Crack propagation test method, apparatus, device, and product for all-solid-state battery

Abstract

The disclosure provides a crack propagation test method, device, equipment and product of an all-solid-state battery. By establishing a lithium ion diffusion induced strain model, a phase field fracture model and a fatigue damage model, not only can the real material strain in the positive electrode particle under the rigid constraint of the solid electrolyte and the crack propagation and interface peeling process in the particle under the strain be simulated in a fine-grained manner during the cycle charging process of the all-solid-state battery, but also the contact interface between the positive electrode particle and the solid electrolyte and the corresponding material strain and crack propagation under the solid electrolyte can be simulated in a fine-grained manner, so that various mechanical failure behaviors of the all-solid-state battery during the cycle charging and discharging process can be truly reflected, the spontaneous propagation and interaction of the crack between the particles, the electrolyte interface and the electrolyte can be fully characterized, and the crack propagation can be fully simulated.

Description

Technical Field

[0001] This disclosure relates to the field of energy storage battery technology, and more specifically, to a method, apparatus, equipment, and product for testing crack propagation in all-solid-state batteries. Background Technology

[0002] All-Solid-State Batteries (ASSBs) are batteries that use solid electrolytes instead of liquid electrolytes. Due to their high energy density and safety, they have become an important development direction for next-generation energy storage systems and are currently widely used in various electric vehicles and low-altitude flight equipment. However, the rigid contact interface between the solid electrolyte and electrode materials in all-solid-state batteries is prone to mechanical failure during battery cycling, leading to easy crack initiation and interface delamination in electrode particles, resulting in battery capacity decay and shortened battery life. Therefore, in the design of all-solid-state batteries, it is necessary to simulate the mechanical failure behavior that may occur during battery cycling in advance to predict battery performance and make corresponding optimizations.

[0003] However, some traditional simulation methods, such as the finite element method, have the problem of not being able to fully simulate the various mechanical behaviors inside the battery during cyclic charging and discharging, which reduces the simulation accuracy. Summary of the Invention

[0004] This disclosure provides at least one method, apparatus, device, and product for testing crack propagation in all-solid-state batteries, enabling fine-grained simulation of various mechanical behaviors inside the battery during cyclic charging and discharging, thereby improving simulation accuracy.

[0005] In a first aspect, embodiments of this disclosure provide a crack propagation testing method for all-solid-state batteries, including:

[0006] Obtain charging and material parameter information for all-solid-state batteries; Based on the phase-field method and the material parameter information, a coupled model for the electrochemical and mechanical behavior inside the all-solid-state battery is constructed. The coupled model includes at least a mutually coupled lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model. The lithium-ion diffusion-induced strain model is used to determine the material strain caused by lithium-ion diffusion inside the all-solid-state battery under the electrochemical and mechanical behaviors. The fatigue damage model is used to determine the material toughness under the material strain. The phase-field fracture model is used to determine the material crack variables under the material strain and the material toughness. The charging and discharging process of the all-solid-state battery is simulated according to the charging parameter information, and the coupling model is used to determine the first material strain and first crack variable inside the positive electrode particles of the all-solid-state battery, the second material strain and second crack variable at the contact interface between the positive electrode particles and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte at each moment in the charging and discharging process. Based on the first crack variable, the second crack variable, the third crack variable, and the damage threshold at each moment, the crack path and damage distribution of the all-solid-state battery during the charging and discharging process are determined, and based on the first material strain, the second material strain, and the third material strain, the stress evolution result of the all-solid-state battery during the charging and discharging process is determined.

[0007] Secondly, embodiments of this disclosure also provide a crack propagation testing apparatus for all-solid-state batteries, including: The acquisition module is used to acquire charging parameter information and material parameter information of the all-solid-state battery; A construction module is used to construct a coupled model of the electrochemical and mechanical behavior inside an all-solid-state battery based on the phase-field method and the material parameter information. The coupled model includes at least a mutually coupled lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model. The lithium-ion diffusion-induced strain model is used to determine the material strain caused by lithium-ion diffusion inside the all-solid-state battery under the electrochemical and mechanical behaviors. The fatigue damage model is used to determine the material toughness under the material strain. The phase-field fracture model is used to determine the material crack variables under the material strain and the material toughness. The first determining module is used to simulate the charging and discharging process of the all-solid-state battery according to the charging parameter information, and use the coupling model to determine the first material strain and first crack variable inside the positive electrode particles of the all-solid-state battery, the second material strain and second crack variable at the contact interface between the positive electrode particles and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte at each moment in the charging and discharging process. The second determining module is used to determine the crack path and damage distribution of the all-solid-state battery during the charging and discharging process based on the first crack variable, the second crack variable, the third crack variable, and the damage threshold at each time moment, and to determine the stress evolution result of the all-solid-state battery during the charging and discharging process based on the first material strain, the second material strain, and the third material strain.

[0008] Thirdly, an optional implementation of this disclosure also provides a computer device, a processor, and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the processor is used to execute the machine-readable instructions stored in the memory, wherein the machine-readable instructions, when executed by the processor, perform the steps in the first aspect described above.

[0009] Fourthly, an optional implementation of this disclosure also provides a computer program product, including a computer program that, when run, implements the steps in the first aspect described above.

[0010] The crack propagation testing method, apparatus, equipment, and product for all-solid-state batteries provided in this disclosure, by establishing a lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model, can not only finely simulate the actual material strain inside the cathode particles under the rigid constraint of the solid electrolyte, as well as the crack propagation and interface delamination process within the particles under strain, during the cyclic charging process of all-solid-state batteries, but also finely simulate the contact interface between the cathode particles and the solid electrolyte, and the corresponding material strain and crack propagation under the solid electrolyte. This realistically reflects various mechanical failure behaviors of all-solid-state batteries during cyclic charging and discharging, comprehensively characterizing the spontaneous propagation and interaction of cracks at the particle-electrolyte interface and between the electrolytes, thus playing a comprehensive role in simulating crack propagation. Finally, by outputting crack paths, damage distribution, and stress evolution results, it can accurately reflect various mechanical failure behaviors of all-solid-state batteries during cyclic charging and discharging, improving simulation accuracy and granularity.

[0011] Furthermore, the crack propagation testing method, apparatus, equipment, and product provided in this disclosure can more accurately predict the failure mode and capacity decay trend of all-solid-state batteries by utilizing the output crack path, damage distribution, and stress evolution results. This improves the accuracy of assessing the lifespan information and safety of all-solid-state batteries and provides effective simulation tools and theoretical basis for electrode material design, contact interface optimization, and battery operating condition strategy formulation.

[0012] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the embodiments will be briefly described below. These drawings are incorporated in and constitute a part of this specification. They illustrate embodiments conforming to this disclosure and, together with the specification, serve to explain the technical solutions of this disclosure. It should be understood that the following drawings only show some embodiments of this disclosure and should not be considered as limiting the scope. Those skilled in the art can obtain other related drawings based on these drawings without creative effort.

[0014] Figure 1 A flowchart of a crack propagation test method for an all-solid-state battery provided in an embodiment of this disclosure is shown; Figure 2 A schematic diagram of the structure of an all-solid-state battery system provided in an embodiment of this disclosure is shown; Figure 3 A schematic diagram of a notch provided in an embodiment of this disclosure is shown; Figure 4 A schematic diagram of a crack propagation testing apparatus for an all-solid-state battery provided in an embodiment of this disclosure is shown. Figure 5 A schematic diagram of the structure of a computer device provided in an embodiment of this disclosure is shown. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. The components of the embodiments of this disclosure described and shown herein can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this disclosure is not intended to limit the scope of the claimed disclosure, but merely represents selected embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0016] Furthermore, the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein.

[0017] In this article, "multiple or several" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0018] Research has revealed that simulating the mechanical failure behavior of all-solid-state batteries suffers from high experimental research costs, long cycles, and difficulty in real-time observation of crack evolution within the battery. For example, traditional finite element simulation methods require pre-setting crack propagation paths during crack propagation simulations, making it difficult to handle multi-crack interactions and complex interface behaviors at the cathode particle interior and the interface between the cathode particle and the solid electrolyte cell, thus failing to simulate realistic crack propagation behavior. Furthermore, traditional mechanical failure simulation methods for composite cathodes in all-solid-state batteries largely fail to adequately consider the rigid constraints of the solid electrolyte (SE), the coupling effect of lithium-ion diffusion and strain-stress, and the fatigue damage evolution under cyclic loading (i.e., the mechanical action applied during cyclic charging and discharging). Consequently, they cannot accurately reflect the crack initiation, propagation, and delamination behavior within the cathode particles and at the contact interface during actual charging and discharging processes. For example, existing methods often use preset crack paths or simplified interface models, which cannot simulate the spontaneous propagation and interaction of cracks at the interface between cathode particles and solid electrolytes, resulting in low simulation accuracy and poor realism.

[0019] Based on the above research, this disclosure provides a method, apparatus, equipment, and product for testing crack propagation in all-solid-state batteries. By establishing a lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model, it can simulate, in a fine-grained manner, the actual material strain inside the cathode particles under the rigid constraint of the solid electrolyte, as well as the crack propagation and interface delamination processes within the particles under strain, during the cyclic charging process of all-solid-state batteries. It can also simulate, in a fine-grained manner, the contact interface between the cathode particles and the solid electrolyte, and the corresponding material strain and crack propagation under the solid electrolyte. This allows for a realistic reflection of various mechanical failure behaviors of all-solid-state batteries during cyclic charging and discharging, comprehensively characterizing the spontaneous propagation and interaction of cracks at the particle-electrolyte interface and between the electrolytes, thus playing a comprehensive role in simulating crack propagation. Finally, by outputting crack paths, damage distribution, and stress evolution results, it can accurately reflect various mechanical failure behaviors of all-solid-state batteries during cyclic charging and discharging, improving simulation accuracy and granularity.

[0020] The shortcomings of the above solutions are the result of the inventor's practical experience and careful research. Therefore, the discovery process of the above problems and the solutions proposed in this disclosure below should be considered as the inventor's contribution to this disclosure.

[0021] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0022] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0023] To facilitate understanding of this embodiment, a detailed description of the crack propagation test method for all-solid-state batteries disclosed in this disclosure will be provided first. The execution subject of the crack propagation test method for all-solid-state batteries provided in this disclosure is generally a terminal device or other processing device with certain computing capabilities. The terminal device can be a user equipment (UE), mobile device, user terminal, terminal, personal digital assistant device (PDA), handheld device, computer device, etc. In some possible implementations, the crack propagation test method for all-solid-state batteries can be implemented by a processor calling computer-readable instructions stored in memory.

[0024] The following describes the crack propagation test method for all-solid-state batteries provided in this disclosure, taking a computer device as the execution subject as an example.

[0025] like Figure 1 The flowchart shown is a method for testing the crack propagation of an all-solid-state battery according to an embodiment of this disclosure, which may include the following steps: S101: Obtain charging parameter information and material parameter information of the all-solid-state battery.

[0026] Here, charging parameter information indicates the battery parameters of the all-solid-state battery during charging and discharging, specifically including the State of Charge (SOC) range and charging rate. Material parameter information can include parameters of various battery materials within the all-solid-state battery. For example, parameters of the cathode particles, the solid electrolyte, and the interface between the cathode particles and the solid electrolyte. Current simulation methods often neglect the parameters of the solid electrolyte and the interface, leading to poor simulation accuracy and performance.

[0027] In this application, the simulation not only considers the parameter information of the cathode particles, but also constructs the contact interface and simultaneously considers the parameter information of the contact interface and the solid electrolyte, thereby achieving fine-grained simulation.

[0028] To facilitate the simulation of the mechanical failure behavior of all-solid-state batteries during the charging and discharging process, embodiments of this application provide, as follows: Figure 2 The diagram shows a structural schematic of an all-solid-state battery system (ASSB). The key components of an ASSB include a composite cathode, carbon black, a cathode-electrolyte interface, a solid electrolyte, and a lithium anode. The composite cathode is also known as a composite positive electrode. Figure 2 The composite cathode particles shown are the positive electrode particles in this application. Carbon black and solid electrolyte serve as the basic conductive materials, improving the conductivity of the all-solid-state battery. The cathode-electrolyte interface is the boundary between the positive electrode particles and the electrolyte. Lithium ions from the solid electrolyte and the lithium anode can diffuse to the positive electrode particles through the cathode-electrolyte interface, thus achieving conductivity. The lithium anode provides lithium ions during charging and discharging. In other words, the composite cathode has active particles (i.e., lithium ions) embedded in the conductive matrix (i.e., solid electrolyte and carbon black). To accurately capture crack initiation and propagation within the battery at the micron-scale, this application employs a representative volumetric unit model to simulate crack initiation and propagation, that is, using the crack initiation and propagation of one positive electrode particle to characterize the crack initiation and propagation of all positive electrode particles. For example, in... Figure 2 The diagram illustrates crack propagation in a composite cathode based on a representative particle-interface model, where the crack propagation of a single representative particle (i.e., a specific cathode particle) represents the crack propagation of all cathode particles. Lithium flux refers to the amount of lithium ions that diffuse into the cathode particles during charging and discharging. Figure 2 The interface in this context refers to the contact interface between the positive electrode particles and the solid electrolyte, as described in this application. The defect refers to the cracks generated inside the positive electrode particles during charging and discharging. At the contact interface, Figure 2The Young's modulus and critical energy release rate of different materials are also shown, i.e., the Young's modulus of the cathode particles. particle and critical energy release rate G c-particle Young's modulus at the contact interface interface and critical energy release rate G c-interface and Young's modulus of solid electrolytes electrolyte and critical energy release rate G c-electrolyte .exist Figure 2 The parameter values ​​for each part of the material can be found in Table 1 below. Figure 2 About interface and G c-interface The values ​​of these parameters are not shown in Table 1, but they are also parameters that need to be obtained synchronously during crack propagation testing.

[0029] As shown in Table 1 below, this application provides a schematic table of material parameters and values ​​for all-solid-state batteries:

[0030] In practice, when it is determined that crack propagation simulation needs to be performed on any all-solid-state battery, it is necessary to simultaneously obtain the state of charge (SOC) range, charging rate, and material parameter information of various materials of the all-solid-state battery.

[0031] S102: Based on the phase-field method and material parameter information, construct a coupled model for the electrochemical and mechanical behavior inside the all-solid-state battery; the coupled model includes at least a mutually coupled lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model; the lithium-ion diffusion-induced strain model is used to determine the material strain caused by lithium-ion diffusion inside the all-solid-state battery under electrochemical and mechanical behavior; the fatigue damage model is used to determine the material toughness under material strain; the phase-field fracture model is used to determine the material crack variables under material strain and material toughness.

[0032] Here, the lithium-ion diffusion-induced strain model can simulate the changes in lithium-ion concentration within the cathode particles caused by electrochemical behavior during cyclic charging and discharging, resulting in changes in material strain within the particles under mechanical behavior, thus achieving the coupling between lithium-ion diffusion and the stress field. The mechanical material strain caused by changes in lithium-ion concentration is also the particle volume strain caused by intercalation within the battery. The fatigue damage model can simulate changes in material toughness under strain, and these changes in toughness can characterize whether the material is experiencing fatigue damage. The phase-field fracture model can simulate crack initiation and evolution under changes in material toughness, and crack initiation and evolution can be characterized using material crack variables.

[0033] By introducing material crack variables that can describe the spontaneous evolution of crack topology and fatigue damage models that can describe material fatigue damage, and coupling the interaction between lithium-ion diffusion and stress field, the dynamic propagation behavior of cracks and the damage behavior of materials during cyclic charging and discharging under the rigid interface constraint of all-solid-state batteries can be simulated more realistically. Furthermore, since the phase-field method can describe crack topological changes by introducing continuous variables, it is suitable for fracture simulation under the coupling of multiple physics fields (i.e., electrochemical and mechanical fields) within solid-state batteries. Therefore, this application proposes a method for creating the coupled model using the phase-field method.

[0034] In practical implementation, it can be based on the phase-field method and Figure 2 The structure of the all-solid-state battery shown is used to construct an initial coupling model that does not include specific material parameter information. Then, the material parameter information of the all-solid-state battery to be tested is substituted into the initial coupling model to obtain a dual-field coupling model related to the all-solid-state battery.

[0035] S103: Simulate the charging and discharging process of the all-solid-state battery according to the charging parameter information, and use the coupled model to determine the first material strain and first crack variable inside the positive electrode particle of the all-solid-state battery, the second material strain and second crack variable at the contact interface between the positive electrode particle and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte at each moment in the charging and discharging process.

[0036] Here, the first material strain can be the strain inside the cathode particle caused by changes in lithium concentration. This strain may lead to cracks inside the cathode particle, and the size of these cracks can be characterized using a first crack variable. The second material strain is used to characterize the strain present at the contact interface, which can be caused by the first material strain. The second material strain may lead to cracks at the contact interface, and the size of these cracks can be characterized using a second crack variable. The third material strain is used to characterize the strain present at the solid electrolyte, which can be caused by the second material strain and / or the first material strain. The third material strain may lead to cracks in the solid electrolyte, and the size of these cracks can be characterized using a third crack variable.

[0037] In practice, the charging and discharging processes of an all-solid-state battery can be simulated cyclically according to the charging state range and charging rate. Then, during the simulated charging process, a coupled model can be used to determine the first material strain and first crack variable inside a representative positive electrode particle at each moment of the charging process, the second material strain and second crack variable at the contact interface at each moment, and the third material strain and third crack variable of the solid electrolyte at each moment. Similarly, during the simulated discharging process, a coupled model can be used to determine the first material strain and first crack variable inside a representative positive electrode particle at each moment of the discharging process, the second material strain and second crack variable at the contact interface at each moment, and the third material strain and third crack variable of the solid electrolyte at each moment.

[0038] Here, by introducing phase-field crack variables that can describe the spontaneous evolution of crack topology, and on this basis coupling the interaction between lithium-ion diffusion and stress field, it is possible to more realistically simulate the dynamic crack propagation behavior of various materials during cyclic charging and discharging under the rigid interface constraint of all-solid-state battery.

[0039] Optionally, to reduce the computational burden of the simulation, the solid electrolyte can be assumed to be a rigid electrolyte, thus setting its corresponding third material strain and third crack variables to 0, meaning that no strain or cracks are generated at the solid electrolyte. During the simulation, only the strain and crack variables inside the cathode particles and at the contact interface can be solved.

[0040] S104: Based on the first crack variable, the second crack variable, the third crack variable, and the damage threshold at each moment, determine the crack path and damage distribution of the all-solid-state battery during the charging and discharging process, and based on the first material strain, the second material strain, and the third material strain, determine the stress evolution result of the all-solid-state battery during the charging and discharging process.

[0041] Here, the damage threshold can be a pre-set threshold, the size of which can be set empirically, and this embodiment does not impose a specific limitation. For example, the preset threshold can be 0.98. The magnitude of the crack variable can characterize the size of the crack, and the relationship between the crack size and the damage threshold can characterize whether fatigue damage exists in the material. The crack path is used to indicate the crack propagation path of the material during the charging and discharging process, and the damage distribution is used to indicate the location distribution of fatigue damage in the material during the charging and discharging process. The stress evolution result is used to indicate the change in the magnitude of stress in the material during the charging and discharging process. The generation of stress will produce strain, so the stress of the material can be determined based on the material strain.

[0042] In practical implementation, the crack path inside the positive electrode particles of the all-solid-state battery during the charging and discharging process can be determined using the first crack variable obtained at each moment during the simulated charging and discharging process. The crack path at the contact interface of the all-solid-state battery during the charging and discharging process can be determined using the second crack variable obtained at each moment during the simulated charging and discharging process. The crack path at the solid electrolyte of the all-solid-state battery during the charging and discharging process can be determined using the relationship between the first / second / third crack variables obtained at each moment and the damage threshold. Based on the first / second / third material strain obtained at each moment, the first / second / third stress at each moment can be determined, and based on the first / second / third stress at each moment, the stress evolution results inside the positive electrode particles / contact interface / solid electrolyte during the charging and discharging process can be determined.

[0043] Optionally, the overall crack path and damage distribution of the all-solid-state battery during the charging and discharging process can be determined based on the first crack variable, the second crack variable, the third crack variable, and the damage threshold at each moment. At the same time, the overall stress evolution result of the all-solid-state battery during the charging and discharging process can be determined based on the first material strain, the second material strain, and the third material strain obtained at each moment.

[0044] Thus, this application provides a method for simulating crack propagation in all-solid-state batteries that integrates phase-field method and fatigue damage mechanics. First, it obtains the battery's state of charge range, charging rate, and material parameters. Then, it establishes a multi-physics coupled model that integrates lithium-ion diffusion, stress field evolution, and phase-field fracture. This coupled model specifically includes a stress-driven lithium-ion diffusion model, an intercalation-induced strain field, a phase-field crack model, and a fatigue damage model under cyclic loading. Then, under set charge-discharge cycle conditions (i.e., within the obtained state of charge range and charging rate), it simulates the entire process from crack initiation and interface peeling to inward propagation of the cathode particles / contact interface / solid electrolyte. This yields results that realistically characterize the crack path, damage distribution, and stress evolution under various mechanical failure behaviors during charge and discharge, thereby improving simulation accuracy and granularity.

[0045] In one embodiment, considering that traditional simulation methods have limitations in quantifying the impact of State of Charge (SOC) range and charging rate on damage accumulation, leading to significant deviations in the prediction of battery life and safety, this application also proposes a method for battery life assessment based on simulation results. Specifically, after obtaining the crack path, damage distribution, and stress evolution results, life assessment can be achieved according to the following steps 1-2: Step 1: Based on the crack path, damage distribution, and stress evolution results of the all-solid-state battery under different charge-discharge cycles, determine the correlation between the crack evolution trend, damage distribution trend, and stress evolution trend of the all-solid-state battery and the number of charge-discharge cycles.

[0046] Here, the correlations can include the relationships between crack evolution within the cathode particles / contact interface / solid electrolyte of an all-solid-state battery and the number of charge-discharge cycles, respectively; the relationships between damage distribution within the cathode particles / contact interface / solid electrolyte of an all-solid-state battery and the number of charge-discharge cycles, respectively; and the relationships between stress evolution within the cathode particles / contact interface / solid electrolyte of an all-solid-state battery and the number of charge-discharge cycles, respectively. Alternatively, the correlations can include the relationships between the overall crack evolution of an all-solid-state battery and the number of charge-discharge cycles, the relationships between the overall damage distribution of an all-solid-state battery and the number of charge-discharge cycles, and the relationships between the overall stress evolution of an all-solid-state battery and the number of charge-discharge cycles, respectively.

[0047] In practice, the crack paths, damage distribution, and stress evolution results of the all-solid-state battery under different charge-discharge cycles can be obtained. Then, the crack paths under each charge-discharge cycle are used as the crack path evolution for each charge-discharge cycle. Based on the crack path evolution for each charge-discharge cycle, the correlation between the crack evolution trend of the all-solid-state battery and the number of charge-discharge cycles is determined. Simultaneously, based on the damage distribution under each charge-discharge cycle, the delamination area ratio of the cathode particle interface and the electrolyte interface, and the cathode particle damage area ratio can be calculated for each charge-discharge cycle. Using these ratios, the total damage area ratio of the all-solid-state battery under each charge-discharge cycle is determined. Based on the total damage area ratio under each charge-discharge cycle, the damage distribution trend of the all-solid-state battery under each charge-discharge cycle is determined. Finally, based on the damage distribution trend under each charge-discharge cycle, the correlation between the damage distribution trend of the all-solid-state battery and the number of charge-discharge cycles is determined. Furthermore, the stress evolution trend corresponding to each charge-discharge cycle can be determined based on the stress evolution results under each charge-discharge process. Then, based on the stress evolution trend corresponding to each charge-discharge cycle, the correlation between the stress evolution trend of the all-solid-state battery and the number of charge-discharge cycles can be determined.

[0048] Step 2: Based on the correlation, determine the battery capacity decay trend and lifespan information of the all-solid-state battery under the charging parameter information and material parameter information.

[0049] In practical implementation, the correlation between crack evolution trends, damage distribution trends, and stress evolution trends and the number of charge-discharge cycles can be established. Based on the influence of cracks, damage, and stress on battery capacity, the battery capacity decay trend of the all-solid-state battery with the number of charge cycles can be determined under specific charging and material parameters. Based on the battery capacity decay trend under the number of charge cycles, the service life of the all-solid-state battery under specific charging and material parameters can be predicted.

[0050] In another embodiment, this application can also optimize the charging parameters and material parameters of the all-solid-state battery based on the battery capacity decay trend and lifespan information of the all-solid-state battery under different charging parameter information and different material parameter information.

[0051] In other words, for all-solid-state batteries, by using steps S102 to S104 above and combining different charging and material parameters, the crack path, damage distribution, and stress evolution results of the all-solid-state battery under various combinations of charging and material parameters can be output using a coupled model. Then, for any combination of charging and material parameters, the battery capacity decay trend and lifespan information of the all-solid-state battery under that combination can be determined based on the crack path, damage distribution, and stress evolution results, following steps 1 and 2 above.

[0052] By utilizing the capacity degradation trends and lifespan information of all-solid-state batteries under different combinations, we can optimize charging parameters, material parameters, and contact interfaces of all-solid-state batteries. Charging parameter optimization includes, for example, optimizing the state of charge range and charging rate. Material parameter optimization includes optimizing the material parameters of the cathode particles, the material parameters of the contact interface, and the overall parameters of the solid electrolyte. Contact interface optimization includes optimizing the compatibility between individual cathode particles and the solid electrolyte, optimizing the mixing relationship between cathode particles, solid electrolyte, and carbon black, and optimizing the thickness of the solid electrolyte interface.

[0053] In this way, by quantifying the relationship between crack damage and key operating parameters (such as SOC range and charging rate), this application can more accurately predict the mechanical failure mode and capacity decay behavior of the battery, thereby significantly improving the accuracy of the assessment of the life and safety of all-solid-state batteries. It provides effective simulation methods and theoretical guidance for electrode material design, contact interface optimization, solid electrolyte interface optimization and cycle charge and discharge strategy formulation.

[0054] In one embodiment, S103 described above can be implemented according to the following steps: S103-1: For any moment during the charging and discharging process, the lithium concentration of the cathode particles at the current moment is determined using the lithium-ion diffusion-induced strain model, based on the lithium flux around the cathode particles at the current moment, the first crack variable at the previous moment, and the charging parameter information.

[0055] Here, lithium flux can be defined as the amount of lithium ions that diffuse to the vicinity of the cathode particles. This flux is affected by the charging parameters of the all-solid-state battery and the size of the cracks in the cathode particles.

[0056] In this context, with the current time being the initial time, the lithium flux around the positive electrode particles at the current time is a preset lithium flux; the first crack variable at the previous time is a preset value. Here, the initial time can be the start time of the first charge, and at the initial time, an external flux load for the lithium flux can be pre-input. ,according to The initial lithium flux vector is determined by the vector in the normal direction and the boundary conditions. , that is ;in, n Indicates the normal direction. Indicate boundary conditions, External flux load on boundary conditions Since no cracks will necessarily form inside the all-solid-state battery at the beginning of the first charge, the first crack variable at the previous moment... d-crack This can be a preset value; for example, the preset value can be 0, meaning there are no cracks. At any time other than the start of the first charge or at any time other than the first charge, the lithium flux around the positive electrode particles at that time can be determined based on the first crack variable at the previous time and the charging parameter information. The first crack variable at the previous time is the actual crack variable determined at the previous time.

[0057] For example, taking a solid-state battery under constant current charge and discharge during cyclic charging and discharging as an example, the external flux load corresponding to the preset lithium flux on the surface of the positive electrode particles is... It can be defined as .in, This indicates the limit value for lithium-ion concentration, which can be preset based on experience. volume This indicates the volume of the positive electrode particles. area This represents the surface area of ​​the positive electrode particles. This represents the reciprocal of the time (in hours) required for a complete charge-discharge cycle of an all-solid-state battery. This parameter can be determined based on charging parameter information. According to this formula, the external flux load applied around the positive electrode particles at the initial moment can be determined. Based on this load, the preset lithium flux at the initial moment can be determined. Then, based on this preset lithium flux, the lithium concentration inside the cathode particle at the initial moment can be determined. According to this lithium concentration and the coupling model of this application, the crack variable at the next moment can be determined. Then, once a crack is generated, the crack variable and charging parameter information will affect the lithium concentration C inside the cathode particle at the next moment. After the lithium concentration C changes, the next cycle simulation process is carried out based on the coupling model of this application until the simulation of the cyclic charge and discharge process is completed.

[0058] In a specific implementation, S103-1 can obtain the lithium flux around the positive electrode particles at any moment during the simulated charge and discharge process. The first crack variable inside the positive electrode particle at the previous moment d -crack Then, using the lithium-ion diffusion-induced strain model, based on the state of charge range and the charging rate at the current moment, the first crack variable was determined. d -crack Lithium flux below Lithium concentration inside the cathode particles C Specifically, the local lithium concentration change inside the positive electrode particle is caused by lithium ions generated at the negative electrode being conducted to the positive electrode through the electrolyte, and then entering the interior of the positive electrode particle, resulting in a change in the lithium ion concentration inside the positive electrode particle.

[0059] S103-2: Using the lithium concentration inside the cathode particle at the current moment, the reference lithium concentration, and the partial molar volume of lithium ions, determine the lithium strain inside the cathode particle caused by the change in lithium concentration.

[0060] In practice, the lithium strain induced by the gradient between the local lithium concentration and the reference lithium concentration inside the cathode particle can be determined using the following formula 1a: (1a) in, Indicates lithium strain. The value represents the partial molar volume of lithium ions, and C represents the lithium concentration. This represents the reference lithium concentration under stress-free conditions, which can be, for example, 0. I represents the unit tensor.

[0061] S103-3: Determine the first material strain inside the cathode particle at the current moment based on lithium strain, the lithium diffusion control equation based on lithium ion conservation, and the correlation between hydrostatic stress and stress tensor and strain tensor.

[0062] In practice, the lithium diffusion control equation under the passive term condition is derived based on lithium ion conservation. That is, the lithium diffusion control equation based on lithium ion conservation can be expressed using the following formulas 1b and 1c: (1b) (1c) in, This represents the derivative of lithium concentration C with respect to time t. The gradient is represented by D, and the lithium diffusion coefficient is represented by D. This represents the product of lithium flux and gradient. The gradient represents the lithium concentration, R represents the gas constant, and T represents the temperature. This indicates the net water stress, specifically... , It represents the stress tensor trace (the sum of principal stresses). This represents the Cauchy stress tensor.

[0063] Furthermore, the Cauchy stress tensor With strain tensor The related constitutive model, taking chemical strain into account, yields the following formula 1d: (1d) in, and This represents the Lamé constant, which can be derived from the Poisson's ratio in the material parameter coefficients. v Calculated in advance; This represents the total strain energy, which is also the first material strain in this application. Formula 1d reflects the relationship between hydrostatic stress and the stress tensor and strain tensor.

[0064] Furthermore, by combining the above formulas 1a to 1d, we can obtain the lithium-ion diffusion-induced strain model shown in formula 1f: (1f) In practice, the lithium strain of the cathode particles at the current moment is obtained. Then, based on the above 1f, the first material strain of the cathode particle at the current moment can be determined. .

[0065] S103-4: Based on the first material strain at the current moment, the second and third material strains at the current moment are determined using the Young's modulus inside the positive electrode particles, the Young's modulus at the contact interface, and the Young's modulus of the solid electrolyte.

[0066] In specific implementation, refer to Figure 2 It is known that the material strain inside the positive electrode particle will be conducted to the contact interface and then to the solid electrolyte. Therefore, after obtaining the first material strain inside the positive electrode particle at the current moment, the Young's modulus of the positive electrode particle can be used as a basis for calculation. particle Young's modulus at the contact interface interface Young's modulus of solid electrolyte electrolyte The material strain transmitted from the first material strain to the contact interface and the material strain transmitted to the solid electrolyte at the current moment are calculated. The material strain transmitted to the contact interface is taken as the second material strain of the contact interface at the current moment, and the material strain transmitted to the solid electrolyte is taken as the third material strain of the solid electrolyte at the current moment. Optionally, if the solid electrolyte is assumed to be a rigid electrolyte, the third material strain can be always 0.

[0067] S103-5: Using a fatigue damage model, based on the first material strain, second material strain, and third material strain at the current moment, determine the fatigue toughness variables of the inside of the positive electrode particle, the contact interface, and the solid electrolyte at the current moment.

[0068] Here, the magnitude of the fatigue toughness variable is used to indicate whether fatigue damage exists in the material.

[0069] In practice, the first material strain at the current moment can be substituted into the fatigue damage model to obtain the fatigue toughness variable inside the positive electrode particle at the current moment; the second material strain at the current moment can be substituted into the fatigue damage model to obtain the fatigue toughness variable of the contact interface at the current moment; and the third material strain at the current moment can be substituted into the fatigue damage model to obtain the fatigue toughness variable of the solid electrolyte at the current moment.

[0070] In one embodiment, S103-5 above can be implemented according to the following steps: S103-5-1: Using a fatigue damage model, determine the tensile strain at the current moment based on the target material strain and lithium strain at the current moment.

[0071] Here, since this application can determine the material strain of the three parts of the material separately (i.e., the material strain inside the cathode particle, the material strain at the contact interface, and the material strain of the solid electrolyte), the fatigue damage of the three parts of the material can also be determined separately when determining fatigue damage. Therefore, the target material strain can be selected from the material strains of the three parts of the material. Since the strain generated by lithium-ion diffusion only occurs inside the cathode particle, the lithium strain used when determining the fatigue damage of the three parts of the material is the lithium strain inside the cathode particle.

[0072] In practice, a volumetric-partial decomposition method can be used to prevent compressive damage. Under this method, the tensile strain of any target material at any time can be determined using the following formulas 2a, 2b, and 2c: (2a) (2b) (2c) in, This represents the tensile strain of the target material, and K represents the preset bulk modulus. Indicates to Perform a double dot product operation. The target material strain (i.e., the total strain energy mentioned above) represents the target material, where the target material is one of the following: the interior of the cathode particle, the contact interface, or the solid electrolyte.

[0073] In practice, for any target material, the target material strain at the current moment and the lithium strain at the current moment can be substituted into the above formulas 2a~2c to obtain the tensile strain of the target material at the current moment.

[0074] S103-5-2: Determine the phase field degradation coefficient at the current moment based on the target crack variable at the previous moment.

[0075] Here, the target crack variable is the crack variable of the target material. The phase field degradation coefficient is used to indicate the degree of phase field degradation of the target material.

[0076] In practical implementation, for any target material, the phase-field degradation coefficient of the target material can be determined according to the following formula 2d: (2d) in, This represents the phase field degradation coefficient. This represents the target crack variable at the previous moment. k A preset threshold is used to prevent when d -crack When the value is 1, a degradation problem occurs, for example, k =10 -5 .in, d -crack =1 can indicate complete breakage. d -crack =0 indicates that there is no break.

[0077] S103-5-3: Determine the elastic strain energy density at the current moment and the rate of change of the elastic strain energy density relative to the initial moment, based on the tensile strain and phase field degradation coefficient at the current moment.

[0078] In practical implementation, for any target material, its elastic strain energy density at the current moment is... It can be determined according to the following formula 2e: (2e) in, This represents the elastic strain energy density of the target material at the current moment, specifically the active portion of the elastic strain energy density.

[0079] Furthermore, the rate of change of elastic strain energy density can be determined based on the elastic strain energy density of the target material at the current moment and the elastic strain energy density at the initial moment of the cyclic charge-discharge process. .

[0080] S103-5-4: Determine the fatigue toughness variables at the current moment based on the elastic strain energy density, rate of change, and target critical energy release rate at the current moment.

[0081] Here, the target critical energy release rate can be the critical energy release rate of the target material.

[0082] In practice, for any target material, the fatigue toughness variable at the current moment can be calculated based on its elastic strain energy density and rate of change at the current moment, as well as the target critical energy release rate of the target material.

[0083] For example, when the target material strain is the first material strain, the target crack variable is the first crack variable, and the target critical energy release rate is... The critical energy release rate inside the positive electrode particle G c-particle The fatigue toughness variable is the fatigue toughness variable inside the positive electrode particle; when the target material strain is the strain of the second material, the target crack variable is the crack variable, and the target critical energy release rate is... Critical energy release rate at the contact interface G c-interface The fatigue toughness variable is the fatigue toughness variable of the contact interface; when the target material strain is the third material strain, the target crack variable is the third crack variable, and the target critical energy release rate is... Critical energy release rate of solid electrolyte G c-electrolyte The fatigue toughness variable is the fatigue toughness variable of the solid electrolyte.

[0084] In one embodiment, S103-5-4 described above can be implemented according to the following steps: S103-5-4-1: Determine the degree of ductile fatigue at the current moment based on the elastic strain energy density and rate of change at the current moment; the degree of ductile fatigue is used to indicate whether crack propagation exists.

[0085] In practice, for any target material, its toughness fatigue degree at any given time can be determined using the following formula 2f: (2f) in, The t represents the toughness and fatigue degree of the target material, and t represents time. It is the Heaviside function used to disable damage accumulation during unloading; and Represent the elastic strain energy density and rate of change of the target material at the current moment, respectively. , Represents the absolute value of the rate of change. It is pseudo-time used for integration. Indicates to The derivative of .

[0086] S103-5-4-2: Determine the fatigue toughness variable at the current moment based on the relationship between the degree of toughness fatigue and the fatigue crack threshold, as well as the target critical energy release rate; whereby the fatigue crack threshold is related to the target critical energy release rate and the phase field characteristic length.

[0087] Here, the fatigue crack threshold for different materials can be determined based on the material's critical energy release rate and phase field characteristic length. The phase field characteristic length can be a preset length.

[0088] Specifically, for any target material, its fatigue crack threshold can be determined according to the following formula 2g: (2g) Among them, This represents the fatigue crack threshold of the target material. This represents the target critical energy release rate of the target material. l This represents the preset phase field characteristic length. Fatigue damage only begins to accumulate when the material's ductile fatigue level exceeds a threshold.

[0089] Considering the toughness of the material in the presence of fatigue damage Depends on the accumulated toughness fatigue level and fatigue degradation function To achieve degradation, therefore, fatigue toughness variables It can be represented as Furthermore, it is necessary to define a fatigue degradation function. This function describes how the material's fracture resistance degrades during the damage caused by cyclic charging. Specifically, it's the fatigue degradation function. The following formula can be used to represent 2h: (2h) For example, for any target material, the toughness fatigue level of the target material at the current moment can be considered. And the fatigue crack threshold of the target material. Based on the magnitude relationship, the fatigue degradation function value of the target material at the current moment is determined according to the above formula 2h. Then, based on the fatigue degradation function value of the target material at the current moment... and the target critical energy release rate of the target material The product of these factors determines the fatigue toughness variable of the target material at the current moment. .

[0090] It is understandable that the model composed of the above formulas 2a to 2h can be the fatigue damage model described in the embodiments of this application.

[0091] S103-6: Using the phase-field fracture model, determine the first crack variable, the second crack variable, and the third crack variable at the current moment based on the fatigue toughness variable.

[0092] In practice, the fatigue toughness variable inside the cathode particle at the current moment can be substituted into the phase field fracture model to obtain the first crack variable inside the cathode particle at the current moment. d -crack Simultaneously, the fatigue toughness variable of the contact interface at the current moment can be substituted into the phase field fracture model to obtain the second crack variable of the contact interface at the current moment. d -crack Furthermore, by substituting the fatigue toughness variable of the solid electrolyte at the current moment into the phase field fracture model, the second crack variable of the solid electrolyte at the current moment is obtained. d -crack .

[0093] Furthermore, the first crack variable inside the positive electrode particle at the current moment is obtained. d -crack Subsequently, the lithium-ion diffusion-induced strain model can be used to determine the lithium concentration of the cathode particle at the next moment based on the crack variable, the lithium flux around the cathode particle, and the charging parameter information. This allows for continuous simulation of crack propagation in all-solid-state batteries by considering the continuous changes in the lithium concentration inside the cathode particle during cyclic charging and discharging.

[0094] In one embodiment, S103-6 described above can be implemented according to the following steps: S103-6-1: Using the phase-field fracture model, determine the target stress at the current moment based on the target material strain at the current moment.

[0095] Here, the target stress can be the Cauchy stress corresponding to the strain of the target material at the current moment. .

[0096] For example, for any target material, a phase-field fracture model can be used to determine the target material strain at the current moment. Determine the target stress at the current moment. .

[0097] S103-6-2: Taking the energy conservation of the stress vector field corresponding to the target stress and phase field degradation coefficient at the current moment as a condition, the target crack variable at the current moment is determined by using the stress balance equation, based on the target fatigue toughness variable, tensile strain and phase field characteristic length at the current moment.

[0098] Specifically, when the target material strain is the first material strain, the target fatigue toughness variable is the fatigue toughness variable inside the positive electrode particle; when the target material strain is the second material strain, the target fatigue toughness variable is the fatigue toughness variable at the contact interface; and when the target material strain is the third material strain, the target fatigue toughness variable is the fatigue toughness variable of the solid electrolyte.

[0099] In practical implementation, the phase-field fracture model based on the variational principle can capture the initiation and evolution of material cracks. This model can be implemented using a scalar field variable. d -crack To describe the crack-solid electrolyte interface, the phase-field method transforms the problem of crack nucleation and evolution into an optimization problem of finding the minimum energy. Therefore, the phase-field fracture model can directly handle complex fractures under multi-field coupling conditions (e.g., bifurcation, intersection, fusion, turning, etc.) without requiring additional crack path tracing methods. Within the phase-field fracture framework, the crack can be considered as a complete region (…). d -crack =0) and the completely fractured region ( d -crack The diffuse interface between the intact region and the fully fractured region (=1) exhibits a continuous transition. That is, the transition between the intact region and the fully fractured region is a continuous process, characterized by changes in crack variables. In this application, crack propagation is controlled by the Griffith criterion, which dissipates the strain energy corresponding to the material strain at the new fracture surface. The dissipated energy equals the product of the newly generated crack area and the material's critical energy release rate. The governing equations are coupled through a body-free stress balance equation and a phase-field evolution law based on Griffith energy balance, and a hybrid solution strategy is employed to address the crack variables of the material. d -crack The solution is as follows. Specifically, the phase-field fracture model of this application can be expressed using the following formulas 3a~3d: (3a) (3b) (3c) (3d) in, Represents the gradient. This represents the phase field degradation coefficient. Indicates the target stress. This represents the target critical energy release rate of the target material. l This indicates the preset phase field characteristic length. Represents the maximum tensile strain A local historical scene, in which, , This represents the boundary conditions, where n represents the normal vector and the direction of the external force vector. The outward normal vector representing the target stress. Indicates the displacement of the target material. express There is no special treatment at the boundary; that is, the displacement of the target material is the same as the displacement of the boundary. It is subject to constraints. The displacement vector. Equation 3a above can represent the energy conservation of the stress vector field corresponding to the target stress and phase field degradation coefficient at the current moment. Equation 3b above is the stress balance equation.

[0100] Furthermore, fatigue damage and phase-field fracture models can be combined to reflect the influence of fatigue damage on the crack propagation process, thereby more accurately simulating fatigue crack propagation. Thus, the above and Equation 3b can be transformed into the following Equation 3e: (3e) in, This represents the gradient of the fatigue toughness variable of the target material.

[0101] For example, regarding the interior of the positive electrode particle, the first material strain inside the positive electrode particle at any moment during the charging and discharging process can be considered. and fatigue toughness variables By substituting the equations 3a, 3e, 3c, and 3d corresponding to the phase-field fracture model and solving them, the first crack variable inside the cathode particle at the current moment can be obtained. d -crack Similarly, for the contact interface, the second material strain at any moment during the charging and discharging process can be considered. and fatigue toughness variables Substituting the equations 3a, 3e, 3c, and 3d corresponding to the phase-field fracture model into the equations and solving them, we can obtain the second crack variable at the contact interface at the current moment. d -crack For solid electrolytes, the third material strain at any moment during the charging and discharging process can be considered. and fatigue toughness variables Substituting the equations 3a, 3e, 3c, and 3d corresponding to the phase-field fracture model and solving them, we can obtain the third crack variable of the solid electrolyte at the current moment. d -crack .

[0102] Understandably, the above formulas 1a~1f, 2a~2h, and 3a~3e constitute the coupled mechanical-electrochemical model of the integrated phase-field method and variational fatigue damage proposed in this application. The coupled model includes processes such as lithium-ion diffusion, fracture, and fatigue damage. Simultaneously, to accurately capture crack initiation and propagation at the micron-scale, a representative volumetric unit model is adopted, using a single cathode particle to represent all cathode particles in the all-solid-state battery. Based on the above coupled model, not only can the evolution of the material's microstructure (i.e., the structural evolution within the cathode particle) be described, but effective macroscopic properties (i.e., fatigue damage, stress, strain, etc.) can also be extracted. A contact interface (such as one set in the all-solid-state battery) is used. Figure 2 The proposed contact interface model avoids the poor simulation accuracy caused by discontinuities in properties at cracks and interfaces. An auxiliary order parameter (i.e., the crack variable at the contact interface) is introduced to work in conjunction with the crack variable, jointly capturing material heterogeneity. The contact interface can be specifically used to describe the interface property transition, while the crack phase field within the particles controls the initiation and progression of fracture. In summary, based on the contact interface and coupling model proposed in this application, not only is the dynamic evolution of cracks addressed, but changes in interface properties can also be accurately tracked, thereby achieving a unified simulation of concurrent fracture and interface phenomena in complex heterogeneous systems (i.e., all-solid-state battery systems).

[0103] This application provides an initial coupled model integrating elasticity, interfaces (including contact interfaces and solid electrolyte interfaces), and crack fracture. Various gradient energy terms are used to regularize interface jumps. Based on this initial coupled model, a coupled model related to the material parameters of the all-solid-state battery is constructed. This model fully reveals that during cyclic charging and discharging, mechanical stress hinders lithium-ion diffusion and reduces the electrochemical reaction rate. Furthermore, lithium-ion diffusion and electrochemical reactions increase the stress in the internal material, further accelerating crack propagation. The phase-field fracture model, by describing crack evolution, tightly links mechanical and electrochemical processes, achieving full coupling between them. For example, in analyzing crack evolution using the above coupled model, the diffusion coefficient can change hydrostatic stress, which further alters material stress, causing material strain and thus affecting the electrochemical process of lithium-ion diffusion.

[0104] In one embodiment, in traditional finite element simulation methods, lithium diffusion during charge-discharge cycles is considered only within the cathode particles, neglecting the formation of the solid electrolyte interface, leading to reduced simulation accuracy. To improve simulation accuracy, this application proposes an artificial defect introduction method. Specifically, a notch can be set at a predetermined location on the cathode particle, containing the starting point of the crack path. The predetermined location can be set empirically, for example, at the edge of the cathode particle. The size and shape of the notch can also be set empirically.

[0105] By setting a notch at a preset position in the cathode particle, cracks inside the cathode particle can be formed, evolved, and expanded from the notch (that is, the crack starts from the notch and continues to expand into the cathode particle), thus making the simulated crack path more consistent with the real crack formation process of all-solid-state batteries.

[0106] like Figure 3 The diagram shown is a schematic representation of a notch provided in an embodiment of this application. Figure 3 In this model, the notch is located at the edge of the positive electrode particle and faces the contact interface. Furthermore, in simulating crack formation using the aforementioned coupling model, the crack can propagate from the notch. For example, in... Figure 2 The image shows a crack that expands from the notch.

[0107] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0108] Based on the same inventive concept, this disclosure also provides a crack propagation testing device for all-solid-state batteries corresponding to the crack propagation testing method for all-solid-state batteries. Since the principle of the device in this disclosure for solving the problem is similar to the crack propagation testing method for all-solid-state batteries described above, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0109] like Figure 4 The diagram shown is a schematic of a crack propagation testing device for an all-solid-state battery provided in an embodiment of this disclosure, comprising: The acquisition module 401 is used to acquire charging parameter information and material parameter information of the all-solid-state battery; Module 402 is used to construct a coupled model of the electrochemical and mechanical behavior inside the all-solid-state battery based on the phase-field method and the material parameter information. The coupled model includes at least a mutually coupled lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model. The lithium-ion diffusion-induced strain model is used to determine the material strain caused by lithium-ion diffusion inside the all-solid-state battery under the electrochemical and mechanical behaviors. The fatigue damage model is used to determine the material toughness under the material strain. The phase-field fracture model is used to determine the material crack variables under the material strain and the material toughness. The first determining module 403 is used to simulate the charging and discharging process of the all-solid-state battery according to the charging parameter information, and use the coupling model to determine the first material strain and first crack variable inside the positive electrode particles of the all-solid-state battery, the second material strain and second crack variable at the contact interface between the positive electrode particles and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte at each moment in the charging and discharging process. The second determining module 404 is used to determine the crack path and damage distribution of the all-solid-state battery during the charging and discharging process based on the first crack variable, the second crack variable, the third crack variable, and the damage threshold at each time moment, and to determine the stress evolution result of the all-solid-state battery during the charging and discharging process based on the first material strain, the second material strain, and the third material strain.

[0110] In one possible implementation, the device further includes an analysis module 405, configured to: Based on the crack path, damage distribution, and stress evolution results of the all-solid-state battery under different charge-discharge cycles, the correlation between the crack evolution trend, damage distribution trend, and stress evolution trend of the all-solid-state battery and the number of charge-discharge cycles is determined. Based on the aforementioned correlation, the battery capacity decay trend and lifespan information of the all-solid-state battery under the charging parameter information and the material parameter information are determined.

[0111] In one possible implementation, the analysis module 405 is further configured to: Based on the battery capacity decay trend and lifespan information of the all-solid-state battery under different charging parameter information and different material parameter information, the charging parameter optimization and material parameter optimization are performed on the all-solid-state battery.

[0112] In one possible implementation, the first determining module 403, when using the coupling model to determine the first material strain and first crack variable inside the positive electrode particles of the all-solid-state battery, the second material strain and second crack variable at the contact interface between the positive electrode particles and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte at each moment during the charging and discharging process, is used to: For any moment in the charging and discharging process, the lithium concentration of the positive electrode particle at the current moment is determined using the lithium-ion diffusion-induced strain model, based on the lithium flux around the positive electrode particle at the current moment, the first crack variable at the previous moment, and the charging parameter information. Using the lithium concentration inside the positive electrode particle at the current moment, the reference lithium concentration, and the partial molar volume of lithium ions, the lithium strain inside the positive electrode particle caused by the change in lithium concentration is determined. Based on the lithium strain, the lithium diffusion control equation based on lithium ion conservation, and the correlation between hydrostatic stress and stress tensor and strain tensor, the first material strain inside the cathode particle at the current moment is determined. Based on the first material strain at the current moment, the second and third material strains at the current moment are determined using the Young's modulus inside the positive electrode particle, the Young's modulus at the contact interface, and the Young's modulus of the solid electrolyte. Using the fatigue damage model, the fatigue toughness variables of the cathode particle interior, the contact interface, and the solid electrolyte at the current moment are determined based on the first material strain, the second material strain, and the third material strain at the current moment, respectively. Using the phase-field fracture model, and based on the fatigue toughness variables, the first crack variable, the second crack variable, and the third crack variable at the current moment are determined.

[0113] In one possible implementation, if the current time is the initial time, the lithium flux around the positive electrode particle at the current time is a preset lithium flux; the first crack variable at the previous time is a preset value.

[0114] In one possible implementation, the first determining module 403, when using the fatigue damage model to determine the fatigue toughness variables of the cathode particle interior, the contact interface, and the solid electrolyte at the current moment based on the first material strain, the second material strain, and the third material strain at the current moment, respectively, is used to: Using the fatigue damage model, the tensile strain at the current moment is determined based on the target material strain and lithium strain at the current moment; Determine the phase field degradation coefficient at the current moment based on the target crack variable at the previous moment; Based on the tensile strain and phase field degradation coefficient at the current moment, determine the elastic strain energy density at the current moment and the rate of change of the elastic strain energy density relative to the initial moment. The fatigue toughness variable at the current moment is determined based on the elastic strain energy density, the rate of change, and the target critical energy release rate at the current moment. Specifically, when the target material strain is a first material strain, the target crack variable is the first crack variable, the target critical energy release rate is the critical energy release rate inside the positive electrode particle, and the fatigue toughness variable is the fatigue toughness variable inside the positive electrode particle; when the target material strain is a second material strain, the target crack variable is the second crack variable, the target critical energy release rate is the critical energy release rate of the contact interface, and the fatigue toughness variable is the fatigue toughness variable of the contact interface; when the target material strain is a third material strain, the target crack variable is the third crack variable, the target critical energy release rate is the critical energy release rate of the solid electrolyte, and the fatigue toughness variable is the fatigue toughness variable of the solid electrolyte.

[0115] In one possible implementation, the first determining module 403, when determining the fatigue toughness variable at the current moment based on the elastic strain energy density, the rate of change, and the target critical energy release rate, is configured to: The degree of ductile fatigue at the current moment is determined based on the elastic strain energy density and the rate of change at the current moment; the degree of ductile fatigue is used to indicate whether crack propagation exists. Based on the relationship between the degree of toughness fatigue and the fatigue crack threshold, as well as the target critical energy release rate, the fatigue toughness variable at the current moment is determined; wherein, the fatigue crack threshold is related to the target critical energy release rate and the phase field characteristic length.

[0116] In one possible implementation, the first determining module 403, when determining the first crack variable, the second crack variable, and the third crack variable at the current moment using the phase-field fracture model and based on the fatigue toughness variable, is used to: Using the phase-field fracture model, the target stress at the current moment is determined based on the target material strain at the current moment; Given the energy conservation of the stress vector field corresponding to the target stress and phase field degradation coefficient at the current moment, the target crack variable at the current moment is determined using the stress balance equation based on the target fatigue toughness variable, tensile strain, and phase field characteristic length at the current moment. Specifically, when the target material strain is a first material strain, the target fatigue toughness variable is the fatigue toughness variable inside the positive electrode particle; when the target material strain is a second material strain, the target fatigue toughness variable is the fatigue toughness variable of the contact interface; and when the target material strain is a third material strain, the target fatigue toughness variable is the fatigue toughness variable of the solid electrolyte.

[0117] In one possible implementation, a notch is provided at a predetermined position of the positive electrode particle, and the notch contains the starting point of the crack path.

[0118] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.

[0119] Based on the same technical concept, embodiments of this application also provide a computer device. (Refer to...) Figure 5 The diagram shown is a structural schematic of a computer device provided in an embodiment of this application, comprising: The system includes a processor 501, a memory 502, and a bus 503. The memory 502 stores machine-readable instructions executable by the processor 501. The processor 501 executes these machine-readable instructions, performing the following steps: S101: Obtaining charging parameter information and material parameter information of the all-solid-state battery; S102: Constructing a coupled model of the electrochemical and mechanical behavior of the all-solid-state battery based on the phase-field method and material parameter information; the coupled model includes at least a mutually coupled lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model; the lithium-ion diffusion-induced strain model is used to determine the material strain caused by lithium-ion diffusion within the all-solid-state battery under electrochemical and mechanical behavior; the fatigue damage model is used to determine the material toughness under material strain; the phase-field... The fracture model is used to determine the material crack variables under material strain and material toughness; S103: Simulate the charging and discharging process of the all-solid-state battery according to the charging parameter information, and use the coupled model to determine the first material strain and first crack variable inside the positive electrode particle of the all-solid-state battery at each moment during the charging and discharging process, the second material strain and second crack variable at the contact interface between the positive electrode particle and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte; and S104: Determine the crack path and damage distribution of the all-solid-state battery during the charging and discharging process based on the first crack variable, second crack variable, third crack variable and damage threshold at each moment, and determine the stress evolution result of the all-solid-state battery during the charging and discharging process based on the first material strain, second material strain and third material strain.

[0120] The aforementioned memory 502 includes a main memory 5021 and an external memory 5022. The main memory 5021, also known as internal memory, is used to temporarily store the computational data in the processor 501, as well as the data exchanged with external memory such as a hard disk 5022. The processor 501 exchanges data with the external memory 5022 through the main memory 5021. When the computer device is running, the processor 501 and the memory 502 communicate through the bus 503, so that the processor 501 executes the execution instructions mentioned in the above method embodiments.

[0121] This disclosure also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs the steps of the crack propagation test method for all-solid-state batteries described in the above-described method embodiments. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0122] This disclosure also provides a computer program product carrying program code. The program code includes instructions that can be used to execute the steps of the crack propagation test method for all-solid-state batteries described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0123] The computer program product can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0124] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here. In the several embodiments provided in this disclosure, it should be understood that the disclosed device and method can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined, or some features may be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0125] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0126] In addition, the functional units in the various embodiments of this disclosure 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.

[0127] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. 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.

[0128] If the technical solution of this application involves personal information, the product using this technical solution has clearly informed the user of the personal information processing rules and obtained the user's voluntary consent before processing the personal information. If the technical solution of this application involves sensitive personal information, the product using this technical solution has obtained the user's separate consent before processing the sensitive personal information, and also meets the requirement of "express consent". For example, at personal information collection devices such as cameras, clear and prominent signs are set up to inform users that they have entered the scope of personal information collection and that personal information will be collected. If an individual voluntarily enters the collection scope, it is deemed that they have agreed to the collection of their personal information; or on the personal information processing device, with clear signs / information informing users of the personal information processing rules, authorization is obtained from the user through pop-up information or by asking the user to upload their personal information; wherein, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the types of personal information processed.

[0129] Finally, it should be noted that the above-described embodiments are merely specific implementations of this disclosure, used to illustrate the technical solutions of this disclosure, and not to limit it. The protection scope of this disclosure is not limited thereto. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this disclosure; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be covered within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the protection scope of the claims.

Claims

1. A method for testing crack propagation in all-solid-state batteries, characterized in that, include: Obtain charging and material parameter information for all-solid-state batteries; Based on the phase-field method and the material parameter information, a coupled model for the electrochemical and mechanical behavior inside the all-solid-state battery is constructed. The coupled model includes at least a mutually coupled lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model. The lithium-ion diffusion-induced strain model is used to determine the material strain caused by lithium-ion diffusion inside the all-solid-state battery under the electrochemical and mechanical behaviors. The fatigue damage model is used to determine the material toughness under the material strain. The phase-field fracture model is used to determine the material crack variables under the material strain and the material toughness. The charging and discharging process of the all-solid-state battery is simulated according to the charging parameter information, and the coupling model is used to determine the first material strain and first crack variable inside the positive electrode particles of the all-solid-state battery, the second material strain and second crack variable at the contact interface between the positive electrode particles and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte at each moment in the charging and discharging process. Based on the first crack variable, the second crack variable, the third crack variable, and the damage threshold at each moment, the crack path and damage distribution of the all-solid-state battery during the charging and discharging process are determined, and based on the first material strain, the second material strain, and the third material strain, the stress evolution result of the all-solid-state battery during the charging and discharging process is determined.

2. The method according to claim 1, characterized in that, The method further includes: Based on the crack path, damage distribution, and stress evolution results of the all-solid-state battery under different charge-discharge cycles, the correlation between the crack evolution trend, damage distribution trend, and stress evolution trend of the all-solid-state battery and the number of charge-discharge cycles is determined. Based on the aforementioned correlation, the battery capacity decay trend and lifespan information of the all-solid-state battery under the charging parameter information and the material parameter information are determined.

3. The method according to claim 2, characterized in that, The method further includes: Based on the battery capacity decay trend and lifespan information of the all-solid-state battery under different charging parameter information and different material parameter information, the charging parameter optimization and material parameter optimization are performed on the all-solid-state battery.

4. The method according to claim 1, characterized in that, The method of using the coupling model to determine the first material strain and first crack variable inside the positive electrode particles of the all-solid-state battery, the second material strain and second crack variable at the contact interface between the positive electrode particles and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte at each moment during the charging and discharging process includes: For any moment in the charging and discharging process, the lithium concentration of the positive electrode particle at the current moment is determined using the lithium-ion diffusion-induced strain model, based on the lithium flux around the positive electrode particle at the current moment, the first crack variable at the previous moment, and the charging parameter information. Using the lithium concentration inside the positive electrode particle at the current moment, the reference lithium concentration, and the partial molar volume of lithium ions, the lithium strain inside the positive electrode particle caused by the change in lithium concentration is determined. Based on the lithium strain, the lithium diffusion control equation based on lithium ion conservation, and the correlation between hydrostatic stress and stress tensor and strain tensor, the first material strain inside the cathode particle at the current moment is determined. Based on the first material strain at the current moment, the second and third material strains at the current moment are determined using the Young's modulus inside the positive electrode particle, the Young's modulus at the contact interface, and the Young's modulus of the solid electrolyte. Using the fatigue damage model, the fatigue toughness variables of the cathode particle interior, the contact interface, and the solid electrolyte at the current moment are determined based on the first material strain, the second material strain, and the third material strain at the current moment, respectively. Using the phase-field fracture model, and based on the fatigue toughness variables, the first crack variable, the second crack variable, and the third crack variable at the current moment are determined.

5. The method according to claim 4, characterized in that, When the current time is the initial time, the lithium flux around the positive electrode particle at the current time is a preset lithium flux; the first crack variable at the previous time is a preset value.

6. The method according to claim 4, characterized in that, The fatigue toughness variables of the cathode particle interior, the contact interface, and the solid electrolyte at the current moment are determined using the fatigue damage model based on the first material strain, the second material strain, and the third material strain at the current moment, respectively, including: Using the fatigue damage model, the tensile strain at the current moment is determined based on the target material strain and lithium strain at the current moment; Determine the phase field degradation coefficient at the current moment based on the target crack variable at the previous moment; Based on the tensile strain and phase field degradation coefficient at the current moment, determine the elastic strain energy density at the current moment and the rate of change of the elastic strain energy density relative to the initial moment. The fatigue toughness variable at the current moment is determined based on the elastic strain energy density, the rate of change, and the target critical energy release rate at the current moment. Specifically, when the target material strain is a first material strain, the target crack variable is the first crack variable, the target critical energy release rate is the critical energy release rate inside the positive electrode particle, and the fatigue toughness variable is the fatigue toughness variable inside the positive electrode particle; when the target material strain is a second material strain, the target crack variable is the second crack variable, the target critical energy release rate is the critical energy release rate of the contact interface, and the fatigue toughness variable is the fatigue toughness variable of the contact interface; when the target material strain is a third material strain, the target crack variable is the third crack variable, the target critical energy release rate is the critical energy release rate of the solid electrolyte, and the fatigue toughness variable is the fatigue toughness variable of the solid electrolyte.

7. The method according to claim 6, characterized in that, The determination of the fatigue toughness variable at the current moment based on the elastic strain energy density, the rate of change, and the target critical energy release rate includes: The degree of ductile fatigue at the current moment is determined based on the elastic strain energy density and the rate of change at the current moment; the degree of ductile fatigue is used to indicate whether crack propagation exists. Based on the relationship between the degree of toughness fatigue and the fatigue crack threshold, as well as the target critical energy release rate, the fatigue toughness variable at the current moment is determined; wherein, the fatigue crack threshold is related to the target critical energy release rate and the phase field characteristic length.

8. The method according to claim 6, characterized in that, The step of using the phase-field fracture model to determine the first crack variable, the second crack variable, and the third crack variable at the current moment based on the fatigue toughness variable includes: Using the phase-field fracture model, the target stress at the current moment is determined based on the target material strain at the current moment; Given the energy conservation of the stress vector field corresponding to the target stress and phase field degradation coefficient at the current moment, the target crack variable at the current moment is determined using the stress balance equation based on the target fatigue toughness variable, tensile strain, and phase field characteristic length at the current moment. Specifically, when the target material strain is a first material strain, the target fatigue toughness variable is the fatigue toughness variable inside the positive electrode particle; when the target material strain is a second material strain, the target fatigue toughness variable is the fatigue toughness variable of the contact interface; and when the target material strain is a third material strain, the target fatigue toughness variable is the fatigue toughness variable of the solid electrolyte.

9. The method according to claim 1, characterized in that, The positive electrode particle has a notch at a preset position, and the notch contains the starting point of the crack path.

10. A crack propagation testing device for all-solid-state batteries, characterized in that, include: The acquisition module is used to acquire charging parameter information and material parameter information of the all-solid-state battery; A construction module is used to construct a coupled model of the electrochemical and mechanical behavior inside the all-solid-state battery based on the phase-field method and the material parameter information. The coupled model includes at least a mutually coupled lithium-ion diffusion-induced strain model, a phase-field fracture model, and a fatigue damage model. The lithium-ion diffusion-induced strain model is used to determine the material strain caused by lithium-ion diffusion inside the all-solid-state battery under the electrochemical and mechanical behaviors. The fatigue damage model is used to determine the material toughness under the material strain. The phase-field fracture model is used to determine the material crack variables under the material strain and the material toughness. The first determining module is used to simulate the charging and discharging process of the all-solid-state battery according to the charging parameter information, and use the coupling model to determine the first material strain and first crack variable inside the positive electrode particles of the all-solid-state battery, the second material strain and second crack variable at the contact interface between the positive electrode particles and the solid electrolyte, and the third material strain and third crack variable of the solid electrolyte at each moment in the charging and discharging process. The second determining module is used to determine the crack path and damage distribution of the all-solid-state battery during the charging and discharging process based on the first crack variable, the second crack variable, the third crack variable, and the damage threshold at each time moment, and to determine the stress evolution result of the all-solid-state battery during the charging and discharging process based on the first material strain, the second material strain, and the third material strain.

11. A computer device, characterized in that, include: The processor and the memory, wherein the memory stores machine-readable instructions executable by the processor, the processor is used to execute the machine-readable instructions stored in the memory, and when the machine-readable instructions are executed by the processor, the processor performs the steps of the crack propagation test method for all-solid-state batteries as described in any one of claims 1 to 9.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is run by a computer device, the computer device performs the steps of the crack propagation test method for all-solid-state batteries as described in any one of claims 1 to 9.

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