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

Abstract

The invention discloses a solid-state battery parameter adjustment method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring an initial parameter of the solid-state battery; based on the initial parameters, determining a first correlation between the electrolyte conductivity of the solid-state battery and the battery voltage and a second correlation between the discharge rate of the solid-state battery and the battery voltage; based on the first correlation and the second correlation, the initial parameter is adjusted to obtain a target parameter, and the performance of the solid-state battery corresponding to the target parameter is better than that of the solid-state battery corresponding to the initial parameter. The technical problem that the parameter adjustment efficiency of the solid-state battery is not ideal in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of electrochemical technology, and more specifically, to a solid-state battery parameter adjustment method, device, storage medium and electronic device. Background Art

[0002] Lithium-ion batteries are facing bottlenecks in safety and performance improvement. All-solid-state batteries (ASSBs) have been considered as alternatives to 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 electrolytes, and dendrites are not easy to generate and grow in the solid interface. All-solid-state thin film laboratories do not require the addition of thermal conductors and adhesives, which reduces the performance degradation. Current experimental research mainly focuses on the design and construction of solid electrolytes. In the battery development process, there are too many design parameters and the experimental tasks are arduous. The impact of each parameter on battery performance is unclear, and the experimental design is somewhat blind. Sometimes it is even time-consuming, labor-intensive, and costly, but the battery performance is significantly improved or even negatively improved. Therefore, there is a technical problem in the related technology that the efficiency of solid-state battery parameter adjustment is not ideal.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

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

[0005] According to one aspect of an embodiment of the present application, a method for adjusting parameters of a solid-state battery is provided, comprising: obtaining initial parameters of a solid-state battery; based on the initial parameters, determining a first correlation between electrolyte conductivity of the solid-state battery and battery voltage, and a second correlation between the discharge rate of the solid-state battery and the battery voltage; 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. By quantifying the correlation, the design flexibility is improved, and the battery parameters can be flexibly adjusted 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, adjusting the initial parameters based on the first association and the second association to obtain target parameters includes: determining the discharge behavior characteristics of the solid-state battery based on the first association and the second association; determining the target conductivity required for the solid-state battery to maintain the battery voltage at a predetermined discharge rate according to the discharge behavior characteristics; and adjusting the initial parameters according to the target conductivity to obtain the target parameters. The above process helps to understand how the conductivity and discharge rate of the solid electrolyte affect the electrochemical performance of the battery, and provides guidance for the design of solid electrolytes and the optimization of battery operating conditions.

[0007] Optionally, determining the target conductivity required for the solid-state battery to maintain the battery voltage at a predetermined discharge rate according to the discharge behavior characteristics includes: determining a conductivity threshold according to the voltage drop rate indicated by the discharge behavior characteristics; and determining that the target conductivity is greater than the conductivity threshold. By setting a conductivity threshold and ensuring that the target conductivity is higher than this threshold, the rate of voltage drop during the discharge process 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 characteristics of the solid-state battery based on the first association and the second association includes: determining a third association representing the voltage drop distribution of the solid-state battery in the length direction of the battery; and determining the discharge behavior characteristics of the solid-state battery based on the first association, the second association, and the third association. Through the above process, the behavioral characteristics of solid-state batteries under different discharge conditions can be fully understood, including voltage stability, voltage drop distribution, and battery efficiency, etc. This multi-dimensional analysis helps to more accurately predict and optimize battery performance.

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

[0010] Optionally, the determination of the simulation model of the solid-state battery includes: determining the solid phase concentration diffusion characteristics based on the electrode characteristics and electrolyte characteristics of the solid-state battery; determining the electrode kinetic characteristics based on the discharge equilibrium potential of the solid-state battery; and determining the simulation model according to the solid phase concentration diffusion characteristics, the electrode kinetic characteristics, and the charge transport characteristics. The simulation model constructed based on the characteristics can more comprehensively consider various factors of the battery during 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 solid-state batteries.

[0011] Optionally, the method further comprises: determining a stop condition of the simulation model according to a cut-off voltage of the solid-state battery. By setting a stop condition that matches the actual cut-off voltage of the solid-state battery, the simulation model can more accurately capture the behavior changes of the battery during the charging and discharging process.

[0012] According to another aspect of an embodiment of the present application, a solid-state battery parameter adjustment device is provided, including: a parameter acquisition module for acquiring initial parameters of a solid-state battery; a determination association module for determining a first association between electrolyte conductivity and battery voltage of the solid-state battery, and a second association between a discharge rate of the solid-state battery and the battery voltage based on the initial parameters; and an adjustment parameter module for 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.

[0013] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided, wherein the non-volatile storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing any one of the solid-state battery parameter adjustment methods.

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

[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 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; 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 rapidly evaluating the performance of the solid-state battery is achieved, and the technical effect of optimizing the solid-state battery parameter adjustment process is achieved, thereby solving the technical problem of unsatisfactory solid-state battery parameter adjustment efficiency existing in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 is a flow chart 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] Fig. 9is an eighth schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application;

[0026] Fig.10 It 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 solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0030] COMSOL Multiphysics is a numerical simulation software with powerful multi-physics field fully coupled simulation analysis capabilities and efficient computing performance. It 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. The establishment of the P2D model can include all the basic components of lithium-ion batteries, including electrodes (positive and negative electrodes), separators, electrolytes and current collectors.

[0032] The main materials of ternary nickel cobalt manganese (NCM) are nickel, cobalt and manganese, which are synthesized through a specific process to form hydroxide. This material is used in the field of lithium batteries, especially in the positive electrode material of lithium batteries.

[0033] Direct Current (DC) polarization refers to the difference between the actual direction of an electrochemical reaction and the theoretical direction under a constant external voltage. When a constant external voltage is applied, the charge distribution on the electrode surface will be affected, causing the potential on the electrode surface to deviate from the ideal equilibrium potential, resulting in DC polarization.

[0034] Galvanostatic Intermittent Titration Technique (GITT) refers to a cyclic process of pulse-constant current-relaxation. Pulse refers to a short current flow process, and relaxation refers to a process without current flow. The basic principle is: within a unit time t, a constant current I is applied for charging or discharging, and then the current is disconnected, and the voltage changes during the constant current process and the relaxation process are recorded at the same time.

[0035] According to an embodiment of the present application, an embodiment of a method for adjusting solid-state battery parameters 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 a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0036] Figure 1 is a flow chart of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

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

[0038] It can be understood that obtaining the initial parameters of the solid-state battery provides key indicators about the basic performance of the battery and is the basis for improving the battery condition and identifying potential problems.

[0039] Optionally, the above initial parameters may be multiple, for example, the thickness of the positive electrode sheet, the thickness of the negative electrode sheet, the thickness of the electrolyte, etc. Figure 2 This is a first schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application. It is preferred to set the thickness of the positive electrode plate to 65 μm (micrometer), the thickness of the electrolyte to 45 μm, and the thickness of the negative electrode plate to 85 μm.

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

[0041] It can be understood that based on the initial parameters, the correlation between the battery voltage and the electrolyte conductivity and the discharge rate of the solid-state battery is determined as the first correlation, and the correlation between the discharge rate and the battery voltage is determined as the 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 initial parameters, a first association between electrolyte conductivity and battery voltage of a solid-state battery, and a second association between a discharge rate of the solid-state battery and battery voltage are determined, including: determining a simulation model of the solid-state battery, wherein the simulation model includes at least 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 association; inputting the initial parameters and a plurality of candidate discharge rates into the simulation model for processing to determine the second association.

[0043] It can be understood that based on the initial parameters, the 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. Multiple candidate electrolyte conductivities, multiple candidate discharge rates and initial parameters are input into the simulation model for processing to determine the association. The association between electrolyte conductivity and battery voltage is the first association, and the association between discharge rate and battery voltage is the second association. Through simulation model simulation, the number of physical experiments can be reduced and efficiency can be improved.

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

[0045] Optionally, the above-mentioned simulation experimental methods can be multiple, for example, methods and applications for predicting the electrical performance of solid-state batteries based on COMSOL simulation. The single particle model is the simplest electrochemical model of lithium-ion batteries. It is a simplified version of the P2D model. Two spherical particles are used to represent the positive and negative electrodes of the lithium-ion battery respectively. It is assumed that the insertion and extraction process of lithium ions occurs on the spherical particles, and the concentration of the electrolyte and its internal potential are considered to be constant. The single particle model has a simple structure, a small amount of calculation, and is easy to implement online applications. Build a lithium-ion battery with a solid electrolyte. The geometry is one-dimensional linear, the negative electrode material is graphite, the positive electrode material is ternary nickel-cobalt-manganese (NCM), and the electrolyte is a solid electrolyte with different conductivity. Analyze the battery behavior under different discharge rates and solid electrolyte conductivity.

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

[0047] Optionally, use 320μm NCM positive electrode sheet and LPSClBr (Li3PS4, i.e. lithium sulfide phosphate) solid electrolyte to assemble NCM mold half-cell. In the same way, use 150μm graphite negative electrode sheet and LPSClBr solid electrolyte to assemble graphite mold half-cell. Use electrochemical workstation, set test voltage 10mV, test time 30min (minutes), perform DC polarization test, after the test is completed, disassemble the battery mold, take out the electrode sheet and test the thickness d NCM =0.043cm(cm), d 石墨 = 0.019 cm, the obtained polarization curve is as follows Figure 3 As shown, Figure 3 It is a second schematic diagram of an optional solid-state battery parameter adjustment method provided in an embodiment of the present application, and the DC polarization curves of the positive and negative electrodes tested. The current-voltage relationship of the electrode material in the DC polarization test is depicted. The DC 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 infer the size of the conductivity. Conductivity is an important indicator of the ion and electron transport capacity of the electrode material. It shows the potential change of the electrode material under different lithium ion concentrations (or state of charge SOC). The equilibrium potential curve is crucial to understanding the electrochemical reaction of the electrode material during the charge and discharge process, and reflects the electrochemical potential energy of the electrode material under different states of charge.

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

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

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

[0051] The NCM half-cell was then charged to the cut-off voltage, discharged at 0.1C for 15 min, left standing for 30 min, discharged at 0.1C for 15 min, left standing for 30 min, and repeated 40 times. D was calculated using mathematical expression. s ;

[0052]

[0053] Among them, D s Represents the positive and negative electrode solid phase diffusion coefficient, n M represents the number of moles of the substance involved in the diffusion process, V M Refers to the volume occupied by a unit mole of substance, S refers to the effective surface area of ​​the electrode material, ΔV sThe voltage change in the solid, measured in V, reflects the change in the internal potential of the solid during the charge and discharge process of the battery. ΔV t Refers to the change in the voltage of the entire system during the charge and discharge process of the battery, including the voltage change of the solid and electrolyte. τ is the time constant.

[0054] 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, showing a calculation method of GITT, such as Figure 4 As shown in the figure, the battery is pulse-discharged for 15 minutes, left to stand for 30 minutes, and repeated until the battery power is 0. Among them, the change from V1 to V2 occurs immediately after the current is loaded. The voltage drop mainly comes from the ohmic impedance and charge exchange impedance. Then the battery voltage slowly drops to V3. V2-V3 is ΔV t , is the change in the voltage of the entire system during the charge and discharge process, representing 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 in the steady-state voltage of the battery in the static state before and after the two charge and discharge processes is ΔV s .

[0055] Figure 5 This is a fourth schematic diagram of an optional solid-state battery parameter adjustment method provided in an embodiment of the present application, and the tested positive and negative electrode equilibrium potential curves show the potential changes of the electrode material under different lithium ion concentrations (or states of charge SOC). The equilibrium potential curve is crucial to understanding the electrochemical reaction of the electrode material during the charge and discharge process, and reflects the electrochemical potential energy 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 solid phase concentration diffusion characteristics based on electrode characteristics and electrolyte characteristics of the solid-state battery; determining electrode kinetic characteristics based on the discharge equilibrium potential of the solid-state battery; and determining a simulation model according to the solid phase concentration diffusion characteristics, electrode kinetic characteristics, and charge transport characteristics.

[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. Fick's law is used to describe the diffusion process of lithium ions in electrode materials (such as NCM positive electrode and graphite negative electrode), which reflects the transmission speed of lithium ions inside the electrode particles. It is an important factor affecting the charge and discharge rate and efficiency of solid-state batteries, and can include parameters such as the diffusion coefficient of the input material. The electrode kinetic characteristics are determined using the discharge equilibrium potential of the solid-state battery. According to factors such as the properties, reaction rate and potential of the electrode material, the behavior of the battery at different states of charge needs to be determined, and the equilibrium potential and other kinetic parameters of the electrode material need to be input. Ohm's law can also be used to describe the transport of 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 charge in the electrode and electrolyte. According to the solid phase concentration diffusion characteristics, electrode kinetic characteristics and charge transport characteristics, the simulation model is determined. The simulation model constructed based on the characteristics can more comprehensively consider various factors in the battery during the charge and discharge process and more accurately predict the performance of the battery. Through the simulation model, the battery behavior 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 solid-state batteries.

[0058] Since the charge inside the battery is conserved, Ohm's law is used to describe the charge transport in the electrodes and electrolytes. The conductivity σ determines the potential The magnitude of the current caused by the gradient, the cross-sectional area a s and the Faraday constant F, which is related to the electrochemical reaction rate at the electrode interface, and the current density j n Reflects the dynamic changes of these electrochemical processes:

[0059]

[0060] Where σ is the conductivity in S / m, which describes the ability of a material to conduct electricity. is the potential of the electrode, in V (volts), which is a key indicator of charge distribution inside the battery. x is a spatial coordinate, usually representing the one-dimensional length of the battery, in m (meters), a s It 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. F is the Faraday constant, which is approximately equal to 96485C / mol (coulomb per mole), describing the charge of one mole of electrons. n is the current density, usually in A / m 2 (amperes per square meter), which reflects the battery's charge and discharge rate.

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

[0062]

[0063] c s The concentration of a substance in the solid phase, in mol / m 3 (mole per cubic meter), which reflects the lithium ion content per unit volume. t is time, in seconds, which represents the time variable of lithium ion diffusion. s Solid phase diffusion coefficient, unit is m 2 / s (square meters per second), which describes the diffusion rate of lithium ions in the electrode material. r is the radius coordinate inside the spherical particle, in m (meter), which is 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, which is used to describe the nonlinear relationship between the rate of lithium ion insertion / extraction on the electrode surface and the potential and 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 potential changes, and is a key equation for understanding the electrochemical reaction rate during battery charging and discharging:

[0065]

[0066] in, The discharge curves using the experimentally measured equilibrium potentials were substituted into the calculations.

[0067] η represents the reaction overpotential, the unit is V (volt), which is the difference between the two-phase potentials minus the kinetic equilibrium potential. The solid phase potential at any point in the model can be obtained by Ohm's law, and the equilibrium potential Eeq 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. r is the reaction current density on the electrode surface, in A / m 2 (ampere per square meter), reflects the rate of electrochemical reaction. s is the solid phase reaction active area. i0 is the exchange current density, in A / m 2(ampere per square meter), represents the reaction rate at equilibrium. αa and αc are the charge transfer coefficients of the anode and cathode, dimensionless, describing the insertion / extraction process of lithium ions on the electrode surface. T is the absolute temperature, the unit is K (Kelvin), and the temperature affects the rate of electrochemical reactions. R is the ideal gas constant, approximately equal to 8.314 J / (mol·K) (joule per mole Kelvin), which plays a role in regulating the temperature effect in the electrochemical reaction kinetics.

[0068] The above mathematical expressions together constitute the core of the solid-state battery simulation model. By solving these equations by numerical methods, the voltage behavior of solid-state batteries under different conditions (such as different electrolyte conductivities and discharge rates) can be simulated, thereby realizing the prediction and optimization of battery performance.

[0069] In an optional embodiment, the method further includes: determining a stop condition of the simulation model according to a cut-off voltage of the solid-state battery.

[0070] It can be understood that the stop condition of the simulation model is determined according to the cut-off voltage of the solid-state battery, such as 2V, which is related to the performance of the specific battery. By setting the stop condition to match the actual cut-off voltage of the solid-state battery, the simulation model can more accurately capture the changes in the battery's behavior during the charging and discharging process.

[0071] Step S106, based on the first association and the second association, 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.

[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 optional embodiment, based on the first association and the second association, the initial parameters are adjusted to obtain the 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 at a predetermined discharge rate; according to the target conductivity, adjusting the initial parameters 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 association and the second association, the discharge behavior characteristics of the solid-state battery are obtained. Based on the analyzed discharge behavior characteristics, the target value that the electrolyte conductivity needs to reach at a specific discharge rate in order to keep the battery voltage stable is determined in the embodiment. By comparing the simulation results under different conductivities, the threshold value at which the conductivity has the greatest impact on voltage stability is identified. Determine the target conductivity required for the solid-state battery to maintain the battery voltage at a predetermined discharge rate, adjust the initial parameters, and obtain the target parameters. According to the determined target conductivity, adjust the initial design parameters of the solid-state battery, such as the material formula or structural design of the electrolyte, to achieve the optimized target parameters. The solid-state battery adjusted in this way will have better electrochemical performance, especially better performance under high-power applications, which helps to understand how the solid-state electrolyte conductivity and discharge rate affect the electrochemical performance of the battery, and provide guidance for the design of solid-state electrolytes and the optimization of battery operating conditions.

[0075] Optionally, when determining the first correlation between electrolyte conductivity and battery voltage, a curve of battery voltage variation over time at different conductivity values ​​can be obtained. Similarly, the second correlation between discharge rate and battery voltage shows the stability of battery voltage at different discharge rates.

[0076] Alternatively, when the electrolyte conductivity is below a certain value, the battery voltage drops significantly at a high discharge rate, while when the conductivity increases to or exceeds 1 S / m, the battery voltage is able to remain at a high level, demonstrating the significant impact of high conductivity on battery performance.

[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 at a predetermined discharge rate is determined, including: determining the conductivity threshold according to the voltage drop rate indicated by the discharge behavior characteristics; and determining that the value of the target conductivity is 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 rate of voltage drop during the discharge process 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 1S / m, that is, below this value, the voltage stability of the battery will be affected. The target conductivity value should be higher than or equal to the determined conductivity threshold, which means that the conductivity of the solid electrolyte should be optimized to at least 1S / m to ensure that the solid-state battery can maintain a stable voltage at a high discharge rate and reduce voltage drop and polarization.

[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 of the solid-state battery representing the voltage drop distribution in the length direction of the battery; based on the first association, the second association, and the third association, determining the discharge behavior characteristics of the solid-state battery.

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

[0082] Optionally, by plotting the curve of electrolyte voltage drop versus battery length, a third correlation representing the voltage drop distribution in the battery length direction is determined for the solid-state battery. Through the one-dimensional plot group, the electrolyte voltage drop curves are created at different discharge rates when the electrolyte conductivity is 0.02S / m and 1S / m. 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, extend battery life, and increase energy density and power density. For example, when the conductivity of the solid electrolyte reaches or exceeds 1S / m, at a 4C discharge rate, the battery voltage can be maintained at a high level, reducing internal losses. The performance characteristics of solid-state batteries at different discharge rates and conductivities have been determined, providing a specific direction for the research and development of solid-state electrolyte materials, that is, the focus should be on the research and development of solid-state electrolytes with a conductivity greater than or equal to 1S / m, providing optimization ideas for the adjustment 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, 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; step S106, based on the first correlation and the second correlation, the initial parameters are adjusted to obtain the 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 solid-state battery parameter adjustment process is achieved, thereby solving the technical problem of unsatisfactory solid-state battery parameter adjustment efficiency existing in the related art.

[0085] Based on the above embodiments and optional embodiments, the present application proposes an optional implementation method. By respectively focusing on the parameter measurement, performance prediction and behavioral characteristic analysis of solid-state batteries, a systematic and scientific solid-state battery performance optimization scheme is jointly formed. Method and application based on COMSOL simulation prediction of solid-state battery electrical performance. The key physicochemical parameters of electrode materials and electrolytes in solid-state batteries are obtained by experimental means, including conductivity, equilibrium potential and solid phase diffusion coefficient. It covers DC 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] Select graphite electrode for negative electrode and NCM electrode for positive electrode, input property parameters such as conductivity, equilibrium potential, diffusion coefficient, reference concentration, etc. into the electrode material, and apply the material to the corresponding geometric line segment domain. Among them, conductivity, equilibrium potential, and diffusion coefficient are obtained according to actual experimental measurements, and reference concentration is obtained through theoretical calculations. Direct current polarization (DC), low-rate charge and discharge cycles, and constant current intermittent titration (GITT) can be used to test battery material properties, and model material parameters can be obtained through relevant electrochemical calculation methods.

[0087] Figure 6 The fifth schematic diagram of an optional solid-state battery parameter adjustment method provided in accordance with an embodiment of the present application, showing the GITT curves of the positive and negative electrodes and the calculation method. The test results of the constant current intermittent titration method (GITT) are shown, and the solid phase diffusion coefficient of the battery material can be measured by GITT. The GITT curve includes the voltage changes of the battery during the constant current discharge and static stages.

[0088] Figure 6 The child Figure 1 This is the graphite negative electrode charging curve tested by constant current intermittent titration method. Figure 2 This is the discharge curve of NCM cathode tested by constant current intermittent titration method. Figure 3 , 4 They are respectively partial enlarged diagrams of voltage changes during the charging and discharging process. Figure 6 The potential data can be obtained by using the formula Calculate the solid phase diffusion coefficient of the corresponding material.

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

[0090]

[0091] Among them, σ eff，- and σ eff，+ They represent the effective conductivity of the negative electrode and positive electrode materials respectively. The effective conductivity is a comprehensive indicator that not only reflects the conductivity characteristics of the material itself, but also takes into account the influence of the electrode structure composition on the conductivity.

[0092] x = 0 (indicates the position of the negative electrode boundary), x = L (indicates the position of the positive electrode boundary, L is the battery thickness), the rate of change of the internal potential of the electrode material with position. The potential gradient describes the change of potential in space and 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 capacity of the battery per unit area. represent the surface potentials of the negative and positive electrodes, respectively.

[0093] In solid-state batteries, the product of the effective conductivity of the negative and positive electrode materials and the potential gradient inside the electrode, at the locations of the negative and positive electrodes, respectively, is equal to the average current density through the battery. This shows that the current density inside the battery is maintained and controlled by the relationship between the effective conductivity of the electrode and the potential gradient. In essence, it reflects Ohm's law of resistance and current flowing through the electrode in solid-state battery electrodes, that is, the current density is the product of conductivity and potential gradient. In order to ensure that the current density inside the battery is constant, the electrode material needs to have a specific effective conductivity to adapt to changes in the potential gradient. During the battery charging and discharging process, 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 and reduce the voltage drop and energy loss inside the battery.

[0094] Add the lithium-ion battery physics field and generate the electrolyte, porous electrode and particle intercalation components, customize the conductivity, active material fraction and particle diameter, the active fraction is automatically calculated by the initial unit charge distribution node, add the porous electrode reaction, define the electrode kinetics, add the initial battery charge distribution, and enter the initial state of charge (SOC) and initial capacity (Q) values. The negative collector is used as the reference, and the boundary condition is selected as electrical grounding. At the positive collector, select Apply electrode current. The 1C current can be obtained from the initial battery charge distribution node.

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

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

[0097] Select the data one by one and add a one-dimensional plot group. For different discharge rates, create battery voltage curves at electrolyte conductivity of 0.02S / m and 1S / m. 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, such as Figure 7 As shown, the battery voltage curve diagram under different conductivities and discharge rates may include multiple groups of curves, which correspond to the battery voltage change curves over time at different discharge rates (such as 1C, 2C and 4C) of different conductivities of solid electrolytes (such as 0.02S / m and 1S / m), which are helpful for analyzing the influence of conductivity and discharge rate on battery performance. Figure 6 The first set of parameters was selected for conductivity, i.e. 0.02S / m as the dependent variable, all parameters were selected for discharge rate, the y-axis data expression was input as the battery potential, and the discharge curves of 0.02S / m solid electrolyte at 1, 2, and 4C were obtained.

[0098] Electrolyte voltage drop curves of different solid electrolyte conductivity values ​​at 1C rate The curves of electrolyte voltage drop changing with battery length correspond to electrolytes with low conductivity (such as 0.02S / m) and high conductivity (such as 1S / m), which are helpful to understand the influence of electrolyte conductivity on voltage drop distribution. All parameters are selected for discharge rate, and the y-axis data expression is input as battery potential to obtain the discharge curves of 1S / m solid electrolyte at 1, 2, and 4C. By comparing the figure, it can be seen that when the electrolyte conductivity is higher, the battery performance is better, which verifies that the higher the conductivity, the lower the battery polarization and the lower the internal loss.

[0099] 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, such as Figure 8 As shown, for different values ​​of electrolyte conductivity, the battery voltage curves at 1C and 4C are created. Create a graph describing the electrolyte voltage drop at different conductivity values ​​at 1C rate, and the change of battery voltage over time, especially under fixed discharge rate conditions (such as 1C and 4C). By comparison, the degree of influence of conductivity on battery performance can be observed. Figure 8 Select all parameters for conductivity in the left sub-graph, select the first set of parameters for discharge rate, i.e. 1C, input the y-axis data expression as the battery potential, and obtain the discharge curves for different electrolyte conductivity values ​​at 1C. Figure 8 In the right sub-graph, select all parameters for conductivity, select the last set of parameters, i.e. 4C, and input the battery potential as the data expression on the y-axis to obtain the discharge curves for different electrolyte conductivity values ​​at 4C. Compare the discharge curves for different electrolyte conductivity values ​​at 1C and 4C. Comparing the graphs, it can be verified that the conductivity at high rate (4C) has a more significant effect on the battery's voltage curve; while at low rate 1C, when the electrolyte conductivity is 0.25-1.5S / m, there is almost no difference in the discharge behavior. Therefore, in the current system, on the solid electrolyte material side, the research and development of a conductivity of 1S / m can meet the charging and discharging requirements at a rate of 4C.

[0100] Fig. 9 is an eighth schematic diagram of an optional solid-state battery parameter adjustment method provided according to an embodiment of the present application, such as Fig. 9 As shown, Fig. 9 The conductivity of the left sub-graph selects the first set of parameters, that is, 0.02S / m, and the discharge rate selects the first set of parameters, that is, 1C. The x-axis is set to the battery length and the y-axis is set to the electrolyte voltage drop. The electrolyte voltage drop curve describing the conductivity value of 0.02S / m at a rate of 1C is obtained; Fig. 9 In the right sub-graph, the conductivity selects the first set of parameters, i.e. 1S / m, and the discharge rate selects the first set of parameters, i.e. 1C. The x-axis is set to the battery length, and the y-axis is set to the electrolyte voltage drop, to obtain the electrolyte voltage drop curve describing the 1S / m conductivity value at a 1C rate. Compare the electrolyte voltage drop curves of 0.02S / m and 1S / m conductivity values ​​at a 1C rate. Comparing the voltage change curves of the spatial scale of this figure, it is verified that the lower the conductivity, the greater the voltage drop in both the time and space dimensions. Therefore, the research and development of solid electrolytes with a conductivity greater than or equal to 1S / m should be emphasized in this system.

[0101] The above optional implementation method achieves at least the following effects: For solid-state batteries, the single-particle model is used to effectively simplify the battery structure, and the influence mechanism of solid electrolyte conductivity on the battery discharge process is quickly and clearly revealed by scanning different discharge rates and different solid electrolyte conductivities, and the test and calculation methods of the parameters in the model are clarified. From parameter acquisition to model construction and completion of simulation calculations, the time and material costs of battery testing are greatly saved, providing an important support for guiding the direction of research and development and accelerating the research and development process.

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

[0103] In this embodiment, a solid-state battery parameter adjustment device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated here. As used below, the terms "module" and "device" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0104] According to an embodiment of the present application, a device embodiment for implementing a solid-state battery parameter adjustment method is also provided. Fig.10 is a schematic diagram of an optional solid-state battery parameter adjustment device provided according to an embodiment of the present application, such as Fig.10 As shown, the above-mentioned solid-state battery parameter adjustment device includes a parameter acquisition module 1002, a correlation determination module 1004, and a parameter adjustment module 1006. The device is described below.

[0105] A parameter acquisition module 1002 is used to acquire initial parameters of the solid-state battery;

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

[0107] The parameter adjustment module 1006 is connected to the association determination module 1004, and is used to adjust the initial parameters based on the first association and the second association to obtain the 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] In a solid-state battery parameter adjustment device provided in an embodiment of the present application, a parameter acquisition module 1002 is set to obtain the initial parameters of the solid-state battery; a determination association module 1004 is connected to the parameter acquisition module 1002, and is used to determine the first association between the electrolyte conductivity of the solid-state battery and the battery voltage, and the second association between the discharge rate of the solid-state battery and the battery voltage based on the initial parameters; an adjustment parameter module 1006 is connected to the determination association module 1004, and is used to adjust the initial parameters based on the first association and the second association to obtain the 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, and the technical effect of optimizing the solid-state battery parameter adjustment process is achieved, thereby solving the technical problem of unsatisfactory efficiency of solid-state battery parameter adjustment existing in the related art.

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

[0110] It should be noted that the above-mentioned acquisition parameter module 1002, determination association module 1004, and adjustment parameter module 1006 correspond to steps S102 to S106 in the embodiment, and the examples and application scenarios implemented by the above-mentioned modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned embodiment. It should be noted that the above-mentioned modules can be run in a computer terminal as part of the device.

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

[0112] The above-mentioned solid-state battery parameter adjustment device may also include a processor and a memory. The parameter acquisition module 1002, the association determination module 1004, the parameter adjustment module 1006, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

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

[0114] An embodiment of the present application provides a non-volatile storage medium on which a program is stored, and when the program is executed by a processor, a method for adjusting parameters of a solid-state battery is implemented.

[0115] The embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and can be run on the processor. When the processor executes the program, the following steps are implemented: obtaining initial parameters of a solid-state battery; based on the initial parameters, 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 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 device in the present application can be a server, a PC, etc.

[0116] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having the following method steps: obtaining initial parameters of a solid-state battery; based on the initial parameters, determining a first correlation between the electrolyte conductivity of the solid-state battery and the battery voltage, and a second correlation between the discharge rate of the solid-state battery and the battery voltage; 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.

[0117] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0118] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, 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 device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0119] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0120] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

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

[0122] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0123] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be 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 erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0124] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0125] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0126] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A solid-state battery parameter adjustment method, characterized in that: include: Obtaining initial parameters of solid-state batteries; Based on the initial parameters, determining a first correlation between electrolyte conductivity and battery voltage of the solid-state battery, and a second correlation between a discharge rate of the solid-state battery and the battery voltage; Based on the first association and the second association, 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.

2. The method according to claim 1, characterized in that The adjusting the initial parameter based on the first association and the second association to obtain the target parameter includes: Determining a discharge behavior characteristic of the solid-state battery based on the first association and the second association; According to the discharge behavior characteristics, determining a target conductivity required for the solid-state battery to maintain the battery voltage at a predetermined discharge rate; The initial parameters are adjusted according to the target conductivity to obtain the target parameters.

3. The method according to claim 2, characterized in that The step of determining, according to the discharge behavior characteristics, a target conductivity required for the solid-state battery to maintain the battery voltage at a predetermined discharge rate comprises: determining a conductivity threshold according to a voltage drop rate indicated by the discharge behavior characteristic; The target conductivity is determined to be greater than the conductivity threshold.

4. The method according to claim 2, characterized in that: The determining, based on the first association and the second association, a discharge behavior characteristic of the solid-state battery includes: Determining a third association of the solid-state battery representing a voltage drop distribution in a 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.

5. The method according to any one of claims 1 to 4, characterized in that: The determining, based on the initial parameters, a first correlation between the electrolyte conductivity of the solid-state battery and the battery voltage, and a second correlation between the discharge rate of the solid-state battery and the battery voltage, 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 a first association; The initial parameters and a plurality of candidate discharge rates are input into the simulation model for processing to determine a second association.

6. The method according to claim 5, characterized in that Determining the simulation model of the solid-state battery includes: Determining solid phase concentration diffusion characteristics based on electrode characteristics and electrolyte characteristics of the solid-state battery; determining electrode kinetic characteristics based on the discharge equilibrium potential of the solid-state battery; The simulation model is determined according to the solid phase concentration diffusion characteristics, the electrode kinetic characteristics, and the charge transport characteristics.

7. The method according to claim 5, characterized in that The method further comprises: The stopping condition of the simulation model is determined according to the cut-off voltage of the solid-state battery.

8. A solid-state battery parameter adjustment device, characterized in that: include: A parameter acquisition module is used to obtain the initial parameters of the solid-state battery; A determination association module, configured to determine, based on the initial parameters, a first association between the electrolyte conductivity of the solid-state battery and the battery voltage, and a second association between the discharge rate of the solid-state battery and the battery voltage; A parameter adjustment module is used 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.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the solid-state battery parameter adjustment method described in any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the solid-state battery parameter adjustment method described in any one of claims 1 to 7.

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