A lithium battery storage life assessment method, device, equipment and storage medium

Abstract

The present application discloses a method, device, equipment, and storage medium for evaluating the storage life of a lithium battery, belonging to the technical field of battery life evaluation. The method includes: determining the SEI film composition influence coefficient based on the molar volume of the SEI film of the 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 and diffusion influence coefficient based on the activation energy of the lithium battery and the SEI film composition influence coefficient of the lithium battery, and determining the state of charge influence coefficient of the lithium battery based on the charge state of the lithium battery and its corresponding electrode potential; determining the fitting relationship between the capacity retention rate of the lithium battery and the storage years and activation energy based on the SEI film composition influence coefficient, the SEI film growth and diffusion influence coefficient, and the state of charge influence coefficient; and based on the fitting relationship, evaluating the storage life of the lithium battery based on the capacity retention rate and activation energy of the lithium battery. The present invention effectively infers the storage life of the lithium battery based on 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 dynamic ecosystem characterized by high humidity, high salinity, wide temperature fluctuations, and potentially corrosive gases. These environmental factors pose a significant challenge to the performance and lifespan of electronic devices, particularly lithium batteries. As one of the most widely used energy storage devices, lithium batteries are susceptible to performance degradation in the marine environment. Therefore, studying the performance changes of lithium batteries in deep-sea environments is of great significance.

[0003] In existing technologies, the evaluation of battery storage life is usually based on a comprehensive assessment 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 subject to more complex and variable influences. 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, making it impossible to evaluate the battery service life 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 that 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:

[0007] 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;

[0008] Determining the activation energy of the lithium battery, and determining the SEI film growth diffusion influence coefficient based on the activation energy of the lithium battery and the composition influence coefficient of the SEI film of the lithium battery;

[0009] Determine the charge state influence coefficient of the lithium battery according to the charge state of the lithium battery and its corresponding electrode potential;

[0010] 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 and diffusion influence coefficient, and the state of charge influence coefficient;

[0011] 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.

[0012] In one possible implementation, determining the activation energy of a lithium battery includes:

[0013] Determine the transfer resistance of lithium batteries at different temperatures;

[0014] Constructing an initial two-dimensional rectangular coordinate system of temperature and transmission resistance, wherein the reciprocal of the transmission resistance is taken as the logarithm with the base e as the ordinate, and the reciprocal of the temperature is taken as the abscissa;

[0015] Determine a 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;

[0016] 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.

[0017] In one possible implementation, determining the transfer resistance of a lithium battery at different temperatures includes:

[0018] Obtain AC impedance spectrum data of lithium batteries at different temperatures;

[0019] Determining a fitting circuit model, the fitting circuit model including a solution resistance connected in series, a first parallel circuit, and a second parallel circuit, the first parallel circuit including a capacitor and a transfer resistor connected in parallel, and the second parallel circuit including a charge transfer resistor and a circuit impedance connected in series and connected in parallel with the capacitor;

[0020] Based on the fitting circuit model, the AC impedance spectrum data is fitted to obtain the transmission resistance at different temperatures.

[0021] In one 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:

[0022] Based on the DFT first principles, the pre-exponential factor coefficient of the SEI film composition is calculated according to the composition of the SEI film;

[0023] Calculating a pre-exponential factor based on the pre-exponential factor coefficient, the activation energy of the lithium battery, a preset molar gas constant, and a preset reaction temperature;

[0024] 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.

[0025] In one possible implementation, determining the state of charge influence coefficient of the lithium battery according to the state of charge of the lithium battery and its corresponding electrode potential includes:

[0026] Set the lithium battery to be fully charged;

[0027] Determine the charging voltage in the fully charged state according to the electrode potential of the lithium battery in the fully charged state;

[0028] The charge state influence coefficient in the fully charged state is calculated according to the charge voltage and the preset normal temperature.

[0029] In one possible implementation, determining a fitting relationship between the capacity retention rate of a lithium battery and storage years and activation energy based on the SEI film composition influence coefficient, the SEI film formation diffusion influence coefficient, and the state of charge influence coefficient includes:

[0030] Calculating the capacity loss of the lithium battery based on the SEI film composition influence coefficient, the SEI film generation and diffusion influence coefficient, and the state of charge influence coefficient;

[0031] determining a rated capacity of the battery, and determining a capacity loss rate of the battery based on the rated capacity and the capacity loss;

[0032] 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 years and activation energy is determined according to the fitting relationship between the capacity loss rate and the capacity retention rate.

[0033] In one possible implementation, the fitting relationship between the capacity retention rate, storage years, and activation energy is:

[0034] ,

[0035] in, is the capacity retention rate of the lithium battery, is the activation energy, The storage life of lithium batteries.

[0036] In a second aspect, the present invention further provides a lithium battery storage life assessment device, comprising:

[0037] An SEI film composition influence coefficient determination module is used to determine the SEI film composition influence coefficient based on the molar volume of the SEI film of the lithium battery and the stoichiometric number of lithium in the SEI film;

[0038] 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;

[0039] A state of charge influence coefficient determination module 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;

[0040] A fitting relationship confirmation module 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 and diffusion influence coefficient, and the charge state influence coefficient;

[0041] The storage life evaluation module 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.

[0042] 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.

[0043] 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.

[0044] The beneficial effects of the present invention are as follows: first, 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, the SEI film growth diffusion influence coefficient is determined based on the activation energy of the lithium battery and the SEI film composition influence coefficient of the lithium battery, and the state of charge influence coefficient of the lithium battery is determined based on 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 based on the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient, and the state of charge influence coefficient; finally, based on the fitting relationship, the storage life of the lithium battery is evaluated based on the capacity retention rate and activation energy of the lithium battery. The present invention analyzes the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient, and the state of charge 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 based on the fitting relationship, thereby achieving a multi-faceted analysis of the factors affecting the storage life of the lithium battery and accurately and effectively calculating the storage life of the lithium battery based on these factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] 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.

[0046] Figure 1 A schematic flow chart of an embodiment of a method for evaluating the storage life of a lithium battery provided by the present invention;

[0047] Figure 2 For the present invention Figure 1 Flow chart of the first embodiment of step S102;

[0048] Figure 3 For the present invention Figure 2 A flow chart of an embodiment of step S201;

[0049] Figure 4 The AC impedance spectrum fitting equivalent circuit diagram provided by the present invention;

[0050] Figure 5 For the present invention Figure 1 Flow chart of the second embodiment of step S102;

[0051] Figure 6 For the present invention Figure 1 A flow chart of an embodiment of step S103;

[0052] Figure 7 For the present invention Figure 1 A flow chart of an embodiment of step S104;

[0053] Figure 8 A schematic structural diagram of an embodiment of a lithium battery storage life assessment device provided by the present invention;

[0054] Figure 9 This is a schematic structural diagram of an embodiment of a lithium battery storage life assessment storage medium provided by the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0056] In the description of the embodiments of the present invention, unless otherwise specified, "plurality" means two or more. "And / or" describes the association relationship between associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone.

[0057] The terms "first," "second," and so on, used in the embodiments of the present invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature designated as "first" or "second" may explicitly or implicitly include at least one such feature.

[0058] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0059] Before describing the embodiments, the following definitions are given for the relevant terms:

[0060] The activation energy of a lithium battery is the energy barrier that lithium ions need to overcome during migration, insertion, and extraction between the positive and negative electrode materials. This energy barrier determines the rate and efficiency of the electrochemical reaction inside the battery.

[0061] The SEI film (solid electrolyte interface) of a lithium battery 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 initial charge and discharge process of a lithium-ion battery. This film has the characteristics of a solid electrolyte and is an electronic insulator but has good conductivity for Li+ ions, allowing lithium ions to be freely inserted and removed.

[0062] Molar volume describes the volume occupied by a unit amount of a substance. It 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.

[0063] The stoichiometric coefficient is the coefficient before the substances involved in the reaction in the chemical reaction equation. It is the number obtained after balancing by the method of undetermined coefficients. It reveals the relationship between the components of the chemical reaction, including the relationship between the ratio of the stoichiometric coefficient and the ratio of the number of particles, the ratio of the amount of substance, the ratio of the gas volume, the ratio of the reaction rate, etc.

[0064] The present invention provides a lithium battery storage life assessment method, device, equipment and storage medium, which are described below respectively.

[0065] Figure 1 A schematic flow chart of an embodiment of the lithium battery storage life evaluation method provided by the present invention is shown as follows: Figure 1 As shown, the lithium battery storage life assessment method includes:

[0066] S101, determining an SEI film composition influence coefficient based on a molar volume of an SEI film of a lithium battery and a stoichiometric number of lithium in the SEI film;

[0067] 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;

[0068] 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;

[0069] S104, determining a 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 and diffusion influence coefficient, and the state of charge influence coefficient;

[0070] 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.

[0071] It should be noted that activation energy is the ability barrier of the Huaxin reaction inside the battery. SEI film (solid electrolyte interface film) is an interface layer formed during the discharge process of lithium batteries, 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 composition 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, electrolyte properties, etc. 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.

[0072] It should be further explained that this embodiment evaluates the storage life of a reversibly activated lithium battery subjected to high-rate discharge in a deep-sea high-pressure environment. The high-rate discharge in this embodiment is a 25C discharge reversibly activated lithium battery.

[0073] This embodiment determines the SEI film composition influence coefficient based on 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 based on the activation energy of the lithium battery and the composition of the SEI film of the lithium battery, and determines the state of charge influence coefficient of the lithium battery based on 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 based on the SEI film composition influence coefficient, the SEI film growth diffusion influence coefficient, and the state of charge influence coefficient; and based on the fitting relationship, evaluates the storage life of the lithium battery based on 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 state of charge 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 based on the fitting relationship, thereby achieving a comprehensive analysis of the factors affecting the storage life of the lithium battery and accurately and effectively calculating the storage life of the lithium battery based on these factors.

[0074] This embodiment analyzes the factors affecting the storage life of lithium batteries from multiple perspectives, and accurately and effectively calculates the storage life of lithium batteries based on these factors.

[0075] In some embodiments of the present invention, Figure 2 As shown, Figure 2 The present invention provides Figure 1 The flowchart of the first embodiment of step S102 includes:

[0076] S201, determining the transmission resistance of the lithium battery at different temperatures;

[0077] S202, constructing initial two-dimensional coordinates;

[0078] S203, taking the reciprocal of the transmission resistance and setting the logarithm thereof with base e as the ordinate, and taking the reciprocal of the temperature as the abscissa, to generate a two-dimensional coordinate of the transmission resistance;

[0079] S204, determining a linear fitting relationship of the two-dimensional coordinates of the transmission resistance according to the transmission resistance at different temperatures;

[0080] 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.

[0081] 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.

[0082] Specifically, the transmission resistance at different temperatures is obtained by taking the reciprocal of each temperature value. , is the temperature; take the logarithm of the reciprocal of the transmission resistance at each temperature 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 .

[0083] This embodiment processes the temperature and its corresponding transfer resistance, analyzes the linear fitting relationship between the processed temperature and 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 subsequent storage life evaluation of the lithium battery.

[0084] 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:

[0085] S301, obtaining AC impedance spectrum data of lithium batteries at different temperatures;

[0086] S302: Determine a fitting circuit model, where the fitting circuit model includes a solution resistance connected in series, a first parallel circuit, and a second parallel circuit, where 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.

[0087] S303 : Fitting the AC impedance spectrum data based on the fitting circuit model to obtain the transmission resistance at different temperatures.

[0088] Specifically, the temperature of the constant temperature box is set to the target temperature. After the temperature of the constant temperature box is stable, the battery cell sample to be tested in the storage state is placed in the constant temperature box, 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 cell 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 temperature is 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.

[0089] Furthermore, the AC impedance spectrum data measured at different temperatures are fitted according to the AC impedance spectrum fitting equivalent circuit diagram using a computer software tool to obtain the transfer resistance of the lithium battery. The software tool used in this embodiment is Z-View software or the fitting software that comes with 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: is the solution resistance, and is the capacitance, is the transmission resistance, is the charge transfer resistance.

[0090] 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.

[0091] 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 FIG. 1 is a flowchart of the second embodiment of step S102, wherein 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:

[0092] S501. Based on the DFT first principles, calculate the pre-exponential factor coefficient of the SEI film composition according to the composition of the SEI film;

[0093] S502, calculating a pre-exponential factor according to a pre-exponential factor coefficient, activation energy of the lithium battery, a preset molar gas constant, and a preset reaction temperature;

[0094] S503. Calculate the SEI film growth diffusion influence coefficient based on the pre-exponential factor and the negative electrode lithium concentration in the lithium battery.

[0095] 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 pre-exponential factor, which is related to the collision frequency between reactant molecules.

[0096] 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.

[0097] In some embodiments of the present invention, Figure 6 As shown, Figure 6 The present invention provides Figure 1The flowchart of the second embodiment of step S103 in FIG. 1 includes:

[0098] S601, setting the lithium battery to a fully charged state;

[0099] S602, determining the charged voltage in the fully charged state according to the electrode potential of the lithium battery in the fully charged state;

[0100] S603: Calculate the state of charge influence coefficient in the fully charged state according to the charged voltage and the preset normal temperature.

[0101] 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.

[0102] 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 includes:

[0103] S701, calculating the capacity loss of the lithium battery according to the SEI film composition influence coefficient, the SEI film generation and diffusion influence coefficient, and the charge state influence coefficient;

[0104] 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;

[0105] 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.

[0106] 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 bonding mode between lithium and other elements. In this embodiment, the main component of the SEI film of the lithium battery is lithium fluoride (LiF).

[0107] 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 the specified cut-off voltage. Finally, the battery capacity can be obtained by calculating the discharge time and discharge current.

[0108] 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. According to the capacity loss of the lithium battery and the relationship between the capacity retention rate of the lithium battery and the capacity loss, the fitting relationship between the capacity retention rate of the lithium battery and the storage life and activation energy is finally obtained.

[0109] This embodiment analyzes the relationship between the SEI film composition influence coefficient, SEI film growth and diffusion influence coefficient, and state of charge influence coefficient of the lithium battery and the capacity retention rate of the lithium battery to obtain the final fitting relationship between the capacity retention rate, storage life and activation energy of the lithium battery. The fitting relationship between the capacity retention rate, storage life and activation energy is evaluated based on the activation energy and capacity retention rate of the lithium battery, thereby achieving a multi-faceted analysis of the factors affecting the storage life of the lithium battery, and accurately and effectively calculating the storage life of the lithium battery based on these influencing factors.

[0110] In some embodiments of the present invention, the fitting relationship between capacity retention rate, storage years and activation energy is:

[0111] ,

[0112] in, is the capacity retention rate of the lithium battery, is the activation energy, The storage life of lithium batteries.

[0113] 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 8 As shown, an embodiment of the present invention further provides a lithium battery storage life assessment device 800 including:

[0114] SEI film composition influence coefficient determination module 801, used to determine 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;

[0115] 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 based on the activation energy of the lithium battery and the SEI film component influence coefficient of the lithium battery;

[0116] 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;

[0117] 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 based on the SEI film composition influence coefficient, the SEI film growth and diffusion influence coefficient, and the state of charge influence coefficient;

[0118] 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.

[0119] 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.

[0120] In the embodiments of the present invention, the lithium battery storage life assessment device may be a standalone server, or a server network or server cluster composed of servers. For example, the lithium battery storage life assessment device described in the embodiments of the present invention includes, but is not limited to, a computer, a network host, a single network server, a set of multiple network servers, or a cloud server composed of multiple servers. A cloud server is composed of a large number of computers or network servers based on cloud computing.

[0121] The present invention also provides a lithium battery storage life evaluation device, such as Figure 9 As shown, Figure 8 This is a 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, desktop computer, notebook, PDA, or 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 .

[0122] In some embodiments, the memory 902 may be an internal storage unit of the computer device, such as a hard disk or memory of the computer device. In other embodiments, the memory 902 may also be an external storage device of the computer device, such as a plug-in hard disk equipped on the computer device, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Furthermore, the memory 902 may include both an internal storage unit of the computer device and an external storage device. The memory 902 is used to store application software installed on the computer device and various types of data, such as program code installed on the computer device. The memory 902 may also be used to temporarily store data that has been output or is about to be output. In one embodiment, the lithium battery storage life assessment program 903 can be executed by the processor 901, thereby implementing the lithium battery storage life assessment method, apparatus, device, and storage device of each embodiment of the present invention.

[0123] In some embodiments, the processor 901 may be a central processing unit (CPU), a microprocessor, or other data processing chip, configured to execute program codes or process data stored in the memory 902 , such as executing a lithium battery storage life assessment program.

[0124] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media used in the various embodiments provided herein 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. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM).

[0125] The above is a detailed introduction to the lithium battery storage life assessment method, device, equipment and storage device provided by the present invention. Specific examples are used herein 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 ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting 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; Determining the activation energy of the lithium battery, and determining the SEI film growth diffusion influence coefficient based on 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; 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 and diffusion influence coefficient, and the state of charge influence coefficient; The fitting relationship between the capacity retention rate, storage years and activation energy is: ， in, is the capacity retention rate of the lithium battery, is the activation energy, The storage life of lithium batteries; 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 lithium batteries, including: Determine the transfer resistance of lithium batteries at different temperatures; Constructing an initial two-dimensional rectangular coordinate system of temperature and transmission resistance, wherein the reciprocal of the transmission resistance is taken as the logarithm with the base e as the ordinate, and the reciprocal of the temperature is taken as the abscissa; Determine a 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; Determining a fitting circuit model, the fitting circuit model including a solution resistance connected in series, a first parallel circuit, and a second parallel circuit, the first parallel circuit including a capacitor and a transfer resistor connected in parallel, and the second parallel circuit including a charge transfer resistor and a circuit impedance connected in series and 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: Determining the SEI film growth diffusion influence coefficient according to the activation energy of the lithium battery and the SEI film composition influence coefficient of the lithium battery includes: Based on the DFT first principles, the pre-exponential factor coefficient of the SEI film composition is calculated according to the composition of the SEI film; Calculating a pre-exponential factor based on 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 lithium battery storage life evaluation method according to claim 1, characterized in that: The charge state influence coefficient of the lithium battery is determined based on 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 lithium battery storage life evaluation method 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 and diffusion influence coefficient, and the state of charge influence coefficient, including: Calculating the capacity loss of the lithium battery based on the SEI film composition influence coefficient, the SEI film generation and diffusion influence coefficient, and the state of charge influence coefficient; determining a rated capacity of the battery, and determining a capacity loss rate of the battery based on 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 years and activation energy is determined according to the fitting relationship between the capacity loss rate and the capacity retention rate.

7. A lithium battery storage life assessment device, used to execute the lithium battery storage life assessment method according to any one of claims 1 to 6, characterized in that: include: An SEI film composition influence coefficient determination module is used to determine the SEI film composition influence coefficient based on 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 state of charge influence coefficient determination module 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 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 and 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 according to the capacity retention rate and activation energy of the lithium battery based on the fitting relationship.

8. A lithium battery storage life assessment device, characterized in that: The device 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 according to any one of claims 1 to 6 are implemented.

9. 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 6.

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