Battery management device and operation method thereof

Abstract

A battery management device according to an embodiment disclosed in the present document may comprise: an interface for obtaining first impedance data of a battery on the basis of electrochemical impedance spectroscopy (EIS); and a controller for generating second impedance data obtained by correcting inductance data in the first impedance data, and diagnosing a state of the battery on the basis of the second impedance data.

Description

Battery management device and method of operation thereof

[0001] Cross-citation with related applications

[0002] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2024-0198958 filed on December 27, 2024, priority based on Korean Patent Application No. 10-2024-0198959 filed on December 27, 2024, and priority based on Korean Patent Application No. 10-2025-0194052 filed on December 09, 2025, and includes all contents disclosed in the documents of said Korean patent applications as part of this specification.

[0003] Technology field

[0004] The embodiments disclosed in this document relate to a battery management device and a method of operating the same.

[0005] Recently, active research and development on secondary batteries has been underway. Here, the term "secondary battery" refers to a rechargeable battery, encompassing conventional Ni / Cd and Ni / MH batteries as well as the more recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of significantly higher energy density compared to conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in a compact and lightweight form factor, making them suitable for use as power sources for mobile devices. Recently, their scope of application has expanded to include electric vehicles, drawing attention as a next-generation energy storage medium.

[0006] As the industrial sectors utilizing batteries expand, technologies for diagnosing battery safety are also advancing. Electrochemical Impedance Spectroscopy (EIS), one method for diagnosing batteries, is a technique that analyzes the electrochemical characteristics of batteries and allows for the non-destructive diagnosis of their condition. Based on impedance data obtained through EIS inspection, it is possible to model an equivalent circuit containing circuit elements capable of simulating the battery's electrochemical characteristics. However, EIS spectra present a problem in that it is difficult to select appropriate circuit elements when different processes overlap within the same frequency range. To overcome this issue, the Distribution of Relaxation Times (DRT) technique is available.

[0007] DRT is a technique that transforms impedance data, which is in the form of a function of frequency, into a distribution of time constants. By utilizing DRT, the resolution of individual electrochemical processes that are difficult to distinguish using only impedance spectra can be improved. The DRT data, which is the result of performing DRT transformation on impedance data obtained through EIS inspection, can contain multiple peaks corresponding to different time constants; since each of these peaks corresponds to the impedance of the battery, the condition of the battery can be diagnosed based on these peaks.

[0008] As the frequency increases, inductive reactance (Inductance, X) LAs (=2πfL) increases, the influence of inductance on the impedance data can become greater. However, since conventional impedance analysis was performed by modeling an equivalent circuit composed solely of multiple resistor-capacitor circuits, a problem existed where the actual impedance data did not match the impedance data reconstructed based on the equivalent circuit during the DRT conversion process. Based on this, there is a problem in that peaks corresponding to impedance in specific frequency ranges are not identified in the DRT conversion results.

[0009] The technical problems of the embodiments disclosed in 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 description below.

[0010] A battery management device according to one embodiment disclosed in this document may include: an interface for acquiring first impedance data of a battery based on electrochemical impedance spectroscopy (EIS); and a controller for generating second impedance data by correcting inductance data from the first impedance data and diagnosing the state of the battery based on the second impedance data.

[0011] In one embodiment, the controller can generate the second impedance data by correcting the inductance data corresponding to the resistor-inductor circuit in the first impedance data based on an equivalent circuit comprising one or more resistor-capacitor (RC) circuits and one or more resistor-inductor (RL) circuits.

[0012] In one embodiment, the controller can generate the second impedance data by removing the inductance data from the first impedance data.

[0013] In one embodiment, the controller may generate a first impedance data reconstructed based on a plurality of Voigt circuits corresponding to the first impedance data, calculate an error value between the first impedance data and the reconstructed first impedance data, and generate the second impedance data when the error value exceeds a threshold value.

[0014] In one embodiment, the controller can generate second DRT data by converting the second impedance data into DRT (Distribution of Relaxation Time).

[0015] In one embodiment, the controller can identify one or more peaks included in the second DRT data, calculate one or more impedance values ​​corresponding to the one or more peaks, and diagnose the state of the battery based on the impedance values.

[0016] In one embodiment, the controller can extract resistance based on the second impedance data and diagnose the state of the battery based on the resistance.

[0017] In one embodiment, the controller can generate second DRT data by converting the second impedance data into DRT (Distribution of Relaxation Times) data and extract a first resistance based on the second DRT data.

[0018] In one embodiment, the controller identifies a peak corresponding to the first resistance among a plurality of peaks included in the second DRT data, calculates the value of the first resistance corresponding to the identified peak, and can diagnose the state of the battery based on the value of the first resistance.

[0019] In one embodiment, the first resistance may include charge transfer resistance, interface resistance (SEI / CEI layer resistance), and contact resistance.

[0020] In one embodiment, the controller can calculate the value of the second resistance based on the second impedance data.

[0021] In one embodiment, the controller can detect an abnormal battery cell among the plurality of battery cells based on an InterQuartile Range (IQR) based on the value of the second resistance.

[0022] In one embodiment, the second resistor may correspond to an ohmic resistance, and the controller may calculate the value of the ohmic resistance.

[0023] A method of operation of a battery management device according to an embodiment disclosed in this document may include: acquiring first impedance data of a battery based on electrochemical impedance spectroscopy (EIS); generating second impedance data by correcting inductance data from the first impedance data; and diagnosing the state of the battery based on the second impedance data.

[0024] In one embodiment, the operation of generating the second impedance data may include the operation of generating the second impedance data by correcting the inductance data corresponding to the resistor-inductor circuit in the first impedance data based on an equivalent circuit comprising one or more resistor-capacitor (RC) circuits and one or more resistor-inductor (RL) circuits.

[0025] In one embodiment, the operation of generating the second impedance data may include the operation of generating the second impedance data by removing the inductance data from the first impedance data.

[0026] In one embodiment, the method of operation of the battery management device may further include: generating first impedance data reconstructed based on a plurality of Voigt Circuits corresponding to the first impedance data; and calculating an error value between the first impedance data and the reconstructed first impedance data, and the operation of generating second impedance data may include generating the second impedance data when the error value exceeds a threshold value.

[0027] In one embodiment, the method of operation of the battery management device may further include the operation of generating second DRT data by converting the second impedance data into DRT (Distribution of Relaxation Time).

[0028] In one embodiment, the method of operation of the battery management device may further include: an operation of identifying one or more peaks included in the second DRT data; and an operation of calculating one or more impedance values ​​corresponding to the one or more peaks, and the operation of diagnosing the state of the battery based on the second impedance data may include an operation of diagnosing the state of the battery based on the impedance values.

[0029] In one embodiment, the operation of diagnosing the state of the battery based on the second impedance data may include the operation of extracting resistance based on the second impedance data, and the operation of diagnosing the state of the battery based on the resistance.

[0030] In one embodiment, the operation of extracting the resistance based on the second impedance data may include the operation of generating second DRT data by converting the second impedance data into DRT (Distribution of Relaxation Times), and the operation of extracting the first resistance based on the second DRT data.

[0031] In one embodiment, the operation of extracting the first resistance based on the second DRT data may include the operation of identifying a peak corresponding to the first resistance among a plurality of peaks included in the second DRT data, and the operation of calculating the value of the first resistance corresponding to the identified peak, and the operation of diagnosing the state of the battery based on the resistance may include the operation of diagnosing the state of the battery based on the value of the first resistance.

[0032] In one embodiment, the first resistance may include charge transfer resistance, interface resistance (SEI / CEI layer resistance), and contact resistance.

[0033] In one embodiment, the operation of extracting the resistance based on the second impedance data may include the operation of calculating the value of the second resistance based on the second impedance data, and the operation of diagnosing the state of the battery based on the resistance may include the operation of diagnosing the state of the battery based on the value of the second resistance.

[0034] In one embodiment, the operation of diagnosing the state of the battery based on the value of the second resistance may include the operation of diagnosing the state of the battery based on an interquartile range (IQR) based on the value of the second resistance.

[0035] In one embodiment, the second resistance may correspond to ohmic resistance.

[0036] The battery management device and the method of operation thereof according to the various embodiments disclosed in this document can model an equivalent circuit including a plurality of RL circuits corresponding to impedance data. Accordingly, the actual impedance data and the impedance data reconstructed based on the equivalent circuit can be matched.

[0037] In addition, the battery management device and the method of operation thereof according to the various embodiments disclosed in this document can generate corrected impedance data in which the inductance influence is minimized by correcting the inductance data corresponding to the RL circuit in the impedance data. Accordingly, when performing DRT conversion on the corrected impedance data, a peak corresponding to the specific impedance can be identified.

[0038] A battery management device and a method of operation thereof according to various embodiments disclosed in this document can diagnose whether there is an abnormality in the battery based on diagnostic data (e.g., impedance data and DRT data).

[0039] The effects of the battery management device and the method of operation thereof disclosed in this document are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art in accordance with the disclosure of this document.

[0040] FIG. 1 is a block diagram of a battery management device according to one embodiment disclosed in this document.

[0041] FIGS. 2a and 2b illustrate DRT data according to an embodiment disclosed in this document.

[0042] FIGS. 3a to 3c are drawings illustrating a conventional method of modeling an equivalent circuit corresponding to impedance data.

[0043] FIGS. 4a and FIGS. 4b are drawings illustrating a conventional method for modeling an equivalent circuit including one or more RC circuits.

[0044] FIGS. 5a to 5c are drawings illustrating a method for modeling an equivalent circuit comprising one or more RC circuits and one or more RL circuits according to one embodiment disclosed in this document.

[0045] FIGS. 6a to 6d are drawings illustrating a method for generating diagnostic data and a method for analyzing impedance based on diagnostic data according to an embodiment disclosed in this document.

[0046] FIG. 7 is a drawing illustrating a method for a battery diagnostic device to detect an abnormal battery cell according to one embodiment disclosed in this document.

[0047] FIG. 8 illustrates an image of the interior of an abnormal battery cell according to one embodiment disclosed in this document.

[0048] FIG. 9 is a flowchart illustrating the operation method of a battery diagnostic system according to one embodiment disclosed in this document.

[0049] FIG. 10 illustrates a computing system that executes the operations of a battery management device according to an embodiment disclosed in this document.

[0050] In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0051] Hereinafter, embodiments of the present invention are described with reference to the accompanying drawings. However, this is not intended to limit the present invention to specific embodiments and should be understood to include various modifications, equivalents, and / or alternatives of the embodiments of the present invention.

[0052] The embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise.

[0053] 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. Terms such as “first,” “second,” “first,” “second,” “A,” “B,” “(a),” or “(b)” may be used simply to distinguish a component from another component and, unless specifically stated otherwise, do not limit the components in any other aspect (e.g., importance or order).

[0054] In this document, where it is stated that any (e.g., 1) component is "connected," "coupled," or "joined" to another (e.g., 2) component, with or without the terms "functionally" or "communicationly," or where it is stated that the component is "coupled" or "connected," it means that the component may be connected to the other component directly (e.g., by wire or wirelessly) or indirectly (e.g., through a 3) component.

[0055] Methods according to the various embodiments disclosed in this document may be provided as part of 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.

[0056] According to the embodiments disclosed in this document, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to the embodiments disclosed in this document, one or more of the components or operations of the aforementioned components 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 such a case, the integrated component may perform one or more functions of each of the components of the multiple components in the same or similar manner as those performed by the corresponding components among the multiple components prior to the integration. According to the embodiments disclosed in this document, operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0057] FIG. 1 is a block diagram of a battery management device according to one embodiment disclosed in this document.

[0058] A battery management device (10) can acquire impedance data of a battery and generate diagnostic data corrected from the impedance data, and can diagnose the condition of the battery based on the diagnostic data. In one embodiment, operations performed by the battery diagnostic system (1) may be performed on a PC or an external server to diagnose whether there is an abnormality before shipping a battery manufactured in a battery manufacturing process. In one embodiment, the battery diagnostic system (1) may be included in a BMS capable of diagnosing battery cells included in an electronic device, and operations performed by the battery management device (10) may be performed in the BMS. Here, the electronic device may be a mobile device (e.g., mobile phone, laptop computer, smartphone, smart pad), an electric vehicle (e.g., EV, HEV, PHEV, fuel cell EV), an energy storage system (ESS), or a battery swapping system (BSS). In one embodiment, the battery diagnostic system (1) may be included in a server or a charger / discharger capable of diagnosing battery cells outside of an electronic device, and the operations performed by the battery diagnostic system (1) may be performed on an external server or charger / discharger.

[0059] Referring to FIG. 1, the battery management device (10) may include an interface (100) and a controller (102). According to an embodiment, the battery management device (10) illustrated in FIG. 1 may further include at least one component (e.g., a display, an input device, or an output device) other than the components illustrated in FIG. 1. The battery management device (10) may acquire impedance data of the battery based on electrochemical impedance spectroscopy (EIS) and may generate diagnostic data for diagnosing the battery by correcting the impedance data. The battery management device (10) may diagnose the condition of the battery using the diagnostic data corrected from the actual impedance data.

[0060] Hereinafter, with reference to FIGS. 1 to 10, a method for a battery management device (10) to generate diagnostic data and a method for a battery management device (10) to diagnose the state of a battery will be described.

[0061] How to generate diagnostic data

[0062] Referring to FIG. 1, the battery management device (10) may include an interface (100) and a controller (102). The battery management device (10) may generate diagnostic data using the interface (100) and the controller (102). Here, the diagnostic data may include not only the first impedance data but also the second impedance data and the second DRT data described below.

[0063] The interface (100) can acquire first impedance data of the battery based on electrochemical impedance spectroscopy (EIS). According to various embodiments, the interface (100) may include various interface circuits for acquiring signals, information and / or data, such as sensors and communication circuits. For example, the interface (100) may include a communication circuit and receive the impedance data through communication with an EIS measuring device (not shown).

[0064] The controller (102) can obtain second impedance data corrected from first impedance data. The controller (102) can generate second impedance data corrected from the first impedance data by inductance data corresponding to the RL circuit based on an equivalent circuit comprising one or more resistor-capacitor circuits (hereinafter RC circuits) and one or more resistor-inductor circuits (hereinafter RL circuits) corresponding to the first impedance data. In one embodiment, the controller (102) can generate second impedance data by removing inductance data corresponding to the RL circuit from the first impedance data. A method for generating second impedance data based on an equivalent circuit is described later in FIGS. 3a to 4b.

[0065] In one embodiment, the controller (102) may determine whether to generate second impedance data. The controller (102) may determine whether to generate second impedance data based on first impedance data. The controller (102) may generate first impedance data reconstructed based on an equivalent circuit composed only of a plurality of RC circuits (e.g., a plurality of Vogit Circuits) based on the first impedance data. Here, the plurality of Vogit Circuits may refer to an equivalent circuit in which a plurality of RC circuits are connected in series to correspond to the first impedance data, and may include an infinite Vogit Circuit corresponding to an equivalent circuit in which an infinite number of RC circuits are connected in series. A detailed explanation thereof will be provided later in FIGS. 3a to 4b.

[0066] The controller (102) can calculate an error value based on the first impedance data and the reconstructed first impedance data, and can determine whether to generate the second impedance data based on the error value. Here, the error value can be calculated based on Equation 1.

[0067] [Mathematical Formula 1]

[0068] Error value (%) = (First impedance data (Z1) - Reconstructed first impedance data (Z 1R )) / (Magnitude of the first impedance data (abs(Z1)) * 100

[0069] The controller (102) can calculate an error value based on mathematical formula 1 and determine that if the error value exceeds a threshold value (e.g., 1%), it must generate second impedance data.

[0070] In one embodiment, the controller (102) can generate second DRT data by transforming the second impedance data into a DRT (Distribution of Relaxation Times). Here, DRT may refer to a relaxation time distribution, and DRT transformation is a method of transforming impedance data (Z(f)) which is a function of frequency into a distribution with respect to a time constant (τ). The controller (102) can identify one or more peaks included in the second DRT data. The controller (102) can calculate one or more impedance values ​​corresponding to each of the identified one or more peaks.

[0071] How to diagnose the condition of a battery

[0072] The battery management device (10) can diagnose the condition of the battery based on diagnostic data. Here, the diagnostic data may include the aforementioned impedance data and DRT data.

[0073] The controller (102) can diagnose whether there is an abnormality in the battery based on diagnostic data (e.g., second DRT data and impedance data). The controller (102) can identify one or more peaks included in the second DRT data. The controller (102) can identify a peak among one or more peaks included in the second DRT data that corresponds to a specific impedance (e.g., charge transfer resistance, interface resistance (SEI / CEI layer resistance), and contact resistance). The controller (102) can diagnose whether there is an abnormality in the battery based on the peak corresponding to the specific impedance.

[0074] In one embodiment, the controller (102) can calculate the charge transfer resistance value of the battery based on the second DRT data and diagnose the state of the battery based on the calculated charge transfer resistance value. For example, the controller (102) can identify a peak corresponding to the charge transfer resistance based on the time constant value and the frequency value among a plurality of peaks included in the second DRT data, calculate the charge transfer resistance value, and diagnose the state of the battery based on the calculated resistance value.

[0075] In one embodiment, the controller (102) can identify a peak corresponding to a specific impedance (e.g., charge transfer resistance, interface resistance, and contact resistance) among the peak points included in the second DRT data and calculate an impedance value corresponding to the peak. Here, the impedance value can be calculated based on a time constant value corresponding to the peak and a frequency value (log(frequency)) corresponding to the peak and the area of ​​the peak. Specifically, the impedance value can be calculated by multiplying a constant by an integral value in the frequency domain containing the peak.

[0076] In one embodiment, the controller (102) can calculate an ohmic resistance value based on second impedance data. For example, the controller (102) can calculate an ohmic resistance value corresponding to the ohmic resistance in a Nyquist plot corresponding to the second impedance data. Here, the ohmic resistance value may be an impedance value corresponding to the x-axis intercept among the impedance values ​​included in the Nyquist plot. Based on the calculated ohmic resistance value, the controller (102) can diagnose whether there is a crack in the electrode assembly included in the battery.

[0077] The controller (102) can detect an abnormal battery cell among the battery cells based on the ohmic resistance value of each of the battery cells. The controller (102) can detect a cracked battery cell based on the ohmic resistance values ​​of the battery cells.

[0078] In one embodiment, the controller (102) can detect a cracked battery cell based on an interquartile range (IQR). Here, the interquartile is data located at the 1 / 4 position from the top or bottom when data is sorted in order according to size, and the interquartile range is a type of variability that excludes the 1 / 4 of the ends of the data distribution. A method for the controller (102) to detect a cracked battery cell based on the interquartile range is described later in FIG. 7.

[0079] FIGS. 2a and 2b illustrate DRT data according to an embodiment disclosed in this document.

[0080] The first DRT data (20) of FIG. 2a may be the result of performing a DRT conversion on the first impedance data without correcting the first impedance data. The second DRT data (22) of FIG. 2b may be the result of performing a DRT conversion on the second impedance data, which is the first impedance data with inductance data corrected.

[0081] Referring to the first DRT data (20) and the second DRT data (22), when performing DRT conversion on the first impedance data, no peak is detected in a specific region (200) included in the high-frequency region, whereas when performing DRT conversion on the second impedance data corrected for the impedance data, a peak (P) corresponding to contact resistance is detected in a specific region (220) included in the high-frequency region. c ) can be detected.

[0082] FIGS. 3a to 3c illustrate a conventional method for modeling an equivalent circuit corresponding to impedance data. FIGS. 4a and 4b illustrate a conventional method for modeling an equivalent circuit including one or more RC circuits. Hereinafter, with reference to FIGS. 3a to 4b, a conventional method for generating an equivalent circuit based on first impedance data will be described.

[0083] The graphs (30, 32, 34) illustrated in FIGS. 3a to 3c may include impedance values ​​(300, 320, 340) measured based on EIS inspection. The graphs (30, 32, 34) of FIGS. 3a to 3c may include impedance values ​​(302, 322, 342) fitted based on an equivalent circuit comprising one or more RC circuits corresponding to the impedance values ​​(300, 320, 340).

[0084] The impedance value (302) included in the graph (30) of FIG. 3a is an impedance value fitted based on an equivalent circuit containing one RC circuit, the impedance value (322) included in the graph (32) of FIG. 3b is an impedance value fitted based on an equivalent circuit containing two RC circuits, and the impedance value (342) included in the graph (34) of FIG. 3c may be an impedance value fitted based on an equivalent circuit containing ten RC circuits. Referring to FIG. 3a through FIG. 3c, it can be seen that as the number of RC circuits included in the equivalent circuit increases, the fitted impedance values ​​(302, 322, 342) become similar to the impedance values ​​(300, 320, 340) measured based on actual EIS inspection.

[0085] FIG. 4a illustrates an equivalent circuit (40) comprising an ohmic resistance (400) and n (n: natural number) RC circuits (402). The equivalent circuit (40) may be an equivalent circuit based on first impedance data. Here, the equivalent circuit (40) may be referred to as a finite Voigt circuit, and each of the RC circuits may be referred to as a Voigt element. The impedance of the finite Voigt circuit may be expressed by Equation 2.

[0086] [Mathematical Formula 2]

[0087]

[0088] Here, is R k and C k It can be a time constant based on the product of.

[0089] Referring to FIG. 4b, the graph (40) shows the sum of squares of standardized residuals based on the difference between the first impedance data and the impedance data fitted based on the equivalent circuit (40) as the number (n) of RC circuits included in the equivalent circuit (40) increases. It can be observed that the value gradually decreases. When the number of RC circuits included in the equivalent circuit (40) is increased infinitely (where n diverges to infinity), it can be observed that the error value decreases and eventually converges to a minimum value. Based on this, if the equivalent circuit (40) is represented by an infinite number of RC circuits connected in series, the impedance data fitted based on the equivalent circuit (40) (reconstructed first impedance data) can be similar to the first impedance data measured based on the actual EIS test. If the equivalent circuit (40) is composed of an infinite number of RC circuits connected in series, the equivalent circuit (40) can be referred to as an Infinite Voigt Circuit. The impedance of the Infinite Voigt Circuit can be expressed by Equation 3.

[0090] [Mathematical Formula 3]

[0091]

[0092] As described above, the battery management device (10) can model an equivalent circuit (40) including infinite RC circuits based on the first impedance data. However, when the proportion of inductance in the high-frequency region increases, there is a problem in that the impedance data fitted based on the equivalent circuit (40) consisting only of a combination of multiple RC circuits does not match the first impedance data. Accordingly, as described in FIGS. 5a to 5c to be described later, the battery management device (10) can resolve the above problem that occurs as the influence of inductance increases at high frequencies by modeling an equivalent circuit including RL circuits corresponding to inductance and correcting the inductance data corresponding to RL circuits in the first impedance data.

[0093] FIGS. 5a to 5c are drawings illustrating a method for modeling an equivalent circuit comprising one or more RC circuits and one or more RL circuits according to one embodiment disclosed in this document.

[0094] Referring to FIG. 5a, the equivalent circuit (50) may further include n RC circuits (502) as well as n RL circuits (504). The battery management device (10) can reflect the inductance effect in the high-frequency region in the equivalent circuit by generating an equivalent circuit (50) that includes a plurality of RL circuits (504), and can obtain second impedance data with the inductance effect minimized by performing a correction to remove inductance data from the fitted impedance data (reconstructed first impedance data) based on the equivalent circuit (50).

[0095] FIG. 5b illustrates a first graph (51) before correcting inductance data from the first impedance data and a second graph (52) after correcting inductance data from the first impedance data. The first graph (51) may include first impedance data (510) and impedance data (reconstructed first impedance data, 512) fitted based on an equivalent circuit (50) modeled based on the first impedance data (510). The second graph (52) may include second impedance data (520) with inductance data removed from the first graph (51) and reconstructed second impedance data (522).

[0096] Referring to the first graph (51), one can see an area (514) where the first impedance data (510) and the reconstructed first impedance data (512) do not match. On the other hand, referring to the second graph (52), one can see that the second impedance data (520) and the reconstructed second impedance data (522) match.

[0097] By referring to the first graph (51) and the second graph (52) together, the battery management device (10) can generate corrected impedance data (e.g., reference numeral 520) by removing inductance data corresponding to inductance from impedance data based on EIS inspection (e.g., reference numeral 510), and can improve the degree of agreement between the impedance data (e.g., reference numeral 520) and the reconstructed impedance data (e.g., reference numeral 522).

[0098] FIG. 5c illustrates a second DRT data (54) corresponding to the result of performing a DRT transformation on the second impedance data from which inductance data has been removed from the first impedance data. When referring to the second DRT data (54), it can be seen that, unlike the DRT data (20) of FIG. 2a, a peak is generated in the high-frequency region (540). Based on the above, the battery management device (10) can generate a second DRT data (54) in which the influence of inductance is minimized by removing inductance data from the first impedance data.

[0099] FIGS. 6a to 6d are drawings illustrating a method for generating diagnostic data and a method for analyzing impedance based on diagnostic data according to an embodiment disclosed in this document.

[0100] Referring to FIG. 6a, the graph (60) may include first impedance data (600) measured based on actual EIS inspection and reconstructed first impedance data (602). Here, the reconstructed first impedance data (602) may include impedance values ​​fitted based on the equivalent circuit (50) of FIG. 5a.

[0101] Referring to FIG. 6b, the graph (62) may include first impedance data (620) and second impedance data (622) in which inductance data has been corrected.

[0102] Referring to FIG. 6c, graph (64) may include second impedance data (640) and reconstructed second impedance data (642). The battery management device (10) may generate second impedance data by correcting the inductance for the first impedance data (640), model an equivalent circuit based on the second impedance data, and generate fitted impedance data (reconstructed second impedance data (642)) based on the equivalent circuit. Referring to FIG. 6d, graph (66) may include second DRT data obtained by DRT-converting the second impedance data. Referring to graphs (64, 66), it can be confirmed that the second impedance data (640) and the reconstructed second impedance data (642) match, and that a peak corresponding to contact resistance is generated in the second DRT data.

[0103] FIG. 7 is a diagram illustrating a method for a battery diagnostic device to detect an abnormal battery cell according to an embodiment disclosed in this document. FIG. 8 illustrates an image taken of the interior of an abnormal battery cell according to an embodiment disclosed in this document.

[0104] Referring to FIG. 7, the y-axis of the graph (70) may represent ohmic resistance values, and the points included in the graph (70) may correspond to the ohmic resistance values ​​of each battery cell. The battery management device (10) may diagnose battery cells corresponding to the ohmic resistance values ​​included in the first region (700) as abnormal cells. For example, the battery management device (10) may diagnose the first battery cell (710) as an abnormal cell. The battery management device (10) may diagnose the first battery cell (710) as an abnormal cell in which a crack has occurred in the electrode assembly.

[0105] Referring to FIG. 8, it can be seen that a crack actually occurred in the electrode assembly wound in the shape of a jelly roll through an image (80) taken of the interior of the first battery cell (710) diagnosed as an abnormal cell.

[0106] By combining the contents described in FIGS. 1 to 8, the battery management device (10) can generate impedance data with minimized inductance influence compared to conventional methods by performing correction on the impedance data, and the battery management device (10) can detect an abnormal cell among a plurality of battery cells without photographing the inside of the battery using the corrected impedance data. Accordingly, the battery diagnostic system (1) disclosed in this document can generate more accurate diagnostic data than conventional methods, thereby improving the diagnostic rate, and can detect an abnormal cell among countless battery cells manufactured during the battery manufacturing process without photographing the inside, thus shortening the time for detecting an abnormal cell.

[0107] FIG. 9 is a flowchart illustrating the operation method of a battery diagnostic system according to one embodiment disclosed in this document.

[0108] Referring to FIG. 9, in operation 900, the battery management device (10) can acquire first impedance data. The battery management device (10) can acquire first impedance data of the battery based on electrochemical impedance spectroscopy (EIS).

[0109] In operation 902, the battery management device (10) can generate second impedance data that corrects the first impedance data. The battery management device (10) can generate second impedance data that corrects the inductance data corresponding to the RL circuit in the first impedance data based on an equivalent circuit comprising one or more resistor-capacitor (RC) circuits and one or more resistor-inductor (RL) circuits corresponding to the first impedance data.

[0110] In operation 904, the battery management device (10) can generate second DRT data by converting second impedance data into DRT data.

[0111] In operation 906, the battery management device (10) can diagnose the condition of the battery based on the second DRT data. The battery management device (10) can identify one or more peaks included in the second DRT data. The battery management device (10) can identify a peak among the one or more peaks included in the second DRT data that corresponds to a specific impedance. The battery management device (10) can diagnose whether the battery is abnormal based on the peak corresponding to the specific impedance.

[0112] FIG. 10 illustrates a computing system that executes the operations of a battery management device according to an embodiment disclosed in this document.

[0113] Referring to FIG. 10, a computing system (1000) according to one embodiment disclosed in this document may include an MCU (1010), a memory (1020), an input / output I / F (1030), and a communication I / F (1040).

[0114] The MCU (1010) may be a processor that executes various programs (e.g., impedance data correction program and battery diagnostic program) stored in memory (1020), processes various data from these programs, and performs the operations of the battery diagnostic system (1) included in the aforementioned FIGS. 1 to 9.

[0115] The memory (1020) can store various programs regarding the operation of the battery management device (10). In addition, the memory (1020) can store operation data of the battery management device (10).

[0116] These memories (1020) may be provided in multiple quantities as needed. The memories (1020) may be volatile memories or non-volatile memories. As volatile memories, the memory (1020) may use RAM, DRAM, SRAM, etc. As non-volatile memories, the memory (1020) may use ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc. The memories (1020) listed above are merely examples and are not limited to these examples.

[0117] The input / output I / F (1030) can provide an interface that enables data transmission and reception between an input device (not shown), such as a keyboard, mouse, or touch panel, an output device (not shown), and an MCU (1010).

[0118] The communication I / F (1040) 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, through the communication I / F (1040), a program for diagnosing abnormalities or various data (e.g., status values) can be transmitted and received from a separately provided external server.

[0119] Terms such as "include," "compose," or "have" as used above, unless specifically stated otherwise, mean that the relevant component may be inherent; therefore, 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 meaning in the context of the relevant technology and, unless explicitly defined in this document, should not be interpreted in an ideal or overly formal sense.

[0120] The foregoing description is merely an illustrative explanation of the technical concept disclosed in this document, and a person skilled in the art to which the embodiments disclosed in this document pertain can make various modifications and variations within the scope of the essential characteristics of the embodiments disclosed in this document. Accordingly, the embodiments disclosed in this document are intended to explain, not limit, the technical concept of the embodiments disclosed in this document, and the scope of the technical concept disclosed in this document is not limited by these embodiments. The scope of protection of the technical concept disclosed in this document shall be interpreted by the claims below, and all technical concepts within an equivalent scope shall be interpreted as being included within the scope of rights of this document.

Claims

1. An interface for acquiring first impedance data of a battery based on electrochemical impedance spectroscopy (EIS); and A second impedance data is generated by correcting the inductance data from the first impedance data above, and A controller comprising a battery condition diagnosing based on the second impedance data. Battery management device.

2. In Claim 1, The above controller is, Generating the second impedance data by correcting the inductance data corresponding to the resistor-inductor circuit in the first impedance data based on an equivalent circuit comprising one or more resistor-capacitor (RC) circuits and one or more resistor-inductor (RL) circuits. Battery management device.

3. In Claim 2, The above controller is, Generating the second impedance data by removing the inductance data from the first impedance data. Battery management device.

4. In Claim 2, The above controller is, A first impedance data is generated by reconstructing the first impedance data based on a plurality of Voigt Circuits corresponding to the first impedance data, and Calculate the error value between the first impedance data and the reconstructed first impedance data, and When the above error value exceeds a threshold value, the second impedance data is generated. Battery management device.

5. In Claim 2, The above controller is, Generating second DRT data by converting the above second impedance data into DRT (Distribution of Relaxation Time), Battery management device.

6. In Claim 5, The above controller is, Identify one or more peaks included in the above second DRT data, and Calculate one or more impedance values ​​corresponding to the one or more peaks mentioned above, and Diagnosing the state of the battery based on the above impedance value, Battery management device.

7. In Claim 1, The above controller is, Based on the above second impedance data, the resistance is extracted, and Diagnosing the state of the battery based on the above resistance, Battery management device.

8. In Claim 7, The above controller is, Generate second DRT data by converting the above second impedance data into DRT (Distribution of Relaxation Times), and Extracting the first resistance based on the above second DRT data, Battery management device.

9. In Claim 8, The above controller is, Identifying the peak corresponding to the first resistance among the plurality of peaks included in the second DRT data, and Calculate the value of the first resistance corresponding to the identified peak, and Diagnosing the state of the battery based on the value of the first resistance above, Battery management device.

10. In Claim 8, The first resistance above includes charge transfer resistance, interface resistance (SEI / CEI layer resistance), and contact resistance. Battery management device.

11. In Claim 7, The above controller is, Calculating the value of the second resistance based on the above second impedance data, Battery management device.

12. In Claim 11, The above controller is, Detecting an abnormal battery cell among the plurality of battery cells based on an Interquartile Range (IQR) based on the value of the second resistance, Battery management device.

13. In Claim 11, The above second resistance corresponds to ohmic resistance, and The above controller is, Calculating the value of the above ohmic resistance, Battery management device.

14. Operation of acquiring first impedance data of a battery based on electrochemical impedance spectroscopy (EIS); The operation of generating second impedance data by correcting inductance data from the first impedance data; and A method including an operation to diagnose the state of the battery based on the second impedance data. Method of operation of a battery management device.

15. In Claim 14, The operation of generating the above second impedance data is, The method comprises an operation of generating the second impedance data by correcting the inductance data corresponding to the resistor-inductor circuit in the first impedance data based on an equivalent circuit comprising one or more resistor-capacitor (RC) circuits and one or more resistor-inductor (RL) circuits. Method of operation of a battery management device.

16. In Claim 15, The operation of generating the above second impedance data is, A method comprising the operation of generating the second impedance data by removing the inductance data from the first impedance data. Method of operation of a battery management device.

17. In Claim 15, The operation of generating first impedance data reconstructed based on a plurality of Voigt circuits corresponding to the first impedance data; and The method further includes an operation to calculate an error value between the first impedance data and the reconstructed first impedance data. The operation of generating the above second impedance data is, The operation of generating the second impedance data when the above error value exceeds a threshold value, Method of operation of a battery management device.

18. In Claim 15, The method further includes the operation of generating second DRT data by converting the second impedance data into DRT (Distribution of Relaxation Time). Method of operation of a battery management device.

19. In Claim 18, An operation to identify one or more peaks included in the second DRT data; and The method further includes an operation of calculating one or more impedance values ​​corresponding to one or more of the above-mentioned peaks, and The operation of diagnosing the state of the battery based on the second impedance data is, A method including an operation to diagnose the state of the battery based on the above impedance value. Method of operation of a battery management device.

20. In Claim 14, The operation of diagnosing the state of the battery based on the second impedance data is, The operation of extracting resistance based on the above second impedance data, and A method including an operation to diagnose the state of the battery based on the resistance above. Method of operation of a battery management device.

21. In claim 20, The operation of extracting the resistance based on the second impedance data is, The operation of generating second DRT data by converting the above second impedance data into DRT (Distribution of Relaxation Times), and The operation of extracting a first resistance based on the second DRT data above, Method of operation of a battery management device.

22. In Claim 21, The operation of extracting the first resistance based on the second DRT data is, An operation of identifying a peak corresponding to the first resistance among a plurality of peaks included in the second DRT data, and The operation includes calculating the value of the first resistance corresponding to the identified peak, and The operation of diagnosing the state of the battery based on the above resistance is, A method including an operation to diagnose the state of the battery based on the value of the first resistance. Method of operation of a battery management device.

23. In Claim 21, The first resistance above includes charge transfer resistance, interface resistance (SEI / CEI layer resistance), and contact resistance. Method of operation of a battery management device.

24. In claim 20, The operation of extracting the resistance based on the second impedance data is, It includes an operation to calculate the value of a second resistance based on the second impedance data above, and The operation of diagnosing the state of the battery based on the above resistance is, A method including an operation to diagnose the state of the battery based on the value of the second resistance. Method of operation of a battery management device.

25. In Claim 24, The operation of diagnosing the state of the battery based on the value of the second resistance is, The operation of diagnosing the state of the battery based on an interquartile range (IQR) based on the value of the second resistance, Method of operation of a battery management device.

26. In Claim 24, The above second resistance corresponds to ohmic resistance, Method of operation of a battery management device.

27. A computer-readable medium storing a program for executing the method described in any one of claims 14 to 26.

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