A design system for energy storage battery system, a design method for preparing an energy storage battery system, an energy storage battery system and an electronic device

Abstract

The present invention relates to the field of battery technology, and in particular to a design system for an energy storage battery system, a design method for preparing an energy storage battery system, an energy storage battery system, and an electronic device. The energy storage battery design system includes an input module, a database module, and a design module; after the design module receives the target performance parameters input by the input module, the data information in the database module is calculated to obtain the initial preparation parameters of the energy storage battery system for reference in the subsequent battery system preparation, and the initial preparation parameters include the material parameters and process parameters of the initial preparation of the energy storage battery system. The design system of the energy storage battery system is based on the target performance parameters of the energy storage battery system to be prepared provided by the user. The design module iterates the model design parameters through an automated program to better obtain accurate initial preparation parameters, better assist the research on the energy storage battery system, speed up the research and development speed, and also improve the performance of the energy storage battery system obtained by research and development.

Description

Technical field

[0002] The present invention relates to the field of battery technology, and in particular to a design system for an energy storage battery system, a design method for preparing an energy storage battery system, an energy storage battery system, and an electronic device. [Background Technology]

[0004] With the advancement of battery technology, particularly lithium-ion battery technology, energy storage battery systems are rapidly developing and being applied in a variety of fields, including consumer electronics, smart homes, electric vehicles, unmanned vehicles, general aviation, large-scale energy storage, and medical equipment. In existing energy storage battery system development, battery design often relies on researchers adjusting formulas and process parameters based on experience, or typically requires researchers to apply specific mathematical models based on experience to achieve the desired design. Due to the lack of precise theoretical tools to guide accurate design, this design approach is time-consuming, labor-intensive, and highly uncertain. The digital simulation and precise design of energy storage battery systems aims to build digital models of energy materials, processes, devices, systems, and equipment through the integration of battery mechanisms, battery data, and artificial intelligence algorithms, establish a precise mapping relationship between digital space and physical space, and use data flow to drive workflows to achieve digital simulation of the entire process of energy product research and development, manufacturing, and application, as well as digital iterative optimization of the entire chain of energy material-device-system product design, process development, and application evaluation, to achieve independent design and independent performance iteration of battery systems, break through the bottleneck problem of existing design tools that mainly rely on trial and error and can only meet single-function design requirements, such as EDA software, and break through the bottleneck problem of materials, devices, and systems in the advanced energy field. [Summary of the invention]

[0006] To overcome the shortcomings of current lithium battery design tools that mainly rely on trial and error testing and have a long development cycle, the present invention provides a design system for an energy storage battery system, a design method for preparing an energy storage battery system, an energy storage battery system, and an electronic device.

[0007] To solve the above-mentioned technical problems, the present invention provides a technical solution as follows: a design system for an energy storage battery system, comprising an input module, a database module, and a design module; the database module pre-stores data information related to the preparation of the energy storage battery system; the input module is used to input target performance parameters of the energy storage battery system; after receiving the target performance parameters, the design module calculates based on the data information in the database module to obtain initial preparation parameters of the energy storage battery system for reference in subsequent battery system preparation, wherein the initial preparation parameters include material parameters, structural parameters, and process parameters of the energy storage battery system.

[0008] Preferably, the design system of the energy storage battery system also includes a material design module and an output module associated with the design module; the specific steps for the design module to calculate and obtain the preparation parameters are as follows: determine whether the initial battery system performance parameters of the energy storage battery system are equivalent to the target performance parameters, and if so, the output module outputs the initial preparation parameters for reference in subsequent battery system preparation; if not, execute the following steps: the material design module designs new materials and new structures based on the target performance parameters and obtains new data information, and the design module calls the new data information to calculate until the initial battery system performance parameters are equivalent to the target performance parameters, and further the output module outputs the initial preparation parameters for reference in subsequent battery system preparation.

[0009] Preferably, the database module is also used to store new data information obtained based on the design of the material design module.

[0010] Preferably, the data information and the new data information are at least one of the data information about the material type, material properties and process parameters for preparing the energy storage battery system; the database module includes one or more of an atomic scale database, a molecular scale database, an electrode scale database, a cell scale database, a module scale database and a system scale database; and the at least one data information is stored in a corresponding database according to different scale ranges, constituent elements, physical properties and geometric space representations of each constituent element.

[0011] Preferably, the atomic scale database includes at least one material among lithium ions, positive electrode active material atoms, negative electrode active material atoms, electrolyte atoms and / or at least one of the thermodynamic properties, atomic transport properties, lattice parameters, and energy level parameters of the material in one-dimensional, two-dimensional, and three-dimensional space; the molecular scale database includes at least one of the positive electrode active material, negative electrode active material, electrolyte material, and packaging material and / or at least one of the solid-phase ion diffusion characteristics, interface properties, structural stability, particle deformation, and fatigue resistance of the material in one-dimensional, two-dimensional, and three-dimensional space; the electrode scale database includes at least one of the types and ratios of positive electrode materials, types and ratios of negative electrode materials, types and ratios of electrolyte materials, and / or the material's effects on charge transport and leveling. The cell-scale database includes the structure-activity relationship of the battery potential distribution, current distribution, heat distribution and pressure distribution among several of the positive electrode structure, negative electrode structure, diaphragm structure, electrolyte type, tab, shell and insulating pad and / or these structures; the module-scale database includes the structure-activity relationship of the single battery, wiring harness, shell, structural parts, battery management system, cooling and heating system and / or these structures or systems with potential distribution, current distribution, heat distribution and safety management strategy; the system-scale database includes the structure-activity relationship of the battery module, wiring harness, shell, structural parts, battery management system and / or these structures or systems with potential distribution, current distribution, heat distribution, safety management strategy and control strategy.

[0012] Preferably, the design module includes one or more of an electrode model, an electrolyte model, a diaphragm model, an interface model, a connection model, a cell model, a switch model, a control model, a current collector model, and a shell model; according to the type of target performance parameters, the design module selects one or more of the models for calculation to obtain the initial preparation parameters of the energy storage battery system.

[0013] Preferably, the design module also includes an instrument model library, which stores at least one instrument model, and the instrument model is an equipment model for controlling process parameters related to the preparation of the energy storage battery system; the design module selects one or several models and combines them with at least one instrument model to calculate to obtain the initial preparation parameters of the energy storage battery system.

[0014] Preferably, the design system of the energy storage battery system further includes a geometric space establishment module, which is associated with the design module or the output module, and establishes a 3D model of the energy storage battery system based on the preparation parameters to achieve visualization.

[0015] Preferably, the design system of the energy storage battery system further includes a parameter configuration module; before the design module selects one or several models and calculates in combination with at least one instrument model to obtain the preparation parameters of the energy storage battery system, the boundary constraint conditions of the energy storage battery system to be prepared are input into the design module through the parameter configuration module.

[0016] Preferably, the design system of the energy storage battery system further includes a parameter configuration module; before the design module selects one or several models and calculates in combination with at least one instrument model to obtain the preparation parameters of the energy storage battery system, the boundary constraint conditions of the energy storage battery system to be prepared are input into the design module through the parameter configuration module.

[0017] In order to solve the above technical problems, a design method for preparing an energy storage battery system is also provided, which inputs the target performance parameters of the energy storage battery system; after receiving the target performance parameters, a method is called to calculate based on the pre-stored data information in the database module to obtain the initial preparation parameters of the energy storage battery system for reference in subsequent battery preparation, and the initial preparation parameters include material parameters, structural parameters, and process parameters of the energy storage battery system.

[0018] Preferably, it also includes the step of designing new materials and new structures, wherein calling the data information in the pre-stored database to calculate and obtain the initial preparation parameters specifically includes the following steps: judging whether the initial battery system performance parameters of the energy storage battery system are equivalent to the target performance parameters, and if so, outputting the initial preparation parameters for reference in subsequent battery preparation; if not, executing the following steps: designing new materials and new structures based on the target performance parameters and obtaining new data information, and the design module calling the new data information to calculate until the initial battery system performance parameters are equivalent to the target performance parameters, and further outputting the initial preparation parameters for reference in subsequent battery preparation and storing the new data information in the database.

[0019] Preferably, it further includes establishing a database, which is used to pre-store data information about the preparation of the energy storage battery system. The steps of establishing the database are as follows: first, providing the types of materials for preparing the energy storage battery system within the range of atomic scale, molecular scale, electrode scale, battery cell scale, module scale, and system scale; establishing an atomic scale database, a molecular scale database, an electrode scale database, a battery cell scale database, a module scale database, and a system scale database, and storing the types of materials for preparing the energy storage battery system in corresponding databases according to different scale ranges, constituent elements, physical properties, and the geometric space representation of each constituent element; performing instrument measurement, simulation calculation, and literature review on the data of the materials stored in the corresponding database in different dimensions, scales, and physical fields.

[0020] In order to solve the above technical problems, the present invention also provides an energy storage battery system, which is prepared by the design system of the energy storage battery system as described above and / or prepared by the design method for preparing the energy storage battery system as described above.

[0021] In order to solve the above technical problems, the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-mentioned design method for preparing an energy storage battery system based on the above-mentioned design system of the energy storage battery system through the computer program.

[0022] Compared with the prior art, the present invention provides a design system for an energy storage battery system, a design method for preparing an energy storage battery system, an energy storage battery system, and an electronic device, which have the following beneficial effects:

[0023] A design system for an energy storage battery system includes an input module, a database module, and a design module. The database module pre-stores data information related to the preparation of the energy storage battery system. The input module is used to input target performance parameters of the energy storage battery system. After receiving the target performance parameters, the design module calculates, based on the data information in the database module, initial preparation parameters of the energy storage battery system for reference in subsequent battery preparation. The initial preparation parameters include material parameters and process parameters of the energy storage battery system. The design system for the energy storage battery system is based on the target performance parameters of the energy storage battery system to be prepared, provided by a user. The design module iterates model design parameters through an automated program, tests the performance parameters of the battery model, and selects initial preparation parameters with better target performance parameters. Utilizing artificial intelligence technology, the design module learns from the operating data of existing battery systems and establishes a black box model with the target performance parameters of the energy storage battery system to be prepared as the target. This allows the simulation process to simulate physical phenomena close to those of a real energy storage battery system, supporting simulation operations in complex situations, and better obtaining accurate initial preparation parameters. This helps better assist in energy storage battery research, accelerates R&D, and also improves the performance of the developed energy storage battery system. The system further includes a material design module, which effectively avoids the lack of comprehensiveness of data in the current database module by expanding the data information in the database and improving the comprehensiveness of the data. The database module is divided into multiple databases of different scales, which can effectively select the data in the corresponding scale database according to the category of the input target performance parameters for calculation to obtain more accurate initial preparation parameters. The design module is configured to include multiple different types of models, which can effectively select the corresponding model according to the category of the input target performance parameters and calculate with the input target performance parameters to obtain more accurate initial preparation parameters.

Brief Description of the Drawings

[0024] Figure 1 1 is a schematic diagram of a module of a design system for an energy storage battery system provided in a first embodiment of the present invention;

[0025] Figure 2 is a module diagram of a design system for an energy storage battery system provided in a modified embodiment of the first embodiment of the present invention;

[0026] Figure 3 Schematic diagram of a database at different scales in a database module of a design system for an energy storage battery system according to a first embodiment of the present invention;

[0027] Figure 4 is another module schematic diagram of the design system of the energy storage battery system according to the first embodiment of the present invention;

[0028] Figure 5 1. It is a schematic diagram of a model library of a simulation module in a design system for an energy storage battery system according to a first embodiment of the present invention;

[0029] Figure 6 This is a schematic diagram of an instrument model library in a simulation module in a design system for an energy storage battery system according to a first embodiment of the present invention;

[0030] Figure 7 Schematic diagram of a module when the design system of the energy storage battery structure system according to the first embodiment of the present invention further includes a geometric space establishment module;

[0031] Figure 8 When the energy storage battery system to be prepared is a cell structure, a specific module diagram of the design system of the energy storage battery system;

[0032] Figure 9 It is another specific module schematic diagram of the design system of the energy storage battery system when the energy storage battery system to be prepared is a cell structure;

[0033] Figure 10 A schematic diagram of a specific module for further utilizing geometric space to establish a module based on the obtained initial preparation parameters to realize 3D modeling;

[0034] Figure 11 A schematic diagram of a specific module for further utilizing geometric space to establish a module based on the obtained 3D model to realize 3D modeling;

[0035] Figure 12 is a flow chart of a design method for preparing an energy storage battery system provided in a second embodiment of the present invention;

[0036] Figure 13It is a structural diagram of a computer system of a server provided by the present invention that is suitable for implementing an embodiment of the present invention.

[0037] Description of reference numerals:

[0038] 10. Design system for energy storage battery system; 101. Input module; 102. Database module; 1021. Atomic scale database; 1022. Molecular scale database; 1023. Electrode scale database; 1024. Cell scale database; 1025. Module scale database; 1026. System scale database; 1027. Performance test module; 103. Design module; 1030. Simulation module; 1031. Electrode model; 1032. Electrolyte model; 1033. Diaphragm model; 1034. Interface model; 1035. Connection model; 1036. Cell model; 1037. Switch model; 1038. Control model; 1039. Current collector model; 1040. Housing model; 104. Material design module; 105. Geometric space establishment module; 106. Parameter configuration module; 107. Instrument model library; 1071. Power supply model; 1072. Conductivity meter model; 107 3. Load model; 1074. Impedance meter model; 1075. Voltmeter model; 1076. Thermometer model; 1077. Amperemeter model; 1078. Ion concentration meter model; 1079. Capacitance meter model; 108. Output module; 109. Numerical visualization module; 201. Copper foil 3D model; 202. Negative electrode material 3D model; 203. Separator material 3D model; 204. Bonding 3D model; 205. Positive electrode material 3D model; 206. 3D model of electrolyte material; 207. 3D model of shell; 301. Multi-field physical model library; 3011. Multi-field physical model of copper foil; 3012. Multi-field physical model of negative electrode material; 3013. Multi-field physical model of diaphragm material; 3014. Multi-field physical model of bonding; 3015. Multi-field physical model of positive electrode material; 3016. Multi-field physical model of electrolyte material; 3017. Multi-field physical model of shell; 3018. Multi-field physical simulation software. [Specific implementation method]

[0040] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0041] See also Figure 1A first embodiment of the present invention provides a design system 10 for an energy storage battery system, which is used to design an energy storage battery system to be prepared, thereby obtaining preparation parameters for preparing the energy storage battery system. The system includes an input module 101, a database module 102, and a design module 103, wherein the input module 101 is associated with the design module 103, and the design module 103 is associated with the database module 102.

[0042] The database module 102 pre-stores data information related to the preparation of the energy storage battery system;

[0043] The input module 101 is used to input target performance parameters of the energy storage battery system;

[0044] After receiving the target performance parameters, the design module 103 calculates based on the data information in the database module 102 to obtain the initial preparation parameters of the energy storage battery system for reference in subsequent battery preparation. The initial preparation parameters include material parameters, structural parameters and process parameters of the energy storage battery system.

[0045] Here, it should be noted that based on the obtained initial preparation parameters, an energy storage battery system corresponding to the target performance parameters can be prepared. At this time, the obtained initial preparation parameters can be further sent to the user. It is also possible that there is a large gap between the initial battery system performance parameters of the energy storage battery system prepared by the obtained initial preparation parameters and the target performance parameters, that is, there is a mismatch, indicating that the design module 103 cannot obtain the initial preparation parameters corresponding to the target performance parameters based on the data information in the current database module 102. At this time, the design module 103 needs to recalculate. In some specific embodiments, a threshold can be set to determine whether the initial battery system performance parameters and the target performance parameters match. For example, a threshold is 2-6. When the difference between the initial battery system performance parameters and the target performance parameters is less than the set threshold, it is considered to be matched. If it is greater than the set threshold, it is considered to be mismatched.

[0046] To resolve this issue, see Figure 2 , the energy storage battery system design system 10 further includes a material design module 104 and an output module 108 associated with the design module 103;

[0047] The specific steps of the design module 103 calculating and obtaining the preparation parameters are as follows:

[0048] Determine whether the initial battery system performance parameters of the energy storage battery system are equivalent to the target performance parameters,

[0049] If yes, the output module 108 outputs the initial preparation parameters for reference in subsequent battery preparation;

[0050] If not, perform the following steps:

[0051] The design module 103 sends a signal to the material design module 104, and the material design module 104 designs new materials and new structures based on the target performance parameters and obtains new data information. The design module 103 calls the new data information to calculate until the initial battery system performance parameters are equivalent to the target performance parameters, and the output module 108 further outputs the initial preparation parameters for reference in subsequent battery preparation.

[0052] When material design module 104 designs a new material or structure, it stores the corresponding new data in database module 102 for easy access by design module 103. Material design module 104 primarily utilizes machine learning based on the preparation parameters of existing energy storage battery products, battery performance, or other parameters to establish an artificial intelligence-based material design module 104.

[0053] In some specific embodiments, the energy storage battery system includes any one or more of an electrode structure, a battery cell structure, a battery cell, a battery system, or other battery structures.

[0054] The target performance parameters of energy storage battery systems include charge rate coefficient, discharge rate coefficient, cycle life, safety performance, storage performance at a certain ambient temperature, power, internal resistance, and other parameters that characterize battery performance. Each type of energy storage battery system corresponds to different target performance parameters.

[0055] Usually, as a user developing an energy storage battery system, based on the customer's product needs, you first know what target performance parameters of the energy storage battery system are needed, and then accurately develop the required energy storage battery system according to the user's needs.

[0056] The data information is at least one of the data information about the initial material type, material properties, process parameters and other parameters for preparing the energy storage battery system; or it also includes device structure parameters, such as structural parameters of the shell, structural parameters of the electrode structure, structural parameters of the battery cell structure and other structural data information; or it also includes battery cell static performance parameters, battery cell service condition parameters, battery module static performance parameters, battery module service condition parameters, battery system static performance parameters, battery system operating condition parameters and other battery component performance parameters or service condition parameters and other information.

[0057] Furthermore, the aforementioned data information typically exhibits different properties at one or more scales, such as different spatial and temporal scales. For example, the chemical properties of an active material used to prepare an electrode structure may change over time as the battery is used, or at different operating temperatures. These different data, arising from different spatial and temporal environments, should be collected and stored in the database module 102 to maximize the enrichment of the data information and form a multi-dimensional database.

[0058] It should also be noted that the characteristic data of relevant data information under different physical fields will also be different, thus providing different data information. Some commonly used physical fields include one or a combination of more than one of chemistry, electrochemistry, electricity, optics, acoustics, mechanics, and thermal. For example, the activity of an active material used to prepare an electrode structure will inevitably be different under chemical fields or electrochemical fields. Therefore, we need to collect data information of this type under different physical fields at the same time.

[0059] Therefore, see Figure 3 In some specific embodiments, the database module 102 is divided into one or more of an atomic scale database 1021, a molecular scale database 1022, an electrode scale database 1023, a cell scale database 1024, a module scale database 1025, and a system scale database 1026. At least one piece of data information is stored in a corresponding database according to different scale ranges, dimensions, components, physical field properties, and geometric spatial representations of each component, so that the design module 103 can select the data information in the corresponding database to calculate and obtain initial preparation parameters based on the type of energy storage battery system to be prepared.

[0060] Optionally, in some specific embodiments, the atomic scale database 1021 includes at least one material selected from the group consisting of lithium ions, positive electrode active material atoms, negative electrode active material atoms, and electrolyte atoms, and / or at least one of the material's thermodynamic properties, atomic transport properties, lattice parameters, and energy level parameters in one-dimensional, two-dimensional, or three-dimensional space.

[0061] The molecular scale database 1022 includes at least one of positive electrode active materials, negative electrode active materials, electrolyte materials, and packaging materials, and / or at least one of the solid-phase ion diffusion characteristics, interface properties, structural stability, particle deformation, and fatigue resistance of the material in one-dimensional, two-dimensional, or three-dimensional space;

[0062] The electrode dimension database 1023 includes at least one of the types and proportions of positive electrode materials, negative electrode materials, and electrolyte materials, and / or data on the effects of the materials on charge transfer and balance, and ion transfer and balance.

[0063] The cell dimension database 1024 includes several of the positive electrode structure, negative electrode structure, separator structure, electrolyte type, tab, shell, insulating pad, and / or the structure-activity relationship of battery potential distribution, current distribution, heat distribution, and pressure distribution among these structures.

[0064] The module scale database 1025 includes several of the single cells, wiring harnesses, housings, structural parts, battery management systems, cooling and heating systems and / or the structure-function relationship between these structures or systems and potential distribution, current distribution, heat distribution, and safety management strategies.

[0065] The system scale database 1026 includes several of the battery modules, wiring harnesses, housings, structural parts, battery management systems, and / or the structure-performance relationships between these structures or systems and potential distribution, current distribution, thermal distribution, safety management strategies, and control strategies.

[0066] In some specific embodiments, the database module 102 can be built on a computer device with a memory, a computing unit, and a user interface, which can implement data writing and flexible call. Optionally, a relational or non-relational database can be used as the architecture of the database module 102.

[0067] See also Figure 3 As an option, in order to make each database of different scales more convenient for users to query or manage, the database module 102 is further configured with the following modules:

[0068] Data usage query module: This module is used to query according to predetermined conditions and keywords, or to filter what kind of data exists in the database of the corresponding scale according to preset conditions.

[0069] Data interface and calling module: Through this module, you can select the data information in the corresponding scale database according to the type of energy storage battery system.

[0070] User information management module: This module is specifically used to manage user information, such as the user's name, the user's product category, or some special needs of the user for the product and other customer information.

[0071] Process Information Management Module: This module manages the process information associated with the corresponding dimension database. This facilitates accurate access by the design module 103 and avoids storing different types of data in the same dimension database, which can cause confusion during access due to different storage formats. Specific processes may include homogenization, coating, drying, rolling, tableting, assembly, liquid injection, formation, aging, packaging, and volume fractionation.

[0072] Material information management module: This module manages the material information involved in the corresponding scale database, such as positive electrode materials, negative electrode materials, electrolyte materials, diaphragm materials, packaging materials, etc.

[0073] Management formula information module: This module includes formula information such as positive electrode formula data, negative electrode formula data, electrolyte formula data, and diaphragm parameter data.

[0074] Management system performance information module: such as static electrical performance, safety performance information, operating performance information, etc. of the battery system.

[0075] In some other embodiments, modules such as an electrical performance information management module and a module performance information management module may also be included.

[0076] See also Figure 4 In some specific embodiments, the design module 103 is associated with the input module 101, and the design module 103 includes a simulation module 1030 and a performance testing module 1027. The simulation module 1030 is associated with the performance testing module 1027, and the simulation module 1030 is associated with the input module 101, the output module 108, the material design module 104, and the database module 102. After receiving the target performance parameters, the simulation module 1030 retrieves the data information in the database module 102 and calculates to obtain the initial preparation parameters of the energy storage battery system. During the calculation process, the simulation module 1030 iteratively obtains multiple sets of initial preparation parameters for the target performance parameters through an automated program, and further measures the battery performance parameters of the energy storage battery system obtained by simulating each set of initial preparation parameters by the performance testing module 1027. A set of initial preparation parameters whose battery performance parameters are equivalent to the target performance parameters is selected as the preparation parameters of the energy storage battery system for reference in subsequent battery preparation.

[0077] When the simulation module 1030 selects the data information in the database module 102, the data information in the database of the corresponding scale is selected based on the type of the target performance parameter to perform calculations to obtain the corresponding energy storage battery system. For example, when the input target performance parameter is a parameter about the cell structure, the corresponding initial battery system is the cell structure, and the cell structure usually includes a positive electrode structure, an electrolyte structure, and a negative electrode structure. At this time, after the simulation module 1030 receives the target performance parameter, it is necessary to call the data information in the atomic scale database 1021, the data information in the molecular scale database 1022, the data information in the electrode scale database 1023, and the data information in the cell scale database 1024 to respectively prepare the positive electrode structure, the electrolyte structure, the negative electrode structure, and complete the combination of the three to obtain a series of initial preparation parameters for preparing the energy storage battery system.

[0078] It can also be done in the following way: if the target performance parameter already has a positive electrode structure that matches it, there is no need to call the corresponding data calculation to obtain the parameters for preparing the positive electrode structure. The historical positive electrode structure initial preparation parameters can be used. At this time, the simulation module 1030 only needs to calculate and obtain the corresponding initial preparation parameters for the negative electrode structure, electrolyte structure and the combination of the three.

[0079] It should also be noted that, for example, when preparing a positive electrode structure, there may be multiple suitable materials, and different preparation processes are then matched to different materials. Therefore, after calculation by the simulation module 1030, multiple sets of initial preparation parameters are usually obtained. Further, based on the performance testing module, a preferred set of initial preparation parameters is obtained and provided as a reference for subsequent battery preparation. In this context, the preferred initial preparation parameters can be understood as the optimal performance of the prepared energy storage battery system, or the most favorable production conditions for the customer.

[0080] In some specific embodiments, simulation module 1030 includes a mechanism model and a machine learning model. Optionally, the mechanism model is one or a combination of chemical, electrical, optical, acoustic, mechanical, or thermal models corresponding to at least one of the data information regarding the material type, material properties, and process parameters for manufacturing the energy storage battery system. The mechanism model is used to generate simulation data from the at least one data information, thereby performing model training to obtain a machine learning model. Specifically, simulation module 1030 needs to automatically iterate based on the mechanism model and the machine learning model to obtain multiple sets of preparation parameters related to the target performance parameters.

[0081] In some specific embodiments, the simulation module 1030 can also utilize numerical simulation software developed by existing developers, such as a multi-scale, multi-domain mathematical model developed by NREL. This model uses a scalable, modular, and flexible structure and efficient calculation method. This model analyzes the battery geometry into three coupled calculation domains; specifically, the model is divided into the following three categories:

[0082] 1) Particle Domain Model (PDM), used to address the collective response of electrically and ionically connected batteries; 2) Electrode Domain Model (EDM), used to address the collective behavior of particle domain (PD) batteries; 3) Cell Domain Model (CDM), used to address the response of single or multi-cell batteries. The greatest contribution of this model is that it provides explicit connections between multiple cross-scale physics fields, including battery charging / discharging processes, thermal control, safety, and reliability. The interaction between these physics fields can be directly observed and can be used to design electrodes and electrode materials.

[0083] In the present invention, based on a multi-scale and multi-domain mathematical model developed by NREL, the simulation module 1030 is further divided into the following models: including one or more of the electrode model 1031, the electrolyte model 1032, the diaphragm model 1033, the interface model 1034, the connection model 1035, the cell model 1036, the switch model 1037, the control model 1038, the current collector model 1039, and the shell model 1040.

[0084] According to the type of target performance parameter, the simulation module 1030 selects one or several models to perform calculations to obtain the initial preparation parameters of the energy storage battery system. For example, when the input target performance parameter is a parameter about the cell structure, the corresponding initial battery system is a cell structure, and the cell structure usually includes a positive electrode structure, an electrolyte structure, and a negative electrode structure. At this time, after the simulation module 1030 receives the target performance parameter, it is necessary to call the data information in the atomic scale database 1021, the data information in the molecular scale database 1022, the data information in the electrode scale database 1023, and the data information in the cell scale database 1024 to respectively call the electrode model 1031, the electrolyte model 1032, the interface model 1034, and the cell model 1036 to respectively prepare the positive electrode structure, the negative electrode structure, the electrolyte structure, and complete the combination of the three to obtain a series of initial preparation parameters for preparing the energy storage battery system.

[0085] See also Figure 6 The design module 103 also includes an instrument model library 107, which stores at least one instrument model. Each instrument model is an equipment model for controlling process parameters related to manufacturing an energy storage battery system. The simulation module 1030 selects one or more of these models and combines them with the at least one instrument model to calculate and obtain initial manufacturing parameters for the energy storage battery system.

[0086] See also Figure 6 The specific instrument model library 107 includes a power supply model 1071, a conductivity meter model 1072, a load model 1073, an impedance meter model 1074, a voltmeter model 1075, a thermometer model 1076, an ammeter model 1077, an ion concentration meter model 1078, and a capacitance meter model 1079.

[0087] See also Figure 7 The energy storage battery system design system 10 further includes a geometric space establishment module 105, which is associated with the design module 103 or the output module 108 and establishes a 3D model of the energy storage battery system based on the preparation parameters for visualization. This facilitates the user to manufacture the energy storage battery or optimize the process based on the 3D model of the energy storage battery system.

[0088] In some specific embodiments, the design system 10 of the energy storage battery system further includes a parameter configuration module 106; before the design module 103 selects one or several models and calculates in combination with at least one instrument model to obtain the preparation parameters of the energy storage battery system, the boundary constraint conditions of the energy storage battery to be prepared are input into the design module 103 through the parameter configuration module 106.

[0089] The following provides two different types of energy storage battery system design system 10 module structure association diagrams. Figure 8 Figure 1 is a schematic diagram of a design system 10 for an energy storage battery system, when the energy storage battery system to be manufactured is a cell structure. Parameter configuration module 106 inputs the corresponding parameters into simulation module 1030. Simultaneously, target performance parameters are input into simulation module 1030 via input module 101. Simulation module 1030 further calculates and combines the instrument model to obtain initial preparation parameters, which are then output.

[0090] See also Figure 9 In order to conveniently display the initial preparation parameters on an electronic display for easy viewing and modification by the user, a numerical visualization module 109 is further configured to visualize the initial preparation parameters calculated by the simulation module 1030. At this time, the output module 108 outputs the data information of the initial preparation parameters.

[0091] Please see further Figure 10 To further visualize the preparation of the energy storage battery system, the geometric space establishment module 105 is further coordinated to create a 3D model of the energy storage battery system. Specifically, based on the initial preparation parameters, the corresponding copper foil 3D model 201, negative electrode material 3D model 202, separator material 3D model 203, bonding material 3D model 204, positive electrode material 3D model 205, electrolyte material 3D model 206, and housing 3D model 207 are established. These models can also be assigned to component models in the design module 103.

[0092] The initial preparation parameters output by the output module 108 are input into the corresponding 3D model to achieve 3D structuring of the corresponding battery system. For example, the 3D simulated structure of the copper foil is obtained from the copper foil 3D model 201, the 3D simulated structure of the negative electrode material is obtained from the negative electrode material 3D model 202, the 3D simulated structure of the diaphragm material is obtained from the 3D model of the diaphragm material, the 3D simulated structure of the bonding layer is obtained from the bonding 3D model 204, the 3D simulated structure of the positive electrode material is obtained from the positive electrode material 3D model 205, the 3D simulated structure of the electrolyte is obtained from the 3D model of the electrolyte material 3D model 206, and the 3D simulated structure of the shell is obtained from the shell 3D model 207. After obtaining the 3D simulated structures of these structural components, the 3D virtual structures of these structural components are further constructed into a 3D stereoscopic structure of the energy storage battery system by the geometric space establishment module 105 and visualized. The 3D model of the energy storage battery system can be further output by the output module 108 to allow the user to better adjust the preparation parameters during the preparation process.

[0093] Furthermore, to better obtain accurate initial preparation parameters, the design module 103 further includes a multi-field physics model library 301, which contains multi-field physics models corresponding to various components of the energy storage battery system. For example, these include: a copper foil multi-field physics model 3011, a negative electrode material multi-field physics model 3012, a separator material multi-field physics model 3013, a bonding multi-field physics model 3014, a positive electrode material multi-field physics model 3015, an electrolyte material multi-field physics model 3016, and a casing multi-field physics model 3017. The multi-field physics models are associated with the output module 108 or the geometric space establishment module 105. These multi-field physics models are used to simulate multi-field data of the 3D model obtained by the geometric space establishment module 105. Specifically, the output 3D model is input into the multi-field physics model library 301, parameterized by the parameter configuration module 106, and then simulated by the multi-field physics simulation software 3018 to obtain multi-field physics property parameters of the 3D model. Finally, the output is provided to battery system developers for reference.

[0094] See also Figure 12 The second embodiment of the present invention provides a design method for preparing an energy storage battery system, which is characterized by comprising the following steps:

[0095] S1. Pre-establish a database, in which data information related to the preparation of the energy storage battery system is pre-stored;

[0096] S2. Input target performance parameters of the energy storage battery system;

[0097] S3. After receiving the target performance parameters, the initial preparation parameters of the energy storage battery system are calculated based on the data information in the database module for reference in subsequent battery preparation. The initial preparation parameters include material parameters and process parameters of the energy storage battery system.

[0098] In step S1 , the data information in the database module is the same as that in the first embodiment and will not be described again.

[0099] In step S2, the target performance parameters are input through the input module;

[0100] In step S3, the design module in the first embodiment is used to implement the process, and the specific implementation will not be described in detail here.

[0101] The method also includes the steps of designing new materials and new structures, wherein the calculation based on the data information in the database module to obtain initial preparation parameters specifically includes the following steps:

[0102] Determine whether the initial battery system performance parameters of the energy storage battery system are equivalent to the target performance parameters,

[0103] If yes, the initial preparation parameters are output for reference in subsequent battery preparation;

[0104] If not, perform the following steps:

[0105] Based on the target performance parameters, new materials and new structures are designed and new data information is obtained. The design module calls the new data information to calculate until the initial battery system performance parameters are equivalent to the target performance parameters, and further outputs the initial preparation parameters for reference in subsequent battery preparation.

[0106] The steps to create a database are as follows:

[0107] First, provide the types of materials used to prepare energy storage battery systems within the scope of atomic scale, molecular scale, electrode scale, cell scale, module scale, and system scale;

[0108] Establish atomic scale database, molecular scale database, electrode scale database, cell scale database, module scale database, and system scale database, and store the types of materials used to prepare energy storage battery systems in corresponding databases according to different scale ranges, components, physical properties, and geometric spatial representations of each component;

[0109] Data information about the materials is obtained by performing instrument measurements, simulation calculations, and literature review on the data of materials in different dimensions, scales, and physical fields stored in the corresponding database.

[0110] A third embodiment of the present invention provides an energy storage battery system, which is prepared by the energy storage battery system design system 10 provided in the first embodiment and / or prepared by the energy storage battery system design method provided in the second embodiment.

[0111] A fourth embodiment of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute a design method for preparing an energy storage battery system based on a design system for the energy storage battery system through the computer program.

[0112] Reference below Figure 13 , which shows a structural diagram of a computer system 800 of a terminal device / server suitable for implementing an embodiment of the present application. Figure 13 The terminal device / server shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0113] like Figure 13 As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage unit 808 into a random access memory (RAM) 803. Various programs and data required for the operation of the system 800 are also stored in the RAM 803. The CPU 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0114] The following components are connected to the I / O interface 805: an input section 806 including a keyboard, a mouse, and the like; an output section 807 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 808 including a hard disk; and a communication section 809 including a network interface card such as a LAN card or a modem. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 810 as needed, so that computer programs read therefrom can be installed into the storage section 808 as needed.

[0115] According to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit (CPU) 801, the above-mentioned functions defined in the method of the present application are executed. It should be noted that the computer-readable medium described in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0116] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as the "Like" language or similar programming languages. The program code may be executed entirely on the management computer, partially on the management computer, as a stand-alone software package, partially on the management computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the management computer through any type of network, including a local area network (LAN) or wide area network (WAN) domain, or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0117] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0118] Compared with the prior art, the present invention provides a design system for an energy storage battery system, a design method for preparing an energy storage battery system, an energy storage battery system, and an electronic device, which have the following beneficial effects:

[0119] 1. A design system for an energy storage battery system, comprising an input module, a database module, and a design module; the database module pre-stores data information related to the preparation of the energy storage battery system; the input module receives target performance parameters of the energy storage battery system and calculates, based on the data in the database module, initial preparation parameters for the energy storage battery system for reference in subsequent battery preparation. The initial preparation parameters include material parameters and process parameters of the energy storage battery system. The design system for the energy storage battery system is based on the target performance parameters of the energy storage battery system to be prepared, provided by a user. The design module iterates model design parameters through an automated program, tests the performance parameters of the battery model, and selects initial preparation parameters with optimal target performance parameters. Utilizing artificial intelligence technology, the design module learns from the operating data of existing battery systems and establishes a black box model with the target performance parameters of the energy storage battery system to be prepared as the target. This allows the simulation process to simulate physical phenomena that closely resemble those of a real energy storage battery system, supporting simulation operations in complex situations, and more accurately obtaining initial preparation parameters. This helps improve research on energy storage batteries, accelerates R&D, and also enhances the performance of the resulting energy storage battery system.

[0120] 2. It further includes a material design module, which can effectively avoid the situation where the data in the current database module is less comprehensive, expand the data information in the database, and improve the comprehensiveness of the data.

[0121] 3. Dividing the database module into multiple databases of different scales can well select the data in the corresponding scale database according to the category of the input target performance parameters for calculation to obtain more accurate initial preparation parameters.

[0122] 4. The design module is set to include a variety of different types of models, which can well select the corresponding model according to the category of the input target performance parameters and calculate with the input target performance parameters to obtain more accurate initial preparation parameters.

[0123] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A design system for an energy storage battery system, characterized in that: Includes input module, database module and design module; The database module pre-stores data information related to the design of the energy storage battery system; The input module is used to input target performance parameters of the energy storage battery system; After receiving the target performance parameters, the design module calculates based on the data information in the database module to obtain initial preparation parameters of the energy storage battery system for reference in subsequent battery system preparation, wherein the initial preparation parameters include material parameters, structural parameters, and process parameters of the energy storage battery system; The design system of the energy storage battery system also includes a material design module and an output module associated with the design module; The specific steps of calculating the design module to obtain the preparation parameters are as follows: Determine whether the initial battery system performance parameters of the energy storage battery system model are equivalent to the target performance parameters, If yes, the output module outputs the initial preparation parameters for reference in subsequent battery system preparation; If not, perform the following steps: The material design module designs new materials and new structures based on the target performance parameters and obtains new data information, and the design module calls the new data information to calculate until the initial battery system performance parameters are equivalent to the target performance parameters, and the output module further outputs the initial preparation parameters for reference in subsequent battery system preparation.

2. The design system of the energy storage battery system according to claim 1, characterized in that: The database module is also used to store new data information obtained based on the design of the material design module.

3. The design system of the energy storage battery system according to claim 1, characterized in that: The data information and the new data information are at least one of the data information on the material type, material properties, and process parameters for preparing the energy storage battery system; The database module includes one or more of an atomic scale database, a molecular scale database, an electrode scale database, a battery cell scale database, a module scale database, and a system scale database; At least one data information is stored in a corresponding database according to different scale ranges, constituent elements, physical properties and geometric space expressions of each constituent element.

4. The design system of the energy storage battery system according to claim 3, characterized in that: The atomic scale database includes at least one material of lithium ions, positive electrode active material atoms, negative electrode active material atoms, electrolyte atoms, and / or at least one of the thermodynamic properties, atomic transport properties, lattice parameters, and energy level parameters of the material in one-dimensional, two-dimensional, or three-dimensional space; The molecular scale database includes at least one of positive electrode active materials, negative electrode active materials, electrolyte materials, packaging materials and / or at least one of the solid phase ion diffusion characteristics, interface properties, structural stability, particle deformation and fatigue resistance of the material in one-dimensional, two-dimensional and three-dimensional space; The electrode dimension database includes at least one of the types and proportions of positive electrode materials, negative electrode materials, and electrolyte materials, and / or the influence data of the materials on charge transfer and balance, and ion transfer and balance; The cell scale database includes the structure-activity relationship of battery potential distribution, current distribution, heat distribution, and pressure distribution among several of the positive electrode structure, negative electrode structure, diaphragm structure, electrolyte type, tab, shell, and insulating pad, and / or these structures; The module scale database includes several of the single cells, wiring harnesses, housings, structural parts, battery management systems, cooling and heating systems, and / or the structure-function relationships of these structures or systems with potential distribution, current distribution, heat distribution, and safety management strategies; The system scale database includes battery modules, wiring harnesses, housings, structural parts, battery management systems, and / or the structure-function relationships of these structures or systems with potential distribution, current distribution, heat distribution, safety management strategies, and control strategies.

5. The design system of the energy storage battery system according to any one of claims 1 to 4, characterized in that: The design module includes one or more of an electrode model, an electrolyte model, a diaphragm model, an interface model, a connection model, a cell model, a switch model, a control model, a current collector model, and a housing model; According to the type of target performance parameter, the design module selects one or several models to perform calculations to obtain the initial preparation parameters of the energy storage battery system.

6. The design system of the energy storage battery system according to claim 5, characterized in that: The design module also includes an instrument model library, in which at least one instrument model is stored, and the instrument model is an equipment model for controlling process parameters related to the structure of the energy storage battery system; The design module selects one or several models and combines them with at least one instrument model to calculate and obtain the initial preparation parameters of the energy storage system.

7. The design system of the energy storage battery system according to claim 6, characterized in that: The design system of the energy storage battery system also includes a geometric space establishment module, which is associated with the design module or the output module, and establishes a 3D model of the energy storage battery system based on the preparation parameters to achieve visualization.

8. The design system of the energy storage battery system according to claim 7, characterized in that: The design system of the energy storage battery system also includes a multi-field physical model and multi-field physical simulation software for the energy storage battery system. The multi-field physical model is associated with the geometric space establishment module or the output module. The 3D model is input into the multi-field physical model and further combined with the multi-field physical simulation software for simulation processing to obtain multi-field physical performance parameters of the energy storage battery system for use as a reference for subsequent battery system preparation.

9. The design system of the energy storage battery system according to claim 6, characterized in that: The design system of the energy storage battery system also includes a parameter configuration module; Before the design module selects one or several models and combines them with at least one instrument model to calculate to obtain the preparation parameters of the energy storage battery system, the boundary constraint conditions of the energy storage battery system to be prepared are input into the design module, the geometric space establishment module or the multi-field physical simulation software through the parameter configuration module.

10. A design method for preparing an energy storage battery system, characterized in that: The steps include: Input target performance parameters of the energy storage battery system; After receiving the target performance parameters, the data information in the pre-stored database module is called to calculate to obtain the initial preparation parameters of the energy storage battery system for reference in subsequent battery system preparation, wherein the initial preparation parameters include material parameters, structural parameters, and process parameters of the energy storage battery system; The method also includes the steps of designing new materials and new structures, wherein the method of calling the data information in the pre-stored database module to calculate and obtain the initial preparation parameters specifically includes the following steps: determining whether the initial battery system performance parameters of the energy storage battery system are equivalent to the target performance parameters, If yes, the initial preparation parameters are output for reference in subsequent battery system preparation; If not, perform the following steps: Based on the target performance parameters, new materials and new structures are designed and new data information is obtained, and the new data information is called to calculate until the initial battery system performance parameters are equivalent to the target performance parameters, and the initial preparation parameters are further output for reference in subsequent battery system preparation and the new data information is stored in a database.

11. The design method for preparing an energy storage battery system according to claim 10, characterized in that: The method further includes establishing a database, the database is used to pre-store data information about the preparation of the energy storage battery system, and the steps of establishing the database are as follows: First, provide the types of materials used to prepare energy storage battery systems within the range of atomic scale, molecular scale, electrode scale, cell scale, module scale, and system scale; Establish atomic scale database, molecular scale database, electrode scale database, cell scale database, module scale database, and system scale database, and store the types of materials used to prepare energy storage battery systems in the corresponding databases according to different scale ranges, constituent elements, physical properties, and the geometric spatial representation of each constituent element; Data information about the materials is obtained by performing instrument measurements, simulation calculations, and literature review on the data of materials in different dimensions, scales, and physical fields stored in the corresponding database.

12. An energy storage battery system, characterized in that: The method is obtained by using a design system for an energy storage battery system as described in any one of claims 1 to 9 and / or by using a design method for preparing an energy storage battery system as described in any one of claims 10 to 11.

13. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the design method for preparing an energy storage battery system as described in any one of claims 10-11 based on the design system for the energy storage battery system as described in any one of claims 1-9 through the computer program.

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