Simulation method and device of solid-state battery module, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a simulation method and device of a solid-state battery module, electronic equipment and a storage medium, and relates to the technical field of solid-state batteries. Acquiring attribute parameters of the battery units; performing electrochemical-thermal-mechanical coupling simulation on the charging and discharging process of the battery unit under the target working condition according to the attribute parameters of the battery unit to obtain a coupling simulation result corresponding to the battery unit; according to the coupling simulation result of the battery units, thermal-mechanical coupling simulation is carried out on the charging and discharging process of a battery cell formed by stacking the multiple battery units under the target working condition, and the temperature variation of the battery cell is obtained; and according to the temperature variation of the battery cells, performing mechanical simulation on the battery module formed by the plurality of battery cells to obtain the mechanical characteristics of the battery module under the current structure. Therefore, scientific prediction of the mechanical response characteristics of the solid-state battery module in a real use environment can be realized, and a reliable theoretical basis and an effective simulation means are provided for mechanical structure design and optimization of the solid-state battery module.

Description

Technical Field

[0001] This application relates to the field of solid-state battery technology, and more specifically, to a simulation method, apparatus, electronic device, and storage medium for a solid-state battery module. Background Technology

[0002] With the rapid popularization of new energy vehicles, the market has placed higher demands on power batteries in terms of energy density, safety, and lifespan. Traditional liquid lithium batteries are gradually approaching their performance limits and pose a risk of thermal runaway, making it difficult to fully meet the development needs of future high-end electric vehicles. Against this backdrop, solid-state batteries, which use non-flammable solid electrolytes instead of flammable organic electrolytes, fundamentally improve battery safety while possessing higher energy density potential and longer cycle life. They are considered the core technology path for next-generation automotive power batteries and are becoming a key focus of research and development by industry and research institutions.

[0003] However, the mechanical structure design at the module level faces significant challenges in the practical application of solid-state batteries in automobiles. A key issue is the volume change, or "breathing," that occurs in solid-state batteries during charging and discharging due to the insertion and extraction of lithium ions into the electrode materials. This repeated expansion and contraction is particularly pronounced in solid-state batteries. Because they are entirely composed of solid materials and lack the buffering effect of a liquid electrolyte, the interface between the electrodes and the electrolyte is prone to poor contact, crack propagation, and even delamination under stress. These mechanical failure mechanisms not only affect the performance stability of individual cells but also trigger chain reactions at the module level, leading to uneven stress distribution and pressure imbalance in the overall structure, thereby threatening the long-term reliability and safety of the module.

[0004] Currently, the structural design of solid-state battery modules can often be guided by simulating the charging and discharging process of solid-state battery modules under complex operating conditions. However, the simulation methods in related technologies often cannot predict the actual mechanical response characteristics of solid-state battery modules in real-world usage environments, thus making it difficult to provide sufficiently accurate results to effectively guide engineering design. Summary of the Invention

[0005] In view of this, the purpose of this application is to provide a simulation method, apparatus, electronic device and storage medium for solid-state battery modules, so as to accurately simulate the mechanical response characteristics of solid-state battery modules in real use environments, thereby providing reliable theoretical guidance for the mechanical structure design and optimization of solid-state battery modules.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows: In a first aspect, this application provides a simulation method for a solid-state battery module, the method comprising: Obtain the property parameters of the battery cell; the property parameters include the structural parameters, electrochemical parameters, thermal parameters and mechanical parameters of the battery cell; Based on the attribute parameters of the battery cell, an electrochemical-thermal-mechanical coupled simulation of the charging and discharging process of the battery cell under the target operating conditions is performed to obtain the coupled simulation results corresponding to the battery cell. Based on the coupled simulation results of the battery cells, a thermo-mechanical coupled simulation is performed on the charging and discharging process of a cell composed of multiple stacked battery cells under the target operating condition to obtain the temperature change of the cell; the cell is composed of multiple stacked battery cells. Based on the temperature change of the battery cells, a mechanical simulation is performed on a battery module composed of multiple battery cells to obtain the mechanical characteristics of the battery module under the current structure.

[0007] In an optional implementation, the step of performing electrochemical-thermal-mechanical coupled simulation of the charging and discharging process of the battery cell under target operating conditions based on the attribute parameters of the battery cell, and obtaining the coupled simulation results corresponding to the battery cell, includes: Construct a three-dimensional geometric model of the battery cell based on the structural parameters; An electrochemical-thermal-mechanical coupling model of the battery cell is constructed based on the electrochemical parameters, the thermal parameters, and the mechanical parameters. Based on the electrochemical-thermal-mechanical coupling model, an electrochemical-thermal-mechanical coupling simulation is performed on the three-dimensional geometric model of the battery cell under the target operating conditions to obtain the coupling simulation results. The electrochemical-thermal-mechanical coupling model includes an electrochemical model, a thermal model, and a mechanical model. The electrochemical model and the thermal model are bidirectionally coupled, the electrochemical model and the mechanical model are bidirectionally coupled, and the thermal model and the mechanical model are unidirectionally coupled.

[0008] In an optional embodiment, the electrochemical parameters include maximum lithium concentration, diffusion coefficient, charge transfer coefficient, and reaction rate constant; the thermal parameters include thermal conductivity, specific heat capacity, and density; and the mechanical parameters include elastic modulus, Poisson's ratio, and coefficient of thermal expansion. The construction of the electrochemical-thermal-mechanical coupling model of the battery cell based on the electrochemical parameters, the thermal parameters, and the mechanical parameters includes: The actual contact area ratio is calculated based on the elastic modulus and the Poisson's ratio, and the electrochemical model is constructed based on the actual contact area ratio, the maximum lithium concentration, the diffusion coefficient, the charge transfer coefficient, the reaction rate constant, the temperature value in the thermal model, and the net water stress in the mechanical model. The thermal model is constructed based on the thermal conductivity, specific heat capacity, density, local current density and overpotential in the electrochemical model; The mechanical model is constructed based on the elastic modulus, Poisson's ratio, coefficient of thermal expansion, lithium ion concentration in the electrochemical model, and temperature in the thermal model.

[0009] In an optional embodiment, the step of calculating the actual contact area ratio based on the elastic modulus and the Poisson's ratio, and constructing the electrochemical model based on the actual contact area ratio, the maximum lithium concentration, the diffusion coefficient, the charge transfer coefficient, the reaction rate constant, the temperature value in the thermal model, and the hydrostatic stress in the mechanical model, includes: The actual contact area ratio is calculated using the following formula:

[0010] in, Characterizing the actual contact area ratio Characterized in Contact area under magnification Characterizing the nominal contact area, and Characterizing the elastic modulus, and Characterizing the Poisson's ratio, Characterizing the macroscopic pressure acting on a rough surface, The minimum wave vector represents the maximum length of the corresponding surface, and q represents the wave vector. Power spectral density characterizing surface roughness of rough surfaces; The electrochemical model is constructed using the following formula:

[0011]

[0012] in, Characterizes lithium-ion flux. Characterizing the diffusion coefficient, Characterizing the lithium-ion concentration gradient, Characterizing partial molar volume, Characterizing lithium-ion concentration, The gas constant is represented by T, and the temperature value in the thermal model is represented by T. Characterizing the hydrostatic stress in the mechanical model, Characterizing local current density, Characterizing the exchange current density, Characterizing the actual contact area ratio Characterizing the charge transfer coefficient, Characterizing overpotential, The Faraday constant is represented by k, and the reaction rate constant is represented by k. Characterizing the maximum lithium concentration, Characterizing the lithium concentration on the surface of electrode particles, Characterizes the lithium-ion concentration within the electrolyte. Characterizes the lithium-ion diffusion coefficient within the electrolyte. Characterizes the lithium ion concentration gradient within the electrolyte.

[0013] In an optional implementation, constructing the thermal model based on the thermal conductivity, specific heat capacity, density, local current density, and overpotential in the electrochemical model includes: The thermal model is constructed using the following formula:

[0014] in, Characterizing the density, The specific heat capacity is represented by T, the temperature by K, and the thermal conductivity by k. Characterizes the internal heat source of the battery. Characterizing Ohm heat, Characterizing polarization heat, Characterizing reversible heat, Characterizing the heat of side reactions, I characterizes the total current. The local current density is represented by A, and the local contact area is represented by A. Characterizing the overpotential, U represents the potential gradient, and U represents the voltage.

[0015] In an optional implementation, constructing the mechanical model based on the elastic modulus, the Poisson's ratio, the coefficient of thermal expansion, the lithium-ion concentration in the electrochemical model, and the temperature in the thermal model includes: The mechanical model is constructed using the following formula:

[0016] in, E represents the strain in the ij direction, and E represents the elastic modulus. Characterizing the stress in the ij direction, Characterizing the Poisson's ratio, Characterizes the volume expansion rate related to lithium-ion concentration. Characterizing the lithium-ion concentration in the electrochemical model, Characterizing the coefficient of thermal expansion, Characterizes the amount of temperature change determined based on the temperature in the aforementioned thermal model. Characterize the Kronecker function.

[0017] In an optional implementation, the step of performing a thermo-mechanical coupling simulation on the charging and discharging process of a cell composed of multiple stacked battery cells under the target operating condition, based on the coupling simulation results of the battery cells, to obtain the temperature change of the cell, includes: The coupled simulation results of the battery cells are applied to the cell structure composed of multiple battery cells stacked by scaling, and the cell is subjected to thermo-mechanical coupling simulation under the target operating condition to obtain the volume change of the cell. The temperature change of the battery cell is calculated based on the volume change, the initial volume of the battery cell, and a preset volume expansion formula.

[0018] Secondly, this application provides a simulation device for a solid-state battery module, the device comprising: The acquisition module is used to acquire the attribute parameters of the battery cell; the attribute parameters include the structural parameters, electrochemical parameters, thermal parameters and mechanical parameters of the battery cell; The simulation module is used to perform electrochemical-thermal-mechanical coupling simulation of the charging and discharging process of the battery cell under the target operating conditions based on the attribute parameters of the battery cell, and obtain the coupling simulation results corresponding to the battery cell. The simulation module is also used to perform thermo-mechanical coupling simulation of the charging and discharging process of a cell composed of multiple stacked battery cells under the target operating condition based on the coupling simulation results of the battery cells, so as to obtain the temperature change of the cell; the cell is composed of multiple stacked battery cells. The simulation module is also used to perform mechanical simulation on a battery module composed of multiple battery cells based on the temperature change of the battery cells, so as to obtain the mechanical characteristics of the battery module under the current structure.

[0019] Thirdly, this application provides an electronic device including a processor and a memory, wherein the memory stores a computer program executable by the processor, and the processor can execute the computer program to implement the method described in any of the foregoing embodiments.

[0020] Fourthly, this application provides a storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in any of the foregoing embodiments.

[0021] The simulation method, apparatus, electronic device, and storage medium for solid-state battery modules provided in this application acquire the attribute parameters of battery cells and perform electrochemical-thermal-mechanical coupled simulation of the charging and discharging process of the battery cells under target operating conditions based on these attribute parameters. The coupled simulation results reflect the interactions between various physical mechanisms during the charging and discharging process of the battery cells. Based on these coupled simulation results, a thermo-mechanical coupled simulation is performed on a battery cell composed of multiple stacked battery cells, enabling scale transfer from micro-units to macro-cells. During this process, the temperature change of the battery cell can be accurately calculated. Finally, the obtained temperature change of the battery cell is used to perform mechanical simulation of a battery module composed of multiple battery cells. This simulation can model the mechanical interactions between external constraint structures, buffer materials, and the battery cells, thereby obtaining the mechanical characteristics of the battery module under the current structural design. As can be seen, this method effectively transmits the multi-physics coupling behavior of battery cells to the module level through a progressive simulation process, so that the mechanical response analysis of the module is based on the real physical mechanism, rather than relying on empirical assumptions or simplified models. This enables the scientific prediction of the mechanical response characteristics of solid-state battery modules in real-world usage environments, providing a reliable theoretical basis and effective simulation means for the mechanical structure design and optimization of solid-state battery modules.

[0022] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A block diagram of an electronic device provided in an embodiment of this application is shown; Figure 2 This paper illustrates a flowchart of a simulation method for a solid-state battery module provided in an embodiment of this application. Figure 3 This shows the pressure distribution cloud map on the surface of the battery cell obtained after mechanical simulation; Figure 4 The stress distribution cloud map of the battery module obtained after mechanical simulation is shown. Figure 5 The volumetric strain distribution cloud map of the battery cell obtained through simulation is shown. Figure 6The simulation-obtained volumetric strain distribution cloud map of the battery cell is shown. Figure 7 An example diagram of equivalent volumetric strain calculation is shown; Figure 8 A schematic diagram of the simulation process for automotive solid-state lithium batteries is shown. Figure 9 A functional block diagram of a simulation device for a solid-state battery module provided in an embodiment of this application is shown. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can be arranged and designed in various different configurations.

[0026] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0027] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0028] In the structural design of automotive solid-state battery modules, accurately predicting their mechanical response characteristics under actual operating conditions is crucial for ensuring system safety, reliability, and cycle life. However, traditional simulation methods often fail to provide sufficiently accurate results to effectively guide engineering design. This limitation mainly stems from the simplified handling of multiphysics coupling mechanisms and scale transfer relationships.

[0029] Specifically, related technologies often treat electrochemical behavior, thermal effects, and mechanical deformation separately, failing to fully reflect the essential characteristics of the interaction between various physical processes within solid-state batteries. Especially during charging and discharging, the insertion and extraction of lithium ions in the electrode material not only induces local volume changes, the so-called "intercalation stress," but also leads to spatial differences in stress distribution due to reaction inhomogeneity. The evolution of such stress is directly affected by changes in the temperature field and the interfacial contact state.

[0030] In this context, if the simulation model does not systematically integrate the interactions between electrochemistry, thermodynamics, and mechanical forces, it cannot accurately reproduce the expansion behavior of the battery cell under target operating conditions. For example, increased temperature accelerates the electrochemical reaction rate, thereby altering the heat generation intensity and lithium-ion diffusion flux, which in turn affects the elastic response and thermal expansion of the material. When these coupling effects are ignored or roughly approximated, the obtained stress and strain data deviate from the actual state, rendering subsequent structural assessments based on these results meaningless.

[0031] Furthermore, in automotive solid-state battery systems, battery modules are structural units composed of multiple cells, and each cell is assembled from several battery units through layering or stacking. From battery units to cells and then to battery modules, the mechanical response exhibits the characteristics of gradual accumulation and mutual feedback. Deformation or stress state at any level will directly affect the performance and reliability of the upper structure.

[0032] However, current research largely focuses on simulations and experimental analyses at the individual cell level, emphasizing internal electrochemical processes, thermal distribution, and expansion characteristics. This often neglects the actual stress environment of the cell within the overall module structure and its mechanical interactions with other components. This single-cell-based analytical approach struggles to reflect issues such as uneven pressure distribution and expansion interference between adjacent cells under real-world assembly conditions, resulting in inaccurate results that cannot guide module-level structural design.

[0033] It is evident that traditional simulation methods, lacking a systematic modeling path that spans multiple scales and encompasses multiple physics fields, result in significant deviations between simulation results and actual mechanical behavior. This fragmented analytical framework cannot meet the structural design accuracy requirements of automotive solid-state battery modules under complex vibration, shock, and thermal cycling conditions, thus limiting its application value in optimizing pressurization mechanisms, improving pressure uniformity, and preventing structural failure.

[0034] Based on this, embodiments of this application provide a simulation method, apparatus, electronic device, and storage medium for solid-state battery modules to solve the above-mentioned problems.

[0035] Figure 1Please refer to the block diagram of the electronic device provided in the embodiments of this application. Figure 1 The electronic device includes a memory, a processor, and a communication module. These components are electrically connected directly or indirectly to enable data transmission or interaction. For example, they can be electrically connected via one or more communication buses or signal lines.

[0036] Memory is used to store computer programs or data that can be executed by a processor. Memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc.

[0037] The processor is used to read / write data computer programs stored in the memory, and execute the computer programs to implement the simulation method of the solid-state battery module provided in the embodiments of this application.

[0038] The communication module is used to establish communication connections between electronic devices and other communication terminals via a network, and to send and receive data via the network.

[0039] It should be understood that, Figure 1 The structure shown is only a schematic diagram of an electronic device; the electronic device may also include components that are larger than those shown. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown. Figure 1 The components shown can be implemented using hardware, software, or a combination thereof.

[0040] The following is based on the above. Figure 1 The electronic devices in this application serve as the execution entity. The simulation method for a solid-state battery module provided in this embodiment is illustrated with a flowchart. Specifically, Figure 2 For a flowchart illustrating the simulation method of the solid-state battery module provided in this application embodiment, please refer to [link / reference]. Figure 2 The method includes: Step S20: Obtain the attribute parameters of the battery cell.

[0041] Among them, the attribute parameters include the structural parameters, electrochemical parameters, thermal parameters, and mechanical parameters of the battery cell.

[0042] In this embodiment, the structural parameters reflect the spatial dimensions and geometric configuration of each functional layer of the battery cell, including the thickness, length, and width information of components such as the positive electrode current collector, positive electrode active layer, solid electrolyte, negative electrode active layer, and negative electrode current collector. This data is used to construct a three-dimensional geometric model of the battery cell, ensuring that the simulation model is consistent with the actual product in terms of spatial scale.

[0043] Electrochemical parameters refer to key physical quantities in the process of lithium-ion migration and charge transfer. These parameters together determine the distribution of lithium-ion concentration, evolution of current density, and changes in local overpotential within the electrode. Thermal parameters describe the material's ability to generate and transfer heat during charging and discharging. Accurate prediction of the temperature field by these parameters provides the input basis. Mechanical parameters characterize the deformation properties of the material under external force or temperature changes and are the core input for establishing stress-strain relationships.

[0044] Optionally, the property parameters of the battery cell can be obtained based on the actual material system used inside the battery cell. For example, the thermophysical parameters and mechanical performance indicators of each layer of material can be obtained through material property testing or technical data provided by the supplier; key electrochemical parameters can be determined through electrochemical experimental calibration or literature reference; and structural parameters can be set according to the overall layout requirements of the battery module.

[0045] Based on this, electronic devices can unify various parameters into an input dataset that can be used for numerical simulation, thereby completing the systematic acquisition of battery cell attribute parameters. This process not only ensures the physical authenticity of the simulation model, but also provides the necessary boundary and initial conditions for the subsequent construction of an electrochemical-thermal-mechanical coupling model.

[0046] Step S21: Perform electrochemical-thermal-mechanical coupling simulation on the charging and discharging process of the battery cell under the target operating conditions based on the attribute parameters of the battery cell, and obtain the coupling simulation results corresponding to the battery cell.

[0047] In this embodiment, the behavior of the battery cell during charging and discharging is not the result of a single physical field, but a complex process involving the coupling of electrochemical reactions, heat generation, and mechanical deformation. To accurately characterize this multi-physics interaction mechanism, the electronic device needs to construct a simulation model that reflects its intrinsic response law based on the acquired battery cell attribute parameters. This is achieved by building an electrochemical-thermal-mechanical coupling model of the solid-state lithium battery cell, applying target operating conditions to its three-dimensional geometry, and conducting coupled simulations to obtain the corresponding coupled simulation results for the battery cell.

[0048] Optionally, electronic devices can integrate the above-mentioned models and the inherent coupling mechanism between the three physical fields of electrochemistry, thermodynamics and mechanics into a simulation platform to perform numerical calculations under set target operating conditions (such as specific charge and discharge rates and ambient temperature boundary conditions), and finally output the coupled simulation results corresponding to the battery cells, such as lithium ion concentration distribution, temperature distribution, stress and strain state and overall volume change trend.

[0049] Therefore, this step, through the synergistic modeling and joint solution of electrochemical, thermal, and mechanical behaviors, achieves refined prediction of the multi-physics response of battery cells under real operating conditions. The obtained coupled simulation results not only reflect the spatial distribution characteristics of local physical quantities, but also provide a reliable input basis for subsequently extending the battery cell behavior to the cell level.

[0050] Understandably, electronic devices can improve the accuracy and engineering guidance value of the entire simulation chain by integrating physical models from multiple fields and establishing reasonable inter-field coupling mechanisms, making the simulation process closer to the actual operating mechanism.

[0051] Step S22: Based on the coupled simulation results of the battery cells, perform a thermo-mechanical coupled simulation of the charging and discharging process of a cell composed of multiple stacked battery cells under the target operating conditions to obtain the temperature change of the cell.

[0052] The battery cell is composed of multiple stacked battery units.

[0053] It should be understood that the simulation results of a battery cell, as the smallest functional level of electrochemical structure, mainly reflect the local response behavior of a single-layer structure under target operating conditions. However, in actual applications, a battery cell is composed of multiple stacked battery cells, and its overall expansion characteristics depend not only on the deformation trend of individual battery cells but also on interlayer constraints, boundary conditions, and structural symmetry. Therefore, to accurately predict the macroscopic mechanical and thermal performance of a battery cell during charging and discharging, it is necessary to extend the coupling simulation results of the battery cell to the cell level and conduct thermo-mechanical coupling simulations based on this.

[0054] In this embodiment, the electronic device can analyze the volume change of the battery cell under target operating conditions by performing thermo-mechanical coupling simulation on the entire cell. This simulation process no longer repeatedly solves the complete electrochemical model, but instead uses the coupled simulation results of the aforementioned battery cell as a basis to extract key physical quantities such as lithium concentration distribution, heat generation rate, and local strain as boundary conditions or loads applied to the multilayer structure model, thereby simulating the temperature evolution and mechanical deformation of the battery cell during operation.

[0055] Due to the end constraints and non-ideal interlayer contact of the stacked structure, the actual expansion behavior may exhibit non-uniform characteristics. Simulation can capture such effects and output the equivalent temperature change of the entire cell.

[0056] It should be noted that in the simulation modeling process, the analysis objects at different levels have different functional orientations and computational objectives. As the smallest electrochemical functional unit, the lithium-ion migration, charge transfer, and interfacial reactions that occur inside the battery cell must be described through a complete electrochemical model. Therefore, it is necessary to establish a full-physics field model that couples electrochemistry, thermodynamics, and mechanics to accurately capture the bidirectional influence between various physical mechanisms.

[0057] However, when the research focus shifts from individual battery cells to battery cells stacked together, the simulation focus changes from microscopic reaction mechanisms to macroscopic structural responses, particularly overall expansion behavior and its impact on surrounding components. In this context, the primary purpose of cell-level simulations is to obtain the temperature changes during charging and discharging, which serve as input loads for subsequent module structural mechanics simulations. Since the expansion characteristics of a battery cell are essentially driven by the electrochemical behavior of its individual battery cells, which has already been fully solved and determined in the previous level of cell simulation, there is no need to repeat electrochemical calculations at the cell level. At this point, the effects of the electrochemical process are transformed into intermediate physical quantities such as local strain, heat generation rate, and lithium concentration distribution, and introduced as boundary conditions or source terms into the current level of thermo-mechanical coupling simulations.

[0058] Therefore, this step effectively connects the microscopic mechanism to the macroscopic response by transferring the detailed simulation results at the battery cell level to the cell level. Electronic devices can utilize the electrochemical-thermal-mechanical coupling simulation results of the battery cell to perform thermo-mechanical coupling simulation of the cell, significantly reducing computational resource consumption while ensuring simulation accuracy, thereby efficiently obtaining the comprehensive expansion characteristics of the cell under target operating conditions.

[0059] Step S23: Based on the temperature change of the battery cells, perform mechanical simulation on the battery module composed of multiple battery cells to obtain the mechanical characteristics of the battery module under the current structure.

[0060] In this embodiment, the battery module, as a complex structural system composed of multiple integrated cells, must withstand the expansion forces generated by the cells during charge-discharge cycles during actual operation, and also maintain the mechanical balance between the external pressurization mechanism and internal components in the assembled state. To accurately evaluate the load-bearing capacity and stability of this structure under real-world conditions, a mechanical simulation analysis of the overall configuration is required. The key input condition for this simulation comes from the cell temperature changes obtained from previous levels; both factors together reflect the comprehensive deformation behavior of the cells under operating conditions.

[0061] During the above steps, the electronic device can use professional mechanical simulation software to import the three-dimensional geometric model of the solid-state battery module and assign corresponding material properties to each component to ensure that the simulation environment is consistent with the physical structure.

[0062] Based on this, the electronic device can input the temperature change calculated in the previous steps as an initial condition into the mechanical simulation software and apply it to the cell region to simulate the expansion effect it exhibits during charging and discharging. This equivalent processing method can retain the characteristics of the cell expansion's effect on the surrounding structure without repeatedly solving the thermo-mechanical coupling field, thereby improving computational efficiency and ensuring the physical rationality of the boundary conditions.

[0063] Furthermore, in the simulation settings, the electronic device can also apply fixed constraints to both ends of the module to simulate the boundary constraints of the end plate or shell on the overall structure; at the same time, an initial preload is applied to bolts, cable ties, or other pressure structures to reproduce the pressure state applied manually during assembly. In addition, considering the non-rigid contact characteristics between the battery cell and the interface of the buffer pad, insulation layer, etc., it is also necessary to input the preset contact relationship and friction coefficient to ensure the authenticity of the force transmission path.

[0064] In one example Figure 3 This is a cloud map of the pressure distribution on the surface of the battery cell obtained after mechanical simulation. Figure 4 For the stress distribution cloud map of the battery module obtained after mechanical simulation, please refer to [link / reference]. Figure 3 and Figure 4 After completing the above boundary conditions and load configuration, the electronic device can perform simulation calculations and output the stress distribution, strain response, and spatial distribution of pressure on the surface of the battery cell for each component inside the module.

[0065] In this embodiment, the electronic device can focus on extracting two key evaluation indicators for structural design optimization: the first is the structural strength indicator, namely, the maximum Von-Mises stress at each point of the module must be less than the yield strength of the material at the corresponding location divided by a set safety factor, in order to avoid plastic deformation or fatigue failure; the second is the pressure uniformity indicator. It should be less than or equal to the preset value, where, ,in, Characterizes the maximum pressure on a specified surface. Characterizes the minimum pressure on a specified surface. Characterizes the average pressure on a specified surface. This indicator is used to quantify the uniformity of pressure distribution on the cell surface and prevent poor interfacial contact or material damage caused by local over- or under-voltage.

[0066] It can be seen that this step, by introducing the output of the previous level simulation as an equivalent source, realizes the cross-scale mapping from cell expansion behavior to module structure response.

[0067] In this embodiment, the electronic device can simplify the complex multiphysics expansion mechanism into a mechanical input that can be directly used for structural simulation by utilizing an equivalent temperature load. This reduces modeling complexity while maintaining high-fidelity reproduction of key mechanical properties. The resulting stress and pressure distribution data can be directly used to evaluate the rationality of existing design schemes and guide the adjustment of pressurization mechanism parameters, selection of buffer materials, and optimization of assembly processes, thereby improving the overall safety and reliability of the module.

[0068] The simulation method for solid-state battery modules provided in this application allows electronic devices to acquire the attribute parameters of battery cells and perform electrochemical-thermal-mechanical coupled simulations of the charging and discharging process of the battery cells under target operating conditions based on these attribute parameters. The coupled simulation results reflect the interactions between various physical mechanisms during the charging and discharging process of the battery cells. Based on these coupled simulation results, a thermo-mechanical coupled simulation is performed on a battery cell composed of multiple stacked battery cells, enabling scale transfer from micro-units to macro-cells. During this process, the temperature change of the battery cell can be accurately calculated. Finally, the obtained temperature change of the battery cell is used to perform mechanical simulations on a battery module composed of multiple battery cells. This simulates the mechanical interactions between external constraint structures, buffer materials, and the battery cells, thereby obtaining the mechanical characteristics of the battery module under the current structural design. As can be seen, this method effectively transmits the multi-physics coupling behavior of battery cells to the module level through a progressive simulation process, so that the mechanical response analysis of the module is based on the real physical mechanism, rather than relying on empirical assumptions or simplified models. This enables the scientific prediction of the mechanical response characteristics of solid-state battery modules in real-world usage environments, providing a reliable theoretical basis and effective simulation means for the mechanical structure design and optimization of solid-state battery modules.

[0069] The following section discusses a possible approach to perform electrochemical-thermal-mechanical coupled simulation of the charging and discharging process of a battery cell under target operating conditions based on the cell's property parameters, in order to obtain the corresponding coupled simulation results.

[0070] Specifically, electronic devices can construct a three-dimensional geometric model of the battery cell based on structural parameters, construct an electrochemical-thermal-mechanical coupling model of the battery cell based on electrochemical parameters, thermal parameters, and mechanical parameters, and perform electrochemical-thermal-mechanical coupling simulation on the three-dimensional geometric model of the battery cell under target operating conditions based on the electrochemical-thermal-mechanical coupling model to obtain coupling simulation results.

[0071] The electrochemical-thermal-mechanical coupling model includes an electrochemical model, a thermal model, and a mechanical model. The electrochemical model and the thermal model are bidirectionally coupled, the electrochemical model and the mechanical model are bidirectionally coupled, and the thermal model and the mechanical model are unidirectionally coupled.

[0072] In this embodiment, in order to accurately predict the comprehensive response behavior of the unit under the target operating conditions, it is necessary to construct a joint simulation model containing three physical fields—electrochemical, thermal, and mechanical—based on its geometric structure, and to clarify the interaction mechanism between each field.

[0073] During the above steps, the electronic device can first establish a three-dimensional geometric model of the battery cell based on the structural parameters. This model covers the basic constituent layers such as the positive electrode current collector, positive electrode active layer, solid electrolyte, negative electrode active layer, and negative electrode current collector, and also includes conductive lead-out structures such as positive and negative electrode tabs, ensuring that the geometric configuration is consistent with the actual design. This three-dimensional model is a spatially continuous solid structure used to carry out subsequent multiphysics numerical solutions and serves as the basic carrier for conducting simulations.

[0074] Based on this, electronic devices can use electrochemical parameters, thermal parameters, and mechanical parameters to construct electrochemical models, thermal models, and mechanical models respectively, and form a complete electrochemical-thermal-mechanical coupling model by setting reasonable coupling relationships.

[0075] In one possible approach, the electrochemical model can employ a pseudo-two-dimensional (P2D) modeling method. This treats the electrode region as a stack of multiple two-dimensional planes, solving for the diffusion of lithium ions within the active particles, their migration in the electrolyte, and the charge transfer reactions at the interface on each cross-section. This avoids directly modeling the complex microstructure in the thickness direction. The positive and negative active layers are configured as porous electrodes, while the solid electrolyte is treated as a single-ion conductor. For boundary conditions, a charge / discharge current density or cyclic current signal is applied to the positive electrode tab, while the negative electrode tab is set to ground potential to simulate the external circuit connection state.

[0076] The thermal model can be constructed based on the principle of energy conservation, treating the ohmic heat, polarization heat, and reversible heat generated during the electrochemical reaction as internal heat sources, distributing them to the corresponding material regions, and calculating the heat conduction and accumulation process within the battery cell by combining the thermal properties of the material, such as thermal conductivity, specific heat capacity, and density. Simultaneously, by setting appropriate surface heat transfer conditions or heat flux boundaries, the heat dissipation behavior under actual operating conditions can be simulated.

[0077] The mechanical model assumes that the materials in each layer of the battery cell obey a linear elastic constitutive relation, meaning that stress and strain satisfy Hooke's law. Based on this, an intercalation strain term is introduced into the positive and negative active layers. This strain is generated by the lattice volume change caused by lithium-ion insertion or extraction, and its magnitude is related to the local lithium-ion concentration. By superimposing the intercalation effect as an additional strain source into the total strain field, the resulting internal stress distribution can be calculated. Furthermore, the thermal expansion effect caused by temperature changes is also included as an independent strain contribution term in the model.

[0078] In this process, a clear interaction mechanism is established between the various physical fields: the electrochemical reaction rate is affected by temperature, and the heat generated by the reaction changes the temperature distribution, forming a two-way coupling between the electrochemical model and the thermal model; changes in lithium ion concentration cause intercalation stress, which in turn changes the local strain state of the material, and the stress gradient, in turn, affects the diffusion driving force of lithium ions, forming a two-way feedback between the electrochemical model and the mechanical model; temperature changes cause thermal expansion, thereby generating thermal stress, but the stress has no direct reaction effect on the temperature field, so the thermal model and the mechanical model are unidirectionally coupled.

[0079] Once the model is built, the electronic device can perform joint simulations under the set target operating conditions, outputting key results such as the lithium-ion concentration distribution, temperature field evolution, stress-strain state, and overall volume change trend within the battery cell. These results together constitute the coupled simulation results corresponding to the battery cell, which not only reflect the spatial distribution characteristics of each physical quantity but also provide necessary data support for the subsequent transmission of expansion behavior to the cell level.

[0080] In one possible implementation, the electrochemical parameters include maximum lithium concentration, diffusion coefficient, charge transfer coefficient, and reaction rate constant; the thermal parameters include thermal conductivity, specific heat capacity, and density; and the mechanical parameters include elastic modulus, Poisson's ratio, and coefficient of thermal expansion.

[0081] Based on this, electronic devices can calculate the actual contact area ratio using the elastic modulus and Poisson's ratio, and construct an electrochemical model based on the actual contact area ratio, maximum lithium concentration, diffusion coefficient, charge transfer coefficient, reaction rate constant, temperature value in the thermal model, and net water stress in the mechanical model; construct a thermal model based on thermal conductivity, specific heat capacity, density, local current density and overpotential in the electrochemical model; and construct a mechanical model based on the elastic modulus, Poisson's ratio, coefficient of thermal expansion, lithium ion concentration in the electrochemical model, and temperature in the thermal model.

[0082] In this embodiment, the electrochemical model is established based on the Butler-Volmer kinetic equation, Fick's law, and Ohm's law to describe the diffusion process of lithium ions in the electrode active layer, their migration behavior in the electrolyte, and the charge transfer reaction at the electrode / electrolyte interface. The maximum lithium concentration characterizes the maximum molar density of lithium that can be intercalated in the electrode material and is a key variable for calculating the lithium ion concentration gradient and intercalation stress. The diffusion coefficient reflects the mass transfer capability of lithium ions within the solid particles and directly affects the evolution rate of the concentration distribution during charging and discharging. The charge transfer coefficient and reaction rate constant determine the kinetics of the interfacial electrochemical reaction, thus affecting the local current density and overpotential. These parameters are substituted into the Butler-Volmer equation and the mass conservation equation to achieve quantitative simulation of the internal electrochemical behavior of the battery.

[0083] Building upon this foundation, to accurately describe the interfacial contact state between the electrode and the solid electrolyte, a contact model can be introduced to calculate the actual contact area ratio. This ratio is calculated using mechanical parameters such as elastic modulus and Poisson's ratio, combined with surface roughness power spectral density and macroscopic pressure. Its core principle lies in considering the non-ideal contact characteristics of the two solid surfaces at the microscopic scale. Since solid-state batteries use rigid electrolytes, incomplete interfacial contact can lead to localized current concentration or uneven reactions. Therefore, the actual contact area ratio is introduced as a correction factor into the local current density term, thereby improving the accuracy of the electrochemical model in depicting the real reaction region.

[0084] Understandably, this allows the electrochemical reaction rate to be dynamically adjusted based on the effective contact area, rather than the nominal contact area, thus enhancing the model's ability to predict interfacial behavior.

[0085] In this embodiment, the thermal model is constructed based on the principle of energy conservation, comprehensively considering various heat sources generated during the electrochemical process, including ohmic heat, polarization heat, reversible heat, and side reaction heat, which are then incorporated as internal heat source terms into the heat conduction equation. Thermal conductivity determines the efficiency of heat transfer between the positive electrode, negative electrode, and electrolyte layers. Specific heat capacity and density jointly affect the material's thermal capacity characteristics, i.e., the amount of heat absorbed by a unit mass of material to raise its temperature by a unit. These thermal parameters are derived from material property test data; for example, the thermal conductivity of NMC positive electrode material is 3.6 W / (m·K), graphite negative electrode is 1 W / (m·K), and sulfide electrolyte is 0.3 W / (m·K). Combined with the local current density and overpotential output from the electrochemical model, the spatially uneven heat generation rate is calculated, ultimately solving for the temperature field distribution inside the battery cell.

[0086] The mechanical model is established based on the linear elasticity assumption and stress-strain relationship, aiming to capture the mechanical deformation caused by the intercalation effect and thermal expansion. The elastic modulus and Poisson's ratio define the material's stiffness and lateral deformation response under stress, while the coefficient of thermal expansion characterizes the material's volume change with temperature. During modeling, lithium-ion concentration information from the electrochemical model is used, combined with empirical functions or constitutive relations, to determine the volume expansion rate related to lithium content, which is added to the total strain expression as an intercalation strain source term. Simultaneously, the thermal strain component is calculated based on the temperature distribution in the thermal model, combined with the coefficient of thermal expansion. The superposition of these two strain components is used to solve for the internal stress state, revealing the potential stress concentration or interface delamination risks that may occur in the battery cell during charge-discharge cycles.

[0087] The simulation method for solid-state battery modules provided in this application integrates three types of parameters—electrochemical, thermal, and mechanical—to support the construction of their respective physical field models. It also achieves collaborative simulation of multiple physical processes through an inter-field coupling mechanism, deeply integrating measured material parameters with physical mechanism models. This enables high-fidelity reproduction of the interactions between electrochemical reactions, heat generation, and structural deformation, providing a solid data foundation for the subsequent transfer of simulation results to the cell and module levels.

[0088] In addition, the electrochemical parameters may also include initial lithium concentration, active material volume fraction, electronic conductivity, porosity, particle radius, lithium-ion conductivity, etc., which are used to define the initial state, spatial distribution weights, transport paths and interface behavior during the simulation.

[0089] In one example, a sulfide solid-state battery is used. Table 1 shows the attribute parameters of this solid-state battery. Please refer to Table 1.

[0090] Table 1

[0091]

[0092] Alternatively, the electronic device can calculate the actual contact area ratio using the following formula:

[0093] in, Characterizing the actual contact area ratio, Characterized in Contact area under magnification Characterizing the nominal contact area, and Characterizing the elastic modulus, and Characterizing Poisson's ratio, Characterizing the macroscopic pressure acting on a rough surface, The minimum wave vector represents the maximum length of the corresponding surface, and q represents the wave vector. Power spectral density characterizing surface roughness of rough surfaces; An electrochemical model is constructed using the following formula:

[0094]

[0095] in, Characterizes lithium-ion flux. Characterizing the diffusion coefficient, Characterizing the lithium-ion concentration gradient, Characterizing partial molar volume, Characterizing lithium-ion concentration, The gas constant is represented by T, and the temperature value in the thermal model is represented by T. Characterizing hydrostatic stress in the mechanical model, Characterizing local current density, Characterizing the exchange current density, Characterizing the actual contact area ratio, Characterizing the charge transfer coefficient, Characterizing overpotential, The Faraday constant is represented by k, and the reaction rate constant is represented by k. Characterizing the maximum lithium concentration, Characterizing the lithium concentration on the surface of electrode particles, Characterizes the lithium-ion concentration within the electrolyte. Characterizes the lithium-ion diffusion coefficient within the electrolyte. Characterizes the lithium ion concentration gradient within the electrolyte.

[0096] Alternatively, the electronic device can also construct a thermal model using the following formula:

[0097] in, Characterizing density, Specific heat capacity is represented by T, temperature by K, and thermal conductivity by k. Characterizes the internal heat source of the battery. Characterizing Ohm heat, Characterizing polarization heat, Characterizing reversible heat, Characterizing the heat of side reactions, I characterizes the total current. A represents the local current density, and A represents the local contact area. Characterizing overpotential, U represents the potential gradient, and U represents the voltage.

[0098] Alternatively, the electronic device can also be modeled using the following formula:

[0099] in, E represents the strain in the ij direction, and E represents the elastic modulus. Characterizing the stress in the ij direction, Characterizing Poisson's ratio, Characterizes the volume expansion rate related to lithium-ion concentration. Characterizing the lithium-ion concentration in the electrochemical model, Characterizing the coefficient of thermal expansion, Characterizes the amount of temperature change determined based on the temperature in the thermal model. Characterize the Kronecker function.

[0100] In this formula, the first term The second term is the elastic action term. The third term represents the intercalation stress. This is a term related to thermal stress.

[0101] Next, we will provide a possible approach to perform thermo-mechanical coupling simulation of the charging and discharging process of a battery cell composed of multiple stacked battery cells under target operating conditions, based on the coupling simulation results of the battery cells, to obtain the temperature change of the battery cell.

[0102] Specifically, electronic devices can apply the coupled simulation results of battery cells to a cell structure composed of multiple stacked battery cells through scale expansion. Thermo-mechanical coupling simulation of the cell is performed under target operating conditions to obtain the volume change of the cell. Based on the volume change, the initial volume of the cell, and a preset volume expansion formula, the temperature change of the cell is calculated.

[0103] In this embodiment, the electronic device can first apply the coupling simulation results of the battery cells to a cell structure composed of multiple stacked battery cells through a scale-up method. The cell is formed by stacking multiple battery cells sequentially along the thickness direction, and the stacking method includes, but is not limited to, common configurations such as lamination or winding. Since each battery cell is consistent in material composition, geometry, and operating environment, and undergoes similar electrochemical processes during charging and discharging, it can be reasonably assumed that the electrochemical behavior of the layers other than the first layer is consistent with that of the first layer.

[0104] To reduce computational costs and improve simulation efficiency, electronic devices can use generalized stretching or other spatial mapping methods to copy the electrochemical simulation results of the first layer of battery cells to other corresponding locations, thereby constructing the initial state input of the entire cell and avoiding repeatedly solving the complete electrochemical model for each layer.

[0105] Based on this, a thermo-mechanical coupling simulation of the battery cell was performed under target operating conditions, focusing on analyzing the volume change caused by the combined effects of intercalation stress and thermal expansion. In one example... Figure 5 This is a volumetric strain distribution cloud map of the battery cell obtained through simulation. Figure 6 For the cell volume strain distribution cloud map obtained through simulation, please refer to [link / reference]. Figure 5 , Figure 6 This simulation process is based on the coupled simulation results of the aforementioned battery cells. Key physical quantities such as lithium-ion concentration distribution, heat generation rate, and local strain are extracted as boundary conditions or loads and applied to the multilayer structure model to simulate the temperature evolution and mechanical deformation of the cell during operation. Considering the end constraints and non-ideal contact interfaces in the stacked structure, the actual expansion behavior may exhibit non-uniform characteristics. The simulation can capture such effects and output the overall volume change of the cell.

[0106] Subsequently, equivalent volumetric strain calculations are required. In one example, Figure 7 For an example diagram of equivalent volumetric strain calculation, please refer to [link / reference]. Figure 7 The equivalent calculation of volumetric strain refers to the calculation based on the volume change, the initial volume of the battery cell, and a preset volume expansion formula. By working backward, an equivalent temperature change can be derived. This treatment method combines the combined volume changes caused by electrochemical intercalation expansion and thermal expansion. This is equivalent to a temperature rise caused solely by thermal expansion, allowing the expansion behavior to be expressed as a virtual temperature load. The purpose of this equivalent conversion is to adapt to the data interface requirements of subsequent mechanical simulation software, because in most professional structural mechanics simulation platforms, thermal expansion is one of the main mechanisms causing structural deformation, and directly inputting complex non-thermal source volume changes is usually not feasible.

[0107] Optionally, in the above volume expansion formula, Characterizing the volume change of the battery cell. Characterizing the initial volume of the battery cell, The coefficient of volumetric thermal expansion characterizing the battery cell. It characterizes the amount of temperature change.

[0108] Therefore, this step, through a combination of scale expansion and equivalent transformation, achieves the transfer of physical quantities from the battery cell level to the cellular level. The key to this embodiment lies in using validated cell-level simulation results as a foundation, combined with reasonable simplification assumptions, to significantly reduce computational overhead while maintaining accuracy. Simultaneously, by employing the equivalent temperature rise method, the overall expansion behavior of the cellular cell can be seamlessly imported into the subsequent module-level mechanical simulation process, providing a feasible path for cross-scale, multi-level structural performance prediction.

[0109] The following section uses the simulation process of a solid-state lithium battery module as an example to provide an overall introduction to the simulation method of the solid-state battery module provided in the embodiments of this application.

[0110] In this embodiment, Figure 8 For a simulation flowchart of automotive solid-state lithium batteries, please refer to [link / reference]. Figure 8 Electronic devices can obtain design inputs for automotive solid-state battery modules, including the attribute parameters of battery cells, target operating conditions, and the number of stacked layers of cells. Based on the attribute parameters of the battery cells, electrochemical-thermal-mechanical coupling simulations are performed. Then, the coupling simulation results are stacked and simplified, and thermal-mechanical coupling simulations are performed on the cells. Based on the temperature change obtained from the thermal-mechanical coupling simulations, mechanical simulations are performed on the battery module to obtain mechanical property indicators such as structural strength and pressure uniformity, so as to guide the mechanical structure design of the battery module.

[0111] To perform the corresponding steps in the above embodiments and various possible methods, an implementation of a simulation device for a solid-state battery module is given below. Optionally, the simulation device for the solid-state battery module can adopt the above-described... Figure 1 The device structure of the electronic device is shown. Further, please refer to... Figure 9 , Figure 9 This is a functional block diagram of a simulation device for a solid-state battery module provided in this application embodiment. It should be noted that the basic principle and technical effects of the simulation device for the solid-state battery module provided in this embodiment are the same as those in the above embodiments. For the sake of brevity, any parts not mentioned in this embodiment can be referred to the corresponding content in the above embodiments. The simulation device for the solid-state battery module includes: an acquisition module and a simulation module.

[0112] This acquisition module is used to acquire the property parameters of the battery cell; the property parameters include the structural parameters, electrochemical parameters, thermal parameters and mechanical parameters of the battery cell.

[0113] Understandably, this acquisition module can also be used to perform the above step S20.

[0114] This simulation module is used to perform electrochemical-thermal-mechanical coupling simulation of the charging and discharging process of the battery cell under target operating conditions based on the battery cell's property parameters, and obtain the corresponding coupling simulation results of the battery cell.

[0115] Understandably, this simulation module can also be used to perform the above step S21.

[0116] This simulation module is also used to perform thermo-mechanical coupling simulation of the charging and discharging process of a battery cell composed of multiple battery cells stacked under target operating conditions based on the coupling simulation results of the battery cells, and to obtain the temperature change of the battery cell; the battery cell is composed of multiple battery cells stacked.

[0117] Understandably, this simulation module can also be used to perform the above step S22.

[0118] This simulation module is also used to perform mechanical simulation on a battery module composed of multiple battery cells based on the temperature change of the battery cells, so as to obtain the mechanical characteristics of the battery module under the current structure.

[0119] Understandably, this simulation module can also be used to perform the above step S23.

[0120] Optionally, the simulation module is also used to construct a three-dimensional geometric model of the battery cell based on structural parameters; construct an electrochemical-thermal-mechanical coupling model of the battery cell based on electrochemical parameters, thermal parameters, and mechanical parameters; perform electrochemical-thermal-mechanical coupling simulation on the three-dimensional geometric model of the battery cell under target operating conditions based on the electrochemical-thermal-mechanical coupling model to obtain coupling simulation results; the electrochemical-thermal-mechanical coupling model includes an electrochemical model, a thermal model, and a mechanical model, and the electrochemical model and the thermal model are bidirectionally coupled, the electrochemical model and the mechanical model are bidirectionally coupled, and the thermal model and the mechanical model are unidirectionally coupled.

[0121] Optionally, the simulation module is also used to calculate the actual contact area ratio based on the elastic modulus and Poisson's ratio, and to construct an electrochemical model based on the actual contact area ratio, maximum lithium concentration, diffusion coefficient, charge transfer coefficient, reaction rate constant, temperature value in the thermal model, and net water stress in the mechanical model; to construct a thermal model based on thermal conductivity, specific heat capacity, density, local current density and overpotential in the electrochemical model; and to construct a mechanical model based on the elastic modulus, Poisson's ratio, coefficient of thermal expansion, lithium ion concentration in the electrochemical model, and temperature in the thermal model.

[0122] Optionally, the simulation module is also used to calculate the actual contact area ratio using the following formula:

[0123] in, Characterizing the actual contact area ratio, Characterized in Contact area under magnification Characterizing the nominal contact area, and Characterizing the elastic modulus, and Characterizing Poisson's ratio, Characterizing the macroscopic pressure acting on a rough surface, The minimum wave vector represents the maximum length of the corresponding surface, and q represents the wave vector. Power spectral density characterizing surface roughness of rough surfaces; An electrochemical model is constructed using the following formula:

[0124]

[0125] in, Characterizes lithium-ion flux. Characterizing the diffusion coefficient, Characterizing the lithium-ion concentration gradient, Characterizing partial molar volume, Characterizing lithium-ion concentration, The gas constant is represented by T, and the temperature value in the thermal model is represented by T. Characterizing hydrostatic stress in the mechanical model, Characterizing local current density, Characterizing the exchange current density, Characterizing the actual contact area ratio, Characterizing the charge transfer coefficient, Characterizing overpotential, The Faraday constant is represented by k, and the reaction rate constant is represented by k. Characterizing the maximum lithium concentration, Characterizing the lithium concentration on the surface of electrode particles, Characterizes the lithium-ion concentration within the electrolyte. Characterizes the lithium-ion diffusion coefficient within the electrolyte. Characterizes the lithium ion concentration gradient within the electrolyte.

[0126] Optionally, this simulation module is also used to construct a thermal model using the following formula:

[0127] in, Characterizing density, Specific heat capacity is represented by T, temperature by K, and thermal conductivity by k. Characterizes the internal heat source of the battery. Characterizing Ohm heat, Characterizing polarization heat, Characterizing reversible heat, Characterizing the heat of side reactions, I characterizes the total current. A represents the local current density, and A represents the local contact area. Characterizing overpotential, U represents the potential gradient, and U represents the voltage.

[0128] Optionally, this simulation module is also used to construct a mechanical model using the following formula:

[0129] in, E represents the strain in the ij direction, and E represents the elastic modulus. Characterizing the stress in the ij direction, Characterizing Poisson's ratio, Characterizes the volume expansion rate related to lithium-ion concentration. Characterizing the lithium-ion concentration in the electrochemical model, Characterizing the coefficient of thermal expansion, Characterizes the amount of temperature change determined based on the temperature in the thermal model. Characterize the Kronecker function.

[0130] Optionally, the simulation module is also used to apply the coupled simulation results of the battery cells to the cell structure composed of multiple battery cells stacked by scaling, to perform thermo-mechanical coupling simulation of the cell under target operating conditions, and obtain the volume change of the cell; and to calculate the temperature change of the cell based on the volume change, the initial volume of the cell and the preset volume expansion formula.

[0131] Optionally, the above modules can be stored in the form of software or firmware. Figure 1 The memory shown is either stored in or embedded in the operating system (OS) of the electronic device, and can be used by... Figure 1 The processor executes the commands. Meanwhile, the data and program code required to execute these modules can be stored in memory.

[0132] This application also provides a storage medium storing a computer program thereon, which, when executed by a processor, can implement the simulation method for the solid-state battery module provided in this application.

[0133] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0134] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0135] If a function is implemented as a software module and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part 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 of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0136] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A simulation method for a solid-state battery module, characterized in that, The method includes: Obtain the property parameters of the battery cell; the property parameters include the structural parameters, electrochemical parameters, thermal parameters and mechanical parameters of the battery cell; Based on the attribute parameters of the battery cell, an electrochemical-thermal-mechanical coupled simulation of the charging and discharging process of the battery cell under the target operating conditions is performed to obtain the coupled simulation results corresponding to the battery cell. Based on the coupled simulation results of the battery cells, a thermo-mechanical coupled simulation is performed on the charging and discharging process of a cell composed of multiple stacked battery cells under the target operating condition to obtain the temperature change of the cell; the cell is composed of multiple stacked battery cells. Based on the temperature change of the battery cells, a mechanical simulation is performed on a battery module composed of multiple battery cells to obtain the mechanical characteristics of the battery module under the current structure.

2. The method according to claim 1, characterized in that, The step of performing electrochemical-thermal-mechanical coupled simulation of the charging and discharging process of the battery cell under target operating conditions based on the attribute parameters of the battery cell, and obtaining the coupled simulation results corresponding to the battery cell, includes: Construct a three-dimensional geometric model of the battery cell based on the structural parameters; An electrochemical-thermal-mechanical coupling model of the battery cell is constructed based on the electrochemical parameters, the thermal parameters, and the mechanical parameters. Based on the electrochemical-thermal-mechanical coupling model, an electrochemical-thermal-mechanical coupling simulation is performed on the three-dimensional geometric model of the battery cell under the target operating conditions to obtain the coupling simulation results. The electrochemical-thermal-mechanical coupling model includes an electrochemical model, a thermal model, and a mechanical model. The electrochemical model and the thermal model are bidirectionally coupled, the electrochemical model and the mechanical model are bidirectionally coupled, and the thermal model and the mechanical model are unidirectionally coupled.

3. The method according to claim 2, characterized in that, The electrochemical parameters include maximum lithium concentration, diffusion coefficient, charge transfer coefficient, and reaction rate constant; the thermal parameters include thermal conductivity, specific heat capacity, and density; and the mechanical parameters include elastic modulus, Poisson's ratio, and coefficient of thermal expansion. The construction of the electrochemical-thermal-mechanical coupling model of the battery cell based on the electrochemical parameters, the thermal parameters, and the mechanical parameters includes: The actual contact area ratio is calculated based on the elastic modulus and the Poisson's ratio, and the electrochemical model is constructed based on the actual contact area ratio, the maximum lithium concentration, the diffusion coefficient, the charge transfer coefficient, the reaction rate constant, the temperature value in the thermal model, and the net water stress in the mechanical model. The thermal model is constructed based on the thermal conductivity, specific heat capacity, density, local current density and overpotential in the electrochemical model; The mechanical model is constructed based on the elastic modulus, Poisson's ratio, coefficient of thermal expansion, lithium ion concentration in the electrochemical model, and temperature in the thermal model.

4. The method according to claim 3, characterized in that, The step of calculating the actual contact area ratio based on the elastic modulus and the Poisson's ratio, and constructing the electrochemical model based on the actual contact area ratio, the maximum lithium concentration, the diffusion coefficient, the charge transfer coefficient, the reaction rate constant, the temperature value in the thermal model, and the hydrostatic stress in the mechanical model, includes: The actual contact area ratio is calculated using the following formula: in, Characterizing the actual contact area ratio Characterized in Contact area under magnification Characterizing the nominal contact area, and Characterizing the elastic modulus, and Characterizing the Poisson's ratio, Characterizing the macroscopic pressure acting on a rough surface, The minimum wave vector represents the maximum length of the corresponding surface, and q represents the wave vector. Power spectral density characterizing surface roughness of rough surfaces; The electrochemical model is constructed using the following formula: in, Characterizes lithium-ion flux. Characterizing the diffusion coefficient, Characterizing the lithium-ion concentration gradient, Characterizing partial molar volume, Characterizing lithium-ion concentration, The gas constant is represented by T, and the temperature value in the thermal model is represented by T. Characterizing the hydrostatic stress in the mechanical model, Characterizing local current density, Characterizing the exchange current density, Characterizing the actual contact area ratio Characterizing the charge transfer coefficient, Characterizing overpotential, The Faraday constant is represented by k, and the reaction rate constant is represented by k. Characterizing the maximum lithium concentration, Characterizing the lithium concentration on the surface of electrode particles, Characterizes the lithium-ion concentration within the electrolyte. Characterizes the lithium-ion diffusion coefficient within the electrolyte. Characterizes the lithium ion concentration gradient within the electrolyte.

5. The method according to claim 3, characterized in that, The construction of the thermal model based on the thermal conductivity, specific heat capacity, density, local current density and overpotential in the electrochemical model includes: The thermal model is constructed using the following formula: in, Characterizing the density, The specific heat capacity is represented by T, the temperature by K, and the thermal conductivity by k. Characterizes the internal heat source of the battery. Characterizing Ohm heat, Characterizing polarization heat, Characterizing reversible heat, Characterizing the heat of side reactions, I characterizes the total current. The local current density is represented by A, and the local contact area is represented by A. Characterizing the overpotential, U represents the potential gradient, and U represents the voltage.

6. The method according to claim 3, characterized in that, The mechanical model is constructed based on the elastic modulus, Poisson's ratio, coefficient of thermal expansion, lithium-ion concentration in the electrochemical model, and temperature in the thermal model, including: The mechanical model is constructed using the following formula: in, E represents the strain in the ij direction, and E represents the elastic modulus. Characterizing the stress in the ij direction, Characterizing the Poisson's ratio, Characterizes the volume expansion rate related to lithium-ion concentration. Characterizing the lithium-ion concentration in the electrochemical model, Characterizing the coefficient of thermal expansion, Characterizes the amount of temperature change determined based on the temperature in the aforementioned thermal model. Characterize the Kronecker function.

7. The method according to claim 1, characterized in that, The step of performing a thermo-mechanical coupling simulation on the charging and discharging process of a battery cell composed of multiple stacked battery cells under the target operating condition, based on the coupled simulation results of the battery cells, to obtain the temperature change of the battery cell, includes: The coupled simulation results of the battery cells are applied to the cell structure composed of multiple battery cells stacked by scaling, and the cell is subjected to thermo-mechanical coupling simulation under the target operating condition to obtain the volume change of the cell. The temperature change of the battery cell is calculated based on the volume change, the initial volume of the battery cell, and a preset volume expansion formula.

8. A simulation device for a solid-state battery module, characterized in that, The device includes: The acquisition module is used to acquire the attribute parameters of the battery cell; the attribute parameters include the structural parameters, electrochemical parameters, thermal parameters and mechanical parameters of the battery cell; The simulation module is used to perform electrochemical-thermal-mechanical coupling simulation of the charging and discharging process of the battery cell under the target operating conditions based on the attribute parameters of the battery cell, and obtain the coupling simulation results corresponding to the battery cell. The simulation module is also used to perform thermo-mechanical coupling simulation of the charging and discharging process of a cell composed of multiple stacked battery cells under the target operating condition based on the coupling simulation results of the battery cells, so as to obtain the temperature change of the cell; the cell is composed of multiple stacked battery cells. The simulation module is also used to perform mechanical simulation on a battery module composed of multiple battery cells based on the temperature change of the battery cells, so as to obtain the mechanical characteristics of the battery module under the current structure.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a computer program executable by the processor, the processor being able to execute the computer program to implement the method of any one of claims 1-7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-7.

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