CN117744415A

CN117744415A - Method and device for simulating capacity attenuation of battery, computer equipment and storage medium

Info

Publication number: CN117744415A
Application number: CN202410187072.5A
Authority: CN
Inventors: 张帆; 贾鹏飞; 焦君宇; 冯兆斌
Original assignee: Shenzhen Yigen Technology Co ltd
Current assignee: Shenzhen Yigen Technology Co ltd
Priority date: 2024-02-20
Filing date: 2024-02-20
Publication date: 2024-03-22

Abstract

The application relates to a capacity fade simulation method, a device, a computer device and a storage medium of a battery, wherein the method comprises the following steps: acquiring simulation working condition data of a lithium ion battery; inputting the simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery separation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data by the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery; the capacity fade simulation model is constructed based on lithium ion battery lithium evolution reaction areas at different lithium evolution levels. The method can accurately simulate the capacity attenuation of the lithium ion battery caused by lithium separation.

Description

Method and device for simulating capacity attenuation of battery, computer equipment and storage medium

Technical Field

The present invention relates to the field of battery simulation technologies, and in particular, to a method and apparatus for simulating capacity attenuation of a battery, a computer device, and a storage medium.

Background

With the rapid development of lithium ion batteries, lithium ion batteries are widely applied to the fields of portable electronic devices, electric vehicles, energy storage systems and the like.

As the number of charge and discharge cycles of a lithium ion battery increases, the available capacity of the lithium ion battery gradually decreases. Among them, lithium precipitation is one of the main causes of capacity deterioration of lithium ion batteries. Therefore, in order to improve the usability of the lithium ion battery, capacity fading of the lithium ion battery caused by lithium precipitation in the cyclic use process can be simulated, so that the lithium ion battery is optimized according to the capacity fading result.

However, the capacity fade of the lithium ion battery due to lithium precipitation cannot be accurately simulated in the related art.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a method, apparatus, computer device, and storage medium for simulating capacity fade of a battery, which can accurately simulate the capacity fade of a lithium ion battery due to lithium precipitation.

In a first aspect, the present application provides a method for simulating capacity fade of a battery, including:

acquiring simulation working condition data of a lithium ion battery;

inputting the simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery separation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data by the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery; the capacity fade simulation model is constructed based on lithium ion battery lithium evolution reaction areas at different lithium evolution levels.

In one embodiment, the capacity fade simulation model includes an electrochemical model and an output model; simulating the lithium-ion battery lithium-ion analysis reaction area change condition in the cyclic charge-discharge process according to the simulation working condition data through a capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium-ion battery, wherein the method comprises the following steps:

for any charge and discharge process, simulating the lithium precipitation reaction area of the lithium ion battery in the charge and discharge process through an electrochemical model according to the simulation working condition data, and determining the available capacity of the electrochemical model output after the simulation of the charge and discharge process;

and inputting each available capacity into an output model to obtain a capacity attenuation curve of the lithium ion battery.

In one embodiment, the electrochemical model includes a lithium-ion reaction area calculation equation; simulating the lithium precipitation reaction area of the lithium ion battery in the charge-discharge process through an electrochemical model according to the simulation working condition data, and determining the available capacity of the lithium ion battery output after the charge-discharge process, wherein the method comprises the following steps:

obtaining the current volume fraction of electrolyte in the lithium ion battery and the parameters of the model to be calibrated through simulation working condition data;

substituting the model parameters to be calibrated and the current volume fraction into a lithium-ion reaction area calculation equation, determining the lithium separation reaction area of a lithium ion battery;

The available capacity is determined based on the lithium evolution reaction area.

In one embodiment, obtaining the model parameters to be calibrated includes:

obtaining a film thickness variation value of a negative electrode of the lithium ion battery due to lithium precipitation;

if the film thickness variation value is smaller than the preset critical film thickness, determining a preset first calibration parameter value as a model parameter to be calibrated;

if the film thickness variation value is larger than or equal to the critical film thickness and the current volume fraction is larger than the preset critical volume fraction, determining a preset second calibration parameter value as a model parameter to be calibrated;

and if the film thickness variation value is larger than or equal to the critical film thickness and the current volume fraction is smaller than or equal to the critical volume fraction, determining a preset third calibration parameter value as a model parameter to be calibrated.

In one embodiment, determining the available capacity from the lithium-ion reaction area includes:

determining lithium-precipitation reaction current density according to the lithium-precipitation reaction area;

determining the capacity loss of the lithium ion battery according to the lithium separation reaction current density;

the available capacity is determined based on the initial available capacity and the capacity loss amount of the lithium ion battery.

In one embodiment, the method further comprises:

Inputting the simulation working condition data into a capacity attenuation simulation model to obtain a model parameter value to be calibrated of the lithium ion battery in the cyclic charge and discharge process;

and determining the lithium precipitation degree of the lithium ion battery in the cyclic charge and discharge process according to the parameter values of the models to be calibrated.

In one embodiment, the process of constructing the capacity fade simulation model includes:

performing charge-discharge cycle test on the historical lithium ion battery to obtain an actual capacity attenuation curve of the historical lithium ion battery;

performing capacity attenuation simulation on the historical lithium ion battery according to the historical simulation working condition data, the multiple groups of model parameters to be calibrated and the initial capacity attenuation simulation model to be calibrated to obtain a simulation capacity attenuation curve of the historical lithium ion battery under each group of model parameters to be calibrated;

determining model parameters to be calibrated of an initial capacity attenuation simulation model according to the actual capacity attenuation curve and each simulation capacity attenuation curve;

and correcting the lithium precipitation reaction area parameter in the initial capacity attenuation simulation model according to the model parameter to be calibrated, and determining the capacity attenuation simulation model.

In a second aspect, the present application further provides a capacity fade simulation device for a battery, including:

The data acquisition module is used for acquiring simulation working condition data of the lithium ion battery;

the simulation module is used for inputting simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery separation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data through the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery; the capacity fade simulation model is constructed based on lithium ion battery lithium evolution reaction areas at different lithium evolution levels.

In a third aspect, embodiments of the present application provide a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of the method provided by any of the embodiments of the first aspect described above when the computer program is executed.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method provided by any of the embodiments of the first aspect described above.

In a fifth aspect, embodiments of the present application also provide a computer program product comprising a computer program which, when executed by a processor, implements the steps of the method provided by any of the embodiments of the first aspect described above.

The capacity attenuation simulation method, the device, the computer equipment and the storage medium of the battery acquire simulation working condition data of the lithium ion battery; inputting the simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery separation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data by the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery; the capacity fade simulation model is constructed based on lithium ion battery lithium evolution reaction areas at different lithium evolution levels. According to the method, the capacity simulation attenuation model is constructed in advance by considering the relevant characteristics of lithium-ion battery lithium-ion reaction area change caused by surface morphology change under different lithium-ion battery lithium-ion degree, and the capacity simulation attenuation model is used for simulating the lithium-ion battery lithium-ion reaction area change condition in the cyclic charge and discharge process so as to determine the capacity attenuation curve of the lithium ion battery, so that the accuracy of capacity attenuation of the simulated lithium ion battery caused by lithium-ion battery lithium-ion is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person having ordinary skill in the art.

FIG. 1 is an internal block diagram of a computer device in one embodiment;

FIG. 2 is a flow chart of a method of simulating capacity fade of a battery in one embodiment;

FIG. 3 is a schematic diagram of a capacity fade curve in one embodiment;

FIG. 4 is a flow chart of a method of simulating capacity fade of a battery in another embodiment;

FIG. 5 is a flow chart of a method of simulating capacity fade of a battery in another embodiment;

FIG. 6 is a flow chart of a method of simulating capacity fade of a battery in another embodiment;

fig. 7 is a schematic diagram of a morphology change of a negative electrode of a lithium ion battery during a charge and discharge process according to an embodiment;

FIG. 8 is a flow chart of a method of simulating capacity fade of a battery in another embodiment;

FIG. 9 is a flow chart of a method of simulating capacity fade of a battery in another embodiment;

FIG. 10 is a flow chart of a method of simulating capacity fade of a battery in another embodiment;

FIG. 11 is a schematic diagram of capacity fade curves corresponding to different model parameters to be calibrated in one embodiment;

FIG. 12 is a flow chart of a method of simulating capacity fade of a battery in another embodiment;

fig. 13 is a block diagram showing the structure of a capacity fade simulation device of a battery in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The capacity attenuation simulation method of the battery, provided by the embodiment of the application, can be applied to computer equipment. The computer device may be a server, the internal structure of which may be as shown in FIG. 1. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store capacity fade simulation data for the battery. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a method of simulating capacity fade of a battery.

It will be appreciated by those skilled in the art that the structure shown in fig. 1 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

The lithium ion battery has the advantages of high energy density, no memory effect, low self-discharge rate, long service life, recyclability and the like. This has led to the widespread use of lithium ion batteries in the fields of portable electronic devices, electric vehicles, energy storage systems, and the like. The lithium ion battery has capacity attenuation due to lithium precipitation, growth of a solid electrolyte interface (Solid Electrolyte Interphase, SEI) film, loss of active substances and the like, and the simulation based on a physical model can reflect the attenuation mechanism of the lithium ion battery. In practical use of lithium ion batteries, lithium precipitation dominant decay mainly occurs in the following two cases: (1) Unreasonable charging modes, such as low-temperature and high-rate charging; (2) end of decay of the battery under normal use.

However, in the related art, when the capacity attenuation of the lithium ion battery is simulated through the physical model, the difference of lithium precipitation behaviors at different stages of the capacity attenuation is not distinguished, so that the physical model lacks versatility in the actual use process, and the simulation result has larger deviation from the actual result; the change of the reaction area of lithium precipitation caused by the surface appearance change during the lithium precipitation is not considered.

Therefore, the capacity fade simulation performed on the lithium ion battery in the related art has a problem of low accuracy.

Based on the above, the embodiment of the application provides a capacity attenuation simulation method of a battery, which constructs a capacity simulation attenuation model by considering the relevant characteristics of the lithium ion battery that the deposited lithium of the lithium ion battery reacts with electrolyte due to the change of the surface morphology under different lithium precipitation degrees, simulates the capacity attenuation of the lithium ion battery through the capacity simulation attenuation model, and determines the capacity attenuation curve of the lithium ion battery, thereby improving the accuracy of the capacity attenuation of the simulated lithium ion battery due to lithium precipitation.

In an exemplary embodiment, as shown in fig. 2, there is provided a capacity fade simulation method of a battery, which is described by taking an example that the method is applied to the computer device in fig. 1, including the steps of:

s201, simulation working condition data of the lithium ion battery are obtained.

The simulation working condition data can comprise the charging rate, the discharging rate and the ambient temperature during charging and discharging of the lithium ion battery. For example, the charge rate and the discharge rate may be 1C, and the ambient temperature may be 25 ℃.

It should be noted that, parameters included in the simulation working condition data and corresponding parameter values may be set according to actual conditions.

S202, inputting simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery separation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data through the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery; the capacity fade simulation model is constructed based on lithium ion battery lithium evolution reaction areas at different lithium evolution levels.

The lithium precipitation reaction, which is an undesirable side reaction in the lithium ion battery, can lead to a decrease in the recyclable lithium in the lithium ion battery and an increase in the internal resistance of the battery, thereby leading to capacity fade of the lithium ion battery.

Because the lithium ion battery has different lithium separation reaction areas under different lithium separation degrees, a capacity attenuation simulation model can be constructed according to the principle so as to simulate the lithium separation reaction area change condition of the lithium ion battery in the cyclic charge and discharge process, so that the capacity attenuation curve of the obtained lithium ion battery is more accurate; the lithium-separating reaction area may represent the area of the lithium ion battery where deposited lithium reacts with the electrolyte per unit volume.

The capacity fading curve may be a change condition of capacity retention rate of the lithium ion battery along with cycle number of the lithium ion battery; as shown in fig. 3, fig. 3 is a schematic diagram of a capacity fading curve of the lithium ion battery, wherein the abscissa is the cycle number and the ordinate is the capacity retention rate; the cycle number indicates the number of cycles of charge and discharge of the lithium ion battery.

And inputting the simulation working condition data into a capacity attenuation simulation model, and simulating the lithium precipitation reaction area change condition of the lithium ion battery in the cyclic charge and discharge process according to the simulation working condition data by the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery output by the capacity attenuation curve.

Specifically, the lithium-separating reaction area change condition may include a change value of the lithium-separating reaction area of each simulated charge-discharge process compared with the lithium-separating reaction area of the last simulated charge-discharge process; the change of the available capacity in each simulated charge and discharge process can be determined according to the change value, and the capacity fading curve can be determined according to the change of the available capacity in each simulated charge and discharge process.

Optionally, the simulation working condition data can be continuously input into the capacity attenuation simulation model for multiple times, the capacity attenuation curve analyzes the simulation working condition data input each time, and the real-time lithium analysis reaction area of the lithium ion battery is simulated to obtain the available capacity of the lithium ion battery output each time by the capacity attenuation simulation model; and then drawing a capacity attenuation curve of the lithium ion battery according to the available capacity of the lithium ion battery output every time.

After the charge and discharge process of the lithium ion battery is simulated by the capacity fading simulation model, parameters representing the state of the lithium ion battery in the capacity fading simulation model are changed, that is, the capacity fading simulation model is updated, so that the charge and discharge process of the lithium ion battery is simulated by the capacity fading simulation model after the last update every time the charge and discharge process of the lithium ion battery is simulated by the capacity fading simulation model.

According to the capacity attenuation simulation method of the battery, simulation working condition data of the lithium ion battery are obtained; inputting the simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery separation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data by the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery; the capacity fade simulation model is constructed based on lithium ion battery lithium evolution reaction areas at different lithium evolution levels. According to the method, the capacity simulation attenuation model is constructed in advance by considering the relevant characteristics of lithium-ion battery lithium-ion reaction area change caused by surface morphology change under different lithium-ion battery lithium-ion degree, and the capacity simulation attenuation model is used for simulating the lithium-ion battery lithium-ion reaction area change condition in the cyclic charge and discharge process so as to determine the capacity attenuation curve of the lithium ion battery, so that the accuracy of capacity attenuation of the simulated lithium ion battery caused by lithium-ion battery lithium-ion is improved.

In one exemplary embodiment, as shown in FIG. 4, the capacity fade simulation model includes an electrochemical model and an output model; simulating the lithium-ion battery capacity attenuation curve by a capacity attenuation simulation model according to simulation working condition data, wherein the lithium-ion battery capacity attenuation curve is obtained by simulating the lithium-ion battery reaction area change condition in the cyclic charge-discharge process, and the method comprises the following steps:

s401, simulating the lithium precipitation reaction area of the lithium ion battery in the charge and discharge process according to the simulation working condition data through the electrochemical model aiming at any charge and discharge process, and determining the available capacity of the electrochemical model output after the simulation charge and discharge process.

The electrochemical model is constructed based on lithium-ion battery lithium-separating reaction areas under different lithium-separating degrees.

And carrying out iterative solution on the electrochemical model through the simulation working condition data to obtain the available capacity of the lithium ion battery in each iterative process. Each time an iteration is carried out through the electrochemical model, the simulation of the charging and discharging process of the lithium ion battery can be represented; the simulation working condition data can comprise simulation working condition data in each charge-discharge cycle process, the simulation working condition data comprises charge-discharge multiplying power and temperature in each charge-discharge cycle process, and the simulation working condition data in each charge-discharge cycle process can be the same or different.

Specifically, according to any charge-discharge process (iteration), substituting simulation working condition data into an electrochemical model, solving the electrochemical model, simulating a lithium ion battery reaction area in the charge-discharge process, determining the output available capacity of the electrochemical model according to the lithium reaction area, and simultaneously, correspondingly updating parameters in the electrochemical model along with the operation of the electrochemical model, and simulating the next charge-discharge process of the updated electrochemical model through the simulation working condition data until the electrochemical model reaches preset iteration conditions; the iteration condition may be the number of iterations, or the available capacity of the output reaches a preset capacity threshold.

The capacity attenuation simulation model comprises a capacity calculation model; the capacity attenuation simulation model is constructed based on different lithium-ion battery lithium-ion reaction areas under different lithium-ion battery lithium-ion degree, namely the capacity attenuation simulation model comprises different lithium-ion reaction areas corresponding to different lithium-ion degrees; in each charge and discharge simulation of the capacity attenuation simulation model to the lithium ion battery, determining the lithium precipitation reaction area of the lithium ion battery in real time according to the real-time lithium precipitation degree of the lithium ion battery, inputting the lithium precipitation reaction area into a capacity calculation model in the capacity attenuation simulation model, and solving the capacity calculation model according to the lithium precipitation reaction area to obtain the available capacity of the lithium ion battery.

And S402, inputting each available capacity into an output model to obtain a capacity attenuation curve of the lithium ion battery.

The capacity fading curve may be a curve in which the capacity retention rate of the battery varies with the number of charge and discharge cycles; therefore, after each available capacity after the simulated cyclic charge and discharge process is obtained, the ratio between each available capacity and the initial rated capacity of the lithium ion battery can be determined as the capacity retention rate of each charge and discharge process; and then drawing a capacity attenuation curve of the lithium ion battery according to the capacity retention rate and the corresponding charge and discharge cycle times.

Alternatively, the capacity fading curve may be a curve of the available capacity of the battery changing with the cycle number of charge and discharge cycles, so after each available capacity after the simulated cyclic charge and discharge process is obtained, the capacity fading curve of the lithium ion battery may be drawn according to each available capacity and the corresponding charge and discharge cycle number.

In the capacity attenuation simulation method of the battery, for any charge and discharge process, the lithium-ion battery is simulated according to simulation working condition data through an electrochemical model to determine the available capacity of the electrochemical model output after the simulation of the charge and discharge process; and inputting each available capacity into an output model to obtain a capacity attenuation curve of the lithium ion battery. In the method, the electrochemical model is constructed based on the lithium-ion battery lithium-ion reaction areas under different lithium-ion-separation degrees, and the lithium-ion battery lithium-ion reaction areas in each charge and discharge process are simulated through the electrochemical model, so that the available capacity of the lithium-ion battery after each charge and discharge process is finished can be accurately determined, and the accuracy of the capacity fading curve is improved.

In one exemplary embodiment, as shown in FIG. 5, the electrochemical model includes a lithium-ion reaction area calculation equation; simulating the lithium precipitation reaction area of the lithium ion battery in the charge-discharge process through an electrochemical model according to the simulation working condition data, and determining the available capacity of the lithium ion battery output after the charge-discharge process, wherein the method comprises the following steps:

s501, obtaining the current volume fraction of the electrolyte in the lithium ion battery and the model parameters to be calibrated through simulation working condition data.

The electrochemical model also comprises a Newman model and a lithium-ion secondary reaction model; wherein the Newman model is also called Pseudo-2-Dimensional (P2D) model; the model parameters to be calibrated can be parameters to be calibrated in the electrochemical model.

The new man model mainly comprises five main equations, namely a charge conservation equation in a solid-liquid phase of the lithium ion battery, a mass conservation equation in the solid-liquid phase and an electrochemical reaction rate equation on a solid-liquid phase interface, wherein as shown in formulas (1) - (5), the formula (1) is the charge conservation equation in the solid phase, the formula (2) is the charge conservation equation in the liquid phase, the formula (3) is the mass conservation equation of lithium ions in the solid phase, the formula (4) is the mass conservation equation of lithium ions in the liquid phase, and the formula (5) is a total heat collection model in the lithium ion battery.

（1）

（2）

（3）

（4）

（5）

Wherein,for the solid phase effective ionic conductivity of lithium ion battery, < >>For solid phase potential, ++>Is a local current density and also represents the electrochemical reaction rate of the particle surface; />Effective ion conductivity of electrolyte in lithium ion battery, < >>Is of liquid phase potential->Effective ionic conductivity for active material particles in lithium ion batteries, +.>For the liquid phase concentration of lithium ions in the electrolyte, t is time, +>Is the migration number of lithium ions, < >>Is the volume fraction of the electrolyte, +.>Effective lithium ion diffusion coefficient of lithium ion battery electrolyte, +.>Is Faraday constant; />Is lithium ion in active material particleDiffusion coefficient in grains, < >>Is active particle radius>Solid phase lithium ion concentration; />For the mass of lithium ion batteries, +.>Is the specific heat capacity of the lithium ion battery +.>For the temperature of the lithium ion battery, +.>Exothermic for side reactions during thermal runaway +.>For the heat exchange coefficient of the lithium ion battery and the air fluid, < >>Is the cross-sectional area of the lithium ion battery, < >>Is ambient temperature.

Wherein the electrochemical model further comprises boundary conditions:wherein n represents a normal unit vector of the electrode surface, < ->Representing the externally applied charge-discharge current, and determining by the charge-discharge multiplying power; wherein, charge rate=charge current for 1 hour/rated capacity, discharge rate=discharge current for 1 hour/rated capacity.

The basic chemical reactions that occur at the negative electrode during the charging phase of a lithium ion battery include: normal embeddingLithium reaction, lithium precipitation reaction, etc., are generated when lithium ion battery undergoes lithium precipitation reactionAnd (5) depositing. Can be expressed by the formula (6) and the formula (7).

（6）

（7）

In addition, during the operation of the lithium ion battery, an SEI film is also generated as shown in formula (8).

（8）

Thus, the lithium-eluting side reaction model may include a current density formula, as shown in formula (9) -formula (19). In the case of lithium-precipitation side reaction and SEI film side reaction, the local current density of the lithium ion battery should include a main reaction current density, an SEI film side reaction current density, and a lithium-precipitation side reaction current density, as shown in formula (9).

（9）

Wherein,for the main reaction current density, +.>Is SEI film side reaction current density, +.>The current density is the lithium secondary reaction.

Main reaction current density of lithium ion batteryThe Butler-Volmer (BV) equation is satisfied as shown in equation (10).

（10）

Wherein,indicating the reaction area>Exchange current density for intercalation and deintercalation of lithium ions,>transfer coefficient for electrochemical reaction of anode in lithium ion battery, < > >Transfer coefficient for electrochemical reaction of cathode in lithium ion battery, < >>And->0.5 can be taken; />Is a gas constant->And (3) representing the overpotential of the electrode surface in the lithium ion battery, representing the polarization degree of the electrode, and satisfying the formula (11).

（11）

Wherein,membrane resistance of a film produced for side reactions in lithium ion batteries, < >>The balance potential of the active material of the lithium ion battery can be also regarded as the open circuit voltage of the active material of the positive electrode and the negative electrode.

SEI film side reaction current densityIs composed of the following formula.

（12）

Wherein,is kinetic rate constant, +>For the concentration of graphite surface EC>Represents the SEI side reaction cathode transfer coefficient, +.>A reaction equilibrium potential is formed for the SEI.

（13）

Wherein,for the diffusion coefficient of EC in SEI, +.>，/>For the initial diffusion rate of EC in the electrolyte, < >>Is the thickness of the surface film.

Lithium secondary reaction current densityIs composed of the following formula.

（14）

Wherein,exchange current density for depositing lithium, +.>Cathode transfer coefficient of lithium-evolution side reaction.

The material balance of the SEI film and the metallic lithium can be expressed by equation (15) and equation (16), respectively.

（15）

（16）

Wherein,is the molar concentration of SEI per unit volume of the electrode, +.>Is the molar concentration of Li per unit volume of the electrode, ">Indicating the proportion of lithium plating to form SEI.

And, SEI and metallic lithium together constitute the surface film that covers the negative electrode particle, assuming that the thickness of the surface film is uniform, the quantity of SEI film and solid lithium can be converted into equivalent surface film thickness, defined as the ratio of the total volume of SEI film and metallic lithium to the reaction area of lithium precipitation, as shown in formula (17).

（17）

Wherein,is SEI film molar mass, +.>Is the molar mass of Li>For SEI density->Is Li density.

In conjunction with the above formula (17), the surface film resistance may be determined only by the SEI film, as shown in formula (18).

（18)

Wherein,for the volume fraction of SEI film, +.>Is the ionic conductivity of the SEI film.

In addition, if the capacity fade simulation model considers a decrease in anode porosity due to surface film growth, this can be related to a change in anode porosity to an increase in surface film thickness by equation (19).

（19）

Based on the equation of the electrochemical model, the simulation working condition data can be substituted into the equations to obtain the current volume fraction of the electrolyte.

The parameters of the model to be calibrated may be fixed values set in advance, or may be determined according to the current lithium precipitation degree of the lithium ion battery, where the lithium precipitation degree may be represented by the film thickness of the negative electrode increased by side reactions such as lithium precipitation and the current volume fraction of the electrolyte, so in an exemplary embodiment, as shown in fig. 6, the parameters of the model to be calibrated are obtained, including the following steps:

S601, obtaining a film thickness variation value of a negative electrode of the lithium ion battery due to lithium precipitation.

Substituting the simulation working condition data into the electrochemical model to directly obtain the film thickness variation value of the negative electrode of the lithium ion battery caused by lithium precipitation; wherein the film thickness variation value may be a difference between an initial thickness of the surface film and a current thickness of the surface film.

S602, if the film thickness variation value is smaller than the preset critical film thickness, determining a preset first calibration parameter value as a model parameter to be calibrated.

S603, if the film thickness variation value is greater than or equal to the critical film thickness and the current volume fraction is greater than the preset critical volume fraction, determining a preset second calibration parameter value as a model parameter to be calibrated.

S604, if the film thickness variation value is greater than or equal to the critical film thickness and the current volume fraction is less than or equal to the critical volume fraction, determining a preset third calibration parameter value as a model parameter to be calibrated.

The model parameters to be calibrated can be realized through a piecewise function, and different parameter combinations are used for reflecting the morphology evolution in the lithium precipitation process, so that the model parameters to be calibrated can be defined through a formula (20).

（20）

Wherein,for the model parameters to be calibrated, < >>For the first calibration parameter value, < >>For the second calibration parameter value,/->For the third calibration parameter value, +.>For the film thickness variation value, +.>Critical film thickness +.>For the current volume fraction +.>Is the critical volume fraction; wherein the definition of the above parameters can be determined experimentally, and +.>May be 0, & gt>Can be a fixed value less than 0, < + >>May be a fixed value greater than 0; />Critical film thickness expressed as lithium dendrite formation, < + >>Critical volume fraction for electrolyte to plug pores. Wherein the specific values of the first model parameter value to be calibrated, the second model parameter value to be calibrated and the third model parameter value to be calibrated can be obtainedThe test results and the simulation results can be compared and determined according to historical experience.

The above equation (20) defines a dynamic evolution process: the early-stage small amount of lithium precipitation does not affect the reaction area, the middle-stage lithium dendrite is generated, the reaction area is increased along with the lithium precipitation, the later-stage hole blocking reaction area is reduced along with the lithium precipitation, as shown in fig. 7, fig. 7 can be a diagram showing the morphology change of a lithium ion battery when the negative electrode is subjected to lithium precipitation in the charging and discharging process, fig. 7 (a) shows a fresh lithium ion battery without lithium precipitation, fig. 7 (b) shows a uniform small amount of lithium precipitation of the lithium ion battery, the lithium precipitation mode of the lithium precipitation reaction area is not changed, and the diagram corresponds to the lithium precipitation mode in the formula (20) The method comprises the steps of carrying out a first treatment on the surface of the Fig. 7 (c) shows a lithium-ion battery in a lithium-dendrite formation mode, in which the lithium dendrite growth causes the lithium-precipitation reaction area to become larger as the lithium precipitation proceeds, corresponding to the formula (20)The method comprises the steps of carrying out a first treatment on the surface of the Fig. 7 (d) shows a lithium-ion battery separator and a negative electrode in a lithium-ion battery separator with a near-hole blocking mode, the reaction area of lithium precipitation becomes smaller as lithium precipitation proceeds, corresponding to +.>. It should be noted that the lithium ion battery may correspond to one or more of the cases in fig. 7 during the charge-discharge cycle.

In the embodiment, the film thickness variation value of the negative electrode caused by lithium precipitation of the lithium ion battery and the current volume fraction of the electrolyte are used for defining the model parameters to be calibrated in a segmented mode, and the corresponding model parameters to be calibrated are determined according to the actual lithium precipitation degree of the lithium ion battery, so that the accuracy of the lithium precipitation reaction area is improved.

S502, substituting the model parameters to be calibrated and the current volume fraction into a lithium analysis reaction area calculation equation, and determining the lithium precipitation reaction area of the lithium ion battery.

First, it should be noted that, for the formula(10) Reaction area in (a)Can be expressed as the reaction area of the deintercalation reaction, namely the deintercalation reaction area; reaction area in formula (12) >The reaction area of the SEI reaction, i.e., the SEI reaction area, may be represented; reaction area in equation (14)>The reaction area of the lithium precipitation reaction, i.e., the lithium precipitation reaction area, may be represented.

The lithium analysis reaction area calculation equation may be shown in formula (21).

（21）

Wherein,for the initial reaction area per unit volume +.>For the current electrolyte volume fraction +.>For the initial electrolyte volume fraction +.>And the model parameters to be calibrated are obtained.

Therefore, the model parameters to be calibrated and the current volume fraction can be substituted into the formula (21), and the lithium ion battery lithium precipitation reaction area can be calculated.

In the embodiment of the application, the reaction areas of different reactions, that is, the deintercalation reaction area, the SEI reaction area and the lithium analysis reaction area are the same, so that the lithium analysis reaction area is the deintercalation reaction area and the SEI reaction area, and therefore, the deintercalation reaction area and the SEI reaction area are obtained by substituting the model parameters to be calibrated and the current volume fraction into the formula (21).

The lithium intercalation reaction area, the SEI reaction area and the lithium precipitation reaction area may be the same or different.

S503, determining the available capacity according to the lithium precipitation reaction area.

In the lithium ion battery, under normal conditions, the reaction in which lithium ions participate should be a lithium intercalation reaction, namely, reversible intercalation and intercalation of lithium ions occur at the negative electrode, as shown in formula (6), and the lithium separation reaction is used as an unexpected side reaction in the lithium ion battery, which can lead to reduction of recyclable lithium in the lithium ion battery and increase of internal resistance of the battery, thereby bringing about capacity attenuation of the lithium battery; while the lithium-separating reaction area may be the area where deposited lithium reacts with the electrolyte, which results in loss of recyclable lithium, and thus the available capacity of the lithium-ion battery may be determined according to the lithium-separating reaction area.

And depositing lithium and electrolyte to react under the lithium-separating reaction area, so as to consume recyclable lithium in the lithium ion battery, wherein the available capacity of the lithium ion battery is determined by the quantity of lithium ions in the lithium ion battery, therefore, the lithium loss amount in the lithium ion battery can be determined according to the lithium-separating reaction area, and further, the lost capacity in the lithium ion battery can be determined according to the lithium loss amount, thereby determining the available capacity of the lithium ion battery according to the rated capacity and the lost capacity of the lithium ion battery.

In one exemplary embodiment, as shown in fig. 8, the available capacity is determined according to the lithium-precipitation reaction area, comprising the steps of:

S801, determining lithium precipitation reaction current density according to the lithium precipitation reaction area.

Can be used for separating lithium reaction areaSubstituting into formula (14) to obtain lithium precipitation reaction current density +.>。

It should be noted that, the values of other parameters in the formula (14) may be obtained by other formulas, or may be fixed values set in advance.

S802, determining the capacity loss of the lithium ion battery according to the lithium precipitation reaction current density.

The molar concentration of Li per unit volume in the lithium ion battery can be determined according to formula (16), and then the capacity loss amount of the lithium ion battery can be calculated according to formula (22).

The capacity loss amount in the present embodiment may represent the capacity loss amount of the lithium ion battery due to lithium precipitation. Therefore, the capacity loss amount of the lithium ion battery can be calculated as shown in the formula (22).

（22）

Wherein,is the capacity loss of lithium ion battery, +.>For the volume of the whole negative electrode inside the lithium ion battery, < >>Is the loss of lithium.

S803, determining the available capacity according to the initial available capacity and the capacity loss amount of the lithium ion battery.

The available capacity of the lithium ion battery may be a difference between an initial available capacity of the lithium ion battery and a capacity loss amount.

However, since capacity loss of the lithium ion battery due to the SEI film may occur due to the growth of the SEI film in the lithium ion battery, the amount of capacity loss due to the growth of the SEI film may be considered when calculating the available capacity of the lithium ion battery:。

thus, the usable capacity of the lithium ion battery can be calculated by the formula (23).

（23）

Wherein,for the available capacity of a lithium ion battery, +.>Is the initial available capacity of the lithium ion battery.

It should be noted that the initial available capacity of the lithium ion battery may be the available capacity of the lithium ion battery after the last charge-discharge cycle is completed.

According to the capacity fading simulation method for the battery, provided by the embodiment of the application, the current volume fraction of the electrolyte in the lithium ion battery and the model parameters to be calibrated are obtained through simulation working condition data, the model parameters to be calibrated and the current volume fraction are substituted into a lithium analysis reaction area calculation equation, the lithium analysis reaction area of the lithium ion battery is determined, and then the available capacity is determined according to the lithium analysis reaction area. According to the method, the current volume fraction of the electrolyte and the model parameters to be calibrated which are simulated by the electrochemical model are determined through simulation working condition data, then the lithium-ion battery real-time data update the lithium-ion reaction area in the simulated charge and discharge process, and the available capacity of the lithium-ion battery is determined according to the lithium-ion quantity in the lithium-ion battery because the lithium-ion reaction area can reflect the consumption of recyclable lithium in the lithium-ion battery, so that the available capacity of the lithium-ion battery can be accurately determined according to the lithium-ion battery real-time updated lithium-ion reaction area.

The model parameters to be calibrated can show the morphology evolution of the lithium ion battery in the lithium precipitation process, so that the lithium precipitation degree of the lithium ion battery in the cyclic charge-discharge process can be determined through the model parameters to be calibrated used in the simulation process when the charge-discharge cyclic simulation of the lithium ion battery is carried out through the capacity attenuation simulation model. In one exemplary embodiment, as shown in fig. 9, the embodiment includes the steps of:

and S901, inputting the simulation working condition data into a capacity attenuation simulation model to obtain a model parameter value to be calibrated of the lithium ion battery in the cyclic charge and discharge process.

The simulation working condition data are input into the capacity attenuation simulation model, the change condition of the lithium ion battery in the lithium precipitation reaction area in the cyclic charge and discharge process is simulated through the capacity attenuation simulation model according to the simulation working condition data, and the capacity attenuation simulation model can be controlled to output the parameter value of the model to be calibrated, which is used in the cyclic charge and discharge process of the simulated lithium ion battery, in the process of obtaining the capacity attenuation curve of the lithium ion battery.

S902, determining the lithium precipitation degree of the lithium ion battery in the cyclic charge and discharge process according to the parameter values of the models to be calibrated.

The lithium-ion battery lithium-ion separation degree in the cyclic charge and discharge process can comprise the initial, middle and late lithium-ion battery lithium-ion separation degree in the cyclic charge and discharge process.

The model parameter values to be calibrated can be model parameter values to be calibrated at all times, so that the model parameter values to be calibrated at all times can be obtained according to the model parameter values to be calibrated at all times, determining the lithium-ion battery lithium-ion separation degree at each moment in the cyclic charge and discharge process, and dividing the integral lithium-ion battery lithium-ion separation degree according to the lithium-ion battery lithium-ion separation degree at each moment.

For example, the number of times of cyclic charge and discharge includes 500 times, the model parameter to be calibrated in the previous 100 times of cyclic charge and discharge of the lithium ion battery is 0, the model parameter to be calibrated in the cycle charge and discharge process of 100 to 500 times is-3, the lithium ion battery is represented to have uniform and small lithium precipitation at the initial stage of cyclic charge and discharge, and lithium dendrite is generated at the middle and late stages of cyclic charge and discharge.

It should be noted that, the initial stage, the middle stage and the late stage of the cyclic charge-discharge process of the lithium ion battery can be defined according to actual requirements.

In the capacity attenuation simulation method of the battery, simulation working condition data are input into a capacity attenuation simulation model to obtain model parameter values to be calibrated in the cyclic charge and discharge process of the lithium ion battery, and then the lithium precipitation degree of the lithium ion battery in the cyclic charge and discharge process is determined according to the model parameter values to be calibrated. In the method, the to-be-calibrated model parameters can reflect the attenuation behaviors of the lithium ion battery in different stages and paths due to lithium precipitation, so that the lithium precipitation degree of the lithium ion battery in the cyclic charge and discharge process can be determined according to the to-be-calibrated model parameters in the simulation process.

The foregoing embodiments describe the application process of the capacity fade simulation model, and the following describes the construction process of the capacity fade simulation model by means of an embodiment, and in an exemplary embodiment, as shown in fig. 10, the construction process of the capacity fade simulation model includes the following steps:

s1001, performing charge-discharge cycle test on the historical lithium ion battery to obtain an actual capacity attenuation curve of the historical lithium ion battery.

The historical lithium ion battery is a lithium ion battery to be subjected to actual test; and carrying out charge-discharge cycle test on the historical lithium ion battery according to the historical test working condition data to obtain an actual capacity attenuation curve of the historical lithium ion battery.

The historical test operating condition data may include charge-discharge strategies, such as at what temperatures and at what charge-discharge rates to charge and discharge cycles.

Specifically, after the historical lithium ion battery is subjected to a charge-discharge test according to a preset charge-discharge strategy, the available capacity of the historical lithium ion battery is determined, so that the available capacity of the historical lithium ion battery after each charge-discharge is sequentially collected; and determining an actual capacity attenuation curve of the historical lithium ion battery according to the available capacity of the historical lithium ion battery after each charge and discharge.

It should be noted that, the historical lithium ion battery can be subjected to multiple charge-discharge cycle tests at multiple different temperatures and multiple different charge-discharge multiplying powers, so as to obtain multiple different actual capacity attenuation curves of the historical lithium ion battery.

S1002, performing capacity attenuation simulation on the historical lithium ion battery according to the historical simulation working condition data, the multiple groups of model parameters to be calibrated and the initial capacity attenuation simulation model to be calibrated, and obtaining a simulation capacity attenuation curve of the historical lithium ion battery under each group of model parameters to be calibrated.

The historical simulation working condition data can be the same as the charge-discharge strategy used for the charge-discharge cycle test of the historical lithium ion battery.

The initial capacity-fading simulation model may be a capacity-fading simulation model construction in which the value of the model parameter to be calibrated is not determined, i.e., the value of the model parameter to be calibrated in the initial capacity-fading simulation model is not determined; the multiple groups of model parameters to be calibrated are preset multiple groups of model parameter values to be calibrated.

And inputting the historical simulation working condition data and the model parameters to be calibrated into an initial capacity simulation model aiming at any group of model parameters to be calibrated, and simulating the lithium analysis reaction area change condition of the historical lithium ion battery in the cyclic charge and discharge process according to the historical simulation working condition data through the initial capacity attenuation simulation model to obtain a simulation capacity attenuation curve of the historical lithium ion battery.

It should be noted that, the manner of acquiring the simulated capacity fading curve of the historical lithium ion battery in the embodiment of the present application is similar to the manner of acquiring the capacity fading curve of the lithium ion battery in the above embodiment, and the embodiment of the present application is not repeated here.

Based on the mode, the simulation capacity attenuation curve under each group of model parameters to be calibrated can be obtained.

FIG. 11 is a schematic diagram of capacity fading curves corresponding to different model parameters to be calibrated, as shown in FIG. 11; the influence of the model parameters to be calibrated on the simulation capacity attenuation curves can be determined through the graph 11, the three simulation capacity attenuation curves use the model parameters to be calibrated which are defined in a segmented mode, wherein the model parameters to be calibrated at the cyclic charge and discharge end of the simulation capacity attenuation curve 1 are smaller than 0, and the growth of lithium dendrites occurs, and the graph corresponds to the graph (c) in the graph 7; the simulated capacity fading curves 2 and 3 correspond to the (b) and (d) graphs in fig. 7 using values for which the model parameters to be calibrated are equal to 0 and for which the model parameters to be calibrated are greater than 0, respectively.

S1003, determining model parameters to be calibrated of an initial capacity attenuation simulation model according to the actual capacity attenuation curve and each simulation capacity attenuation curve.

The actual capacity attenuation curve and each simulated capacity attenuation curve can be compared, and the model parameters to be calibrated corresponding to the simulated capacity attenuation curve consistent with the actual capacity attenuation curve are determined as the model parameters to be calibrated of the initial capacity attenuation simulation model.

If the simulated capacity attenuation curves consistent with the actual capacity attenuation curves do not exist in the simulated capacity attenuation curves, resetting a plurality of groups of model parameters to be calibrated, and continuously obtaining the simulated capacity attenuation curves of the historical lithium ion battery under the new model parameters to be calibrated until the simulated capacity attenuation curves consistent with the actual capacity attenuation curves exist.

Optionally, the actual capacity fading curve may include actual capacity fading curves under various test condition data, and the simulated capacity fading curve under each set of model parameters to be calibrated also includes simulated capacity fading curves under various historical simulation condition data; the plurality of test working condition data corresponds to the plurality of historical simulation working condition data one by one; then the actual capacity fade curve is consistent with the simulated capacity fade curve, indicating that the capacity fade curve is consistent under each operating mode data.

S1004, correcting the lithium precipitation reaction area parameter in the initial capacity attenuation simulation model according to the model parameter to be calibrated, and determining the capacity attenuation simulation model.

And determining the obtained parameters of the model to be calibrated as the parameter values of the model to be calibrated corresponding to the lithium reaction area parameter in the initial capacity attenuation simulation model, namely the first calibration parameter value, the second calibration parameter value and the third calibration parameter value in the formula (20), so as to determine the initial capacity attenuation simulation model after the assignment of the parameters of the model to be calibrated as the capacity attenuation simulation model.

In the capacity fading simulation method for the battery provided by the embodiment of the application, charge-discharge cycle test is conducted on the historical lithium ion battery to obtain an actual capacity fading curve of the historical lithium ion battery, capacity fading simulation is conducted on the historical lithium ion battery according to historical simulation working condition data, multiple groups of model parameters to be calibrated and initial capacity fading simulation models to be calibrated to obtain simulated capacity fading curves of the historical lithium ion battery under each group of model parameters to be calibrated, then the model parameters to be calibrated of the initial capacity fading simulation models are determined according to the actual capacity fading curves and the simulated capacity fading curves, finally lithium analysis reaction area parameters in the initial capacity fading simulation models are corrected according to the model parameters to be calibrated, and the capacity fading simulation models are determined. According to the method, the parameters of the model to be calibrated are determined through comparison of simulation data and experimental data, rated modeling of the lithium precipitation reaction area in the lithium precipitation process is achieved, so that the capacity attenuation simulation model is determined, the accuracy of the capacity attenuation simulation model in simulating the lithium precipitation reaction area change of the lithium ion battery in the cyclic charge and discharge process is improved, and the accuracy of capacity attenuation simulation of the lithium ion battery is improved.

In an exemplary embodiment, there is further provided a capacity fade simulation method of a battery, as shown in fig. 12, including the steps of:

and S1201, constructing a lithium analysis reaction area calculation equation and a plurality of groups of model parameters to be calibrated according to historical experience.

And determining a lithium-precipitation reaction area calculation equation according to the current volume fraction parameter of the electrolyte, the initial volume fraction of the electrolyte, the initial lithium-precipitation reaction area per unit volume, the model parameters to be calibrated and the lithium-precipitation reaction area parameter. Each group of model parameters to be calibrated comprises model parameter values to be calibrated defined in a segmented mode.

S1202, determining an initial capacity attenuation simulation model according to a lithium precipitation reaction area calculation equation.

The initial capacity attenuation simulation model is obtained by improving a basic electrochemical model of the lithium ion battery based on a lithium-ion reaction area calculation equation, and the specific surface area parameter in the basic electrochemical model is corrected to be a lithium-ion reaction area parameter.

S1203, inputting historical simulation working condition data and model parameters to be calibrated into an initial capacity attenuation simulation model according to any group of preset model parameters to be calibrated, and simulating the lithium precipitation reaction area change condition of the historical lithium ion battery in the cyclic charge and discharge process through the initial capacity attenuation simulation model according to the historical simulation working condition data and the model parameters to be calibrated to obtain a simulation capacity attenuation curve of the lithium ion battery.

And S1204, performing charge-discharge cycle test on the historical lithium ion battery through the same historical simulation working condition data to obtain an actual capacity attenuation curve of the historical lithium ion battery.

S1205, comparing the actual capacity attenuation curve with each simulated capacity attenuation curve, and determining the model parameters to be calibrated of the initial capacity attenuation simulation model.

S1206, instantiating the model parameters to be calibrated of the initial capacity attenuation simulation model according to the model parameters to be calibrated of the initial capacity attenuation simulation model, and determining the capacity attenuation simulation model.

S1207, inputting the simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery separation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data through the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a capacity fade simulation device of the battery for realizing the capacity fade simulation method of the battery. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the capacity fade simulation device for one or more batteries provided below may be referred to the limitation of the capacity fade simulation method for a battery hereinabove, and will not be repeated herein.

In one exemplary embodiment, as shown in fig. 13, there is provided a capacity fade simulation device 1300 of a battery, comprising: a data acquisition module 1301 and a simulation module 1302, wherein:

the data acquisition module 1301 is configured to acquire simulation working condition data of the lithium ion battery;

the simulation module 1302 is configured to input simulation working condition data into a preset capacity attenuation simulation model, simulate a lithium ion battery according to the simulation working condition data by using the capacity attenuation simulation model, and obtain a capacity attenuation curve of the lithium ion battery; the capacity fade simulation model is constructed based on lithium ion battery lithium evolution reaction areas at different lithium evolution levels.

In one exemplary embodiment, the capacity fade simulation model includes an electrochemical model and an output model; the simulation module 1302 includes:

the simulation unit is used for simulating the lithium precipitation reaction area of the lithium ion battery in the charge-discharge process according to the simulation working condition data through the electrochemical model aiming at any charge-discharge process, and determining the available capacity of the electrochemical model output after the simulation of the charge-discharge process;

and the output unit is used for inputting each available capacity into the output model to obtain a capacity attenuation curve of the lithium ion battery.

In one exemplary embodiment, the electrochemical model includes a lithium-ion reaction area calculation equation; the simulation unit includes:

the first acquisition subunit is used for acquiring the current volume fraction of the electrolyte in the lithium ion battery and the model parameters to be calibrated through the simulation working condition data;

a calculating subunit for substituting the model parameters to be calibrated and the current volume fraction into a lithium-analysis reaction area calculating equation, determining the lithium separation reaction area of a lithium ion battery;

and the first determination subunit is used for determining the available capacity according to the lithium precipitation reaction area.

In one exemplary embodiment, the first acquisition subunit comprises:

a second obtaining subunit, configured to obtain a film thickness variation value of the negative electrode of the lithium ion battery due to lithium precipitation;

The second determining subunit is used for determining a preset first calibration parameter value as a model parameter to be calibrated if the film thickness variation value is smaller than a preset critical film thickness;

a third determining subunit, configured to determine a preset second calibration parameter value as a model parameter to be calibrated if the film thickness variation value is greater than or equal to the critical film thickness and the current volume fraction is greater than a preset critical volume fraction;

and the fourth determination subunit is used for determining a preset third calibration parameter value as a model parameter to be calibrated if the film thickness variation value is larger than or equal to the critical film thickness and the current volume fraction is smaller than or equal to the critical volume fraction.

In one embodiment, the first determining subunit comprises:

a fifth determining subunit, configured to determine a lithium-precipitation reaction current density according to the lithium-precipitation reaction area;

a sixth determining subunit, configured to determine a lithium loss amount of the lithium ion battery according to the lithium analysis reaction current density;

a seventh determination subunit, configured to determine a capacity loss amount of the lithium ion battery according to the lithium loss amount;

and an eighth determination subunit, configured to determine the available capacity according to the initial available capacity and the capacity loss amount of the lithium ion battery.

In an exemplary embodiment, the apparatus 1300 further comprises:

the first determining module is used for inputting the simulation working condition data into the capacity attenuation simulation model to obtain a model parameter value to be calibrated of the lithium ion battery in the cyclic charge and discharge process;

and the second determining module is used for determining the lithium precipitation degree of the lithium ion battery in the cyclic charge and discharge process according to the parameter values of the models to be calibrated.

In an exemplary embodiment, the apparatus 1300 further comprises:

the testing module is used for carrying out charge-discharge cycle testing on the historical lithium ion battery to obtain an actual capacity attenuation curve of the historical lithium ion battery;

the simulation module is used for carrying out capacity attenuation simulation on the historical lithium ion battery according to the historical simulation working condition data, the multiple groups of model parameters to be calibrated and the initial capacity attenuation simulation model to be calibrated, so as to obtain a simulation capacity attenuation curve of the historical lithium ion battery under each group of model parameters to be calibrated;

the third determining module is used for determining the model parameters to be calibrated of the initial capacity attenuation simulation model according to the actual capacity attenuation curve and each simulation capacity attenuation curve;

and the fourth determining module is used for correcting the lithium precipitation reaction area parameter in the initial capacity attenuation simulation model according to the model parameter to be calibrated to determine the capacity attenuation simulation model.

The respective modules in the capacity fade simulation device of the battery described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.

The implementation principle and technical effect of each step implemented by the processor in this embodiment are similar to those of the above-mentioned capacity attenuation simulation method of the battery, and are not described herein again.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.

The steps of the computer program implemented when executed by the processor in this embodiment realize the principle and technical effects similar to those of the capacity fade simulation method of the battery described above, and are not described here again.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use, and processing of the related data are required to meet the related regulations.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims

1. A method of simulating capacity fade of a battery, the method comprising:

acquiring simulation working condition data of a lithium ion battery;

inputting the simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery lithium precipitation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data by using the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery; the capacity fading simulation model is constructed based on lithium-ion battery lithium-ion reaction areas under different lithium-ion battery lithium-ion separation degrees.

2. The method of claim 1, wherein the capacity fade simulation model comprises an electrochemical model and an output model; simulating the lithium ion battery lithium analysis reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data through the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery, wherein the capacity attenuation curve comprises the following steps:

for any charge and discharge process, simulating the lithium ion battery lithium precipitation reaction area in the charge and discharge process according to the simulation working condition data through the electrochemical model, and determining the available capacity of the electrochemical model output after simulating the charge and discharge process;

and inputting each available capacity into the output model to obtain a capacity attenuation curve of the lithium ion battery.

3. The method of claim 2, wherein the electrochemical model comprises a lithium-eluting reaction area calculation equation; simulating the lithium ion battery by the electrochemical model according to the simulation working condition data to determine the available capacity of the lithium ion battery output after the charging and discharging process, wherein the method comprises the following steps:

Acquiring the current volume fraction of the electrolyte in the lithium ion battery and the model parameters to be calibrated through the simulation working condition data;

substituting the model parameters to be calibrated and the current volume fraction into the lithium-ion reaction area calculation equation, determining the lithium precipitation reaction area of the lithium ion battery;

and determining the available capacity according to the lithium separation reaction area.

4. A method according to claim 3, wherein obtaining the model parameters to be calibrated comprises:

obtaining a film thickness variation value of a negative electrode of the lithium ion battery caused by lithium precipitation;

if the film thickness variation value is smaller than a preset critical film thickness, determining a preset first calibration parameter value as the model parameter to be calibrated;

if the film thickness variation value is larger than or equal to the critical film thickness and the current volume fraction is larger than a preset critical volume fraction, determining a preset second calibration parameter value as the model parameter to be calibrated;

and if the film thickness variation value is larger than or equal to the critical film thickness and the current volume fraction is smaller than or equal to the critical volume fraction, determining a preset third calibration parameter value as the model parameter to be calibrated.

5. A method according to claim 3, wherein said determining said available capacity from said lithium-ion reaction area comprises:

and determining the available capacity according to the initial available capacity of the lithium ion battery and the capacity loss.

6. The method according to any one of claims 1-5, further comprising:

inputting the simulation working condition data into the capacity attenuation simulation model to obtain a model parameter value to be calibrated of the lithium ion battery in the cyclic charge and discharge process;

and determining the lithium precipitation degree of the lithium ion battery in the cyclic charge and discharge process according to the parameter values of the model to be calibrated.

7. The method of any one of claims 1-5, wherein the constructing of the capacity fade simulation model comprises:

performing charge-discharge cycle test on a historical lithium ion battery to obtain an actual capacity attenuation curve of the historical lithium ion battery;

performing capacity attenuation simulation on the historical lithium ion battery according to historical simulation working condition data, preset multiple groups of model parameters to be calibrated and an initial capacity attenuation simulation model to be calibrated to obtain a simulation capacity attenuation curve of the historical lithium ion battery under each group of model parameters to be calibrated;

Determining model parameters to be calibrated of the initial capacity attenuation simulation model according to the actual capacity attenuation curve and each simulation capacity attenuation curve;

8. A capacity fade simulation device for a battery, the device comprising:

the simulation module is used for inputting the simulation working condition data into a preset capacity attenuation simulation model, and simulating the lithium ion battery in the lithium ion battery lithium precipitation reaction area change condition in the cyclic charge and discharge process according to the simulation working condition data through the capacity attenuation simulation model to obtain a capacity attenuation curve of the lithium ion battery; the capacity fading simulation model is constructed based on lithium-ion battery lithium-ion reaction areas under different lithium-ion battery lithium-ion separation degrees.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.