Electronic device and battery diagnosis method therefor

Abstract

An electronic device according to one embodiment of the present disclosure may comprise: an information acquisition interface for acquiring, per charging cycle, voltage data of a plurality of battery cells included in a battery pack; a memory for storing at least one instruction; and a processor operatively connected to the memory. For example, the electronic device can identify a differential capacity curve on the basis of the voltage data and current data of the plurality of battery cells, identify at least one feature point for the respective battery cells by using the differential capacity curve, and diagnose whether the plurality of battery cells are abnormal on the basis of whether the at least one feature point satisfies a predetermined condition.

Description

Diagnostic methods for electronic devices and their batteries

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2025-0023771 dated February 24, 2025, and all contents disclosed in the document of said Korean patent application are incorporated herein as part of this specification.

[0002] The embodiments disclosed in this document relate to an electronic device and a method for diagnosing its battery.

[0003] Recently, active research and development on secondary batteries has been underway. Here, secondary batteries refer to rechargeable batteries, 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 manner, 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.

[0004] As the applications of such secondary batteries expand, there is a need to advance algorithms for diagnosing abnormalities. Generally, methods can be used to monitor battery voltage and identify specific battery cells with abnormalities by utilizing various voltage-dependent profiles (e.g., differential capacity curve profiles).

[0005] In particular, differential capacity curves, which represent the relationship between voltage and differential capacity (dQ / Dv) obtained by differentiating the charge / discharge capacity of a battery cell with respect to voltage, are widely utilized in battery cell diagnosis. Differential capacity curves can appear in various forms depending on the real-time state of the battery cell or voltage; therefore, there is a need to develop technologies that diagnose battery cells more accurately through characteristic points identified based on these forms.

[0006] According to one embodiment of the present disclosure, an electronic device and a battery diagnostic method thereof can be provided for acquiring data (e.g., voltage data or current data) for each battery cell, identifying a differential capacity curve based on the data, and diagnosing whether there is an abnormality for each of a plurality of battery cells using at least one feature point included in the differential capacity curve.

[0007] The technical problems to be solved by the embodiments of the present disclosure are not limited to the technical problems described above, and other technical problems can be inferred from the following embodiments.

[0008] An electronic device according to one embodiment of the present disclosure may include an information acquisition interface that acquires voltage data and current data of a plurality of battery cells included in a battery pack for each charging cycle, a memory that stores at least one instruction, and a processor operatively connected to said memory. For example, said at least one instruction may be configured such that, when executed by said processor, the electronic device identifies a differential capacity curve based on the voltage data and current data of said battery cells, identifies at least one feature point for each of said battery cells using said differential capacity curve, and diagnoses whether said battery cells are abnormal based on whether said at least one feature point satisfies a predetermined condition.

[0009] In an electronic device according to one embodiment of the present disclosure, the at least one feature point may include a target peak and a target valley within a specified voltage range of the differential capacitance curve.

[0010] In an electronic device according to one embodiment of the present disclosure, the specified voltage range may correspond to 3.8V to 4.2V.

[0011] In an electronic device according to one embodiment of the present disclosure, the at least one instruction may be configured such that, when executed by the processor, the electronic device determines the target peak using the dQ / dV value corresponding to each of the plurality of peaks or the current data when a plurality of peaks are identified within the specified voltage range.

[0012] In an electronic device according to one embodiment of the present disclosure, the at least one instruction may be configured such that, when executed by the processor, the electronic device checks the distance between the target peak and the target valley for a first battery cell among the plurality of battery cells, and if the distance satisfies the predetermined condition, it determines that there is an abnormality in the first battery cell.

[0013] In an electronic device according to one embodiment of the present disclosure, the at least one instruction may be configured such that, when executed by the processor, the electronic device monitors the number of times the distance satisfies the predetermined condition, and if the number exceeds a specified number, it determines that there is an abnormality in the first battery cell.

[0014] In an electronic device according to one embodiment of the present disclosure, the at least one instruction may be configured such that, when executed by the processor, the electronic device checks an Inter Quatile Range (IQR) value corresponding to the difference between the third quartile and the first quartile of the distance of each of the plurality of battery cells, checks a first distance and a second distance smaller than the first distance based on the IQR value, and determines that the distance exceeding the first distance or less than the second distance satisfies the predetermined condition.

[0015] In an electronic device according to one embodiment of the present disclosure, the first distance corresponds to a value obtained by adding a first value based on the IQR value to the median of the distance, and the second distance corresponds to a value obtained by subtracting a second value based on the IQR value from the median of the distance.

[0016] In an electronic device according to one embodiment of the present disclosure, the at least one instruction may be configured such that, when executed by the processor, the electronic device determines that a first type of abnormality exists in a first battery cell in which the number of times the distance exceeds the first distance is greater than or equal to the specified number of times, and determines that a second type of abnormality exists in a second battery cell in which the number of times the distance is less than the second distance is greater than or equal to the specified number of times.

[0017] In an electronic device according to one embodiment of the present disclosure, the at least one instruction may be configured such that, when executed by the processor, the electronic device determines the average distance between the peak and the valley of each of the plurality of battery cells, and determines that the distance other than a specified range based on the average distance satisfies the predetermined condition.

[0018] In an electronic device according to one embodiment of the present disclosure, the at least one instruction may be configured such that, when executed by the processor, the electronic device checks the difference between the maximum distance and the minimum distance among the distances, checks a third distance obtained by adding the median value of the distance and the difference between the distances, checks a fourth distance obtained by subtracting the median value of the distance and the difference between the distances, and determines that the distance exceeding the third distance or less than the fourth distance satisfies the predetermined condition.

[0019] A battery diagnostic method performed by an electronic device according to one embodiment of the present disclosure may include: an operation of identifying a differential capacity curve based on voltage data and current data of a plurality of battery cells obtained for each charging cycle; an operation of identifying at least one feature point for each of the plurality of battery cells using the differential capacity curve; and an operation of diagnosing whether the plurality of battery cells are abnormal based on whether the at least one feature point satisfies a predetermined condition.

[0020] In a battery diagnostic method performed by an electronic device according to one embodiment of the present disclosure, the at least one feature point may include a target peak and a target valley within a designated voltage range of the differential capacity curve. For example, the battery diagnostic method may further include an operation of determining a target peak using a dQ / dV value corresponding to each of the plurality of peaks or current data when a plurality of peaks are identified within the designated voltage range.

[0021] A battery diagnostic method performed by an electronic device according to one embodiment of the present disclosure may further include: an operation of determining the distance between the target peak and the target valley for a first battery cell among the plurality of battery cells; an operation of monitoring the number of times the distance satisfies the predetermined condition; and an operation of determining that there is an abnormality in the first battery cell when the number exceeds a specified number.

[0022] The battery diagnostic method performed by an electronic device according to one embodiment of the present disclosure may further include an operation of checking an Inter Quatile Range (IQR) value corresponding to the difference between the third quartile and the first quartile of the distance of each of the plurality of battery cells, an operation of checking a first distance and a second distance smaller than the first distance based on the IQR, and an operation of determining that the distance exceeding the first distance or less than the second distance satisfies the predetermined condition.

[0023] According to the embodiments disclosed in this document, the abnormality of each battery cell can be accurately diagnosed by using at least one feature point of the differential capacity curve identified based on the voltage data of the battery cell.

[0024] The effects of the invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art from the description in the claims.

[0025] FIG. 1 is a block diagram of an electronic device according to one embodiment of the present disclosure.

[0026] FIG. 2 illustrates a graph relating to voltage data and differential capacity curves of a battery cell according to one embodiment of the present disclosure.

[0027] FIG. 3 illustrates a box-and-whisker plot showing an InterQuartile Range (IQR) identified based on the distance between at least one feature point of a battery cell according to one embodiment of the present disclosure.

[0028] FIG. 4 is a flowchart of the operation of a battery diagnostic method performed by an electronic device according to one embodiment of the present disclosure.

[0029] FIG. 5 is a flowchart of the operation of a battery diagnostic method performed by an electronic device according to one embodiment of the present disclosure.

[0030] In describing the embodiments, technical details that are well known in the technical field to which this disclosure belongs and are not directly related to this disclosure are omitted. This is intended to convey the essence of this disclosure more clearly without obscuring it by omitting unnecessary explanations.

[0031] For the same reason, some components in the attached drawings have been exaggerated, omitted, or schematically depicted. Additionally, the size of each component does not entirely reflect its actual dimensions. Identical or corresponding components in each drawing have been assigned the same reference numbers.

[0032] The advantages and features of the present disclosure and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below but may be implemented in various different forms. The embodiments provided are merely to ensure that the disclosure is complete and to fully inform those skilled in the art of the scope of the invention, and the present disclosure is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components.

[0033] At this time, it will be understood that each block of the process flow diagrams and combinations of the flow diagrams can be executed by computer program instructions. Since these computer program instructions can be loaded into the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, the instructions executed through the processor of the computer or other programmable data processing equipment create means for performing the functions described in the flow diagram block(s). Since these computer program instructions can also be stored in computer-available or computer-readable memory that can be directed toward the computer or other programmable data processing equipment to implement functions in a specific way, the instructions stored in such computer-available or computer-readable memory can also produce a manufactured item containing means of instruction for performing the functions described in the flow diagram block(s). Since computer program instructions can also be loaded onto a computer or other programmable data processing equipment, the instructions that execute the computer or other programmable data processing equipment by creating a process that is executed by a computer through a series of operation steps performed on the computer or other programmable data processing equipment can also provide steps for executing the functions described in the flow diagram block(s).

[0034] Additionally, each block may represent a module, segment, or part of code containing one or more executable instructions for executing a specific logical function(s). It should also be noted that in some alternative execution examples, the functions mentioned in the blocks may occur out of order. For instance, two blocks described in succession may actually be executed substantially simultaneously, or the blocks may be executed in reverse order according to their corresponding functions.

[0035] In this embodiment, the term "part" refers to a software or hardware component, such as an FPGA or ASIC, and the "part" performs certain roles. However, the meaning of "part" is not limited to software or hardware. The "part" may be configured to reside in an addressable storage medium or configured to operate one or more processors. Thus, for example, the "part" includes components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and "parts" may be combined into a smaller number of components and "parts" or further separated into additional components and "parts." Furthermore, the components and "parts" may be implemented to operate one or more CPUs within a device or secure multimedia card.

[0036] The expression “at least one of a, b, and c” described throughout the specification may include ‘a alone’, ‘b alone’, ‘c alone’, ‘a and b’, ‘a and c’, ‘b and c’, or ‘a, b, and c all’.

[0037] The "terminal" mentioned below may be implemented as a computer or portable terminal capable of connecting to a server or other terminal via a network. Here, the computer includes, for example, a notebook, desktop, or laptop equipped with a web browser, and the portable terminal is a wireless communication device that ensures portability and mobility, and may include all types of handheld-based wireless communication devices such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution), communication-based terminals, smartphones, tablet PCs, etc.

[0038] Embodiments of the present disclosure are described below with reference to the attached drawings so that those skilled in the art can easily implement them. However, the present disclosure may be embodied in various different forms and is not limited to the embodiments described herein.

[0039] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0040]

[0041] FIG. 1 is a block diagram of an electronic device (100) according to one embodiment of the present disclosure.

[0042] Referring to FIG. 1, the electronic device (100) may include a memory (110), a processor (120), and an information acquisition interface (130). According to an embodiment, the electronic device (100) 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.

[0043] According to one embodiment, the memory (110) may include volatile memory and / or non-volatile memory.

[0044] According to one embodiment, the memory (110) may store data used by at least one component of the electronic device (100) (e.g., processor (120)). For example, the data may include software (or related instructions), input data, or output data. In one embodiment, the instructions may cause the electronic device (100) to perform operations defined by the instructions when executed by the processor (120).

[0045] According to one embodiment, the memory (110) may store instructions or data. For example, the memory (110) may store at least one instruction that causes the electronic device (100) (or the processor (120)) to perform various operations when executed by the processor (120). For example, a program (or at least one instruction) stored in the memory (110) may be executed by the processor (120).

[0046] According to one embodiment, the memory (110) may include a plurality of storage devices of different types. For example, the memory (110) may include a volatile and / or non-volatile storage medium. For example, the memory (110) may include at least one of RAM (random-access memory), ROM (read-only memory), eMMC (Embedded Multi-Media Card), or any combination thereof. For example, the memory (110) may include a buffer for temporarily storing data and a data area for storing data transferred from the buffer or an external device.

[0047] According to one embodiment, the processor (120) may be implemented as a computer or a similar device according to hardware, software, or a combination thereof. Hardware-wise, the processor (120) may be implemented in the form of an electronic circuit that processes electrical signals to perform control functions, and software-wise, it may be implemented in the form of a program that drives the hardware processor (120). According to one embodiment, the processor (120) may be operatively connected to a component included in the electronic device (100) (e.g., memory (110) and / or information acquisition interface (130)) to control the connected component.

[0048] According to one embodiment, the processor (120) may include a central processing unit, an application processor, a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor.

[0049] Meanwhile, unless otherwise specifically mentioned in the following description, the operation of the electronic device (100) may be interpreted as being performed under the control of the processor (120). According to one embodiment, the electronic device (100) may be implemented as at least one of a notebook, desktop, laptop, and server computing device that acquires and processes various information regarding a battery from an external device.

[0050] According to one embodiment, the information acquisition interface (130) may include a communication device and / or at least one sensor.

[0051] For example, the information acquisition interface (130) can establish a wired communication channel and / or a wireless communication channel between the electronic device (100) and an external device, and can transmit and receive data with the external device through the established communication channel. The information acquisition interface (130) can receive battery charging data from the external device and / or an external server. Here, communication, i.e., the transmission and reception of data, can be performed via wired or wireless means. To this end, the information acquisition interface (130) may include a wired communication module that connects to the internet, etc., via a LAN (Local Area Network), a mobile communication module that connects to a mobile communication network via a mobile communication base station to transmit and receive data, a short-range communication module that uses a WLAN (Wireless Local Area Network) type communication method such as Wi-Fi or a WPAN (Wireless Personal Area Network) type communication method such as Bluetooth or Zigbee, a satellite communication module that uses a GNSS (Global Navigation Satellite System) such as GPS (Global Positioning System), or a combination thereof.

[0052] For example, the information acquisition interface (130) may include at least one sensor that acquires and detects information regarding the battery. The information acquisition interface (130) may acquire data (e.g., voltage data) regarding each of the plurality of battery cells included in the battery pack. The information acquisition interface (130) may acquire voltage data of the plurality of battery cells in a time-series manner. The information acquisition interface (130) may acquire voltage data and current data of the plurality of battery cells for each charging cycle. Here, a charging cycle may refer to, for example, a procedure of charging the voltage (or charging voltage) of a battery cell from a first voltage range (e.g., 2.5 to 2.75 V) to a second voltage range (e.g., 3.8 to 4.2 V). When the voltage of the battery cell falls within the second range, one charging cycle is terminated, and a discharge cycle may be performed to discharge the battery cell so that the voltage of the battery cell falls back within the first voltage range. As described above, as the charging and discharging cycles of the battery cell are repeated, the information acquisition interface (130) can acquire voltage data and current data for each charging cycle.

[0053] According to one embodiment, the electronic device (100) can determine a differential capacity curve based on voltage data and current data of a plurality of battery cells.

[0054] For example, the electronic device (100) can acquire voltage data and current data corresponding to each of a plurality of battery cells for each charging cycle using an information acquisition interface (130).

[0055] For example, the differential capacity curve may refer to a graph showing the relationship between the voltage and the differential capacity (dQ / dV) obtained by differentiating the charge / discharge capacity of a battery cell with respect to voltage. For example, the differential capacity curve can be identified as a graph such as reference number 220 in FIG. 2.

[0056] According to one embodiment, the electronic device (100) can identify at least one feature point for each of a plurality of battery cells using a differential capacity curve.

[0057] For example, the electronic device (100) can identify at least one feature point for each of the plurality of battery cells based on the differential capacity curve for each of the plurality of battery cells.

[0058] For example, at least one feature point may include a target peak and a target valley within a specified voltage range of the differential capacitance curve. The peak may refer, for example, to a maximum point having the maximum differential capacitance value within the specified voltage range (e.g., the first point (221) in FIG. 2). The valley may refer, for example, to a minimum point having the minimum differential capacitance value within the specified voltage range (e.g., the second point (222) in FIG. 2). The specified voltage range may be 3.8 to 4.2 V, but this is exemplary and the embodiments of the present disclosure are not limited to such numerical limitations.

[0059] For example, if multiple peaks or multiple valleys are identified within a specified voltage range, the electronic device (100) may determine one peak or one valley as a target peak using differential capacitance values ​​(or dQ / dV values) and / or current data corresponding to each of the multiple peaks or multiple valleys. For example, the electronic device (100) may not determine a peak among the multiple peaks or multiple valleys as a target peak or target valley if the current data falls outside the specified range. For example, the electronic device (100) may determine the peak with the largest differential capacitance value among the multiple peaks as the target peak. For example, the electronic device (100) may determine the valley with the smallest differential capacitance value among the multiple valleys as the target valley.

[0060] According to one embodiment, the electronic device (100) can diagnose whether there is an abnormality in a plurality of battery cells based on whether at least one feature point satisfies a predetermined condition.

[0061] For example, the electronic device (100) can determine the distance between the target peak and the target valley for the first battery cell among a plurality of battery cells, and if the distance satisfies a predetermined condition, it can determine that there is an abnormality in the first battery cell. As an example, the "distance" between the target peak and the target valley may mean the straight-line distance between the points corresponding to the target peak and the target valley, respectively, within the differential capacity curve.

[0062] For example, the electronic device (100) monitors the number of times the distance between the target peak and the target valley identified for each of the plurality of battery cells satisfies a predetermined condition during each charging cycle, and can determine that there is a problem with the battery cell if the number exceeds a specified number of times (e.g., 5 times).

[0063] For example, the electronic device (100) can determine whether the distance satisfies a predetermined condition based on a statistical analysis of the "distance" of each of the multiple battery cells identified during each charging cycle. For example, the electronic device (100) can determine an Inter-Quatile Range (IQR) value corresponding to the difference between the third quartile and the first quartile of the distance between the target peak and the target valley of each of the multiple battery cells, and can determine a first distance and a second distance smaller than the first distance based on the IQR value. For example, the first distance may correspond to a value obtained by adding a first value based on the IQR value to the median of the distances of each of the multiple battery cells, and the second distance may correspond to a value obtained by subtracting a second value based on the IQR value from the median of the distances of each of the multiple battery cells. For example, the electronic device (100) can determine that among the distances between the target peak and the target valley of each of the multiple battery cells, the distance that exceeds the first distance or is less than the second distance satisfies a predetermined condition. For example, the electronic device (100) may determine that a first type of abnormality exists in a first battery cell where the number of times the distance exceeds a first distance is greater than or equal to a specified number of times. For example, the electronic device (100) may determine that a second type of abnormality exists in a second battery cell where the number of times the distance is less than a second distance is greater than or equal to a specified number of times. That is, the electronic device (100) may determine that different types of abnormalities exist depending on whether the distance exceeds a first distance or is less than a second distance.

[0064] For example, the electronic device (100) can determine the average distance between the target peak and the target valley of each of the plurality of battery cells and determine that a distance outside a specified range based on the average distance satisfies a predetermined condition. For example, the electronic device (100) can determine that a distance not included within a first range (e.g., a range up to 110% of the average distance) and a second range (e.g., a range up to 90% of the average distance) from the average distance satisfies a predetermined condition. In this case as well, the electronic device (100) can diagnose that there is a defect in a battery cell where the number of times the predetermined condition is satisfied exceeds a specified number.

[0065] For example, the electronic device (100) can determine whether a predetermined condition is satisfied based on the difference between the maximum distance and the minimum distance among the distances between the target peak and the target valley of each of the plurality of battery cells. For example, the electronic device (100) can determine a third distance by summing the difference between the maximum distance and the minimum distance and the median of the distance between the target peak and the target valley of each of the plurality of battery cells, and a fourth distance by subtracting the difference between the median and the distance. The electronic device (100) can determine that a distance exceeding the third distance or less than the fourth distance satisfies the predetermined condition. Likewise, in this case, the electronic device (100) can diagnose that there is an abnormality in a battery cell where the number of times the predetermined condition is satisfied exceeds a specified number.

[0066] Hereinafter, with reference to FIGS. 2 and 3, the voltage data, differential capacity curve, and process and results of statistical analysis of the battery cell identified by the electronic device (100) will be described.

[0067]

[0068] FIG. 2 illustrates a graph relating to voltage data and differential capacity curves of a battery cell according to one embodiment of the present disclosure.

[0069] According to an embodiment of the present disclosure, an electronic device (100) can acquire data according to FIG. 2 regarding a battery cell using an information acquisition interface (130). The graph shown in FIG. 2 may correspond to a graph representing data regarding one of a plurality of battery cells.

[0070] Referring to the graph according to reference number 210, according to one embodiment, the electronic device (100) can obtain voltage data of a plurality of battery cells included in a battery pack in a time series.

[0071] For example, the electronic device (100) may acquire voltage data (e.g., OCV data) for each of a plurality of battery cells during each charging cycle. The voltage data may correspond, for example, to the voltage (or OCV voltage) acquired while the charging cycle of the plurality of battery cells is being performed. The graph according to reference numeral 210 may represent the result of acquiring voltage data acquired during each charging cycle in a time series. The voltage of the battery cell may gradually increase over time as charging takes place.

[0072] Referring to the graph according to reference number 220, according to one embodiment, the electronic device (100) can determine the differential capacity curve using voltage data of a plurality of battery cells included in a battery pack.

[0073] For example, the electronic device (100) can identify a differential capacitance curve containing a plurality of feature points (221, 222, 231, 232) according to reference number 220. The x-axis of the differential capacitance curve may correspond to voltage (V), and the y-axis may correspond to differential capacitance (dQ / dV).

[0074] For example, the differential capacity curve illustrated in reference number 220 may correspond to the differential capacity curve according to the charging cycle of one of the plurality of battery cells. The electronic device (100) can identify a plurality of feature points (221, 222, 231, 232) included in the differential capacity curve of the battery cell.

[0075] For example, the electronic device (100) can diagnose whether there is an abnormality in the battery cell by using only the designated feature points within the designated voltage range (SV) of the differential capacity curve among a plurality of feature points (221, 222, 231, 232). The designated voltage range (SV) may be 3.8 to 4.2V. As an example, the designated feature points may include a first peak (221) and a first valley (222). The first peak (221) corresponds to a point having the maximum differential capacity value within the designated voltage range (SV), and the first valley (222) corresponds to a point having the minimum differential capacity value within the designated voltage range (SV).

[0076] For example, the electronic device (100) may not use the second peak (231) and second valley (222) identified in a voltage range other than the designated voltage range (SV) for diagnosing abnormalities in the battery cell.

[0077] For example, the electronic device (100) may determine the first peak (221) and the first valley (222) as the target peak and the target valley, respectively. The electronic device (100) may determine whether there is an abnormality in the battery cell based on whether the distance between the first peak (221) and the first valley (222) identified on the differential capacity curve satisfies a predetermined condition. The criteria for determining whether the distance satisfies a predetermined condition may be replaced by the description of FIG. 1 described above.

[0078] For example, if multiple peaks or multiple valleys are identified within a specified voltage range (SV) as in reference number 220, the electronic device (100) may determine one target peak or one target valley using a differential capacitance value (or, dQ / dV value) or current data corresponding to each of the multiple peaks. For example, the electronic device (100) may not determine a peak among the multiple peaks or multiple valleys where the current data falls outside the specified range as a target peak or target valley. For example, the electronic device (100) may determine the peak among the multiple peaks that has the largest differential capacitance value as the target peak. For example, the electronic device (100) may determine the valley among the multiple valleys that has the smallest differential capacitance value as the target valley.

[0079]

[0080] FIG. 3 illustrates a box-and-whisker plot showing an InterQuartile Range (IQR) identified based on the distance between at least one feature point of a battery cell according to one embodiment of the present disclosure.

[0081] Referring to reference number 310, according to one embodiment, the electronic device (100) can see a box whisker plot according to the distance between the target peak and the target valley of each of the plurality of battery cells.

[0082] For example, the electronic device (100) can determine the median value (315) of the “distance” corresponding to each of the plurality of battery cells.

[0083] For example, the electronic device (100) can determine the first and third quartiles of "distance" corresponding to each of the plurality of battery cells. The electronic device (100) can determine the IQR value corresponding to the difference between the first and third quartiles. In the drawing illustrated in reference numeral 310, the vertical length of the rectangular box may correspond to the IQR value.

[0084] For example, the electronic device (100) can determine a first distance (311) by adding a first value (D1) based on the IQR value to the median value (315) of the "distance" corresponding to each of the plurality of battery cells.

[0085] For example, the electronic device (100) can determine a second distance (312) by subtracting a second value (D2) based on the IQR value from the median value (315) of the "distance" corresponding to each of the multiple battery cells.

[0086] For example, the first value (D1) and the second value (D2) may each correspond to the value obtained by multiplying IQR by the first weight and the second weight, respectively. The first weight and the second weight may be the same at 1.5, but the embodiments of the present disclosure are not limited thereto.

[0087] Referring to reference number 320, the electronic device (100) can perform an abnormality diagnosis on the battery cell through a box whisker diagram.

[0088] For example, the electronic device (100) can identify a first battery cell (321) in which the distance between the target peak and the target valley exceeds a first distance (311).

[0089] For example, the electronic device (100) can identify a second battery cell (322) in which the distance between the target peak and the target valley is less than the second distance (312).

[0090] For example, the electronic device (100) may determine that there is a first type of abnormality in the first battery cell (321) if the number of times the distance between the target peak and the target valley of the first battery cell (321) exceeds the first distance (311) exceeds a specified number of times.

[0091] For example, the electronic device (100) may determine that there is a second type of abnormality in the second battery cell (322) if the number of times the distance between the target peak and the target valley of the second battery cell (322) is less than the second distance (312) exceeds a specified number of times.

[0092] That is, the electronic device (100) can determine whether different types of abnormalities exist depending on whether the distance between the target peak and the target valley of the battery cell falls within a certain range.

[0093]

[0094] FIG. 4 is a flowchart of the operation of a battery diagnostic method performed by an electronic device according to one embodiment of the present disclosure.

[0095] According to one embodiment, the electronic device (100) can perform the operations disclosed in FIG. 4. For example, at least some of the components included in the electronic device (100) (e.g., memory (110), processor (120), and information acquisition interface (130) of FIG. 1) may be configured to perform the operations of FIG. 4.

[0096] In the following embodiments, the operations S410 to S430 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 4 may be briefly explained or omitted.

[0097] According to one embodiment, the electronic device (100) can determine a differential capacity curve based on voltage data and current data of a plurality of battery cells obtained for each charging cycle (S410).

[0098] For example, the electronic device (100) can determine a differential capacity curve corresponding to each of the plurality of battery cells based on voltage data and / or current data corresponding to each of the plurality of battery cells.

[0099] According to one embodiment, the electronic device (100) can identify at least one feature point for each of a plurality of battery cells using a differential capacity curve (S420).

[0100] For example, at least one feature point may include a target peak and a target valley within a specified voltage range of the differential capacitance curve.

[0101] For example, the specified voltage range may be 3.8 to 4.2V.

[0102] According to one embodiment, the electronic device (100) can diagnose whether there is an abnormality in a plurality of battery cells based on whether at least one feature point satisfies a predetermined condition (S430).

[0103] For example, the electronic device (100) can determine the distance between a target peak and a target valley for a first battery cell among a plurality of battery cells, and if the distance satisfies a predetermined condition, it can determine that there is a problem with the first battery cell. As an example, the electronic device (100) can monitor the number of times the distance satisfies a predetermined condition, and if the number exceeds a specified number of times (e.g., 5 times), it can determine that there is a problem with the first battery cell.

[0104] For example, the electronic device (100) can determine an Inter Quatile Range (IQR) value corresponding to the difference between the third quartile and the first quartile of the distance of each of the plurality of battery cells, determine a first distance and a second distance smaller than the first distance based on the IQR value, and determine that a distance exceeding the first distance or less than the second distance satisfies a predetermined condition. For example, the first distance may correspond to a value obtained by adding a first value based on the IQR value to the median of the distances, and the second distance may correspond to a value obtained by subtracting a second value based on the IQR value from the median of the distances. For example, the electronic device (100) may determine that a first type of abnormality exists in a first battery cell where the number of times the distance exceeds the first distance is greater than a specified number, and determine that a second type of abnormality exists in a second battery cell where the number of times the distance is less than the second distance is greater than a specified number.

[0105] For example, the electronic device (100) can determine the average distance between the target peak and the target valley of each of the plurality of battery cells, and determine that a distance other than a specified range based on the average distance satisfies a predetermined condition.

[0106] For example, the electronic device (100) can determine the difference between the maximum distance and the minimum distance among the distances, determine a third distance by adding the median of the distances and the difference between the distances, determine a fourth distance by subtracting the median of the distances and the difference between the distances, and determine that a distance exceeding the third distance or less than the fourth distance satisfies a predetermined condition.

[0107]

[0108] FIG. 5 is a flowchart of the operation of a battery diagnostic method performed by an electronic device according to one embodiment of the present disclosure.

[0109] According to one embodiment, the electronic device (100) can perform the operations disclosed in FIG. 5. For example, at least some of the components included in the electronic device (100) (e.g., memory (110), processor (120), and information acquisition interface (130) of FIG. 1) may be configured to perform the operations of FIG. 5.

[0110] In the following embodiments, the operations S510 to S570 may be performed sequentially, but are not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. Additionally, content corresponding to or overlapping with the above description in relation to FIG. 5 may be briefly explained or omitted.

[0111] According to one embodiment, the electronic device (100) can acquire voltage data and current data while charging the battery cell (S510).

[0112] For example, the electronic device (100) can check voltage data and current data for each charging cycle.

[0113] According to one embodiment, the electronic device (100) can check whether the voltage of the battery cell is within a specified voltage range (S520).

[0114] For example, the specified voltage range may be 3.8 to 4.2 V, but this is exemplary and the embodiments of the present disclosure are not limited thereto.

[0115] For example, if the voltage of the battery cell is within a specified voltage range (e.g., operation S520 - Yes), the electronic device (100) can perform operation S530.

[0116] For example, if the voltage of the battery cell is outside the specified voltage range (e.g., operation S520 - No), the electronic device (100) can repeat operation S510.

[0117] According to one embodiment, the electronic device (100) can calculate the differential capacity curve of each of the plurality of battery cells (S530).

[0118] According to one embodiment, the electronic device (100) can calculate the distance between the peaks and valleys of the differential capacitance curve (S540).

[0119] For example, the electronic device (100) can calculate the distance between a target peak and a target valley that are included within a specified voltage interval among a plurality of peaks and a plurality of valleys of a differential capacitance curve.

[0120] According to one embodiment, the electronic device (100) can determine a distance that satisfies a predetermined condition through statistical analysis of the calculated distance (S550).

[0121] For example, the electronic device (100) can determine a distance that satisfies a predetermined condition based on methods such as average distance-based statistical analysis, IQR-based statistical analysis, and maximum / minimum-based statistical analysis.

[0122] According to one embodiment, the electronic device (100) can check whether the number of times the distance of the target battery cell satisfies a predetermined condition exceeds a specified number (S560).

[0123] For example, if the number of times the distance of the target battery cell satisfies a predetermined condition exceeds a specified number (e.g., operation S560 - Yes), the electronic device (100) can perform operation S570.

[0124] For example, if the number of times the distance of the target battery cell satisfies a predetermined condition is less than or equal to a specified number (e.g., operation S560 - No), the electronic device (100) can repeat operation S510.

[0125] According to one embodiment, the electronic device (100) can determine that there is a problem with the target battery cell (S570).

[0126] For example, the electronic device (100) can identify the type of abnormality determined to exist in the target battery cell and provide abnormality information, including the type of abnormality, degree of abnormality, etc., to the user through various devices (e.g., displays).

[0127]

[0128] The electronic device (100) according to the above-described embodiments may include a processor, memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with an external device, and user interface devices such as a touch panel, a key, an icon, etc. Methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable code or program instructions executable on the processor. Here, computer-readable recording media include magnetic storage media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disk, hard disk, etc.) and optical reading media (e.g., CD-ROM, DVD (Digital Versatile Disc)). Computer-readable recording media may be distributed across networked computer systems, allowing computer-readable code to be stored and executed in a distributed manner. The medium may be readable by a computer, stored in memory, and executed by a processor.

[0129] Various embodiments of the present disclosure may be represented by functional block configurations and various processing steps. These functional blocks may be implemented by various numbers of hardware and / or software configurations that execute specific functions. For example, the embodiments may employ integrated circuit configurations such as memory, processing, logic, look-up tables, etc., which can execute various functions by the control of one or more microprocessors or other control devices. Similar to how components may be implemented as software programming or software elements, the embodiments may be implemented in programming or scripting languages ​​such as C, C++, Java, assembler, etc., including various algorithms implemented as combinations of data structures, processes, routines, or other programming configurations. Functional aspects may be implemented as algorithms executed on one or more processors. Additionally, the embodiments may employ prior art for electronic configuration, signal processing, and / or data processing. Terms such as “mechanism,” “element,” “means,” and “configuration” may be used broadly and are not limited to mechanical and physical configurations. The above terms may include the meaning of a series of software processes (routines) in conjunction with processors, etc.

[0130] The aforementioned embodiments are merely examples, and other embodiments may be implemented within the scope of the claims set forth below.

Claims

1. In an electronic device, Information acquisition interface for acquiring voltage data and current data of multiple battery cells included in a battery pack for each charging cycle; Memory for storing at least one instruction; and A processor operatively connected to the above memory; comprising, When the above at least one instruction is executed by the processor, the electronic device: Based on the voltage data and current data of the plurality of battery cells, the differential capacity curve is identified, Using the above differential capacity curve, at least one feature point for each of the plurality of battery cells is identified, and A configuration for diagnosing abnormalities in the plurality of battery cells based on whether the above at least one feature point satisfies a predetermined condition, Electronic device.

2. In Paragraph 1, The above at least one feature point is, including target peaks and target valleys within a specified voltage range of the above differential capacitance curve, Electronic device.

3. In Paragraph 2, The above-mentioned voltage range corresponds to 3.8 to 4.2V, Electronic device.

4. In Paragraph 2, When the above at least one instruction is executed by the processor, the electronic device: When multiple peaks are identified within the specified voltage range, the target peak is determined using the dQ / dV value corresponding to each of the multiple peaks or the current data. Electronic device.

5. In Paragraph 2, When the above at least one instruction is executed by the processor, the electronic device: Check the distance between the target peak and the target valley for the first battery cell among the plurality of battery cells, and A configuration configured to determine that there is an abnormality in the first battery cell when the above distance satisfies the above predetermined condition, Electronic device.

6. In Paragraph 5, When the above at least one instruction is executed by the processor, the electronic device: Monitor the number of times the above distance satisfies the above predetermined conditions, and Configured to determine that there is a defect in the first battery cell when the above number exceeds a specified number, Electronic device.

7. In Paragraph 5, When the above at least one instruction is executed by the processor, the electronic device: Check the IQR (Inter Quatile Range) value corresponding to the difference between the third quartile and the first quartile of the distance of each of the plurality of battery cells, and Based on the above IQR value, a first distance and a second distance smaller than the first distance are identified, and The distance exceeding the first distance or less than the second distance is configured to be determined to satisfy the predetermined condition, Electronic device.

8. In Paragraph 7, The first distance above corresponds to a value obtained by adding a first value based on the IQR value to the median of the distance, and The second distance is a value obtained by subtracting a second value based on the IQR value from the median value of the distances, Electronic device.

9. In Paragraph 7, When the above at least one instruction is executed by the processor, the electronic device: It is determined that a first type of abnormality exists in a first battery cell in which the number of times the above distance exceeds the above first distance is greater than or equal to the above specified number, and A second battery cell configured to determine that a second type of abnormality exists for which the number of times the distance is less than the second distance is greater than or equal to the specified number of times, Electronic device.

10. In Paragraph 5, When the above at least one instruction is executed by the processor, the electronic device: Check the average distance between the target peak and the target valley of each of the plurality of battery cells above, and The distance other than the specified range based on the above average distance is configured to be determined as satisfying the above predetermined conditions, Electronic device.

11. In Paragraph 5, When the above at least one instruction is executed by the processor, the electronic device: Check the distance difference between the maximum and minimum distances among the above distances, and Check the third distance obtained by summing the median of the above distances and the difference between the above distances, and Check the fourth distance by subtracting the median of the above distances and the distance difference, and The distance exceeding the third distance or less than the fourth distance is configured to be determined to satisfy the predetermined conditions, Electronic device.

12. A battery diagnostic method performed by an electronic device, An operation to verify a differential capacity curve based on voltage and current data of multiple battery cells obtained for each charging cycle; The operation of identifying at least one feature point for each of the plurality of battery cells using the above differential capacity curve; and An operation to diagnose whether the plurality of battery cells are abnormal based on whether the above at least one feature point satisfies a predetermined condition; comprising Battery diagnostic method.

13. In Paragraph 12, The above at least one feature point includes a target peak and a target valley within a specified voltage interval of the differential capacitance curve, and The above battery diagnostic method is, When a plurality of peaks are identified within the specified voltage range, the operation of determining a target peak using a dQ / dV value corresponding to each of the plurality of peaks or the current data; further comprising Battery diagnostic method.

14. In Paragraph 13, The above battery diagnostic method is, An operation to determine the distance between the target peak and the target valley for the first battery cell among the plurality of battery cells; An operation to monitor the number of times the above distance satisfies the above predetermined condition; and Further comprising: an operation of determining that there is an abnormality in the first battery cell when the above number exceeds a specified number; Battery diagnostic method.

15. In Paragraph 14, The above battery diagnostic method is, An operation to check the IQR (Inter Quatile Range) value corresponding to the difference between the third quartile and the first quartile of the distance of each of the plurality of battery cells; An operation to determine a first distance and a second distance smaller than the first distance based on the above IQR; and The operation of determining that the distance exceeding the first distance or less than the second distance satisfies the predetermined condition; further comprising Battery diagnostic method.

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