A method and system for testing energy storage battery material degradation and stress distribution

Abstract

The application discloses a kind of energy storage battery material decay and stress distribution test method and system, belong to battery technical field, including the two-dimensional plane geometric model comprising active particles, solid electrolyte, lithium metal negative electrode is constructed;Coupling solution lithium ion diffusion equation, linear elasticity mechanics equation and cohesive zone damage evolution equation, calculate diffusion-induced stress, and lithium ion flux attenuation is reversely coupled to concentration field;Variable parameter is set;Constant current charge-discharge cycle simulation is executed, and first principal stress distribution, debonding gap, damage variable and capacity attenuation curve are output;By comparing the interface debonding start time under different variable parameter combinations, intergranular crack area and residual stress after cycle, the influence degree of each variable parameter on electrochemical-mechanical synergistic failure is evaluated;The application uses the above method and system, can realize the synergistic test of material decay characteristics and stress-strain distribution, and it has important significance to optimize electrode structure design and prolong battery life.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and in particular to a method and system for testing the decay and stress distribution of energy storage battery materials. Background Technology

[0002] During charge-discharge cycles, energy storage batteries (such as lithium-ion batteries and all-solid-state batteries) undergo irreversible structural decay in their electrode materials due to the repeated insertion and extraction of lithium ions, resulting in complex internal stress distributions. Material decay primarily manifests as the formation and thickening of the solid electrolyte interphase (SEI) film, intergranular cracks in active particles, phase transitions in the positive electrode material, and lithium plating in the negative electrode. Stress distribution, on the other hand, originates from the volume expansion / contraction of active particles and their mechanical constraints with the surrounding medium. These two factors are coupled: material decay alters local mechanical properties, while stress concentration accelerates the decay process. Therefore, accurately testing the material decay characteristics and stress distribution throughout the entire lifespan of an energy storage battery is crucial for understanding battery failure mechanisms, optimizing electrode structures, and assessing battery health.

[0003] Currently, testing techniques for the decay and stress distribution of energy storage battery materials include online or implantable sensing methods, such as implanted fiber Bragg grating (FBG) sensors, pressure sensors, or strain gauges. These sensors can be placed inside or on the surface of the battery to monitor temperature, pressure, and strain signals in real time. However, existing implantable sensing technologies generally face the following challenges: poor compatibility between the sensor and the battery system (e.g., difficulty in simultaneously achieving low barrier properties, high stability, and long lifespan); and the significant impact of sensor implantation on the battery's electrochemical performance. A single sensing method cannot simultaneously acquire coupled information on material decay (chemical composition, crystal structure) and stress-strain; furthermore, the quantitative relationship between the optical signal output by the fiber optic sensor and the microscopic decay characteristics of the material is still unclear, and verification methods are lacking.

[0004] In summary, there is an urgent need to develop a testing method for the decay and stress distribution of energy storage battery materials. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for testing the decay and stress distribution of energy storage battery materials, which can achieve coordinated testing of material decay characteristics and stress-strain distribution throughout the entire battery life cycle, providing technical support for battery life prediction and safety assessment.

[0006] To achieve the above objectives, the present invention provides a method for testing the decay and stress distribution of energy storage battery materials, comprising the following steps: S1. Construct a two-dimensional planar geometric model containing active particles, solid electrolyte, and lithium metal anode, and embed cohesive units at the solid-solid interface between active particles and solid electrolyte and at the grain boundaries between primary particles. S2. The lithium-ion diffusion equation, linear elasticity equation and cohesive damage evolution equation are coupled and solved. The diffusion-induced stress is calculated by anisotropic lattice strain, and the lithium-ion flux attenuation caused by interface debonding is reverse-coupled to the concentration field by the gap-transfer function. S3. Set the external working pressure, internal porosity, preset pore crack length, Young's modulus ratio of active particles to solid electrolyte, and Poisson's ratio as variable parameters. S4. Perform constant current charge-discharge cycle simulation and output the first principal stress distribution, debonding gap, damage variables and capacity decay curve; S5. By comparing the interface debonding initiation time, intergranular crack area, and residual stress after cycling under different combinations of variable parameters, the influence of each variable parameter on electrochemical-mechanical synergistic failure is evaluated.

[0007] Preferably, the two-dimensional planar geometric model in step S1 is constructed based on boundary recognition of real focused ion beam scanning electron microscope images, specifically as follows: Serial slice imaging of active particles was performed using a real focused ion beam scanning electron microscope to obtain the boundary contours of primary particles. Morphological parameters of primary particles are extracted using image recognition technology; The Voronoi algorithm was used to generate a polycrystalline aggregate particle model containing several primary particles, and each primary particle was assigned a random crystal orientation angle to simulate anisotropic lithium diffusion and lattice strain behavior.

[0008] Preferably, in step S1, the gap between the active particles and the solid electrolyte is set to an initial zero contact interface, and the cohesive unit adopts the triangular traction-separation softening law, whose constitutive parameters include: initial stiffness. Cohesive strength Fixed fracture energy release rate The damage evolution process of the cohesive unit is as follows: In the elastic stage, stiffness increases linearly until it reaches the cohesive strength threshold. In the initial stage of damage, the maximum stress is used for accurate determination. During the damage propagation stage, the stiffness linearly degenerates to zero, and the cohesive elements completely fail.

[0009] Preferably, the lithium-ion diffusion equation in step S2 adopts a modified Fick's second law, taking into account the contribution of the stress gradient to the chemical potential: ; in, Lithium ion concentration, For time, The diffusion coefficient of lithium ions is given by different values ​​along the a-axis and c-axis due to the anisotropy of the active particle crystal. The local diffusion coefficient of each primary particle is obtained by rotating the crystal orientation angle. This represents the partial molar volume of lithium ions. Let be the ideal gas constant. Absolute temperature It is the hydrostatic pressure; The equation of linear elasticity is expressed as: ; in, For stress tensor, For the isotropic elastic stiffness tensor, For total strain, This is the inelastic strain induced by lithium insertion / extraction; Damage variables in the cohesive region damage evolution equation Defined as: ; in, This is the current separation displacement. The initial displacement of the damage. This is the displacement of complete failure.

[0010] Preferably, in step S2, the anisotropic lattice strain is input through X-ray diffraction experimental data. The lattice strain along the a-axis and c-axis of the primary particle are different. The volumetric strain caused by lithium insertion / extraction has a nonlinear relationship with the normalized lithium concentration. The lattice constant of the active particle material under different charge states is measured by X-ray diffraction experiments. For each primary particle, based on its crystal orientation angle Transform the strain in the crystal coordinate system to the global coordinate system: ; in, This refers to the anisotropic inelastic strain caused by lithium insertion / extraction. Let be the rotation matrix components from the crystal coordinate system to the global coordinate system. This is the other component of the rotation matrix from the crystal coordinate system to the global coordinate system. The lattice strain tensor in the local coordinate system of the crystal is used; the diffusion-induced stress is then calculated using the linear elasticity equations and coupled with the concentration gradient. Define a gap-transfer function to feed back the hindering effect of interface debonding on lithium-ion transport to the concentration field, and the local lithium-ion flux. Revised to: ; in, For lithium-ion flux at a healthy interface. This is a localized debonding gap. For reference gap, This is the empirical attenuation coefficient.

[0011] Preferably, the value range of each variable parameter in step S3 is as follows: External working pressure range: 0 MPa to 200 MPa; internal porosity range: 0% to 15%; ratio of preset pore crack length to active particle radius range: 0 to 0.5; Young's modulus of active particles range: 90 GPa to 130 GPa; Young's modulus of solid electrolyte range: 20 GPa to 80 GPa; Poisson's ratio of active particles range: 0.2 to 0.4.

[0012] Preferably, in step S4, the constant current charge-discharge cycle simulation has a charge-discharge rate of 0.5C to 4C, a charging cut-off voltage of 4.25V, a discharging cut-off voltage of 3.6V, a constant simulation temperature of 293.15K, and the cycle time is set according to the normalization of the charge-discharge rate.

[0013] Preferably, in step S5, the degree of influence of each variable parameter on electrochemical-mechanical synergistic failure is evaluated, specifically as follows: A single-parameter scanning method was used, with other variable parameters fixed and the target variable parameter changed. The number of cycles at the start of interface debonding, the percentage of intergranular crack area, and the residual first principal stress after the cycle were recorded. Calculate the local sensitivity coefficient for variable parameters. The sensitivity coefficient is defined as: ; in, The output value is the reference parameter. As the baseline parameter value, This represents the change in the output value after the parameter is changed. For parameter changes; when When this happens, the parameter is considered a sensitive parameter; By comparing the absolute values ​​of the sensitivity coefficients of different parameters, the parameter with the larger absolute value has a greater impact on the cooperative failure.

[0014] Preferred options also include: A phase-field damage model and a cohesive zone model are used to simulate crack propagation. Elastic strain energy is used as the driving force for crack propagation. Phase-field variables are introduced to represent the continuous transition of the material from intact to completely cracked. The phase-field evolution equation is bidirectionally coupled with the stress field and concentration field to simulate the further propagation of cracks inside the particles after the cohesive zone unit completely fails.

[0015] The present invention also provides a testing system for the decay and stress distribution of energy storage battery materials, comprising: The model building module is used to construct a two-dimensional planar geometric model containing active particles, solid electrolyte, and lithium metal anode, and to embed cohesive units at the solid-solid interface between active particles and solid electrolyte and at the grain boundaries between primary particles. The coupled solution module is used to solve the lithium-ion diffusion equation, the linear elasticity equation, and the cohesive damage evolution equation. It calculates the diffusion-induced stress through anisotropic lattice strain, and the lithium flux attenuation caused by interface debonding is back-coupled to the concentration field through the gap-transfer function. The crack propagation module is used to simulate crack propagation by combining the phase field damage model and the cohesive zone model. It uses elastic strain energy as the driving force for crack propagation, introduces phase field variables to represent the continuous transition of the material from intact to completely cracked, and couples the phase field evolution equation with the stress field and concentration field in both directions to simulate the further propagation of cracks inside the particles after the cohesive unit completely fails. The parameter setting module is used to set the external working pressure, internal porosity, preset pore crack length, Young's modulus ratio of active particles to solid electrolyte, and Poisson's ratio as variable parameters. The cyclic simulation module is used to perform constant current charge-discharge cyclic simulation and output the first principal stress distribution, debonding gap, damage variables and capacity decay curve. The parameter evaluation module is used to assess the influence of each parameter on electrochemical-mechanical synergistic failure by comparing the interface debonding initiation time, intergranular crack area, and post-cycle residual stress under different parameter combinations.

[0016] Therefore, the present invention employs the above-mentioned method and system for testing the decay and stress distribution of energy storage battery materials, which has the following beneficial effects: (1) It realizes the synergistic simulation of interface debonding and intergranular cracks, overcomes the limitation of existing technologies that only focus on a single failure mode, and through the bidirectional coupling of the cohesive region model with the concentration field and stress field, it truly reproduces the positive feedback evolution process of “interface debonding → concentration polarization → intergranular cracks → accelerated failure”. (2) It can systematically study the dual effects of initial defects such as internal porosity and opening crack length on the mechanical response and electrochemical performance of composite cathodes, providing a quantitative basis for optimizing material preparation processes; (3) By using single-parameter scanning and local sensitivity coefficient calculation, the influence of Young's modulus matching degree and Poisson's ratio on interface integrity between active particles and solid electrolyte is quantitatively evaluated, providing design criteria for material selection; (4) Using a two-dimensional planar model instead of a three-dimensional fully coupled model can significantly reduce computational costs while ensuring the capture of spatial concentration gradient and stress distribution characteristics, and facilitate multi-parameter batch scanning optimization.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] Figure 1 This is a flowchart of a method for testing the decay and stress distribution of energy storage battery materials according to the present invention; Figure 2 This is an overall flowchart of a testing system for the decay and stress distribution of energy storage battery materials according to the present invention; Figure 3 This is a flowchart of Embodiment 1 of the present invention; Figure 4 This is an overall flowchart of Embodiment 1 of the present invention. Detailed Implementation

[0019] The following detailed description of embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0020] Please see Figure 1 A method for testing the decay and stress distribution of energy storage battery materials, comprising the following steps: S1. Construct a two-dimensional planar geometric model containing active particles, solid electrolyte, and lithium metal anode, and embed cohesive units at the solid-solid interface between active particles and solid electrolyte and at the grain boundaries between primary particles; the aim is to establish a geometric model for simulating the composite cathode of energy storage batteries (such as all-solid-state batteries).

[0021] The active particles can be NCM811 (LiNi) 0.8 Co 0.1 Mn 0.1 O2 is used as the positive electrode active material. The active particles are polycrystalline aggregates, formed by the aggregation of multiple irregularly shaped primary particles. Simplifying the actual three-dimensional structure into a two-dimensional planar model can reduce computational complexity and clearly visualize the interface evolution. Other materials can be selected as the positive electrode active material.

[0022] A sulfide electrolyte, Li4PS4Cl, can be selected as the solid electrolyte due to its high ionic conductivity and good machinability. Other types of electrolytes can also be used as solid electrolytes.

[0023] The lithium metal anode can be set as a pure lithium metal layer, forming an interface with the solid electrolyte layer.

[0024] The two-dimensional planar geometric model is constructed based on boundary identification of real focused ion beam scanning electron microscope images, specifically as follows: Serial slice imaging of NCM811 particles was performed using real focused ion beam scanning electron microscopy (FIB-SEM) to obtain the boundary contours of primary particles. Image recognition technology is used to extract the morphological parameters (such as area, perimeter, shape factor, etc.) of primary particles. The Voronoi algorithm was used to generate a polycrystalline aggregate particle model containing 15-30 primary particles, and each primary particle was given a random crystal orientation angle (0° to 360°) to simulate anisotropic lithium diffusion and lattice strain behavior.

[0025] The gap between the active particles and the solid electrolyte is set to an initial zero contact interface.

[0026] The embedding of cohesive units can embed zero-thickness cohesive units at every solid-solid interface (SSI) between the active particles and the solid electrolyte.

[0027] Within polycrystalline active particles, cohesive units with zero thickness can also be embedded at the grain boundaries between adjacent primary particles.

[0028] The cohesive unit adopts the triangular traction-separation softening principle, and its constitutive parameters include: initial stiffness. (Take 1×10) 6 Pa / μm), cohesive strength (Taking 25MPa), with a fixed fracture energy release rate (Taking 10 N / m), damage begins when the interface normal or tangential stress reaches the cohesive strength, and the stiffness linearly degrades until complete separation. The damage evolution process of the cohesive unit is as follows: In the elastic stage, stiffness increases linearly until it reaches the cohesive strength threshold. In the initial stage of damage, the maximum stress is used for accurate determination. During the damage propagation stage, the stiffness linearly degenerates to zero, and the cohesive elements completely fail.

[0029] Boundary conditions can be applied to the outer surface of secondary particles as mechanical boundary conditions to simulate the compaction state of electrode materials in the battery; the grain boundaries of the internal primary particles are set as mutually supporting conditions, allowing free displacement under normal constraints.

[0030] S2. Coupled solution of the lithium-ion diffusion equation, the linear elasticity equation, and the cohesive region damage evolution equation, specifically: The lithium-ion diffusion equation employs a modified Fick's second law, taking into account the contribution of the stress gradient to the chemical potential: ; in, Lithium ion concentration (mol / m 3The initial full-state lithium concentration was set at 38860 mol / m. 3 The maximum concentration was taken as 46990 mol / m 3 ; For time (s), Lithium-ion diffusion coefficient (m) 2 / s), due to the anisotropy of the active particle crystals, different values ​​are set along the a-axis and c-axis respectively: =5×10⁻¹⁴m 2 / s, =1×10⁻¹⁴m 2 / s (c-axis diffusion is slower), the local diffusion coefficient of each primary particle is obtained by rotating the crystal orientation angle. The partial molar volume of lithium ions can be taken as 3.497 × 10⁻⁶ m³. 3 / mol, The ideal gas constant is 8.314 J / (mol·K). The absolute temperature is constant at 293.15 K. The hydrostatic pressure (Pa) can be calculated from the stress field.

[0031] The equation of linear elasticity is expressed as: ; in, For stress tensor, For the isotropic elastic stiffness tensor, derived from the elastic modulus Compared to Poisson Confirmed, active particles Take 93 GPa, Take 0.3; solid electrolyte Take 58 GPa, Take 0.3; The total strain is obtained by differentiating the displacement field. This refers to the inelastic strain (anisotropic lattice strain) induced by lithium insertion / extraction. Damage variables in the cohesive region damage evolution equation Defined as: ; in, This is the current separation displacement. The damage initiation displacement (equal to cohesive strength / initial stiffness) is the initial displacement. The displacement of complete failure (equal to) Damage variables Monotonically increasing, when The time unit is intact. It completely fails at that time.

[0032] Anisotropic lattice strain was input using X-ray diffraction experimental data. The lattice strain along the a-axis and c-axis of the primary particles differed. The volumetric strain caused by lithium insertion / extraction exhibited a nonlinear relationship with the normalized lithium concentration. The lattice constant of NCM811 material under different states of charge (SOC) was measured using X-ray diffraction (XRD) experiments. Along the a-axis: the lattice constant decreases monotonically with decreasing lithium concentration, and the fitting relationship is: ; in, Current lithium-ion concentration Corresponding crystal axial lattice constant, The initial a-axis lattice constant is given under full lithium conditions (SOC = 100%, maximum lithium ion concentration). The linear fitting coefficients for the a-axis lattice constant as a function of lithium insertion / extraction are given. This represents the maximum saturated lithium-ion concentration inside the active particles. Along the c-axis: the lattice constant first increases and then decreases as the lithium concentration decreases, and a sudden contraction of about 5% occurs in the H2→H3 phase transition range (SOC about 70% to 100%), using piecewise linear interpolation input.

[0033] For each primary particle, based on its crystal orientation angle Transform the strain in the crystal coordinate system to the global coordinate system: ; in, The anisotropic inelastic lattice strain caused by lithium insertion / extraction in the global coordinate system. Crystal coordinate system Rotation matrix components of the global coordinate system This is another component of the same set of rotation matrices. The lattice strain tensor in the local coordinate system of the crystal; China only and Non-zero, respectively determined by the current lithium concentration. , The relative change from the initial value is calculated. Then, the diffusion-induced stress is calculated using the linear elasticity equations, coupled with the concentration gradient.

[0034] Define a gap-transfer function to feed back the hindering effect of interface debonding on lithium-ion transport to the concentration field, and the local lithium-ion flux. Revised to: ; in, For lithium-ion flux at a healthy interface. This represents the local debonding gap (the normal component of the current separation displacement). As a reference gap, we take 1 μm. The empirical attenuation coefficient is set to 5.

[0035] As the debonding gap increases, the lithium-ion flux decreases exponentially, thus simulating the blocking effect of interface separation on lithium transport.

[0036] Coupled solutions can be implemented using the "Solid Mechanics," "Dilute Mass Transport," and "Cohesive Region" interfaces of finite element software (such as COMSOL Multiphysics), combined with custom subroutines to achieve strong coupling of the above equations. A fully coupled solver (PARDISO or MUMPS) is used, with adaptive time step adjustment (initial step size 0.01 s, minimum step size 0.001 s) to ensure nonlinear convergence. Within each time step, the following steps are performed sequentially: update the concentration field → calculate anisotropic strain → update the stress field → calculate cohesive region damage → correct lithium flux → proceed to the next step.

[0037] S3. Set external working pressure, internal porosity, preset pore crack length, Young's modulus ratio of active particles to solid electrolyte, and Poisson's ratio as variable parameters; used to define the variables that can be parameterized in the model and study the influence of each factor on electrochemical-mechanical synergistic failure.

[0038] Material decay refers to the structural degradation, chemical changes, or mechanical deterioration of materials inside a battery during cycling. It can include interface separation, crack formation (such as crack area), debinding (such as debinding initiation time), intergranular cracks, damage variables, capacity decay, etc.

[0039] Stress distribution refers to the stress and strain fields inside a battery caused by lithium insertion / extraction, external constraints, etc. It can include diffusion-induced stress, anisotropic strain, first principal stress, residual stress, etc.

[0040] The specific variable parameters are as follows: (1) External working pressure can be defined as the uniform normal pressure applied to the outer surface of the composite cathode, simulating the stacking pressure during battery assembly or operation.

[0041] Value range: 0MPa~200MPa, typical values ​​may include 0, 10, 20, 50, 100, 200MPa.

[0042] Implementation method: Apply a normal distributed load to the outer boundary of the model, with the direction perpendicular to the boundary and pointing inward.

[0043] (2) Internal porosity is defined as the volume (area) fraction of pre-existing circular or elliptical pores inside the active particles, simulating internal defects generated during the preparation process.

[0044] Value range: 0% to 15%, typical values ​​are 0%, 3%, 5%, and 10%.

[0045] Implementation method: Within the primary particles generated by Voronoi, randomly generated circular pores are created. The pore diameter is 0.5~2μm relative to the primary particle size, and the pore locations avoid grain boundaries. Porosity is controlled by the ratio of the total pore area to the total particle area.

[0046] (3) The preset opening crack length can be defined as the ratio of the crack length that penetrates the solid-solid interface on the surface of the active particle to the particle radius. ).

[0047] Value range: 0 to 0.5, typical values: 0, 0.1, 0.3, 0.5.

[0048] Implementation method: During model construction, a straight crack is generated inward along the particle surface at a specified location. The crack tip is sharp, and the two sides of the crack are initially free boundaries.

[0049] (4) The ratio of the Young's modulus of the active particles to that of the solid electrolyte can be defined as the elastic modulus of the active particles. Elastic modulus of solid electrolyte The ratios can also be treated as independent parameters.

[0050] Value range: =90~130 GPa (typically 93, 113, 123 GPa). =20~80GPa (typically 28, 58, 78GPa).

[0051] Implementation method: Assign values ​​separately in the material property definition.

[0052] (5) Poisson's ratio can be defined as the Poisson's ratio of active particles. .

[0053] Value range: 0.2 to 0.4, typical values: 0.24, 0.30, 0.36.

[0054] Implementation method: Assign values ​​in the material properties.

[0055] All variable parameters can be set in batches via input files or a GUI interface, supporting single-parameter scans and multi-parameter full-factor combination scans.

[0056] S4. Perform constant current charge-discharge cycle simulation, outputting the first principal stress distribution, debonding gap, damage variables, and capacity decay curve. The charge-discharge rate in the constant current charge-discharge cycle simulation is 0.5C to 4C, the charging cut-off voltage is 4.25V, the discharging cut-off voltage is 3.6V, the simulation temperature is constant at 293.15K, and the cycle time is set according to the normalized rate. Output quantities include: First principal stress distribution: used to identify the areas of maximum tensile stress inside the particles and at the interfaces; Average debonding gap: the average distance of separation of all solid-solid interface cohesive units; Maximum debonding gap: The maximum distance between all solid-solid interface cohesive units; Average damage level: the average of damage variables across all cohesive units; Capacity decay curve: Cycle capacity retention rate calculated based on the integral of lithium flux decay.

[0057] In this embodiment, the relevant variable parameters and output content are as follows: (1) Charge and discharge regime: Charge / discharge rates: 0.5C, 1C, 2C, 3C, and 4C are selectable. Taking 1C as an example, the nominal cycle time is: =14400 seconds.

[0058] Charging method: constant current charging, cutoff voltage 4.25V (relative to Li / Li). + ).

[0059] Discharge method: constant current discharge, cutoff voltage 3.6V.

[0060] Number of cycles: can be set from 1 to 500.

[0061] Normalized time: Definition =0 indicates the start of charging. =0.5 indicates the end of charging / the beginning of discharging. =1 indicates the end of discharge.

[0062] (2) Output content: First principal stress distribution: maximum principal stress (tensile stress is positive), used to identify tensile stress concentration areas at interfaces and grain boundaries.

[0063] Output method: Output the first principal stress cloud map of the whole field at each time step (or every 100 seconds), as well as the line distribution map along each interface and grain boundary.

[0064] Debonding gap: The normal separation displacement of the cohesive unit at the solid-solid interface.

[0065] Output two metrics: Average debonding gap : The average value of the normal displacement of all cohesive elements; Maximum debonding gap : The maximum value of the normal displacement of all cohesive elements.

[0066] Output method: Record these two values ​​in each lap cycle and plot the curve that changes with the number of laps.

[0067] Damage variables: Damage variables of cohesive units (0-1), and the overall average degree of damage. .

[0068] Output method: At the end of each cycle, output the full damage cloud map and the curve of the average damage degree changing with the number of cycles.

[0069] Capacity decay curve: The ratio of the discharge capacity per cycle to the discharge capacity of the first cycle (capacity retention rate).

[0070] Calculation method: Discharge capacity is obtained by measuring the lithium flux during the integral discharge stage.

[0071] Output method: Plot the capacity retention rate as a function of the number of cycles.

[0072] (3) Simulation convergence judgment: When the maximum debonding gap exceeds 10 μm or the average damage level exceeds 0.8 in a certain calculation cycle, the battery is considered to have failed severely, and the simulation can be terminated early.

[0073] S5. By comparing the interface debonding initiation time, intergranular crack area, and residual stress after cycling under different combinations of variable parameters, the influence of each variable parameter on electrochemical-mechanical synergistic failure is evaluated. Specifically: A single-parameter scanning method was used, with other parameters fixed to baseline values ​​(such as working pressure of 10 MPa, porosity of 0%, and no open-pore cracks). =93GPa =58GPa =0.3), take 5-8 values ​​for the target parameter evenly within its range, and run a complete simulation for each; record the three failure indicators corresponding to each parameter value: Interface debonding start time: refers to the time from the start of the cycle to the damage variable of any solid-solid interface cohesive unit. The time (or number of loops) to first reach 0.5. The smaller this value, the easier it is for the interface to detach from the sticky interface.

[0074] Percentage of intergranular crack area: refers to the damage variable at all grain boundaries (including grain boundaries within active particles). The total length covered by the cohesive units (length in 2D models, area in 3D models) is normalized to the total grain boundary length. This value characterizes the severity of the crack.

[0075] Residual stress after cycle: refers to the stress at the end of discharge ( =1) The maximum or average value of the first principal stress inside the particle. The greater the residual stress, the more severe the irreversible damage. Calculate the local sensitivity coefficient for variable parameters. The sensitivity coefficient is defined as: ; in, The output value is the value under the reference parameter value. As the baseline parameter value, This represents the change in the output value after the parameter is changed. For parameter changes; when When this happens, the parameter is considered a sensitive parameter; By comparing the absolute values ​​of the sensitivity coefficients of different parameters, the larger the absolute value, the more significant the effect of the parameter on the cooperative failure.

[0076] Example of evaluation results: Operating pressure: At 10 MPa, interfacial debonding begins at the 15th ring; at 50 MPa, it is delayed to the 40th ring; and at 200 MPa, it is advanced to the 10th ring (due to grain boundary damage induced by high pressure). The optimal pressure window is 20–80 MPa.

[0077] Internal porosity: 3% porosity can delay the debonding initiation time by about 20%, but 10% porosity will increase the area of ​​intergranular cracks by 50% due to stress concentration.

[0078] Preset opening crack: When the ratio is 0.3, the debonding gap decreases by 40%, but the stress concentration at the crack tip leads to a 15% increase in the area of ​​intergranular cracks. When the value is 0.5, the disadvantages outweigh the advantages.

[0079] Young's modulus matching: and The smaller the difference, the later the interface debonding begins and the lower the residual stress. The effect is significant when the difference is <30GPa.

[0080] Poisson's ratio: Increasing from 0.3 to 0.36 increases the peak value of the first principal stress by about 25%, making it the most sensitive parameter affecting stress.

[0081] Based on the above evaluation results, the results can be presented in the form of sensitivity bar charts, parameter-failure index curves, etc., and the optimal parameter combination can be recommended based on the evaluation results.

[0082] like Figure 2 As shown, a testing system for the decay and stress distribution of energy storage battery materials includes: The model building module is used to construct a two-dimensional planar geometric model containing active particles, solid electrolyte, and lithium metal anode, and to embed cohesive units at the solid-solid interface between active particles and solid electrolyte and at the grain boundaries between primary particles. The coupled solution module is used to solve the lithium-ion diffusion equation, the linear elasticity equation, and the cohesive damage evolution equation. It calculates the diffusion-induced stress through anisotropic lattice strain, and the lithium flux attenuation caused by interface debonding is back-coupled to the concentration field through the gap-transfer function. The parameter setting module is used to set the external working pressure, internal porosity, preset pore crack length, Young's modulus ratio of active particles to solid electrolyte, and Poisson's ratio as variable parameters. The cyclic simulation module is used to perform constant current charge-discharge cyclic simulation and output the first principal stress distribution, debonding gap, damage variables and capacity decay curve. The parameter evaluation module is used to assess the influence of each parameter on electrochemical-mechanical synergistic failure by comparing the interface debonding initiation time, intergranular crack area, and post-cycle residual stress under different parameter combinations.

[0083] Example 1 like Figure 3 As shown, a method for testing the decay and stress distribution of energy storage battery materials further includes: A combined phase-field damage model and cohesive zone model are used to simulate crack propagation. Elastic strain energy is used as the driving force for crack propagation, and phase-field variables are introduced to represent the continuous transition of the material from intact to fully cracked. The phase-field evolution equation is bidirectionally coupled with the stress and concentration fields to simulate the further propagation of cracks within the grains after the complete failure of the cohesive units. This aims to address the limitation of the cohesive zone model, which can only simulate crack initiation and propagation along grain boundaries or interfaces (i.e., intergranular cracks), but cannot describe cracks transitioning from grain boundaries to the grain interior (i.e., transgranular cracks). Therefore, a phase-field damage model is introduced, using elastic strain energy as the direct driving force for crack propagation, to simulate the entire process from interfacial debonding to fracture within the grains.

[0084] Phase field variables are defined in the computational domain Introduce a continuous phase field variable. The value range is [0,1]: This indicates that the material is in good condition and undamaged. This indicates that the material has completely cracked and lost its load-bearing capacity; This indicates that the material is in a state of transitional damage, with partial degradation of stiffness; Phase field variables describe cracks in a diffuse manner, avoiding the complex calculations of explicitly tracing crack surfaces, and can naturally simulate crack initiation, bifurcation, merging, and reversal.

[0085] The phase-field evolution equations are driven by the minimization principle and employ Allen-Cahn or Ginzburg-Landau type equations: ; in, Phase mobility (m) 2 ·N -1 ·s -1 This controls the rate of crack propagation, and the value is generally in the range of 1×10. -6 ~1×10 -5 m 2 ·N -1 ·s -1 In this embodiment, 1×10 can be used. -6 m 2 ·N -1 ·s -1 , Let be the variational derivative of the energy functional with respect to the phase field variables. The total energy functional of the system (J / m 2 or J / m 3 ), including elastic strain energy, fracture surface energy, and chemical energy; defined as: ; Among them, elastic strain energy density Given by the linear elastic constitutive model: ; in, For total strain, This refers to the anisotropic inelastic strain caused by lithium insertion / extraction. For the elastic stiffness tensor, For the anisotropic lattice inelastic strain tensor caused by lithium insertion / extraction in the crystal's own coordinate system.

[0086] Stiffness degradation function The form used to represent material softening caused by cracks is as follows: ; in, It is a very small positive number (such as 1×10). -6 ), used to avoid numerical singularities caused by zero stiffness when fully degraded.

[0087] fracture surface energy density Using the AT2 model (second-order regularization): ; in, This represents the phase field length dimension (μm), which controls the width of the crack dispersion region. In this embodiment, it is taken as... =4.5×10 -3 μm; The fixed fracture energy release rate of the material (J / m) 2 (or N / m), for NCM cathode materials, take 10 N / m.

[0088] The complete form of the total energy functional is: ; Substituting the above equation into the phase-field evolution equation, we get: ; According to the above formula, elastic strain energy The larger the phase field variable, the faster it grows, and the easier it is for the crack to propagate; when Reaching the critical value (approximately equal to) When the crack begins to grow spontaneously, the crack starts to grow spontaneously.

[0089] Two-way coupling of phase field rain stress field and concentration field: (1) Feedback of the phase field to the stress field: The effective stress tensor after damage is: ; That is, the cracked area ( The stress was significantly attenuated, and the simulated material lost its load-bearing capacity.

[0090] (2) The effect of phase field on concentration field: when At that time, the local lithium-ion diffusion coefficient decreases proportionally: ; in, The original diffusion coefficient of lithium ions within the grains when the active particle crystals are free from cracks and damage is considered. Meanwhile, the lithium flux attenuation caused by interface debonding and the diffusion coefficient attenuation caused by the phase field are superimposed and jointly affect the concentration field.

[0091] (3) The driving force of the stress field and concentration field on the phase field: elastic strain energy It itself depends on the concentration gradient (through) The phase field evolution is indirectly controlled by the concentration field and the stress field, and thus the phase field is controlled by the concentration field and the stress field.

[0092] In this embodiment, the cohesive zone model (CZM) and the phase field model work together in a relay manner.

[0093] 1) Initial stage (intergranular cracks): At the solid-solid interface between active particles and the solid electrolyte, and at the grain boundaries between primary particles, cohesive units dominate damage evolution. When the interfacial normal or tangential stress exceeds the cohesive strength... At that time, the cohesive units begin to soften, and the damage variable... Increasing from 0 to 1 simulates the initiation and propagation of intergranular cracks.

[0094] 2) Transition phase (complete failure of cohesive units): When the damage variable of the cohesive unit When the condition reaches step 1 (i.e., complete separation), the element no longer bears weight. At this point, the location of the element is marked as the initial crack source, and its geometric information (location, orientation) is passed to the phase field model.

[0095] 3) Subsequent stage (transgranular cracking): After receiving the initial crack source, the phase-field model automatically drives the phase-field variables, using the region of concentrated high elastic strain energy at the crack tip as the starting point. The crack evolves into the grain interior, simulating the transgranular propagation process of cracks moving from grain boundaries to the grain interior.

[0096] 4) Key points of numerical implementation: In the finite element framework, cohesive elements and solid elements share nodes. When a cohesive element completely fails, the initial phase field value at the boundary of its adjacent solid element is set to... (Completely cracked), and an initial elastic strain energy disturbance is applied to the region.

[0097] The phase-field equations employ a solver similar to that used for the diffusion equations, with the time step synchronized with the mechanical step to ensure strong coupling convergence.

[0098] In this embodiment, the parameter settings and boundary conditions are as follows: Phase field length scale 4.5 × 10 can be taken. -3 μm, approximately 1 / 200 to 1 / 500 of the particle size, ensuring that the crack width is much smaller than the particle size.

[0099] Phase mobility You can take 1×10 -6 m 2 ·N -1 ·s -1 This ensures that the crack propagation rate is comparable to the actual physical process.

[0100] Initial conditions: throughout the entire computational domain =0.

[0101] Boundary conditions: Apply Neumann boundary strips in regions far from the crack. This ensures that the phase field gradient does not cause spurious energy flow.

[0102] Based on the above, the following additional output can be obtained: Phase field variables Spatial distribution cloud map, intuitively displaying crack path ( (area) The relationship between transgranular crack length and number of cycles; Phase-field driven crack propagation rate.

[0103] In each time step of step S2, the lithium-ion diffusion equation, the linear elasticity equation, the cohesive region damage evolution equation, and the aforementioned phase field evolution equation are solved simultaneously.

[0104] When the cohesive region damage variable At that time, the phase-field equation is not activated or only performs background calculations. The threshold was not reached. Keep it at 0); When the cohesive region damage variable Then, the phase-field equations are activated. It begins to grow from the crack tip into the interior of the particle.

[0105] Therefore, the above content is an important part of the "coupled solution" in step S2, and its results are directly used for the output of step S4 (such as the distribution of phase field variables) and the parameter evaluation of step S5 (such as the effect of transgranular crack area on cycle life).

[0106] like Figure 4 As shown in this embodiment, a test system for the decay and stress distribution of energy storage battery materials includes: The model building module is used to construct a two-dimensional planar geometric model containing active particles, solid electrolyte, and lithium metal anode, and to embed cohesive units at the solid-solid interface between active particles and solid electrolyte and at the grain boundaries between primary particles. The coupled solution module is used to solve the lithium-ion diffusion equation, the linear elasticity equation, and the cohesive damage evolution equation. It calculates the diffusion-induced stress through anisotropic lattice strain, and the lithium flux attenuation caused by interface debonding is back-coupled to the concentration field through the gap-transfer function. The crack propagation module is used to simulate crack propagation by combining the phase field damage model and the cohesive zone model. It uses elastic strain energy as the driving force for crack propagation, introduces phase field variables to represent the continuous transition of the material from intact to completely cracked, and couples the phase field evolution equation with the stress field and concentration field in both directions to simulate the further propagation of cracks inside the particles after the cohesive unit completely fails. The parameter setting module is used to set the external working pressure, internal porosity, preset pore crack length, Young's modulus ratio of active particles to solid electrolyte, and Poisson's ratio as variable parameters. The cyclic simulation module is used to perform constant current charge-discharge cyclic simulation and output the first principal stress distribution, debonding gap, damage variables and capacity decay curve. The parameter evaluation module is used to assess the influence of each parameter on electrochemical-mechanical synergistic failure by comparing the interface debonding initiation time, intergranular crack area, and post-cycle residual stress under different parameter combinations.

[0107] Therefore, this invention employs the aforementioned method and system for testing the decay and stress distribution of energy storage battery materials, enabling the synergistic testing of energy storage battery material decay (interface debonding, intergranular cracks, capacity decay, etc.) and stress distribution (diffusion-induced stress, residual stress, etc.). It has the advantages of being non-destructive, low-cost, and repeatable, and can reveal the electrochemical-mechanical coupling failure mechanism and quantify the impact of key parameters. This is of great significance for battery material screening, structural optimization, life prediction, and extending battery life.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for testing the decay and stress distribution of energy storage battery materials, characterized in that, Includes the following steps: S1. Construct a two-dimensional planar geometric model containing active particles, solid electrolyte, and lithium metal anode, and embed cohesive units at the solid-solid interface between active particles and solid electrolyte and at the grain boundaries between primary particles. S2. The lithium-ion diffusion equation, linear elasticity equation and cohesive damage evolution equation are coupled and solved. The diffusion-induced stress is calculated by anisotropic lattice strain, and the lithium-ion flux attenuation caused by interface debonding is reverse-coupled to the concentration field by the gap-transfer function. S3. Set the external working pressure, internal porosity, preset pore crack length, Young's modulus ratio of active particles to solid electrolyte, and Poisson's ratio as variable parameters. S4. Perform constant current charge-discharge cycle simulation and output the first principal stress distribution, debonding gap, damage variables and capacity decay curve; S5. By comparing the interface debonding initiation time, intergranular crack area, and residual stress after cycling under different combinations of variable parameters, the influence of each variable parameter on electrochemical-mechanical synergistic failure is evaluated.

2. The method for testing the decay and stress distribution of energy storage battery materials according to claim 1, characterized in that, The two-dimensional planar geometric model in step S1 is constructed based on boundary recognition of real focused ion beam scanning electron microscope images, specifically as follows: Serial slice imaging of active particles was performed using a real focused ion beam scanning electron microscope to obtain the boundary contours of primary particles. Morphological parameters of primary particles are extracted using image recognition technology; The Voronoi algorithm was used to generate a polycrystalline aggregate particle model containing several primary particles, and each primary particle was assigned a random crystal orientation angle to simulate anisotropic lithium diffusion and lattice strain behavior.

3. The method for testing the decay and stress distribution of energy storage battery materials according to claim 1, characterized in that, In step S1, the gap between the active particles and the solid electrolyte is set to an initial zero contact interface. The cohesive unit adopts the triangular traction-separation softening law, and its constitutive parameters include: initial stiffness. Cohesive strength Fixed fracture energy release rate The damage evolution process of the cohesive unit is as follows: In the elastic stage, stiffness increases linearly until it reaches the cohesive strength threshold. In the initial stage of damage, the maximum stress is used for accurate determination. During the damage propagation stage, the stiffness linearly degenerates to zero, and the cohesive elements completely fail.

4. The method for testing the decay and stress distribution of energy storage battery materials according to claim 1, characterized in that, The lithium-ion diffusion equation in step S2 adopts a modified Fick's second law, taking into account the contribution of the stress gradient to the chemical potential: ； in, Lithium ion concentration, For time, The diffusion coefficient of lithium ions is given by the anisotropy of the active particle crystals, with different values ​​set along the a-axis and c-axis respectively. The local diffusion coefficient of each primary particle is obtained by rotating the crystal orientation angle. This represents the partial molar volume of lithium ions. Let be the ideal gas constant. Absolute temperature It is the hydrostatic pressure; The equation of linear elasticity is expressed as: ； in, For stress tensor, For the isotropic elastic stiffness tensor, For total strain, This is the inelastic strain induced by lithium insertion / extraction; Damage variables in the cohesive region damage evolution equation Defined as: ； in, This is the current separation displacement. For the initial displacement of the damage, This represents the displacement of complete failure.

5. The method for testing the decay and stress distribution of energy storage battery materials according to claim 1, characterized in that, In step S2, the anisotropic lattice strain is input using X-ray diffraction experimental data. The lattice strain along the a-axis and c-axis of the primary particle are different. The volumetric strain caused by lithium insertion / extraction has a nonlinear relationship with the normalized lithium concentration. The lattice constant of the active particle material under different charge states is measured by X-ray diffraction experiments. For each primary particle, based on its crystal orientation angle Transform the strain in the crystal coordinate system to the global coordinate system: ； in, This refers to the anisotropic inelastic strain caused by lithium insertion / extraction. Let be the rotation matrix components from the crystal coordinate system to the global coordinate system. This is the other component of the rotation matrix from the crystal coordinate system to the global coordinate system. The lattice strain tensor in the local coordinate system of the crystal is used; the diffusion-induced stress is then calculated using the linear elasticity equations and coupled with the concentration gradient. Define a gap-transfer function to feed back the hindering effect of interface debonding on lithium-ion transport to the concentration field, and the local lithium-ion flux. Revised to: ； in, For lithium-ion flux at a healthy interface. This is a localized debonding gap. For reference gap, This is the empirical attenuation coefficient.

6. The method for testing the decay and stress distribution of energy storage battery materials according to claim 1, characterized in that, The range of values ​​for each variable parameter in step S3 is as follows: External working pressure range: 0 MPa to 200 MPa; internal porosity range: 0% to 15%; ratio of preset pore crack length to active particle radius range: 0 to 0.5; Young's modulus of active particles range: 90 GPa to 130 GPa; Young's modulus of solid electrolyte range: 20 GPa to 80 GPa; Poisson's ratio of active particles range: 0.2 to 0.

4.

7. The method for testing the decay and stress distribution of energy storage battery materials according to claim 1, characterized in that: In step S4, the constant current charge-discharge cycle simulation has a charge-discharge rate of 0.5C to 4C, a charging cut-off voltage of 4.25V, a discharging cut-off voltage of 3.6V, a constant simulation temperature of 293.15K, and the cycle time is set according to the normalization of the charge-discharge rate.

8. The method for testing the decay and stress distribution of energy storage battery materials according to claim 1, characterized in that, Step S5 assesses the impact of each variable parameter on the electrochemical-mechanical synergistic failure, specifically as follows: A single-parameter scanning method was used, with other variable parameters fixed and the target variable parameter changed. The number of cycles at the start of interface debonding, the percentage of intergranular crack area, and the residual first principal stress after the cycle were recorded. Calculate the local sensitivity coefficient for variable parameters. The sensitivity coefficient is defined as: ； in, The output value is the reference parameter. As the baseline parameter value, This represents the change in the output value after the parameter is changed. For parameter changes; when When this happens, the parameter is considered a sensitive parameter; By comparing the absolute values ​​of the sensitivity coefficients of different parameters, the parameter with the larger absolute value has a greater impact on the cooperative failure.

9. The method for testing the decay and stress distribution of energy storage battery materials according to claim 1, characterized in that, Also includes: A phase-field damage model and a cohesive zone model are used to simulate crack propagation. Elastic strain energy is used as the driving force for crack propagation. Phase-field variables are introduced to represent the continuous transition of the material from intact to completely cracked. The phase-field evolution equation is bidirectionally coupled with the stress field and concentration field to simulate the further propagation of cracks inside the particles after the cohesive zone unit completely fails.

10. A system for testing the decay and stress distribution of energy storage battery materials, applied to the method for testing the decay and stress distribution of energy storage battery materials according to any one of claims 1-9, characterized in that, include: The model building module is used to construct a two-dimensional planar geometric model containing active particles, solid electrolyte, and lithium metal anode, and to embed cohesive units at the solid-solid interface between active particles and solid electrolyte and at the grain boundaries between primary particles. The coupled solution module is used to solve the lithium-ion diffusion equation, the linear elasticity equation, and the cohesive damage evolution equation. It calculates the diffusion-induced stress through anisotropic lattice strain, and the lithium flux attenuation caused by interface debonding is back-coupled to the concentration field through the gap-transfer function. The crack propagation module is used to simulate crack propagation by combining the phase field damage model and the cohesive zone model. It uses elastic strain energy as the driving force for crack propagation, introduces phase field variables to represent the continuous transition of the material from intact to completely cracked, and couples the phase field evolution equation with the stress field and concentration field in both directions to simulate the further propagation of cracks inside the particles after the cohesive unit completely fails. The parameter setting module is used to set the external working pressure, internal porosity, preset pore crack length, Young's modulus ratio of active particles to solid electrolyte, and Poisson's ratio as variable parameters. The cyclic simulation module is used to perform constant current charge-discharge cyclic simulation and output the first principal stress distribution, debonding gap, damage variables and capacity decay curve. The parameter evaluation module is used to assess the influence of each parameter on electrochemical-mechanical synergistic failure by comparing the interface debonding initiation time, intergranular crack area, and post-cycle residual stress under different parameter combinations.

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