Battery simulation calculation method, device, computer equipment and storage medium

Abstract

The present application relates to a battery simulation calculation method, device, computer device, storage medium, and computer program product. The method includes obtaining a battery simulation scenario; selecting a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario; obtaining historical battery information of an adjacent time step corresponding to the current time step, inputting the historical battery information into the solid-liquid phase diffusion model for calculation to obtain a current diffusion concentration value at the current time step; and inputting the current diffusion concentration value into the electron transport model for calculation to obtain electrical state information at the current time step. The entire solution performs battery simulation calculation according to the solid-liquid phase diffusion model and the electron transport model corresponding to the battery simulation requirement data, can expand the application scenarios of the battery simulation model, and can realize the calculation of the battery state for different battery application scenarios, improving the flexibility of the calculation of the battery state information.

Description

Technical Field

[0001] The present application relates to the field of battery simulation, and particularly to a battery simulation calculation method, device, computer device, storage medium, and computer program product. Background Art

[0002] Batteries represented by lithium-ion batteries have been widely used as energy storage carriers, such as mobile phones, laptops, medical devices, electric vehicles, energy storage power stations, signal base stations, etc. In order to ensure the safe and efficient operation of the battery, a battery management system (BMS) is generally equipped to manage the battery, such as state estimation, fault diagnosis, and charge equalization.

[0003] Currently, many BMSs adopt model-based control technologies, which require the establishment of a simulation model for the controlled battery. However, most battery simulation models can only be applied to specific scenarios. When performing simulation calculations based on the battery simulation model in a fixed scenario, the obtained battery state information can only be applicable to the current application scenario, and it is impossible to flexibly perform battery simulation calculations for different battery application scenarios to obtain battery state information. Summary of the Invention

[0004] In view of the above problems, the present application provides a battery simulation calculation method, device, computer device, storage medium, and computer program product, which can solve the problem that battery simulation calculations cannot adapt to different battery application scenarios, resulting in inflexible calculation of battery state information, and improve the flexibility of calculating battery state information.

[0005] In a first aspect, the present application provides a battery simulation calculation method, including:

[0006] Obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario;

[0007] Obtain historical battery information of adjacent time steps corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value of the current time step;

[0008] Input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information of the current time step.

[0009] The above battery simulation calculation method performs simulation calculations on the battery through a solid-liquid phase diffusion model and an electron transport model, determines the solid-liquid phase diffusion model and the electron transport model based on the battery simulation scenario, and performs battery simulation calculations according to the solid-liquid phase diffusion model and the electron transport model corresponding to the battery simulation scenario. This can expand the application scenarios of the battery simulation model, enable the calculation of the battery state for different battery application scenarios, and improve the flexibility of calculating battery state information.

[0010] In one embodiment, selecting the solid-liquid phase diffusion model and the electron transport model for battery simulation calculations according to the battery simulation scenario includes:

[0011] According to the battery simulation scenario, select the target solid-liquid phase diffusion model for battery simulation calculations from a plurality of preset solid-liquid phase diffusion models, and select the target electron transport model for battery simulation calculations from a plurality of preset electron transport models.

[0012] In the above embodiment, determining the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models based on the battery simulation scenario, and determining the target electron transport model from a plurality of electron transport models, and performing battery simulation calculations according to the target solid-liquid phase diffusion model and the target electron transport model corresponding to the battery simulation scenario can accurately select the corresponding target solid-liquid phase diffusion model and the target electron transport model according to the battery simulation scenario, expand the application scenarios of the battery simulation model, enable the calculation of the battery state for different battery application scenarios, and improve the flexibility of calculating battery state information.

[0013] In one embodiment, selecting the target solid-liquid phase diffusion model for battery simulation calculations from a plurality of preset solid-liquid phase diffusion models according to the battery simulation scenario, and selecting the target electron transport model for battery simulation calculations from a plurality of preset electron transport models includes:

[0014] According to the battery simulation scenario, determine the simulation requirements;

[0015] According to the simulation requirements, select the target solid-liquid phase diffusion model for battery simulation calculations from a plurality of preset solid-liquid phase diffusion models, and select the target electron transport model for battery simulation calculations from a plurality of preset electron transport models.

[0016] In the above embodiment, by determining the simulation requirements of the battery simulation scenario, determining the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models based on the simulation requirements, and determining the target electron transport model from a plurality of electron transport models, and performing battery simulation calculations according to the target solid-liquid phase diffusion model and the target electron transport model corresponding to the simulation requirements, the battery state information that meets the battery simulation scenario can be obtained, and the flexibility of calculating battery state information is improved.

[0017] In one embodiment, according to the simulation requirements, selecting the target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting the target electron transport model for battery simulation calculation from a plurality of preset electron transport models includes:

[0018] When the simulation requirement is a high-precision simulation requirement, select the diffusion equation model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models as the target solid-liquid phase diffusion model, and select the charge transfer model for battery simulation calculation from a plurality of preset electron transport models as the target electron transport model.

[0019] In the above embodiment, by selecting the diffusion equation model and the charge transfer model according to the high-precision simulation requirements, the battery state information can be accurately calculated.

[0020] In one embodiment, obtaining the historical battery information of the adjacent time step corresponding to the current time step, and inputting the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step includes:

[0021] Obtain the historical battery information of the adjacent time step corresponding to the current time step, and input the historical battery information into the diffusion equation model for calculation to obtain the diffusion concentration value of the current time step; wherein, the diffusion equation model calculates the diffusion concentration based on Fick's law;

[0022] Inputting the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information of the current time step includes:

[0023] Obtain the historical electrical state information of the adjacent time step corresponding to the current time step, and input the historical electrical state information and the current diffusion concentration value into the charge transfer model for calculation to obtain the electrical state information of the current time step; wherein, the charge transfer model calculates the electrical state information based on Ohm's law and Kirchhoff's law.

[0024] In the above embodiment, according to the high-precision simulation requirements, the accuracy of concentration calculation can be improved by calculating the diffusion concentration based on Fick's law, and the accuracy of electrical state information calculation can be improved by calculating the electrical state information based on Ohm's law and Kirchhoff's law, thereby improving the battery simulation accuracy.

[0025] In one embodiment, according to the simulation requirements, selecting the target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting the target electron transport model for battery simulation calculation from a plurality of preset electron transport models includes:

[0026] In the case where the simulation requirement is a high-efficiency simulation requirement, among a plurality of preset solid-liquid phase diffusion models, the polynomial fitting model for battery simulation calculation is selected as the target solid-liquid phase diffusion model, and among a plurality of preset electron transport models, the transmission line model for battery simulation calculation is selected as the target electron transport model.

[0027] In the above implementation, selecting the polynomial fitting model and the transmission line model for battery simulation according to the high-efficiency simulation requirement can improve the calculation speed of battery state information.

[0028] In one of the embodiments, obtaining the historical battery information of the adjacent time step corresponding to the current time step, and inputting the historical battery information into the solid-liquid phase diffusion model for calculation, the current diffusion concentration value of the current time step is obtained, including:

[0029] Obtaining the historical battery information of the adjacent time step corresponding to the current time step, and based on polynomial fitting, inputting the historical battery information into the polynomial fitting model for calculation to obtain the diffusion concentration value of the current time step;

[0030] Inputting the current diffusion concentration value into the electron transport model for calculation, the electrical state information of the current time step is obtained, including:

[0031] Obtaining the historical electrical state information of the adjacent time step corresponding to the current time step, and inputting the historical electrical state information and the current diffusion concentration value into the transmission line model for calculation to obtain the electrical state information of the current time step; wherein, the transmission line model calculates the electrical state information based on the equivalent circuit principle of the transmission line.

[0032] In the above embodiments, according to the high-efficiency simulation requirement, calculating the diffusion concentration through the polynomial fitting model can improve the rate of concentration calculation, and calculating the electrical state information based on the equivalent circuit principle of the transmission line can improve the rate of electrical state information calculation, thereby improving the battery simulation efficiency.

[0033] In one of the embodiments, obtaining the historical battery information of the adjacent time step corresponding to the current time step, and inputting the historical battery information into the solid-liquid phase diffusion model for calculation, the current diffusion concentration value of the current time step is obtained, including:

[0034] Obtaining the historical diffusion concentration value of the adjacent time step corresponding to the current time step, and inputting the historical diffusion concentration value into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step.

[0035] In the above embodiments, based on the solid-liquid phase diffusion model, and calculating the current diffusion concentration value of the current time step according to the historical diffusion concentration value and the historical surface current density, the battery change process can be accurately simulated, and the current diffusion concentration value can be calculated quickly and accurately.

[0036] In one embodiment, the current diffusion concentration value is input into the electron transport model for calculation, and the electrical state information at the current time step obtained includes:

[0037] Obtain the historical electrical state information of the adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information at the current time step.

[0038] In the above embodiment, based on the electron transport model and according to the historical electrical state information and the current diffusion concentration value, the electrical state information at the current time step is calculated, which can accurately simulate the battery change process and quickly and accurately calculate the electrical state information at the current time step.

[0039] In a second aspect, the present application provides a battery simulation calculation device, including:

[0040] A selection module for obtaining a battery simulation scenario and selecting a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario;

[0041] A concentration calculation module for obtaining the historical battery information of the adjacent time step corresponding to the current time step, inputting the historical battery information into the solid-liquid phase diffusion model for calculation, and obtaining the current diffusion concentration value at the current time step;

[0042] An electrical information calculation module for inputting the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

[0043] In a third aspect, the present application provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0044] Obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario;

[0045] Obtain the historical battery information of the adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value at the current time step;

[0046] Input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

[0047] In a fourth aspect, the present application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0048] Obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario;

[0049] Obtain historical battery information of an adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value at the current time step;

[0050] Input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

[0051] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0052] Obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario;

[0053] Obtain historical battery information of an adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value at the current time step;

[0054] Input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

[0055] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically listed below.

[0056] For the above battery simulation calculation method, device, computer device, storage medium and computer program product, a battery simulation scenario is obtained, and a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation are selected according to the battery simulation scenario; historical battery information of an adjacent time step corresponding to the current time step is obtained, and the historical battery information is input into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step; the current diffusion concentration value is input into the electron transport model for calculation to obtain the electrical state information at the current time step. The entire solution performs simulation calculation on the battery through the solid-liquid phase diffusion model and the electron transport model, determines the solid-liquid phase diffusion model and the electron transport model based on the battery simulation scenario, and performs battery simulation calculation according to the solid-liquid phase diffusion model and the electron transport model corresponding to the battery simulation scenario, which can expand the application scenario of the battery simulation model, and can realize the calculation of the battery state for different battery application scenarios, improving the flexibility of the calculation of the battery state information. Description of the Drawings

[0057] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The accompanying drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present application. Moreover, in all the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0058] Figure 1 It is an application environment diagram of a battery simulation calculation method according to an embodiment of the present application;

[0059] Figure 2 It is a schematic flowchart of a battery simulation calculation method according to an embodiment of the present application;

[0060] Figure 3 It is a schematic flowchart of the process of determining a battery simulation calculation model according to an embodiment of the present application;

[0061] Figure 4 It is a schematic flowchart of a battery simulation calculation method according to another embodiment of the present application;

[0062] Figure 5 It is a schematic flowchart of a battery simulation calculation method according to still another embodiment of the present application;

[0063] Figure 6 It is a schematic flowchart of a battery simulation calculation method according to still another embodiment of the present application;

[0064] Figure 7 It is a structural block diagram of a battery simulation calculation device according to an embodiment of the present application;

[0065] Figure 8 It is an internal structure diagram of a computer device according to an embodiment of the present application. Detailed Embodiments

[0066] The following will describe in detail the embodiments of the technical solutions of the present application with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application and are therefore only examples and cannot be used to limit the protection scope of the present application.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion.

[0068] In the description of the embodiments of the present application, technical terms such as "first" and "second" are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity, specific order or primary-secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "a plurality of" is more than two, unless otherwise clearly and specifically defined.

[0069] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0070] In the description of the embodiments of the present application, the term "and / or" is merely a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0071] In the description of the embodiments of the present application, the term "a plurality of" refers to more than two (including two). Similarly, "a plurality of groups" refers to more than two groups (including two groups), and "a plurality of sheets" refers to more than two sheets (including two sheets).

[0072] Since the invention of lithium-ion batteries, people have been committed to developing simulation models of lithium-ion batteries. The pseudo-two-dimensional (P2D) model is established based on the porous electrode theory and the concentrated solution theory, and uses one dimension in the thickness direction of a battery electrode and an additional dimension (pseudo-dimension) in the radial direction of a solid-phase particle assumed to be spherical to describe the behavior of the battery. The classical P2D model mainly includes five parts:

[0073] Use Fick's diffusion law to describe the solid-phase lithium-ion concentration in spherical particles;

[0074] Use diffusion and electromigration to describe the lithium-ion concentration in the electrolyte and separator;

[0075] Use Ohm's law to describe the solid-phase potential in the electrode;

[0076] Use Ohm's law and Kirchhoff's law to describe the liquid-phase potential in the electrolyte and separator;

[0077] Use the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface.

[0078] Since it was proposed in 1993, the P2D model has undergone decades of testing and verification and has now become one of the important models for lithium-ion battery simulation. However, the form of the control equations of the P2D model is complex and no complete analytical solution can be obtained. Only numerical methods can be used for solving, such as the finite difference method and the finite volume method, etc. The calculation consumption is large and the single calculation time is long, which limits its application in many scenarios, such as scenarios that require large-scale calculations like life prediction and tolerance prediction, and scenarios with limited computing power like in-vehicle BMS (Battery Management System).

[0079] Currently, there have been many attempts to simplify the P2D model in order to obtain a model that can describe the behavior of lithium-ion batteries more concisely, quickly, and accurately. However, there is currently no model that can meet all requirements. Among them, the relatively well-known one is the Single Particle Model (SPM), that is, regarding the electrode as a single particle and completely ignoring the changes in the concentration and potential of the electrolyte. This treatment simplifies the calculation to a large extent. However, since the properties of the electrolyte are completely ignored, it is difficult for this method and its derivative models to accurately calculate the charge and discharge at high rates, and it is also unable to provide a relatively complete description of the internal mechanism of the battery. In addition, the RC (Resistor-Capacitor) equivalent circuit model commonly used in the BMS system also has the advantages of extremely fast calculation speed and low calculation consumption. However, since its parameters are completely obtained by fitting and almost completely ignore the physical meaning, it cannot be used for the research on the specific physical processes and mechanisms of the battery.

[0080] In addition, there have also been attempts to simplify some processes of the P2D model. For example, using polynomial fitting to obtain the solid-liquid phase concentration and replacing the original diffusion process described by Fick's law can greatly improve the calculation speed, but the accuracy is low, the application range is narrow, it cannot adapt to complex working conditions such as variable current, and it does not include the complete physical meaning, which affects the research on the internal mechanism. In addition, there is also a model that uses the transmission line equivalent circuit model to describe the electron transport process and replaces the original solid-liquid phase potential calculation method. This equivalent circuit largely guarantees the physical meaning, and the simplification of the original solid-liquid phase potential calculation method also improves the calculation speed to a certain extent. However, this simplification will also affect the calculation accuracy and stability. For example, when the current is extremely small, extremely large resistance values may occur, which will affect subsequent calculations and other situations.

[0081] Based on the above considerations, in order to solve the problem that the current battery simulation calculation cannot adapt to different application scenarios, resulting in inflexible calculation of battery state information, the applicant has conducted in-depth research and provided a battery simulation calculation method, device, computer device, storage medium, and computer program product. The method includes obtaining a battery simulation scenario, selecting a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario; obtaining historical battery information of adjacent time steps corresponding to the current time step, inputting the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step; and inputting the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

[0082] The above battery simulation calculation method performs simulation calculation on the battery through the solid-liquid phase diffusion model and the electron transport model, determines the solid-liquid phase diffusion model and the electron transport model based on the battery simulation scenario, and performs battery simulation calculation according to the solid-liquid phase diffusion model and the electron transport model corresponding to the battery simulation scenario. This can expand the application scenarios of the battery simulation model, enable the calculation of battery states for different battery application scenarios, and improve the flexibility of calculating battery state information.

[0083] The battery simulation calculation method provided by this application can be applied to an application environment as Figure 1 shown. Among them, user 102 operates on terminal 104. User 102 inputs a battery simulation scenario on the display interface of terminal 104, and terminal 104 obtains the battery simulation scenario; according to the battery simulation scenario, selects a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation; obtains historical battery information of adjacent time steps corresponding to the current time step, inputs the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step; and inputs the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step. Among them, terminal 104 can be, but is not limited to, various personal computers, laptop computers, smartphones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc.

[0084] In one embodiment, as Figure 2 shown, a battery simulation calculation method is provided. Taking the method applied to terminal 104 in Figure 1 as an example, the method includes the following steps:

[0085] Step 202, obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario.

[0086] Among them, the battery simulation scenario refers to the application scenario of the battery. The application scenario includes batteries under different working conditions and different uses of the battery. Batteries under different working conditions include batteries of different sizes, different charging rates, different physical property parameters, and different electrochemical parameters, etc. Batteries of different sizes include square batteries and cylindrical batteries, etc. Different uses of the battery include battery life prediction scenarios, variable current charging scenarios, constant current charging scenarios, and lithium plating process scenarios, etc. The simulation requirements for batteries in different application scenarios are different. Therefore, it is necessary to select a simulation model corresponding to the battery simulation scenario to calculate the battery state information. The battery simulation requirements include physical simulation accuracy requirements and simulation efficiency requirements. The higher the physical simulation accuracy requirements, the more accurate the battery state data obtained by simulation calculation. And the higher the simulation efficiency requirements, the faster the simulation calculation process and the higher the efficiency of obtaining the battery state data.

[0087] In this embodiment, the battery simulation calculation process is divided into the calculation of the solid-liquid phase diffusion process and the calculation of the electron transport process. The solid-liquid phase diffusion model is used to calculate the change in the solid-phase concentration and the liquid-phase concentration of lithium ions during the battery simulation process. The electron transport model is used to calculate the electrical state information such as current, voltage, and resistance of the solid phase and the liquid phase of lithium ions during the battery simulation process. The solid-liquid phase diffusion model includes a diffusion equation model, a polynomial fitting model, and other models that can realize the calculation of the change in the solid-phase concentration and the liquid-phase concentration of lithium ions, such as the full homogenization model, etc. Other calculation models for realizing the change in the solid-phase concentration and the liquid-phase concentration of lithium ions are not limited in this embodiment. New calculation models can be added according to the simulation requirements of the battery simulation scenario to improve the diversity of the battery simulation scenario and the flexibility of the battery state information calculation. In this embodiment, the calculation of the change in the solid-phase concentration and the liquid-phase concentration of lithium ions is taken as an example to be explained by using the diffusion equation model and the polynomial fitting model. The change in the solid-phase concentration and the liquid-phase concentration of lithium ions can be calculated by the diffusion equation model or the polynomial fitting model. The electron transport model includes a charge transfer model, a transmission line model, and other models that can realize the calculation of the electrical state information such as current, voltage, and resistance of the solid phase and the liquid phase of lithium ions. Other calculation models for realizing the electrical state information such as current, voltage, and resistance of the solid phase and the liquid phase of lithium ions are not limited in this embodiment. New calculation models can be added according to the simulation requirements of the battery simulation scenario to improve the diversity of the battery simulation scenario and the flexibility of the battery state information calculation. In this embodiment, the calculation of the electrical state information such as current, voltage, and resistance of the solid phase and the liquid phase of lithium ions is taken as an example to be explained by using the charge transfer model or the transmission line model. The electrical state information such as current, voltage, and resistance of the solid phase and the liquid phase of lithium ions can be calculated by the charge transfer model or the transmission line model.

[0088] Specifically, the user sends a battery simulation request to the terminal. The battery simulation request carries a battery simulation scenario, simulation requirements corresponding to the battery simulation scenario, and simulation data. The terminal listens for and responds to the battery simulation instruction, parses the battery simulation request, and obtains the battery simulation scenario and the simulation requirements corresponding to the battery simulation scenario.

[0089] The simulation data refers to the actual operating condition parameters of the battery, including the operating condition, external environmental temperature, battery current value, battery state of charge, battery health state, and curve parameters of the charging rate at different times, etc. The simulation data is used for subsequent simulation calculations of the battery.

[0090] The user can also directly send a battery simulation request carrying the battery simulation scenario to the terminal. The terminal listens for and responds to the battery simulation request, parses the battery simulation request, and obtains the battery simulation scenario. Further, each battery simulation scenario has a unique scenario identifier, different battery simulation scenarios correspond to different scenario identifiers, and the corresponding relationship between the battery simulation scenario and the simulation requirements is stored in the data storage system of the terminal. The data storage system can be integrated on the server, or placed in the cloud or other network servers. The terminal determines the scenario identifier according to the battery application scenario, queries the simulation data corresponding to the scenario identifier in the corresponding relationship between the battery simulation scenario and the simulation requirements, and obtains the simulation requirements for this battery simulation. Then, the terminal selects a solid-liquid phase diffusion model and an electron transport model corresponding to the simulation requirements of the battery simulation scenario according to the simulation requirements of the battery simulation scenario.

[0091] Step 204: Obtain the historical battery information of the adjacent time step corresponding to the current time step, and input the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step.

[0092] Wherein, the current time step refers to the timing information of the current battery simulation calculation, that is, the round information of this round of battery simulation. The adjacent time step corresponding to the current time step refers to the previous time step, that is, the round information of the previous round of battery simulation. The historical battery information includes the historical diffusion concentration value and the historical electrical state information. The diffusion concentration value includes the solid-phase diffusion concentration and the liquid-phase diffusion concentration.

[0093] Specifically, the terminal obtains the historical battery information of the previous time step corresponding to the current time step. Obtain the battery information required for solid-liquid phase concentration calculation from the historical battery information and the simulation data, and input the battery information required for solid-liquid phase concentration calculation into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the battery at the current time step.

[0094] Step 206: Input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

[0095] Specifically, the terminal calculates the required battery information from the historical battery information and the electrical state in the simulation data, inputs the calculated current diffusion concentration value and the battery information required for the electrical state calculation into the electron transport model for calculation, obtains the electrical state information of the battery at the current time step, and can output the electrical state information at the current time step and the current diffusion concentration value according to the user application requirements.

[0096] In the above battery simulation calculation method, a battery simulation scenario is obtained; according to the battery simulation scenario, a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation are selected; historical battery information corresponding to the current time step is obtained, and the historical battery information is input into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step; the current diffusion concentration value is input into the electron transport model for calculation to obtain the electrical state information at the current time step. The entire solution performs simulation calculations on the battery through the solid-liquid phase diffusion model and the electron transport model, determines the solid-liquid phase diffusion model and the electron transport model based on the battery simulation scenario, and performs battery simulation calculations according to the solid-liquid phase diffusion model and the electron transport model corresponding to the battery simulation scenario, which can expand the application scenarios of the battery simulation model, and can calculate the battery state for different battery application scenarios, improving the flexibility of the calculation of the battery state information.

[0097] In an optional embodiment, selecting a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario includes:

[0098] According to the battery simulation scenario, a target solid-liquid phase diffusion model for battery simulation calculation is selected from a plurality of preset solid-liquid phase diffusion models, and a target electron transport model for battery simulation calculation is selected from a plurality of preset electron transport models.

[0099] Among them, the solid-liquid phase diffusion model is used to calculate the changes in the solid-phase concentration and the liquid-phase concentration of lithium ions during the battery simulation process. The plurality of preset solid-liquid phase diffusion models include a diffusion equation model, a polynomial fitting model, and other models that can implement the calculation of the changes in the solid-phase concentration and the liquid-phase concentration of lithium ions, such as a full homogenization model, etc.

[0100] The electron transport model is used to calculate the electrical state information such as the current, voltage, and resistance of the solid phase and the liquid phase of lithium ions during the battery simulation process. The electron transport model includes a charge transfer model, a transmission line model, and other models that can implement the calculation of the electrical state information such as the current, voltage, and resistance of the solid phase and the liquid phase of lithium ions.

[0101] Specifically, according to the simulation requirements of the battery simulation scenario, the terminal selects a solid-liquid phase diffusion model corresponding to the simulation requirements of the battery simulation scenario from a preset diffusion equation model and a polynomial fitting model to obtain a target solid-liquid phase diffusion model, and selects an electron transport model corresponding to the simulation requirements of the battery simulation scenario from a preset charge transfer model and a transmission line model to obtain a target electron transport model.

[0102] In this embodiment, based on the battery simulation scenario, a target solid-liquid phase diffusion model is determined from a preset plurality of solid-liquid phase diffusion models, and a target electron transport model is determined from a plurality of electron transport models. Battery simulation calculations are performed according to the target solid-liquid phase diffusion model and the target electron transport model corresponding to the battery simulation scenario. The corresponding target solid-liquid phase diffusion model and the target electron transport model can be accurately selected according to the battery simulation scenario, the application scenario of the battery simulation model is extended, and the calculation of the battery state can be realized for different battery application scenarios, improving the flexibility of the calculation of the battery state information.

[0103] In an alternative embodiment, as Figure 3 shown, selecting a target solid-liquid phase diffusion model for battery simulation calculation from a preset plurality of solid-liquid phase diffusion models according to the battery simulation scenario, and selecting a target electron transport model for battery simulation calculation from a preset plurality of electron transport models includes:

[0104] Step 302, determine the simulation requirements according to the battery simulation scenario.

[0105] Among them, the simulation requirements include physical simulation accuracy requirements and simulation efficiency requirements. The higher the physical simulation accuracy requirement, the higher the accuracy of the battery state information obtained by battery simulation. The higher the simulation efficiency requirement, the faster the speed of obtaining the battery state information by battery simulation.

[0106] Specifically, the terminal determines the simulation requirements according to the corresponding relationship between the battery simulation scenario and the simulation requirements stored locally according to the battery simulation scenario.

[0107] Step 304, select a target solid-liquid phase diffusion model for battery simulation calculation from a preset plurality of solid-liquid phase diffusion models according to the simulation requirements, and select a target electron transport model for battery simulation calculation from a preset plurality of electron transport models.

[0108] Specifically, according to the simulation requirements of the battery simulation scenario, the terminal selects a solid-liquid phase diffusion model corresponding to the simulation requirements of the battery simulation scenario from a preset diffusion equation model and a polynomial fitting model to obtain a target solid-liquid phase diffusion model, and selects an electron transport model corresponding to the simulation requirements of the battery simulation scenario from a preset charge transfer model and a transmission line model to obtain a target electron transport model.

[0109] In this embodiment, by determining the simulation requirements of the battery simulation scenario, the target solid-liquid phase diffusion model is determined from a plurality of preset solid-liquid phase diffusion models, and the target electron transport model is determined from a plurality of electron transport models. According to the target solid-liquid phase diffusion model and the target electron transport model corresponding to the simulation requirements, battery simulation calculations are performed, and the battery state information that meets the battery simulation scenario can be obtained, improving the flexibility of the calculation of the battery state information.

[0110] In an alternative embodiment, according to the simulation requirements, selecting the target solid-liquid phase diffusion model for battery simulation calculations from a plurality of preset solid-liquid phase diffusion models, and selecting the target electron transport model for battery simulation calculations from a plurality of preset electron transport models includes:

[0111] In the case where the simulation requirements are high-precision simulation requirements, select the diffusion equation model for battery simulation calculations from a plurality of preset solid-liquid phase diffusion models as the target solid-liquid phase diffusion model, and select the charge transfer model for battery simulation calculations from a plurality of preset electron transport models as the target electron transport model.

[0112] Among them, the diffusion equation model is the model for calculating the solid-liquid phase concentration of lithium ions in the P2D model. The charge transfer model is the model for calculating the electrical state information in the P2D model.

[0113] Specifically, the terminal compares the physical simulation accuracy requirement with a preset accuracy threshold, and compares the simulation efficiency requirement with a preset efficiency threshold. If the physical simulation accuracy requirement is greater than or equal to the preset accuracy threshold, the simulation requirements for this battery simulation scenario are high-precision simulation requirements. Then, determine the diffusion equation model as the target solid-liquid phase diffusion model from a plurality of solid-liquid phase diffusion models, and select the charge transfer model for battery simulation calculations from a plurality of preset electron transport models as the target electron transport model.

[0114] If the battery simulation scenario is a high-precision physical simulation requirement and a high-efficiency simulation requirement, then determine the target solid-liquid phase diffusion model as the diffusion equation model, and determine the target electron transport model as the transmission line model, or determine the target solid-liquid phase diffusion model as the polynomial fitting model, and determine the target electron transport model as the charge transfer model.

[0115] In this implementation, selecting the diffusion equation model and the charge transfer model according to the high-precision simulation requirements for battery simulation can accurately calculate the battery state information.

[0116] In an alternative embodiment, as Figure 4 shown, obtaining the historical battery information of the adjacent time step corresponding to the current time step, and inputting the historical battery information into the solid-liquid phase diffusion model for calculation, obtaining the current diffusion concentration value of the current time step includes:

[0117] Step 402: Obtain the historical battery information of adjacent time steps corresponding to the current time step, input the historical battery information into the diffusion equation model for calculation, and obtain the diffusion concentration value at the current time step.

[0118] Among them, the diffusion equation model calculates the diffusion concentration based on Fick's law.

[0119] Specifically, if the terminal selects the diffusion equation model as the target solid-liquid phase diffusion model, then input the historical diffusion concentration value and the historical surface current density at the previous time step required for calculating the solid-liquid phase concentration information in the historical battery information into the diffusion equation model for calculation, and obtain the diffusion concentration value at the current time step.

[0120] Furthermore, the diffusion process is described by Fick's law, that is, it is considered that the molar flux caused by diffusion is proportional to the concentration gradient, and the rate of change of the concentration at a certain point in space is proportional to the second-order spatial derivative of the concentration. The solid-phase concentration expression is as follows:

[0121]

[0122]

[0123] Among them, c s is the solid-phase concentration, t is the time step, D s is the diffusion coefficient, r is the position in the direction of the radius of the solid-phase particle, j is the surface current density, F is the Faraday constant, and R is the radius of the solid-phase particle.

[0124] The liquid-phase diffusion process is calculated by the following liquid-phase concentration expression, considering the diffusion process and the electromigration process of lithium ions in the thickness direction:

[0125]

[0126]

[0127] Among them, ε l is the porosity of the corresponding region, c l is the liquid-phase concentration, x is the position in the thickness direction, D eff,l is the effective liquid-phase diffusion coefficient, t + is the transference number of lithium ions in the electrolyte, a is the specific surface area of the solid-phase particle, j(x, t) is the concentration flux at this point, and L is the total thickness of the electrode sheet.

[0128] Then, perform the calculation of the electrical state information, input the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information at the current time step, including:

[0129] Step 404: Obtain the historical electrical state information of the adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the charge transfer model for calculation, and obtain the electrical state information of the current time step.

[0130] Among them, the charge transfer model calculates the electrical state information based on Ohm's law and Kirchhoff's law.

[0131] Specifically, the terminal obtains the historical electrical state information of the previous time step corresponding to the current time step, inputs the historical electrical state information and the current diffusion concentration value into the charge transfer model for calculation, and obtains the electrical state information of the current time step.

[0132] Furthermore, the electrode surface current density in the charge transfer model and the transmission line model is obtained from the Butler-Volmer equation:

[0133]

[0134]

[0135] Where i0 is the exchange current density, k a and k c are the anodic and cathodic reaction rate constants respectively, α a and α c are the anodic and cathodic transfer coefficients respectively, η is the overpotential of the electrode reaction, R is the gas constant, and T is the temperature.

[0136] The charge transfer model simulates the liquid-phase conductance and electromigration process, calculates the electric potential and current at each position in the battery system by Ohm's law and Kirchhoff's law, and the charge transfer calculation mainly includes the following control equations:

[0137]

[0138]

[0139] Where σ s,eff and σ l,eff are the effective conductivities of the solid phase and the liquid phase respectively, Φ s and Φ l are the electric potentials of the solid phase and the liquid phase respectively.

[0140] In this embodiment, according to the high-precision simulation requirements, the accuracy of concentration calculation can be improved by calculating the diffusion concentration based on Fick's law, and the accuracy of electrical state information calculation can be improved by calculating the electrical state information based on Ohm's law and Kirchhoff's law, thus improving the battery simulation accuracy.

[0141] In an optional embodiment, according to the simulation requirements, selecting a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting a target electron transport model for battery simulation calculation from a plurality of preset electron transport models includes:

[0142] When the simulation requirement is a high-efficiency simulation requirement, select the polynomial fitting model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models as the target solid-liquid phase diffusion model, and select the transmission line model for battery simulation calculation from a plurality of preset electron transport models as the target electron transport model.

[0143] Among them, the polynomial fitting model is a model for calculating the solid-liquid phase concentration process in the simplified model. The transmission line model is a model for calculating the electrical state information process in the simplified model.

[0144] Specifically, the terminal compares the physical simulation accuracy requirement with a preset accuracy threshold, and compares the simulation efficiency requirement with a preset efficiency threshold. If the simulation efficiency requirement is greater than or equal to the preset efficiency threshold, the simulation requirement for this battery simulation scenario is a high-efficiency simulation requirement. Then, determine the polynomial fitting model as the target solid-liquid phase diffusion model from a plurality of solid-liquid phase diffusion models, and select the transmission line model for battery simulation calculation from a plurality of preset electron transport models as the target electron transport model.

[0145] In this embodiment, selecting the polynomial fitting model and the transmission line model for battery simulation according to the high-efficiency simulation requirement can improve the calculation speed of battery state information.

[0146] In an optional embodiment, as Figure 5 shown, obtaining historical battery information of an adjacent time step corresponding to the current time step, and inputting the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step includes:

[0147] Step 502, obtain historical battery information of an adjacent time step corresponding to the current time step, and based on polynomial fitting, input the historical battery information into the polynomial fitting model for calculation to obtain the diffusion concentration value of the current time step.

[0148] Specifically, if the terminal selects the polynomial fitting model as the target solid-liquid phase diffusion model, input the historical diffusion concentration value and the historical surface current density of the previous time step required for calculating the solid-liquid phase concentration information in the historical battery information into the polynomial fitting model for calculation to obtain the diffusion concentration value of the current time step.

[0149] Furthermore, the polynomial fitting model simplifies the partial differential equation describing the solid phase concentration in the P2D model into a simple differential algebraic equation. The polynomial fitting control equation is as follows:

[0150]

[0151] Where a(t) and b(t) are time-related constants, which can be obtained by processing the input of the model through an algorithm.

[0152] The liquid-phase diffusion process in the polynomial fitting model is consistent with the calculation process in the diffusion equation model, and both are calculated from the liquid-phase concentration expression (2).

[0153] Then, the current diffusion concentration value is input into the electron transport model for calculation to obtain the electrical state information at the current time step, including:

[0154] Step 504: Obtain the historical electrical state information of the adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the transmission line model for calculation, and obtain the electrical state information at the current time step.

[0155] Among them, the transmission line model calculates the electrical state information based on the equivalent circuit principle of the transmission line.

[0156] Specifically, obtain the historical electrical state information of the previous time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the transmission line model for calculation, and obtain the electrical state information at the current time step.

[0157] Furthermore, introduce the equivalent circuit of the transmission line model to describe the electrical state of the system, use Kirchhoff's law for this equivalent circuit model, and obtain a matrixed model, which can be described by the following matrix equation:

[0158]

[0159] Where I system , R system and U system are matrices composed of the current, resistance, and voltage of the system respectively. At each time step, R system and U system are known, and then I system can be obtained, which represents the current state of the system current at this time step.

[0160] In this embodiment, according to the requirements of high-efficiency simulation, calculating the diffusion concentration through the polynomial fitting model can improve the rate of concentration calculation, and calculating the electrical state information based on the equivalent circuit principle of the transmission line can improve the rate of electrical state information calculation, thus improving the battery simulation efficiency.

[0161] In an alternative embodiment, historical battery information corresponding to adjacent time steps of the current time step is obtained, and the historical battery information is input into a solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step, including: obtaining the historical diffusion concentration value of the adjacent time step corresponding to the current time step, and inputting the historical diffusion concentration value into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step.

[0162] Specifically, the solid-liquid phase diffusion model is used to calculate the changes in solid-phase and liquid-phase concentrations within the current time step. The terminal obtains the historical diffusion concentration value and the historical surface current density of the adjacent time step corresponding to the current time step according to the current time step information, and inputs the historical diffusion concentration value and the historical surface current density into the diffusion equation model for calculation to obtain the current time step diffusion concentration value. When the current time step is the first step and there is no historical battery information, the default initial battery information is used as the battery information, and the default initial battery information can be obtained through comprehensive analysis of the initial electrical state information and concentration information of different batteries.

[0163] In the above embodiment, based on the solid-liquid phase diffusion model and according to the historical diffusion concentration value and the historical surface current density to calculate the current diffusion concentration value of the current time step, the battery change process can be accurately simulated, and the current diffusion concentration value can be calculated quickly and accurately.

[0164] In an alternative embodiment, the current diffusion concentration value is input into an electron transport model for calculation to obtain the electrical state information of the current time step, including: obtaining the historical electrical state information of the adjacent time step corresponding to the current time step, and inputting the historical electrical state information and the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information of the current time step.

[0165] Specifically, the electron transport model is used to calculate electrical quantities such as electric potential and current corresponding to the time step. The terminal obtains the historical electrical state information of the previous time step corresponding to the current time step, and inputs the historical electrical state information and the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information of the current time step. When the current time step is the first step and there is no historical battery information, the default initial battery information is used as the battery information, and the default initial battery information can be obtained through comprehensive analysis of the initial electrical state information and concentration information of different batteries.

[0166] In the above embodiment, based on the electron transport model and according to the historical electrical state information and the current diffusion concentration value to calculate the electrical state information of the current time step, the battery change process can be accurately simulated, and the electrical state information of the current time step can be calculated quickly and accurately.

[0167] In an optional embodiment, when it is determined that the battery simulation process reaches a preset simulation end condition according to the diffusion concentration value at the current time step and the electrical state information at the current time step, the battery simulation calculation terminates. The preset simulation end conditions include that the battery reaches the maximum battery voltage or the minimum battery press, reaches a preset maximum simulation time threshold, and simulation calculation errors occur, etc. Simulation calculation errors include that the concentration is negative or imaginary, etc.

[0168] When the battery simulation calculation terminates, the data required by the user application can be output and stored in the local memory, and other relevant information (such as calculation time consumption, error report, etc.) during the current simulation process can also be output and stored.

[0169] In this embodiment, taking the battery simulation calculation method provided by the present application applied to the life prediction scenario as an example for illustration, the simulation requirements of the life prediction scenario are fast calculation speed to save the total time required for a large amount of calculations; relatively complete physical meaning to obtain the data required in the life model; applicable to complex working conditions, such as variable current charging, constant voltage charging, etc. Therefore, in the life prediction scenario, the solid-liquid phase diffusion model is the diffusion equation model, and the electron transport model is the transmission line model. The diffusion equation model + the transmission line model is used to quickly and accurately calculate the battery state information.

[0170] In this embodiment, taking the battery simulation calculation method provided by the present application applied to the lithium plating process analysis scenario as an example for illustration, the simulation requirements of the lithium plating process analysis scenario are high precision to obtain accurate potential values; complete physical meaning to provide sufficient data to support the research on the lithium plating process. Therefore, in the life prediction scenario, the solid-liquid phase diffusion model is the diffusion equation model, and the electron transport model is the charge transfer model. The diffusion equation model + the charge transfer model is used to accurately calculate the battery state information.

[0171] To facilitate understanding of the technical solution provided by the embodiments of the present application, as Figure 6 shown, the battery simulation calculation method provided by the embodiments of the present application is briefly described with a complete battery simulation calculation process:

[0172] Step 602, obtain the battery simulation scenario.

[0173] Step 604, determine the simulation requirements according to the battery simulation scenario.

[0174] Step 606, in the case where the simulation requirement is a high-precision simulation requirement, select the diffusion equation model for battery simulation calculation as the target solid-liquid phase diffusion model from a preset plurality of solid-liquid phase diffusion models, and select the charge transfer model for battery simulation calculation as the target electron transport model from a preset plurality of electron transport models.

[0175] Step 608: Obtain the historical diffusion concentration values and historical surface current densities of adjacent time steps corresponding to the current time step, input the historical diffusion concentration values and historical surface current densities into the diffusion equation model for calculation, and obtain the diffusion concentration value of the current time step.

[0176] Step 610: Obtain the historical electrical state information of adjacent time steps corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the charge transfer model for calculation, and obtain the electrical state information of the current time step.

[0177] Step 612: In the case where the simulation requirement is a high-efficiency simulation requirement, select the polynomial fitting model for battery simulation calculation among the preset multiple solid-liquid phase diffusion models as the target solid-liquid phase diffusion model, and select the transmission line model for battery simulation calculation among the preset multiple electron transport models as the target electron transport model.

[0178] Step 614: Obtain the historical diffusion concentration values and historical surface current densities of adjacent time steps corresponding to the current time step, input the historical diffusion concentration values and historical surface current densities into the polynomial fitting model for calculation, and obtain the diffusion concentration value of the current time step.

[0179] Step 616: Obtain the historical electrical state information of adjacent time steps corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the transmission line model for calculation, and obtain the electrical state information of the current time step.

[0180] It should be understood that although each step in the flowcharts involved in the above-described embodiments is shown in sequence according to the indication of the arrows, these steps do not necessarily need to be executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages do not necessarily need to be executed at the same moment, but can be executed at different moments. The execution order of these steps or stages does not necessarily need to be sequential, but can be executed alternately or in turns with at least a part of other steps or steps or stages in other steps.

[0181] Based on the same inventive concept, an embodiment of the present application further provides a battery simulation calculation device for implementing the battery simulation calculation method described above. The solution provided by this device for solving problems is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the battery simulation calculation device provided below can refer to the limitations on the battery simulation calculation method in the above text, and will not be repeated here.

[0182] In one embodiment, as Figure 7 shown, a battery simulation calculation device is provided, including: a selection module 702, a concentration calculation module 704, and an electrical information calculation module 706, where:

[0183] The selection module 702 is configured to obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario.

[0184] The concentration calculation module 704 is configured to obtain historical battery information of an adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value of the current time step.

[0185] The electrical information calculation module 706 is configured to input the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information of the current time step.

[0186] In one of the embodiments, the selection module 702 is further configured to select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models according to the battery simulation scenario, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

[0187] In one of the embodiments, the selection module 702 is further configured to determine simulation requirements according to the battery simulation scenario; according to the simulation requirements, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

[0188] In one of the embodiments, when the simulation requirement is a high-precision simulation requirement, the selection module 702 is further configured to select a diffusion equation model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and select a charge transfer model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

[0189] In one of the embodiments, the concentration calculation module 704 is further configured to obtain historical battery information of an adjacent time step corresponding to the current time step, input the historical battery information into the diffusion equation model for calculation, and obtain the diffusion concentration value of the current time step; wherein, the diffusion equation model calculates the diffusion concentration based on Fick's law; the electrical information calculation module 706 is further configured to obtain historical electrical state information of an adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the charge transfer model for calculation, and obtain the electrical state information of the current time step; wherein, the charge transfer model calculates the electrical state information based on Ohm's law and Kirchhoff's law.

[0190] In one embodiment, the selection module 702 is further configured to, when the simulation requirement is a high-efficiency simulation requirement, select a polynomial fitting model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and select a transmission line model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

[0191] In one embodiment, the concentration calculation module 704 is further configured to obtain historical battery information of an adjacent time step corresponding to the current time step, and based on polynomial fitting, input the historical battery information into the polynomial fitting model for calculation to obtain the diffusion concentration value at the current time step; the electrical information calculation module 706 is further configured to obtain historical electrical state information of an adjacent time step corresponding to the current time step, and input the historical electrical state information and the current diffusion concentration value into the transmission line model for calculation to obtain the electrical state information at the current time step; wherein, the transmission line model calculates the electrical state information based on the equivalent circuit principle of the transmission line.

[0192] In one embodiment, the concentration calculation module 704 is further configured to obtain the historical diffusion concentration value of an adjacent time step corresponding to the current time step, and input the historical diffusion concentration value into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step.

[0193] In one embodiment, the electrical information calculation module 706 is further configured to obtain historical electrical state information of an adjacent time step corresponding to the current time step, and input the historical electrical state information and the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

[0194] Each module in the above battery simulation calculation device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or stored in a memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0195] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 8As shown. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be achieved through WIFI, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a battery simulation calculation method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads provided on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0196] Those skilled in the art can understand that Figure 8 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0197] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0198] Obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario;

[0199] Obtain historical battery information of adjacent time steps corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value of the current time step;

[0200] Input the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information of the current time step.

[0201] In one embodiment, when the processor executes the computer program, the following steps are also implemented: Selecting a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario includes: According to the battery simulation scenario, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

[0202] In one embodiment, when the processor executes a computer program, the following steps are further implemented: According to the battery simulation scenario, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: According to the battery simulation scenario, determine the simulation requirements; According to the simulation requirements, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

[0203] In one embodiment, when the processor executes a computer program, the following steps are further implemented: According to the simulation requirements, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: When the simulation requirement is a high-precision simulation requirement, select the diffusion equation model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models as the target solid-liquid phase diffusion model, and select the charge transfer model for battery simulation calculation from a plurality of preset electron transport models as the target electron transport model.

[0204] In one embodiment, when the processor executes a computer program, the following steps are further implemented: Obtain the historical battery information of the adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step, including: Obtain the historical battery information of the adjacent time step corresponding to the current time step, input the historical battery information into the diffusion equation model for calculation to obtain the diffusion concentration value of the current time step; wherein, the diffusion equation model calculates the diffusion concentration based on Fick's law; Input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information of the current time step, including: Obtain the historical electrical state information of the adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the charge transfer model for calculation to obtain the electrical state information of the current time step; wherein, the charge transfer model calculates the electrical state information based on Ohm's law and Kirchhoff's law.

[0205] In one embodiment, when the processor executes a computer program, the following steps are further implemented: According to the simulation requirements, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: When the simulation requirement is a high-efficiency simulation requirement, select the polynomial fitting model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models as the target solid-liquid phase diffusion model, and select the transmission line model for battery simulation calculation from a plurality of preset electron transport models as the target electron transport model.

[0206] In one embodiment, when the processor executes the computer program, the following steps are further implemented: According to the simulation requirements, select the target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select the target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: when the simulation requirement is a high-efficiency simulation requirement, select the polynomial fitting model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models as the target solid-liquid phase diffusion model, and select the transmission line model for battery simulation calculation from a plurality of preset electron transport models as the target electron transport model.

[0207] In one embodiment, when the processor executes the computer program, the following steps are further implemented: Obtain the historical battery information of the adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value of the current time step, including: Obtain the historical battery information of the adjacent time step corresponding to the current time step, based on polynomial fitting, input the historical battery information into the polynomial fitting model for calculation, and obtain the diffusion concentration value of the current time step; Input the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information of the current time step, including: Obtain the historical electrical state information of the adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the transmission line model for calculation, and obtain the electrical state information of the current time step; wherein, the transmission line model calculates the electrical state information based on the equivalent circuit principle of the transmission line.

[0208] In one embodiment, when the processor executes the computer program, the following steps are further implemented: Obtain the historical battery information of the adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value of the current time step, including: Obtain the historical diffusion concentration value of the adjacent time step corresponding to the current time step, input the historical diffusion concentration value into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value of the current time step.

[0209] In one embodiment, when the processor executes the computer program, the following steps are further implemented: Input the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information of the current time step, including: Obtain the historical electrical state information of the adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information of the current time step.

[0210] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0211] Obtain a battery simulation scenario. According to the battery simulation scenario, select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation;

[0212] Obtain historical battery information of an adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value at the current time step;

[0213] Input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

[0214] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: According to the battery simulation scenario, selecting a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation includes: According to the battery simulation scenario, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

[0215] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: According to the battery simulation scenario, selecting a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting a target electron transport model for battery simulation calculation from a plurality of preset electron transport models includes: According to the battery simulation scenario, determine the simulation requirements; According to the simulation requirements, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models. In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: According to the simulation requirements, selecting a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting a target electron transport model for battery simulation calculation from a plurality of preset electron transport models includes: In the case where the simulation requirement is a high-precision simulation requirement, select the diffusion equation model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and select the charge transfer model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

[0216] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining historical battery information of adjacent time steps corresponding to the current time step, inputting the historical battery information into a solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step, including: obtaining historical battery information of adjacent time steps corresponding to the current time step, inputting the historical battery information into a diffusion equation model for calculation to obtain the diffusion concentration value at the current time step; wherein, the diffusion equation model calculates the diffusion concentration based on Fick's law; inputting the current diffusion concentration value into an electron transport model for calculation to obtain the electrical state information at the current time step, including: obtaining historical electrical state information of adjacent time steps corresponding to the current time step, inputting the historical electrical state information and the current diffusion concentration value into a charge transfer model for calculation to obtain the electrical state information at the current time step; wherein, the charge transfer model calculates the electrical state information based on Ohm's law and Kirchhoff's law.

[0217] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: according to the simulation requirements, selecting a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting a target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: in the case where the simulation requirement is a high-efficiency simulation requirement, selecting a polynomial fitting model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and selecting a transmission line model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

[0218] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: according to the simulation requirements, selecting a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting a target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: in the case where the simulation requirement is a high-efficiency simulation requirement, selecting a polynomial fitting model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and selecting a transmission line model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

[0219] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining historical battery information of adjacent time steps corresponding to the current time step, inputting the historical battery information into a solid-liquid phase diffusion model for calculation, and obtaining the current diffusion concentration value at the current time step, including: obtaining historical battery information of adjacent time steps corresponding to the current time step, based on polynomial fitting, inputting the historical battery information into a polynomial fitting model for calculation, and obtaining the diffusion concentration value at the current time step; inputting the current diffusion concentration value into an electron transport model for calculation, and obtaining the electrical state information at the current time step, including: obtaining historical electrical state information of adjacent time steps corresponding to the current time step, inputting the historical electrical state information and the current diffusion concentration value into a transmission line model for calculation, and obtaining the electrical state information at the current time step; wherein, the transmission line model calculates the electrical state information based on the equivalent circuit principle of the transmission line.

[0220] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining historical battery information of adjacent time steps corresponding to the current time step, inputting the historical battery information into a solid-liquid phase diffusion model for calculation, and obtaining the current diffusion concentration value at the current time step, including: obtaining historical diffusion concentration values of adjacent time steps corresponding to the current time step, inputting the historical diffusion concentration values into the solid-liquid phase diffusion model for calculation, and obtaining the current diffusion concentration value at the current time step.

[0221] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: inputting the current diffusion concentration value into an electron transport model for calculation, and obtaining the electrical state information at the current time step, including: obtaining historical electrical state information of adjacent time steps corresponding to the current time step, inputting the historical electrical state information and the current diffusion concentration value into the electron transport model for calculation, and obtaining the electrical state information at the current time step.

[0222] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0223] Obtaining a battery simulation scenario, and selecting a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario;

[0224] Obtaining historical battery information of adjacent time steps corresponding to the current time step, inputting the historical battery information into a solid-liquid phase diffusion model for calculation, and obtaining the current diffusion concentration value at the current time step;

[0225] Inputting the current diffusion concentration value into an electron transport model for calculation, and obtaining the electrical state information at the current time step.

[0226] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: According to the battery simulation scenario, select the solid-liquid phase diffusion model and the electron transport model for battery simulation calculation, including: According to the battery simulation scenario, select the target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select the target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

[0227] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: According to the battery simulation scenario, select the target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select the target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: According to the battery simulation scenario, determine the simulation requirements; According to the simulation requirements, select the target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select the target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

[0228] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: According to the simulation requirements, select the target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select the target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: In the case where the simulation requirements are high-precision simulation requirements, select the diffusion equation model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and select the charge transfer model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

[0229] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: Obtain the historical battery information of the adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value of the current time step, including: Obtain the historical battery information of the adjacent time step corresponding to the current time step, input the historical battery information into the diffusion equation model for calculation, and obtain the diffusion concentration value of the current time step; wherein, the diffusion equation model calculates the diffusion concentration based on Fick's law; Input the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information of the current time step, including: Obtain the historical electrical state information of the adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the charge transfer model for calculation, and obtain the electrical state information of the current time step; wherein, the charge transfer model calculates the electrical state information based on Ohm's law and Kirchhoff's law.

[0230] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: according to the simulation requirements, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: when the simulation requirements are high-efficiency simulation requirements, select the polynomial fitting model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and select the transmission line model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

[0231] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: according to the simulation requirements, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models, including: when the simulation requirements are high-efficiency simulation requirements, select the polynomial fitting model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and select the transmission line model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

[0232] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtain historical battery information of an adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step, including: obtain historical battery information of an adjacent time step corresponding to the current time step, based on polynomial fitting, input the historical battery information into the polynomial fitting model for calculation to obtain the diffusion concentration value at the current time step; input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step, including: obtain historical electrical state information of an adjacent time step corresponding to the current time step, input the historical electrical state information and the current diffusion concentration value into the transmission line model for calculation to obtain the electrical state information at the current time step; wherein, the transmission line model calculates the electrical state information based on the equivalent circuit principle of the transmission line.

[0233] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtain historical battery information of an adjacent time step corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step, including: obtain the historical diffusion concentration value of an adjacent time step corresponding to the current time step, input the historical diffusion concentration value into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step.

[0234] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: input the current diffusion concentration value into the electronic transport model for calculation to obtain the electrical state information of the current time step, including: obtaining the historical electrical state information of adjacent time steps corresponding to the current time step, and inputting the historical electrical state information and the current diffusion concentration value into the electronic transport model for calculation to obtain the electrical state information of the current time step.

[0235] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memories can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., and are not limited thereto.

[0236] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present application, and they should all be covered within the scope of the claims and the specification of the present application. In particular, as long as there is no structural conflict, the technical features mentioned in each embodiment can be combined in any way. The present application is not limited to the specific embodiments disclosed in the text, but includes all technical solutions falling within the scope of the claims.

Claims

1. A battery simulation calculation method, characterized in that, The method includes: Obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario; wherein, the solid-liquid phase diffusion model is used to calculate the change in the solid-phase concentration and the change in the liquid-phase concentration of lithium ions during the battery simulation process, and the electron transport model is used to calculate the electrical state information of the solid phase and the liquid phase of lithium ions during the battery simulation process; Obtain historical battery information of an adjacent time step corresponding to the current time step, and input the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step; Input the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step.

2. The method according to claim 1, wherein The selecting a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario includes: According to the battery simulation scenario, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

3. The method according to claim 2, wherein The selecting a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting a target electron transport model for battery simulation calculation from a plurality of preset electron transport models according to the battery simulation scenario includes: Determine the simulation requirements according to the battery simulation scenario; According to the simulation requirements, select a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and select a target electron transport model for battery simulation calculation from a plurality of preset electron transport models.

4. The method according to claim 3, wherein The selecting a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting a target electron transport model for battery simulation calculation from a plurality of preset electron transport models according to the simulation requirements includes: In the case where the simulation requirement is a high-precision simulation requirement, select a diffusion equation model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models as the target solid-liquid phase diffusion model, and select a charge transfer model for battery simulation calculation from a plurality of preset electron transport models as the target electron transport model.

5. The method according to claim 4, characterized in that The obtaining historical battery information of an adjacent time step corresponding to the current time step, and inputting the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value at the current time step includes: Obtain historical battery information of an adjacent time step corresponding to the current time step, and input the historical battery information into the diffusion equation model for calculation to obtain the diffusion concentration value at the current time step; wherein, the diffusion equation model calculates the diffusion concentration based on Fick's law; The inputting the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information at the current time step includes: Obtain the historical electrical state information of adjacent time steps corresponding to the current time step, and input the historical electrical state information and the current diffusion concentration value into the charge transfer model for calculation to obtain the electrical state information of the current time step; wherein, the charge transfer model calculates the electrical state information based on Ohm's law and Kirchhoff's law.

6. The method according to claim 3, wherein The selecting, according to the simulation requirements, a target solid-liquid phase diffusion model for battery simulation calculation from a plurality of preset solid-liquid phase diffusion models, and selecting a target electron transport model for battery simulation calculation from a plurality of preset electron transport models includes: In the case where the simulation requirements are high-efficiency simulation requirements, select the polynomial fitting model for battery simulation calculation as the target solid-liquid phase diffusion model from a plurality of preset solid-liquid phase diffusion models, and select the transmission line model for battery simulation calculation as the target electron transport model from a plurality of preset electron transport models.

7. The method according to claim 6, wherein The obtaining the historical battery information of adjacent time steps corresponding to the current time step, and inputting the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step includes: Obtain the historical battery information of adjacent time steps corresponding to the current time step, and based on polynomial fitting, input the historical battery information into the polynomial fitting model for calculation to obtain the diffusion concentration value of the current time step. The inputting the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information of the current time step includes: Obtain the historical electrical state information of adjacent time steps corresponding to the current time step, and input the historical electrical state information and the current diffusion concentration value into the transmission line model for calculation to obtain the electrical state information of the current time step; wherein, the transmission line model calculates the electrical state information based on the equivalent circuit principle of the transmission line.

8. The method according to claim 1, wherein The obtaining the historical battery information of adjacent time steps corresponding to the current time step, and inputting the historical battery information into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step includes: Obtain the historical diffusion concentration value of adjacent time steps corresponding to the current time step, and input the historical diffusion concentration value into the solid-liquid phase diffusion model for calculation to obtain the current diffusion concentration value of the current time step.

9. The method according to claim 1, characterized in that, The inputting the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information of the current time step includes: Obtain the historical electrical state information of adjacent time steps corresponding to the current time step, and input the historical electrical state information and the current diffusion concentration value into the electron transport model for calculation to obtain the electrical state information of the current time step.

10. A battery simulation calculation device, characterized in that, The device includes: A selection module, configured to obtain a battery simulation scenario, and select a solid-liquid phase diffusion model and an electron transport model for battery simulation calculation according to the battery simulation scenario; wherein, the solid-liquid phase diffusion model is used to calculate the change in the solid-phase concentration and the change in the liquid-phase concentration of lithium ions during the battery simulation process, and the electron transport model is used to calculate the electrical state information of the solid phase and the liquid phase of lithium ions during the battery simulation process. A concentration calculation module, configured to obtain historical battery information of adjacent time steps corresponding to the current time step, input the historical battery information into the solid-liquid phase diffusion model for calculation, and obtain the current diffusion concentration value of the current time step; An electrical information calculation module, configured to input the current diffusion concentration value into the electron transport model for calculation, and obtain the electrical state information of the current time step.

11. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 9 are implemented.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 9 are implemented.

Images