Information processing method, information processing system, display control method, and program

Abstract

To facilitate shortening of the time to calculate battery characteristics of a solid-state battery.SOLUTION: An information processing method is executed by a computer, and the information processing method includes: acquiring one or more parameters of a solid-state battery (S10); generating an electric circuit model for simulating the behavior of charge and discharge of the solid-state battery on the basis of the acquired one or more parameters (S11); calculating the battery characteristics of the solid-state battery on the basis of the generated electric circuit model (S12); and outputting battery characteristic information indicating the calculated battery characteristics (S13).SELECTED DRAWING: Figure 11

Description

[Technical Field]

[0001] The present disclosure relates to a technique for calculating battery characteristics of an all-solid-state battery. [Background technology]

[0002] Non-Patent Documents 1, 2, and 3 disclose techniques for calculating the battery characteristics of lithium ion batteries. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] BEST-Batterie- und Elektrochemie-Simulationstool,[Retrieved May 2, 2024],Internet, <URL:https: / / www.itwm.fraunhofer.de / de / abteilungen / sms / produkte-und-leistungen / best-battery-and-electrochemistry-simulation-tool.html> [Non-patent document 2] Micro-Scale Modeling of Li-Ion Batteries: Parameterization and Validation, J. Electrochem. Soc. 159 (2012) A697-A704 [Non-patent document 3] A. Latz and J. Zausch: Thermodynamic consistent transport theory of Li-ion batteries, Journal of Power Sources 196 (2011) 3296-3302. Summary of the Invention [Problem to be solved by the invention]

[0004] The present disclosure provides an information processing method and the like that can easily reduce the time required to calculate the battery characteristics of an all-solid-state battery. [Means for solving the problem]

[0005] An information processing method according to one aspect of the present disclosure is an information processing method executed by a computer, which acquires one or more parameters of an all-solid-state battery, generates an electric circuit model that simulates the charge / discharge behavior of the all-solid-state battery based on the acquired one or more parameters, calculates battery characteristics of the all-solid-state battery based on the generated electric circuit model, and outputs battery characteristic information indicating the calculated battery characteristics. [Effects of the Invention]

[0006] According to the present disclosure, it is easy to reduce the time required to calculate the battery characteristics of an all-solid-state battery. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing an overall configuration including an information processing system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the configuration of an all-solid-state battery. [Figure 3] FIG. 3 is a diagram showing an example of an electric circuit model of an all-solid-state battery. [Figure 4] FIG. 4 is a diagram showing an example of a charge / discharge curve of an all-solid-state battery. [Figure 5] FIG. 5 is a diagram showing an example of a first image displayed on a display unit in the embodiment. [Figure 6] FIG. 6 is a diagram showing another example of the first image displayed on the display unit in the embodiment. [Figure 7] FIG. 7 is a diagram showing yet another example of the first image displayed on the display unit in the embodiment. [Figure 8] FIG. 8 is a diagram showing an example of a second image displayed on the display unit in the embodiment. [Figure 9]FIG. 9 is a diagram showing an example of a third image displayed on the display unit in the embodiment. [Figure 10] FIG. 10 is a diagram showing an example of a fourth image displayed on the display unit in the embodiment. [Figure 11] FIG. 11 is a flowchart illustrating an example of the operation of the information processing system according to the embodiment. [Figure 12] FIG. 12 is a flowchart showing an example of calculating the charge voltage (or discharge voltage) of an all-solid-state battery from an electric circuit model by the information processing system according to the embodiment. [Figure 13] FIG. 13 is a flowchart illustrating an example of generating an image showing battery characteristics of an all-solid-state battery by the information processing system according to the embodiment. [Figure 14] FIG. 14 is a flowchart illustrating another operation example of the information processing system according to the embodiment. [Figure 15] FIG. 15 is a diagram showing an example of a UI for inputting one or more parameters in the embodiment. [Figure 16] FIG. 16 is a diagram showing another example of a UI for inputting one or more parameters in the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] (Findings that led to this disclosure) All-solid-state batteries are expected to be the next generation of energy storage devices in modern society. Compared to conventional lithium-ion batteries that use liquid electrolytes, all-solid-state batteries using solid electrolytes reduce the risk of electrical leakage or fire, and are expected to realize safer battery systems. Furthermore, as technological innovation is required to achieve high energy density and long life, all-solid-state batteries are attracting attention as a solution that can be used in a wide range of applications, such as portable electronic devices, electric vehicles, and large-scale energy storage systems.

[0009] In the development of all-solid-state batteries, each component, such as the cathode material, anode material, solid electrolyte, or interface design, is crucial. The type, structure, or overall battery design of these materials can directly affect the performance of the all-solid-state battery. Therefore, systematic prototyping and testing are essential to optimize the composition or physical properties of these materials. However, the fabrication and evaluation of all-solid-state battery prototypes requires advanced technology, especially in handling the solid electrolyte, and tends to be more time-consuming and costly than the fabrication and evaluation of conventional lithium-ion battery prototypes. Furthermore, the interfacial properties or unpredictable reactions between solid materials can often be understood only through detailed experiments, complicating the technology development process.

[0010] In order to rapidly evaluate new design concepts or innovative material systems and to derive design guidelines that can be efficiently implemented in the production of actual all-solid-state batteries, an approach that utilizes simulation in addition to experiments is essential. This is expected to enable rapid screening of various design variables or theoretical assumptions, leading to a more efficient and accurate development process.

[0011] In light of the above background, the inventors considered it important to provide a simulation technology for predicting the characteristics and optimizing the design of all-solid-state batteries in order to support the rapid development of high-quality all-solid-state batteries that can meet market needs.

[0012] Here, for example, the simulation technique based on a continuum model of a lithium-ion battery described in Non-Patent Document 1 is effective for detailed analysis of ion transport through an electrolyte or the dynamic behavior of the liquid phase, but has the problem of requiring a long time for calculation processing. In particular, when simulating a solid-solid interface and its complex physicochemical interactions, such as in an all-solid-state battery, the calculation load increases, and therefore, when using the simulation technique described in Non-Patent Document 1, there is a problem that the calculation processing may require an enormous amount of time. In addition, there is also the problem that there remains uncertainty as to whether a simulation based on a continuum model can reproduce the behavior of an all-solid-state battery with sufficient accuracy, considering the difficulties unique to all-solid-state batteries.

[0013] In order to solve the above problems, an information processing method according to a first aspect of the present disclosure is an information processing method executed by a computer, which acquires one or more parameters of an all-solid-state battery, generates an electric circuit model that simulates the charge / discharge behavior of the all-solid-state battery based on the acquired one or more parameters, calculates battery characteristics of the all-solid-state battery based on the generated electric circuit model, and outputs battery characteristic information indicating the calculated battery characteristics.

[0014] This has the advantage that the battery characteristics of an all-solid-state battery are calculated using an electric circuit model, which makes it easier to shorten the processing time for calculating the battery characteristics of an all-solid-state battery compared to simulating the battery characteristics of an all-solid-state battery using a continuum model. In other words, the electric circuit model has the advantage that it can reduce the consumption of computer resources compared to the continuum model. This makes it possible to reduce research and development costs and perform more simulations in parallel.

[0015] Furthermore, the electrical circuit model has a relatively simple structure and can be easily applied to different types of all-solid-state batteries, which enables the rapid evaluation of the characteristics of all-solid-state batteries made of different materials or designs, thereby streamlining the development process of all-solid-state batteries.

[0016] Furthermore, the use of an electric circuit model allows for rapid and accurate evaluation of the characteristics of all-solid-state batteries, which allows for rapid feedback at the design stage, thereby facilitating rapid optimization of the design or material selection of all-solid-state batteries, and ultimately facilitating improvement in the performance of actual all-solid-state batteries.

[0017] Furthermore, for example, in the information processing method according to the second aspect of the present disclosure, in the first aspect, in the process of calculating the battery characteristics of the all-solid-state battery, the process of calculating the battery characteristics may be repeatedly executed for each of a plurality of combinations of one or more variables among the one or more parameters.

[0018] This provides the advantage that a plurality of calculation results of the battery characteristics of the all-solid-state battery according to each parameter can be obtained, making it easy to design an all-solid-state battery having desired battery characteristics based on the plurality of calculation results.

[0019] Furthermore, for example, in the information processing method according to the third aspect of the present disclosure, in the first or second aspect, the process of generating the electric circuit model may generate an electrode structure model that simulates a structure of the all-solid-state battery by executing a simulation using the one or more parameters, and calculate some circuit parameters in the electric circuit model based on the generated electrode structure model.

[0020] This has the advantage that it becomes easier to calculate some circuit parameters with high accuracy, and the accuracy of simulating the charging and discharging behavior of the all-solid-state battery in the electric circuit model is easily improved.

[0021] Furthermore, for example, in the information processing method according to the fourth aspect of the present disclosure, in any one of the first to third aspects, the process of calculating the battery characteristics may calculate an average discharge voltage and an energy capacity of the all-solid-state battery as the battery characteristics.

[0022] This has the advantage of making it easier to shorten the processing time required to calculate the average discharge voltage and energy capacity of the all-solid-state battery.

[0023] Furthermore, for example, in the information processing method according to the fifth aspect of the present disclosure, in the fourth aspect, the process of outputting the battery characteristics may output an image representing a relationship between the average discharge voltage and the energy capacity of the all-solid-state battery to a display unit.

[0024] This has the advantage that it is possible to determine whether the average discharge voltage and energy capacity of the all-solid-state battery have the characteristics desired by the user, making it easier to design an all-solid-state battery having the desired battery characteristics.

[0025] Furthermore, for example, in the information processing method according to the sixth aspect of the present disclosure, in any one of the first to fifth aspects, a process may be executed to further acquire target battery characteristic information indicating the target battery characteristics of the all-solid-state battery, compare the target battery characteristic information with the battery characteristic information, and, if the battery characteristic information satisfies the target battery characteristic information, output the one or more parameters that satisfy the target battery characteristics.

[0026] This has the advantage that it is possible to perform a reverse analysis to search for one or more parameters that satisfy the battery characteristics of the all-solid-state battery desired by the user.

[0027] Furthermore, for example, an information processing system according to a seventh aspect of the present disclosure includes an acquisition unit that acquires one or more parameters of an all-solid-state battery, a processing unit that generates an electric circuit model that simulates charging and discharging behavior of the all-solid-state battery based on the one or more parameters acquired by the acquisition unit and calculates battery characteristics of the all-solid-state battery based on the generated electric circuit model, and an output unit that outputs battery characteristic information indicating the battery characteristics calculated by the processing unit.

[0028] This has the advantage that the battery characteristics of the all-solid-state battery are calculated using an electric circuit model, which makes it easier to shorten the processing time for calculating the battery characteristics of the all-solid-state battery compared to simulating the battery characteristics of the all-solid-state battery using a continuum model.

[0029] Furthermore, for example, a program according to an eighth aspect of the present disclosure causes a computer to execute the steps of acquiring one or more parameters of an all-solid-state battery, generating an electric circuit model that simulates the charge / discharge behavior of the all-solid-state battery based on the acquired one or more parameters, calculating battery characteristics of the all-solid-state battery based on the generated electric circuit model, and outputting battery characteristic information indicating the calculated battery characteristics.

[0030] This has the advantage that the battery characteristics of the all-solid-state battery are calculated using an electric circuit model, which makes it easier to shorten the processing time for calculating the battery characteristics of the all-solid-state battery compared to simulating the battery characteristics of the all-solid-state battery using a continuum model.

[0031] Furthermore, for example, a display control method according to a ninth aspect of the present disclosure receives input of one or more parameters of an all-solid-state battery, then generates an image showing battery characteristics of the all-solid-state battery based on the one or more input parameters, and displays the generated image on a display unit.

[0032] This has the advantage that it is possible to determine whether the battery characteristics of the all-solid-state battery are as desired by the user, making it easier to design an all-solid-state battery having the desired battery characteristics.

[0033] Furthermore, for example, in a display control method according to a tenth aspect of the present disclosure, in the ninth aspect, the image may represent a relationship between an average discharge voltage and an energy capacity of the all-solid-state battery.

[0034] This has the advantage that it is possible to determine whether the average discharge voltage and energy capacity of the all-solid-state battery have the characteristics desired by the user, making it easier to design an all-solid-state battery having the desired battery characteristics.

[0035] Furthermore, for example, in a display control method according to an eleventh aspect of the present disclosure, in the tenth aspect, the image may be a scatter plot in which each point indicates the battery characteristic of the all-solid-state battery.

[0036] This has the advantage that by looking at the distribution of each point, the user can easily visually grasp the battery characteristics of an all-solid-state battery that can be realized using one or more parameters, making it easier to design an all-solid-state battery with desired battery characteristics.

[0037] Furthermore, for example, a display control system according to a twelfth aspect of the present disclosure includes a display control unit that, after receiving input of one or more parameters of an all-solid-state battery, causes a display unit to display an image indicating battery characteristics of the all-solid-state battery that is generated based on the one or more input parameters.

[0038] This has the advantage that it is possible to determine whether the battery characteristics of the all-solid-state battery are as desired by the user, making it easier to design an all-solid-state battery having the desired battery characteristics.

[0039] Furthermore, for example, a program according to a thirteenth aspect of the present disclosure causes a computer to execute a step of receiving input of one or more parameters of an all-solid-state battery, and then displaying on a display unit an image showing battery characteristics of the all-solid-state battery that is generated based on the one or more input parameters.

[0040] This has the advantage that it is possible to determine whether the battery characteristics of the all-solid-state battery are as desired by the user, making it easier to design an all-solid-state battery having the desired battery characteristics.

[0041] Furthermore, the characteristic processes included in the information processing method of the present disclosure can be realized as a computer program that causes a computer to execute the processes. Needless to say, such a computer program can be distributed on a computer-readable non-transitory recording medium such as a CD-ROM or via a communication network such as the Internet. The same applies to the display control method of the present disclosure.

[0042] Hereinafter, the embodiments will be specifically described with reference to the drawings.

[0043] The embodiments described below are comprehensive or specific examples of the present disclosure. The numerical values, shapes, materials, components, component placement and connection configurations, steps, and step order shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components that are not described in the independent claims that represent the highest concepts are described as optional components. Furthermore, each figure is a schematic diagram and is not necessarily an exact illustration. Furthermore, the same components are designated by the same reference numerals in each figure.

[0044] Furthermore, the information processing system according to the embodiment of the present disclosure may be configured so that all of the components are included in one computer, or may be configured as a system in which multiple components are distributed across multiple computers.

[0045] (Embodiment) An information processing system (information processing method or program) and a display control system (display control method or program) according to embodiments of the present disclosure will be described below with reference to the drawings.

[0046] [1. Configuration] First, the configurations of the information processing system and the display control system used in the embodiment will be described.

[0047] 1 is a block diagram showing an overall configuration including an information processing system 100 according to an embodiment. The information processing system 100 is configured as a computer such as a personal computer or a server. That is, the information processing system 100 may be realized by cloud computing, for example. In the embodiment, the information processing system 100 will be described as being a stationary computer.

[0048] The information processing system 100 includes an acquisition unit 11, a processing unit 12, an output unit 13, and a storage unit 14. Also connected to the information processing system 100 are an input unit 2, a display control unit 30, and a display unit 3. The input unit 2, the display control unit 30, and the display unit 3 are configured by an information terminal used by a user, such as a smartphone, a tablet terminal, or a personal computer. In the embodiment, the display control unit 30 and the display unit 3 configure a display control system 100A.

[0049] The input unit 2 and the display control unit 30 may both be connected to the information processing system 100 via a LAN (Local Area Network) or the like, or may be connected to the information processing system 100 via a network such as the Internet.

[0050] The input unit 2 is an input interface that accepts user input and is configured, for example, with a keyboard, a touch sensor, a touchpad, or a mouse. The input unit 2 accepts an input operation by the user and outputs a signal corresponding to the input operation to the information processing system 100. In the present disclosure, the display unit 3 and the input unit 2 are configured independently of each other, but they may be configured integrally, such as a touch panel. In the present disclosure, the information processing system 100 does not include a display control unit 30, a display unit 3, and an input unit 2, but these may be included. In other words, the information processing system 100 and the display control system 100A may be configured integrally.

[0051] The input unit 2 receives input of one or more parameters of the all-solid-state battery 4 (see FIG. 2). Here, the parameters are parameters that configure the all-solid-state battery 4 and are parameters related to the charge and discharge operations of the all-solid-state battery 4.

[0052] FIG. 2 is a diagram showing an example of the configuration of an all-solid-state battery 4. In the embodiment, one or more parameters are parameters assuming that the all-solid-state battery 4 has a configuration as shown in FIG. 2. As shown in FIG. 2, the all-solid-state battery 4 includes a positive electrode mixture layer 41 including a positive electrode active material 411 and a solid electrolyte 412, a negative electrode mixture layer 42 including a negative electrode active material 421 and a solid electrolyte 422, and a solid electrolyte layer (SE (Solid Electrolyte) layer) 43 serving as a separator located between the positive electrode mixture layer 41 and the negative electrode mixture layer 42. Note that the solid electrolyte 412 of the positive electrode mixture layer 41, the solid electrolyte 422 of the negative electrode mixture layer 42, and the solid electrolyte of the solid electrolyte layer 43 are generally made of different materials.

[0053] In the embodiment, the one or more parameters may include a cross-sectional area of ​​the cell, a thickness of the positive electrode mixture layer 41, a thickness of the negative electrode mixture layer 42, an electronic conductivity of each of the positive electrode mixture layer 41 and the negative electrode mixture layer 42, a volume ratio of the positive electrode active material 411 and the negative electrode active material 421, a volume ratio of the solid electrolyte 412 in the positive electrode mixture layer 41 and the solid electrolyte 422 in the negative electrode mixture layer 42, a porosity, an interface resistance, or a particle size of each of the positive electrode active material 411 and the negative electrode active material 421. In addition, the one or more parameters may include a density of the active material, a lithium ion diffusion coefficient of the active material, an OCV (Open Circuit Voltage) curve, a thickness of the solid electrolyte layer 43, a lithium ion conductivity of the solid electrolyte layer 43, or a volume ratio.

[0054] Here, the OCV characteristic curve is a function showing the change in potential (i.e., electromotive force) with the change in the lithium content (i.e., composition) of the positive electrode active material 411 and the negative electrode active material 421, and is a function specific to each material of the positive electrode active material 411 and the negative electrode active material 421. The lithium content of the positive electrode active material 411 and the negative electrode active material 421 corresponds one-to-one to the state of charge (SOC), which represents the state of charge of the battery. Therefore, the OCV curve may be considered as a function of SOC. SOC is usually expressed as a percentage, with 0% representing a fully discharged state and 100% representing a fully charged state. Furthermore, the one or more parameters may include other parameters as a function of SOC instead of the OCV curve. For example, it is known that the lithium ion diffusion coefficient of the active material depends on the SOC, and this diffusion coefficient may be included as a function of SOC.

[0055] The one or more parameters may include the electronic conductivity or shape of each of the positive electrode active material 411 and the negative electrode active material 421. The one or more parameters may also include the volume ratio, electronic conductivity, particle size, shape, or the like of the conductive additive in the positive electrode mixture layer 41 and the conductive additive in the negative electrode mixture layer 42.

[0056] The input unit 2 may accept an input of the film thickness of the all-solid-state battery 4 (i.e., the sum of the thickness of the positive electrode mixture layer 41, the thickness of the negative electrode mixture layer 42, and the thickness of the solid electrolyte layer 43) instead of accepting an input of the thickness of the positive electrode mixture layer 41, the thickness of the negative electrode mixture layer 42, and the thickness of the solid electrolyte layer 43. Furthermore, the input unit 2 may accept an input of the thickness of the solid electrolyte layer 43 and the ratio of the thickness of the positive electrode mixture layer 41 to the thickness of the negative electrode mixture layer 42 instead of accepting an input of the thickness of the positive electrode mixture layer 41, the thickness of the negative electrode mixture layer 42, and the thickness of the solid electrolyte layer 43.

[0057] Furthermore, the input unit 2 may accept, as one or more parameters, actual measurement values ​​or values ​​obtained by a simulation other than the simulation of the present disclosure.

[0058] Furthermore, the input unit 2 accepts input of condition information relating to conditions for charging and discharging the all-solid-state battery 4 as one or more parameters. The condition information may include, for example, the rate of charging and discharging the all-solid-state battery 4, the waveforms of the input current and output current of the all-solid-state battery 4, or the temperature of the all-solid-state battery 4. Here, the waveforms of the input current and output current of the all-solid-state battery 4 include, for example, a square wave or a pulse, and in other words, are parameters that indicate the time dependency of the input current and output current of the all-solid-state battery 4.

[0059] The display control unit 30 generates an image based on information output from the output unit 13 of the information processing system 100, and causes the display unit 3 to display the generated image, etc.

[0060] The display unit 3 displays images and the like under the control of the display control unit 30. The display unit 3 is, for example, a liquid crystal display, a plasma display, an organic EL (Electro-Luminescence) display, or the like, but is not limited to these.

[0061] The acquisition unit 11 acquires one or more parameters (including condition information) received by the input unit 2. The acquisition unit 11 is an entity that executes the step of acquiring one or more parameters in the information processing method of the present disclosure.

[0062] The processing unit 12 generates an electric circuit model 5 (see FIG. 3) that simulates the charging and discharging behavior of the all-solid-state battery 4, based on one or more parameters acquired by the acquisition unit 11. In the embodiment, the processing unit 12 generates the electric circuit model 5 by calculating the values ​​of each element (circuit parameters) of the electric circuit model 5 shown in FIG. 3, based on one or more parameters. The processing unit 12 is an entity that executes the step of generating the electric circuit model 5.

[0063] Fig. 3 is a diagram showing an example of the electric circuit model 5. The electric circuit model 5 shown in Fig. 3 is a model that can take into account the one-dimensional distribution of a physical quantity, such as current or potential, inside the all-solid-state battery 4 in a direction passing through the positive and negative electrodes, and is one of the simple models that takes into account the spatial distribution inside the all-solid-state battery 4. In the electric circuit model 5, the all-solid-state battery 4 is expressed as an equivalent circuit including one or more voltage sources and one or more internal resistances.

[0064] In Fig. 3, "I" represents the current flowing through the all-solid-state battery 4. In the example shown in Fig. 3, "I" represents the charging current, but in the reverse direction, it represents the discharging current. Also in Fig. 3, Vc represents the positive electrode side potential, and Va represents the negative electrode side potential.

[0065] As shown in FIG. 3, the positive electrode mixture layer 41 in the electric circuit model 5 has a plurality of electronic resistances R e,c and the electromotive force E due to multiple OCVs c,1 ,…,E c,n and multiple interface resistances R int,c and multiple ionic resistances R ion,c The negative electrode mixture layer 42 in the electric circuit model 5 includes a plurality of electronic resistances R e,a and the electromotive force E due to multiple OCVs a,1 ,…,E a,n and multiple interface resistances R int,a and multiple ionic resistances R ion,a The solid electrolyte layer 43 in the electric circuit model 5 includes the resistance R of the solid electrolyte layer. SE It contains as an element.

[0066] Here, assuming that the spatial distribution inside the all-solid-state battery 4 is treated discretely and that the positive electrode mixture layer 41 and the negative electrode mixture layer 42 are each divided into n (n is an integer of 2 or more), the positive electrode mixture layer 41 in the electric circuit model 5 has n electronic resistances R e,c and the electromotive force E due to n OCVs c,1 ,…,E c,n and n interface resistances R int,c and n ionic resistances R ion,cSimilarly, in the negative electrode mixture layer 42 in the electric circuit model 5, n electronic resistances R e,a and the electromotive force E due to n OCVs a,1 ,…,E a,n and n interface resistances R int,a and n ionic resistances R ion,a and are arranged as elements. In the embodiment, the processing unit 12 generates the electric circuit model 5 with n=20. Note that the number of divisions in the positive electrode mixture layer 41 and the number of divisions in the negative electrode mixture layer 42 may be different from each other.

[0067] In the electric circuit model 5 shown in FIG. 3, any electronic resistance R e,c ,R e,a The interface resistance R int,c ,R int,a The ionic resistance R ion,c ,R ion,a On the other hand, the electromotive force E c,1 ,…,E c,n ,E a,1 ,…,E a,n are all expressed by the same function of SOC, but since SOC is generally a value that depends on location, these values ​​are different from each other.

[0068] The elements of the electric circuit model 5 are not limited to those shown in Fig. 3. That is, the electric circuit model 5 may have elements different from those shown in Fig. 3. Furthermore, the electric circuit model 5 is not limited to the model shown in Fig. 3, and may be another model.

[0069] The processing unit 12 may calculate the values ​​of all elements (circuit parameters) in the electric circuit model 5 based on one or more parameters acquired by the acquisition unit 11. Furthermore, the processing unit 12 may use actual measured values ​​for some of the circuit parameters in the electric circuit model 5.

[0070] An example of calculating the circuit parameters will be described below. For example, the ionic resistance R of the positive electrode mixture layer 41 in the electric circuit model 5 is ion,cThe value of is the cross-sectional area of ​​the cell A cell and the effective ionic conductivity σ in the positive electrode mixture layer 41 ioneff,c It can be calculated by taking the reciprocal of the product of (R ion,c =1 / (A cell σ ioneff,c )). This effective ionic conductivity σ ioneff,c can be calculated by an electrode structure simulation using software for material development such as GeoDict (registered trademark). Specifically, first, the processing unit 12 calculates the volume ratio, porosity, and particle size of the positive electrode active material 411 in the positive electrode mixture layer 41, as well as the volume ratio ε of the solid electrolyte 412 in the positive electrode mixture layer 41. ion,c , and particle size, the processing unit 12 generates an electrode structure model that is a composite of the positive electrode active material 411 and the solid electrolyte 412. Then, the processing unit 12 calculates the ionic conductivity σ of the solid electrolyte 412 in the positive electrode mixture layer 41 in the generated electrode structure model. ion,c By solving the equation for ionic conduction in the solid electrolyte 412 using ioneff,c That is, the processing unit 12 may generate an electrode structure model that simulates the structure of the all-solid-state battery by executing a simulation using one or more parameters, and calculate some of the circuit parameters in the electric circuit model 5 based on the generated electrode structure model.

[0071] The effective ionic conductivity σ ioneff,c can also be calculated by the method disclosed in the reference (P. Braun et al. “Assessment of all-solid-state lithium-ion batteries” Journal of Power Sources 393 (2018) 119-127). Specifically, the processing unit 12 calculates the tortuosity τ of the ion conduction path in the positive electrode mixture layer 41. ion,c , and the volume ratio ε of the solid electrolyte 412 in the positive electrode mixture layer 41 ion,c Using the formula σ ioneff,c =σ ion,c ε ion,c / τ ion,c The effective ionic conductivity σioneff,c Here, the curvature ratio τ ion,c =1 / ε ion,c α (α=0.9), but the tortuosity τ ion,c may be calculated.

[0072] The processing unit 12 calculates the effective ionic conductivity σ in the negative electrode mixture layer 42 in the electric circuit model 5. ioneff,a The processing unit 12 can also calculate the effective ionic conductivity σ in the negative electrode mixture layer 42 by using the method using the above-mentioned electrode structure model or the method disclosed in the above-mentioned reference. ioneff,a and the cross-sectional area of ​​the cell A cell The ionic resistance R of the negative electrode mixture layer 42 is calculated by calculating the reciprocal of the product of ion,a The value of can be calculated (R ion,a =1 / (A cell σ ioneff,a )).

[0073] In addition, for example, the electronic resistance R of the positive electrode mixture layer 41 in the electric circuit model 5 e,c is the cross-sectional area of ​​the cell A cell and the effective electronic conductivity σ of the positive electrode mixture layer 41. eleeff,c It can be calculated by taking the reciprocal of the product of (R e,c =1 / (A cell σ eleeff,c )) The effective electronic conductivity σ in the positive electrode mixture layer 41 eleeff,c For the positive electrode active material 411, the electrode structure model described above is generated, and the electronic conductivity σ ele,c The electrode structure model may be obtained by solving the equation for electronic conduction using the above formula. In this case, the electrode structure model may include a conductive additive. In this case, the processing unit 12 generates an electrode structure model by further adding the volume ratio, electronic conductivity, particle size, or shape of the conductive additive in addition to the parameters related to the positive electrode active material 411 and the solid electrolyte 412 in the positive electrode mixture layer 41, and solves the equation for electronic conduction on the generated electrode structure model to obtain the effective electronic conductivity σ of the positive electrode mixture layer 41. eleeff,c can be calculated.

[0074] The processing unit 12 calculates the effective electronic conductivity σ in the negative electrode mixture layer 42 in the electric circuit model 5. eleeff,a The processing unit 12 can also calculate the effective electronic conductivity σ in the negative electrode mixture layer 42 by using the method using the electrode structure model described above. eleeff,a and the cross-sectional area of ​​the cell A cell The electronic resistance R of the negative electrode mixture layer 42 is calculated by calculating the reciprocal of the product of e,a The value of can be calculated (R e,a =1 / (A cell σ eleeff,a )).

[0075] Furthermore, for example, the processing unit 12 calculates the resistance R of the solid electrolyte layer in the electric circuit model 5 based on the ionic conductivity, particle size, and thickness of the solid electrolyte 431 in the solid electrolyte layer 43. SE It is possible to calculate the following. Note that a description of the calculation method for other circuit parameters will be omitted here. Furthermore, the electromotive force by OCV and the interface resistance may both be actual measured values.

[0076] The processing unit 12 also calculates the battery characteristics of the all-solid-state battery 4 based on the generated electric circuit model 5. In the embodiment, the processing unit 12 calculates a charge / discharge curve (see FIG. 4 ), which is one of the main performance indexes of the all-solid-state battery 4, as the battery characteristics based on the generated electric circuit model 5 and condition information from among the one or more parameters acquired by the acquisition unit 11. The processing unit 12 also executes the step of calculating the battery characteristics of the all-solid-state battery 4.

[0077] 4 is a diagram showing an example of a charge / discharge curve of an all-solid-state battery 4. Here, the charge / discharge curve is a graph showing the correlation between the voltage of the all-solid-state battery 4 and the battery capacity (unit: "mAh" or "Ah") during charge / discharge. Specifically, the charge / discharge curve shows how the voltage increases in the charging process of the all-solid-state battery 4, or how the voltage decreases as the available charge is consumed in the discharging process.

[0078] The example shown in FIG. 4 shows charge / discharge curves for four C-rates: "1C," "0.3C," "0.1C," and "0.05C." Here, the C-rate is a dimensionless numerical value that represents the charge rate or discharge rate relative to the battery capacity. For example, the rate (current value) at which the battery capacity (unit: "Ah") is charged or discharged in one hour corresponds to "1C." In addition, in FIG. 4, the dashed line represents the charge / discharge curve of the all-solid-state battery 4 when actually measured, and the solid line represents the charge / discharge curve when calculated using an electric circuit model 5 corresponding to the all-solid-state battery 4.

[0079] The processing unit 12 executes a simulation using the electric circuit model 5 based on the current value (here, C rate) specified by the user in the condition information among one or more parameters acquired by the acquisition unit 11, and calculates the predicted voltage change in the charge / discharge process. The internal resistance of the all-solid-state battery 4 reflects an appropriate voltage change according to the C rate, taking into account the voltage drop that occurs during charge / discharge. The processing unit 12 integrates the voltage drop in each element and calculates the potential difference (V c -V a ) can be used to calculate the charge voltage or discharge voltage of the all-solid-state battery 4. A specific example of a method for calculating the charge voltage or discharge voltage of the all-solid-state battery 4 will be described in detail in [2. Operation] below.

[0080] In the embodiment, the processing unit 12 further calculates the average discharge voltage and energy capacity of the all-solid-state battery 4 as battery characteristics based on the calculated charge / discharge curve. The average discharge voltage can be calculated by integrating the voltage value from the start of discharge to the end of discharge of the all-solid-state battery 4 over time or capacity, and dividing the integrated value by the total discharge capacity (in other words, dividing the area below the target charge / discharge curve in FIG. 4 by the range of time or capacity that forms the charge / discharge curve). The energy capacity can be calculated by multiplying the total discharge capacity by the average discharge voltage.

[0081] The processing unit 12 may calculate battery characteristics other than the above-mentioned battery characteristics, or may calculate battery characteristics without going through a charge / discharge curve. The processing unit 12 may also calculate a potential distribution, an SOC distribution, or the like as internal information of the all-solid-state battery 4.

[0082] The output unit 13 outputs information about the image, etc. to the display control unit 30, thereby displaying the image, etc. on the display unit 3. The output unit 13 also outputs battery characteristic information indicating the battery characteristics calculated by the processing unit 12. The output unit 13 is the entity that executes the step of outputting the battery characteristic information in the information processing method of the present disclosure. Specifically, the output unit 13 outputs the battery characteristic information indicating the battery characteristics calculated by the processing unit 12 to the display control system 100A. As a result, the display control unit 30 of the display control system 100A generates an image indicating the battery characteristic information and displays the generated image on the display unit 3.

[0083] In the embodiment, the display control unit 30 of the display control system 100A generates a first image, for example, as shown in Fig. 5, and displays the generated first image on the display unit 3. Fig. 5 is a diagram showing an example of the first image displayed on the display unit 3 in the embodiment.

[0084] The first image is an image showing battery characteristic information (here, average discharge voltage and energy capacity) calculated by the processing unit 12. Specifically, the first image is a scatter plot, and each point represents battery characteristic information calculated by the processing unit 12. The processing unit 12 calculates a large amount of battery characteristic information required to generate the first image by repeating the process of calculating battery characteristics for each of a plurality of combinations of one or more variables among the one or more parameters. Note that in each combination, each variable is a value that can actually be taken.

[0085] 5, the one or more variables are the film thickness of the all-solid-state battery 4 (that is, the sum of the thickness of the positive electrode mixture layer 41, the thickness of the negative electrode mixture layer 42, and the thickness of the solid electrolyte layer 43), the volume ratio of the positive electrode active material 411 in the positive electrode mixture layer 41, and the volume ratio of the negative electrode active material 421 in the negative electrode mixture layer 42. The difference in the shape of each point in FIG. 5 represents the difference in film thickness of the all-solid-state battery 4.

[0086] Fig. 6 is a diagram showing another example of the first image displayed on the display unit 3 in the embodiment. For example, when the first image shown in Fig. 5 is displayed on the display unit 3, if the input unit 2 receives an input to select any point with a mouse pointer or the like, the battery characteristic information of the selected point is highlighted and displayed as shown in Fig. 6. In the example shown in Fig. 6, the energy capacity of the selected point is "Ci," the average discharge voltage is "Di," the film thickness of the all-solid-state battery 4 is "Ei," the volume ratio of the positive electrode active material 411 in the positive electrode mixture layer 41 is "Fi," and the volume ratio of the negative electrode active material 421 in the negative electrode mixture layer 42 is "Gi." In addition, in the example shown in Fig. 6, two orthogonal dotted lines passing through the selected point are displayed on the display unit 3.

[0087] Fig. 7 is a diagram showing yet another example of the first image displayed on the display unit 3 in the embodiment. For example, when the first image shown in Fig. 5 is displayed on the display unit 3, if the input unit 2 receives an input from the user instructing to display a boundary line, a boundary line between an area where points exist and an area where points do not exist is displayed on the display unit 3, as shown in Fig. 7. In addition, in the example shown in Fig. 7, when the input unit 2 receives an input to select any point on the boundary line with a mouse pointer or the like, the battery characteristic information of the selected point is displayed in an emphasized manner, similar to the example shown in Fig. 6.

[0088] By viewing the first image, the user can visually grasp the battery characteristics of the all-solid-state battery 4 that can be realized by realistic parameters. Furthermore, by viewing the first image, the user can visually grasp the theoretical limit values ​​of the battery characteristics of the all-solid-state battery 4. For example, in the example shown in FIG. 6, if the user wants to make the average discharge voltage of the all-solid-state battery 4 "D2" or higher, the user can visually grasp that the energy capacity will be "C4" or lower.

[0089] Therefore, by looking at the first image, the user can easily understand whether or not it is possible to design an all-solid-state battery 4 having the battery characteristics desired by the user (in other words, whether or not there are one or more parameters that satisfy the battery characteristics desired by the user).

[0090] The information processing system 100 according to the embodiment can generate the first image at a very high speed. For example, the first image shown in FIG. 5 has a total of 810 points, meaning that the processing unit 12 executes the process of calculating the battery characteristics a total of 810 times, with a total processing time of approximately 37 minutes. Note that the machine specifications (i.e., the performance of the processing unit 12) in this case are a Xeon® W-2223 CPU manufactured by Intel® Corporation, with an operating frequency of 3.60 GHz.

[0091] When the processing of calculating battery characteristics by processing unit 12 is executed in a charge / discharge simulation using the BatteryDict module of GeoDict (registered trademark), the processing time is approximately 11 hours. Therefore, if the processing is executed a total of 810 times, an unrealistically large amount of processing time is required compared to the information processing system 100 according to the embodiment.

[0092] Incidentally, the image showing the battery characteristic information (here, the average discharge voltage and the energy capacity) calculated by the processing unit 12 is not limited to a scatter diagram, and may be an image in another form. Below, a second image, a third image, and a fourth image that can be displayed on the display unit 3 instead of the first image will be described.

[0093] 8 is a diagram showing an example of a second image displayed on the display unit 3 in the embodiment. The second image is a three-dimensional graph in which the battery characteristic information calculated by the processing unit 12 is represented on a total of three axes: an axis indicating the energy capacity, an axis indicating the average discharge voltage, and an axis indicating the film thickness of the all-solid-state battery 4.

[0094] 9 is a diagram showing an example of a third image displayed on the display unit 3 in the embodiment. The third image is an image including a plurality of scatter plots in which the battery characteristic information calculated by the processing unit 12 is displayed for each film thickness of the all-solid-state battery 4.

[0095] 10 is a diagram showing an example of a fourth image displayed on the display unit 3 in the embodiment. The fourth image is an image including a plurality of contour lines that represent the battery characteristic information calculated by the processing unit 12, divided by film thickness of the all-solid-state battery 4. Each contour line represents the density of each point in the scatter plot.

[0096] Note that the image that can be displayed on the display unit 3 may be, for example, an image including a plurality of heat maps that represent the battery characteristic information calculated by the processing unit 12, divided by film thickness of the all-solid-state battery 4. Each heat map represents the density of each point in the scatter plot.

[0097] The storage unit 14 is a recording medium for storing data (including programs) used in various processes that can be executed by the information processing system 100. The recording medium is, for example, a hard disk drive, a RAM (Random Access Memory), a ROM (Read Only Memory), or a semiconductor memory. Note that such a recording medium may be volatile or non-volatile.

[0098] [2. Operation] The following describes the operation (that is, the information processing method) of the information processing system 100 according to the embodiment. Fig. 11 is a flowchart showing an example of the operation of the information processing system 100 according to the embodiment.

[0099] (Step S10) The acquisition unit 11 acquires one or more parameters (including condition information). In the embodiment, the acquisition unit 11 acquires one or more parameters (including condition information) received by the input unit 2.

[0100] (Step S11) The processing unit 12 generates the electric circuit model 5 based on the one or more parameters acquired by the acquisition unit 11. In the embodiment, the processing unit 12 generates the electric circuit model 5 by calculating the values ​​of each element (circuit parameters) of the electric circuit model 5 shown in Fig. 3 based on the one or more parameters.

[0101] (Step S12) The processing unit 12 calculates the battery characteristics of the all-solid-state battery 4 based on the generated electric circuit model 5. In the embodiment, the processing unit 12 calculates a charge / discharge curve (see FIG. 4 ), which is one of the main performance indexes of the all-solid-state battery 4, as the battery characteristics based on the generated electric circuit model 5 and condition information from among the one or more parameters acquired by the acquisition unit 11.

[0102] As already described, the processing unit 12 executes a simulation using the electric circuit model 5 to calculate a predicted voltage change in the charge / discharge process. A specific example of a method for calculating the charge voltage (or discharge voltage) of the all-solid-state battery 4 will be described below with reference to Fig. 12. Fig. 12 is a flowchart showing an example of calculating the charge voltage (or discharge voltage) of the all-solid-state battery 4 from the electric circuit model 5 by the information processing system 100 according to the embodiment.

[0103] (Step S120) The processing unit 12 calculates the values ​​of each element of the electric circuit model 5 (parameters for each circuit) and the end time t end Here, the processing unit 12 obtains the electronic resistance R e,c ,R e,a and the electromotive force E by the OCV c,1 ,…,E c,n ,E a,1 ,…,E a,n and the interface resistance R int,c ,R int,a and ionic resistance R ion,c ,R ion,a and the resistance of the solid electrolyte layer R SE and the charging current (or discharging current) I as circuit parameters. endInstead of the cut-off voltage V that triggers the end of the simulation, cut may be obtained.

[0104] (Step S121) The processing unit 12 detects the electromotive force E c,1 ,…,E c,n ,E a,1 ,…,E a,n is set as the initial value in the SOC function.

[0105] (Step S122) The processing unit 12 calculates the partial current flowing through each element group in the electric circuit model 5. Here, the element group refers to each group when the positive electrode mixture layer 41 and the negative electrode mixture layer 42 are each divided into n groups. In the embodiment, each element group in the positive electrode mixture layer 41 has one electronic resistance R e,c and the electromotive force E by one OCV c,m (m is an integer satisfying 1≦m≦n) and one interface resistance R int,c and one ionic resistance R ion,c Each element group in the negative electrode mixture layer 42 has one electronic resistance R e,a and the electromotive force E by one OCV a,m and one interface resistance R int,a and one ionic resistance R ion,a Hereinafter, the partial current flowing through each of the n element groups in the positive electrode mixture layer 41 will be referred to as "i c,1 ,i c,2 ,…,i c,n (See FIG. 3). In the following, the partial currents flowing through the n element groups in the negative electrode mixture layer 42 are referred to as "i a,1 ,i a,2 ,…,i a,n (See Figure 3).

[0106] In the electric circuit model 5 shown in FIG. 3, there are n-1 closed circuits in each of the positive electrode mixture layer 41 and the negative electrode mixture layer 42. By applying Kirchhoff's law to each closed circuit, it is possible to derive the following equation (1), which is expressed by the parameters for each circuit, the charge current (or discharge current) I, and the partial current. Here, the equation (1) for the negative electrode mixture layer 42 will be specifically described. Note that "k" in equation (1) is an integer that satisfies 1≦k≦n-1.

[0107]

number

[0108] Furthermore, by combining the above equation (1) with the following equation (2), which expresses that the charging current (or discharging current) I is equal to the sum of the partial currents, n simultaneous linear equations are obtained using the n partial currents as variables in the negative electrode mixture layer 42. Similarly, for the positive electrode mixture layer 41, n simultaneous linear equations are obtained using the n partial currents as variables.

[0109]

number

[0110] Therefore, by solving n simultaneous linear equations for each of the positive electrode mixture layer 41 and the negative electrode mixture layer 42, the partial current i c,1 ,i c,2 ,…,i c,n and the partial current i flowing through each of the n element groups in the negative electrode mixture layer 42. a,1 ,i a,2 ,…,i a,n It is possible to calculate

[0111] (Step S123) The processing unit 12 calculates the lithium ion concentration on the surface of the active material in the mixture layer using a diffusion equation with the calculated partial currents flowing through each element group as boundary conditions. Here, a calculation method will be described assuming that each active material is spherical, has the same radius, is uniformly distributed in the mixture layer, and lithium ions flow in and out of the surface evenly. Under this assumption, the current density i of the current flowing into the surface of each active material is * is the formula i * = a·i / (3ε·d), where "a" is the radius of the active material, "i" is the current density of the partial current flowing into the element group, "ε" is the volume ratio of the active material in the mixture layer, and "d" is the length of the element group (length in the direction perpendicular to the cell cross section). The current density i of the partial current can be calculated by dividing the partial current by the cross-sectional area of ​​the cell.

[0112] Based on the above assumption, the lithium ion concentration in each active material is spherically symmetric. When expressed in spherical coordinates with the center of the active material as the origin, the lithium ion concentration c can be expressed as a function c(r) of the radial coordinate r. Here, the center of the active material corresponds to r=0, and the surface of the active material corresponds to r=R. s Then, the lithium ion concentration c(r) is expressed by the spherically symmetric diffusion equation shown in the following equation (3) and the boundary condition shown in equation (4). Note that in equations (3) and (4), "D" represents the lithium ion diffusion coefficient in the active material, and "e" represents the elementary charge.

[0113]

number

[0114] Then, the processing unit 12 calculates the lithium ion concentration c(R s ) is calculated. Hereafter, the calculated lithium ion concentration c(R s ) converted to SOC local It is called.

[0115] (Step S124) The processing unit 12 calculates the SOC local Using this, the potential difference between the positive and negative electrodes (i.e., the battery voltage) V c -V a Here, the OCV curve is expressed by the SOC function EOCV(SOC), and the SOC calculated for each element group is calculated as follows: local Using EOCV(SOC local ) and calculate the electromotive force E due to the OCV in each element group. c,1 ,…,E c,n ,E a,1 ,…,E a,n Then, the processing unit 12 updates the electromotive force E by the updated OCV. c,1 ,…,E c,n ,E a,1 ,…,E a,n Using the following equation (5), the potential difference (battery voltage) V c -V a Calculate.

[0116]

number

[0117] (Step S125) The processing unit 12 determines whether the current time of the simulation is the end time t end If the current time of the simulation has not reached the end time t (step S125: No), the processing unit 12 executes step S126. end If it is reached (step S125: Yes), the simulation is ended.

[0118] In step S125, the potential difference (battery voltage) V c -V a and cut-off voltage V cut Specifically, in the simulation during charging, the processing unit 12 may compare the potential difference (battery voltage) V c -V a is the cut-off voltage V cutIf the potential difference (battery voltage) V is less than the threshold voltage (V) (step S125: No), the processing unit 12 executes step S126. c -V a is the cut-off voltage V cut If the potential difference (battery voltage) V exceeds the threshold (step S125: Yes), the simulation is terminated. c -V a is the cut-off voltage V cut If it is greater than (step S125: No), step S126 is executed. c -V a is the cut-off voltage V cut If it is lower than (step S125: Yes), the simulation is ended.

[0119] (Step S126) The processing unit 12 updates the time t. Furthermore, if the charging current (or discharging current) I has time dependency, the processing unit 12 updates the charging current (or discharging current) I. After that, the processing unit 12 executes step S122.

[0120] (Step S13) 11 , the output unit 13 outputs battery characteristic information indicating the battery characteristics calculated by the processing unit 12. In the embodiment, the output unit 13 outputs the battery characteristic information indicating the battery characteristics calculated by the processing unit 12 to the display control system 100A. As a result, the display control unit 30 of the display control system 100A generates an image indicating the battery characteristic information and causes the display unit 3 to display the generated image.

[0121] Fig. 13 is a flowchart showing an example of generation of an image (for example, a first image) showing battery characteristics of the all-solid-state battery 4 by the information processing system 100 according to the embodiment. Note that steps S20 to S23 in Fig. 13 are the same as steps S10 to S13 in Fig. 11, and therefore description thereof will be omitted here.

[0122] (Step S24) If the processing unit 12 has not completed the process of calculating the battery characteristics for all combinations of one or more variables among the one or more parameters (step S24: No), the processing unit 12 executes step S25. On the other hand, if the processing unit 12 has completed the process of calculating the battery characteristics for all combinations (step S24: Yes), the processing unit 12 executes step S26.

[0123] (Step S25) The processing unit 12 updates any one of the one or more variables. After that, the processing unit 12 executes step S21. As a result, the processing unit 12 executes the process of calculating battery characteristics for the combinations for which the process has not yet been executed.

[0124] (Step S26) The output unit 13 outputs the plurality of pieces of battery characteristic information calculated by the processing unit 12 to the display control system 100A, causing the display control unit 30 of the display control system 100A to generate an image (for example, a first image). As a result, the generated image is displayed on the display unit 3.

[0125] [3. Advantages] As described above, the information processing system 100 (information processing method) according to the embodiment employs a simulation method using an electric circuit model 5 as a new approach for quickly and efficiently evaluating the battery characteristics of an all-solid-state battery 4. The electric circuit model 5 is a simple yet robust modeling method that expresses the behavior of a battery using electric circuit elements such as resistors or electrochemical voltage sources. This approach makes it possible to associate the ionic conduction of the solid electrolyte, the electronic conduction of the electrode material, and the reaction process at the interface between the electrode and the solid electrolyte with each element of the electric circuit.

[0126] The information processing system 100 according to the embodiment calculates the battery characteristics of the all-solid-state battery 4 using the electric circuit model 5, which has the advantage of easily shortening the processing time for calculating the battery characteristics of the all-solid-state battery 4. Specifically, a simulation of the battery characteristics of the all-solid-state battery 4 using the electric circuit model 5 can significantly shorten the calculation time compared to a simulation of the battery characteristics of the all-solid-state battery 4 using a continuum model. Therefore, by using the information processing system 100 according to the embodiment, it is expected that the cycle of design changes and evaluation of the all-solid-state battery 4 can be speeded up.

[0127] Furthermore, the information processing system 100 according to the embodiment calculates the battery characteristics of the all-solid-state battery 4 using the electric circuit model 5, and therefore has the advantage that various design-related variables of the all-solid-state battery 4 (for example, the thickness of the solid electrolyte, the conductivity, or the constituent materials of the electrodes) can be set as parameters of the circuit elements in the electric circuit model 5, making it easy to evaluate various designs of the all-solid-state battery 4.

[0128] Furthermore, the information processing system 100 according to the embodiment calculates the battery characteristics of the all-solid-state battery 4 using the electric circuit model 5, which has the advantage that the characteristics of the interface between the electrode and the solid electrolyte can be expressed by circuit elements, making it easier to analyze the influence of the interface on the performance of the all-solid-state battery 4.

[0129] As described above, the information processing system 100 according to the embodiment has the advantages described above, and therefore is likely to accelerate the development process of the all-solid-state battery 4 and contribute to improving the battery performance and reducing the manufacturing cost of the all-solid-state battery 4. Furthermore, the increased speed of the simulation is expected to significantly contribute to improving the production efficiency of the all-solid-state battery 4, such as reducing the number of prototypes of the all-solid-state battery 4 or optimizing the selection of materials for the all-solid-state battery 4.

[0130] [4. Back analysis] However, the simulation based on the continuum model disclosed in Non-Patent Document 1 has a problem in that when a user sets the battery characteristics of a battery desired by the user, it is not possible to perform an inverse analysis to calculate one or more parameters that can realize the battery characteristics. Furthermore, the above simulation also has a problem in that when a user sets the battery characteristics of a battery obtained by actual measurement, it is not possible to perform an inverse analysis to predict the internal state of the battery that can realize the battery characteristics. Furthermore, since the above simulation is a simulation for a lithium-ion battery, it is not intended to be applied to an all-solid-state battery 4.

[0131] In contrast, the information processing system 100 according to the embodiment can solve the above problem. An example of the operation of the information processing system 100 according to the embodiment for solving the above problem will be described below. Fig. 14 is a flowchart showing another example of the operation of the information processing system 100 according to the embodiment.

[0132] (Step S30) The acquisition unit 11 acquires target battery characteristic information indicating the battery characteristics desired by the user of the all-solid-state battery 4. In the embodiment, the acquisition unit 11 acquires the target battery characteristic information received by the input unit 2.

[0133] (Step S31) The acquisition unit 11 acquires the initial values ​​of the parameters. Note that the acquisition unit 11 may acquire the initial values ​​of the parameters prepared in advance in the information processing system 100, instead of the initial values ​​of the parameters received by the input unit 2.

[0134] (Step S32) The processing unit 12 generates an electric circuit model 5 based on the one or more parameters acquired by the acquisition unit 11, and calculates the battery characteristics of the all-solid-state battery 4 based on the generated electric circuit model 5. Step S32 is the same as steps S11 and S12 in the operation example shown in FIG.

[0135] (Step S33) The processing unit 12 compares the target battery characteristic information acquired by the acquisition unit 11 with the battery characteristic information indicating the battery characteristics calculated by the processing unit 12. For example, an evaluation function based on the target battery characteristic information and the calculated battery characteristic information is defined. Then, the processing unit 12 determines that the battery characteristic information satisfies the target battery characteristic information if the evaluation function is smaller than a threshold value, and determines that the battery characteristic information does not satisfy the target battery characteristic information if the evaluation function is equal to or greater than the threshold value.

[0136] Note that when there are multiple types of target battery characteristic information (e.g., average discharge voltage, energy capacity, etc.), the processing unit 12 compares the evaluation function with a threshold for each piece of target battery characteristic information (comparison between battery characteristic information and target battery characteristic information). Alternatively, the processing unit 12 may multiply multiple evaluation functions set for each piece of target battery characteristic information by weighting coefficients, add the resulting evaluation functions, and compare the evaluation function with a threshold. In this case, compared to when an evaluation function is set for each piece of target battery characteristic information, it is expected that the efficiency of optimization will be improved depending on the setting of the weighting coefficient when differentiating the evaluation function in the optimization algorithm used in step S37, which will be described later, for example.

[0137] If the battery characteristic information does not satisfy the target battery characteristic information (step S33: No), the processing unit 12 executes step S36. On the other hand, if the battery characteristic information satisfies the target battery characteristic information (step S33: Yes), the processing unit 12 executes step S34.

[0138] (Step S34) If the processing unit 12 searches for parameters different from the parameters when the battery characteristic information first satisfied the target battery characteristic information in step S33 (step S34: Yes), the processing unit 12 executes step S37. On the other hand, if the processing unit 12 does not search for other parameters (step S34: No), the processing unit 12 executes step S35. Whether or not to search for other parameters can be set by the user as appropriate.

[0139] (Step S35) The output unit 13 outputs one or more parameters that satisfy the target battery characteristics calculated by the processing unit 12 to the display control system 100A, causing the display control unit 30 of the display control system 100A to generate an image representing the one or more parameters. The generated image is then displayed on the display unit 3. By viewing the image, the user can understand the one or more parameters that can achieve the target battery characteristics. The image displayed on the display unit 3 may be in a table format or a graph format. The output unit 13 may also output the results as a file.

[0140] (Step S36) The processing unit 12 determines whether step S37, which will be described later, has been executed a predetermined number of times. If step S37 has not been executed a predetermined number of times (step S36: No), the processing unit 12 executes step S37. On the other hand, if step S37 has been executed a predetermined number of times (step S36: Yes), the processing unit 12 executes step S38.

[0141] (Step S37) The processing unit 12 changes at least a part of the one or more parameters. Then, the processing unit 12 executes step S32. Specifically, the processing unit 12 changes at least a part of the one or more parameters by executing an optimization algorithm of an objective function configured from the evaluation function and threshold value used in step S33. For example, the optimization algorithm may be grid search, random search, Bayesian optimization, evolutionary algorithm, simulated annealing, or the like.

[0142] For example, when a grid search is employed as the optimization algorithm, the processing unit 12 sets an order for all combinations of one or more parameters in any range, and updates at least some of the one or more parameters according to the order.

[0143] Furthermore, for example, when a random search is adopted as the optimization algorithm, the processing unit 12 updates at least a portion of the one or more parameters by randomly selecting parameters using pseudo-random numbers from all combinations within any range of the one or more parameters.

[0144] Furthermore, for example, when Bayesian optimization is adopted as the optimization algorithm, the processing unit 12 selects parameters to be updated and updates at least a portion of one or more parameters by modeling the behavior of the objective function using a probabilistic model such as a Gaussian process.

[0145] Furthermore, for example, when an evolutionary algorithm is adopted as the optimization algorithm, the processing unit 12 searches for and improves a solution through a population based on the principle of natural selection, and further updates at least a part of one or more parameters through "crossover" and "mutation."

[0146] Furthermore, for example, when simulated annealing is employed as the optimization algorithm, the acquisition unit 11 sets the "temperature" using an optimization method that mimics a cooling process, and updates at least a part of one or more parameters based on the temperature.

[0147] (Step S38) When the processing unit 12 executes a search for parameters different from the parameters when the battery characteristic information first satisfied the target battery characteristic information, i.e., when step S32 is executed after step S34: Yes and step S37, the output unit 13 outputs one or more parameters that satisfy the target battery characteristics calculated by the processing unit 12 in the initial step S32 to the display control system 100A. The one or more parameters are a parameter set consisting of one or more groups. The output unit 13 also causes the display control unit 30 of the display control system 100A to generate an image representing the one or more parameters. The generated image is then displayed on the display unit 3. The user can then understand the one or more parameters that can achieve the target battery characteristics by viewing the image. The image displayed on the display unit 3 may be in a table format or a graph format. The output unit 13 may also output the results as a file.

[0148] Furthermore, if the battery characteristic information never satisfies the target battery characteristic information, that is, if the determination in step S33: No continues without a determination of step S33: Yes being made even once until the number of executions reaches a predetermined number in step S36, the output unit 13 outputs information indicating that the processing unit 12 was unable to calculate one or more parameters that satisfy the target battery characteristics to the display control system 100A, thereby causing the display control unit 30 of the display control system 100A to generate a result image. As a result, the result image is displayed on the display unit 3. Then, by looking at the result image, the user can understand that one or more parameters that can achieve the target battery characteristics could not be calculated.

[0149] As described above, the information processing system 100 according to the embodiment is capable of performing inverse analysis (steps S31 to S34) to search for one or more parameters that satisfy the user's desired battery characteristics of the all-solid-state battery 4. Furthermore, when the information processing system 100 according to the embodiment causes the acquisition unit 11 to acquire information indicating the battery characteristics of the all-solid-state battery 4 obtained by actual measurement by the user as target battery characteristic information in step S30, it is also possible to perform inverse analysis to search for one or more parameters that satisfy the battery characteristics, that is, to predict the internal state of the all-solid-state battery 4 that can realize the battery characteristics.

[0150] [5. UI (User Interface)] The following describes, with reference to the drawings, the UI displayed on the display unit 3 when one or more parameters are input through the input unit 2 of the information processing system 100 according to the embodiment.

[0151] FIG. 15 is a diagram showing an example of a UI for inputting one or more parameters in an embodiment. The display control unit 30 generates an input UI in a table format, for example, as shown in FIG. 15, and displays the generated input UI on the display unit 3. In the example shown in FIG. 15, the input UI has a first column indicating the type of each parameter, such as "positive electrode mixture layer thickness" or "positive electrode active material particle shape," a second column for inputting the numerical value of each parameter, and a third column for inputting the unit of each parameter. The user can input each parameter by inputting the numerical value of each parameter in the second column and selecting the unit of each parameter from several options.

[0152] When inputting an OCV curve, for example, an input UI other than the table may be provided in the input UI. The user may input the OCV curve in the form of a function in the input UI, may input (upload) tabular data representing the OCV curve, or may input (upload) an image on which a function representing the OCV curve is plotted.

[0153] FIG. 16 is a diagram showing another example of a UI for inputting one or more parameters in an embodiment. The display control unit 30 generates an input UI in the form of a GUI (Graphical User Interface), for example, as shown in FIG. 16, and displays the generated input UI on the display unit 3. In the example shown in FIG. 16, each parameter, such as "positive electrode mixture layer thickness" or "positive electrode active material particle shape," is visually displayed, and the numerical value of each parameter is entered in an input field corresponding to each parameter. The user can input each parameter by entering a numerical value in the input field for each parameter.

[0154] 15 and the input UI shown in Fig. 16 may be used in combination by, for example, simultaneously displaying these input UIs on the display unit 3. For example, when a user inputs any parameter in the input UI shown in Fig. 15, the input of that parameter may be reflected in the input UI shown in Fig. 16. Conversely, when a user inputs any parameter in the input UI shown in Fig. 16, the input of that parameter may be reflected in the input UI shown in Fig. 15.

[0155] (Variation) While the information processing system (information processing method) and display control system (display control method) according to one or more aspects of the present disclosure have been described based on the embodiments, the present disclosure is not limited to the above-described embodiments. As long as the modifications do not deviate from the spirit of the present disclosure, various modifications conceivable by those skilled in the art may also be included in the present disclosure.

[0156] In the above-described embodiments, each component may be configured with dedicated hardware, or may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU (Central Processing Unit) or a processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0157] The following cases are also included in this disclosure:

[0158] (1) The at least one device is specifically a computer system consisting of a microprocessor, a ROM (Read Only Memory), a RAM (Random Access Memory), a hard disk unit, a display unit, a keyboard, a mouse, etc. A computer program is stored in the RAM or hard disk unit. The at least one device achieves its function when the microprocessor operates in accordance with the computer program. Here, the computer program is composed of a combination of multiple instruction codes that indicate instructions to the computer to achieve a predetermined function.

[0159] (2) Some or all of the components constituting at least one of the above devices may be configured as a single system LSI (Large Scale Integration). A system LSI is an ultra-multifunctional LSI manufactured by integrating multiple components on a single chip, and specifically, is a computer system configured to include a microprocessor, ROM, RAM, etc. A computer program is stored in the RAM. The system LSI achieves its functions when the microprocessor operates in accordance with the computer program.

[0160] (3) Some or all of the components constituting at least one of the above devices may be configured as an IC card or a standalone module that can be attached to the device. The IC card or module is a computer system composed of a microprocessor, ROM, RAM, etc. The IC card or module may include the above-mentioned ultra-multifunctional LSI. The IC card or module achieves its functions when the microprocessor operates according to a computer program. This IC card or module may be tamper-resistant.

[0161] (4) The present disclosure may be embodied as the methods described above, a computer program for implementing these methods on a computer, or a digital signal comprising the computer program.

[0162] The present disclosure may also be a computer program or a digital signal recorded on a computer-readable recording medium, such as a flexible disk, a hard disk, a CD (Compact Disc)-ROM, a DVD, a DVD-ROM, a DVD-RAM, a BD (Blu-ray (registered trademark) Disc), or a semiconductor memory, or a digital signal recorded on such a recording medium.

[0163] The present disclosure may also be applied to transmitting a computer program or a digital signal via a telecommunications line, a wireless or wired communication line, a network such as the Internet, or data broadcasting.

[0164] Furthermore, the program or digital signal may be recorded on a recording medium and transferred, or the program or digital signal may be transferred via a network or the like, so that the program or digital signal may be implemented by another independent computer system. [Industrial Applicability]

[0165] The present disclosure has an effect of making it easier to grasp the battery characteristics of an all-solid-state battery to be designed, for example, and can be used in a computer device or system for displaying information about the battery characteristics. [Explanation of symbols]

[0166] 11 Acquisition Department 12 Processing section 13 Output section 14 Storage section 100 Information Processing Systems 100A Display Control System 2 Input section 3 Display section 30 Display control unit 4 All-solid-state battery 41 Positive electrode mixture layer 411 Cathode active material 412 Solid electrolyte 42 negative electrode mixture layer 421 Negative electrode active material 422 Solid electrolyte 43 Solid electrolyte layer 431 Solid electrolyte 5 Electrical Circuit Model

Claims

1. 1. A computer-implemented information processing method, comprising: obtaining one or more parameters of the solid-state battery; generating an electric circuit model that simulates the charge / discharge behavior of the all-solid-state battery based on the one or more acquired parameters; Calculating battery characteristics of the all-solid-state battery based on the generated electric circuit model; outputting battery characteristic information indicating the calculated battery characteristics; Information processing methods.

2. In the process of calculating the battery characteristics of the all-solid-state battery, repeatedly executing the process of calculating the battery characteristics for each of a plurality of combinations of one or more variables of the one or more parameters; The information processing method according to claim 1 .

3. In the process of generating the electric circuit model, generating an electrode structure model that simulates a structure of the all-solid-state battery by performing a simulation using the one or more parameters; calculating some circuit parameters in the electric circuit model based on the generated electrode structure model; The information processing method according to claim 1 .

4. In the process of calculating the battery characteristics, an average discharge voltage and an energy capacity of the all-solid-state battery are calculated as the battery characteristics. The information processing method according to claim 1 .

5. In the process of outputting the battery characteristics, outputting an image showing the relationship between the average discharge voltage and the energy capacity of the all-solid-state battery to a display unit; The information processing method according to claim 4.

6. further acquiring target battery characteristic information indicating the target battery characteristics of the all-solid-state battery; comparing the target battery characteristic information with the battery characteristic information; If the battery characteristic information satisfies the target battery characteristic information, a process of outputting the one or more parameters that satisfy the target battery characteristic is executed. The information processing method according to any one of claims 1 to 5.

7. an acquisition unit that acquires one or more parameters of the all-solid-state battery; generating an electric circuit model that simulates the charging and discharging behavior of the all-solid-state battery based on the one or more parameters acquired by the acquisition unit; and a processing unit that calculates battery characteristics of the all-solid-state battery based on the generated electric circuit model; an output unit that outputs battery characteristic information indicating the battery characteristics calculated by the processing unit, Information processing system.

8. obtaining one or more parameters of the solid-state battery; generating an electric circuit model that simulates the charge / discharge behavior of the all-solid-state battery based on the one or more acquired parameters; Calculating battery characteristics of the all-solid-state battery based on the generated electric circuit model; and outputting battery characteristic information indicating the calculated battery characteristics. program.

9. after receiving input of one or more parameters of the all-solid-state battery, generating an image showing battery characteristics of the all-solid-state battery based on the input one or more parameters, and displaying the generated image on a display unit; Display control method.

10. The image shows the relationship between the average discharge voltage and the energy capacity of the all-solid-state battery. The display control method according to claim 9.

11. The image is a scatter plot in which each point indicates the battery characteristics of the all-solid-state battery. The display control method according to claim 10.

Images