Lithium battery storage life evaluation method, apparatus and device, and storage medium

Abstract

The invention discloses a lithium battery storage life evaluation method, device and equipment and a storage medium, and belongs to the technical field of battery life evaluation, and the method comprises the following steps: determining an SEI film component influence coefficient according to the molar volume of an SEI film of a lithium battery and the stoichiometric number of lithium in the SEI film; determining the activation energy of the lithium battery, determining the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the SEI film component influence coefficient of the lithium battery, and determining the charge state influence coefficient of the lithium battery according to the charge state of the lithium battery and the corresponding electrode potential; according to the SEI film component influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient, determining a fitting relationship between the capacity retention ratio of the lithium battery and the storage age limit and the activation energy; and based on the fitting relationship, evaluating the storage life of the lithium battery according to the capacity retention ratio and the activation energy of the lithium battery. The storage life of the lithium battery can be effectively calculated according to the activation energy of the battery.

Description

Technical Field

[0001] The present invention relates to the technical field of battery storage life assessment, and in particular to a lithium battery storage life assessment method, device, equipment and storage medium. Background Art

[0002] The deep-sea environment is a complex and changeable ecosystem, which contains characteristics such as high humidity, high salinity, large temperature changes, and possible corrosive gases. These environmental factors pose a severe challenge to the performance and life of electronic devices, especially lithium batteries. As one of the most widely used energy storage devices, the performance of lithium batteries is easily affected in the marine environment. Therefore, it is of great significance to study the performance changes of lithium batteries in the deep-sea environment.

[0003] In the existing technology, the evaluation of battery storage life is usually based on a comprehensive evaluation of multiple indicators, including cycle life, battery health status, and capacity retention rate. In the marine environment, due to the complexity and uncertainty of naval factors, these indicators may be affected in a more complex and variable manner. At the same time, when the water depth reaches 11,000 meters, the water pressure is extremely high. At such a depth, the water pressure exceeds 110 MPa, and the battery service life cannot be evaluated based on the current status of the battery.

[0004] Therefore, there is an urgent need for a method for evaluating the storage life of lithium batteries suitable for marine environments, which can accurately evaluate the storage life of lithium batteries in deep-sea environments. Summary of the invention

[0005] In view of this, it is necessary to provide a lithium battery storage life assessment method, device, equipment and storage medium, which can comprehensively analyze the factors affecting the storage life of lithium batteries and accurately and effectively calculate the storage life of lithium batteries based on the comprehensive influencing factors.

[0006] In order to solve the above technical problems, on the one hand, the present invention provides a method for evaluating the storage life of a lithium battery, comprising: The SEI film composition influence coefficient is determined based on the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film; Determine the activation energy of the lithium battery, and determine the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the composition influence coefficient of the SEI film of the lithium battery; Determine the charge state influence coefficient of the lithium battery according to the charge state of the lithium battery and its corresponding electrode potential; Determine the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy according to the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient; Based on the fitting relationship, the storage life of the lithium battery is evaluated according to the capacity retention rate and activation energy of the lithium battery.

[0007] In one possible implementation, determining the activation energy of a lithium battery includes: Determine the transfer resistance of lithium batteries at different temperatures; An initial two-dimensional rectangular coordinate system of temperature and transmission resistance is constructed, wherein the reciprocal of the transmission resistance is taken as the logarithm with base e as the ordinate, and the reciprocal of the temperature is taken as the abscissa; Determine the linear fitting relationship between temperature and transmission resistance according to the coordinates of the transmission resistance of the lithium battery at different temperatures in the initial two-dimensional rectangular coordinate system; The slope of the linear fitting relationship is calculated, and the absolute value of the slope is used as the activation energy of the lithium battery.

[0008] In one possible implementation, determining the transfer resistance of a lithium battery at different temperatures includes: Obtain AC impedance spectrum data of lithium batteries at different temperatures; Determine a fitting circuit model, wherein the fitting circuit model includes a solution resistance connected in series, a first parallel circuit, and a second parallel circuit, wherein the first parallel circuit includes a capacitor and a transfer resistor connected in parallel, and the second parallel circuit includes a charge transfer resistor and a circuit impedance connected in series and then connected in parallel with the capacitor; Based on the fitting circuit model, the AC impedance spectrum data is fitted to obtain the transmission resistance at different temperatures.

[0009] In a possible implementation, determining the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the composition of the SEI film of the lithium battery includes: Based on the DFT first principle, the pre-exponential factor coefficient of the SEI film composition is calculated according to the composition of the SEI film; Calculating the pre-exponential factor according to the pre-exponential factor coefficient, the activation energy of the lithium battery, a preset molar gas constant and a preset reaction temperature; The SEI film growth diffusion influence coefficient is calculated based on the pre-exponential factor and the negative electrode lithium concentration in the lithium battery.

[0010] In one possible implementation, the charge state influence coefficient of the lithium battery is determined according to the charge state of the lithium battery and its corresponding electrode potential, including: Set the lithium battery to be fully charged; Determine the charging voltage in the fully charged state according to the electrode potential of the lithium battery in the fully charged state; The charge state influence coefficient in the fully charged state is calculated according to the charge voltage and the preset normal temperature.

[0011] In a possible implementation, the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy is determined according to the SEI film composition influence coefficient, the SEI film generation diffusion influence coefficient and the charge state influence coefficient, including: Calculating the capacity loss of the lithium battery according to the SEI film composition influence coefficient, the SEI film generation diffusion influence coefficient and the charge state influence coefficient; Determining a rated capacity of the battery, and determining a capacity loss rate of the battery according to the rated capacity and the capacity loss; The capacity retention rate of the lithium battery is obtained, and the fitting relationship between the capacity retention rate of the lithium battery and the storage life and activation energy is determined according to the fitting relationship between the capacity loss rate and the capacity retention rate.

[0012] In a possible implementation, the fitting relationship between the capacity retention rate, storage years and activation energy is: , in, is the capacity retention rate of lithium battery, is the activation energy, The storage life of lithium batteries.

[0013] In a second aspect, the present invention further provides a lithium battery storage life assessment device, comprising: A module for determining the SEI film component influence coefficient, used to determine the SEI film component influence coefficient according to the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film; An SEI film growth diffusion influence coefficient determination module is used to determine the activation energy of the lithium battery, and determine the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the component influence coefficient of the SEI film of the lithium battery; A charge state influence coefficient determination module, used to determine the charge state influence coefficient of the lithium battery according to the charge state of the lithium battery and its corresponding electrode potential; A fitting relationship confirmation module is used to determine the fitting relationship between the capacity retention rate of the lithium battery and the storage life and activation energy according to the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient; The storage life evaluation module is used to evaluate the storage life of the lithium battery based on the fitting relationship and according to the capacity retention rate and activation energy of the lithium battery.

[0014] In a third aspect, the present invention also provides a device comprising a memory and a processor, wherein the memory is used to store programs and data; the processor is coupled to the memory, and is used to execute the program stored in the memory to implement the lithium battery storage life assessment method as described above, and / or to implement the lithium battery storage life assessment as described above.

[0015] In a fourth aspect, the present invention further provides a computer storage medium for storing computer-readable programs or instructions, which, when executed by a processor, can implement the lithium battery storage life evaluation method as described above.

[0016] The beneficial effects of the present invention are as follows: first, the SEI film component influence coefficient is determined according to the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film, the SEI film growth diffusion influence coefficient is determined according to the activation energy of the lithium battery and the SEI film component influence coefficient of the lithium battery, and the charge state influence coefficient of the lithium battery is determined according to the charge state of the lithium battery and its corresponding electrode potential; then, the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy is determined according to the SEI film component influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient; finally, based on the fitting relationship, the storage life of the lithium battery is evaluated according to the capacity retention rate and activation energy of the lithium battery. The present invention analyzes the SEI film component influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient of the lithium battery, analyzes the fitting relationship between these influence coefficients and the capacity retention rate of the lithium battery and the storage years and activation energy, and evaluates the storage life of the lithium battery according to the fitting relationship, thereby realizing a multi-faceted analysis of the influencing factors affecting the storage life of the lithium battery, and accurately and effectively deduces the storage life of the lithium battery according to these influencing factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A schematic diagram of an embodiment of a lithium battery storage life assessment method provided by the present invention; Figure 2 For the present invention Figure 1 Schematic diagram of the process of the first embodiment of step S102; Figure 3 For the present invention Figure 2 A schematic diagram of a flow chart of an embodiment of step S201; Figure 4 The AC impedance spectrum fitting equivalent circuit diagram provided by the present invention; Figure 5 For the present invention Figure 1 A schematic flow chart of a second embodiment of step S102; Figure 6 For the present invention Figure 1A schematic flow chart of an embodiment of step S103; Figure 7 For the present invention Figure 1 A schematic flow chart of an embodiment of step S104; Figure 8 A schematic diagram of the structure of an embodiment of a lithium battery storage life assessment device provided by the present invention; Fig. 9 A schematic structural diagram of an embodiment of a lithium battery storage life assessment storage medium provided by the present invention. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0020] In the description of the embodiments of the present invention, unless otherwise specified, "multiple" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" may mean: A exists alone, A and B exist at the same time, and B exists alone.

[0021] The descriptions of "first", "second", etc. involved in the embodiments of the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the technical features defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0022] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0023] Before describing the embodiments, the following definitions are given for the relevant terms: The activation energy of a lithium battery is the energy barrier that lithium ions need to overcome during migration, embedding, and extraction between positive and negative electrode materials. This energy barrier determines the rate and efficiency of the electrochemical reaction inside the battery. The SEI film (solid electrolyte interface film) of lithium batteries is a passivation layer covering the surface of the electrode material formed by the reaction between the electrode material and the electrolyte at the solid-liquid interface during the first charge and discharge process of lithium-ion batteries. This film has the characteristics of a solid electrolyte, is an electronic insulator but has good conductivity for Li+ ions, allowing lithium ions to be freely embedded and removed; Molar volume is the volume occupied by a unit amount of a substance, and refers to the volume occupied by a unit amount of a substance (i.e. 1 mole) of gas or solid (for solids, it usually refers to its molar volume in a specific crystal form) at a certain temperature and pressure; The stoichiometric number is the coefficient before the substances involved in the reaction in the chemical reaction equation, that is, the number obtained after balancing by the method of undetermined coefficients, which reveals the relationship between the components of the chemical reaction, including the relationship between the ratio of the stoichiometric number and the ratio of the number of particles, the ratio of the amount of substance, the gas volume ratio, the ratio of the reaction rate, etc.

[0024] The present invention provides a lithium battery storage life assessment method, device, equipment and storage medium, which are described below respectively.

[0025] Figure 1 A schematic diagram of an embodiment of the lithium battery storage life evaluation method provided by the present invention is shown in FIG. Figure 1 As shown, the lithium battery storage life assessment method includes: S101, determining the SEI film composition influence coefficient according to the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film; S102, determining the activation energy of the lithium battery, and determining the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the composition influence coefficient of the SEI film of the lithium battery; S103, determining a charge state influence coefficient of the lithium battery according to the charge state of the lithium battery and its corresponding electrode potential; S104, determining the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy according to the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient; S105. Based on the fitting relationship, the storage life of the lithium battery is evaluated according to the capacity retention rate and activation energy of the lithium battery.

[0026] It should be noted that activation energy is the ability barrier of the internal Huaxin reaction of the battery. SEI film (solid electrolyte interface film) is an interface layer formed during the discharge process of the lithium battery, which has an important influence on the cycle stability and capacity retention rate of the battery. According to the molar volume of the SEI film, the stoichiometric number of lithium and the chemical properties of the SEI film, the SEI film component influence coefficient can be analyzed to reflect the influence of the SEI film composition on the battery performance. The generation and diffusion rate of the SEI film are also important factors affecting the performance of lithium batteries. The growth and diffusion influence coefficient of the SEI film of the lithium battery is analyzed according to the composition of the SEI film combined with the activation energy, temperature, and electrolyte properties of the lithium battery. The state of charge (SOC) of the lithium battery has a direct impact on its internal reaction and performance. Under different states of charge, the electrode potential and the chemical reaction rate inside the battery will change. By measuring the performance parameters of the battery under different states of charge, the state of charge influence coefficient can be calculated. This coefficient directly reflects the influence of the state of charge on the battery performance.

[0027] It should be further explained that this embodiment evaluates the storage life of a high-rate discharge reversibly activated lithium battery in a deep-sea high-pressure environment. The high-rate discharge in this embodiment is a 25C discharge reversibly activated lithium battery.

[0028] This embodiment determines the SEI film composition influence coefficient according to the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film, determines the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the composition of the SEI film of the lithium battery, and determines the charge state influence coefficient of the lithium battery according to the charge state of the lithium battery and its corresponding electrode potential; determines the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy according to the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient; based on the fitting relationship, evaluates the storage life of the lithium battery according to the capacity retention rate and activation energy of the lithium battery. This embodiment analyzes the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient of the lithium battery, analyzes the fitting relationship between these influence coefficients and the capacity retention rate of the lithium battery and the storage years and activation energy, and evaluates the storage life of the lithium battery according to the fitting relationship, thereby realizing a multi-faceted analysis of the influencing factors affecting the storage life of the lithium battery, and accurately and effectively infers the storage life of the lithium battery based on these influencing factors.

[0029] This embodiment analyzes the factors affecting the storage life of the lithium battery from all aspects, and accurately and effectively calculates the storage life of the lithium battery based on these factors.

[0030] In some embodiments of the present invention, Figure 2 As shown, Figure 2 The present invention provides Figure 1The flowchart of the first embodiment of step S102 in FIG. 1 includes: S201, determining the transmission resistance of the lithium battery at different temperatures; S202, constructing initial two-dimensional coordinates; S203, taking the logarithm with base e as the vertical coordinate after calculating the reciprocal of the transmission resistance, and taking the reciprocal of the temperature as the horizontal coordinate, to generate a two-dimensional coordinate of the transmission resistance; S204, determining a linear fitting relationship of the two-dimensional coordinates of the transmission resistance according to the transmission resistance at different temperatures; S205. Calculate the slope of the linear fitting relationship, and use the absolute value of the slope as the activation energy of the lithium battery.

[0031] It should be noted that the activation energy of lithium batteries has a direct impact on the performance and life of the battery. The lower the activation energy of the lithium battery, the higher the transmission efficiency of lithium ions in the lithium battery, the better the battery performance and the longer the storage life.

[0032] Specifically, the transmission resistance at different temperatures is obtained by taking the reciprocal of each temperature value. , is the temperature; the reciprocal of the transmission resistance at each temperature is taken as the logarithm with base e, that is, ,in is the transmission resistance; As the Y axis, As the X-axis, construct a two-dimensional coordinate, perform linear fitting, calculate the slope of the linear fitting relationship, and use the absolute value of the slope of the linear fitting relationship as the activation energy of the lithium battery, in units of .

[0033] This embodiment processes the temperature and its corresponding transfer resistance, analyzes the linear fitting relationship between the processed temperature and the transfer resistance, and obtains the slope of the linear fitting relationship as the activation energy of the lithium battery, which can reflect the performance and storage life of the lithium battery and provide a basis for the subsequent storage life evaluation of the lithium battery.

[0034] In some embodiments of the present invention, Figure 3 As shown, Figure 3 The present invention provides Figure 2 The flowchart of the second embodiment of step S201 in FIG. 1 includes: S301, obtaining AC impedance spectrum data of lithium batteries at different temperatures; S302, determining a fitting circuit model, where the fitting circuit model includes a solution resistance, a first parallel circuit, and a second parallel circuit connected in series, the first parallel circuit includes a capacitor and a transfer resistor connected in parallel, and the second parallel circuit includes a charge transfer resistor and a circuit impedance connected in series and then connected in parallel with the capacitor; S303 , fitting the AC impedance spectrum data based on the fitting circuit model to obtain the transmission resistance at different temperatures.

[0035] Specifically, the temperature of the thermostat is set to the target temperature. After the temperature of the thermostat is stable, the battery monomer sample to be tested in the storage state is placed in the thermostat, and the battery is connected to the charge and discharge test cabinet and left to stand for 2 hours. When the temperature of the battery monomer sample to be tested is stable, the battery is connected to the electrochemical workstation, and the electrochemical impedance test is performed using the constant voltage AC impedance mode of the electrochemical workstation. In this embodiment, the target temperatures are set from 20°C, 10°C, 0°C, -10°C, and -20°C in sequence, the test frequency range is 0.1Hz~100KHz, multi-frequency signal excitation (multisine), the disturbance voltage amplitude is set to 20mV, and the AC impedance spectrum data is obtained after the test.

[0036] Furthermore, the AC impedance spectrum data measured at different temperatures are fitted according to the AC impedance spectrum fitting equivalent circuit diagram through a computer software tool to obtain the transmission resistance of the lithium battery. The software tool used in this embodiment is Z-View software or the fitting software provided by the AC impedance meter. The AC impedance spectrum fitting equivalent circuit diagram is as follows: Figure 4 , Figure 4 The AC impedance spectrum fitting equivalent circuit diagram provided by the present invention is as follows: is the solution resistance, and is the capacitance, is the transmission resistance, is the charge transfer resistance.

[0037] In this embodiment, AC impedance spectrum data at different temperatures are obtained through testing, and circuit fitting is performed on the AC impedance spectrum data to obtain the transmission resistance at different temperatures, providing data support for the subsequent calculation of the activation energy of the lithium battery.

[0038] In some embodiments of the present invention, Figure 5 As shown, Figure 5 The present invention provides Figure 1 The flowchart of the second embodiment of step S102 in the embodiment of the present invention is as follows: determining the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the composition of the SEI film of the lithium battery, including: S501, based on the DFT first principle, calculating the pre-exponential factor coefficient of the SEI film component according to the composition of the SEI film; S502, calculating the pre-exponential factor according to the pre-exponential factor coefficient, the activation energy of the lithium battery, the preset molar gas constant and the preset reaction temperature; S503, calculating the SEI film growth diffusion influence coefficient according to the pre-exponential factor and the negative electrode lithium concentration in the lithium battery.

[0039] It should be noted that the DFT first principles utilize the first principles of density functional theory. The pre-exponential factor is also called the frequency factor or the pre-exponential factor, which is related to the collision frequency between the reactant molecules.

[0040] This example uses DFT first-principles calculations combined with analysis of SEI film composition and activation energy to accurately determine the SEI film growth diffusion influence coefficient, which is of great significance for understanding the performance degradation of lithium batteries and evaluating battery storage life.

[0041] In some embodiments of the present invention, Figure 6 As shown, Figure 6 The present invention provides Figure 1 The flowchart of the second embodiment of step S103 in FIG. 1 includes: S601, setting the lithium battery to a fully charged state; S602, determining a charge voltage in a fully charged state according to an electrode potential of the lithium battery in a fully charged state; S603: Calculate the charge state influence coefficient in the fully charged state according to the charge voltage and the preset normal temperature.

[0042] This embodiment uses the battery state of charge to represent the remaining available power in the battery. Based on the analysis of the battery state of charge and its corresponding electrode potential, the state of charge influence coefficient on the battery storage life is obtained, which can accurately evaluate and predict the storage life of the lithium battery.

[0043] In some embodiments of the present invention, Figure 7 As shown, Figure 7 The present invention provides Figure 1 The flowchart of an embodiment of step S104 in the embodiment includes: S701, calculating the capacity loss of the lithium battery according to the SEI film composition influence coefficient, the SEI film generation diffusion influence coefficient and the charge state influence coefficient; S702, determining the rated capacity of the battery, and determining the capacity loss rate of the battery according to the rated capacity and the capacity loss; S703, obtaining the capacity retention rate of the lithium battery; and determining the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy according to the fitting relationship between the capacity loss rate and the capacity retention rate.

[0044] It should be noted that the molar volume of the SEI film reflects the ratio of the total volume of all components in the SEI film to the total molar number of the SEI film components, and the size of the molar volume is closely related to the thickness, density and composition of the SEI film; the stoichiometric number of lithium in the SEI film is the ratio of the number of lithium ions in the SEI film to the number of other key elements (such as oxygen, carbon, fluorine, etc.) in the SEI film, and the size of the stoichiometric number of lithium in the SEI film is closely related to the lithium content in the SEI film and the combination mode of lithium and other elements. In this embodiment, the main component of the SEI film of the lithium battery is lithium fluoride (LiF).

[0045] It should be further explained that the capacity retention rate of a lithium battery is the ratio of the discharge capacity after storage to the initial capacity of the battery. It is an important indicator for measuring battery performance and can be obtained in a variety of ways. In this embodiment, it is obtained by measurement. First, the lithium battery needs to be fully charged and then discharged at a certain voltage and current until the battery voltage drops to a specified cut-off voltage. Finally, the battery capacity can be obtained by calculating the discharge time and discharge current.

[0046] Specifically, the capacity loss of the lithium battery can be calculated based on the SEI film composition influence coefficient, the SEI film generation and diffusion influence coefficient and the charge state influence coefficient. The capacity loss of the lithium battery is combined with the capacity retention rate of the lithium battery and its relationship to finally obtain the fitting relationship between the capacity retention rate of the lithium battery, the storage life and the activation energy.

[0047] This embodiment analyzes the relationship between the SEI film composition influence coefficient, SEI film growth diffusion influence coefficient and charge state influence coefficient and the capacity retention rate of the lithium battery, and obtains the final fitting relationship between the capacity retention rate, storage life and activation energy of the lithium battery. The storage life of the lithium battery is evaluated according to the activation energy and capacity retention rate of the lithium battery, and a multi-faceted analysis of the influencing factors affecting the storage life of the lithium battery is achieved. The storage life of the lithium battery is accurately and effectively calculated based on these influencing factors.

[0048] In some embodiments of the present invention, the fitting relationship between the capacity retention rate, the storage life and the activation energy is: , in, is the capacity retention rate of lithium battery, is the activation energy, The storage life of lithium batteries.

[0049] In order to better implement the lithium battery storage life evaluation method in the embodiment of the present invention, based on the lithium battery storage life evaluation method, correspondingly, Figure 8As shown, the embodiment of the present invention further provides a lithium battery storage life assessment device 800 including: The SEI film component influence coefficient determination module 801 is used to determine the SEI film component influence coefficient according to the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film; SEI film growth diffusion influence coefficient determination module 802, used to determine the activation energy of the lithium battery, and determine the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the component influence coefficient of the SEI film of the lithium battery; The state of charge influence coefficient determination module 803 is used to determine the state of charge influence coefficient of the lithium battery according to the charge state of the lithium battery and its corresponding electrode potential; A fitting relationship confirmation module 804 is used to determine the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy according to the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient; The storage life evaluation module 805 is used to evaluate the storage life of the lithium battery according to the capacity retention rate and activation energy of the lithium battery based on the fitting relationship.

[0050] The lithium battery storage life assessment device 800 provided in the above embodiment can implement the technical solution described in the above lithium battery storage life assessment method embodiment. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above lithium battery storage life assessment method embodiment, which will not be repeated here.

[0051] In the embodiment of the present invention, the lithium battery storage life evaluation device can be an independent server, or a server network or server cluster composed of servers. For example, the lithium battery storage life evaluation device described in the embodiment of the present invention includes but is not limited to a computer, a network host, a single network server, a plurality of network server sets or a cloud server composed of multiple servers. The cloud server is composed of a large number of computers or network servers based on cloud computing.

[0052] The present invention also provides a lithium battery storage life evaluation device, such as Fig. 9 As shown, Figure 8 This is a structural block diagram of an embodiment of a lithium battery storage life assessment device provided by the present invention. The lithium battery storage life assessment device 900 can be a computing device such as a mobile terminal, a desktop computer, a notebook, a palm computer, and a server. The lithium battery storage life assessment device 900 includes a processor 901 and a memory 902, wherein the memory 902 stores a lithium battery storage life assessment program 903.

[0053] In some embodiments, the memory 902 may be an internal storage unit of a computer device, such as a hard disk or memory of a computer device. In other embodiments, the memory 902 may also be an external storage device of a computer device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the computer device. Furthermore, the memory 902 may also include both an internal storage unit of a computer device and an external storage device. The memory 902 is used to store application software and various types of data installed in the computer device, such as program codes for installing the computer device. The memory 902 may also be used to temporarily store data that has been output or is to be output. In one embodiment, the lithium battery storage life assessment program 903 may be executed by the processor 901, thereby realizing the lithium battery storage life assessment method, device, equipment and storage device of each embodiment of the present invention.

[0054] In some embodiments, the processor 901 may be a central processing unit (CPU), a microprocessor or other data processing chip, and is used to run program codes or process data stored in the memory 902, such as executing a lithium battery storage life assessment program.

[0055] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0056] The lithium battery storage life assessment method, device, equipment and storage device provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for evaluating the storage life of a lithium battery, characterized in that: include: The SEI film composition influence coefficient is determined based on the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film; Determine the activation energy of the lithium battery, and determine the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the composition influence coefficient of the SEI film of the lithium battery; Determine the charge state influence coefficient of the lithium battery according to the charge state of the lithium battery and its corresponding electrode potential; Determine the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy according to the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient; Based on the fitting relationship, the storage life of the lithium battery is evaluated according to the capacity retention rate and activation energy of the lithium battery.

2. The lithium battery storage life evaluation method according to claim 1, characterized in that: Determine the activation energy of a lithium battery, including: Determine the transfer resistance of lithium batteries at different temperatures; An initial two-dimensional rectangular coordinate system of temperature and transmission resistance is constructed, wherein the reciprocal of the transmission resistance is taken as the logarithm with base e as the ordinate, and the reciprocal of the temperature is taken as the abscissa; Determine the linear fitting relationship between temperature and transmission resistance according to the coordinates of the transmission resistance of the lithium battery at different temperatures in the initial two-dimensional rectangular coordinate system; The slope of the linear fitting relationship is calculated, and the absolute value of the slope is used as the activation energy of the lithium battery.

3. The lithium battery storage life evaluation method according to claim 2, characterized in that: Determine the transfer resistance of lithium batteries at different temperatures, including: Obtain AC impedance spectrum data of lithium batteries at different temperatures; Determine a fitting circuit model, wherein the fitting circuit model includes a solution resistance connected in series, a first parallel circuit, and a second parallel circuit, wherein the first parallel circuit includes a capacitor and a transfer resistor connected in parallel, and the second parallel circuit includes a charge transfer resistor and a circuit impedance connected in series and then connected in parallel with the capacitor; Based on the fitting circuit model, the AC impedance spectrum data is fitted to obtain the transmission resistance at different temperatures.

4. The lithium battery storage life evaluation method according to claim 3, characterized in that: The SEI film growth diffusion influence coefficient is determined according to the activation energy of the lithium battery and the composition of the SEI film of the lithium battery, including: Based on the DFT first principle, the pre-exponential factor coefficient of the SEI film composition is calculated according to the composition of the SEI film; Calculating the pre-exponential factor according to the pre-exponential factor coefficient, the activation energy of the lithium battery, a preset molar gas constant and a preset reaction temperature; The SEI film growth diffusion influence coefficient is calculated based on the pre-exponential factor and the negative electrode lithium concentration in the lithium battery.

5. The method for evaluating the storage life of a lithium battery according to claim 1, characterized in that: The charge state influence coefficient of the lithium battery is determined according to the charge state of the lithium battery and its corresponding electrode potential, including: Set the lithium battery to be fully charged; Determine the charging voltage in the fully charged state according to the electrode potential of the lithium battery in the fully charged state; The charge state influence coefficient in the fully charged state is calculated according to the charge voltage and the preset normal temperature.

6. The method for evaluating the storage life of a lithium battery according to claim 1, characterized in that: The fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy is determined according to the SEI film composition influence coefficient, the SEI film generation diffusion influence coefficient and the charge state influence coefficient, including: Calculating the capacity loss of the lithium battery according to the SEI film composition influence coefficient, the SEI film generation diffusion influence coefficient and the charge state influence coefficient; Determining a rated capacity of the battery, and determining a capacity loss rate of the battery according to the rated capacity and the capacity loss; The capacity retention rate of the lithium battery is obtained, and the fitting relationship between the capacity retention rate of the lithium battery and the storage life and activation energy is determined according to the fitting relationship between the capacity loss rate and the capacity retention rate.

7. The method for evaluating the storage life of a lithium battery according to claim 6, characterized in that: The fitting relationship between the capacity retention rate, storage life and activation energy is: ， in, is the capacity retention rate of lithium battery, is the activation energy, The storage life of lithium batteries.

8. A lithium battery storage life assessment device, characterized in that: include: A module for determining the SEI film component influence coefficient, used to determine the SEI film component influence coefficient according to the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film; An SEI film growth diffusion influence coefficient determination module is used to determine the activation energy of the lithium battery, and determine the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the component influence coefficient of the SEI film of the lithium battery; A charge state influence coefficient determination module, used to determine the charge state influence coefficient of the lithium battery according to the charge state of the lithium battery and its corresponding electrode potential; A fitting relationship confirmation module is used to determine the fitting relationship between the capacity retention rate of the lithium battery and the storage life and activation energy according to the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient and the charge state influence coefficient; The storage life evaluation module is used to evaluate the storage life of the lithium battery based on the fitting relationship and according to the capacity retention rate and activation energy of the lithium battery.

9. A lithium battery storage life assessment device, characterized in that: It comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the lithium battery storage life evaluation method as claimed in any one of claims 1 to 7 are implemented.

10. A storage medium, characterized in that: The storage medium stores computer program instructions, and when the computer program instructions are executed by a computer, the computer is caused to execute the lithium battery storage life evaluation method according to any one of claims 1 to 7.

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