申请的技术构思范围内，可以对本申请的技术方案进行多种简单变型，这些简单变型均属于本申请的保护范围。
另外需要说明的是，在上述具体实施方式中所描述的各个具体技术特征，在不矛盾的情况下，可以通过任何合适的方式进行组合，为了避免不必要的重复，本申请对各种可能的组合方式不再另行说明。
此外，本申请的各种不同的实施方式之间也可以进行任意组合，只要其不违背本申请的思想，其同样应当视为本申请所公开的内容。

Claims (10)

  1. 一种确定电芯充放电性能的方法，其特征在于，所述方法包括：
    获取预先设置的目标电芯模型，所述目标电芯模型用于对目标电芯在预设环境温度下的充放电性能进行仿真，所述目标电芯包括由至少两层涂布电极制成的电芯；
    通过所述目标电芯模型对所述目标电芯在所述预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电的过程进行仿真；
    根据仿真结果确定目标电芯的目标性能参数，所述目标性能参数包括在该预设环境温度下对所述目标电芯进行恒流倍率充电时的充电性能参数，或者包括在该预设环境温度下对所述目标电芯进行恒流倍率放电时的放电性能参数。
  2. 根据权利要求1所述的方法，其特征在于，所述目标性能参数包括所述目标电芯上的锂离子浓度分布和电势分布；所述仿真结果包括在多个预设时刻分别得到的所述目标电芯不同位置的锂离子浓度、不同位置的固相电势和不同位置的液相电势；
    所述根据仿真结果确定目标电芯的目标性能参数包括：
    根据多个所述预设时刻分别得到的所述目标电芯不同位置的锂离子浓度确定所述目标电芯在目标时刻的所述锂离子浓度分布；
    根据多个所述预设时刻分别得到的所述目标电芯不同位置的所述固相电势和不同位置的所述液相电势确定所述目标电芯在所述目标时刻的所述电势分布。
  3. 根据权利要求2所述的方法，其特征在于，所述目标电芯模型包括一维电芯模型、二维电芯模型或者三维电芯模型，其中，所述一维电芯模型用于对所述目标电芯预设厚度方向上的所述锂离子浓度分布和所述电势分布进行仿真；所述二维电芯模型用于对所述目标电芯的预设厚度方向和预设高度方向上的所述锂离子浓度分布和所述电势分布进行仿真；所述三维电芯模型用于对所述目标电芯的预设厚度方向、预设高度方向以及预设长度方向上的所述锂离子浓度分布和所述电势分布进行仿真。
  4. 根据权利要求1所述的方法，其特征在于，所述目标性能参数包括所述目标电芯对应的容量和能量，所述仿真结果包括对所述目标电芯按照所述第一预设电流进行恒流倍率充电或者恒流倍率放电的目标时间和不同预设时刻分别测得的电芯仿真电压，所述目标时间包括充电截止时间或者放电截止时间；
    所述根据仿真结果确定目标电芯的目标性能参数包括：
    根据所述目标时间和不同预设时刻分别测得的所述电芯仿真电压确定所述目标电芯对应的所述能量；
    根据所述目标时间确定所述目标电芯对应的所述容量。
  5. 根据权利要求1所述的方法，其特征在于，所述目标性能参数包括所述目标电芯上至少一个指定位置的目标电芯温度，所述仿真结果包括设置在不同预设位置的温度感应装置采集的电芯温度，所述指定位置包括任一所述预设位置；
    所述根据仿真结果确定目标电芯的目标性能参数包括：
    将设置在所述指定位置的温度感应装置采集的所述电芯温度作为所述目标电芯温度。
  6. 根据权利要求1所述的方法，其特征在于，所述目标电芯模型包括电化学模型和固体传热模型；所述电化学模型用于对所述目标电芯在充放电过程中的电化学性能进行仿真，所述固体传热模型用于对所述目标电芯在充放电过程中的温度传递进行仿真。
  7. 根据权利要求1-6任一项所述的方法，其特征在于，所述目标电芯模型通过以下方式预先建立：
    获取预设模型参数，所述预设模型参数包括自定义参数、电芯设计参数、电化学参数以及热力学参数；
    建立所述目标电芯对应的有限元电化学几何模型和有限元固体传热几何模型，并根据用户的触发操作设置所述有限元电化学几何模型和所述有限元固体传热几何模型中每个区域的材料属性；
    获取用户自定义的模型输入参数和模型输出参数；
    根据所述预设模型参数、所述模型输入参数、所述模型输出参数、被设置材料属性的有限元电化学几何模型以及被设置材料属性的有限元固体传热几何模型建立所述目标电芯模型。
  8. 一种确定电芯充放电性能的装置，其特征在于，所述装置包括：
    获取模块，用于获取预先设置的目标电芯模型，所述目标电芯模型用于对目标电芯在预设环境温度下的充放电性能进行仿真，所述目标电芯包括由至少两层涂布电极制成的电芯；
    仿真模块，用于通过所述目标电芯模型对所述目标电芯在所述预设环境温度下按照第一预设电流进行恒流倍率充电或者恒流倍率放电的过程进行仿真；
    确定模块，用于根据仿真结果确定目标电芯的目标性能参数，所述目标性能参数包括在该预设环境温度下对所述目标电芯进行恒流倍率充电时的充电性能参数，或者包括在该预设环境温度下对所述目标电芯进行恒流倍率放电时的放电性能参数。
  9. 一种非临时性计算机可读存储介质，其上存储有计算机程序，其特征在于，该程序被处理器执行时实现权利要求1-7中任一项所述方法的步骤。
  10. 一种电子设备，其特征在于，包括：
    存储器，其上存储有计算机程序；
    处理器，用于执行所述存储器中的所述计算机程序，以实现权利要求1-7中任一项所述方法的步骤。
PCT/CN2022/093382 2021-05-17 2022-05-17 确定电芯充放电性能的方法、装置、存储介质及电子设备 WO2022242653A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202110535290.X 2021-05-17
CN202110535290.XA CN113253131B (zh) 2021-05-17 2021-05-17 确定电芯充放电性能的方法、装置、存储介质及电子设备

Publications (1)

Publication Number Publication Date
WO2022242653A1 true WO2022242653A1 (zh) 2022-11-24

Family

ID=77182240

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2022/093382 WO2022242653A1 (zh) 2021-05-17 2022-05-17 确定电芯充放电性能的方法、装置、存储介质及电子设备

Country Status (2)

Country Link
CN (1) CN113253131B (zh)
WO (1) WO2022242653A1 (zh)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116227310A (zh) * 2023-05-10 2023-06-06 深圳市华宝新能源股份有限公司 电池模组电芯温度的快速推测方法、装置、设备和介质
CN116227295A (zh) * 2023-03-10 2023-06-06 宁夏宝丰昱能科技有限公司 电池包有限元建模方法、装置、计算机设备及存储介质
CN117973238A (zh) * 2024-04-02 2024-05-03 深圳和润达科技有限公司 一种电芯化成流程充放电时间的智能预测方法及装置
CN118381163A (zh) * 2024-06-20 2024-07-23 西安奇点能源股份有限公司 一种储能柜电量异常分级故障检测方法及系统
CN118410686A (zh) * 2024-07-03 2024-07-30 华硼中子科技(杭州)有限公司 靶体温升的数值模拟方法及装置、存储介质与终端

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113253131B (zh) * 2021-05-17 2022-08-30 蜂巢能源科技股份有限公司 确定电芯充放电性能的方法、装置、存储介质及电子设备
CN113821942B (zh) * 2021-11-23 2022-03-15 苏州易来科得科技有限公司 对电化学装置内部微观结构进行标记的方法和装置

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2293091A2 (fr) * 2009-09-02 2011-03-09 IFP Energies nouvelles Méthode pour simuler le comportement thérmique d'un système électrochimique
CN104035048A (zh) * 2014-06-20 2014-09-10 上海出入境检验检疫局工业品与原材料检测技术中心 一种锂离子电池过充安全性能的热电检测方法及其装置
CN108169683A (zh) * 2017-12-15 2018-06-15 浙江隆劲电池科技有限公司 多层叠片结构锂离子电池的内部分布特征仿真分析方法
CN108761341A (zh) * 2018-06-01 2018-11-06 哈尔滨工业大学 一种锂离子电池电化学模型参数获取方法
CN109738806A (zh) * 2018-12-29 2019-05-10 蜂巢能源科技有限公司 模拟电池产热率的方法、装置、介质
CN110165314A (zh) * 2019-04-30 2019-08-23 蜂巢能源科技有限公司 电池电芯性能参数获取方法及获取装置
CN110208704A (zh) * 2019-04-29 2019-09-06 北京航空航天大学 一种基于电压滞后效应的锂电池建模方法和系统
CN111506977A (zh) * 2019-12-11 2020-08-07 安徽贵博新能科技有限公司 一种动力电池建模方法
CN113253131A (zh) * 2021-05-17 2021-08-13 蜂巢能源科技有限公司 确定电芯充放电性能的方法、装置、存储介质及电子设备

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7498772B2 (en) * 2006-04-06 2009-03-03 International Truck Intellectual Property Company, Llc Method and system of modeling energy flow for vehicle battery diagnostic monitoring
CN107729607A (zh) * 2017-09-12 2018-02-23 合肥国轩高科动力能源有限公司 一种磷酸铁锂大电芯充放电温度分布测试方法
CN108009397B (zh) * 2017-12-01 2020-01-17 中南大学 预测锂离子电池材料电化学性能的仿真方法、装置及设备
CN108509762A (zh) * 2018-03-29 2018-09-07 北京普莱德新能源电池科技有限公司 一种电池的物理化学变化性能参数模拟方法及装置
CN110232201A (zh) * 2019-04-02 2019-09-13 中南大学 一种多参数协同作用的电池设计方法

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2293091A2 (fr) * 2009-09-02 2011-03-09 IFP Energies nouvelles Méthode pour simuler le comportement thérmique d'un système électrochimique
CN104035048A (zh) * 2014-06-20 2014-09-10 上海出入境检验检疫局工业品与原材料检测技术中心 一种锂离子电池过充安全性能的热电检测方法及其装置
CN108169683A (zh) * 2017-12-15 2018-06-15 浙江隆劲电池科技有限公司 多层叠片结构锂离子电池的内部分布特征仿真分析方法
CN108761341A (zh) * 2018-06-01 2018-11-06 哈尔滨工业大学 一种锂离子电池电化学模型参数获取方法
CN109738806A (zh) * 2018-12-29 2019-05-10 蜂巢能源科技有限公司 模拟电池产热率的方法、装置、介质
CN110208704A (zh) * 2019-04-29 2019-09-06 北京航空航天大学 一种基于电压滞后效应的锂电池建模方法和系统
CN110165314A (zh) * 2019-04-30 2019-08-23 蜂巢能源科技有限公司 电池电芯性能参数获取方法及获取装置
CN111506977A (zh) * 2019-12-11 2020-08-07 安徽贵博新能科技有限公司 一种动力电池建模方法
CN113253131A (zh) * 2021-05-17 2021-08-13 蜂巢能源科技有限公司 确定电芯充放电性能的方法、装置、存储介质及电子设备

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116227295A (zh) * 2023-03-10 2023-06-06 宁夏宝丰昱能科技有限公司 电池包有限元建模方法、装置、计算机设备及存储介质
CN116227295B (zh) * 2023-03-10 2023-11-28 宁夏宝丰昱能科技有限公司 电池包有限元建模方法、装置、计算机设备及存储介质
CN116227310A (zh) * 2023-05-10 2023-06-06 深圳市华宝新能源股份有限公司 电池模组电芯温度的快速推测方法、装置、设备和介质
CN116227310B (zh) * 2023-05-10 2023-08-22 深圳市华宝新能源股份有限公司 电池模组电芯温度的快速推测方法、装置、设备和介质
CN117973238A (zh) * 2024-04-02 2024-05-03 深圳和润达科技有限公司 一种电芯化成流程充放电时间的智能预测方法及装置
CN117973238B (zh) * 2024-04-02 2024-06-04 深圳和润达科技有限公司 一种电芯化成流程充放电时间的智能预测方法及装置
CN118381163A (zh) * 2024-06-20 2024-07-23 西安奇点能源股份有限公司 一种储能柜电量异常分级故障检测方法及系统
CN118410686A (zh) * 2024-07-03 2024-07-30 华硼中子科技(杭州)有限公司 靶体温升的数值模拟方法及装置、存储介质与终端

Also Published As

Publication number Publication date
CN113253131A (zh) 2021-08-13
CN113253131B (zh) 2022-08-30

Similar Documents

Publication Publication Date Title
WO2022242653A1 (zh) 确定电芯充放电性能的方法、装置、存储介质及电子设备
CN113420475B (zh) 三电极锂离子电池锂沉积的预测方法、装置、设备及介质
Mei et al. Numerical study on tab dimension optimization of lithium-ion battery from the thermal safety perspective
CN112949101B (zh) 电池脉冲充放电最大电流的获取方法、装置、设备及介质
Jung et al. Multi-dimensional modeling of large-scale lithium-ion batteries
Jiang et al. A microscopic investigation of ion and electron transport in lithium-ion battery porous electrodes using the lattice Boltzmann method
Jiang et al. Lattice Boltzmann simulation of ion and electron transport during the discharge process in a randomly reconstructed porous electrode of a lithium-ion battery
CN108509762A (zh) 一种电池的物理化学变化性能参数模拟方法及装置
CN109614754B (zh) 一种锂离子电池三维简化模型的仿真方法
CN113051852B (zh) 电芯结构件接触电阻的获取方法、装置、设备及存储介质
CN109738806B (zh) 模拟电池产热率的方法、装置、介质
Zadin et al. Designing the 3D-microbattery geometry using the level-set method
Lee et al. Study on microstructures of electrodes in lithium-ion batteries using variational multi-scale enrichment
CN112883610B (zh) 叠片式锂离子电池的电化学-热-结构耦合多尺度建模方法
An et al. A comparison of model prediction from P2D and particle packing with experiment
CN113011065B (zh) 预测电芯充放电性能的方法、装置、存储介质及电子设备
CN115828685A (zh) 基于切比雪夫谱方法的锂电池温度仿真方法、装置及介质
Taralova et al. Derivation and numerical validation of a homogenized isothermal Li-ion battery model
CN118351985A (zh) 电池三维电化学模型构建方法与计算方法
CN116068408B (zh) 电池老化数据确定方法、装置、计算机设备和存储介质
JP2015050062A (ja) リチウムイオン二次電池の設計方法
KR101956266B1 (ko) 이차 전지 특성 시뮬레이션 방법 및 이를 지원하는 전자 장치
Li et al. Control-oriented implementation and model order reduction of a lithium-ion battery electrochemical model
Spotnitz et al. Geometry-resolved electro-chemistry model of Li-ion batteries
CN117744415B (zh) 电池的容量衰减仿真方法、装置、计算机设备和存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 22803973

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: 2301007530

Country of ref document: TH

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 22803973

Country of ref document: EP

Kind code of ref document: A1