Solid-state battery parameter adjustment method and device, storage medium and electronic equipment

Abstract

The application discloses a solid-state battery parameter adjustment method and device, a storage medium and an electronic device. The method comprises the following steps: obtaining initial parameters of a solid-state battery; determining a first correlation between electrolyte conductivity and battery voltage of the solid-state battery and a second correlation between discharge rate and battery voltage of the solid-state battery based on the initial parameters; and adjusting the initial parameters based on the first correlation and the second correlation to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters. The application solves the technical problem of low efficiency of solid-state battery parameter adjustment in the related art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electrochemistry, in particular to a solid-state battery parameter adjustment method and device, a storage medium and an electronic device. BACKGROUND

[0002] Lithium-ion batteries face the bottleneck of safety and performance improvement. All-solid-state batteries (ASSBs) are always considered as the substitutes of lithium-ion batteries due to their better thermal stability, longer cycle life and higher energy density. The working principle of ASSBs is the same as that of lithium-ion batteries, except that the liquid electrolyte and separator are replaced by solid electrolyte, and dendrites are not easy to produce and grow in the solid-state interface. The all-solid-state thin film laboratory does not need to add thermal conductive agent and adhesive, which reduces the performance decline. Current experimental research mainly focuses on the design and construction of solid electrolyte. During the battery development process, there are too many design parameters, and the experimental task is heavy. The influence of each parameter on the battery performance is not clear, and the experimental design has a certain blindness. Sometimes it even takes time, effort and money, but the battery performance is not obviously improved, even negative. Therefore, there is a technical problem of low efficiency of solid-state battery parameter adjustment in the related art.

[0003] To solve the above problems, an effective solution has not been proposed yet. SUMMARY

[0004] Embodiments of the present application provide a solid-state battery parameter adjustment method and device, a storage medium and an electronic device to at least solve the technical problem of low efficiency of solid-state battery parameter adjustment in the related art.

[0005] According to an aspect of embodiments of the present application, a solid-state battery parameter adjustment method is provided, including: obtaining initial parameters of a solid-state battery; determining, based on the initial parameters, a first association between electrolyte conductivity and battery voltage of the solid-state battery, and a second association between discharge rate and battery voltage of the solid-state battery; and adjusting the initial parameters based on the first association and the second association to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters. By quantifying the association, the design flexibility is improved, and the battery parameters can be adjusted flexibly according to actual needs. At the same time, the use of optimized parameter combinations helps to improve the reliability and stability of the model.

[0006] Optionally, the adjusting the initial parameter based on the first correlation and the second correlation to obtain a target parameter comprises: determining a discharge behavior characteristic of the solid-state battery based on the first correlation and the second correlation; determining a target conductivity required for the solid-state battery to maintain the battery voltage under a predetermined discharge rate according to the discharge behavior characteristic; and adjusting the initial parameter according to the target conductivity to obtain the target parameter. Through the above process, it is helpful to understand how the solid-state electrolyte conductivity and the discharge rate affect the electrochemical performance of the battery, thereby providing guidance for the design of the solid-state electrolyte and the optimization of the battery operating conditions.

[0007] Optionally, the determining the target conductivity required for the solid-state battery to maintain the battery voltage under a predetermined discharge rate according to the discharge behavior characteristic comprises: determining a conductivity threshold according to a voltage drop rate indicated by the discharge behavior characteristic; and determining the value of the target conductivity to be greater than the conductivity threshold. By setting the conductivity threshold and ensuring that the target conductivity is higher than the threshold, the voltage drop rate during discharge can be effectively slowed down, thereby ensuring that the solid-state battery can maintain a relatively stable voltage output during discharge.

[0008] Optionally, the determining the discharge behavior characteristic of the solid-state battery based on the first correlation and the second correlation comprises: determining a third correlation of the solid-state battery representing the voltage drop distribution in the length direction of the battery; and determining the discharge behavior characteristic of the solid-state battery based on the first correlation, the second correlation, and the third correlation. Through the above process, the behavior characteristics of the solid-state battery under different discharge conditions, including voltage stability, voltage drop distribution, and battery efficiency, can be comprehensively understood, and such multi-dimensional analysis is helpful to more accurately predict and optimize the battery performance.

[0009] Optionally, the determining the first correlation between the electrolyte conductivity of the solid-state battery and the battery voltage and the second correlation between the discharge rate of the solid-state battery and the battery voltage based on the initial parameter comprises: determining a simulation model of the solid-state battery, wherein the simulation model at least includes geometric simulation parameters and physical field simulation parameters of the solid-state battery; inputting the initial parameter and a plurality of candidate electrolyte conductivities into the simulation model for processing to determine the first correlation; and inputting the initial parameter and a plurality of candidate discharge rates into the simulation model for processing to determine the second correlation. Through the above steps, simulation modeling can be used to reduce the number of entity experiments and improve efficiency.

[0010] Optionally, the determining the simulation model of the solid-state battery comprises: determining a solid-phase concentration diffusion feature based on electrode characteristics and electrolyte characteristics of the solid-state battery; determining an electrode kinetics feature based on a discharge equilibrium potential of the solid-state battery; and determining the simulation model according to the solid-phase concentration diffusion feature, the electrode kinetics feature, and a charge transport feature. The simulation model constructed based on characteristics can more comprehensively consider various factors of the battery in the charging and discharging process, more accurately predict the performance of the battery, avoid a large amount of expensive experimental materials and time consumption, and thus accelerate the research and development process of the solid-state battery.

[0011] Optionally, the method further comprises: determining a stop condition of the simulation model according to a cutoff voltage of the solid-state battery. By setting the stop condition matched with the actual cutoff voltage of the solid-state battery, the simulation model can more accurately capture the behavior change of the battery in the charging and discharging process.

[0012] According to another aspect of the embodiments of the present application, a solid-state battery parameter adjustment apparatus is provided, comprising: an initial parameter acquisition module configured to acquire initial parameters of a solid-state battery; a correlation determination module configured to determine, based on the initial parameters, a first correlation between electrolyte conductivity and battery voltage of the solid-state battery and a second correlation between discharge rate and the battery voltage of the solid-state battery; and a parameter adjustment module configured to adjust the initial parameters based on the first correlation and the second correlation to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters.

[0013] According to another aspect of the embodiments of the present application, a non-volatile storage medium is provided, which stores a plurality of instructions adapted to be loaded and executed by a processor to implement any of the solid-state battery parameter adjustment methods.

[0014] According to another aspect of the embodiments of the present application, an electronic device is provided, comprising: one or more processors and a memory configured to store one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement any of the solid-state battery parameter adjustment methods.

[0015] In the embodiment of the present application, the initial parameters of the solid-state battery are obtained; based on the initial parameters, the first correlation between the electrolyte conductivity and the battery voltage of the solid-state battery and the second correlation between the discharge rate and the battery voltage of the solid-state battery are determined; and based on the first correlation and the second correlation, the initial parameters are adjusted to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters. The purpose of quickly evaluating the performance of the solid-state battery is achieved, the technical effect of optimizing the parameter adjustment process of the solid-state battery is realized, and the technical problem of the unsatisfactory parameter adjustment efficiency of the solid-state battery in the related art is solved. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings, which are included to provide a further understanding of the present application, constitute a part of the present application and illustrate the illustrative embodiments of the present application and their description serve to explain the present application, and do not constitute improper limitations on the present application. In the drawings:

[0017] Figure 1 is a flowchart of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0018] Figure 2 is a first schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0019] Figure 3 is a second schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0020] Figure 4 is a third schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0021] Figure 5 is a fourth schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0022] Figure 6 is a fifth schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0023] Figure 7 is a sixth schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0024] Figure 8 is a seventh schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0025] Figure 9is a schematic diagram of an optional solid-state battery parameter adjustment device provided according to an embodiment of the present application.

[0026] Figure 10 is a schematic diagram of an optional solid-state battery parameter adjustment device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0029] For the convenience of description, part of the nouns or terms related to the embodiments of the present application are described as follows:

[0030] COMSOL Multiphysics is a numerical simulation software with powerful multi-physical field fully coupled simulation analysis function and efficient computing performance, which can ensure the high accuracy of numerical simulation and has been widely used in various disciplines.

[0031] The P2D (pseudo-two-dimensions) model is used to simulate the entire battery structure, and the establishment of the P2D model can include all basic components of the lithium ion battery, including electrodes (positive electrode, negative electrode), separators, electrolyte and current collectors.

[0032] Ternary nickel-cobalt-manganese (NCM, Nickel Cobalt Manganese) is a material mainly composed of three metal elements: nickel, cobalt and manganese, which is synthesized by a specific process to form a hydroxide. This material is applied in the field of lithium batteries, especially in the positive electrode material of lithium batteries.

[0033] Direct current polarization (DC) refers to the difference between the actual direction of the electrochemical reaction and the theoretical direction under constant external voltage. When a constant external voltage is applied, the charge distribution on the electrode surface will be affected, so that the potential of the electrode surface deviates from the ideal equilibrium potential, thereby generating direct current polarization.

[0034] Galvanostatic intermittent titration technique (GITT) refers to a cycle process of pulse-constant current-relaxation. The pulse refers to a short current passing process, and the relaxation refers to the process without current passing. The basic principle is that in a unit time t, a constant current I is applied for charging or discharging, and then the current is disconnected, and the voltage changes of the constant current process and the relaxation process are recorded.

[0035] According to the embodiments of the present application, a method for adjusting the parameters of a solid-state battery is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in a different order.

[0036] Figure 1 is a flowchart of an optional solid-state battery parameter adjustment method according to an embodiment of the present application, as shown in Figure 1 The method comprises the following steps:

[0037] Step S102, obtaining the initial parameters of the solid-state battery;

[0038] It can be understood that the initial parameters of the solid-state battery are obtained, and the initial parameters provide key indicators about the basic performance of the battery, which are the basis for improving the battery condition and identifying potential problems.

[0039] Optionally, the above initial parameters can be various, for example, the thickness of the positive electrode sheet, the thickness of the negative electrode sheet, the thickness of the electrolyte, etc. Figure 2 is a first schematic diagram of an optional solid-state battery parameter adjustment method according to an embodiment of the present application, preferably setting the thickness of the positive electrode sheet to 65 μm (microns), the thickness of the electrolyte to 45 μm, and the thickness of the negative electrode sheet to 85 μm.

[0040] Step S104, based on the initial parameters, determining the first correlation between the electrolyte conductivity of the solid-state battery and the battery voltage, and the second correlation between the discharge rate of the solid-state battery and the battery voltage;

[0041] It can be understood that, based on the initial parameters, the correlation between the battery voltage and the electrolyte conductivity of the solid-state battery and the discharge rate of the solid-state battery is determined as a first correlation, and the correlation between the discharge rate and the battery voltage is determined as a second correlation. By quantifying the correlation, the design flexibility is improved, and the battery parameters can be flexibly adjusted according to actual needs.

[0042] In an optional embodiment, based on the initial parameters, the first correlation between the electrolyte conductivity of the solid-state battery and the battery voltage and the second correlation between the discharge rate of the solid-state battery and the battery voltage are determined, comprising: determining a simulation model of the solid-state battery, wherein the simulation model at least includes geometric simulation parameters and physical field simulation parameters of the solid-state battery; inputting the initial parameters and a plurality of candidate electrolyte conductivities into the simulation model for processing to determine the first correlation; inputting the initial parameters and a plurality of candidate discharge rates into the simulation model for processing to determine the second correlation.

[0043] It can be understood that, based on the initial parameters, a simulation model of the solid-state battery is determined, and the simulation model at least includes geometric simulation parameters and physical field simulation parameters of the solid-state battery. A plurality of candidate electrolyte conductivities, a plurality of candidate discharge rates and initial parameters are input into the simulation model for processing to determine the correlation, and the correlation between the electrolyte conductivity and the battery voltage is the first correlation, and the correlation between the discharge rate and the battery voltage is the second correlation. By simulation modeling, the number of entity experiments is reduced, and the efficiency is improved.

[0044] Optionally, in the simulation model, a plurality of candidate electrolyte conductivities and discharge rates can be set, and by using a one-dimensional linear geometric model, using a single particle model theory, combining transient research and auxiliary scanning technology, the influence of different conductivities and discharge rates on the battery voltage is systematically analyzed. For example, by setting the conductivity to 0.02 S / m (Siemens per meter), 0.05 S / m, 0.1 S / m, 0.25 S / m, 0.5 S / m, 1 S / m, 1.25 S / m and 1.5 S / m, and setting the discharge rate to 1C, 2C and 4C, C is the theoretical capacity of the battery, a series of battery voltage-time curves can be obtained, and then the first and second correlation relationships are determined.

[0045] Optionally, the simulation experiment method described above can be various, for example, a method and application for predicting the electrical performance of a solid-state battery based on COMSOL simulation. The single particle model is the simplest electrochemical model of lithium-ion batteries, which is derived from the P2D model by simplification, and adopts two spherical particles to represent the positive and negative electrodes of the lithium-ion battery, assuming that the lithium ion insertion and extraction process occurs on the spherical particles, and considering that the concentration of the electrolyte and its internal potential are constant. The single particle model is simple in structure, small in calculation amount and easy to realize online application. A lithium-ion battery with a solid-state electrolyte is built, which has a one-dimensional linear geometry, a graphite negative electrode material, a ternary nickel-cobalt-manganese (NCM) positive electrode material, and a solid-state electrolyte with different conductivities. The battery behavior under different discharge rates and solid-state electrolyte conductivities is analyzed.

[0046] Optionally, the COMSOL simulation described above can be various, for example, selecting a single particle interface transient study, inputting model parameters such as positive electrode sheet thickness, negative electrode sheet thickness, electrolyte thickness, etc., and establishing a line segment geometry with the size. Add materials, select graphite electrode for negative electrode and NCM electrode for positive electrode, and input attribute parameters such as conductivity, equilibrium potential, diffusion coefficient, reference concentration, etc. to the electrode material, and apply the material to the corresponding geometric line segment domain; wherein the conductivity, equilibrium potential and diffusion coefficient are obtained according to actual experimental measurement, and the reference concentration is obtained by theoretical calculation.

[0047] Optionally, a NCM mold half-cell is assembled using a 320μm NCM positive electrode sheet and a LPSClBr (Li3PS4, lithium phosphorus sulfide) solid-state electrolyte, and a graphite mold half-cell is assembled using a 150μm graphite negative electrode sheet and a LPSClBr solid-state electrolyte in the same way. Using an electrochemical workstation, set the test voltage to 10mV, the test time to 30min, and perform direct current polarization test. After the test is completed, the battery mold is disassembled, the electrode sheet is taken out and the thickness d NCM =0.043cm, d 石墨 =0.019cm, the obtained polarization curve is as shown in Figure 3 Figure 3 is a second schematic diagram of an optional solid-state battery parameter adjustment method provided by an embodiment of the present application, a positive and negative electrode direct current polarization curve is tested. The current-voltage relationship of the electrode material in the direct current polarization test is depicted. The direct current polarization test is used to measure the conductivity of the electrode material, and the slope of the curve can be used to calculate the resistance of the electrode material, and then the size of the conductivity is deduced. The conductivity is an important indicator of the ion and electron transmission capacity in the electrode material. The potential change of the electrode material under different lithium ion concentrations (or state of charge SOC) is shown. The equilibrium potential curve is crucial for understanding the electrochemical reaction of the electrode material during charging and discharging, and reflects the electrochemical potential of the electrode material at different states of charge. ​

[0048] In the direct polarization test, a certain voltage is applied to the positive sheet NCM and the negative sheet graphite respectively, and the stable current I of the positive sheet after 30 minutes is read NCM = 0.118 mA (milliampere), the resistance R of the positive sheet NCM = U / I NCM = 84.82 Ω (ohm), U is the applied voltage, and the electronic conductivity σ of the positive sheet is obtained NCM = d NCM / R NCM *S NCM = 0.64 mS / cm (millisiemens per centimeter), d NCM is the thickness of the positive sheet, and S NCM is the cross-sectional area of the positive sheet.

[0049] I 石墨 = 3.545 mA, R 石墨 = U / I 石墨 = 2.82 Ω, and the electronic conductivity σ is obtained 石墨 = d 石墨 / R 石墨 *S 石墨 = 8.58 mS / cm, d 石墨 is the thickness of the negative sheet, and S 石墨 is the cross-sectional area of the negative sheet.

[0050] Optionally, the GITT (GITT) method is used to test the charge and discharge cycles of the NCM mold half-cell and the graphite mold half-cell, and the voltage setting range is NCM / LiIn (NCM half-cell): 2 ~ 3.68 V (volt), G / LiIn (graphite half-cell): -0.61 ~ 1 V, and the initial test uses a current of 0.1C for activation, that is, charging and discharging, to ensure that the battery material is fully activated, so as to obtain a more accurate diffusion coefficient.

[0051] Subsequently, the NCM half-cell is charged to the cut-off voltage, discharged at 0.1C for 15 min (minutes), rested for 30 min, discharged at 0.1C for 15 min, rested for 30 min, repeated 40 times, and D s is calculated using mathematical representation.

[0052]

[0053] Among them, represents the solid-phase diffusion coefficient of the positive and negative electrodes, represents the number of moles of substances participating in the diffusion process, refers to the volume occupied by a unit of substance, and S refers to the effective surface area of the electrode material, Voltage change in solid, unit is V, reflects the change of potential in solid during charge and discharge. Refers to the change of the whole system voltage during charge and discharge, including the voltage change of solid and electrolyte. Is the time constant.

[0054] Figure 4 is a third schematic diagram of an optional solid-state battery parameter adjustment method provided by an embodiment of the present application, which shows the calculation method of GITT, as shown in Figure 4 , is the process of pulse discharging the battery for 15 minutes, resting for 30 minutes, and repeating until the power is 0. Among them, the change from V1 to V2 occurs immediately after the current is loaded, and the voltage drop is mainly caused by ohmic impedance and charge exchange impedance. Then the battery voltage slowly decreases to V3, and V2-V3 is , is the change of the whole system voltage during charge and discharge, which represents the voltage drop caused by solid-phase diffusion. When the discharge process stops, the battery voltage gradually recovers to V4, which corresponds to the redistribution of lithium ions in the solid phase. The change of the steady-state voltage of the battery in the resting state before and after the two charge and discharge processes is .

[0055] Figure 5 is a fourth schematic diagram of an optional solid-state battery parameter adjustment method provided by an embodiment of the present application, which tests the positive and negative electrode equilibrium potential curve, and shows the potential change of the electrode material under different lithium ion concentrations (or state of charge SOC). The equilibrium potential curve is crucial for understanding the electrochemical reaction of the electrode material during charge and discharge, and reflects the electrochemical potential of the electrode material under different states of charge.

[0056] In an optional embodiment, a simulation model of a solid-state battery is determined, including: determining a solid-phase concentration diffusion characteristic based on electrode characteristics and electrolyte characteristics of the solid-state battery; determining an electrode kinetics characteristic based on a discharge equilibrium potential of the solid-state battery; and determining the simulation model according to the solid-phase concentration diffusion characteristic, the electrode kinetics characteristic, and a charge transport characteristic.

[0057] It can be understood that according to the electrode characteristics and electrolyte characteristics of the solid-state battery, the solid-phase concentration diffusion characteristics can be determined, the diffusion process of lithium ions in the electrode material (such as NCM positive electrode and graphite negative electrode) is described using Fick's law, which reflects the transmission speed of lithium ions inside the electrode particles, is an important factor affecting the charging and discharging rate and efficiency of the solid-state battery, and can include parameters such as the diffusion coefficient of the input material. The electrode kinetics characteristics are determined using the discharge equilibrium potential of the solid-state battery. According to factors such as the properties of the electrode material, the reaction rate and the potential, the behavior of the battery at different states of charge is determined, which requires the input of the equilibrium potential and other kinetic parameters of the electrode material. Ohm's law can also be used to describe the transport of electric charge in the battery to obtain the charge transport characteristics, which is an indispensable part of the solid-state battery model and aims to reflect the movement of electric charge in the electrode and electrolyte. The simulation model is determined according to the solid-phase concentration diffusion characteristics, the electrode kinetics characteristics and the charge transport characteristics. Based on the simulation model constructed based on the characteristics, various factors of the battery during charging and discharging can be more comprehensively considered, and the performance of the battery can be more accurately predicted. Through the simulation model, the behavior of the battery can be simulated and analyzed outside the laboratory, avoiding a large amount of expensive experimental materials and time consumption, thereby accelerating the research and development process of the solid-state battery.

[0058] Due to the charge conservation inside the battery, the charge transport in the electrode and electrolyte is described using Ohm's law, which describes the transport process of electric charge in the electrode and electrolyte, and the conductivity determines the potential gradient-induced current size, cross-sectional area and Faraday constant , which is related to the electrochemical reaction rate of the electrode interface, and the current density reflects the dynamic changes of these electrochemical processes:

[0059]

[0060] where, is the conductivity, with a unit of S / m, which describes the ability of the material to conduct electricity. is the potential of the electrode, with a unit of V (volt), and the potential is a key indicator of the charge distribution inside the battery. x is the spatial coordinate, usually representing the one-dimensional length direction of the battery, with a unit of m (meter), is the cross-sectional area of the electrode along the length direction, which affects the size of the contact area between the electrode and the electrolyte, thereby affecting the electrochemical reaction rate of the battery. is the Faraday constant, approximately equal to 96485 C / mol (coulomb per mole), which describes the charge amount of one mole of electrons. is the current density, usually with a unit of A / m² (ampere per square meter), which reflects the charging and discharging rate of the battery.

[0061] Since both the electrode and the solid-state electrolyte are solid, Fick's law can be used to describe the material transport process within the spherical particles of the electrode, i.e., the mathematical expression of solid-phase concentration diffusion, which describes the diffusion behavior of lithium ions inside the spherical electrode particles, and explains the spatiotemporal distribution of lithium ions in the electrode through the interaction of concentration gradient and diffusion coefficient:

[0062]

[0063] The concentration of the substance in the solid phase is in mol / m³ (moles per cubic meter), which reflects the lithium ion content per unit volume. t is the time, in s (seconds), indicating the time variable of lithium ion diffusion. The solid-phase diffusion coefficient is in m² / s (square meters per second), which describes the diffusion speed of lithium ions in the electrode material. r is the radius coordinate inside the spherical particle, in m (meters), used to describe the diffusion path of lithium ions inside the spherical electrode particles.

[0064] At the electrode interface, the Butler Volmer equation is used to describe the electrode kinetics characteristics, which describes the nonlinear relationship between the rate of lithium ion intercalation / deintercalation on the electrode surface and the potential, current density. In solid-state batteries, it describes how the electrochemical reaction rate at the interface between the electrode material and the electrolyte is affected by the change in potential, which is a key equation for understanding the electrochemical reaction rate during battery charging and discharging:

[0065]

[0066] where, The discharge curve of the equilibrium potential is calculated by substituting the experimentally measured value.

[0067] represents the reaction overpotential, in V (volts), which is the difference between the two-phase potential minus the kinetic equilibrium potential. The solid-phase potential at any point in the model can be obtained from Ohm's law, while the equilibrium potential is a parameter that needs to be input into the model, reflecting the kinetic characteristics of the electrochemical reaction. represents the potential of the electrode material under standard conditions. is the reaction current density on the electrode surface, in A / m² (amperes per square meter), reflecting the rate of electrochemical reaction. is the solid-phase reaction active area. is the exchange current density, in A / m² (amperes per square meter), representing the reaction speed at equilibrium. and is the anodic and cathodic charge transfer coefficient, dimensionless, describing the intercalation / deintercalation process of lithium ions at the electrode surface. T is the absolute temperature, in K (Kelvin), which affects the rate of electrochemical reactions. R is the ideal gas constant, approximately equal to 8.314 J / (mol·K) (Joules per mole Kelvin), which serves to adjust the temperature effect in electrochemical reaction kinetics.

[0068] The above mathematical expressions collectively form the core of the solid-state battery simulation model. By numerically solving these equations, the voltage behavior of the solid-state battery under different conditions (such as different electrolyte conductivities and discharge rates) can be simulated, thereby achieving the prediction and optimization of battery performance.

[0069] In an alternative embodiment, the method further comprises: determining a stopping condition for the simulation model according to the cutoff voltage of the solid-state battery.

[0070] It can be understood that the stopping condition of the simulation model is determined according to the cutoff voltage of the solid-state battery, such as being set to 2V, which is related to the performance of the specific battery. By setting a stopping condition that matches the actual cutoff voltage of the solid-state battery, the simulation model can more accurately capture the changes in the behavior of the battery during charging and discharging.

[0071] Step S106, based on the first association and the second association, adjusting the initial parameters to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters.

[0072] It can be understood that the initial parameters are adjusted according to the first association and the second association to obtain the target parameters, and the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters. The optimized parameter combination helps to improve the reliability and stability of the model.

[0073] In an alternative embodiment, based on the first association and the second association, the initial parameters are adjusted to obtain target parameters, including: based on the first association and the second association, determining the discharge behavior characteristics of the solid-state battery; according to the discharge behavior characteristics, determining the target conductivity required for the solid-state battery to maintain the battery voltage under the predetermined discharge rate; adjusting the initial parameters according to the target conductivity to obtain the target parameters.

[0074] It can be understood that through model analysis, the voltage behavior of the solid-state battery will be different under different electrolyte conductivity and discharge rate conditions. According to the first correlation and the second correlation, the discharge behavior characteristics of the solid-state battery are obtained, and based on the analyzed discharge behavior characteristics, it is determined in the embodiment that in order to maintain the stability of the battery voltage, the target value of the electrolyte conductivity needs to be reached under a certain discharge rate. By comparing the simulation results under different conductivities, the threshold value of the conductivity that has the greatest impact on the voltage stability is identified. The target conductivity required for the solid-state battery to maintain the battery voltage under a predetermined discharge rate is determined, the initial parameters are adjusted, and the target parameters are obtained. According to the determined target conductivity, the initial design parameters of the solid-state battery, such as the material formula or structural design of the electrolyte, are adjusted to achieve the optimized target parameters. The solid-state battery adjusted in this way will have better electrochemical performance, especially under high-power applications, which helps to understand how the solid-state electrolyte conductivity and the discharge rate affect the electrochemical performance of the battery, and provides guidance for the design of the solid-state electrolyte and the optimization of the battery operating conditions.

[0075] Optionally, when determining the first correlation between the electrolyte conductivity and the battery voltage, the change curve of the battery voltage with time under different conductivity values can be obtained. Similarly, the second correlation between the discharge rate and the battery voltage shows the stability of the battery voltage under different discharge speeds.

[0076] Optionally, when the electrolyte conductivity is lower than a certain value, the battery voltage significantly decreases at a high discharge rate, while when the conductivity is increased to or above 1 S / m, the battery voltage can be maintained at a high level, proving the significant impact of high conductivity on the performance of the battery.

[0077] In an optional embodiment, according to the discharge behavior characteristics, the target conductivity required for the solid-state battery to maintain the battery voltage under a predetermined discharge rate is determined, including: determining the conductivity threshold according to the voltage drop rate indicated by the discharge behavior characteristics; determining the value of the target conductivity to be greater than the conductivity threshold.

[0078] It can be understood that according to the voltage drop rate indicated by the discharge behavior characteristics, the conductivity threshold is determined, and the value of the target conductivity is determined to be greater than the conductivity threshold. By setting the conductivity threshold and ensuring that the target conductivity is higher than this threshold, the voltage drop speed during discharge can be effectively slowed down, thereby ensuring that the solid-state battery can maintain a relatively stable voltage output during discharge.

[0079] Optionally, by comparing the voltage drop rate at different conductivity values, the conductivity threshold is determined to be 1 S / m, below which the voltage stability of the battery will be affected. The value of the target conductivity should be higher than or equal to the determined conductivity threshold, meaning that the conductivity of the solid-state electrolyte should be optimized to at least 1 S / m to ensure that the solid-state battery can maintain stable voltage at high discharge rate, reducing voltage drop and polarization phenomenon.

[0080] In an optional embodiment, based on the first association and the second association, the discharge behavior characteristics of the solid-state battery are determined, including: determining a third association representing the distribution of pressure drop in the length direction of the battery; based on the first association, the second association, and the third association, the discharge behavior characteristics of the solid-state battery are determined.

[0081] It can be understood that in the solid-state battery, the conductivity of the electrolyte not only affects the overall voltage characteristics of the battery, but also affects the distribution of pressure drop inside the battery. The distribution of electrolyte pressure drop in the length direction of the battery, i.e. the third association, is obtained through model simulation, reflecting the resistance of charge transfer at different positions. After introducing the third association, the subtle changes of the battery during discharge are more comprehensively captured, improving the accuracy of the discharge behavior characteristics description. Based on the first association (relationship between electrolyte conductivity and battery voltage), the second association (relationship between discharge rate and battery voltage) and the third association (relationship between electrolyte pressure drop distribution and battery length), the discharge behavior characteristics of the solid-state battery are determined: the embodiment integrates three different dimensional association relationships, and through comprehensive analysis, the behavior characteristics of the solid-state battery under different discharge conditions can be comprehensively understood, including voltage stability, pressure drop distribution and battery efficiency, etc. This multi-dimensional analysis helps to more accurately predict and optimize battery performance.

[0082] Optionally, by plotting the electrolyte voltage drop curve with respect to the length of the battery, the third association representing the distribution of pressure drop in the length direction of the battery is determined. Through a one-dimensional drawing group, the electrolyte voltage drop curves when the electrolyte conductivity is 0.02 S / m and 1 S / m under different discharge rates are created. It can be found that the lower the conductivity, the greater the electrolyte voltage drop in both time and space dimensions.

[0083] Optionally, based on the analysis results of the model, the target conductivity and discharge rate can be determined to optimize the voltage characteristics of the battery, prolong the battery life, and improve the energy density and power density. For example, when the conductivity of the solid-state electrolyte reaches or exceeds 1 S / m, the battery voltage can be maintained at a high level under 4C discharge rate, reducing internal losses. The performance characteristics of the solid-state battery under different discharge rates and conductivities are determined, providing a specific direction for the research and development of solid-state electrolyte materials, i.e. the development of solid-state electrolyte with conductivity greater than or equal to 1 S / m should be focused on, providing an optimization idea for the adjustment direction of battery parameters.

[0084] Through the above step S102, the initial parameters of the solid-state battery are obtained; step S104, based on the initial parameters, determining the first correlation between the electrolyte conductivity of the solid-state battery and the battery voltage, and the second correlation between the discharge rate of the solid-state battery and the battery voltage; step S106, based on the first correlation and the second correlation, adjusting the initial parameters to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters. The purpose of quickly evaluating the performance of the solid-state battery can be achieved, and the technical effect of optimizing the parameter adjustment process of the solid-state battery is achieved, thereby solving the technical problem of unsatisfactory parameter adjustment efficiency of the solid-state battery in the related art.

[0085] Based on the above embodiments and optional embodiments, an optional implementation is provided. By respectively focusing on parameter measurement, performance prediction and behavior characteristic analysis of the solid-state battery, a systematic and scientific solid-state battery performance optimization scheme is formed. The method and application of COMSOL simulation for predicting the electrical performance of the solid-state battery. The key physical and chemical parameters of the electrode material and the electrolyte in the solid-state battery are obtained through experimental means, including conductivity, equilibrium potential and solid-phase diffusion coefficient. It covers direct current polarization method, charge and discharge cycle and constant current intermittent titration method (GITT). These tests accurately measure the conductivity, equilibrium potential and diffusion coefficient of each material, which is the basis for building a solid-state battery simulation model, and can ensure the accuracy and reliability of the model.

[0086] The negative electrode selects a graphite electrode, and the positive electrode selects an NCM electrode. Attribute parameters such as conductivity, equilibrium potential, diffusion coefficient, and reference concentration are input into the electrode material, and the material is applied to the corresponding geometric line segment domain. Among them, the conductivity, equilibrium potential, and diffusion coefficient are obtained according to actual experimental measurement, and the reference concentration is obtained by theoretical calculation. The battery material properties can be tested by direct current polarization method (DC), small rate charge and discharge cycle, and constant current intermittent titration method (GITT), and the model material parameters can be obtained by related electrochemical calculation method.

[0087] Figure 6 FIG. 5 is a fifth schematic diagram of an optional solid-state battery parameter adjustment method according to the embodiments of the present application, which is a test positive and negative electrode GITT curve and calculation method diagram. It shows the test results of the constant current intermittent titration method (GITT). The solid-phase diffusion coefficient of the battery material can be measured by GITT. The GITT curve contains the voltage change of the battery in the constant current discharge and static stage.

[0088] Figure 6 The sub Figure 1 is the charging curve of the graphite negative electrode tested by the constant current intermittent titration method, and the sub Figure 2 is the discharging curve of the NCM positive electrode tested by the constant current intermittent titration method, and the subFigure 3 , 4 are the partial amplification of voltage change during charging and discharging process, respectively. According to the potential data in Figure 6 , the solid-phase diffusion coefficient of the corresponding material can be calculated using the formula .

[0089] Set the positive and negative boundary conditions, where the boundary conditions can be described by differential equations, which represent the relationship between the effective conductivity of electrode materials and the potential gradient in solid-state batteries, and how they work together to maintain the current density inside the battery:

[0090]

[0091] where, and represent the effective conductivity of the negative and positive materials, respectively. The effective conductivity is a comprehensive indicator that not only reflects the conductivity characteristics of the material itself, but also considers the impact of electrode structure composition on conductivity.

[0092] x=0 (representing the position of the negative electrode boundary), x=L (representing the boundary position of the positive electrode, L is the thickness of the battery), the rate of change of potential inside the electrode material with position. The potential gradient describes the change of potential in space, which is the basis for driving the transmission of charges (such as electrons and ions) in the electrode. represents the average current density through the battery, where I is the total current of the battery, and A is the effective cross-sectional area of the battery. Current density is an important indicator for evaluating battery performance, which reflects the current output capability of the battery per unit area. , represent the surface potential of the negative and positive electrodes, respectively.

[0093] In solid-state batteries, the product of the effective conductivity of the negative and positive materials and the potential gradient inside the electrode is equal to the average current density through the battery at the position of the negative and positive electrodes, respectively. This indicates that the current density inside the battery is maintained and controlled through the relationship between the effective conductivity of the electrode and the potential gradient. In essence, it reflects the Ohm's law of resistance in the electrode of the solid-state battery and the current flowing through the electrode, that is, the current density is the product of the conductivity and the potential gradient. In order to ensure the constant current density inside the battery, the electrode material needs to have a specific effective conductivity to adapt to the change of the potential gradient. During the charging and discharging process of the battery, the potential gradient will change with the change of lithium ion concentration and charge state, so the effective conductivity of the electrode material must be high enough to ensure that the current density is maintained at an ideal level, reducing the voltage drop and energy loss inside the battery.

[0094] Add lithium-ion battery physical fields and generate electrolyte, porous electrode, and particle intercalation components, customize electrical conductivity, active material fraction, and particle diameter, active fraction is automatically calculated from the initial cell charge distribution node, add porous electrode reactions, define electrode kinetics, add initial battery charge distribution, input initial state of charge (SOC) and initial capacity (Q) values. The negative current collector serves as a reference, the boundary condition is selected as electrical grounding, and at the positive current collector, the electrode current is selected to be applied, and the 1C current can be obtained from the initial battery charge distribution node.

[0095] Modify the transient study time through the initialization study to assist in scanning for different discharge rates and different solid electrolyte conductivities. Based on the transient study settings, modify the time to be 0-4000 s, and add scanning parameters, such as setting the discharge rate to 1, 2, and 4 C, and setting the conductivity to 0.02, 0.05, 0.1, 0.25, 0.5, 1, 1.25, and 1.5 S / m.

[0096] Set the stop condition in the solver window to stop the discharge process when the voltage drops to 2 V.

[0097] Select data in sequence and add a one-dimensional plot group. For different discharge rates, create battery voltage curve graphs under electrolyte conductivities of 0.02 S / m and 1 S / m, respectively, Figure 7 is a sixth schematic diagram of an optional solid-state battery parameter adjustment method provided by an embodiment of the present application, as Figure 7 shown, the battery voltage curve graphs under different conductivities and discharge rates can include multiple groups of curves, respectively corresponding to the battery voltage change curves of the solid-state electrolyte under different discharge rates (such as 1 C, 2 C, and 4 C) at different conductivities (such as 0.02 S / m and 1 S / m), which are helpful for analyzing the influence of conductivity and discharge rate on battery performance. Figure 6 Conductivity selects the first group of parameters, that is, 0.02 S / m as the dependent variable, discharge rate selects all parameters, and the y-axis data expression input is battery potential, to obtain the discharge curves of the 0.02 S / m solid-state electrolyte under 1 C, 2 C, and 4 C.

[0098] The electrolyte voltage drop curves of different solid-state electrolyte conductivity values under 1 C rate, that is, the change curves of electrolyte voltage drop with battery length, respectively correspond to low-conductivity (such as 0.02 S / m) and high-conductivity (such as 1 S / m) electrolytes, which are helpful for understanding the influence of electrolyte conductivity on voltage drop distribution, discharge rate selects all parameters, and the y-axis data expression input is battery potential, to obtain the discharge curves of the 1 S / m solid-state electrolyte under 1 C, 2 C, and 4 C. As can be seen from the comparison of the graphs, the higher the electrolyte conductivity, the better the battery performance, verifying that the increase in conductivity reduces battery polarization and internal loss.

[0099] Figure 8 is a seventh schematic diagram of an optional solid-state battery parameter adjustment method provided by an embodiment of the present application, as shown in Figure 8 For different electrolyte conductivity values, battery voltage curves at 1C and 4C are created respectively. The graph describing the voltage drop of electrolytes with different conductivity values at 1C is created, and the battery voltage changes with time, especially under the condition of fixed discharge rate (such as 1C and 4C). By comparison, the degree of influence of conductivity on battery performance can be observed. Figure 8 The left subgraph selects all parameters of conductivity, and selects the first group of parameters of discharge rate, that is, 1C. The y-axis data expression input is battery potential, and the discharge curve of different electrolyte conductivity values at 1C is obtained, Figure 8 The right middle subgraph selects all parameters of conductivity, and selects the last group of parameters of discharge rate, that is, 4C. The y-axis data expression input is battery potential, and the discharge curve of different electrolyte conductivity values at 4C is obtained. By comparing the discharge curves of different electrolyte conductivity values at 1C and 4C, it can be verified that the influence of conductivity on the voltage curve of the battery is more significant at high rate (4C); and at low rate 1C, when the electrolyte conductivity is 0.25-1.5 S / m, the discharge behavior is almost the same. Therefore, under the current system, the solid-state electrolyte material end, the research and development of conductivity reaching 1 S / m can meet the charge and discharge requirements at 4C rate.

[0100] Figure 9 is an eighth schematic diagram of an optional solid-state battery parameter adjustment method provided by an embodiment of the present application, as shown in Figure 9 Figure 9 The left subgraph selects the first group of parameters of conductivity, that is, 0.02 S / m, and selects the first group of parameters of discharge rate, that is, 1C. Set the x-axis as the battery length and the y-axis as the electrolyte voltage drop, and the electrolyte voltage drop curve of 0.02 S / m conductivity value at 1C rate is obtained. Figure 9 The right subgraph selects the first group of parameters of conductivity, that is, 1 S / m, and selects the first group of parameters of discharge rate, that is, 1C. Set the x-axis as the battery length and the y-axis as the electrolyte voltage drop, and the electrolyte voltage drop curve of 1 S / m conductivity value at 1C rate is obtained. By comparing the electrolyte voltage drop curves of 0.02 S / m and 1 S / m conductivity values at 1C rate, it can be verified by comparing the voltage change curve of the space dimension that the lower the conductivity, the greater the voltage drop in the time and space dimensions. Therefore, the research and development of solid-state electrolyte with conductivity greater than or equal to 1 S / m should be focused on in this system.

[0101] ​The above optional embodiments at least achieve the following effects: for a solid-state battery, a single particle model is used to effectively simplify the battery structure, by scanning different discharge rates and different solid-state electrolyte conductivities, the influence mechanism of the solid-state electrolyte conductivity on the battery discharge process is quickly and clearly revealed, and the testing and calculation methods of the parameters in the model are determined. From parameter acquisition to model building and completion of simulation calculation, the time and material cost of battery testing are greatly saved, which provides an important support for guiding the research and development direction and accelerating the research and development process.

[0102] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown.

[0103] In this embodiment, a solid-state battery parameter adjustment device is also provided, which is used to implement the above embodiments and preferred embodiments, which have been described and will not be repeated. As used below, the term "module" "device" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware implementation is also possible and contemplated.

[0104] According to the embodiments of the present application, a device embodiment for implementing the solid-state battery parameter adjustment method is also provided, Figure 10 is a schematic diagram of an optional solid-state battery parameter adjustment device provided according to the embodiments of the present application, as Figure 10 shown, the above solid-state battery parameter adjustment device includes an acquisition parameter module 1002, a determination association module 1004, and an adjustment parameter module 1006, which will be described below.

[0105] The acquisition parameter module 1002 is configured to acquire initial parameters of a solid-state battery.

[0106] The determination association module 1004 is connected with the acquisition parameter module 1002, and is configured to determine a first association between an electrolyte conductivity of the solid-state battery and a battery voltage, and a second association between a discharge rate of the solid-state battery and the battery voltage, based on the initial parameters.

[0107] The adjustment parameter module 1006 is connected with the determination association module 1004, and is configured to adjust the initial parameters based on the first association and the second association to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters.

[0108] The solid-state battery parameter adjustment device provided in the embodiment of the application includes an obtaining parameter module 1002, which is configured to obtain initial parameters of a solid-state battery; a determining correlation module 1004, which is connected to the obtaining parameter module 1002 and configured to determine a first correlation between electrolyte conductivity and battery voltage of the solid-state battery and a second correlation between discharge rate and battery voltage of the solid-state battery based on the initial parameters; and an adjusting parameter module 1006, which is connected to the determining correlation module 1004 and configured to adjust the initial parameters based on the first correlation and the second correlation to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters. The purpose of quickly evaluating the performance of the solid-state battery is achieved, the technical effect of optimizing the solid-state battery parameter adjustment process is achieved, and the technical problem of low solid-state battery parameter adjustment efficiency in the related art is solved.

[0109] It should be noted that each of the above modules can be implemented by software or hardware. For example, for the latter, each of the above modules can be located in the same processor, or each of the above modules can be located in different processors in any combination.

[0110] It should be noted that the obtaining parameter module 1002, the determining correlation module 1004, and the adjusting parameter module 1006 correspond to steps S102 to S106 in the embodiment, and the above modules have the same instances and application scenarios as the corresponding steps, but are not limited to the content disclosed in the above embodiment. It should be noted that the above modules can run in a computer terminal as part of the device.

[0111] It should be noted that the optional or preferred implementation of the embodiment can refer to the related description in the embodiment, which will not be repeated here.

[0112] The solid-state battery parameter adjustment device can further include a processor and a memory, and the obtaining parameter module 1002, the determining correlation module 1004, and the adjusting parameter module 1006 are stored in the memory as program units, and the processor executes the above program units stored in the memory to realize the corresponding functions.

[0113] The processor includes a core, and the core retrieves the corresponding program unit from the memory. The core can be provided with one or more. The memory can include a non-persistent memory in a computer readable medium, a random access memory (RAM), and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory includes at least one memory chip.

[0114] The embodiment of the application provides a non-volatile storage medium, which stores a program, and the program is executed by a processor to realize a solid-state battery parameter adjustment method.

[0115] An electronic device is provided, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: obtaining initial parameters of a solid-state battery; determining, based on the initial parameters, a first correlation between electrolyte conductivity and battery voltage of the solid-state battery, and a second correlation between discharge rate and battery voltage of the solid-state battery; and adjusting the initial parameters based on the first correlation and the second correlation to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters. The device in the present application can be a server, a PC, etc.

[0116] The present application also provides a computer program product adapted to execute, when executed on a data processing device, a program that initializes the following method steps: obtaining initial parameters of a solid-state battery; determining, based on the initial parameters, a first correlation between electrolyte conductivity and battery voltage of the solid-state battery, and a second correlation between discharge rate and battery voltage of the solid-state battery; and adjusting the initial parameters based on the first correlation and the second correlation to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters.

[0117] Those skilled in the art should understand that embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) containing computer-usable program code.

[0118] The present application is described with reference to flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce an apparatus that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in a flow or multiple flows and / or blocks Figure 1 The functions specified in a flow or multiple flows and / or blocks

[0119] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0120] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0121] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0122] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) about which the processor can execute instructions. The memory can also include non-volatile memory, such as read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), flash memory, or other memory technologies, about which the processor can execute instructions. The memory is an example of computer readable media.

[0123] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to computing devices. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0124] It is also to be noted that the terms "comprising", "including", and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises a... " does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0125] Those skilled in the art will appreciate that embodiments of the present application can be devised for a method, a system, or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer-readable program code.

[0126] The embodiments of the present application are only illustrative and are not intended to limit the present application. Various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method of solid state battery parameter adjustment, characterized by, The method comprises: obtaining initial parameters of a solid-state battery; based on the initial parameters, determining a first correlation between the electrolyte conductivity and the battery voltage of the solid-state battery, and a second correlation between the discharge rate and the battery voltage of the solid-state battery; based on the first correlation and the second correlation, adjusting the initial parameters to obtain target parameters, wherein the performance of the solid-state battery corresponding to the target parameters is better than the performance of the solid-state battery corresponding to the initial parameters; wherein, based on the first correlation and the second correlation, the initial parameters are adjusted to obtain target parameters, comprising: based on the first correlation and the second correlation, determining the discharge behavior characteristics of the solid-state battery; according to the discharge behavior characteristics, determining the target conductivity required for the solid-state battery to maintain the battery voltage under the predetermined discharge rate; according to the target conductivity, adjusting the initial parameters to obtain the target parameters.

2. The method of claim 1, wherein, According to the discharge behavior characteristics, the target conductivity required for the solid-state battery to maintain the battery voltage under the predetermined discharge rate is determined, comprising: determining the conductivity threshold according to the voltage drop rate indicated by the discharge behavior characteristics; determining the value of the target conductivity to be greater than the conductivity threshold.

3. The method of claim 1, wherein, The determination of the discharge behavior characteristics of the solid-state battery based on the first correlation and the second correlation comprises: determining a third correlation representing the voltage drop distribution in the length direction of the battery of the solid-state battery; based on the first correlation, the second correlation, and the third correlation, the discharge behavior characteristics of the solid-state battery are determined.

4. The method according to any one of claims 1 to 3, characterized in that, The determination of the first correlation and the second correlation between the electrolyte conductivity and the battery voltage of the solid-state battery based on the initial parameters comprises: determining a simulation model of the solid-state battery, wherein the simulation model at least includes geometric simulation parameters and physical field simulation parameters of the solid-state battery; inputting the initial parameters and a plurality of candidate electrolyte conductivities into the simulation model for processing to determine the first correlation; inputting the initial parameters and a plurality of candidate discharge rates into the simulation model for processing to determine the second correlation.

5. The method of claim 4, wherein, The determination of the simulation model of the solid-state battery comprises: based on the electrode characteristics and electrolyte characteristics of the solid-state battery, determining the solid-phase concentration diffusion characteristics; based on the discharge equilibrium potential of the solid-state battery, determining the electrode kinetics characteristics; determining the simulation model according to the solid-phase concentration diffusion characteristics, the electrode kinetics characteristics, and the charge transport characteristics.

6. The method of claim 4, wherein, The method further comprises: determining the stop condition of the simulation model according to the cutoff voltage of the solid-state battery.

7. A solid state battery parameter adjustment device, characterized by, The method comprises: a parameter acquisition module for obtaining initial parameters of a solid-state battery; a correlation determination module for determining a first correlation between the electrolyte conductivity and the battery voltage of the solid-state battery, and a second correlation between the discharge rate and the battery voltage of the solid-state battery based on the initial parameters; An adjusting parameter module is configured to adjust the initial parameter based on the first correlation and the second correlation to obtain a target parameter, wherein the performance of the solid-state battery corresponding to the target parameter is superior to the performance of the solid-state battery corresponding to the initial parameter. The adjusting parameter module is further configured to determine a discharge behavior characteristic of the solid-state battery based on the first correlation and the second correlation, determine a target conductivity required for the solid-state battery to maintain the battery voltage at a predetermined discharge rate according to the discharge behavior characteristic, and adjust the initial parameter according to the target conductivity to obtain the target parameter.

8. A non-volatile storage medium, characterized by The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by the processor to implement the solid-state battery parameter adjustment method in any one of claims 1 to 6.

9. An electronic device, comprising: The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by the processor to implement the solid-state battery parameter adjustment method in any one of claims 1 to 6. The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by the processor to implement the solid-state battery parameter adjustment method in any one of claims 1 to 6. The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by the processor to implement the solid-state battery parameter adjustment method in any one of claims 1 to 6.

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