Electronic device for detecting battery abnormalities and method of operation thereof

Abstract

According to one embodiment of the present disclosure, an electronic device includes a battery module including a plurality of cells, a sensor circuit for acquiring a state value of each of the plurality of cells, and a processor, wherein the processor acquires the state value of each of the plurality of cells as input data via the sensor circuit, acquires feature data based on a feature matrix derived from the input data using a specified matrix decomposition algorithm, and identifies whether each of the plurality of cells is abnormal based on the feature data. The feature matrix may be a diagonal matrix corresponding to the input data, in which a specified number of major diagonal elements are replaced with zeros.

Description

[Technical Field]

[0001] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2022-0113111, filed on September 6, 2022, and all contents disclosed in the documents of this Korean patent application are incorporated herein by reference.

[0002] SUMMARY OF THE INVENTION The embodiments disclosed herein relate to an electronic device for detecting battery anomalies and a method of operation thereof. [Background technology]

[0003] Secondary batteries, which are highly applicable to various products and have electrical properties such as high energy density, are widely used not only in portable devices but also in electric vehicles (EVs) and hybrid electric vehicles (HEVs) that are driven by electrical sources.

[0004] Currently widely used types of secondary batteries include lithium-ion batteries, lithium polymer batteries, nickel-cadmium batteries, nickel-metal hydride batteries, and nickel-zinc batteries. The operating voltage of such unit secondary battery cells, i.e., unit battery cells, is approximately 2.5 to 4.5 volts (V). Therefore, if a higher output voltage is required, a battery pack may be constructed by connecting multiple battery cells in series. Alternatively, a battery pack may be constructed by connecting multiple battery cells in parallel depending on the required charge / discharge capacity of the battery pack. Therefore, the number of battery cells included in the battery pack can be variously set depending on the required output voltage or charge / discharge capacity. Summary of the Invention [Problem to be solved by the invention]

[0005] A battery pack may include a plurality of battery cells connected in series and / or parallel, and therefore, even if an abnormal battery cell is present among the plurality of battery cells, it may not be easy to detect the abnormality of the battery cell. Therefore, a method for detecting an abnormal battery cell among a plurality of battery cells is required.

[0006] The technical problems of the embodiments disclosed in this document are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0007] An electronic device according to one embodiment disclosed in this document includes a battery module including a plurality of cells, a sensor circuit configured to acquire a state value for each of the plurality of cells, and a processor, wherein the processor acquires a state value for each of the plurality of cells as input data via the sensor circuit, acquires feature data based on a feature matrix derived from the input data using a specified matrix decomposition algorithm, and identifies whether each of the plurality of cells is abnormal based on the feature data, and the feature matrix may be a matrix in which values ​​of a specified number of major diagonal elements of a diagonal matrix corresponding to the input data are replaced with zeros.

[0008] According to one embodiment of the present disclosure, the specified number may be the smallest number that ensures that the occupancy rate of the major diagonal element relative to the sum of the plurality of diagonal elements exceeds a specified value.

[0009] According to one embodiment of the present disclosure, the input data may be obtained over a specified range of measurements, and the measurements may include at least one of voltage, current, resistance, SOC (state of charge), SOH (state of health), or temperature. According to an embodiment of the present disclosure, when the measurement item is voltage, the specified range may be within 3.9 to 4.1V.

[0010] According to one embodiment of the present disclosure, the input data may be acquired at specified time intervals during a specified time period when the battery module is being charged.

[0011] According to an embodiment of the present disclosure, the processor may be configured to identify additional input data based on the input data, and obtain the feature data based on the input data and the additional input data.

[0012] According to an embodiment of the present disclosure, the additional input data may include state values ​​of cells other than the plurality of cells. According to one embodiment of the present disclosure, the additional input data may include previously obtained state values ​​of the plurality of cells.

[0013] According to one embodiment of the present disclosure, the processor can obtain feature values ​​for each of the plurality of cells based on the feature components of each of the plurality of cells included in the feature data, and identify cells among the plurality of cells that have feature values ​​that exceed a specified reference feature value.

[0014] According to one embodiment of the present disclosure, the electronic device may further include a display, and the processor may be configured to provide a user notification via the display in response to at least one cell of the plurality of cells being identified as being in an abnormal state.

[0015] According to one embodiment of the present disclosure, a method for operating an electronic device includes the following operations: acquiring values ​​relating to the state of each of a plurality of cells of the electronic device as input data via a sensor circuit of the electronic device; acquiring feature data based on a feature matrix derived from the input data using a specified matrix decomposition algorithm; and identifying whether each of the plurality of cells is abnormal based on the feature data. The feature matrix may be a matrix in which the values ​​of a specified number of major diagonal elements of a diagonal matrix for the input data are replaced with zeros.

[0016] According to one embodiment of the present disclosure, the operation of obtaining the feature data may include an operation of identifying reference input data based on the input data, and an operation of obtaining the feature data based on the input data and the reference input data.

[0017] According to one embodiment of the present disclosure, the operation of identifying whether each of the plurality of cells is abnormal may include an operation of obtaining a feature value for each of the plurality of cells based on the feature components of each of the plurality of cells included in the feature data, and an operation of identifying cells among the plurality of cells that have a feature value that exceeds a specified reference feature value. [Effects of the Invention]

[0018] The electronic device and its operating method according to various embodiments disclosed herein can detect an abnormal battery cell among a plurality of battery cells.

[0019] The effects of the electronic device for detecting battery abnormalities and the operating method thereof disclosed in this document are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the disclosure of this document. [Brief explanation of the drawings]

[0020] [Figure 1] FIG. 1 is a block diagram of an electronic device according to an embodiment of the present disclosure. [Figure 2] 10 is a flowchart illustrating an operation of an electronic device according to an embodiment of the present disclosure. [Figure 3a] 1 illustrates a graph according to an embodiment of the present disclosure. [Figure 3b] 1 illustrates a graph according to an embodiment of the present disclosure. [Figure 3c] 1 illustrates a graph according to an embodiment of the present disclosure. [Figure 3d] 1 illustrates a graph according to one embodiment of the present disclosure.In connection with the description of the drawings, the same or similar reference numerals may be used for the same or similar components. DETAILED DESCRIPTION OF THE INVENTION

[0021] Embodiments of the present invention will now be described with reference to the accompanying drawings, although it should be understood that this is not intended to limit the present invention to the particular embodiments, but rather to include various modifications, equivalents, and / or alternatives to the embodiments of the present invention.

[0022] The embodiments and terms used in this document are not intended to limit the technical features described in this document to a specific embodiment, but should be understood to include various modifications, equivalents, or alternatives of the embodiment. In connection with the description of the drawings, like reference numerals may be used for like or related components. The singular form of a noun corresponding to an item may include one or more of the said item unless the relevant context clearly dictates otherwise.

[0023] In this document, each phrase 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 or all possible combinations of the items listed with that phrase. Terms such as "first," "second," "first," "second," "A," "B," "(a)," or "(b)" may be used simply to distinguish that element from other elements and do not limit that element in other respects (e.g., importance or order) unless specifically stated to the contrary.

[0024] In this document, when a (e.g., first) component is referred to as being "coupled," "coupled," or "connected" to another (e.g., second) component, with or without the terms "functionally" or "communicatively," or when a reference is made to "coupled" or "connected," this means that the component may be coupled to the other component directly (e.g., by wire or wirelessly) or indirectly (e.g., via a third component).

[0025] Methods according to various embodiments disclosed herein may be provided in a computer program product. The computer program product may be traded between a seller and a buyer as a commodity. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disc read-only memory (CD-ROM)) or distributed online (e.g., downloaded or uploaded) via 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 at least temporarily stored or temporarily generated on a machine-readable storage medium such as the memory of a manufacturer's server, an application store server, or an intermediary server.

[0026] According to the embodiments disclosed herein, each of the aforementioned components (e.g., modules or programs) may include one or more entities, and some of the entities may be located separately in other components. According to the embodiments disclosed herein, one or more of the aforementioned components or operations may be omitted, or one or more other components or operations may be added. Alternatively or additionally, multiple components (e.g., modules or programs) 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 to those performed by the respective components of the multiple components before the integration. According to the embodiments disclosed herein, operations performed by modules, programs, or other components may be performed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be performed in a different order, omitted, or one or more other operations may be added.

[0027] FIG. 1 is a block diagram of an electronic device 101 according to one embodiment of the present disclosure. 1 , the electronic device 101 may include a battery module 110, a sensor circuit 120, a communication circuit 130, a memory 140, and a processor 150. According to an embodiment, at least one component (e.g., the battery module 110) of the electronic device 101 shown in FIG. 1 may be replaced with another component (e.g., a battery pack including a plurality of battery modules 110). According to an embodiment, at least one component (e.g., the battery module 110) of the electronic device 101 shown in FIG. 1 may be configured in plural. According to an embodiment, at least one component (e.g., the sensor circuit 120 or the communication circuit 130) of the electronic device 101 shown in FIG. 1 may be excluded from the electronic device 101. According to an embodiment, the electronic device 101 may further include at least one component (e.g., a power device (e.g., a motor), a display, an input device, or an output device) other than the components shown in FIG. 1 .

[0028] In one embodiment, the electronic device 101 may be a battery management system (BMS). When the electronic device 101 is implemented with a battery management system, the electronic device 101 can provide power from the battery module 110 to an external component (e.g., a motor).

[0029] In one embodiment, the electronic device 101 may be a battery swapping station (BSS). When the electronic device 101 is implemented as a battery swapping station, the electronic device 101 may include multiple slots for storing and / or charging multiple battery modules 110.

[0030] In one embodiment, the battery module 110 can provide power to one or more components of the electronic device 101. In one embodiment, the battery module 110 is detachable from the electronic device 101.

[0031] In one embodiment, the battery module 110 may include one or more battery cells 111, 113, or 115. The one or more battery cells 111, 113, or 115 may be included in the battery module 110 in a state where they are electrically connected to each other. For example, the one or more battery cells 111, 113, or 115 may be connected to each other in series and / or in parallel. According to an embodiment, the one or more battery cells 111, 113, or 115 may be included in the battery module 110 in a state where they are electrically isolated from each other.

[0032] In one embodiment, the sensor circuit 120 can obtain information about the battery module 110. In one embodiment, the sensor circuit 120 can obtain a value (or information) related to the status of each of one or more battery cells 111, 113, or 115. In one embodiment, the status value can include one or more values ​​related to the voltage, current, resistance, state of charge (SOC), state of health (SOH), temperature, or a combination thereof, of the battery cell. Hereinafter, the status value may be referred to as a "status value."

[0033] In one embodiment, the sensor circuit 120 can provide information (eg, status values) of one or more battery cells 111, 113, or 115, respectively, to the processor 150.

[0034] In one embodiment, the communication circuitry 130 can establish a wired or wireless communication channel between the electronic device 101 and the external electronic device 102 and send and receive data to and from the external electronic device 102 via the established communication channel.

[0035] In one embodiment, the communication circuitry 130 is capable of communicating based on at least one radio access technology (RAT). In one embodiment, the communication circuitry 130 is capable of transmitting and receiving data to and from the external electronic device 102 using at least one RAT.

[0036] In one embodiment, memory 140 may include volatile memory and / or non-volatile memory. In one embodiment, memory 140 can store data used by at least one component of electronic device 101 (e.g., processor 150 or sensor circuitry 120). For example, the data can include software (or instructions therefor), input data, or output data. In one embodiment, the instructions, when executed by processor 150, can cause electronic device 101 to perform the operation defined by the instructions.

[0037] In one embodiment, processor 150 can execute software to control at least one other component (e.g., hardware or software component) of electronic device 101 coupled to processor 150 and perform various data processing or calculations.

[0038] A method for determining whether one or more battery cells 111, 113, or 115 included in the battery module 110 are abnormal in the electronic device 101 according to an embodiment of the present disclosure will be described below.

[0039] In one embodiment, the electronic device 101 can acquire status values ​​(e.g., one or more values ​​related to voltage, current, resistance, SOC, SOH, or temperature) of each of the one or more battery cells 111, 113, or 115. In one embodiment, the electronic device 101 can acquire status values ​​of each of the one or more battery cells 111, 113, or 115 during a specified time period (e.g., 180 seconds (sec)). In one embodiment, the electronic device 101 can acquire status values ​​of each of the one or more battery cells 111, 113, or 115 at specified time intervals (e.g., 0.1 seconds) during the specified time period (e.g., 180 seconds (sec)). For example, the electronic device 101 can acquire voltage values ​​of each of the one or more battery cells 111, 113, or 115. As another example, the electronic device 101 can acquire current values ​​of each of the one or more battery cells 111, 113, or 115.

[0040] In one embodiment, the electronic device 101 may obtain a state value of the battery cell while the battery cell satisfies a specified condition. In one embodiment, the specified condition of the battery cell may refer to a state in which the battery cell is being charged. In one embodiment, the specified state of the battery cell may refer to a state in which the voltage (e.g., open circuit voltage, OCV) exhibited by the battery cell is within a specified voltage range (e.g., 3.9 to 4.1 V) while the battery cell is being charged.

[0041] Hereinafter, the state values ​​of each of the one or more battery cells 111, 113, or 115 may be referred to as "input data." In one embodiment, the input data may be represented as a matrix (e.g., an M×N matrix) consisting of N values ​​for each of the M battery cells 111, 113, or 115. For example, the input data may consist of N voltage values ​​for each of the M battery cells 111, 113, or 115. As another example, the input data may consist of N values ​​of one of current, resistance, SOC, SOH, or temperature for each of the M battery cells 111, 113, or 115. Here, M is the number of battery cells 111, 113, or 115, and N may correspond to a value obtained by dividing a specified time period by a specified time interval. For example, if the number of battery cells 111, 113, or 115 is 100, the specified time period is 180 seconds, and the specified time interval is 0.1 seconds, M may be 100 and N may be 1800. For example, the input data (D input ) can be expressed as the following Equation 1:

[0042]

number

[0043] In Equation 1, the input data (D input ) each entry (v 1、1 , v 1、N , v M、1 , and v M、N ) can indicate the status value of the battery cell 111, 113, or 115. input ) each column (or column vector) can represent M state values ​​acquired at the same time (or at the sensing time of the sensor circuit 120). input ) each row (or row vector) can represent N state values ​​obtained from each of the battery cells 111, 113, or 115 during a specified time interval. For example, the entries of the first column vector (v 1、1 and v M、1) may be the state value of the battery cell 111, 113, or 115 obtained at the first time point. 1、1 and v M、1 ) may be the state value obtained from the first battery cell during the specified time interval. In one embodiment, the input data (D input ) each entry (v 1、1 , v 1、N , v M、1 , and v M、N ) can represent the same type of state value. For example, the entry (v 1、1 , v 1、N , v M、1 , and v M、N ) can indicate one type of status value: current, resistance, SOC, SOH, or temperature.

[0044] In one embodiment, the electronic device 101 can obtain feature data based on input data. In one embodiment, the electronic device 101 can obtain feature data from the input data based on a specified decomposition algorithm. In one embodiment, the specified decomposition algorithm can be based on matrix decomposition. In one embodiment, the specified decomposition algorithm can be based on singular value decomposition (SVD). In one embodiment, the specified decomposition algorithm can be based on eigenvalue decomposition and / or principal component analysis (PCA).

[0045] In one embodiment, the electronic device 101 can perform singular value decomposition of the input data. For example, if the input data consists of N values ​​for each of the M battery cells 111, 113, or 115, the input data can be decomposed into an M×N matrix (D input ), the input data can be subjected to singular value decomposition as shown in Equation 2 below.

[0046]

number

[0047] In Equation 2, U is an M×M unitary matrix, S is an M×N diagonal matrix whose diagonal elements have values ​​equal to or greater than 0 and whose off-diagonal elements are 0, and V T is an N×N unitary matrix. In one embodiment, when M is smaller than N, the matrix S of input data can be expressed as Equation 3 below:

[0048]

number

[0049] In Equation 3, the diagonal elements of the matrix S (s 1、1 , s 2、2 , and s M、M The remaining elements of the matrix S, except for the diagonal elements (s 1、1 , s 2、2 , and s M、M ) where diagonal elements with higher values ​​may have lower row indices and lower column indices.

[0050] In one embodiment, the electronic device 101 may classify diagonal elements (or singular values) based on a matrix S of input data. In one embodiment, the electronic device 101 may classify L diagonal elements included in the matrix S into major diagonal elements or minor diagonal elements. In one embodiment, the electronic device 101 may classify k diagonal elements of the L diagonal elements into major diagonal elements in descending order of value. In one embodiment, the electronic device 101 may classify p diagonal elements of the L diagonal elements into minor diagonal elements in descending order of value. Here, L may be the lower value of M or N, and the sum of k and p may be L. Here, the k diagonal elements may be diagonal elements for obtaining common data from the input data, and the p diagonal elements may be diagonal elements for obtaining feature data from the input data.

[0051] In one embodiment, k and p can be determined based on the occupancy (or ratio) of the diagonal elements. In one embodiment, the occupancy may be the ratio of the sum of the L diagonal elements to the sum of the specified diagonal elements. The occupancy k of the major diagonal element can be determined based on the following Equation 4:

[0052]

number

[0053] In Equation 4, L is the lower value of M or N, and s i、i is the value of the i-th diagonal element (singular value), and s j、j is the value of the j-th diagonal element (singular value), and r(k) denotes the ratio of the sum of the k major diagonal elements to the sum of the L diagonal elements. Hereinafter, M is exemplified as being lower than N, and thus L can be exemplified as being M.

[0054] In one embodiment, the electronic device 101 may identify the smallest k that causes r(k) to have a specified occupancy rate (e.g., 0.998) or greater. In one embodiment, the occupancy rate may be changed based on the acquisition status of the input data. For example, if the input data is below the lower limit of a specified voltage range (e.g., 3.9 to 4.1 V), a higher occupancy rate than the occupancy rate set for the specified voltage range (e.g., 0.998) may be set.

[0055] In another embodiment, the electronic device 101 may obtain the number (k) of diagonal elements (or singular values) that meet a specified criterion based on the magnitude of N or M. For example, the electronic device 101 may identify k that corresponds to the upper, lower, or rounded value of the smaller of N or M multiplied by a ratio value (e.g., 0.98).

[0056] In one embodiment, the electronic device 101 may acquire the feature data. In one embodiment, the electronic device 101 may acquire the feature data based on the identified k. The feature data may be acquired based on the following Equation 5:

[0057]

number

[0058] In Equation 5, U is the M×M unitary matrix in Equation 1, and V T is the N×N unitary matrix in Equation 1, and S feature is an M×N diagonal matrix in which the 1st to kth diagonal elements (i.e., major diagonal elements) of S in Equation 1 are replaced with 0 (or elements other than the pth to Lth diagonal elements are 0). Hereinafter, S feature can be referred to as a feature matrix. According to an embodiment, the common data (D common ) is the input data (D input ) to the feature data (D features ) may be excluded.

[0059] In one embodiment, the electronic device 101 can analyze the characteristic data. In one embodiment, the electronic device 101 can obtain standardized data based on the feature components included in the feature data. In one embodiment, the electronic device 101 can identify a standardized score for each of the feature components of one or more battery cells 111, 113, or 115 included in the feature data. In one embodiment, the feature components of each of the one or more battery cells 111, 113, or 115 are stored in the feature data (D features ) may be the N components contained in its own row among the M rows of the feature data (D features ) may be the N components of the first row.

[0060] In one embodiment, normalization may be converting values ​​into normalized scores (or Z-scores). For example, normalization may be based on Equation 6 below:

[0061]

number

[0062] In equation 6, z feature、i、j may be the standardized score of the j-th entry of the i-th row vector of feature data. feature、i、j may be the value of the j-th entry in the i-th row vector of the feature data. feature、j may be the mean of the entries in the j-th column vector of the feature data. feature、j may be the standard deviation of the entries of the j-th column vector of the feature data, where i is an integer greater than or equal to 1 and less than or equal to the number of rows of the feature data, and j is an integer greater than or equal to 1 and less than or equal to the number of columns of the feature data.

[0063] In one embodiment, the electronic device 101 may obtain a feature value for one or more battery cells 111, 113, or 115 based on the normalized score of each of the one or more battery cells 111, 113, or 115. In one embodiment, the feature value may be obtained based on the maximum, minimum, mean, median, deviation, standard deviation, or a combination thereof, of the normalized scores. In one embodiment, the feature value may be obtained based on the maximum minus the minimum of the normalized scores. In one embodiment, the feature value may be obtained based on the following Equation 7:

[0064]

number

[0065] In equation 7, v feature、i is the feature value of the i-th row vector of the standardized data, and z max、i is the maximum standardized score of the i-th row vector of the standardized data, and zmin、i may be the minimum of the standardized scores of the i-th row vector of the standardized data.

[0066] In one embodiment, the electronic device 101 can identify whether one or more of the battery cells 111, 113, or 115 are abnormal based on the results of analyzing the characteristic data.

[0067] In one embodiment, the electronic device 101 may identify a battery cell among the one or more battery cells 111, 113, or 115 having a characteristic value that exceeds a specified reference characteristic value as being abnormal. In one embodiment, the electronic device 101 may identify a battery cell among the one or more battery cells 111, 113, or 115 having the highest characteristic value as being abnormal. In one embodiment, the electronic device 101 may identify a battery cell among the one or more battery cells 111, 113, or 115 having the lowest characteristic value as being abnormal. According to an embodiment, the electronic device 101 may identify a battery cell among the one or more battery cells 111, 113, or 115 having a characteristic value that is less than a specified reference characteristic value as being abnormal. According to an embodiment, the electronic device 101 may identify a battery cell among the one or more battery cells 111, 113, or 115 having a characteristic value that is outside a specified reference characteristic value range as being abnormal. In one embodiment, the reference characteristic value may be a value for determining whether a battery cell is abnormal. In one embodiment, the reference feature value may be determined experimentally.

[0068] In one embodiment, if a faulty battery cell is identified, the electronic device 101 can provide a notification to the user via an output device (or display). In one embodiment, the notification provided to the user can include a notification prompting the user to check the battery cell for a fault, a notification prompting the user to replace the battery cell, or a combination thereof.

[0069] According to an embodiment, the number of one or more battery cells 111, 113, or 115 may not be sufficient to confirm abnormalities in the battery cells based on the disassembly algorithm. Hereinafter, a method for the electronic device 101 according to an embodiment of the present disclosure to configure input data for obtaining effective characteristic data in a situation where the number of one or more battery cells 111, 113, or 115 is limited will be described.

[0070] In one embodiment, the electronic device 101 can store in the memory 140 the status values ​​of each of the one or more battery cells 111, 113, or 115 acquired via the sensor circuit 120. In one embodiment, the electronic device 101 can store in the memory 140 the status values ​​of each of the one or more battery cells 111, 113, or 115 in units of a specified time interval. For example, the electronic device 101 can store in the memory 140 the status values ​​acquired during a first time interval and the status values ​​acquired during a second time interval. Here, the second time interval may or may not overlap at least partially with the first time interval.

[0071] In one embodiment, the electronic device 101 can acquire additional input data from previously acquired state values ​​stored in the memory 140. In one embodiment, the additional input data can include previously acquired state values ​​of one or more battery cells 111, 113, or 115. Here, the additional input data can be data having an acquisition environment similar to that of the current input data. In one embodiment, the acquisition environment may refer to the voltage, current, resistance, SOC, SOH, or temperature conditions during acquisition of the input data.

[0072] In one embodiment, the electronic device 101 can acquire additional input data in which at least one element of the one or more elements indicating the acquisition environment is the same and / or similar to the current input data. For example, if the current input data is acquired in a state in which the battery cell has a specified voltage range (e.g., 3.9 to 4.1 V) while being charged, the electronic device 101 can acquire additional input data from the information stored in the memory 140 based on a state value acquired in a state in which the battery cell has the specified voltage range (or a voltage range including the specified voltage range) while being charged.

[0073] In one embodiment, the electronic device 101 can configure the input data and the additional input data as new input data (e.g., M×N matrix data). In one embodiment, the electronic device 101 can obtain feature data based on the new input data.

[0074] According to an embodiment, the electronic device 101 can transmit the input data and / or information indicative of the acquisition environment of the input data to the external electronic device 102 using the communication circuitry 130. In one embodiment, the electronic device 101 can acquire additional input data corresponding to the input data and / or the information indicative of the acquisition environment of the input data from the external electronic device 102. In one embodiment, the electronic device 101 can acquire characteristic data based on the input data and the additional input data acquired from the external electronic device 102. In one embodiment, the additional input data from the external electronic device 102 can include status values ​​of cells other than one or more of the battery cells 111, 113, or 115.

[0075] According to an embodiment, at least some of the operations for determining an abnormality in one or more battery cells 111, 113, or 115 included in the battery module 110 via the electronic device 101 may be performed via the external electronic device 102. For example, when the electronic device 101 transmits input data to the external electronic device 102, the external electronic device 102 may obtain characteristic data based on the input data, identify whether each of the one or more battery cells 111, 113, or 115 is abnormal based on the characteristic data, and provide the identification result of whether each is abnormal to the electronic device 101.

[0076] FIG. 2 is a flowchart illustrating the operation of the electronic device 101 according to an embodiment of the present disclosure. 2 , in operation 210, the electronic device 101 may acquire input data. A state value (e.g., voltage, current, resistance, SOC, SOH, or temperature) of each of the one or more battery cells 111, 113, or 115 may be acquired as input data. In one embodiment, the electronic device 101 may acquire a state value of each of the one or more battery cells 111, 113, or 115 acquired at specified time intervals during a specified time period as input data. In one embodiment, the electronic device 101 may acquire a state value of the battery cell acquired while the battery cell has a specified state as input data.

[0077] In one embodiment, the electronic device 101 can utilize as input data additional input data from previously acquired information stored in the memory 140. In one embodiment, the electronic device 101 can utilize as input data additional input data acquired from an external electronic device 102 using the communications circuitry 130.

[0078] In operation 220, the electronic device 101 may extract feature data. In one embodiment, the electronic device 101 may extract (or obtain) the feature data from the input data based on a specified matrix decomposition algorithm. In one embodiment, the specified matrix decomposition algorithm may be based on singular value decomposition, eigenvalue decomposition, and / or principal component analysis.

[0079] For example, the electronic device 101 can perform singular value decomposition on the input data. Then, the electronic device 101 can classify the diagonal elements (or singular values) based on the matrix S of the singular value decomposed input data. Then, the electronic device 101 can classify the input data (D input ) to the feature data (D features ) can be extracted.

[0080] In operation 230, the electronic device 101 can analyze the feature data. The electronic device 101 can identify feature components of each of the one or more battery cells 111, 113, or 115 included in the feature data. In one embodiment, the electronic device 101 can obtain feature values ​​of the one or more battery cells 111, 113, or 115 based on the feature components of each of the one or more battery cells 111, 113, or 115. For example, the electronic device 101 can obtain normalized data based on the feature components included in the feature data, and obtain feature values ​​of the one or more battery cells 111, 113, or 115 based on the normalized scores of each of the one or more battery cells 111, 113, or 115.

[0081] In operation 240, the electronic device 101 can determine whether there is an abnormality. In one embodiment, the electronic device 101 can identify one or more battery cells 111, 113, or 115 that have a characteristic value that exceeds a specified reference characteristic value as being abnormal. According to an embodiment, the electronic device 101 can identify one or more battery cells 111, 113, or 115 that have a characteristic value that is less than a specified reference characteristic value as being abnormal. According to an embodiment, the electronic device 101 can identify one or more battery cells 111, 113, or 115 that have a characteristic value that falls outside a range of specified reference characteristic values ​​as being abnormal.

[0082] The electronic device 101 may then provide a notification to the user via an output device (or display) if a faulty battery cell is identified. In one embodiment, the notification provided to the user may include a notification prompting the user to check the battery cell for a fault, a notification prompting the user to replace the battery cell, or a combination thereof.

[0083] 3a illustrates a graph 301 according to one embodiment of the present disclosure. Referring to FIG. 3a, it can be seen that input data 310 is acquired for approximately 180 seconds (1440-1260 seconds). It can be seen that the input data 310 is acquired within a specified voltage range of the battery cell (e.g., 3.9-4.1 V).

[0084] 3b illustrates a graph 302 according to one embodiment of the present disclosure. The data 320 shown in the graph 302 is common data (D common ) can be shown.

[0085] 3c illustrates a graph 303 according to one embodiment of the present disclosure. The data shown in the graph 303 is feature data (D features ) can be shown. The input data 310 in FIG. 3a can be represented as common data (D common ) and feature data (D features) may be the same as the sum of

[0086] 3c, it can be seen that the voltage value 330 of a particular battery cell in Fig. 3c fluctuates over a particular time range (t0). When the voltage value 330 fluctuates beyond a specified reference value, the characteristic value of the battery cell can exceed the reference characteristic value (e.g., 4).

[0087] 3d illustrates a graph 304 according to one embodiment of the present disclosure. The characteristic values ​​shown in the graph 304 may be characteristic values ​​of each of the battery cells. 3d, when the voltage value 330 in FIG. 3c fluctuates beyond a specified reference value, the characteristic value 340 of the battery cell can be confirmed as 5, which exceeds the reference characteristic value (e.g., 4). This allows the battery cell to be determined to be in an abnormal state.

Claims

1. 1. An electronic device, comprising: a battery module including a plurality of cells; a sensor circuit for acquiring a state value of each of the plurality of cells; a processor; Including, The processor: acquiring values ​​relating to the states of the plurality of cells as input data via the sensor circuit; obtaining feature data based on a feature matrix derived from the input data using a specified matrix decomposition algorithm; identifying whether each of the plurality of cells is abnormal or not based on the characteristic data; The electronic device, wherein the feature matrix is ​​a matrix in which values ​​of a specified number of major diagonal elements among a plurality of diagonal elements of a diagonal matrix for the input data are replaced with 0.

2. The electronic device according to claim 1 , wherein the specified number is the minimum number that ensures that the occupancy rate of the major diagonal element relative to the total of the plurality of diagonal elements exceeds a specified value.

3. The input data is acquired within a specified range of a measurement item; The electronic device of claim 1 , wherein the measurement items include at least one of voltage, current, resistance, SOC, SOH, or temperature.

4. 4. The electronic device according to claim 3, wherein when the measurement item is voltage, the specified range is within 3.9 to 4.1 V.

5. The electronic device of claim 3 , wherein the input data is acquired at specified time intervals during a specified time period when the battery module is being charged.

6. The processor: identifying additional input data based on the input data; The electronic device according to claim 1 , wherein the characteristic data is obtained based on the input data and the additional input data.

7. The electronic device of claim 6 , wherein the additional input data includes state values ​​of cells other than the plurality of cells.

8. The electronic device of claim 6 , wherein the additional input data includes previously obtained state values ​​of the plurality of cells.

9. The processor: acquiring a feature value for each of the plurality of cells based on a feature component of each of the plurality of cells included in the feature data; The electronic device of claim 1 , wherein cells of the plurality of cells are identified that have a characteristic value that exceeds a specified reference characteristic value.

10. further comprising a display; The processor: The electronic device of claim 1 , further comprising: a display configured to provide a user notification via the display in response to at least one cell of the plurality of cells being identified as having an abnormal condition.

11. 1. A method of operating an electronic device, comprising: an operation of obtaining, as input data, values ​​relating to the states of each of a plurality of cells of the electronic device via a sensor circuit of the electronic device; obtaining feature data based on a feature matrix derived from the input data using a specified matrix decomposition algorithm; an operation of identifying whether each of the plurality of cells is abnormal based on the feature data; Including, A method according to claim 1, wherein the feature matrix is ​​a matrix in which values ​​of a specified number of major diagonal elements among a plurality of diagonal elements of a diagonal matrix for the input data are replaced with zeros.

12. The method of claim 11 , wherein the specified number is the smallest number that causes the occupancy of the major diagonal element relative to the sum of the diagonal elements to exceed a specified value.

13. The operation of acquiring the feature data includes: identifying reference input data based on the input data; and obtaining the feature data based on the input data and the reference input data.

14. The method of claim 13 , wherein the reference input data indicates information about the state of cells other than the plurality of cells.

15. The operation of identifying whether each of the plurality of cells is abnormal includes: an operation of acquiring a feature value of each of the plurality of cells based on a feature component of each of the plurality of cells included in the feature data; and identifying cells of the plurality of cells having a feature value that exceeds a specified reference feature value.

Images