An all-solid-state battery simulation method, device and equipment

Abstract

The application provides a kind of all-solid-state battery simulation method, device and equipment, it is related to all-solid-state battery simulation technical field.The method comprises: according to the parameter data of target all-solid-state battery, the coupling simulation model of target all-solid-state battery is constructed.According to the current interface state variable, the interface calculation information of target all-solid-state battery is updated.Based on interface calculation information and coupling simulation model, determine the simulation data of target all-solid-state battery under target working condition.According to simulation data and the test data of target all-solid-state battery collected under target working condition, update interface state variable, repeat the above simulation test, until after meeting the set condition according to simulation test determines the simulation result of target all-solid-state battery, can solve the problem that the accuracy of traditional simulation method is lower to all-solid-state battery performance analysis and life assessment.

Description

Technical Field

[0001] This application relates to the field of all-solid-state battery simulation technology, and in particular to an all-solid-state battery simulation method, apparatus and equipment. Background Technology

[0002] All-solid-state batteries use sulfide, oxide, halide, polymer, or composite solid electrolytes instead of traditional liquid electrolytes, offering higher safety and energy density. In all-solid-state batteries, ion transport and electrochemical reactions occur between the electrodes and the solid electrolyte through a solid-solid interface. The contact state and impedance of the solid-solid interface change during battery operation due to factors such as interface roughness, assembly pressure, material expansion and contraction, temperature variations, interfacial side reactions, and cycle aging.

[0003] Traditional all-solid-state battery simulation methods typically simulate the battery's electrochemical response, temperature changes, stress changes, or capacity decay based on pre-set reaction area, interfacial impedance, and material parameters. Because pre-set interfacial parameters are difficult to synchronize with the battery's operating conditions, traditional simulation methods struggle to accurately reflect the impact of changes in interfacial contact and impedance on the battery's reaction process, polarization, heat generation, and lifespan degradation. This leads to discrepancies between simulation data obtained under target operating conditions and actual battery test data, affecting the accuracy of all-solid-state battery performance analysis and lifespan assessment. Summary of the Invention

[0004] The purpose of this application is to provide a method, apparatus, and equipment for simulating all-solid-state batteries, thereby solving the problem of low accuracy of traditional simulation methods in the performance analysis and life assessment of all-solid-state batteries.

[0005] In a first aspect, embodiments of this application provide a simulation method for an all-solid-state battery. The method includes: constructing a coupled simulation model of the target all-solid-state battery based on parameter data of the target all-solid-state battery. The coupled simulation model includes interface units disposed between specified materials within the target all-solid-state battery and interface state variables characterizing the interface change characteristics at corresponding positions of the interface units. The interface calculation information of the target all-solid-state battery is updated based on the current interface state variables. The interface calculation information is used to characterize the impact of interface changes at corresponding positions of the interface units on the operation of the target all-solid-state battery. Based on the interface calculation information and the coupled simulation model, simulation data of the target all-solid-state battery under target operating conditions is determined. Based on the simulation data and test data of the target all-solid-state battery collected under target operating conditions, the interface state variables are updated, and the above simulation test is repeated until the set conditions are met, after which the simulation result of the target all-solid-state battery is determined based on the simulation test.

[0006] The all-solid-state battery simulation method provided in this application constructs a coupled simulation model of the target all-solid-state battery based on its parameter data. The interface calculation information of the target all-solid-state battery is updated according to the current interface state variables. The interface state variables are then updated based on simulation and test data under the same target operating conditions, and the updated interface state variables are fed back to subsequent simulation tests until the set conditions are met. The simulation results of the target all-solid-state battery are then determined based on the simulation tests. This method reduces the deviation between simulation and test data caused by using fixed interface parameters, allowing the simulation model to adjust according to the actual interface changes of the target all-solid-state battery, thereby improving the accuracy of the all-solid-state battery simulation results.

[0007] One possible implementation involves constructing a coupled simulation model of the target all-solid-state battery based on its parameter data. This includes: constructing a battery model domain containing a positive electrode composite layer, a solid electrolyte layer, a negative electrode layer, and interface units based on the cell structure data in the parameter data; determining the electrochemical, mechanical, thermal, and aging calculation conditions corresponding to the battery model domain based on the material and process data in the parameter data; establishing the coupling relationships between the reaction current and concentration changes generated during electrochemical calculations, the contact pressure and stress changes generated during mechanical calculations, the temperature changes generated during thermal calculations, and the interface degradation information generated during aging calculations; and constructing a coupled simulation model based on the battery model domain, electrochemical calculation conditions, mechanical calculation conditions, thermal calculation conditions, aging calculation conditions, and the coupling relationships.

[0008] One possible implementation involves interface state variables including the true interface contact coefficient. The process of determining the true interface contact coefficient includes: determining the effective contact pressure of the interface unit based on the external stacking pressure, pressure changes caused by chemical expansion, pressure changes caused by thermal expansion, and pressure changes caused by pore relaxation. Based on the effective contact pressure, the interface roughness, and the interface film thickness, the equilibrium contact coefficient of the interface unit is determined. Based on the difference between the equilibrium contact coefficient and the true interface contact coefficient at the previous simulation time, the interface contact recovery is determined. Based on the tensile stress of the interface unit and the cycling history of the target all-solid-state battery, the interface contact loss is determined. Based on the interface contact recovery and interface contact loss, the true interface contact coefficient at the current simulation time is determined.

[0009] One possible implementation includes an interface state variable: interface film resistance. The process of determining the interface film resistance includes: determining the corresponding side reaction current of the interface unit based on the side reaction overpotential and temperature; determining the first influence of interface side reaction film growth on the interface film resistance based on the side reaction current and temperature; determining the second influence of interface cracking on the interface film resistance based on the tensile stress and cracking / debonding state of the interface unit; determining the third influence of interface contact recovery on the interface film resistance based on the actual interface contact coefficient and the interface impedance at the previous simulation time; and determining the interface film resistance at the current simulation time based on the interface film resistance at the previous simulation time, the first influence, the second influence, and the third influence.

[0010] One possible implementation involves the interface state variables further including a comprehensive damage index. The process of determining the comprehensive damage index includes: determining the degree of interface contact damage based on the relationship between the actual interface contact coefficient and a preset allowable contact coefficient value; determining the degree of interface film resistance damage based on the relationship between the interface film resistance and the initial interface film resistance and a preset film resistance limit; determining the degree of stress damage, temperature damage, and capacity damage based on the equivalent stress, maximum temperature, and capacity decay of the target all-solid-state battery, respectively; and determining the comprehensive damage index based on the degree of interface contact damage, the degree of interface film resistance damage, the degree of stress damage, the degree of temperature damage, and the degree of capacity damage, as well as the damage weights corresponding to each degree of damage.

[0011] One possible implementation involves calculating lifespan degradation information on the interface. The process for determining lifespan degradation information includes: determining the lifespan degradation information based on the changes in a comprehensive damage index during the cyclic process.

[0012] One possible implementation involves further calculating the interface information, including: effective reaction area, equivalent interface impedance, effective overpotential, and contact heat source. The interface calculation information of the target all-solid-state battery is updated based on the current interface state variables, including: determining the true contact area based on the nominal interface area and the true interface contact coefficient; determining the reaction current density corresponding to the nominal interface area based on the true contact area, the nominal interface area, and the reaction current density corresponding to the true contact area, while maintaining a consistent total reaction current; determining the effective reaction area based on the true interface contact coefficient and the nominal reaction area of ​​the interface unit; determining the equivalent interface impedance based on the area relationship between the true and nominal interface areas, the interface film resistance, and the contact contraction impedance corresponding to the interface unit; determining the effective overpotential based on the reaction current density corresponding to the nominal interface area, the equivalent interface impedance, the potentials on both sides of the interface unit, the equilibrium potential, and the potential change caused by stress; and determining the contact heat source based on the reaction current density corresponding to the nominal interface area, the equivalent interface impedance, and the nominal unit volume interface area of ​​the interface unit.

[0013] One possible implementation involves determining the simulation data of the target all-solid-state battery under target operating conditions based on interface calculation information and a coupled simulation model. This includes: inputting the operating condition data and interface calculation information corresponding to the target operating conditions into the coupled simulation model; determining the reaction current, terminal voltage, and lithium concentration distribution of the target all-solid-state battery based on the effective reaction area, equivalent interfacial impedance, and effective overpotential; determining the temperature distribution of the target all-solid-state battery based on the reaction current, contact heat source, and thermal boundary conditions of the target all-solid-state battery; determining the contact pressure distribution, stress distribution, and thickness variation of the target all-solid-state battery based on the lithium concentration distribution, temperature distribution, and stacking pressure corresponding to the target operating conditions; determining the impedance and capacity variations of the target all-solid-state battery based on the aging calculation conditions of the coupled simulation, interfacial film resistance, and the cycling state of the target all-solid-state battery; and determining the simulation data based on the terminal voltage, temperature distribution, contact pressure distribution, thickness variation, impedance variation, and capacity variation.

[0014] One possible implementation involves testing data including terminal voltage test data, surface temperature test data, stacking pressure test data, thickness change test data, electrochemical impedance spectroscopy (EIS) test data, and capacity test data. Based on simulation data and test data of the target all-solid-state battery collected under target operating conditions, interface state variables are updated, including: determining the contact coefficient update amount corresponding to the true interface contact coefficient based on the differences between the stacking pressure test data and thickness change test data and their corresponding simulation data, and the differences between the interface impedance characteristics in the EIS test data and their corresponding simulation data. Determining the membrane resistance update amount corresponding to the interface membrane resistance based on the differences between the terminal voltage test data and their corresponding simulation data, and the differences between the interface impedance characteristics and their corresponding simulation data. Determining the damage index update amount corresponding to the comprehensive damage index based on the updated true interface contact coefficient and interface membrane resistance, and the differences between the surface temperature test data and capacity test data and their corresponding simulation data. Finally, updating the true interface contact coefficient, interface membrane resistance, and comprehensive damage index of the interface unit based on the contact coefficient update amount, membrane resistance update amount, and damage index update amount.

[0015] One possible implementation involves updating the interface state variables based on simulation data and test data of the target all-solid-state battery collected under target operating conditions. This includes: determining state sensitivity information based on the changes in the actual contact coefficient, interfacial film resistance, and comprehensive damage index of each simulation data point; determining an information matrix based on the state sensitivity information and the test weights corresponding to each test data point; determining the identifiability results corresponding to the actual contact coefficient, interfacial film resistance, and comprehensive damage index based on the state sensitivity information and the information matrix; determining the target state variables to be updated from the actual contact coefficient, interfacial film resistance, and comprehensive damage index based on the identifiability results; updating the target state variables according to the state update amounts corresponding to each target state variable, while maintaining the remaining interface state variables at their corresponding prior state values.

[0016] One possible implementation involves simulation results including a pressure window corresponding to the target all-solid-state battery. The process of determining the pressure window includes: setting multiple candidate stacking pressures; updating interface state variables and interface calculation information based on any candidate stacking pressure; inputting the operating data corresponding to the candidate stacking pressure and the updated interface calculation information into the coupled simulation model to determine the minimum true contact coefficient, maximum contact heat source, equivalent stress, and comprehensive damage index of the cell corresponding to the candidate stacking pressure; determining the pressure constraint results corresponding to the candidate stacking pressure based on the minimum true contact coefficient, maximum contact heat source, equivalent stress, and comprehensive damage index; selecting the target stacking pressure from the multiple candidate stacking pressures whose pressure constraint results satisfy the preset pressure window conditions; and determining the pressure window based on the target stacking pressure.

[0017] One possible implementation involves simulation results that also include interface risk results and remaining service life. The process of determining the interface risk results includes: determining the interface risk results corresponding to the target all-solid-state battery based on the actual interface contact coefficient, interface film resistance, contact heat source, equivalent stress, and comprehensive damage index. The process of determining the remaining service life includes: determining the first predicted time when the comprehensive damage index reaches the preset failure state based on the trend of the comprehensive damage index during cycling; determining the second predicted time when the battery capacity reaches the preset capacity decay state based on the capacity decay trend of the target all-solid-state battery; and determining the remaining service life based on the first predicted time, the second predicted time, and the current cycle time of the target all-solid-state battery.

[0018] Secondly, embodiments of this application provide an all-solid-state battery simulation device, which includes a construction module, an update module, and a determination module.

[0019] The construction module is used to build a coupled simulation model of the target all-solid-state battery based on its parameter data. The coupled simulation model includes interface units set between specified materials within the target all-solid-state battery and interface state variables characterizing the interface change characteristics at the corresponding positions of the interface units.

[0020] The update module is used to update the interface calculation information of the target all-solid-state battery based on the current interface state variables. The interface calculation information is used to characterize the impact of interface changes at corresponding positions of interface units on the operation of the target all-solid-state battery.

[0021] The determination module is used to determine the simulation data of the target all-solid-state battery under the target operating conditions based on the interface calculation information and the coupled simulation model.

[0022] The determination module is also used to update the interface state variables based on the simulation data and the test data of the target all-solid-state battery collected under the target operating conditions, repeat the above simulation test until the set conditions are met, and then determine the simulation result of the target all-solid-state battery based on the simulation test.

[0023] Thirdly, embodiments of this application provide an all-solid-state battery simulation device, which has the function of implementing the all-solid-state battery simulation method of the first aspect or any possible implementation of the first aspect. This function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above-described function.

[0024] Fourthly, embodiments of this application provide a computer-readable storage medium storing instructions that, when executed on a computer, enable the computer to perform the all-solid-state battery simulation method described in the first aspect or any possible implementation thereof.

[0025] Fifthly, embodiments of this application provide a computer program product containing instructions that, when run on a computer, enable the computer to execute the all-solid-state battery simulation method described in the first aspect or any possible implementation thereof.

[0026] The technical effects of any of the design methods in aspects two through five can be found in aspect one or in different possible implementations of aspect one, and will not be repeated here. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0028] Figure 1 This is a system structure diagram of an all-solid-state battery simulation system provided in an embodiment of this application.

[0029] Figure 2 This is a flowchart illustrating a method for simulating an all-solid-state battery, as provided in an embodiment of this application.

[0030] Figure 3 This is a schematic diagram of a solid-state battery simulation device provided in an embodiment of this application.

[0031] Figure 4 Another system architecture diagram of an all-solid-state battery simulation system provided in this application embodiment. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0033] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0034] In related technologies, when simulating all-solid-state batteries, a simulation model is typically constructed based on the battery's structural, material, and process parameters. Interface parameters such as reaction area and interfacial impedance are pre-defined during the model construction phase. During subsequent charge-discharge or cycle simulations, the simulation model calculates the electrochemical, thermal, mechanical, and aging responses of the target all-solid-state battery according to the pre-defined interface parameters.

[0035] However, during the actual operation of the target all-solid-state battery, the solid-solid interface formed between the electrodes and different materials such as the solid electrolyte does not always remain in the state at the initial modeling moment. For example, the expansion and contraction of materials may change the degree of contact between the materials on both sides of the interface, assembly pressure and pressure relaxation may change the stress state at the interface, temperature changes and interface side reactions may cause the formation or growth of the interface film, and cyclic operation may also cause interface cracking, debonding, or other forms of interface degradation. All of the above changes may cause the actual interface state to gradually deviate from the interface state preset in the simulation model.

[0036] When the actual interface state changes while the simulation model retains the original interface parameters, the computational information within the simulation model used to describe the interface's effects cannot change synchronously with the actual interface state. This may result in the interface changes' impact on the target all-solid-state battery's operation not being accurately reflected in the simulation data. For example, changes in the interface contact state may alter the actual reaction-participating area; changes in interface impedance may further affect battery polarization and heat generation; and the continuous accumulation of interface degradation may also affect the battery's cycle performance. Consequently, there may be discrepancies between the simulation data obtained under the target operating condition and the test data collected under the same condition. If the test data is only used to evaluate simulation errors and cannot adjust the interface state in the simulation model accordingly, these discrepancies may persist into subsequent simulation processes.

[0037] Based on this, embodiments of this application provide a method, apparatus, and device for simulating all-solid-state batteries. The method includes: constructing a coupled simulation model of the target all-solid-state battery based on parameter data. The coupled simulation model includes interface units disposed between specified materials within the target all-solid-state battery and interface state variables characterizing the interface change characteristics at corresponding positions of the interface units. The target all-solid-state battery is subjected to the following simulation test: the interface calculation information of the target all-solid-state battery is updated based on the current interface state variables. The interface calculation information is used to characterize the impact of interface changes at corresponding positions of the interface units on the operation of the target all-solid-state battery. Based on the interface calculation information and the coupled simulation model, simulation data of the target all-solid-state battery under target operating conditions is determined. Based on the simulation data and test data of the target all-solid-state battery collected under target operating conditions, the interface state variables are updated, and the above simulation test is repeated until the set conditions are met, after which the simulation result of the target all-solid-state battery is determined based on the simulation test.

[0038] The all-solid-state battery simulation method provided in this application constructs a coupled simulation model of the target all-solid-state battery based on its parameter data. The interface calculation information of the target all-solid-state battery is updated according to the current interface state variables. The interface state variables are then updated based on simulation data and test data under the same target operating conditions, and the updated interface state variables are fed back to subsequent simulation tests until the set conditions are met. The simulation results of the target all-solid-state battery are then determined based on the simulation tests. This method reduces the deviation between simulation data and test data caused by using fixed interface parameters, allowing the simulation model to adjust according to the actual interface changes of the target all-solid-state battery, thereby improving the accuracy of the all-solid-state battery simulation results.

[0039] The methods provided in the embodiments of this application will now be described in conjunction with the specific accompanying drawings.

[0040] On one hand, embodiments of this application provide an all-solid-state battery simulation system 100. For example... Figure 1 As shown, the all-solid-state battery simulation system 100 may include: a battery testing device 101, a data acquisition device 102, a parameter storage device 103, a simulation calculation device 104, and a result output device 105.

[0041] The battery testing device 101 is used to carry the target all-solid-state battery and test it according to the target operating conditions. The target all-solid-state battery can be a sulfide all-solid-state battery, an oxide all-solid-state battery, a halide all-solid-state battery, a polymer all-solid-state battery, or an inorganic-polymer composite all-solid-state battery. The negative electrode of the target all-solid-state battery can be lithium metal, graphite, silicon carbon, a current collector without negative electrode deposition, or a composite negative electrode, while the positive electrode can be layered oxide, phosphate, sulfide, or lithium-rich materials.

[0042] For example, the battery testing device 101 may include a charge-discharge tester, an electrochemical impedance spectroscopy (EIS) spectrometer, a pressure loading fixture, and a sensor array. The charge-discharge tester is connected to the positive and negative terminals of the target all-solid-state battery and is used to perform charge-discharge tests on the target all-solid-state battery according to set current, voltage, power, or charge-discharge cycle conditions. The EIS spectrometer is used to apply an impedance test signal to the target all-solid-state battery and acquire corresponding electrochemical impedance spectroscopy data. The pressure loading fixture is used to clamp the target all-solid-state battery and apply a set stacking pressure to it. The pressure loading fixture may include a fixed pressure plate, a movable pressure plate, and a pressure application mechanism, with the target all-solid-state battery positioned between the fixed and movable pressure plates. The pressure application mechanism can adjust the position of the movable pressure plate relative to the fixed pressure plate to change the stacking pressure applied to the target all-solid-state battery.

[0043] The sensor group may include one or more of temperature sensors, pressure sensors, and displacement sensors. The temperature sensor may be positioned on the surface of the target all-solid-state battery or at a preset location on the pressure loading fixture to collect temperature data of the target all-solid-state battery. The pressure sensor may be positioned between the pressure loading fixture and the target all-solid-state battery to collect data on the stacking pressure exerted on the target all-solid-state battery. The displacement sensor may be used to detect changes in the position of the movable pressure plate or changes in the thickness of the target all-solid-state battery.

[0044] The data acquisition device 102 is connected to the battery testing device 101. For example, the data acquisition device 102 can be connected to the charge-discharge tester, electrochemical impedance spectroscopy tester and sensor group in the battery testing device 101, respectively, to receive test data such as terminal voltage, current, temperature, stacking pressure, thickness change and electrochemical impedance spectroscopy collected under the target operating conditions, and send the collected test data to the simulation calculation device 104.

[0045] The parameter storage device 103 can be a database server, network storage device, or local storage device equipped with a storage medium, used to store the parameter data of the target all-solid-state battery.

[0046] The simulation computing device 104 can be a computer workstation, a local server, or a cloud server. The simulation computing device 104 includes a processor and a memory, with the memory storing simulation programs executed by the processor. The simulation computing device 104 obtains parameter data of the target all-solid-state battery from the parameter storage device 103 and constructs a coupled simulation model of the target all-solid-state battery based on the parameter data. The coupled simulation model includes interface units corresponding to the interfaces between specified materials within the target all-solid-state battery and corresponding interface state variables. During the simulation process, the simulation computing device 104 can also update the interface calculation information based on the current interface state variables using the all-solid-state battery simulation method provided in this application embodiment, and determine the simulation data under the target operating condition based on the interface calculation information and the coupled simulation model. The simulation computing device 104 also obtains test data under the same target operating condition from the data acquisition device 102, updates the interface state variables based on the simulation data and the test data, and performs the simulation again using the updated interface state variables until the set conditions are met, at which point the simulation results are output.

[0047] The simulation computing device 104 can employ either a fully coupled computing approach or a partitioned coupled computing approach. In the fully coupled computing approach, the simulation computing device 104 can utilize the same processor or multiple coprocessors to determine the electrochemical, mechanical, thermal, and aging responses of the target all-solid-state battery within the same simulation time step. In the partitioned coupled computing approach, the simulation computing device 104 can utilize different processors, different processor cores, or different computing nodes to perform corresponding calculations separately, and transmit calculated data such as reaction current, concentration, temperature, contact pressure, stress, and interface degradation through shared memory or a communication network.

[0048] The result output device 105 is used to receive and output the simulation results generated by the simulation calculation device 104 for use in the performance analysis, structural design, test evaluation, or calibration of the all-solid-state battery. For example, the result output device 105 can be a display, a user terminal, a data server, or a calibration device connected to the battery management system.

[0049] It should be noted that, Figure 1 The all-solid-state battery simulation system 100 shown is merely an example of a scenario for the method provided in this application embodiment, and is not intended to limit the scenario of the method provided in this application embodiment.

[0050] On one hand, embodiments of this application provide a method for simulating all-solid-state batteries. This method can be achieved by... Figure 1 The all-solid-state battery simulation system 100 shown is executed. (As...) Figure 2 As shown, the method may include the following steps.

[0051] S201, Construct a coupled simulation model of the target all-solid-state battery based on the parameter data of the target all-solid-state battery.

[0052] The coupled simulation model includes interface units set between specified materials within the target all-solid-state battery and interface state variables characterizing the interface change characteristics at the corresponding positions of the interface units.

[0053] The parameter data for all-solid-state batteries can include cell structure data, material data, and process data. Cell structure data can include the arrangement order, layer thickness, cross-sectional area, porosity, phase fraction, and current collector size of each material layer in the target all-solid-state battery. Material data can include diffusion coefficient, electrical conductivity, reaction rate constant, elastic modulus, Poisson's ratio, thermal conductivity, heat capacity, density, and coefficient of thermal expansion. Process data can include compaction density, interface roughness, assembly pressure, fixture stiffness, initial interface state, and thermal boundary conditions.

[0054] One possible implementation involves constructing a battery model domain, including a positive electrode composite layer, a solid electrolyte layer, a negative electrode layer, and interface units, based on the cell structure data in the parameter data. Based on the material and process data in the parameter data, the electrochemical, mechanical, thermal, and aging calculation conditions corresponding to the battery model domain are determined. The coupling relationships between the reaction current and concentration changes generated during electrochemical calculations, the contact pressure and stress changes generated during mechanical calculations, the temperature changes generated during thermal calculations, and the interface degradation information generated during aging calculations are established. Based on the battery model domain, electrochemical calculation conditions, mechanical calculation conditions, thermal calculation conditions, aging calculation conditions, and the coupling relationships, a coupled simulation model is constructed.

[0055] Specifically, based on the order, thickness, and cross-sectional area of ​​the positive electrode composite layer, solid electrolyte layer, and negative electrode layer, a battery model domain is constructed that sequentially includes the positive electrode composite layer, solid electrolyte layer, and negative electrode layer. This battery model domain can also include a positive electrode current collector, a negative electrode current collector, and external structures for applying boundary conditions. This battery model domain can be a one-dimensional model domain established along the thickness direction of the target all-solid-state battery, or a two-dimensional or three-dimensional model domain including both the thickness direction and in-plane directions. For different material layers, the computational mesh can be divided according to the size and computational accuracy requirements of the corresponding material layers.

[0056] Interface units are provided between specified materials in contact within the battery model domain. The interfaces between the specified materials may include at least one of the interfaces between the positive electrode composite layer and the solid electrolyte layer, and the interfaces between the negative electrode layer and the solid electrolyte layer. The interface units may be interface units without physical thickness, or they may be interface layer units with a preset equivalent thickness.

[0057] Each interface unit has an interface state variable corresponding to its spatial location, allowing interface changes at different locations to be characterized separately. This interface state variable can include the actual interface contact coefficient, interface film resistance, and overall damage index. When constructing the battery model domain, initial values ​​can be set for each interface state variable based on the initial assembly state, initial interface impedance, and initial cycling state.

[0058] After constructing the battery model domain, the electrochemical calculation conditions, mechanical calculation conditions, thermal calculation conditions, and aging calculation conditions corresponding to the battery model domain are determined based on the material data and process data.

[0059] The electrochemical calculation conditions are used to represent the electrochemical reactions, lithium concentration changes, electron transport, ion transport, and charge conservation relationships in the target all-solid-state battery. These electrochemical calculation conditions may include the electrochemical governing equations, the electrochemical parameters in the governing equations, the initial conditions of each material region, the boundary conditions, and the interfacial reaction conditions.

[0060] One possible implementation method is to determine the electrochemical calculation conditions through the following steps: based on the diffusion coefficient, electronic conductivity, ionic conductivity, reaction rate constant and equilibrium potential data in the material data, as well as the porosity, material phase fraction and compaction density in the process data, determine the electrochemical parameters corresponding to the positive electrode composite layer, solid electrolyte layer and negative electrode layer respectively, and configure each electrochemical parameter to the corresponding material region in the battery model domain.

[0061] Specifically, the effective solid-phase diffusion coefficients of the positive and negative electrode composite layers can be determined based on the diffusion coefficients, porosity, phase fractions, and compaction densities of the active materials in the positive and negative electrode composite layers. The effective electronic conductivity of the corresponding material layers can be determined based on the electronic conductivity, phase fractions, and compaction densities of the electronically conductive materials in the positive and negative electrode composite layers. The effective ionic conductivity of the corresponding material layers can be determined based on the ionic conductivity, phase fractions, and compaction densities of the solid electrolyte materials in the positive, solid electrolyte, and negative electrode layers. Finally, the exchange current density corresponding to the interface unit can be determined based on the reaction rate constants, lithium concentrations, and temperatures of the materials on both sides of the interface unit.

[0062] Interface reaction conditions are set within the interface unit to determine the interface reaction current based on the current interface state and potential state. The reaction current density calculated based on the nominal interface area can be expressed using the following formula. This formula represents the calculated relationship between the true contact coefficient, effective overpotential, and reaction current density.

[0063]

[0064] in, This represents the reaction current density calculated based on the nominal interface area. This indicates the current actual contact coefficient of the interface unit. This represents the exchange current density corresponding to the interface unit. This represents the charge transfer coefficient of the anodic reaction. This represents the charge transfer coefficient of the cathode reaction. This represents the Faraday constant. This represents the effective overpotential corresponding to the interface unit. This represents the ideal gas constant. This indicates the absolute temperature at the corresponding location of the interface unit. This represents an exponential function.

[0065] When constructing a coupled simulation model, this calculation relationship can be configured in each interface element without having to determine the specific values ​​of the actual contact coefficient and effective overpotential at each simulation moment during the model construction phase.

[0066] For the active material regions in the positive and negative electrode composite layers, mass conservation conditions can be set to describe the changes in solid-phase lithium concentration. The relationship between solid-phase lithium concentration and simulation time can be expressed by the following formula.

[0067]

[0068] in, This indicates the solid-phase lithium concentration of the active material in the positive electrode composite layer or negative electrode layer. Indicates the simulation time. This represents the effective solid-phase diffusion coefficient of the corresponding active material region. This represents the gradient of solid-phase lithium concentration. This represents the divergence operation. This represents the rate of change of solid-phase lithium concentration relative to simulation time.

[0069] For the electronically conductive and ionically conductive regions in the battery model domain, electron transport conditions and ion transport conditions can be set separately. The electronic phase current density and ion phase current density can be expressed as follows.

[0070]

[0071] in, This represents the electron phase current density. It represents the effective electronic conductivity of the electronically conductive region. It represents the electronic phase potential. It represents the gradient of the electronic phase potential. This represents the current density in the ionic phase. This indicates the effective ionic conductivity of the ionic conduction region. It represents the potential of the ionic phase. This represents the gradient of the ionic phase potential.

[0072] Furthermore, charge conservation conditions for the electronic and ionic phases can be set in the material region where electrochemical reactions occur.

[0073]

[0074] in, It represents the divergence of the electronic phase current density. This represents the nominal unit volume interface area of ​​the corresponding material region. This represents the reaction current density calculated based on the nominal interface area. It represents the divergence of the current density in the ionic phase.

[0075] To ensure that stress changes obtained from mechanical calculations are reflected in electrochemical calculations, a relationship between stress and equilibrium potential can be established. The equilibrium potential considering the effects of solid-phase lithium concentration, temperature, and stress can be expressed as:

[0076] in, This represents the equilibrium potential after taking stress into account. This indicates that the effect of stress is not considered when the concentration of solid-phase lithium is taken into account. and absolute temperature The fundamental equilibrium potential is determined. It can be predetermined based on material test data and stored in the coupled simulation model in the form of functional relationships, data tables, or fitted curves. This indicates the partial molar volume of lithium in the corresponding active material. This represents the hydrostatic stress obtained from mechanical calculations. This represents the Faraday constant.

[0077] After determining the aforementioned electrochemical governing equations and electrochemical parameters, the initial and boundary conditions corresponding to the electrochemical calculations can also be determined. The initial conditions may include the initial solid-phase lithium concentrations of the positive and negative electrode composite layers, the initial electronic phase potential, the initial ionic phase potential, and the initial state of charge of the target all-solid-state battery. The initial solid-phase lithium concentration can be determined based on the initial state of charge of the target all-solid-state battery and the initial lithium intercalation state of the positive and negative electrode materials.

[0078] The boundary conditions may include current boundary conditions, voltage boundary conditions, and reference potential conditions set at the positive or negative current collector, as well as a flux-free boundary condition set at the outer boundary of the battery model domain. The specific values ​​of the current or voltage boundary conditions can be determined based on the operating data corresponding to the target operating condition during subsequent simulation tests.

[0079] By configuring the above electrochemical governing equations, electrochemical parameters corresponding to each material region, initial conditions, boundary conditions, and interface reaction conditions into the corresponding material regions and interface units in the battery model domain, the electrochemical calculation conditions corresponding to the battery model domain can be determined.

[0080] Mechanical calculation conditions are used to represent the displacement, strain, and stress changes of the target all-solid-state battery under assembly pressure, material chemical expansion, thermal expansion, and interface damage.

[0081] One possible implementation is that the mechanical calculation conditions can be determined through the following steps: based on the elastic modulus, Poisson's ratio, chemical expansion coefficient and thermal expansion coefficient in the material data, and the assembly pressure, fixture stiffness and compaction density in the process data, determine the mechanical parameters corresponding to the positive electrode composite layer, solid electrolyte layer and negative electrode layer respectively, and configure each mechanical parameter to the corresponding material region in the battery model domain.

[0082] Specifically, the elastic stiffness tensor of the corresponding material layer can be determined based on its elastic modulus and Poisson's ratio. The chemical strain of the corresponding material layer can be determined based on the chemical expansion coefficient of the active material and changes in lithium concentration. The thermal strain of the corresponding material layer can be determined based on its thermal expansion coefficient and temperature changes. The damage strain can be determined based on the damage state of the corresponding material region.

[0083] For each material region within the battery model domain, geometric conditions can be set to describe the relationship between material displacement and strain. Under small deformation conditions, the strain tensor can be expressed by the following formula.

[0084] in, This represents the strain tensor of the corresponding material region. This represents the displacement vector of the corresponding material region. This represents the gradient of the displacement vector.

[0085] Furthermore, constitutive relationships between strain and stress can be established in each material region. The stress tensor, considering the effects of chemical strain, thermal strain, and damage strain, can be expressed by the following formula:

[0086] in, This represents the stress tensor of the corresponding material region. Represents the elastic stiffness tensor of the corresponding material region. Represents the double dot product operation between tensors. This represents the total strain tensor of the corresponding material region. This indicates the chemical strain caused by changes in lithium concentration. This indicates the thermal strain caused by temperature changes. This indicates damage strain caused by material damage or interface degradation.

[0087] For each material region in the battery model domain, mechanical equilibrium conditions can also be set:

[0088] in, It represents the divergence of the stress tensor. This represents the volume force acting on the corresponding material region.

[0089] After determining the aforementioned governing equations and mechanical parameters, the initial conditions, boundary conditions, and interface contact conditions corresponding to the mechanical calculations can also be determined. Initial conditions may include the initial displacement, initial strain, and initial stress of each material region. Boundary conditions may include displacement constraints, pressure boundary conditions, and symmetric boundary conditions applied to the outer surface of the battery model domain. The specific values ​​of the pressure boundary conditions can be determined during subsequent simulation testing based on the stacking pressure corresponding to the target operating condition.

[0090] Interface contact conditions can be set at interface units between adjacent material layers to define the normal displacement and force transmission relationships between the materials on both sides of the interface unit. Based on the stress tensor at the corresponding location of the interface unit, the normal contact pressure and normal tensile stress of the interface unit can be determined. The normal contact pressure characterizes the degree of mutual compression between the materials on both sides of the interface unit, while the normal tensile stress characterizes the tendency of the interface unit to crack or debond.

[0091] By configuring the aforementioned mechanical control equations, the mechanical parameters corresponding to each material region, the initial conditions, the boundary conditions, and the interface contact conditions into the corresponding material regions and interface elements in the battery model domain, the mechanical calculation conditions corresponding to the battery model domain can be determined.

[0092] Thermal calculation conditions are used to represent the relationship between heat generation, heat transfer, and temperature changes in a target all-solid-state battery. These thermal calculation conditions may include the thermal governing equations, the thermal parameters in the governing equations, the initial temperature conditions of each material region, the thermal boundary conditions, and the heat generation conditions.

[0093] One possible implementation method is to determine the thermal calculation conditions through the following steps: Based on the density, specific heat capacity, and thermal conductivity in the material data, as well as the ambient temperature, heat exchange method, heat dissipation structure, and thermal contact state in the process data, the thermal parameters corresponding to the positive electrode composite layer, solid electrolyte layer, negative electrode layer, and current collector are determined, and each thermal parameter is configured to the corresponding material region in the battery model domain.

[0094] Specifically, the equivalent density, equivalent specific heat capacity, and equivalent thermal conductivity of each material layer can be determined based on its material composition, phase fraction, and compaction density. The heat transfer conditions corresponding to the outer surface of the battery model domain can be determined based on the contact mode between the target all-solid-state battery and the external environment or thermal management structure.

[0095] For each material region in the battery model domain, energy conservation conditions can be set to describe the relationship between heat generation, heat transfer, and temperature change:

[0096] in, This indicates the density of the corresponding material region. This indicates the specific heat capacity of the corresponding material region. This indicates the absolute temperature of the corresponding material region. Indicates the simulation time. This represents the rate of change of temperature relative to simulation time. This indicates the thermal conductivity of the corresponding material region. This represents the temperature gradient. This represents the heat conduction term within the corresponding material region. This represents the volumetric heat production rate of ohmic heat. It represents the volumetric heat production rate generated by electrochemical reactions and polarization. It represents the reversible heat volumetric heat production rate generated by the entropy change of an electrochemical reaction. This indicates the volumetric heat generation rate generated by interfacial contact.

[0097] The volumetric heat production rate of ohmic heat can be expressed by the following formula:

[0098] in, This represents the volumetric heat production rate of ohmic heat. It represents the effective electronic conductivity of the electronically conductive region. It represents the gradient of the electronic phase potential. This indicates the effective ionic conductivity of the ionic conduction region. This represents the gradient of the ionic phase potential.

[0099] The volumetric heat generation rate from electrochemical reactions and polarization can be determined based on the reaction current and overpotential obtained from electrochemical calculations. The reversible thermal volumetric heat generation rate can be determined based on the reaction current, absolute temperature, and entropy change data of the corresponding electrode materials. The volumetric heat generation rate from interfacial contact can be determined based on the subsequently determined interfacial reaction current density and interfacial equivalent impedance.

[0100] After determining the aforementioned thermal governing equations and thermal parameters, the initial temperature conditions and thermal boundary conditions corresponding to the thermal calculations can also be determined. The initial temperature conditions can be determined based on the temperature of the target all-solid-state battery or the ambient temperature at the start of the simulation test. Thermal boundary conditions can include one or more of the following: constant temperature boundary conditions, convective heat transfer boundary conditions, heat flow boundary conditions, adiabatic boundary conditions, and thermal contact conditions between the target all-solid-state battery and the external thermal management structure.

[0101] For convective heat transfer boundary conditions, the heat dissipation of the target all-solid-state battery surface can be determined based on the heat transfer coefficient between the target all-solid-state battery surface and the external environment, as well as the ambient temperature. For thermal contact conditions, the heat transfer relationship can be determined based on the contact thermal resistance between the target all-solid-state battery and the pressure loading fixture or thermal management structure.

[0102] By configuring the aforementioned thermal control equations, thermal parameters corresponding to each material region, initial temperature conditions, thermal boundary conditions, and heat generation conditions into the corresponding material regions and interface elements in the battery model domain, the thermal calculation conditions corresponding to the battery model domain can be determined.

[0103] The aging calculation conditions are used to represent the changes in interfacial film resistance of the target all-solid-state battery, as well as the damage caused by changes in interfacial contact, interfacial film resistance, stress, temperature, and capacity. These aging calculation conditions may include the evolution relationship of interfacial film resistance, the damage determination relationship, the initial value of interfacial film resistance, the initial value of damage, the damage weight, and the judgment information corresponding to each damage factor.

[0104] One possible implementation involves determining the membrane resistance evolution parameters, damage weights, and damage assessment information corresponding to each interface unit based on the interfacial side reaction parameters, initial state of the interfacial film, interfacial cracking parameters, interfacial repair parameters, initial capacity, and cyclic failure data in the material and process data, and then configuring the above parameters to the corresponding interface unit.

[0105] Specifically, the interfacial film resistance can be updated based on the effects of interfacial side reactions, temperature, interfacial cracking, and interfacial contact recovery. The relationship between interfacial film resistance and simulation time can be expressed by the following formula:

[0106] in, This indicates the current interfacial membrane resistance of the interface unit. Indicates the simulation time. This represents the rate of change of the interfacial membrane resistance relative to simulation time. This represents the growth coefficient of the interfacial side reaction membrane. This represents the interfacial side reaction current. This represents the activation energy corresponding to the growth of the interfacial side reaction membrane. This represents the ideal gas constant. This indicates the absolute temperature at the corresponding location of the interface unit. This represents the coefficient of influence of interfacial cracking on interfacial film resistance. This represents the cracking and debonding function determined by the interfacial tensile stress. This represents the normal tensile stress at the corresponding position of the interface element. This represents the coefficient by which interface contact recovery restores interface film resistance. This indicates the current actual contact coefficient of the interface unit. This indicates the lower reference limit corresponding to the interfacial film resistance.

[0107] Furthermore, a comprehensive damage index can be used to represent the degree of degradation caused by the combined effects of different damaging factors. The comprehensive damage index can be expressed by the following formula:

[0108] in, This indicates a comprehensive damage index. Indicates the degree of damage to the interface contact. This indicates the degree of damage to the interfacial membrane. Indicates the degree of stress damage. Indicates the degree of temperature damage. Indicates the degree of capacity impairment. This represents the damage weight corresponding to the interface contact damage. This represents the damage weight corresponding to interfacial membrane resistance damage. This represents the damage weight corresponding to stress damage. This represents the damage weight corresponding to temperature damage. This represents the damage weight corresponding to capacity damage.

[0109] Each damage weight is a non-negative number, and this loss weight can be determined based on the degree of influence of different damage factors on the failure of the target all-solid-state battery. For example, the sum of all damage weights is 1.

[0110] The degree of interfacial contact damage can be expressed by the following formula:

[0111] in, Indicates the degree of damage to the interface contact. This indicates the preset allowable value for the contact coefficient. This represents the minimum value among the actual contact coefficients of the interfaces of each interface unit within the target all-solid-state battery. This represents the lower reference limit corresponding to the actual contact coefficient of the interface.

[0112] The degree of interfacial membrane resistance damage can be expressed by the following formula:

[0113] in, This indicates the degree of damage to the interfacial membrane. This indicates the current interfacial membrane resistance of the interface unit. This indicates the initial interfacial membrane resistance corresponding to the interface unit. This indicates the preset membrane resistance limit value.

[0114] The degree of stress damage can be expressed by the following formula:

[0115] in, Indicates the degree of stress damage. This represents the equivalent stress obtained from mechanical calculations. This indicates a preset safety stress. This indicates the preset stress limit.

[0116] The degree of temperature damage can be expressed by the following formula:

[0117] in, Indicates the degree of temperature damage. This represents the highest temperature of the target all-solid-state battery obtained from thermal calculations. This indicates the preset safe temperature. This indicates the preset temperature limit.

[0118] The degree of volume impairment can be expressed by the following formula:

[0119] in, Indicates the degree of capacity impairment. This indicates the initial capacity of the target all-solid-state battery. This represents the capacity of the target all-solid-state battery after the Nth cycle. This indicates the preset capacity threshold. This indicates the number of cycles for the target all-solid-state battery.

[0120] After determining the aforementioned membrane resistance evolution relationship and damage determination relationship, the initial state and judgment information corresponding to the aging calculation can also be determined. The initial state may include the initial interface membrane resistance, the initial comprehensive damage index, and the initial capacity. The judgment information may include the preset allowable contact coefficient value, the preset membrane resistance limit value, the preset safe stress, the preset stress limit value, the preset safe temperature, the preset temperature limit value, and the preset capacity threshold.

[0121] By configuring the aforementioned interfacial membrane resistance evolution relationship, damage determination relationship, membrane resistance evolution parameters, damage weight, initial state, and judgment information into the corresponding interface units and material regions in the battery model domain, the aging calculation conditions corresponding to the battery model domain can be determined.

[0122] S202, Update the interface calculation information of the target all-solid-state battery according to the current interface state variables.

[0123] The interface state variables include the actual contact coefficient, interfacial film resistance, and comprehensive damage index. Interface calculation information is used to characterize the impact of interface changes at corresponding locations of interface cells on the operation of the target all-solid-state battery. This calculated information includes effective reaction area, equivalent interfacial impedance, effective overpotential, contact heat source, and lifetime degradation information.

[0124] During the initial simulation test, the current interface state variables can be the initial values ​​set when constructing the coupled simulation model. In subsequent simulations, the current interface state variables can be determined based on the interface state variables from the previous simulation time and data such as pressure, temperature, stress, and cycle status at the current simulation time. When repeating the simulation test, the current interface state variables can also be updated based on the simulation data and test data from the previous simulation test.

[0125] Specifically, the actual contact coefficient, interfacial membrane resistance, and comprehensive damage index of the interface at the current simulation moment can be determined first, and then the interface calculation information can be updated based on the above interface state variables at the current simulation moment.

[0126] The true contact coefficient is used to represent the degree of contact between the actual contact area of ​​the interface cell and the nominal interface area. The true contact coefficient can be determined based on the effective contact pressure of the interface cell, interface roughness, interface film thickness, tensile stress, and the cycling history of the target all-solid-state battery.

[0127] One possible implementation involves determining the effective contact pressure of the interface unit based on the external stacking pressure, pressure changes caused by chemical expansion, pressure changes caused by thermal expansion, and pressure changes caused by pore relaxation. The effective contact pressure can be expressed by the following formula:

[0128] in, This indicates the effective contact pressure of the interface unit. This indicates the external stacking pressure applied to the target all-solid-state battery. This indicates the pressure change caused by the chemical expansion of the material. This indicates the pressure change caused by the thermal expansion of the material. This indicates pressure loss caused by changes in porosity, material relaxation, or fixture loosening. This indicates the preset maximum contact pressure.

[0129] External stacking pressure can be determined based on pressure data corresponding to the target operating condition. Pressure changes caused by chemical expansion can be determined based on lithium concentration changes obtained from electrochemical calculations and chemical strain obtained from mechanical calculations. Pressure changes caused by thermal expansion can be determined based on temperature changes obtained from thermal calculations and thermal strain obtained from mechanical calculations. Pressure changes caused by pore relaxation can be determined based on the material's porosity, compaction density, cycle history, and fixture stiffness.

[0130] In three-dimensional mechanical calculations, the effective contact pressure can also be determined based on the normal pressure at the corresponding location of the interface element. For example, the area-weighted average, minimum, or preset quantile of the normal pressure within the area covered by the interface element can be used to determine the effective contact pressure of that interface element.

[0131] The equilibrium contact coefficient for each interface element is determined based on the effective contact pressure, interface roughness, and interface film thickness. The equilibrium contact coefficient can be expressed by the following formula:

[0132] in, This represents the equilibrium contact coefficient corresponding to the interface unit. This represents the lower limit of the actual contact coefficient of the interface. This indicates the effective contact pressure of the interface unit. This indicates the characteristic contact pressure corresponding to the interface unit. The contact index is used to reflect the interface roughness and elastoplastic contact characteristics. This indicates the equivalent thickness of the interface film. This represents the characteristic scale that indicates the effect of interfacial film thickness on interfacial contact.

[0133] Among them, characteristic contact pressure and contact index It can be determined based on interface roughness, material elastic parameters, and pressure step test data. The greater the interface roughness or the higher the degree of plastic relaxation in the material, the more the characteristic contact pressure and contact index can change accordingly.

[0134] Another possible approach is to omit the interface film thickness when the interface film thickness of the target all-solid-state battery only affects the interface impedance and not the actual contact area. Instead, the interface film thickness can be considered when determining the equilibrium contact coefficient, and the influence of the interface film thickness can be taken into account when determining the interface film resistance or irreversible active sites, so as to avoid the interface film thickness being repeatedly counted.

[0135] Furthermore, the interface contact recovery is determined based on the difference between the equilibrium contact coefficient and the actual interface contact coefficient at the previous simulation time. The interface contact loss is determined based on the tensile stress of the interface cells and the cycling history of the target all-solid-state battery. The relationship between the interface contact state and simulation time can be expressed by the following formula:

[0136] in, This represents the original contact coefficient before physical boundary treatment. Indicates the simulation time. This represents the rate of change of the original contact coefficient relative to the simulation time. This represents the interface contact recovery rate coefficient. This represents the equilibrium contact coefficient. This represents the rate coefficient of interface cracking or debonding. This represents the cracking and debonding function determined by the interfacial tensile stress. This represents the normal tensile stress at the corresponding position of the interface element. This represents the cyclic contact loss rate coefficient. This function represents the effect of the cyclic process on the interface contact loss. This indicates the current cycle number of the target all-solid-state battery.

[0137] The cracking and debonding function can be expressed by the following formula:

[0138] in, This indicates the cracked and debonded state of the interface unit. This represents the normal tensile stress at the corresponding position of the interface element. This indicates the critical tensile stress at which the interface begins to crack or debond. This indicates the preset tensile stress limit.

[0139] When the normal tensile stress is not greater than the critical tensile stress, the cracking and debonding function can be zero. As the normal tensile stress gradually approaches the preset tensile stress limit, the cracking and debonding function gradually increases. Cyclic Influence Function It can be determined based on the number of cycles, cycle depth, or cycle capacity decay, and can be calibrated using cycle test data.

[0140] After determining the change in the original contact coefficient within the current simulation time step, the original contact coefficient at the current simulation time can be obtained by combining it with the original contact coefficient at the previous simulation time. Subsequently, physical boundary processing is performed on the original contact coefficient to obtain the actual interface contact coefficient at the current simulation time.

[0141] in, This represents the actual contact coefficient of the interface at the current simulation moment. This represents the original contact coefficient at the current simulation moment. This represents the lower limit of the actual contact coefficient of the interface. A value of 1 indicates that the nominal interface is in a fully contacted state.

[0142] After determining the actual contact coefficient of the interface at the current simulation moment, the interface film resistance at the current simulation moment can be determined. Specifically, based on the side reaction overpotential and temperature corresponding to the interface element, the side reaction current corresponding to the interface element is determined. The side reaction current can be expressed by the following formula:

[0143] in, This represents the side reaction current corresponding to the interface unit. This represents the exchange current corresponding to the interfacial side reaction. This represents the charge transfer coefficient of the interfacial side reaction. This represents the Faraday constant. This represents the overpotential of the side reaction corresponding to the interface unit. This represents the ideal gas constant. This indicates the absolute temperature at the corresponding location of the interface unit.

[0144] Based on the side reaction current and temperature, the first influence of interfacial side reaction film growth on interfacial film resistance can be determined. Based on the normal tensile stress of the interfacial unit and the determined cracking and debonding state, the second influence of interfacial cracking on interfacial film resistance can be determined. Based on the current true interfacial contact coefficient and the interfacial film resistance at the previous simulation time step, the third influence of interfacial contact recovery on interfacial film resistance can be determined. Based on the interfacial film resistance at the previous simulation time step and the first, second, and third influences within the current simulation time step, the interfacial film resistance at the current simulation time step can be determined.

[0145] After determining the interfacial membrane resistance at the current simulation moment, the physical boundary of the interfacial membrane resistance can be processed:

[0146] in, This indicates the interfacial membrane resistance after physical boundary treatment. This indicates the lower reference limit corresponding to the interfacial film resistance.

[0147] When the target all-solid-state battery does not exhibit interface contact recovery or interface remodeling, the interface repair coefficient can be... Set to 0.

[0148] After determining the actual interface contact coefficient and interface film resistance at the current simulation moment, the comprehensive damage index at the current simulation moment can be determined. Specifically, the minimum actual interface contact coefficient of the cell is determined based on the current actual interface contact coefficient of each interface unit in the target all-solid-state battery, and the degree of interface contact damage is determined based on the minimum actual interface contact coefficient of the cell and preset contact damage judgment information.

[0149] Based on the current interfacial film resistance, initial interfacial film resistance, and preset film resistance limit, the degree of interfacial film resistance damage is determined. Based on the equivalent stress obtained from mechanical calculations and the corresponding stress assessment information, the degree of stress damage is determined. Based on the highest temperature obtained from thermal calculations and the corresponding temperature assessment information, the degree of temperature damage is determined. Based on the current capacity, initial capacity, and preset capacity threshold, the degree of capacity damage is determined. Finally, based on the degree of interfacial contact damage, the degree of interfacial film resistance damage, the degree of stress damage, the degree of temperature damage, and the degree of capacity damage, as well as the damage weight corresponding to each degree of damage, the comprehensive damage index for the current simulation moment is determined.

[0150] After obtaining the comprehensive damage index at the current simulation moment, lifetime degradation information can be determined based on the changes in the comprehensive damage index during the cyclic process. Lifetime degradation information can include one or more of the following: the trend of the comprehensive damage index, the predicted failure cycle time, and the remaining service life. The remaining service life can be expressed by the following formula:

[0151] in, This indicates the remaining useful life, expressed in terms of the number of cycles. This indicates the current cycle number of the target all-solid-state battery. This indicates the predicted number of iterations, which is greater than the current iteration count. This represents the predicted comprehensive damage index of the target all-solid-state battery at the Nth cycle. This indicates the preset failure value corresponding to the comprehensive damage index. This represents the predicted capacity of the target all-solid-state battery at the Nth cycle. This indicates the preset capacity threshold.

[0152] This comprehensive damage index and predicted capacity It can be determined based on cyclic recursion, linear extrapolation, power-law extrapolation, or degradation prediction models.

[0153] Furthermore, based on the actual contact coefficient and interfacial membrane resistance at the current simulation moment, the effective reaction area, equivalent interfacial impedance, effective overpotential, and contact heat source are updated.

[0154] To avoid the true contact coefficient of the interface being repeatedly included in the effective reaction area, the equivalent interface impedance, and the contact heat source, a unified area benchmark can be set in the coupled simulation model. The true contact area of ​​the interface element can be expressed by the following formula:

[0155] in, This represents the actual contact area of ​​the interface unit. This represents the nominal interface area of ​​the interface unit. This indicates the current actual contact coefficient of the interface unit.

[0156] Assuming the total reaction current remains constant, the relationship between the total reaction current under the actual contact area reference and the nominal interface area reference can be expressed as:

[0157] in, This represents the total reactive current passing through the interface unit. This represents the actual contact area. This represents the reaction current density determined based on the actual contact area. Represents the nominal interface area. This represents the reaction current density calculated based on the nominal interface area.

[0158] Correspondingly, the relationship between the reaction current densities under the two area references can be expressed as:

[0159] Based on the actual contact coefficient of the interface and the nominal unit volume interfacial area of ​​the interface unit, the effective unit volume reaction area can be determined:

[0160] in, This represents the effective unit volume reaction area corresponding to the interface unit. This represents the nominal unit volume of the interface area corresponding to the interface unit. This indicates the current actual contact coefficient of the interface.

[0161] When determining the equivalent impedance of an interface, it can be converted based on the area reference used for the interface film resistance. The interface film potential drop determined according to the actual contact area can be expressed as:

[0162] in, This indicates the potential drop caused by the interface film. This represents the reaction current density determined based on the actual contact area. This indicates the interfacial film resistance determined based on the actual contact area. This represents the reaction current density calculated based on the nominal interface area. This represents the actual contact coefficient of the interface.

[0163] One possible implementation, current interfacial membrane resistance When defining based on the actual contact area, then it can be As in the formula When the interfacial film resistance uses other area references, it can be converted to the interfacial film resistance based on the actual contact area reference.

[0164] The equivalent interfacial impedance calculated based on the nominal interfacial area can be expressed by the following formula:

[0165] in, It represents the equivalent impedance of the interface calculated based on the nominal interface area. This indicates the interfacial film resistance determined based on the actual contact area. This represents the actual contact coefficient of the interface. This represents the reference contact shrinkage impedance corresponding to the interface unit. The impedance exponent represents the variation of contact shrinkage resistance with the actual contact coefficient of the interface. Wherein, the reference contact shrinkage resistance... and impedance index It can be determined based on electrochemical impedance spectroscopy data collected under different stacking pressures.

[0166] The effective overpotential can be determined based on the reaction current density corresponding to the nominal interface area, the equivalent impedance of the interface, the potentials on both sides of the interface unit, the equilibrium potential, and the potential change caused by stress.

[0167] in, This represents the effective overpotential corresponding to the interface unit. This represents the electronic phase potential on the electronically conductive side of the interface unit. This represents the ionic phase potential on the ionic conductive side of the interface unit. Indicated by solid-phase lithium concentration ,temperature and stress state A defined equilibrium potential. This represents the reaction current density calculated based on the nominal interface area. It represents the equivalent impedance of the interface calculated based on the nominal interface area. This indicates the additional potential change caused by stress, in addition to the equilibrium potential correction.

[0168] Once the effective overpotential is obtained, the interfacial reaction current density can be re-determined based on this effective overpotential.

[0169] The contact heat source can be determined based on the reaction current density corresponding to the nominal interface area, the equivalent interface impedance, and the nominal interface area per unit volume.

[0170] in, This represents the volumetric heat generation rate of the contact heat source, determined based on the nominal interface area. It represents the interface area per unit volume. This represents the reaction current density calculated based on the nominal interface area. It represents the equivalent impedance of the interface calculated based on the nominal interface area.

[0171] Another possible approach is to determine the contact heat source based on the actual contact area:

[0172] in, This indicates the effective unit volume of reaction area. This represents the reaction current density determined based on the actual contact area. It represents the equivalent interfacial impedance determined based on the actual contact area.

[0173] It should be noted that the two possible implementation methods described above represent two different areas of the contact heat source. In the same simulation calculation, the area reference used for the reaction current density, interface impedance, and reaction area should be consistent to avoid double-counting the actual interface contact coefficient due to the simultaneous use of both implementation methods.

[0174] Through the above process, the actual contact coefficient, interfacial film resistance, and comprehensive damage index of the interface at the current simulation moment can be obtained. Based on this, the effective reaction area, equivalent interfacial impedance, effective overpotential, contact heat source, and lifetime degradation information can be updated, thereby obtaining the interface calculation information used in the current simulation test.

[0175] S203, based on interface calculation information and coupled simulation model, determines the simulation data of the target all-solid-state battery under the target operating conditions.

[0176] The operating data corresponding to the target operating condition may include charging and discharging current, charging and discharging voltage, charging and discharging cutoff conditions, ambient temperature, stacking pressure, initial state of charge, number of cycles, and simulation duration. Simulation data may include terminal voltage, temperature distribution, contact pressure distribution, thickness variation, impedance variation, and capacity variation.

[0177] One possible implementation involves inputting the operating condition data and interface calculation information corresponding to the target operating condition into a coupled simulation model. Based on the effective reaction area, equivalent interfacial impedance, and effective overpotential, the reaction current, terminal voltage, and lithium concentration distribution of the target all-solid-state battery are determined. Based on the reaction current, contact heat source, and thermal boundary conditions of the target all-solid-state battery, the temperature distribution of the target all-solid-state battery is determined. Based on the lithium concentration distribution, temperature distribution, and stacking pressure corresponding to the target operating condition, the contact pressure distribution, stress distribution, and thickness variation of the target all-solid-state battery are determined. Based on the aging calculation conditions of the coupled simulation, interfacial film resistance, and the cycling state of the target all-solid-state battery, the impedance and capacity variations of the target all-solid-state battery are determined. Simulation data is then determined based on the terminal voltage, temperature distribution, contact pressure distribution, thickness variation, impedance variation, and capacity variation.

[0178] Specifically, the operating condition data and interface calculation information corresponding to the target operating condition are input into the coupled simulation model. The initial lithium concentration of the positive electrode composite layer and the negative electrode layer is set according to the initial state of charge, the initial temperature of each material region is set according to the ambient temperature, the electrochemical boundary conditions at the current collector are set according to the charge / discharge current or charge / discharge voltage, the mechanical boundary conditions of the battery model domain are set according to the stacking pressure, and the thermal boundary conditions are set according to the heat transfer mode between the target all-solid-state battery and the external environment.

[0179] The effective reaction area, equivalent interfacial impedance, effective overpotential, and contact heat source are respectively configured to the corresponding interfacial units. The reaction current density of each interfacial unit is determined based on the actual contact coefficient, exchange current density, charge transfer coefficient, effective overpotential, and temperature at the corresponding location of the interfacial unit.

[0180] The reaction current density of each interface unit is used as the reaction source term for electron transport and ion transport processes. The electron phase current density is determined based on the effective electronic conductivity and the electron phase potential gradient, and the ion phase current density is determined based on the effective ionic conductivity and the ion phase potential gradient. The electron phase potential distribution and the ion phase potential distribution are determined based on the charge conservation relationship between the electron and ion phases.

[0181] Based on the current lithium concentration distribution in the positive and negative electrode composite layers, the effective solid-phase diffusion coefficient, and the reaction current density of the corresponding interface units, the lithium concentration distribution at the next simulation time is determined. The equilibrium potential is determined based on the lithium concentration, temperature, and hydrostatic stress. Then, the effective overpotential is updated based on the electronic and ionic phase potentials on both sides of the interface unit, the equilibrium potential, the interface equivalent impedance, and the potential change caused by stress.

[0182] The reaction current density, electronic phase potential distribution, ionic phase potential distribution, lithium concentration distribution, and equilibrium potential are repeatedly determined until the difference between two consecutive calculations meets the preset electrochemical convergence condition. Based on the difference between the electronic phase potential at the corresponding positions of the positive electrode current collector and the negative electrode current collector, the terminal voltage of the target all-solid-state battery is determined, thereby obtaining the reaction current, terminal voltage, and lithium concentration distribution of the target all-solid-state battery.

[0183] Furthermore, the temperature distribution of the target all-solid-state battery is determined based on the reaction current, contact heat source, and thermal boundary conditions.

[0184] Specifically, the ohmic heat generated by electron transport is determined based on the effective electronic conductivity and electronic phase potential gradient; the ohmic heat generated by ion transport is determined based on the effective ionic conductivity and ionic phase potential gradient; the heat generated by electrochemical reaction and polarization is determined based on the reaction current and effective overpotential; and the reversible heat is determined based on the reaction current, temperature, and material entropy change data.

[0185] The ohmic heat generated by electron transport, the ohmic heat generated by ion transport, the heat generated by electrochemical reactions and polarization, reversible heat, and contact heat sources are configured in their corresponding positions within the battery model domain. Based on the density, specific heat capacity, and thermal conductivity of each material region, as well as the isothermal conditions, convective heat transfer conditions, heat flow conditions, or thermal contact conditions on the surface of the target all-solid-state battery, the temperature distribution of the target all-solid-state battery at each simulation time is determined.

[0186] Furthermore, based on the lithium concentration distribution, temperature distribution, and stacking pressure corresponding to the target operating conditions, the contact pressure distribution, stress distribution, and thickness variation of the target all-solid-state battery are determined.

[0187] Specifically, chemical strain is determined based on the difference between the current and initial lithium concentrations and the corresponding chemical expansion coefficients of the materials. Thermal strain is determined based on the difference between the current and initial temperatures and the corresponding thermal expansion coefficients of the materials. Damage strain is determined based on a comprehensive damage index.

[0188] Based on chemical strain, thermal strain, damage strain, elastic stiffness of each material region, and stacking pressure corresponding to the target operating condition, the displacement and stress distribution of the battery model domain are determined. Based on the stress components at corresponding positions of interface elements in the interface normal direction, the contact pressure and tensile stress of each interface element are determined, thereby obtaining the contact pressure and stress distribution of the target all-solid-state battery.

[0189] The thickness variation of the target all-solid-state battery is determined based on the current and initial distances between two relatively positioned outer surfaces in the battery model domain. The effective contact pressure of each interface unit is determined based on external stacking pressure, pressure changes caused by chemical expansion, pressure changes caused by thermal expansion, and pressure changes caused by pore relaxation.

[0190] Furthermore, based on the aging calculation conditions, interfacial film resistance, and the cycling state of the target all-solid-state battery, the impedance and capacity changes of the target all-solid-state battery are determined.

[0191] Specifically, based on the current interfacial film resistance, the actual contact coefficient, and the contact shrinkage resistance, the equivalent interfacial impedance of each interfacial unit is determined. The equivalent interfacial impedance of each interfacial unit is then combined with the ion transport impedance of the solid electrolyte layer, the electron transport impedance of the positive electrode composite layer and the negative electrode layer, and the current collector contact impedance to determine the current impedance of the target all-solid-state battery. The impedance change is then determined based on the difference between the current impedance and the initial impedance.

[0192] When electrochemical impedance spectroscopy simulation data is required, an AC excitation within a preset frequency range is applied to the coupled simulation model. The electrochemical impedance spectrum is determined based on the voltage and current responses corresponding to the AC excitation, and high-frequency ohmic impedance characteristics and mid-to-high-frequency interface impedance characteristics are extracted from the electrochemical impedance spectrum.

[0193] Based on the side reaction current, temperature, tensile stress, cracking and debonding state of the interface unit, the actual contact coefficient of the interface, and the interface film resistance at the previous simulation time, the effects of interface side reaction film growth, interface cracking, and interface contact recovery on the interface film resistance are determined, and the interface film resistance is updated according to each effect.

[0194] The reaction current of the target all-solid-state battery during a single charge or discharge cycle is accumulated over time until the terminal voltage reaches a preset charge cutoff voltage or a preset discharge cutoff voltage. The accumulated capacity is then determined as the usable capacity under the current cycle state. The capacity change is determined based on the difference between the usable capacity under the current cycle state and the initial capacity.

[0195] Based on the current actual contact coefficient, interfacial film resistance, equivalent stress, maximum temperature, and capacity change, the degree of interfacial contact damage, interfacial film resistance damage, stress damage, temperature damage, and capacity damage are determined respectively, and the comprehensive damage index is updated according to each degree of damage and its corresponding damage weight.

[0196] When using a fully coupled calculation method, reaction current, lithium concentration, potential, temperature, displacement, stress, interfacial film resistance, and comprehensive damage indicators are jointly determined within the same simulation time step. When using a partitioned coupled calculation method, electrochemical calculations, thermal calculations, mechanical calculations, and aging calculations are performed sequentially, and information on reaction current, lithium concentration, temperature, contact pressure, stress, and interfacial degradation is transferred between different calculation processes until the data transferred between each calculation process meets the preset internal coupling convergence conditions.

[0197] After completing the simulation corresponding to the target working condition, the terminal voltage is extracted from the electronic phase potential distribution, the surface temperature corresponding to the temperature test position is extracted from the temperature distribution, the pressure data corresponding to the pressure test position is extracted from the contact pressure distribution, the thickness change is extracted from the displacement distribution, and the impedance change and capacity change are extracted from the aging calculation results.

[0198] Based on the extracted terminal voltage, temperature, contact pressure, thickness change, impedance change, and capacity change, simulation data of the target all-solid-state battery under the target operating conditions are determined.

[0199] S204. Based on the simulation data and the test data of the target all-solid-state battery collected under the target operating conditions, update the interface state variables, repeat the above simulation test, and determine the simulation result of the target all-solid-state battery based on the simulation test after the set conditions are met.

[0200] The test data may include terminal voltage test data, surface temperature test data, stacking pressure test data, thickness change test data, electrochemical impedance spectroscopy test data, and capacity test data.

[0201] One possible implementation involves collecting terminal voltage test data, surface temperature test data, stacking pressure test data, thickness change test data, and electrochemical impedance spectroscopy test data using a charge / discharge tester, while the target all-solid-state battery is in the target operating condition. Capacity test data is then determined based on the cumulative amount of charge passing through the target all-solid-state battery during the charge / discharge process.

[0202] Based on the sampling time and location of each test data point, data corresponding to the specified time and location are extracted from the simulation data. The terminal voltage test data is correlated with the simulated terminal voltage; the surface temperature test data with the simulated surface temperature; the stacking pressure test data with the simulated contact pressure or stacking pressure; the thickness change test data with the simulated thickness change; the electrochemical impedance spectroscopy test data with the simulated impedance characteristics; and the capacity test data with the simulated capacity change.

[0203] When test data and simulation data have different sampling frequencies or sampling times, time interpolation can be performed on the test data or simulation data. When temperature test data or pressure test data corresponds to a preset measurement area, spatial averaging or area weighting can be performed on the simulation data within that preset measurement area. After completing the time and spatial correspondence, the differences between each test data point and its corresponding simulation data are determined.

[0204] One possible implementation involves using the actual contact coefficient, interfacial film resistance, and comprehensive damage index as the interface state variables that need to be updated, and then using a state estimation method to update the interface state variables based on the differences between the test data and the simulation data. The state estimation process can be expressed as:

[0205] in, This represents the state vector at the k-th update time. This represents the state vector at the (k-1)th update time. The state vector can include the target all-solid-state battery's state of charge, lithium concentration, temperature, true contact coefficient at the interface, interfacial film resistance, and overall damage index. This represents the working condition input at the (k-1)th update time. This indicates the model parameters used in the coupled simulation model. This represents a process disturbance during a state change that is not described by the coupled simulation model.

[0206] The relationship between test data and interface state variables can be expressed as:

[0207] in, This represents the test data at the k-th update time. This represents the working condition input at the k-th update time. This refers to measurement disturbances introduced by the test equipment, sensors, and data transmission process.

[0208] Based on the state estimate at the previous update time, the current operating condition input, and the model parameters, determine the state prediction at the current update time:

[0209] in, This represents the predicted state value at the k-th update time, obtained based on the data at the (k-1)-th update time. This represents the estimated state value after the update at the (k-1)th update time.

[0210] Based on the changes in the state change relationship relative to the state vector and the process disturbances, determine the prediction covariance corresponding to the predicted state value:

[0211] in, Let represent the prediction covariance at the k-th update time. The Jacobian matrix represents the relationship between state changes and the state vector. Let represent the state covariance after the update at the (k-1)th update time. This represents the covariance matrix corresponding to the process disturbance.

[0212] Based on the variation of test data with the state vector, the predicted covariance, and the measurement error of the test data, determine the residual covariance of the difference between the test data and the simulation data:

[0213] in, This represents the residual covariance. The Jacobian matrix represents the observation mapping relationship relative to the state vector. This represents the measurement noise covariance matrix corresponding to each test data point.

[0214] Test data with higher measurement accuracy can have smaller measurement noise variance, allowing it to play a greater role in the state update process. Test data with large measurement fluctuations or low reliability can have larger measurement noise variance to reduce their impact on the interface state variable update results.

[0215] Determine the state update gain based on the prediction covariance, observation mapping relationship, and residual covariance:

[0216] in, This represents the state update gain at the k-th update time. This represents the inverse matrix of the residual covariance. The state update gain is used to determine the degree to which the difference between the test data and the simulation data corrects for each interface state variable.

[0217] Based on the predicted state value, the state update gain, and the difference between the test data and the corresponding simulation data, the updated state estimate is determined:

[0218] in, This represents the estimated state value after the update at the k-th update time. This indicates the difference between the test data and the corresponding simulation data. This represents the state projection operation that performs physical constraint processing on the state update result.

[0219] State projection operations are used to ensure that the updated interface state variables satisfy the corresponding physical meanings. For example, it can keep the actual contact coefficient of the interface within its allowable physical range, ensure that the interface film resistance is not lower than its physical reference value, and ensure that the comprehensive damage index meets the preset damage change conditions.

[0220] The state update gain is the product of the difference between the test data and the simulation data, forming the state update quantity. Of this state update quantity, the component corresponding to the actual contact coefficient of the interface is the contact coefficient update quantity, the component corresponding to the interfacial membrane resistance is the membrane resistance update quantity, and the component corresponding to the comprehensive damage index is the damage index update quantity.

[0221] Based on the updated state estimate and the state update gain, determine the updated state covariance:

[0222] in, Let represent the state covariance after the update at the k-th update time. This represents the identity matrix. The updated state covariance is used to represent the degree of uncertainty that still exists for each interface state variable after the current update is completed.

[0223] Specifically, the contact coefficient update amount corresponding to the actual contact coefficient of the interface can be determined based on the differences between the stacking pressure test data and the corresponding simulation data, the differences between the thickness change test data and the corresponding simulation data, and the differences between the interfacial impedance characteristics in the electrochemical impedance spectroscopy test data and the corresponding simulation data.

[0224] Stacking pressure and thickness variations can reflect the compaction, expansion, contraction, and interfacial debonding of the target all-solid-state battery, while interfacial impedance characteristics in electrochemical impedance spectroscopy can reflect changes in the effective contact area. Therefore, the differences in stacking pressure, thickness variations, and interfacial impedance characteristics can be configured as the observational differences used when updating the true interfacial contact coefficient.

[0225] The membrane resistance update amount corresponding to the interface membrane resistance can be determined based on the differences between the terminal voltage test data and the corresponding simulation data, as well as the differences between the interfacial impedance characteristics in the electrochemical impedance spectroscopy test data and the corresponding simulation data. The terminal voltage difference reflects the change in the overall polarization of the target all-solid-state battery, while the difference in interface impedance characteristics reflects the changes in interfacial membrane resistance and interfacial reaction impedance. Therefore, the differences corresponding to the terminal voltage and interface impedance characteristics can be configured as the observation differences used for updating the interface membrane resistance.

[0226] After updating the true contact coefficient and interfacial film resistance, the damage index update amount corresponding to the comprehensive damage index can be determined based on the updated true contact coefficient and interfacial film resistance, as well as the differences between the surface temperature test data and capacity test data and the corresponding simulation data.

[0227] Surface temperature differences reflect the deviation between the simulated total heat generation and the actual heat generation of the target all-solid-state battery, while capacity differences reflect the deviation between the simulated degree of degradation and the actual degree of degradation of the target all-solid-state battery. Correcting the comprehensive damage index based on surface temperature and capacity differences allows the comprehensive damage index to correspond to the actual operating state of the target all-solid-state battery.

[0228] Based on the update amounts of contact coefficient, membrane resistance, and damage index, the actual contact coefficient, membrane resistance, and comprehensive damage index of the interface unit are updated respectively, and the updated interface state variables are used as the current interface state variables for the next simulation test.

[0229] Another possible implementation is to use a recursive least squares method to update the interface state variables or model parameters related to the interface state evolution. The parameter update gain can be expressed as:

[0230] in, This represents the parameter update gain at the k-th update time. Let represent the parameter covariance at the (k-1)th update time. This represents the parameter sensitivity matrix of the simulation data relative to the parameters to be updated. This represents the forgetting factor. Represents the identity matrix.

[0231] Based on the parameter update gain and the difference between the test data and the simulation data, determine the updated parameters:

[0232] in, This represents the parameter vector updated at the k-th update time. This represents the parameter vector at the (k-1)th update time. This represents the residual vector between each test data point and the corresponding simulation data. This represents the parametric projection operation that applies physical constraints to the parameter update results.

[0233] Based on the parameter update gain and parameter sensitivity matrix, determine the updated parameter covariance:

[0234] in, This represents the parameter covariance after the update at the k-th update time.

[0235] To determine whether different test data can distinguish the true contact coefficient, interfacial film resistance, and overall damage index, identifiability analysis can be performed on the interfacial state variables. The observation vector used for identifiability analysis can be represented as:

[0236] in, This represents the observation vector. This indicates the terminal voltage. Indicates surface temperature. This indicates stacking pressure. This indicates a change in thickness. This represents the high-frequency ohmic impedance characteristics in electrochemical impedance spectroscopy. This represents the mid-to-high frequency interfacial impedance characteristics in electrochemical impedance spectroscopy.

[0237] The parameter vector used for identifiability analysis can be represented as:

[0238] in, This represents the parameter vector to be identified. This represents the actual contact coefficient of the interface. This indicates the interfacial membrane resistance. This indicates the effective ionic conductivity. represents the effective diffusion coefficient, which is different from the comprehensive damage index D. h represents the heat transfer coefficient corresponding to the thermal boundary. The characteristic contact pressure is indicated by 'm'. 'm' represents the contact index. This represents the interface contact recovery rate coefficient. This represents the rate coefficient of interface cracking or debonding.

[0239] The comprehensive damage index can be set in the state vector for updating, or it can be used as an additional component in the parameter vector for identifiability analysis.

[0240] Based on the changes in various simulation data with the parameters to be identified, the state sensitivity information is determined. The sensitivity matrix can be represented as:

[0241] in, This represents the sensitivity matrix. Each row in the sensitivity matrix corresponds to a simulation data point, and each column corresponds to a parameter to be identified.

[0242] Based on the state sensitivity information and the test weights corresponding to each test data point, the information matrix is ​​determined as follows:

[0243] in, The information matrix is ​​represented by W. W represents the test weight matrix corresponding to each test data point. The test weight matrix can be determined based on the measurement accuracy, measurement noise, and data reliability of each test device, or it can be the inverse of the measurement noise covariance matrix.

[0244] Based on the sensitivity matrix and the information matrix, determine the identifiability result corresponding to the current state variable to be updated:

[0245] in, This represents the sensitivity submatrix corresponding to the state variable to be updated. This represents the rank of the matrix. This indicates the number of state variables that are currently ready to be updated. This represents the information submatrix corresponding to the current state variable to be updated. The condition number of a matrix. This indicates the maximum number of preset conditions.

[0246] When the rank of the sensitivity submatrix is ​​not less than the number of state variables to be updated, and the condition number of the information submatrix is ​​not greater than the preset maximum condition number, it is determined that the corresponding interface state variable can be distinguished under the current test data, and it is determined as the target state variable to be updated.

[0247] When the rank of the sensitivity submatrix is ​​less than the number of state variables to be updated, or the condition number of the information submatrix is ​​greater than the preset maximum condition number, it is determined that some interface state variables cannot be reliably distinguished by the current test data. In this case, state variables that can be constrained by the current test data are selected from the actual contact coefficient, interfacial membrane resistance, and comprehensive damage index for updating, while the remaining interface state variables are kept at their corresponding prior state values.

[0248] After updating the interface state variables, the updated true contact coefficient, interfacial film resistance, and comprehensive damage index are reused to determine the interface calculation information. Simulation tests are then performed again based on the updated interface calculation information and the operating data corresponding to the target condition. After obtaining the simulation data again, the difference between the simulation data and the test data is recalculated, and the interface state variables are updated continuously.

[0249] The set conditions may include one or more of the following: the difference between each simulation data point and the corresponding test data is no greater than the corresponding error threshold; the update amount of each interface state variable between two adjacent simulation tests is no greater than the corresponding state convergence threshold; or the number of simulation tests executed reaches the preset maximum number.

[0250] If the set conditions are not met, the process of updating interface calculation information, determining simulation data, and updating interface state variables continues. When the set conditions are met, the simulation results of the target all-solid-state battery are determined based on the simulation data obtained from the current simulation test and the updated interface state variables.

[0251] One possible implementation involves simulation results that include a pressure window corresponding to the target all-solid-state battery. Multiple candidate stacking pressures can be set, and simulations can be performed separately for each candidate stacking pressure.

[0252] For any candidate stacking pressure, the effective contact pressure of the interface unit is determined based on the candidate stacking pressure. The true contact coefficient, interfacial film resistance, and comprehensive damage index of each interface unit are updated, and the effective reaction area, equivalent interfacial impedance, effective overpotential, and contact heat source are further updated. The operating condition data corresponding to the candidate stacking pressure and the updated interface calculation information are input into the coupled simulation model to determine the minimum true contact coefficient, maximum contact heat source, equivalent stress, comprehensive damage index, and voltage deviation of the cell.

[0253] The target value for evaluating the pressure corresponding to the candidate stacking pressure can be expressed as:

[0254] in, This represents the target value for pressure evaluation corresponding to the candidate stacking pressure. This indicates the candidate stacking pressure. This represents the evaluation weight corresponding to the voltage deviation. This indicates the voltage deviation under candidate stacking pressure. This indicates the preset voltage deviation limit. This indicates the evaluation weight corresponding to contact with the heat source. This represents the maximum contact heat source under candidate stacking pressure. This indicates the preset allowable value for contact with the heat source. This represents the evaluation weight corresponding to the comprehensive damage index. D represents the comprehensive damage index under candidate stacking pressure. This indicates the preset damage tolerance value. This indicates the evaluation weight corresponding to the equivalent stress. This represents the equivalent stress under candidate stacking pressure. This indicates the preset stress limit.

[0255] By dividing voltage deviation, maximum contact heat source, comprehensive damage index, and equivalent stress by their respective limits, the dimensional differences between different evaluation data can be eliminated. The pressure evaluation target value can be used to rank multiple candidate stack pressures that meet the pressure constraints.

[0256] The pressure window corresponding to the target all-solid-state battery can be expressed as:

[0257] in, This indicates the pressure window corresponding to the target all-solid-state battery. This indicates the candidate stacking pressure. This represents the minimum true contact coefficient of the cell interface under candidate stacking pressure. This indicates the preset allowable value for the contact coefficient. This indicates the maximum heat source in contact. This indicates the preset allowable value for contact with the heat source. It represents the equivalent stress. This indicates the preset stress limit. D represents the comprehensive damage index. This indicates the preset damage tolerance value.

[0258] Each candidate stacking pressure is evaluated to determine whether the minimum true contact coefficient of the cell interface, the maximum contact heat source, the equivalent stress, and the comprehensive damage index meet the corresponding pressure constraints. The candidate stacking pressure that simultaneously meets all pressure constraints is determined as the target stacking pressure, and the pressure window is determined based on the distribution range of each target stacking pressure.

[0259] The low-pressure boundary of the pressure window can be determined by the constraint corresponding to the minimum interface actual contact coefficient of the cell or the maximum contact heat source, while the high-pressure boundary of the pressure window can be determined by the constraint corresponding to the equivalent stress or the comprehensive damage index.

[0260] One possible implementation is to include interface risk results in the simulation results. For each interface element, the actual contact coefficient is compared with the preset allowable contact coefficient value, the interface film resistance is compared with the preset film resistance limit value, the contact heat source is compared with the preset allowable contact heat source value, the equivalent stress is compared with the preset stress limit value, and the comprehensive damage index is compared with the preset allowable damage value.

[0261] Based on the comparison results, it can be determined whether the corresponding interface units are subject to risks such as insufficient contact, increased interface impedance, localized overheating, stress damage, or comprehensive degradation. Based on the number, spatial location, and degree of risk of the interface units with risks, the interface risk type, level, and location of the target all-solid-state battery are determined, and these are used as the interface risk results.

[0262] One possible implementation involves simulation results that also include the remaining lifespan of the target all-solid-state battery. Based on the trend of the overall damage index changing during cycling, the first predicted cycle time when the overall damage index reaches a preset failure value is predicted. Based on the capacity decay trend during cycling, the second predicted cycle time when the battery capacity reaches a preset capacity threshold is predicted.

[0263] The remaining useful life can be expressed as:

[0264] in, Indicates the remaining useful life. This represents the current cycle count of the target all-solid-state battery. N represents the predicted cycle count. This represents the predicted comprehensive damage index corresponding to the Nth cycle. This indicates the preset failure value corresponding to the comprehensive damage index. This represents the prediction capacity corresponding to the Nth iteration. This indicates the preset capacity threshold.

[0265] The earlier of the first and second predicted cycle times is determined as the predicted failure time of the target all-solid-state battery, and the remaining service life is determined based on the difference between the predicted failure time and the current cycle time.

[0266] The methods provided in the embodiments of this application will be described below with reference to specific examples.

[0267] Example 1 Example 1 is used to determine the correspondence between the equilibrium contact coefficient and the stacking pressure, and to calibrate the contact parameters in the interface equivalent impedance.

[0268] Single-layer cell samples or corresponding half-cell samples composed of NCM811 cathode material, LPSCl solid electrolyte, and silicon-carbon anode material were selected. Under conditions of 25℃ and 50% state of charge, stacking pressures of 5 MPa, 10 MPa, 20 MPa, 30 MPa, and 50 MPa were sequentially applied to the samples. Each change in stacking pressure was maintained for 20 min, and electrochemical impedance spectroscopy data were collected after the pressure stabilized.

[0269] The high-frequency intercept and mid-to-high-frequency arc radius are extracted from the electrochemical impedance spectroscopy data corresponding to each stacking pressure. The ohmic impedance corresponding to the material layer is subtracted, and the equilibrium contact coefficient and equivalent interfacial impedance corresponding to each stacking pressure are determined based on the remaining interfacial impedance characteristics. For example, when the stacking pressures are 5 MPa, 10 MPa, 20 MPa, 30 MPa, and 50 MPa, the determined equilibrium contact coefficients can be 0.31, 0.49, 0.67, 0.78, and 0.88, respectively.

[0270] Based on the correspondence between stacking pressures, equilibrium contact coefficients, and equivalent interfacial impedances, the parameters in the equilibrium contact coefficient model and the contact shrinkage impedance model are fitted. In one example, the characteristic pressure is 17.6 MPa, the pressure exponent is 1.22, the contact shrinkage impedance exponent is 0.86, and the reference contact shrinkage impedance is... The root mean square relative error of the arc radius in the mid-to-high frequency range is 4.8%.

[0271] When the characteristic error of the electrochemical impedance spectroscopy is less than 8%, and the confidence intervals of the characteristic pressure and pressure index meet the preset calibration requirements, the obtained contact parameters are configured into the coupled simulation model. This allows the true contact coefficient of the interface to be transformed from a pre-set empirical constant into an interface state variable that varies with stacking pressure.

[0272] Example 2 Example 2 uses a single-layer all-solid-state battery cell composed of an NCM811 composite positive electrode, a Li6PS5Cl sulfide solid electrolyte, and a silicon-carbon composite negative electrode as the simulation object. The effective area of ​​the cell is set to 25 cm², the thickness of the positive electrode composite layer is set to 100 μm, the thickness of the solid electrolyte layer is set to 35 μm, the thickness of the negative electrode layer is set to 55 μm, the initial stacking pressure is set to 10 MPa, the ambient temperature is set to 298 K, and the initial value of the convective heat transfer coefficient is set to 10. .

[0273] The effective diffusion coefficient of the positive electrode active material can be set to The effective diffusion coefficient of the negative electrode active material can be set to The effective ionic conductivity of a solid electrolyte can be set to... The interface state parameters were determined using the calibration results obtained in Example 1, and the initial value of the interface film resistance was set to... .

[0274] Based on the aforementioned structural, material, and process data, a one-dimensional electrochemical model domain, along with corresponding thermal and mechanical model domains, was constructed. Interface units were then placed between the positive electrode composite layer and the solid electrolyte layer, and between the negative electrode layer and the solid electrolyte layer. Under 1C charge-discharge conditions, the effective reaction area, equivalent interfacial impedance, effective overpotential, and contact heat source were updated based on the actual contact coefficient and interfacial film resistance of each interface unit. The terminal voltage, temperature distribution, stress distribution, actual contact coefficient distribution, interfacial film resistance variation, and comprehensive damage index were also determined.

[0275] In a set of exemplary simulation results, the root mean square error (RMS) of the terminal voltage obtained using the comparative model with fixed interface parameters was 36 mV, while the RMS error of the terminal voltage obtained using the coupled simulation model of this application was 17 mV. The highest temperature obtained by testing was 34.2℃, while the highest temperature obtained by this application was 34.0℃. The minimum true contact coefficient of the positive electrode interface was 0.63, the minimum true contact coefficient of the negative electrode interface was 0.72, and the average interfacial film resistance was determined by… Growth to The peak value of the contact heat source is The overall damage index was 0.37.

[0276] Therefore, the simulation results can not only represent the terminal voltage and temperature, but also the changes in interface contact loss, interface film resistance growth, contact heat source and damage.

[0277] Example 3 Example 3: Under the same cell structure parameters, material parameters and charge / discharge conditions, a fixed interface model, a first comparative model that only updates the actual interface contact coefficient, a second comparative model that only updates the interface film resistance, and the model of this application that jointly updates the actual interface contact coefficient, interface film resistance and comprehensive damage index were constructed respectively.

[0278] The same initial state, test data and noise parameters were set for each model, and the differences between the terminal voltage, electrochemical impedance spectrum, thickness change, stacking pressure and temperature obtained by each model and the corresponding test data were compared.

[0279] In a set of exemplary results, the root mean square error of the terminal voltage of the fixed interface model is 36 mV, the high-frequency arc error in the electrochemical impedance spectroscopy is 28%, and the thickness and pressure residuals are 22%; the errors corresponding to the first comparative model are 24 mV, 19%, and 8%, respectively; the errors corresponding to the second comparative model are 22 mV, 7%, and 21%, respectively; and the errors corresponding to the model of this application are 17 mV, 5%, and 6%, respectively.

[0280] While updating only the true contact coefficient can reduce thickness and pressure residuals, it may include impedance changes caused by interfacial film growth in the interfacial contact loss. Similarly, updating only the interfacial film resistance can reduce electrochemical impedance spectroscopy errors, but it struggles to account for thickness and pressure variations. The model in this application uses different test data to jointly constrain the true contact coefficient, interfacial film resistance, and comprehensive damage index, enabling a simultaneous reduction in the residuals corresponding to the electrochemical response, interfacial impedance response, and mechanical response.

[0281] Example 4 Example 4 describes a cycle test bench applied to all-solid-state batteries. During each charge-discharge cycle, terminal voltage, surface temperature, stacking pressure, and thickness change data were collected, and electrochemical impedance spectroscopy data were collected every 20 cycles.

[0282] When the residual terminal voltage exceeds 20mV, the residual surface temperature exceeds 1.5K, or the change in the mid-to-high frequency arc characteristics of the electrochemical impedance spectroscopy exceeds 15%, the interface state variables are updated. The true contact coefficients of the positive and negative electrode interfaces are updated based on the residuals of thickness, pressure, and interface impedance characteristics; the interface film resistance is updated based on the residuals of terminal voltage and interface impedance characteristics; and the comprehensive damage index is updated based on the residuals of temperature and capacity.

[0283] In one example, the true contact coefficient of the positive electrode interface was updated from 0.74 to 0.68, the true contact coefficient of the negative electrode interface was updated from 0.80 to 0.76, and the film resistance of the positive electrode interface was... Updated to At the same time, the effective ionic conductivity of solid electrolytes increased from... Revised to The convective heat transfer coefficient is 10 Revised to 11.5 .

[0284] After the update, the root mean square error of the terminal voltage decreased from 29mV to 16mV, the high-frequency arc error in the electrochemical impedance spectroscopy decreased from 18% to 6%, and the thickness and pressure residuals decreased from 14% to 5%. Therefore, the update of the interface state variables not only matches the terminal voltage with the test data, but also matches the interface impedance and mechanical changes with the corresponding test data.

[0285] Example 5 Example 5 uses the single-layer all-solid-state cell from Example 2 as the object, and conducts simulation tests on multiple candidate stacking pressures in the range of 1MPa to 80MPa under the conditions of ambient temperature of 25℃ and charge / discharge rate of 1C.

[0286] For each candidate stacking pressure, update the actual contact coefficient, interfacial film resistance, comprehensive damage index and corresponding interface calculation information, and determine the minimum actual contact coefficient, polarization voltage, maximum contact heat source, equivalent stress and comprehensive damage index after a set number of cycles for the cell corresponding to the candidate stacking pressure.

[0287] For example, when the allowable value of the actual contact coefficient at the interface is set to 0.60, the low-voltage contact insufficiency boundary is 11.7 MPa; when the polarization voltage limit is set to 120 mV, the corresponding low-voltage boundary is 10.4 MPa; when the contact heat source limit is set to... When the equivalent stress limit is set to 180 MPa, the corresponding low-pressure boundary is 9.2 MPa; when the equivalent stress limit is set to 180 MPa, the high-pressure stress boundary is 34.5 MPa; when the allowable value of the comprehensive damage index for the 500th cycle is set to 0.50, the corresponding high-pressure life boundary is 38.8 MPa.

[0288] Based on the above constraints, the recommended stacking pressure window is determined to be 12 MPa to 34 MPa. The low-pressure side of the pressure window is mainly constrained by insufficient interfacial contact, while the high-pressure side is mainly constrained by equivalent stress. As the rate of change, ambient temperature, material system, or cycling history changes, the interfacial state variables can be updated and the corresponding pressure window determined.

[0289] Example 6 Example 6 uses a large-area laminated all-solid-state battery cell for automotive applications as an example. The laminated area of ​​this battery cell can be set to 240mm × 120mm, the rated capacity can be set to 40Ah, the number of laminated layers can be set to 64 layers, and the tabs are located on the short side of the battery cell.

[0290] A one-dimensional electrochemical model is constructed along the cell thickness direction, and a three-dimensional thermo-mechanical model is constructed along the cell planar direction and stacking direction. The electrode position, cell edge clamping conditions, cold plate heat transfer conditions, and module fixture stiffness are configured as corresponding boundary conditions. A data transfer relationship is established between each planar computational unit of the three-dimensional thermo-mechanical model and the corresponding one-dimensional electrochemical model: the three-dimensional thermo-mechanical model transfers local temperature and local normal pressure to the one-dimensional electrochemical model, and the one-dimensional electrochemical model transfers local reaction heat and contact heat source to the three-dimensional thermo-mechanical model. The two models can exchange data every 5 seconds and iterate until the residual between two adjacent calculation results satisfies the convergence condition.

[0291] For example, the edge clamping pressure is set to be 35% lower than that in the center region of the cell, and the contact resistance near the tab is set to be 20% higher than that in other regions. Simulations show that the minimum true contact coefficient at the interface in the center region is 0.71, the minimum true contact coefficient at the interface in the edge region is 0.52, and the highest temperature in the tab region is 39.6℃. When the allowable value of the true contact coefficient at the interface is 0.60, the edge region can be identified as a contact risk area; when the temperature safety limit is 45℃, the tab region can be identified as a major thermal risk area.

[0292] Furthermore, the remaining cycle counts for the central region, edge region, and tab region were determined to be 980, 620, and 760 cycles, respectively, and the minimum remaining cycle count of 620 cycles for each region was determined as the remaining cell-level service life. This allows for the identification of weak areas within the cell based on local interface conditions, providing a basis for adjusting fixture stiffness, tab layout, and thermal management structure.

[0293] Example 7 Example 7 applies the above-described coupled simulation model to a battery management system or a benchtop digital twin system. First, by running the high-fidelity coupled simulation model offline, simulation samples are generated under different states of charge, temperatures, stacking pressures, rate capabilities, and cycling conditions. Then, the high-fidelity coupled simulation model is reduced in order using orthogonal decomposition, response surface methodology, surrogate models, or other order reduction methods.

[0294] The reduced-order online model can retain the state of charge, two concentration modes, two temperature modes, the true contact coefficient of the positive electrode interface, the true contact coefficient of the negative electrode interface, the membrane resistance of the positive electrode interface, the membrane resistance of the negative electrode interface, the comprehensive damage index, and other states selected according to the calculation accuracy. The total number of states can be 10 to 14.

[0295] During online operation, the sampling period for voltage and current data can be set to 100ms, and the sampling period for temperature and pressure data can be set to 1s. Electrochemical impedance spectroscopy test data can be collected every 20 cycles or under preset maintenance conditions. The online model updates the interface state variables based on the currently collected test data and outputs the state of charge, temperature, true contact coefficient of the interface, interface film resistance, comprehensive damage index, pressure window, and remaining service life.

[0296] In one example, the reduced-order model has a single-step runtime of 7.8ms and a peak storage space of 150KB on an automotive-grade microcontroller; under 1C conditions, the terminal voltage error is less than 25mV, the temperature error is less than 1K, and the pressure window error is less than 2MPa.

[0297] When the minimum true contact coefficient at the interface is less than 0.60, the comprehensive damage index is greater than 0.50, or the ratio of the maximum contact heat source to the allowable contact heat source is greater than 0.8, the battery management system can generate interface risk warning information and output prompts for pressure maintenance, power limitation, or shutdown. Therefore, even when the terminal voltage error of the online model is close to that of the equivalent circuit model, it is still possible to further determine whether the battery performance change is mainly caused by interface contact loss or interface film resistance growth. The above operating time and storage space are only examples and can be adjusted according to the processor model, number of states, and sampling period in specific implementations.

[0298] The above primarily describes the solutions provided in this application from the perspective of the device's working principle. It is understood that the all-solid-state battery simulation device, in order to achieve the above functions, includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the algorithm steps of the examples described in the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0299] This application embodiment can divide the all-solid-state battery simulation device into functional modules according to the above method example. For example, each function can be divided into a separate functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module.

[0300] It should be noted that the module division in this embodiment is illustrative and represents only one logical functional division; in actual implementation, other division methods may be used. When dividing functional modules according to their respective functions, Figure 3 A schematic diagram of a possible configuration of the all-solid-state battery simulation device involved in the above and embodiment examples is shown. Figure 3 As shown, the all-solid-state battery simulation device 300 may include: a construction module 301, an update module 302, and a determination module 303.

[0301] Among them, the construction module 301 is used to support the execution of the all-solid-state battery simulation device 300. Figure 2 S201 in the schematic all-solid-state battery simulation method.

[0302] Update module 302 is used to support the execution of the all-solid-state battery simulation device 300. Figure 2 S202 in the schematic all-solid-state battery simulation method.

[0303] Module 303 is used to support the execution of the all-solid-state battery simulation device 300. Figure 2 S203 and S204 in the schematic all-solid-state battery simulation method.

[0304] One possible implementation involves a module used to construct a coupled simulation model of the target all-solid-state battery based on its parameter data. Specifically, this module is used to: construct a battery model domain comprising a positive electrode composite layer, a solid electrolyte layer, a negative electrode layer, and interface units based on the cell structure data in the parameter data; determine the electrochemical, mechanical, thermal, and aging calculation conditions corresponding to the battery model domain based on the material and process data in the parameter data; establish the coupling relationships between changes in reaction current and concentration during electrochemical calculations, changes in contact pressure and stress during mechanical calculations, temperature changes during thermal calculations, and interface degradation information during aging calculations; and construct a coupled simulation model based on the battery model domain, electrochemical calculation conditions, mechanical calculation conditions, thermal calculation conditions, aging calculation conditions, and the coupling relationships.

[0305] One possible implementation involves interface state variables including the true interface contact coefficient. The process of determining the true interface contact coefficient includes: determining the effective contact pressure of the interface unit based on the external stacking pressure, pressure changes caused by chemical expansion, pressure changes caused by thermal expansion, and pressure changes caused by pore relaxation. Based on the effective contact pressure, the interface roughness, and the interface film thickness, the equilibrium contact coefficient of the interface unit is determined. Based on the difference between the equilibrium contact coefficient and the true interface contact coefficient at the previous simulation time, the interface contact recovery is determined. Based on the tensile stress of the interface unit and the cycling history of the target all-solid-state battery, the interface contact loss is determined. Based on the interface contact recovery and interface contact loss, the true interface contact coefficient at the current simulation time is determined.

[0306] One possible implementation includes an interface state variable: interface film resistance. The process of determining the interface film resistance includes: determining the corresponding side reaction current of the interface unit based on the side reaction overpotential and temperature; determining the first influence of interface side reaction film growth on the interface film resistance based on the side reaction current and temperature; determining the second influence of interface cracking on the interface film resistance based on the tensile stress and cracking / debonding state of the interface unit; determining the third influence of interface contact recovery on the interface film resistance based on the actual interface contact coefficient and the interface impedance at the previous simulation time; and determining the interface film resistance at the current simulation time based on the interface film resistance at the previous simulation time, the first influence, the second influence, and the third influence.

[0307] One possible implementation involves the interface state variables further including a comprehensive damage index. The process of determining the comprehensive damage index includes: determining the degree of interface contact damage based on the relationship between the actual interface contact coefficient and a preset allowable contact coefficient value; determining the degree of interface film resistance damage based on the relationship between the interface film resistance and the initial interface film resistance and a preset film resistance limit; determining the degree of stress damage, temperature damage, and capacity damage based on the equivalent stress, maximum temperature, and capacity decay of the target all-solid-state battery, respectively; and determining the comprehensive damage index based on the degree of interface contact damage, the degree of interface film resistance damage, the degree of stress damage, the degree of temperature damage, and the degree of capacity damage, as well as the damage weights corresponding to each degree of damage.

[0308] One possible implementation involves calculating lifespan degradation information on the interface. The process for determining lifespan degradation information includes: determining the lifespan degradation information based on the changes in a comprehensive damage index during the cyclic process.

[0309] One possible implementation includes interface calculation information that further includes: effective reaction area, interface equivalent impedance, effective overpotential, and contact heat source. The update module, used to update the interface calculation information of the target all-solid-state battery based on the current interface state variables, specifically: determining the true contact area based on the nominal interface area and the true interface contact coefficient; determining the reaction current density corresponding to the nominal interface area based on the true contact area, the nominal interface area, and the reaction current density corresponding to the true contact area, while maintaining a consistent total reaction current; determining the effective reaction area based on the true interface contact coefficient and the nominal reaction area of ​​the interface unit; determining the interface equivalent impedance based on the area relationship between the true and nominal interface areas, the interface film resistance, and the contact contraction impedance corresponding to the interface unit; determining the effective overpotential based on the reaction current density corresponding to the nominal interface area, the interface equivalent impedance, the potentials on both sides of the interface unit, the equilibrium potential, and the potential change caused by stress; and determining the contact heat source based on the reaction current density corresponding to the nominal interface area, the interface equivalent impedance, and the nominal unit volume interface area of ​​the interface unit.

[0310] One possible implementation involves a module used to determine the simulation data of the target all-solid-state battery under target operating conditions based on interface calculation information and a coupled simulation model. Specifically, this module: inputs the operating condition data and interface calculation information corresponding to the target operating condition into the coupled simulation model. Based on the effective reaction area, equivalent interface impedance, and effective overpotential, it determines the reaction current, terminal voltage, and lithium concentration distribution of the target all-solid-state battery. Based on the reaction current, contact heat source, and thermal boundary conditions of the target all-solid-state battery, it determines the temperature distribution of the target all-solid-state battery. Based on the lithium concentration distribution, temperature distribution, and stacking pressure corresponding to the target operating condition, it determines the contact pressure distribution, stress distribution, and thickness variation of the target all-solid-state battery. Based on the aging calculation conditions of the coupled simulation, interface film resistance, and the cycling state of the target all-solid-state battery, it determines the impedance and capacity variations of the target all-solid-state battery. Based on the terminal voltage, temperature distribution, contact pressure distribution, thickness variation, impedance variation, and capacity variation, it determines the simulation data.

[0311] One possible implementation involves test data including terminal voltage test data, surface temperature test data, stacking pressure test data, thickness change test data, electrochemical impedance spectroscopy (EIS) test data, and capacity test data. An update module, used to update interface state variables based on simulation data and test data of the target all-solid-state battery collected under target operating conditions, specifically: determining the contact coefficient update amount corresponding to the true interface contact coefficient based on the differences between the stacking pressure test data and thickness change test data and their corresponding simulation data, and the differences between the interface impedance characteristics in the EIS test data and their corresponding simulation data. Determining the membrane resistance update amount corresponding to the interface membrane resistance based on the differences between the terminal voltage test data and their corresponding simulation data, and the differences between the interface impedance characteristics and their corresponding simulation data. Determining the damage index update amount corresponding to the comprehensive damage index based on the updated true interface contact coefficient and interface membrane resistance, and the differences between the surface temperature test data and capacity test data and their corresponding simulation data. Finally, updating the true interface contact coefficient, interface membrane resistance, and comprehensive damage index of the interface unit based on the contact coefficient update amount, membrane resistance update amount, and damage index update amount.

[0312] One possible implementation includes an update module that updates interface state variables based on simulation data and test data of the target all-solid-state battery collected under target operating conditions. This module further includes: determining state sensitivity information based on the changes in the actual contact coefficient, interfacial film resistance, and comprehensive damage index of each simulation data point; determining an information matrix based on the state sensitivity information and the test weights corresponding to each test data point; determining the identifiability results corresponding to the actual contact coefficient, interfacial film resistance, and comprehensive damage index based on the state sensitivity information and the information matrix; determining the target state variable to be updated from the actual contact coefficient, interfacial film resistance, and comprehensive damage index based on the identifiability results; updating the target state variable according to the state update amount corresponding to each target state variable, while maintaining the remaining interface state variables at their corresponding prior state values.

[0313] One possible implementation involves simulation results including a pressure window corresponding to the target all-solid-state battery. The process of determining the pressure window includes: setting multiple candidate stacking pressures; updating interface state variables and interface calculation information based on any candidate stacking pressure; inputting the operating data corresponding to the candidate stacking pressure and the updated interface calculation information into the coupled simulation model to determine the minimum true contact coefficient, maximum contact heat source, equivalent stress, and comprehensive damage index of the cell corresponding to the candidate stacking pressure; determining the pressure constraint results corresponding to the candidate stacking pressure based on the minimum true contact coefficient, maximum contact heat source, equivalent stress, and comprehensive damage index; selecting the target stacking pressure from the multiple candidate stacking pressures whose pressure constraint results satisfy the preset pressure window conditions; and determining the pressure window based on the target stacking pressure.

[0314] One possible implementation involves simulation results that also include interface risk results and remaining service life. The process of determining the interface risk results includes: determining the interface risk results corresponding to the target all-solid-state battery based on the actual interface contact coefficient, interface film resistance, contact heat source, equivalent stress, and comprehensive damage index. The process of determining the remaining service life includes: determining the first predicted time when the comprehensive damage index reaches the preset failure state based on the trend of the comprehensive damage index during cycling; determining the second predicted time when the battery capacity reaches the preset capacity decay state based on the capacity decay trend of the target all-solid-state battery; and determining the remaining service life based on the first predicted time, the second predicted time, and the current cycle time of the target all-solid-state battery.

[0315] It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0316] The all-solid-state battery simulation device 300 provided in this application embodiment is used to perform the above-mentioned... Figure 2 The simulation method for all-solid-state batteries shown can therefore achieve the same effect as the simulation method for all-solid-state batteries described above.

[0317] This application also provides an all-solid-state battery simulation device, which can execute the all-solid-state battery simulation method and related steps in the above method embodiments.

[0318] This application also provides a computer-readable storage medium storing instructions that, when executed, perform the all-solid-state battery simulation method and related steps in the above method embodiments.

[0319] This application also provides a computer program product that, when run on a computer, causes the computer to execute the all-solid-state battery simulation method and related steps described in the above method embodiments.

[0320] In some embodiments, the methods shown in this application can be implemented as computer program instructions encoded in a machine-readable format on a computer-readable storage medium or on other non-transitory media or articles of art.

[0321] This application also provides an all-solid-state battery simulation system 100, such as... Figure 4 As shown, the all-solid-state battery simulation system 100 includes at least one processor 401 and at least one interface circuit 402.

[0322] As an example, when the all-solid-state battery simulation system 100 includes a processor and an interface circuit, the processor can be... Figure 4The processor 401 shown in the solid box (or the processor 401 shown in the dashed box) can be an interface circuit. Figure 4 The interface circuit 402 is shown in the solid box (or the dashed box). When the all-solid-state battery simulation system 100 includes two processors and two interface circuits, then the two processors include... Figure 4 The processor 401 shown in the solid box and the processor 401 shown in the dashed box, these two interface circuits include Figure 4 Interface circuit 402 is shown in both solid and dashed boxes. No limitations are imposed on this.

[0323] Processor 401 and interface circuit 402 can be interconnected via a line. For example, interface circuit 402 can be used to receive signals. Alternatively, interface circuit 402 can be used to send signals to other devices (e.g., processor 401). For instance, interface circuit 402 can read computer instructions stored in memory and send those instructions to processor 401. Processor 401 executes the instructions and, in conjunction with input / output devices, implements the various steps in the above embodiments, such as implementing... Figure 2 The steps performed in the illustrated method embodiment are shown. Of course, this all-solid-state battery simulation system may also include other discrete components, and this application embodiment does not specifically limit this.

[0324] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0325] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0326] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0327] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0328] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to it, or all or part of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0329] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A simulation method for all-solid-state batteries, characterized in that, The method includes: A coupled simulation model of the target all-solid-state battery is constructed based on the parameter data of the target all-solid-state battery. The coupled simulation model includes interface units set between specified materials in the target all-solid-state battery and interface state variables characterizing the interface change characteristics at the corresponding positions of the interface units. The interface calculation information of the target all-solid-state battery is updated according to the current interface state variables; the interface calculation information is used to characterize the impact of interface changes at the corresponding positions of the interface units on the operation of the target all-solid-state battery; Based on the interface calculation information and the coupled simulation model, the simulation data of the target all-solid-state battery under the target operating conditions are determined; Based on the simulation data and the test data of the target all-solid-state battery collected under the target operating conditions, the interface state variable is updated, and the above simulation test is repeated until the set conditions are met. Then, the simulation result of the target all-solid-state battery is determined based on the simulation test.

2. The method according to claim 1, characterized in that, The construction of the coupled simulation model of the target all-solid-state battery based on its parameter data includes: Based on the cell structure data in the parameter data, a battery model domain is constructed that includes a positive electrode composite layer, a solid electrolyte layer, a negative electrode layer, and an interface unit. Based on the material data and process data in the parameter data, the electrochemical calculation conditions, mechanical calculation conditions, thermal calculation conditions and aging calculation conditions corresponding to the battery model domain are determined respectively. The coupling relationship between the reaction current and concentration changes generated during electrochemical calculations, the contact pressure and stress changes generated during mechanical calculations, the temperature changes generated during thermal calculations, and the interface degradation information generated during aging calculations is constructed. The coupled simulation model is constructed based on the battery model domain, the electrochemical calculation conditions, the mechanical calculation conditions, the thermal calculation conditions, the aging calculation conditions, and the coupling relationship.

3. The method according to claim 1, characterized in that, The interface state variables include: the actual interface contact coefficient; the process of determining the actual interface contact coefficient includes: The effective contact pressure of the interface unit is determined based on the external stacking pressure, pressure change caused by chemical expansion, pressure change caused by thermal expansion, and pressure change caused by pore relaxation. The equilibrium contact coefficient corresponding to the interface unit is determined based on the effective contact pressure, the interface roughness of the interface unit, and the interface film thickness. The interface contact recovery amount is determined based on the difference between the equilibrium contact coefficient and the actual interface contact coefficient at the previous simulation moment. Based on the tensile stress of the interface unit and the cycling history of the target all-solid-state battery, the amount of interface contact loss corresponding to the interface unit is determined. The actual contact coefficient of the interface at the current simulation moment is determined based on the interface contact recovery amount and the interface contact loss amount.

4. The method according to claim 3, characterized in that, The interface state variables also include: interface film resistance; the process of determining the interface film resistance includes: The side reaction current corresponding to the interface unit is determined based on the side reaction overpotential and temperature of the interface unit. Based on the side reaction current and the temperature, determine the first influence of the growth of the interfacial side reaction film on the interfacial film resistance; Based on the tensile stress and cracking / debonding state of the interface unit, a second influence of interface cracking on the interface film resistance is determined. Based on the actual contact coefficient of the interface and the interface impedance at the previous simulation time, the third influence of interface contact recovery on the interface film resistance is determined. The interface film resistance at the current simulation moment is determined based on the interfacial film resistance at the time of the upper garment simulation, the first influence quantity, the second influence quantity, and the third influence quantity.

5. The method according to claim 4, characterized in that, The interface state variables also include: a comprehensive damage index; the process of determining the comprehensive damage index includes: The degree of interface contact damage is determined based on the relationship between the actual contact coefficient of the interface and the preset allowable contact coefficient value. The degree of interfacial film resistance damage is determined based on the relationship between the interfacial film resistance, the initial interfacial film resistance, and the preset film resistance limit. Based on the equivalent stress, maximum temperature, and capacity decay of the target all-solid-state battery, the degree of stress damage, temperature damage, and capacity damage are determined respectively. The comprehensive damage index is determined based on the degree of interface contact damage, the degree of interface film resistance damage, the degree of stress damage, the degree of temperature damage, and the degree of capacity damage, as well as the damage weight corresponding to each degree of damage.

6. The method according to claim 5, characterized in that, The interface calculates information including lifetime degradation information; the process for determining the lifetime degradation information includes: The lifespan decline information is determined based on the changes in the comprehensive damage index during the cyclic process.

7. The method according to claim 5, characterized in that, The interface calculation information also includes: effective reaction area, interface equivalent impedance, effective overpotential, and contact heat source; updating the interface calculation information of the target all-solid-state battery according to the current interface state variables includes: The actual contact area is determined based on the nominal interface area and the actual contact coefficient of the interface; Under the condition that the total reaction current remains constant, the reaction current density corresponding to the nominal interface area is determined based on the actual contact area, the nominal interface area, and the reaction current density corresponding to the actual contact area. The effective reaction area is determined based on the actual contact coefficient of the interface and the nominal reaction area of ​​the interface unit. The equivalent impedance of the interface is determined based on the area relationship between the actual contact area and the nominal interface area, the interface film resistance, and the contact shrinkage impedance corresponding to the interface unit. The effective overpotential is determined based on the reaction current density corresponding to the nominal interface area, the equivalent impedance of the interface, the potential on both sides of the interface unit, the equilibrium potential, and the potential change caused by stress. The contact heat source is determined based on the reaction current density corresponding to the nominal interface area, the equivalent impedance of the interface, and the nominal unit volume interface area of ​​the interface unit.

8. The method according to claim 7, characterized in that, The step of determining the simulation data of the target all-solid-state battery under the target operating condition based on the interface calculation information and the coupled simulation model includes: Input the operating condition data corresponding to the target operating condition and the interface calculation information into the coupled simulation model; Based on the effective reaction area, interfacial equivalent impedance, and effective overpotential, the reaction current, terminal voltage, and lithium concentration distribution of the target all-solid-state battery are determined. The temperature distribution of the target all-solid-state battery is determined based on the reaction current, the contact heat source, and the thermal boundary conditions of the target all-solid-state battery. Based on the lithium concentration distribution, temperature distribution, and stacking pressure corresponding to the target operating condition, the contact pressure distribution, stress distribution, and thickness variation of the target all-solid-state battery are determined. Based on the aging calculation conditions of the coupled simulation dipole, the interface film resistance, and the cycling state of the target all-solid-state battery, the impedance change and capacity change of the target all-solid-state battery are determined. The simulation data are determined based on the terminal voltage, temperature distribution, contact pressure distribution, thickness variation, impedance variation, and capacity variation.

9. The method according to claim 8, characterized in that, The test data includes terminal voltage test data, surface temperature test data, stacking pressure test data, thickness change test data, electrochemical impedance spectroscopy test data, and capacity test data; The step of updating the interface state variables based on the simulation data and the test data of the target all-solid-state battery collected under the target operating condition includes: Based on the differences between the stacking pressure test data and thickness change test data and the corresponding simulation data, and the differences between the interface impedance characteristics in the electrochemical impedance spectroscopy test data and the corresponding simulation data, the contact coefficient update amount corresponding to the true interface contact coefficient is determined. Based on the difference between the terminal voltage test data and the corresponding simulation data, and the difference between the interface impedance characteristics and the corresponding simulation data, the membrane resistance update amount corresponding to the interface membrane resistance is determined. Based on the updated true contact coefficient and interfacial film resistance, as well as the differences between the surface temperature test data and capacity test data and the corresponding simulation data, the damage index update amount corresponding to the comprehensive damage index is determined. Based on the updated contact coefficient, updated membrane resistance, and updated damage index, the actual contact coefficient, membrane resistance, and overall damage index of the interface unit are updated.

10. The method according to claim 9, characterized in that, The step of updating the interface state variable based on the simulation data and the test data of the target all-solid-state battery collected under the target operating condition further includes: Based on the changes in the simulation data with respect to the actual contact coefficient, interfacial film resistance, and comprehensive damage index of the interface, the state sensitivity information is determined. Based on the state sensitivity information and the test weights corresponding to each test data, an information matrix is ​​determined; Based on the state sensitivity information and the information matrix, determine the identifiability results corresponding to the true contact coefficient of the interface, the interfacial film resistance, and the comprehensive damage index. Based on the identifiability results, the target state variable to be updated is determined from the actual contact coefficient of the interface, the interfacial film resistance, and the comprehensive damage index. Update the target state variables according to the state update amount corresponding to each target state variable, and keep the remaining interface state variables as their corresponding prior state values.

11. The method according to claim 8, characterized in that, The simulation results include the pressure window corresponding to the target all-solid-state battery; the process of determining the pressure window includes: Set multiple candidate stacking pressures; For any of the candidate stacking pressures, update the interface state variables and the interface calculation information based on the candidate stacking pressures; The working condition data corresponding to the candidate stacking pressure and the updated interface calculation information are input into the coupled simulation model to determine the minimum true contact coefficient of the cell interface, the maximum contact heat source, the equivalent stress and the comprehensive damage index corresponding to the candidate stacking pressure. Based on the actual contact coefficient of the minimum interface of the battery cell, the maximum contact heat source, the equivalent stress, and the comprehensive damage index, the pressure constraint result corresponding to the candidate stacking pressure is determined. Select the target stacking pressure from the multiple candidate stacking pressures whose pressure constraint results satisfy the preset pressure window conditions; The pressure window is determined based on the target stacking pressure.

12. The method according to claim 8, characterized in that, The simulation results also include interface risk results and remaining useful life; the process for determining the interface risk results includes: Based on the actual contact coefficient, interfacial film resistance, contact heat source, equivalent stress, and comprehensive damage index, the interface risk result corresponding to the target all-solid-state battery is determined. The process for determining the remaining useful life includes: Based on the changing trend of the comprehensive damage index with the cyclic process, the first predicted time when the comprehensive damage index reaches the preset failure state is determined. Based on the capacity decay trend of the target all-solid-state battery, determine the second predicted time when the battery capacity reaches the preset capacity decay state; The remaining lifespan is determined based on the first prediction time, the second prediction time, and the current cycle time of the target all-solid-state battery.

13. A fully solid-state battery simulation device, characterized in that, The device includes: A construction module is used to construct a coupled simulation model of the target all-solid-state battery based on the parameter data of the target all-solid-state battery; the coupled simulation model includes interface units set between specified materials in the target all-solid-state battery and interface state variables characterizing the interface change characteristics at the corresponding positions of the interface units; An update module is used to update the interface calculation information of the target all-solid-state battery according to the current interface state variables; the interface calculation information is used to characterize the impact of interface changes at the corresponding positions of the interface units on the operation of the target all-solid-state battery; The determination module is used to determine the simulation data of the target all-solid-state battery under the target operating condition based on the interface calculation information and the coupled simulation model; The determining module is further configured to update the interface state variable based on the simulation data and the test data of the target all-solid-state battery collected under the target operating condition, repeat the above simulation test until the set conditions are met, and then determine the simulation result of the target all-solid-state battery based on the simulation test.

14. A fully solid-state battery simulation device, characterized in that, The all-solid-state battery simulation device includes a processor and a memory, the memory storing machine-executable instructions that can be executed by the processor, and the processor executing the machine-executable instructions to implement the all-solid-state battery simulation method according to any one of claims 1 to 12.

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