Battery diagnostic apparatus and method

Abstract

A battery diagnostic apparatus according to one embodiment of the present document may comprise: a memory for storing at least one instruction; and one or more processors for executing the at least one instruction, wherein the one or more processors: identify at least one of a first degradation index, a second degradation index for a first component, a third degradation index for a second component, and any combination thereof on the basis of a physical model indicating the state of a battery and battery data of a battery cell included in the battery; and diagnose the state of the battery on the basis of the at least one of the first degradation index, the second degradation index, the third degradation index, and any combination thereof.

Description

Battery diagnostic device and method

[0001] Cross-citation with related applications

[0002] The present application claims the benefit of priority based on Korean Patent Application No. 10-2024-0139131 filed on October 14, 2024, and includes all contents disclosed in the document of said patent application as part of this specification.

[0003] Technology field

[0004] The embodiments disclosed in this document relate to a battery diagnostic device and a method thereof.

[0005] Recently, active research and development on secondary batteries has been underway. Here, secondary batteries are rechargeable batteries that can be interpreted to encompass conventional Ni / Cd and Ni / MH batteries, as well as recent lithium-ion batteries. With their scope of application expanding to include power sources for electric vehicles, they are garnering attention as a next-generation energy storage medium.

[0006] With the proliferation of various electronic devices driven by the Fourth Industrial Revolution, battery usage is rapidly increasing. As the usage period of batteries lengthens, physical and chemical changes may occur in the positive and negative plates. Based on these physical and chemical changes in the positive and negative plates, battery performance may degrade. In particular, the degradation of the negative plate can cause problems such as reduced battery capacity, increased internal resistance, and shortened battery life.

[0007] Accordingly, models are being developed to monitor battery cell degradation in real time and identify degradation indicators based on the monitoring results. In particular, the importance of models for identifying degradation indicators is increasing due to the diversification of materials used in negative electrode plates.

[0008] According to the embodiments disclosed in this document, the present invention aims to provide a battery diagnostic device and a method that extend the lifespan of a battery cell by controlling the operation of the battery cell through obtaining a degradation index for each component of the negative plate of the battery cell.

[0009] According to the embodiments disclosed in this document, the present invention aims to provide a battery diagnostic device and a method that contribute to improving the stability of a battery cell by obtaining component-specific degradation indicators of the negative plate of a battery cell.

[0010] According to the embodiments disclosed in this document, the present invention aims to provide a battery diagnostic device and a method that improve the accuracy of diagnosing the condition of a battery cell by obtaining component-specific degradation indicators of the negative plate of a battery cell.

[0011] According to the embodiments disclosed in this document, a battery diagnostic device and a method are provided for obtaining a degradation index by component of the negative plate of a battery cell by inputting parameters according to the component of the negative plate of the battery cell into a physical model.

[0012] The technical problems of this document are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art from the descriptions below.

[0013] A battery diagnostic device according to one embodiment of the present document may include a memory for storing at least one instruction and one or more processors for executing said at least one instruction.

[0014] According to one embodiment, the one or more processors identify at least one of a first degradation indicator, a second degradation indicator for a first component, a third degradation indicator for a second component, or any combination thereof, based on a physical model representing the state of a battery and battery data of a battery cell included in the battery, and can diagnose the state of the battery based on at least one of the first degradation indicator, the second degradation indicator, the third degradation indicator, or any combination thereof.

[0015] According to one embodiment, the first degradation index may include an LLI (loss of lithium inventory) comprising a first parameter related to lithium loss in the middle of life (MOL) relative to the beginning of life (BOL) of the battery cell.

[0016] According to one embodiment, the second degradation index may include a loss of active material (LAM) comprising a second parameter related to the loss of the first component in MOL relative to BOL at the electrode plate of the battery cell, and the third degradation index may include a loss of active material (LAM) comprising a second parameter related to the loss of the second component in MOL relative to BOL at the electrode plate.

[0017] According to one embodiment, the physical model may include a P2D (Pseudo two-dimensional; P2D) model.

[0018] According to one embodiment, the first component may include graphite, and the second component may include silicon.

[0019] According to one embodiment, the negative plate of the battery cell may be composed of the first component and the second component.

[0020] A battery diagnostic method according to another embodiment of the present document may include, based on a physical model representing the state of a battery and battery data of a battery cell included in the battery, an operation of identifying at least one of a first degradation indicator, a second degradation indicator for a first component, a third degradation indicator for a second component, or any combination thereof, and an operation of diagnosing the state of the battery based on at least one of the first degradation indicator, the second degradation indicator, the third degradation indicator, or any combination thereof.

[0021] According to one embodiment, the first degradation index may include an LLI (loss of lithium inventory) comprising a first parameter related to lithium loss in the middle of life (MOL) relative to the beginning of life (BOL) of the battery cell.

[0022] According to one embodiment, the second degradation index may include a loss of active material (LAM) comprising a second parameter related to the loss of the first component in MOL relative to BOL at the electrode plate of the battery cell, and the third degradation index may include a loss of active material (LAM) comprising a second parameter related to the loss of the second component in MOL relative to BOL at the electrode plate.

[0023] According to one embodiment, the physical model may include a P2D (Pseudo two-dimensional; P2D) model.

[0024] According to one embodiment, the first component may include graphite and the second component may include silicon.

[0025] According to one embodiment, the negative plate of the battery cell may be composed of the first component and the second component.

[0026] This technology can extend the lifespan of a battery cell by obtaining degradation indicators for each component of the negative plate of the battery cell.

[0027] In addition, this technology can contribute to improving the stability of a battery cell by obtaining degradation indicators for each component of the negative plate of the battery cell.

[0028] In addition, this technology can improve the accuracy of battery cell condition diagnosis by obtaining degradation indicators for each component of the negative plate of the battery cell.

[0029] In addition, this technology can obtain degradation indicators for each component of the negative plate of a battery cell by inputting parameters according to the components of the negative plate of the battery cell into a physical model.

[0030] In addition, various effects that can be identified directly or indirectly through this document may be provided.

[0031] FIG. 1 is a block diagram showing a battery pack in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0032] FIG. 2 is a block diagram showing the configuration of a battery diagnostic device in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0033] FIG. 3 illustrates examples of a first component and a second component included in a physical model in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0034] FIG. 4 illustrates examples of identified degradation indicators in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0035] FIG. 5 illustrates an example of the voltage of a battery cell identified during discharge in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0036] FIG. 6 illustrates an example of the flow of operation of a battery diagnostic device for detecting whether a battery cell is defective in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0037] FIG. 7 is a block diagram showing the hardware configuration of a computing system performing a battery diagnostic method in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0038] Some embodiments disclosed herein are described below with reference to the various embodiments of the accompanying drawings. However, this is not intended to limit the technology to specific embodiments and should be understood to include various modifications, equivalents, and / or alternatives to embodiments of the technology.

[0039] It should be noted that when assigning reference numerals to the components of each drawing, the same components are assigned the same reference numeral whenever possible, even if they are shown in different drawings. Furthermore, in describing the various embodiments disclosed in this document, if it is determined that a detailed description of related known configurations or functions would hinder understanding of the embodiments of the present invention, such detailed description is omitted. The singular form of a noun corresponding to an item may include one or more items unless the relevant context clearly indicates otherwise.

[0040] In describing the components of the embodiments of this document, terms such as first, second, A, B, (a), (b), etc., may be used. These terms are intended merely to distinguish the components from other components and do not limit the essence, order, or sequence of the components. Furthermore, unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the embodiments disclosed in this document pertain. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this application.

[0041] Additionally, in this disclosure, expressions of "greater than" or "less than" may be used to determine whether a specific condition is satisfied or fulfilled; however, this is merely for the purpose of expressing an example and does not exclude descriptions of "greater than" or "less than." Conditions described as "greater than" may be replaced with "greater than," conditions described as "less than" may be replaced with "less than," and conditions described as "greater than and less than" may be replaced with "greater than and less than." Furthermore, "A" to "B" below refer to at least one of the elements from A (including A) to B (including B).

[0042] In this document, each of the phrases such as "A or B", "at least one of A and B", "at least one of A or B", "A, B or C", "at least one of A, B and C", and "at least one of A, B, or C" may include any one of the items listed together in the corresponding phrase, or all possible combinations thereof.

[0043] In this document, where any component (e.g., 1) is referred to as being “connected,” “coupled,” or “joined” to another component (e.g., 2), with or without the terms “functionally” or “communicationally,” or where it is referred to as “coupled” or “connected,” it means that the component may be connected to the other component directly (e.g., via a wire), wirelessly, or through a third component.

[0044] According to one embodiment, the method according to the various embodiments disclosed herein may be provided as included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or distributed online (e.g., download or upload) through an application store or directly between two user devices. In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0045] According to various embodiments, each component (e.g., module or program) of the described components may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the aforementioned components or operations may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as they were performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically; one or more of the operations may be executed in a different order; may be omitted; or one or more other operations may be added.

[0046] Hereinafter, embodiments of the present document will be described in detail with reference to FIGS. 1 to 7.

[0047] FIG. 1 is a block diagram showing a battery pack in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0048] Referring to FIG. 1, the battery pack (1) may include a battery unit (12), a sensor unit (14), a switching unit (16), and a battery management system (BMS) (20). At this time, the battery pack (1) may be equipped with a plurality of battery units (12), sensor units (14), switching units (16), and battery management systems (20).

[0049] According to one embodiment, the battery unit (12) can supply power to a target device (not shown). To this end, the battery unit (12) may be electrically connected to the target device. Here, the target device may include an electrical, electronic, or mechanical device that operates by receiving power from the battery pack (1). For example, the target device may be an electric vehicle (EV) or an energy storage system (ESS), but is not limited thereto.

[0050] According to one embodiment, the battery unit (12) may include at least one battery cell (10) capable of charging and discharging. Here, the battery cell (10) may be a basic unit of a battery cell capable of charging and discharging electrical energy. For example, the battery cell (10) may be a lithium-ion (Li-ion) battery, a lithium-ion polymer (Li-ion polymer) battery, a nickel-cadmium (Ni-Cd) battery, a nickel-hydrogen (Ni-MH) battery, etc., but is not limited thereto.

[0051] According to one embodiment, a plurality of battery units (12) may be connected in series or in parallel. For example, a battery unit (12) may be a battery module, a battery bank, or a set of battery cells (cell-to-pack structure).

[0052] According to one embodiment, the sensor unit (14) can obtain information related to the battery unit (12). According to one embodiment, the sensor unit (14) can obtain values ​​(or information) related to the state of each of the battery unit (12) or battery cells (10). In one embodiment, the values ​​related to the state may include one or more values ​​for the voltage, current, resistance, state of charge (SOC), state of health (SOH), or temperature of the battery cell, or a combination thereof.

[0053] According to one embodiment, the sensor unit (14) can provide information of each of the plurality of battery units (12) to the battery management system (20).

[0054] According to one embodiment, the switching unit (16) may include an element for controlling the current flow for charging or discharging the battery unit (12). For example, the switching unit (16) may include at least one relay and / or magnetic contactor, etc., depending on the specifications of the battery pack (1).

[0055] According to one embodiment, a battery management system (BMS) (20) can monitor the voltage, current, temperature, etc. of a battery pack (1) and control or manage the battery pack (1) to prevent overcharging and over-discharging. For example, the battery management system (20) may include a plurality of terminals as an interface for receiving values ​​of the various parameters described above, and a circuit connected to these terminals to perform processing of the received values. Additionally, the battery management system (20) may control a sensor unit (14) and / or a switching unit (16). For example, the battery management system (20) may be connected to a plurality of battery units (12) to monitor the status of each of the plurality of battery units (12) and control the ON / OFF of relays or contactors.

[0056] According to one embodiment, the operation of the battery management system (20) can be performed by a battery management system (BMS) in the vehicle, as well as by various devices such as a server, cloud, charger, or discharger.

[0057] The upper controller (2) can transmit control signals for a plurality of battery units (12) to the battery management system (20). Accordingly, the operation of the battery management system (20) can be controlled based on the signals applied from the upper controller (2).

[0058] According to one embodiment, the battery management system (20) may include the battery diagnostic device (201) of FIG. 2. According to another embodiment, the battery management system (20) may be a different system from the battery diagnostic device (201) of FIG. 2. That is, the diagnostic device (201) of FIG. 2 may be included in the battery pack (1) or may be configured as another device outside the battery pack (1). For convenience of explanation, the following description assumes that the battery diagnostic device (201) is configured as another device outside the battery pack (1). Furthermore, the operation of the battery diagnostic device (201) below may be performed by a battery management system (BMS) within the vehicle, as well as by various devices such as a server, cloud, charger, or discharger.

[0059] FIG. 2 is a block diagram showing the configuration of a battery diagnostic device in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0060] FIG. 3 illustrates examples of a first component and a second component included in a physical model in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0061] Referring to FIGS. 2 and 3, the battery diagnostic device (201) may include a memory (203) and one or more processors (205). The memory (203) may store at least one instruction. One or more processors (205) may execute at least one instruction.

[0062] The battery cell (301) may include a negative plate and a positive plate separated by a separator (e.g., a separator). The particles (311) of the first component may represent graphite particles. The particles (313) of the second component may represent silicon particles.

[0063] According to one embodiment, the negative plate of the battery cell (301) may be composed of a first component (e.g., graphite) and a second component (e.g., silicon).

[0064] According to one embodiment, as the battery cell (301) is used, phenomena resulting from side reactions within the battery cell (e.g., formation of a solid electrolyte interphase (SEI) layer, loss of active material, loss of lithium) may occur, and the performance of the battery may be degraded.

[0065] According to one embodiment, one or more processors (205) of the battery diagnostic device (201) provide battery data of the battery cell (e.g., voltage profile of the battery, current profile of the battery, state of charge (SOC) profile of the battery), parameters for the first component (e.g., radius of the particle of the first component ( ), inter-particle distance of the first component, surface area of ​​the first component particles, volume of the first component particles ( ), number of particles of the first component contained in the cathode plate ( )), and parameters for the second component (e.g., radius of the particle of the second component ( ), distance between particles of the second component, surface area of ​​particles of the second component, volume of particles of the second component ( ), number of particles of the second component contained in the cathode plate ( )), and parameters for the battery cell (e.g., length of the negative plate ( ), length of the positive plate( ), length of the separator ( Based on inputting )) into the physical model, at least one of a first degeneration indicator, a second degeneration indicator for the first component, a third degeneration indicator for the second component, or any combination thereof can be identified.

[0066] For example, one or more processors (205) of the battery diagnostic device (201) can construct a physical model based on at least one of the radius value of the particles of the first component, the distance between the particles of the first component, the surface area value of the particles of the first component, or any combination thereof, and can identify a second degradation indicator through the physical model.

[0067] For example, one or more processors (205) of the battery diagnostic device (201) can construct a physical model based on at least one of the radius value of the particles of the second component, the distance between the particles of the second component, the surface area value of the particles of the second component, or any combination thereof, and can identify a third degradation indicator through the physical model.

[0068] According to one embodiment, the physical model may include a P2D (Pseudo two-dimensional; P2D) model, which is an electrochemical lithium-ion battery model. The P2D model can identify parameters representing the state of a battery cell (e.g., a first degradation index, a second degradation index, a third degradation index) based on material transport equations (e.g., an equation representing ion diffusion in an electrolyte, an equation representing ion diffusion in a solid), electrochemical equations (e.g., an equation representing potential in an electrolyte, an equation representing potential in a solid), and the Butler-Volmer equation.

[0069] According to one embodiment, the physical model can identify parameters representing the state of the battery cell using mathematical formulas 1 to 7.

[0070] For example, an equation representing the lithium ion concentration in silicon particles due to ion diffusion within a solid can be expressed by Equation 1.

[0071]

[0072] Referring to mathematical formula 1, is time t and position The concentration of lithium ions in silicon particles can be expressed. It can represent the radial distance of silicon particles. It can represent the effective diffusion coefficient of lithium ions for silicon particles.

[0073] For example, the equation representing the concentration of lithium ions in graphite particles due to ion diffusion within a solid can be expressed by Equation 2.

[0074]

[0075] Referring to mathematical formula 2, is time t and position The concentration of lithium ions in graphite particles can be expressed. It can represent the radial distance of the particle. can represent the effective diffusion coefficient of lithium ions for graphite particles.

[0076] For example, the equation representing the concentration of lithium ions in the electrolyte can be expressed by mathematical equation 3.

[0077]

[0078] Referring to mathematical formula 3, It can represent the lithium ion concentration in the electrolyte. can represent the porosity of the electrolyte. can represent the effective diffusion coefficient of lithium ions in the electrolyte. a can represent a defined constant. It can represent the cation mobility of the electrolyte. can represent a constant representing the properties of the material. j can represent the current density at the electrode-electrolyte interface.

[0079] For example, the equation representing the potential within a solid can be expressed by mathematical equation 4.

[0080]

[0081] Referring to mathematical formula 4, can represent the effective conductivity of the solid (graphite, silicon) phase. In this document, can have the same value in graphite and silicon. a can represent a predefined constant. can represent the potential within a solid (graphite, silicon). In this document, can have the same value in graphite and silicon. a can represent a defined constant. F can represent the Faraday constant. j can represent the current density at the electrode.

[0082] For example, the equation representing the potential within the electrolyte can be expressed by mathematical equation 5.

[0083]

[0084] Referring to mathematical formula 5, can represent the effective conductivity of the electrolyte. a can represent a predefined constant. It can represent the potential within the electrolyte. ε₀ can represent cation mobility. j can represent current density at the electrode. R can represent the gas constant. T can represent temperature. F can represent the Faraday constant. It can represent the ion concentration within the electrolyte.

[0085] For example, the electrochemical reaction rate equation according to the reaction rate of silicon particles can be expressed by Equation 6.

[0086]

[0087] Referring to mathematical formula 6, It can represent the electrochemical reaction rate constant due to silicon. It can represent the ion concentration within the electrolyte. This can represent the theoretical amount of lithium ions that silicon can secure. It can represent the silicon particle concentration of the cathode. It can represent the difference between the electrode potential and the equilibrium potential. can be determined based on the properties of the material (e.g., silicon). F can represent the Faraday constant. R can represent the gas constant. T can represent the temperature.

[0088] For example, the electrochemical reaction rate equation according to the reaction rate of graphite particles can be expressed by Equation 7.

[0089]

[0090] Referring to mathematical formula 7, It can represent the electrochemical reaction rate constant due to graphite. It can represent the ion concentration within the electrolyte. This can represent the theoretical amount of lithium ions that graphite can secure. It can represent the concentration of graphite particles in the cathode. It can represent the difference between the electrode potential and the equilibrium potential. can be determined depending on the properties of the material (e.g., graphite). F can represent the Faraday constant. R can represent the gas constant. T can represent the temperature.

[0091] According to one embodiment, the physical model can identify a parameter representing the state of the battery cell (e.g., an OCV (open circuit voltage; OCV) curve according to capacity) using Equation 8.

[0092]

[0093] For example, the physical model can identify the open-circuit potential (OCP) of the entire cathode according to the capacitance of the entire cathode through Equation 8. Here, the physical model may not be limited to the P2D model. Equation 8 may not be included in the material transport equations, electrochemical equations, and the Butler-Volmer equation, which are the governing equations of the P2D model.

[0094] Referring to mathematical formula 8, It can represent the total capacitance of the cathode. It can represent the capacity of graphite. It can represent the capacity of silicon. can represent the stoichiometric ratio of graphite. In other words, represents the amount of lithium ions inserted into graphite, and the current density (e.g., , It can be determined by ). It can represent the stoichiometric ratio of silicon. represents the amount of lithium ions inserted into silicon, and the current density (e.g., , It can be determined by ). This can represent the theoretical capacity at which graphite can contain the maximum amount of lithium ions. This represents the theoretical capacity at which silicon can contain the maximum amount of lithium ions. It can represent the mass of graphite used in the cathode composed of a mixture of silicon and graphite. It can represent the mass of silicon used in the cathode composed of a mixture of silicon and graphite.

[0095] According to one embodiment, the physical model can obtain an OCP curve for the entire cathode according to the total capacity of the cathode based on the OCP curve according to the capacity of silicon and the OCP curve according to the capacity of graphite, and the total capacity of the cathode obtained based on the capacity of silicon contained in the cathode and the capacity of graphite contained in the cathode. The OCP curve according to the capacity of silicon and the OCP curve according to the capacity of graphite can be given.

[0096] According to one embodiment, the physical model can obtain an open circuit voltage (OCV) curve of the battery cell in the middle of life (MOL) state based on the OCP curve of the entire cathode according to the capacity of the entire cathode and the OCP curve of a designated anode. By calculating or adding a specific value to the OCV value included in the MOL state OCV curve so that the deviation between the OCV curve of the beginning of life (BOL) and the OCV curve of the middle of life (MOL) state of the battery cell is minimized, a degradation indicator (e.g., a first degradation indicator, a second degradation indicator, a third degradation indicator) can be identified.

[0097] According to one embodiment, the first degradation index may include a loss of lithium inventory (LLI) comprising a first parameter related to the lithium loss in the middle of life (MOL) relative to the beginning of life (BOL) of the battery cell. In other words, the LLI may indicate the degree of lithium loss within the battery cell.

[0098] According to one embodiment, the second degradation index may include a loss of active material (LAM) comprising a second parameter related to the loss of a first component in the MOL relative to the BOL in the negative electrode plate of the battery cell. In other words, the second degradation index may indicate the degree of loss of the first component (e.g., graphite) in the negative electrode plate.

[0099] According to one embodiment, the third degradation index may include a loss of active material (LAM) comprising a second parameter related to the loss of a second component in the MOL relative to the BOL in the negative plate of the battery cell. In other words, the third degradation index may indicate the degree of loss of the second component (e.g., silicon) in the negative plate.

[0100] According to one embodiment, the physical model may include a simulation that identifies degeneration indicators based on a P2D model.

[0101] FIG. 4 illustrates examples of identified degradation indicators in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0102] Referring to FIG. 4, the first graph (401) may represent the LAM of the entire battery cell according to the charge and discharge cycles obtained through a physical model. The second graph (403) may represent the LAM of the positive electrode included in the battery cell according to the charge and discharge cycles obtained through a physical model. The third graph (405) may represent the LAM of the negative electrode included in the battery cell according to the charge and discharge cycles obtained through a physical model. The fourth graph (407) may represent the LLI related to the lithium loss of the entire battery cell according to the charge and discharge cycles obtained through a physical model. The fifth graph (409) may represent the LAM of the first component (e.g., graphite) included in the negative electrode plate according to the charge and discharge cycles obtained through a physical model. The sixth graph (411) may represent the LAM of the second component (e.g., silicon) included in the negative electrode plate according to the charge and discharge cycles obtained through a physical model.

[0103] According to one embodiment, one or more processors (205) of a battery diagnostic device (201) can construct a physical model based on battery data of a battery cell, parameter values ​​regarding the characteristics of a first component particle (e.g., radius of a first component particle, distance between first component particles, surface area of ​​a first component particle, volume of a first component particle, number of first component particles included in a negative plate), parameter values ​​regarding the characteristics of a second component particle (e.g., radius of a second component particle, distance between second component particles, surface area of ​​a second component particle, volume of a second component particle, number of second component particles included in a negative plate), parameter values ​​for a battery cell (e.g., length of a negative plate, length of a positive plate, length of a separator), and equations included in the physical model, and can identify at least one of a first degradation index, a second degradation index, a third degradation index, or any combination thereof through the physical model. The equations included in the physical model can describe the behavior of the first component particles and the second component particles.

[0104] According to one embodiment, one or more processors (205) of the battery diagnostic device (201) can assign 1.5 dimensions to the particles of the first component and assign 1.5 dimensions to the particles of the second component to calculate equations included in the physical model.

[0105] According to one embodiment, one or more processors (205) of a battery diagnostic device (201) can obtain at least one of a first degeneration index, a second degeneration index, a third degeneration index, or any combination thereof by distinguishing between parameter values ​​regarding the characteristics of a first component particle and parameter values ​​regarding the characteristics of a second component particle and substituting them into equations included in a physical model.

[0106] According to one embodiment, the accuracy of the degeneration index obtained by distinguishing the parameter value regarding the characteristics of the first component particle and the parameter value regarding the characteristics of the second component particle and substituting them into the equations included in the physical model may be higher than the accuracy of the degeneration index obtained by making the parameter value regarding the characteristics of the first component particle and the parameter value regarding the characteristics of the second component particle the same value and substituting them into the equations included in the physical model.

[0107] According to one embodiment, one or more processors (205) of a battery diagnostic device (201) can identify LAM of the entire battery cell, LAM of the positive plate, LAM of the negative plate, LLI of the battery cell, LAM of the graphite of the negative plate, and LAM of the silicon of the negative plate through a physical model, such as a first graph (401), a second graph (403), a third graph (405), a fourth graph (407), a fifth graph (409), and a sixth graph (411).

[0108] FIG. 5 illustrates an example of the voltage of a battery cell identified during discharge in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0109] Referring to FIG. 5, the first graph (501) may represent the voltage of a battery cell according to the flow of discharge time at a first temperature and a first discharge cycle. The second graph (501) may represent the voltage of a battery cell according to the flow of discharge time at a first temperature and a second discharge cycle that is later than the first discharge cycle. The third graph (505) may represent the voltage of a battery cell according to the flow of discharge time at a second temperature higher than the first temperature and a first discharge cycle. The fourth graph (507) may represent the voltage of a battery cell according to the flow of discharge time at a second temperature and a second discharge cycle.

[0110] According to one embodiment, the first line (531) may represent the intermediate value of the voltage of the battery cell identified based on a physical model. According to one embodiment, the second line (541) may represent the upper boundary line and the lower boundary line of the voltage of the battery cell identified based on a physical model. According to one embodiment, the third line (551) may represent the voltage of the battery cell obtained through experimentation.

[0111] According to one embodiment, one or more processors (205) of the battery diagnostic device (201) can identify parameters representing the performance of the battery, such as the voltage of the battery, by a physical model, even if the temperature and discharge cycle are changed.

[0112] FIG. 6 illustrates an example of the flow of operation of a battery diagnostic device for detecting whether a battery cell is defective in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0113] Referring to FIG. 6, in the first operation (601), one or more processors (205) of a battery diagnostic device (201) according to one embodiment can identify at least one of a first degradation indicator, a second degradation indicator for a first component, a third degradation indicator for a second component, or any combination thereof, based on a physical model representing the state of the battery and battery data of a battery cell included in the battery.

[0114] In the second operation (603), one or more processors (205) according to one embodiment may diagnose the state of the battery based on at least one of a first degeneration indicator, a second degeneration indicator, a third degeneration indicator, or any combination thereof.

[0115] FIG. 7 is a block diagram showing the hardware configuration of a computing system performing a battery diagnostic method in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document.

[0116] Referring to FIG. 7, a computing system (700) according to one embodiment disclosed in this document may include an MCU (710), memory (720), an input / output I / F (730), and a communication I / F (740).

[0117] The MCU (710) may be one or more processors that execute various programs stored in memory (720) (e.g., battery cell data collection program, graph generation program, data analysis program, data decomposition algorithm, normalization program, battery cell diagnosis program, etc.), process various information including characteristic data of the battery cell, potential variables, etc. through these programs, and perform the functions of the battery diagnosis device (201) shown in FIGS. 2 to 5.

[0118] The memory (720) can store various programs such as a battery cell data collection program, a graph generation program, a data analysis program, a data decomposition algorithm, a normalization program, and a battery cell diagnosis program.

[0119] These memories (720) may be provided in multiple quantities as needed. The memories (720) may be volatile memories or non-volatile memories. As volatile memories, the memory (720) may use RAM, DRAM, SRAM, etc. As non-volatile memories, the memory (720) may use ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc. The examples of the listed memories (720) are merely examples and are not limited to these examples.

[0120] The input / output I / F (730) can provide an interface that enables data transmission and reception between an input device (not shown), such as a keyboard, mouse, or touch panel, and an output device (not shown), such as a display, and the MCU (710).

[0121] The communication I / F (740) is configured to transmit and receive various data with a server and may be various devices capable of supporting wired or wireless communication. For example, the diagnostic device (201) can transmit and receive various information, including the shape model of a battery cell, from a separately provided external server via the communication I / F (740).

[0122] In this way, a computer program according to one embodiment disclosed in this document may be implemented as a module that performs, for example, the functions illustrated in FIG. 2, by being written to memory (720) and processed by an MCU (710).

[0123] As described above, even though all components constituting the embodiments disclosed in this document have been described as being combined or operating in combination, the embodiments disclosed in this document are not necessarily limited to such embodiments. That is, within the scope of the purposes of the embodiments disclosed in this document, all components may be selectively combined in one or more ways to operate.

[0124] Furthermore, terms such as "include," "compose," or "have" as described above, unless specifically stated otherwise, mean that the relevant component may be inherent; thus, they should be interpreted as allowing for the inclusion of additional components rather than excluding them. All terms, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the embodiments disclosed in this document pertain, unless otherwise defined. Commonly used terms, such as those defined in advance, should be interpreted in accordance with their contextual meanings in the relevant technology and, unless explicitly defined in this document, should not be interpreted in an ideal or overly formal sense.

[0125] The foregoing disclosure outlines the features of several embodiments to enable those skilled in the art to better understand the aspects of the present disclosure. Those skilled in the art will understand that the present disclosure can be readily used as a basis for designing or modifying other structures to perform the same purpose or achieve the same advantages as the embodiments introduced herein. Furthermore, those skilled in the art will recognize that such equivalent configurations do not depart from the scope of the present disclosure and that various changes, substitutions, and modifications may be made in the present specification without departing from the scope of the present disclosure.

Claims

1. Memory storing at least one instruction; and It includes one or more processors that execute at least one of the above instructions, The above one or more processors, Based on a physical model representing the state of a battery and battery data of a battery cell included in the battery, at least one of a first degradation indicator, a second degradation indicator for a first component, a third degradation indicator for a second component, or any combination thereof is identified, and Configured to diagnose the state of the battery based on at least one of the first degradation indicator, the second degradation indicator, the third degradation indicator, or any combination thereof. Battery diagnostic device.

2. In Claim 1, The above first degeneration indicator is, Configured to include an LLI (loss of lithium inventory) comprising a first parameter related to lithium loss in the MOL (middle of life) relative to the BOL (beginning of life) of the battery cell, Battery diagnostic device.

3. In Claim 1, The above second degeneration indicator is, It includes a loss of active material (LAM) comprising a second parameter related to the loss of the first component in MOL relative to BOL in the electrode plate of the battery cell, and The above third degeneration indicator is, A configuration comprising a loss of active material (LAM) including a second parameter related to the loss of the second component in MOL relative to BOL in the electrode plate, Battery diagnostic device.

4. In Claim 1, The above physical model is, Configured to include a P2D (Pseudo two-dimensional; P2D) model, Battery diagnostic device.

5. In Claim 1, The above first component is, It contains graphite The above second component is configured to include silicon Battery diagnostic device.

6. In Claim 1, The negative plate of the above battery cell is, Composed of the above first component and the above second component, Battery diagnostic device.

7. An operation to identify at least one of a first degradation indicator, a second degradation indicator for a first component, a third degradation indicator for a second component, or any combination thereof, based on a physical model representing the state of the battery and battery data of a battery cell included in the battery; and A method comprising diagnosing the state of the battery based on at least one of the first degradation indicator, the second degradation indicator, the third degradation indicator, or any combination thereof. Battery diagnostic method.

8. In Claim 7, The above first degeneration indicator is, A battery cell comprising a battery cell comprising a battery cell comprising a first parameter including a loss of lithium inventory (LLI) related to the lithium loss in the middle of life (MOL) relative to the beginning of life (BOL), Battery diagnostic method.

9. In Claim 7, The above second degeneration indicator is, It includes a loss of active material (LAM) comprising a second parameter related to the loss of the first component in MOL relative to BOL in the electrode plate of the battery cell, and The above third degeneration indicator is, A LAM (loss of active material; LAM) comprising a second parameter related to the loss of the second component in MOL relative to BOL in the electrode plate, Battery diagnostic method.

10. In Claim 7, The above physical model is, including P2D (Pseudo two-dimensional; P2D) models, Battery diagnostic method.

11. In Claim 7, The above first component is, It contains graphite The above second component is containing silicon Battery diagnostic method.

12. In Claim 7, The negative plate of the above battery cell is, Composed of the above first component and the above second component, Battery diagnostic method.

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