Battery diagnosis apparatus, battery diagnosis method, and battery diagnosis system

Abstract

According to some embodiments disclosed in this document, there is provided a battery management device configured to: receive a plurality of standing voltages for a plurality of battery cells, respectively, during a standing period after charging or discharging of the plurality of battery cells has been completed; calculating a plurality of voltage deviations for the plurality of battery cells, respectively, based on differences between each of a plurality of rest voltages for the plurality of battery cells, respectively, and representative values of the plurality of rest voltages; calculating a rate of change of the plurality of voltage deviations for the plurality of battery cells, respectively; and diagnosing a state of at least one battery cell of the plurality of battery cells based on a rate of change over time of the at least one battery cell.

Description

Technical Field

[0001] Cross-references to related applications

[0002] This application claims priority to Korean Patent Application No. 10-2023-0139022, filed with the Korean Intellectual Property Office on October 17, 2023, and Korean Patent Application No. 10-2024-0141241, filed with the Korean Intellectual Property Office on October 16, 2024, the disclosures of which are incorporated herein by reference. Technical Field

[0004] This invention relates to battery diagnostic equipment, battery diagnostic methods, and battery diagnostic systems. Background Technology

[0005] Recently, research and development on rechargeable batteries have been actively underway. Here, a rechargeable battery is a battery that can be charged and discharged, and can be interpreted as including both Ni / Cd and Ni / MH batteries, as well as the newly developed lithium-ion batteries. Among rechargeable batteries, lithium-ion batteries can have a higher energy density than Ni / Cd and Ni / MH batteries, and can be manufactured in a smaller and lighter form, thus making them highly usable as power sources for mobile devices. Recently, the application of lithium-ion batteries has expanded to include power sources for electric vehicles, and they are gaining attention as a next-generation energy storage medium.

[0006] If a low-voltage defect occurs in a particular battery cell, unlike other battery cells, the voltage of the low-voltage cell may fluctuate significantly during rest after charging or discharging. For example, self-discharge may occur in the low-voltage cell after charging is complete, which may cause the resting voltage to drop to a greater extent than in other battery cells. Such low-voltage phenomena in battery cells can lead to fires and may therefore require less time for diagnosis. Summary of the Invention

[0007] Technical issues

[0008] One aspect of the present invention provides a battery diagnostic device, a battery diagnostic method, and a battery diagnostic system, which can reduce the time required to diagnose low voltage phenomena in battery cells.

[0009] The technical objectives of the embodiments disclosed in this document are not limited to the technical problems to be solved mentioned above, and other technical problems to be solved that are not mentioned will be clearly understood by those skilled in the art based on the following description.

[0010] Technical solutions

[0011] According to one aspect of the present invention, a battery management device is provided, the battery management device comprising: a controller including one or more processors; and one or more computer-readable media storing calculation instructions, the calculation instructions, when executed on the one or more processors, causing the one or more processors to perform: receiving a plurality of resting voltages of each of the plurality of battery cells during a resting period after charging or discharging of a plurality of battery cells is completed; calculating a plurality of voltage deviations of each of the plurality of battery cells based on the difference between each of the plurality of resting voltages of each of the plurality of battery cells and a representative value of the plurality of resting voltages; calculating the rate of change of the plurality of voltage deviations of each of the plurality of battery cells; and diagnosing the state of at least one battery cell based on the rate of change of at least one of the plurality of battery cells over time.

[0012] According to another aspect, when the calculation instructions are executed on one or more processors, one or more processors perform the following: calculate the average and standard deviation of the rate of change of a plurality of battery cells, and diagnose the presence of low-voltage cells among the plurality of battery cells based on the average and standard deviation.

[0013] According to another aspect, when the calculation instructions are executed on one or more processors, one or more processors perform the following: calculating a standard score for at least one of the plurality of battery cells based on the average value and standard deviation, and diagnosing at least one battery cell as a low-voltage cell when the standard score of at least one battery cell is below a lower limit threshold.

[0014] According to another aspect, when the calculation instructions are executed on one or more processors, the one or more processors perform: calculating a plurality of second deviations based on the difference between a representative value of a plurality of voltage deviations and each of the plurality of voltage deviations, and diagnosing the presence of low-voltage cells among the plurality of battery cells based on the rate of change of the plurality of second deviations and the plurality of voltage deviations of each of the plurality of battery cells.

[0015] According to another aspect, when the calculation instructions are executed on one or more processors, one or more processors perform: setting a normal range for multiple battery cells based on multiple second deviations and multiple rates of change over time, and diagnosing battery cells with second deviations or rates of change outside the normal range as low-voltage cells.

[0016] According to another aspect, when the calculation instructions are executed on one or more processors, one or more processors perform: calculating multiple voltage deviations of each of the multiple battery cells based on the median of multiple resting voltages of each of the multiple battery cells, and estimating the slope of each of multiple rates of change of each of the multiple battery cells by means of linear regression analysis.

[0017] According to another aspect, when the computation instructions are executed on one or more processors, the one or more processors perform the following: receiving a plurality of resting voltages, wherein the plurality of resting voltages are collected during a first time period after a buffer time following the end time of charging of the plurality of battery cells, and / or wherein the plurality of resting voltages are collected during a second time period following the end time of discharging of the plurality of battery cells.

[0018] According to another aspect, when the calculation instructions are executed on one or more processors, one or more processors perform: calculating the rate of change of multiple voltage deviations for each of the multiple battery cells by means of regression analysis.

[0019] According to another aspect, when the computational instructions are executed on one or more processors, one or more processors perform: diagnosing the state of each of the multiple battery cells based on the rate of change of the multiple battery cells over time.

[0020] According to another aspect, the battery management device also includes a sensor configured to collect multiple resting voltages of each of the multiple battery cells during a resting period after charging or discharging of the multiple battery cells has been completed.

[0021] According to another aspect, the battery management device also includes an interface configured to communicate with a sensor to receive multiple resting voltages of each of a plurality of battery cells, wherein the sensor is configured to collect multiple resting voltages of each of the plurality of battery cells during a resting period after charging or discharging of the plurality of battery cells has been completed.

[0022] According to another aspect, when the computational instructions are executed on one or more processors, the processors perform the following: diagnose at least one of the plurality of battery cells as a low-voltage cell and an abnormal cell, and in response to the diagnosis, perform any of the following: i) send a warning alarm to at least one of the user device and the display terminal regarding the at least one diagnosed cell; ii) disconnect or cut off power to the at least one diagnosed cell; iii) electrically ground the at least one diagnosed cell; iv) limit or modify at least one of the performance, output, and operating mode of the electrical device using the at least one diagnosed cell; and v) send information about the at least one diagnosed cell to an external server.

[0023] According to another aspect, a battery management device includes: a controller including one or more processors; and one or more computer-readable media storing calculation instructions, which, when executed on the one or more processors, cause the one or more processors to perform: receiving a plurality of resting voltages of each of the plurality of battery cells during a resting period after charging or discharging of a plurality of battery cells; calculating a plurality of voltage deviations of each of the plurality of battery cells based on the difference between each of the plurality of resting voltages of each of the plurality of battery cells and a representative value of the plurality of resting voltages; calculating a plurality of second deviations based on the difference between the representative value of the plurality of voltage deviations and each of the plurality of voltage deviations; and diagnosing the presence of low-voltage cells among the plurality of battery cells based on the plurality of second deviations.

[0024] According to another aspect, a battery management device includes: a sensor configured to collect multiple resting voltages from multiple battery cells during a resting period after charging or discharging is completed; and a controller configured to calculate multiple voltage deviations based on the difference between representative values ​​of the multiple resting voltages and each resting voltage, calculate multiple rates of change of the multiple voltage deviations over time by regression analysis, and diagnose the state of the multiple battery cells based on the multiple rates of change over time.

[0025] According to one aspect, the controller can be configured to: calculate the average and standard deviation of multiple rates of change over time; and diagnose the presence of low-voltage cells among multiple battery cells based on the average and standard deviation.

[0026] According to one aspect, the controller can be configured to: calculate a standard score for each of a plurality of rates of change over time based on the average value and standard deviation; and diagnose a battery cell among the plurality of battery cells that has a standard score below a lower threshold as a low-voltage cell.

[0027] According to one aspect, the controller can be configured to: calculate multiple second deviations based on the difference between representative values ​​of multiple voltage deviations and each voltage deviation; and diagnose the presence of low-voltage cells among multiple battery cells based on multiple rates of change over time and multiple second deviations.

[0028] According to one aspect, the controller can be configured to: set a normal range for multiple battery cells based on multiple second deviations and multiple rates of change over time; and diagnose battery cells with second deviations or rates of change over time that are outside the normal range as low-voltage cells.

[0029] According to one aspect, the controller can be configured to: calculate multiple voltage deviations based on the median of multiple resting voltages; and estimate the slope of each of multiple rates of change over time through linear regression analysis.

[0030] According to one aspect, the sensor can be configured to: collect multiple resting voltages during a first time period after a buffer time following the end of charging of the multiple battery cells; and collect multiple resting voltages during a second time period following the end of discharging of the multiple battery cells.

[0031] According to another aspect, a battery management method is provided, implemented via the execution of computational instructions configured to run on one or more processors, the method comprising: receiving, during a rest period following the completion of charging or discharging of a plurality of battery cells, a plurality of rest voltages collected for each of the plurality of battery cells; calculating a plurality of voltage deviations for each of the plurality of battery cells based on the difference between each of the plurality of rest voltages for each of the plurality of battery cells and a representative value of the plurality of rest voltages; calculating the rate of change of the plurality of voltage deviations for each of the plurality of battery cells; and diagnosing the state of at least one battery cell based on the rate of change of at least one of the plurality of battery cells.

[0032] According to one aspect, diagnosing the state of at least one of a plurality of battery cells includes: calculating the average and standard deviation of the rate of change of the plurality of battery cells; and diagnosing, based on the average and standard deviation, whether a low-voltage cell exists among the plurality of battery cells.

[0033] According to one aspect, diagnosing the state of at least one of a plurality of battery cells includes: calculating a standard score for at least one of the plurality of battery cells based on a mean and a standard deviation; and diagnosing at least one battery cell as a low-voltage cell when the standard score of at least one battery cell is below a lower limit threshold.

[0034] According to one aspect, diagnosing the state of at least one of a plurality of battery cells includes: calculating a plurality of second deviations based on the difference between a representative value of a plurality of voltage deviations and each of the plurality of voltage deviations, and diagnosing the presence of a low-voltage cell among the plurality of battery cells based on the rate of change of the plurality of second deviations and the plurality of voltage deviations of each of the plurality of battery cells.

[0035] According to one aspect, diagnosing the state of at least one of a plurality of battery cells includes: setting a normal range for the plurality of battery cells based on a plurality of second deviations and a plurality of rates of change over time; and diagnosing a battery cell having a second deviation or rate of change outside the normal range as a low-voltage cell.

[0036] According to one aspect, calculating multiple voltage deviations for each of the multiple battery cells includes: calculating multiple voltage deviations for each of the multiple battery cells based on the median of multiple resting voltages, and calculating the rate of change of the multiple voltage deviations includes: estimating the slope of each of the multiple rates of change for each of the multiple battery cells by means of linear regression analysis.

[0037] According to one aspect, receiving multiple static voltages includes: receiving multiple static voltages collected during a first time period after a buffer time following the end time of charging of multiple battery cells, and receiving multiple static voltages collected during a second time period following the end time of discharging of multiple battery cells.

[0038] According to one aspect, a battery management method is provided, implemented via the execution of computational instructions configured to run on one or more processors, the method comprising: collecting a plurality of resting voltages of each of the plurality of battery cells during a resting period following the completion of charging or discharging of the plurality of battery cells; calculating a plurality of voltage deviations of each of the plurality of battery cells based on the difference between each of the plurality of resting voltages of each of the plurality of battery cells and a representative value of the plurality of resting voltages; calculating a plurality of second deviations based on the difference between the representative value of the plurality of voltage deviations and each of the plurality of voltage deviations; and diagnosing, based on the plurality of second deviations, whether a target battery cell among the plurality of battery cells is a low-voltage cell.

[0039] According to another aspect of the present invention, a battery diagnostic method is provided, the battery diagnostic method comprising: collecting multiple resting voltages from multiple battery cells during a resting period after charging or discharging is completed; calculating multiple voltage deviations based on the difference between representative values ​​of the multiple resting voltages and each resting voltage; calculating multiple rates of change of the multiple voltage deviations over time by regression analysis; and diagnosing the state of the multiple battery cells based on the multiple rates of change over time.

[0040] In one aspect, diagnosing the state of multiple battery cells includes: calculating the average and standard deviation of multiple rates of change over time; and diagnosing, based on the average and standard deviation, whether there are low-voltage cells among the multiple battery cells.

[0041] In one aspect, diagnosing the state of multiple battery cells includes: calculating a standard score for each of multiple rates of change over time based on the mean and standard deviation; and diagnosing battery cells among the multiple battery cells that have a standard score below a lower threshold as low-voltage cells.

[0042] In one aspect, diagnosing the state of multiple battery cells includes: calculating multiple second deviations based on representative values ​​of multiple voltage deviations and the difference between each voltage deviation; and diagnosing the presence of low-voltage cells among the multiple battery cells based on multiple rates of change over time and the multiple second deviations.

[0043] In one aspect, diagnosing the state of multiple battery cells includes: setting a normal range for multiple battery cells based on multiple second deviations and multiple rates of change over time; and diagnosing battery cells with second deviations or rates of change over time that are outside the normal range as low-voltage cells.

[0044] In one aspect, calculating multiple voltage deviations includes calculating multiple voltage deviations based on the median of multiple resting voltages, and calculating multiple rates of change over time includes estimating the slope of each of the multiple rates of change over time by means of linear regression analysis.

[0045] In one aspect, collecting multiple resting voltages includes: collecting multiple resting voltages during a first time period after a buffer time following the end of charging of multiple battery cells; and collecting multiple resting voltages during a second time period following the end of discharging of multiple battery cells.

[0046] According to another aspect, a battery management system is provided, which includes a battery management device according to embodiments herein, the battery management system including a charger / discharger configured to charge or discharge a plurality of battery cells.

[0047] According to another aspect of the present invention, a battery diagnostic system is provided, comprising: a charger / discharger configured to charge or discharge a plurality of battery cells; and a battery diagnostic device configured to: collect a plurality of resting voltages from the plurality of battery cells during a resting period after charging or discharging is completed; calculate a plurality of voltage deviations based on the difference between representative values ​​of the plurality of resting voltages and each resting voltage; calculate a plurality of rates of change of the plurality of voltage deviations over time by regression analysis; and diagnose the state of the plurality of battery cells based on the plurality of rates of change over time.

[0048] Beneficial effects

[0049] According to various aspects of the present invention, a battery diagnostic device, a battery diagnostic method, and a battery diagnostic system can be provided, which can reduce the time required to diagnose low voltage phenomena in battery cells.

[0050] The technical effects of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art based on the disclosure of this document. Attached Figure Description

[0051] Figure 1 The components constituting a battery diagnostic system according to some embodiments are shown;

[0052] Figure 2 The components constituting a battery diagnostic device according to some embodiments are shown;

[0053] Figure 3 This illustrates how the voltage of multiple battery cells changes during a resting period after charging or discharging is complete, according to some embodiments.

[0054] Figure 4 Multiple resting voltages measured from multiple battery cells according to some embodiments are shown;

[0055] Figure 5 Multiple voltage deviations of multiple resting voltages according to some embodiments are shown;

[0056] Figure 6 The process of diagnosing the state of a battery cell based on multiple rates of change over time, according to some implementations, is illustrated.

[0057] Figure 7 The process of calculating multiple second deviations based on the difference between a representative value of multiple voltage deviations and each voltage deviation, according to some implementations, is illustrated.

[0058] Figure 8The process of setting the normal range of multiple battery cells based on multiple second deviations and multiple rates of change over time, according to some embodiments, is illustrated; and

[0059] Figure 9 The steps of constructing a battery diagnostic method according to some embodiments are shown. Detailed Implementation

[0060] In the following description, embodiments described in this document are illustrated with reference to the accompanying drawings. However, this is not intended to limit the disclosure of this document to the specific embodiments, but should be understood to include various modifications, equivalents, and / or alternatives to the embodiments described in this document.

[0061] The embodiments and terminology used in this document are not intended to limit the technical features described herein to specific embodiments, but should be understood to include various modifications, equivalents, or alternatives to the embodiments. Similar reference numerals may be used for similar or related parts in conjunction with the description of the accompanying drawings. The singular form of a noun corresponding to an item may include one or more items unless the relevant context clearly indicates otherwise.

[0062] In this document, each of the phrases such as “A or B”, “at least one of A and B”, “at least one of A or B”, “A, B or C”, “at least one of A, B and C”, and “at least one of A, B or C” can include any of the items listed together in that phrase, or any possible combination thereof. Terms such as “first”, “second”, “firstly”, “secondarily”, “A”, “B”, “(a)”, or “(b)” may be used simply to distinguish such a component from other such components, and unless explicitly stated otherwise, do not limit such elements in any other respect (e.g., in terms of importance or order).

[0063] In this document, when a particular (e.g., first) component is referred to as “connected,” “coupled,” or “joined” to another (e.g., second) component (whether or not the terms “functionally” or “communically” are used) or is referred to as “coupled” or “connected,” it means that the particular component can be connected to the other component directly (e.g., wired or wirelessly) or indirectly (e.g., via a third component).

[0064] Methods according to the various embodiments disclosed in this document can be provided by being included in a computer program product. The computer program product is a commodity and can be traded between a seller and a buyer. The computer program product can be distributed in the form of a computer-readable storage medium (e.g., an optical disc read-only memory (CD-ROM)), or distributed online directly between two user devices via an app store (e.g., it can be downloaded or uploaded). In the case of online distribution, at least a portion of the computer program product can be at least temporarily stored or temporarily created in the memory of a computer-readable storage medium, such as a manufacturer's server, an app store's server, or a relay server. According to various aspects herein, one or more computer-readable media can store computational instructions that, when executed on one or more processors, cause the processor to perform aspects of the battery cell management and / or diagnostic embodiments described herein.

[0065] According to the embodiments disclosed in this document, each of the above-described components (e.g., a module, computational instructions, or a program) may include one or more entities, and some of the multiple entities may be separately located in other components. According to the embodiments disclosed in this document, one or more of the corresponding components or their operations may be omitted, or one or more other components or their operations may be added. Alternatively or additionally, multiple components (e.g., modules, computational instructions, or programs) may be integrated into a single component. In this case, the component integrating multiple components may perform one or more functions of each of the multiple components in the same or similar manner as the corresponding components of the multiple components performed one or more functions before integration. According to the embodiments disclosed in this document, the operations performed by modules, computational instructions, programs, or other components may be performed sequentially, in parallel, iteratively, or heuristically, or one or more operations may be performed in a different order or omitted, or one or more other operations may be added.

[0066] Figure 1 The components constituting a battery diagnostic system according to some embodiments are shown.

[0067] Reference Figure 1 The battery diagnostic system 100 may include a charger / discharger 110, multiple battery cells 120, a battery diagnostic device 130, and a management server 140. However, it is not limited to this, and some components may be omitted from the battery diagnostic system 100, or other common components may be included in the battery diagnostic system 100.

[0068] The battery diagnostic system 100 can refer to a system for diagnosing multiple battery cells 120. The multiple battery cells 120 can be charged or discharged by a charger / discharger 110, and the battery diagnostic device 130 can diagnose the multiple battery cells 120 by analyzing data on the charging and discharging of the multiple battery cells 120.

[0069] Charger / discharger 110 can charge or discharge multiple battery cells 120. According to one embodiment, charger / discharger 110 may include a power supply device configured to apply a test voltage or test current to the multiple battery cells 120. The test voltage / current may include multiple charge / discharge cycle voltages / currents. According to another embodiment, charger / discharger 110 may include a mobile device such as a hybrid electric vehicle (HEV), a hybrid electric vehicle (HEV), or an electric bicycle equipped with multiple battery cells 120.

[0070] Multiple battery cells 120 can constitute a battery to be diagnosed. According to one embodiment, the battery to be diagnosed may include multiple battery modules, and the multiple battery modules may include multiple battery cells 120. According to another embodiment, the multiple battery cells 120 may constitute a cylindrical battery pack, and the cylindrical battery pack may be used in a battery swapping system (BSS).

[0071] The battery diagnostic device 130 can perform operations for diagnosing a plurality of battery cells 120. The battery diagnostic device 130 can measure battery data from the plurality of battery cells 120 and diagnose the plurality of battery cells 120 based on the battery data. According to one embodiment, the battery diagnostic device 130 can diagnose whether a low voltage anomaly has occurred in at least one of the plurality of battery cells 120. According to another embodiment, the battery diagnostic device 130 can be a battery management system (BMS) device configured to be integrated with the plurality of battery cells 120.

[0072] The management server 140 can manage the diagnostic process and results of the battery diagnostic device 130. The management server 140 can exchange data with the battery diagnostic device 130 via wired / wireless communication methods. When battery data is measured from multiple battery cells 120 or defects are diagnosed, the results can be sent to the management server 140 and recorded in a database. According to an embodiment, the management server 140 can receive data for battery diagnostics and can perform operations for diagnosing the battery 120 to be diagnosed, replacing the battery diagnostic device 130. On the other hand, the battery diagnostic device 130 can perform diagnostic operations by executing battery management software including calculation instructions, and the management server 140 can provide the battery diagnostic device 130 with installation and update information for the battery management software.

[0073] Figure 2The components constituting a battery diagnostic device according to some embodiments are shown.

[0074] Reference Figure 2 The battery diagnostic device 130 may include a sensor 131 and a controller 132. However, it is not limited to this, and some components may be omitted from the battery diagnostic device 130, or other common components may be included in the battery diagnostic device 130. According to one embodiment, the battery diagnostic device 130 includes one or more sensors, such as one or more sensors on-board of the device 130. According to another embodiment, the battery diagnostic device is capable of communicating with one or more off-board or remote sensors, such as via an interface including communication circuitry, modules, and / or chips capable of receiving information from one or more remote sensors. For example, in cases where the battery diagnostic device is located in a remote server or is part of a battery charger or vehicle controller separate from one or more sensors, the battery diagnostic device may be able to communicate with one or more remote sensors.

[0075] According to an embodiment, in the battery diagnostic device 130, the sensor 131 and the controller 132 can be electrically connected to each other via an inter-device communication method. The inter-device communication method may include a bus, general purpose input / output (GPIO), serial peripheral interface (SPI), mobile industrial processor interface (MIPI), etc.

[0076] Sensor 131 can be configured to generate various battery measurements from the battery 120 to be diagnosed. For this purpose, sensor 131 may include measuring devices such as a voltmeter, ammeter, or thermometer. According to some embodiments, sensor 131 may be a single device, or sensor 131 may include multiple separate devices capable of generating various battery measurements and providing communication with controller 132.

[0077] The controller 132 may have a structure for executing instructions that implement the operation of the battery diagnostic device 130. The controller 132 may be implemented as an array of multiple logic gates or a general-purpose microprocessor for handling various arithmetic operations, and may consist of a single processor or multiple processors. For example, the controller 132 may be implemented as at least one of a microprocessor, CPU, GPU, and AP.

[0078] The controller 132 can operate in conjunction with a computer-readable storage medium, such as a memory configured to store various data, computational instructions, mobile applications, computer programs, etc. The memory can be configured separately or integrated with the controller 132. The controller 132 can process various arithmetic operations by executing computational instructions stored in a computer-readable storage medium, such as the memory. For example, the memory can be implemented as a non-volatile device, such as ROM, PROM, EPROM, EEPROM, flash memory, PRAM, MRAM, RRAM, FRAM, etc., or as a volatile device, such as DRAM, SRAM, SDRAM, PRAM, HDD, etc., and can be implemented in the form of SSD, SD, Micro-SD, etc., or combinations thereof. According to one embodiment, the controller 132 includes an interface capable of communicating with one or more sensors, such as communication circuitry, modules, and / or chips capable of receiving information from one or more sensors, such as one or more remote sensors. According to one embodiment, controller 132 may include one or more processors and one or more computer-readable media storing computational instructions that, when executed on one or more processors, cause one or more processors to perform aspects of the present disclosure described herein, such as battery management and diagnostics.

[0079] Sensor 131 can be configured to collect multiple resting voltages from multiple battery cells 120 during a resting period after charging or discharging is complete. During this resting period, the multiple battery cells 120 may exhibit specific voltage patterns, and a corresponding resting voltage can be collected from each battery cell. For example, during a resting state after charging is complete, a pattern of steadily decreasing battery cell voltage may occur, and during a resting state after discharging is complete, a pattern of steadily increasing battery cell voltage may occur. According to embodiments, the resting voltage collected from each battery cell can be a voltage curve consisting of measurements over time. For example, sensor 131 can collect multiple resting voltages from each of the multiple cells to provide a voltage curve for each of the multiple cells consisting of measurements over time. According to some embodiments, sensor 131 can be a single device capable of collecting multiple resting voltages from each of the multiple cells. According to some other embodiments, sensor 131 can include multiple separate devices capable of collecting multiple resting voltages from each of the multiple cells.

[0080] Controller 132 can be configured to calculate multiple voltage deviations based on the difference between representative values ​​of multiple resting voltages and each resting voltage. For example, when collecting n resting voltage curves for n battery cells, a representative value curve consisting of representative values ​​(e.g., the average or median of the n resting voltage curves) at each measurement time point can be calculated, and n voltage deviation curves can be generated based on the differences between the n resting voltage curves and the representative value curve. According to one embodiment, controller 132 is configured to calculate multiple voltage deviations for each of the multiple battery cells based on the difference between each of the multiple resting voltages of each of the multiple battery cells and representative values ​​of the multiple resting voltages (e.g., the average or median of the resting voltages of the multiple battery cells at each time point).

[0081] According to one embodiment, controller 132 can be configured to calculate multiple rates of change of voltage deviations for each of a plurality of units. For example, controller 132 can be configured to calculate multiple rates of change of voltage deviations over time using regression analysis. When n voltage deviation curves are generated, the rate of change of each voltage deviation curve over time can be calculated. The rate of change over time can refer to the slope in a time-voltage graph. The rate of change of each voltage deviation curve over time can be estimated using regression analysis or other suitable fitting techniques.

[0082] The controller 132 can be configured to diagnose the state of at least one battery cell 120, or even the state of all battery cells, among a plurality of battery cells 120, based on the rate of change of voltage deviation determined for at least one battery cell, or even based on multiple rates of change of multiple voltage deviations for each of the plurality of battery cells. For example, in the case of a normal battery cell, the rate of change of the voltage deviation curve over time may remain constant, while in the case of a low-voltage battery cell, the rate of change of the voltage deviation curve over time may continuously decrease or increase. Based on this mode, battery cells corresponding to the increasing or decreasing rate of change over time among the plurality of rates of change over time can be diagnosed as defective battery cells.

[0083] According to an implementation, the controller 132 can be configured to calculate the average and standard deviation of multiple (time-varying) rates of change for multiple battery cells, and to diagnose the presence of low-voltage cells among the multiple battery cells 120 based on the average and standard deviation. To determine whether the rate of change of the voltage deviation curve over time is continuously decreasing or increasing, statistical techniques based on the average and standard deviation of multiple rates of change over time can be used.

[0084] According to one embodiment, controller 132 can be configured to calculate a standard score for each of a plurality of rates of change over time based on an average and a standard deviation, and to diagnose battery cells among the plurality of battery cells 120 that have a standard score below a lower threshold as low-voltage cells. According to one embodiment, controller can be configured to calculate a standard score for at least one battery cell and even all battery cells among the plurality of battery cells based on an average and a standard deviation. As in Equation 1 below, a standard score can mean a value obtained by dividing the value obtained by subtracting the average from each rate of change over time value by the standard deviation. The standard score can be... i It is compared with a lower threshold, and according to the implementation, the lower threshold can be -3, which may mean -3σ corresponding to the bottom 0.3%.

[0085] [Formula 1]

[0086]

[0087] According to an implementation, controller 132 can be configured to calculate a plurality of second deviations based on the difference between a representative value of a plurality of voltage deviations and each of the plurality of voltage deviations, and to diagnose the presence of low-voltage cells among the plurality of battery cells 120 based on a plurality of second deviations and / or a plurality of (over time) rates of change of the plurality of voltage deviations of each of the plurality of cells. The plurality of second deviations can refer to deviation values ​​of the plurality of voltage deviations (e.g., deviations at each point in time). For example, the plurality of second deviations can be calculated based on representative values ​​of the plurality of voltage deviations, such as an average or median (e.g., the average or median of the voltage deviations of the plurality of battery cells at each point in time). Each second deviation can indicate how far the voltage deviation of the corresponding battery cell is from the voltage deviations of other battery cells. When the plurality of second deviations are considered together with a plurality of rates of change over time, abnormal battery cells can be identified.

[0088] According to an embodiment, the controller 132 can be configured to set a normal range for a plurality of battery cells 120 based on a plurality of second deviations and a plurality of rates of change over time, and to diagnose battery cells having second deviations or rates of change over time outside the normal range as low-voltage cells. According to an embodiment, lower limits for the second deviations and rates of change over time can be set, and the normal range for the plurality of battery cells 120 can be set based on these lower limits, and battery cells outside the normal range can be diagnosed as defective cells. The lower limits for the second deviations and rates of change over time can be set to appropriate statistical values. For example, at least one value from -1σ to -3σ can be used as the lower limit.

[0089] According to an implementation, controller 132 can be configured to calculate multiple voltage deviations (e.g., at each time point) based on the median of multiple resting voltages, and to estimate the slope of each of the multiple rates of change over time using linear regression analysis. The representative value used to calculate the multiple voltage deviations may be the median of the multiple resting voltages (e.g., the median of the multiple resting voltages at each time point), and the regression analysis technique used to estimate the slope of each rate of change over time may be linear regression analysis.

[0090] According to one embodiment, controller 132 can be configured to calculate a plurality of second deviations based on the difference between a representative value of a plurality of voltage deviations and each of the plurality of voltage deviations, and to diagnose whether the at least one battery cell is a low-voltage cell based on the second deviation of at least one of the plurality of battery cells. According to another embodiment, controller 132 may be able to diagnose each of the plurality of battery cells based on the plurality of second deviations of each of the plurality of battery cells.

[0091] According to an embodiment, sensor 131 can be configured to collect multiple resting voltages during a first time period following a buffer time after the end of charging of the multiple battery cells 120, and / or during a second time period following the end of discharging of the multiple battery cells 120. The period during which the multiple resting voltages are collected can vary depending on whether the resting occurs after charging or discharging. In the case of resting after discharging, the multiple resting voltages can be collected immediately after the end of discharging, while in the case of resting after charging, the multiple resting voltages can be collected after a specific buffer time. This may be because the voltage behavior in the resting state may differ in the cases of charging and discharging.

[0092] Figure 3 This illustrates how the voltage of multiple battery cells changes during a resting period after charging or discharging is complete, according to some embodiments.

[0093] Reference Figure 3 Figures 310 and 320 show how the voltage of multiple battery cells fluctuates during a resting period after charging or discharging is complete.

[0094] Figure 310 can represent the resting period after charging is complete. The State of Charge (SOC) 311 can continuously rise due to charging, and when entering the charging completion SOC period 312, charging voltage may no longer be provided at the charging completion time point 313. Immediately following the charging completion time point 313, after a buffer time 314, the SOC 311 can gradually decrease, and multiple resting voltages can be collected during the first time period 315. According to an embodiment, the buffer time 314 can be 5 minutes, the first time period 315 can be 10 minutes, and the specific values ​​can be varied as needed.

[0095] Figure 320 can represent the resting period after discharge completion. The State of Charge (SOC) 321 can continuously decrease due to discharge, and the discharge can end at the discharge completion time point 323 when entering the discharge completion SOC section 322. The amount of discharge up to the discharge completion time point 323 can be represented as the depth of discharge (DOD) (324). Multiple resting voltages can be collected during a second time period 325 immediately following the discharge completion time point 323. According to an embodiment, the second time period 325 can be 10 minutes, and the specific value can be varied as needed.

[0096] Figure 4 Multiple resting voltages measured from multiple battery cells according to some embodiments are shown.

[0097] Reference Figure 4 Figure 400 illustrates multiple resting voltages 410 measured from multiple battery cells 120. Figure 400 shows n resting voltage curves for n battery cells. Figure 400 can represent the resting state after charging is complete.

[0098] As mentioned above Figure 3 In the first time segment 315 of Figure 310, the plurality of resting voltages 410 of Figure 400 can continue to decrease after charging is terminated. In this case, the presence of a low-voltage cell among the plurality of battery cells 120 can be determined based on the rate of change (slope) of each of the plurality of resting voltages 410 over time.

[0099] Figure 5 Multiple voltage deviations of multiple resting voltages according to some embodiments are shown.

[0100] Reference Figure 5 Figure 500 illustrates multiple voltage deviations of multiple resting voltages. Figure 500 can show... Figure 4 Figure 400 shows multiple voltage deviations of multiple resting voltages 410.

[0101] The multiple voltage deviations in Figure 500 can be calculated based on representative values ​​of multiple resting voltages 410 (e.g., the average or median of the resting voltage of each of the multiple cells at each time point). According to an embodiment, the difference between each of the multiple resting voltages 410 and the median of the multiple resting voltages 410 can be calculated as a voltage deviation. In the case of a normal battery cell, the voltage deviation over time can remain constant, as shown by the first voltage deviation curve 510. On the other hand, in the case of a low-voltage battery cell, the voltage deviation over time can continuously decrease or increase, as shown by the second voltage deviation curve 520. A reference value for the slope used to diagnose a low-voltage defect can be calculated based on a standard score using the average and standard deviation.

[0102] Figure 6 The process of diagnosing the state of a battery cell based on multiple rates of change over time, according to some implementations, is illustrated.

[0103] Reference Figure 6 An algorithm 600 is shown to represent the process of diagnosing the state of a battery cell based on multiple rates of change over time.

[0104] In step 610, the resting voltage can be collected during the resting state after charging or discharging is complete. In step 620, the voltage deviation of the resting voltage can be calculated based on the median. In step 630, linear regression can be used to calculate the slope value of the voltage deviation. In step 640, the standard score of the slope value can be calculated using the mean and standard deviation.

[0105] In step 650, a standard score for each slope (rate of change over time) can be compared to a threshold. The threshold for low-voltage diagnosis can be -3, which may correspond to -3σ, meaning the bottom 0.3%. The threshold can also be changed to different values ​​depending on the diagnostic requirement. If the standard score is not less than -3 (No), the corresponding battery cell can be diagnosed as a normal cell in step 660. If the standard score is less than -3 (Yes), the corresponding battery cell can be diagnosed as a low-voltage cell in step 670.

[0106] Figure 7 The process of calculating multiple second deviations based on the difference between representative values ​​of multiple voltage deviations (e.g., the average or median of the voltage deviations of each cell at each time point) and each voltage deviation is illustrated in some embodiments.

[0107] Reference Figure 7 Figure 700 illustrates the process of calculating multiple second deviations based on representative values ​​of multiple voltage deviations and the differences between each voltage deviation.

[0108] Figure 700 can be compared with Figure 5 The same as Figure 500. Figure 700 shows multiple voltage deviations 710 of the plurality of battery cells 120. The first voltage deviation 720 corresponding to the first battery cell among the plurality of battery cells 120 can continue to decrease due to self-discharge after charging is complete.

[0109] Representative values ​​730 for multiple voltage deviations 710 can be calculated. The representative value 730 can be the average, median, etc., of the multiple voltage deviations 710 (e.g., at each time point). Additionally, a representative value 740 for a first voltage deviation 720 can be calculated. The representative value 740 can be the average, median, etc., of the measured values ​​of the first voltage deviation 720 (e.g., at each time point).

[0110] The second deviation 750 between representative values ​​730 and 740 can be a second deviation calculated relative to the first voltage deviation 720. The second deviation can also be calculated for other voltage deviations among a plurality of voltage deviations 710 besides the first voltage deviation 720. The plurality of second deviations calculated in this way can be a characteristic of a plurality of battery cells 120.

[0111] Figure 8 The process of setting the normal range of multiple battery cells based on multiple second deviations and multiple rates of change over time, according to some implementation methods, is shown.

[0112] Reference Figure 8 Figure 800 illustrates the process of setting the normal range of multiple battery cells based on multiple second deviations and multiple rates of change over time.

[0113] Figure 800 shows the normal range and lower limit of the rate of change (slope) over time on the horizontal axis, and the normal range and lower limit of the second deviation on the vertical axis. (This can be illustrated as follows...) Figure 5 The rate of change (slope) of Figure 800 over time can be calculated as shown in Figure 500, and it can be done as follows: Figure 7 The second deviation in Figure 800 is calculated in the same way as the second deviation 750. Each of the plurality of battery cells 120 can be represented as a point having a slope value and a second deviation value.

[0114] Figure 800 shows a representative value 810 of the slope values ​​of the plurality of battery cells 120 and a representative value 820 of the second deviation values ​​of the plurality of battery cells 120. The representative values ​​810 and 820 can be the average or median, etc. A lower limit value 830 of the slope can be set based on the standard deviation of the slope values ​​and the representative value 810, and a lower limit value 840 of the second deviation can be set based on the standard deviation of the second deviation values ​​and the representative value 820. According to an embodiment, the lower limit value 830 of the slope and / or the lower limit value 840 of the second deviation can be set to any one of -1σ to -3σ or any other suitable value.

[0115] In Figure 800, the normal range of the plurality of battery cells 120 can be set by a slope lower limit 830 and a second deviation lower limit 840. For example, among the plurality of battery cells 120, a first battery cell 850 falling within the normal range can be diagnosed as a normal battery cell, and a second battery cell 860 falling outside the normal range can be diagnosed as a low-voltage battery cell.

[0116] Figure 9 The steps of constructing a battery diagnostic method according to some embodiments are shown.

[0117] Reference Figure 9 The battery diagnostic method 900 may include steps 910 to 940. However, it is not limited thereto; some steps may be omitted or other general steps may be added, and the steps of the battery diagnostic method 900 may be performed in a different order than that shown.

[0118] Battery diagnostic method 900 may include steps processed in a time sequence by battery diagnostic device 130. Therefore, even though the following description of battery diagnostic device 130 is omitted, the same applies to battery diagnostic method 1000.

[0119] Steps 910 to 940 of the battery diagnostic method 900 can be performed by the sensors 131 and controller 132 of the battery diagnostic device 130. According to one embodiment, the battery diagnostic method 900 can be implemented via the execution of computational instructions configured to run on one or more processors.

[0120] In step 910, the battery diagnostic device 130 may collect multiple resting voltages from multiple battery cells during a resting period after charging or discharging has ended. In step 920, the battery diagnostic device 130 may calculate multiple voltage deviations based on the difference between a representative value of the multiple resting voltages and each of the multiple resting voltages. Step 910 may further include calculating multiple second deviations based on the difference between a representative value of the multiple voltage deviations and each of the multiple voltage deviations.

[0121] In step 930, the battery diagnostic device 130 can calculate multiple rates of change over time for multiple voltage deviations using regression analysis. In step 940, the battery diagnostic device 130 can diagnose the state of at least one or more battery cells based on the multiple rates of change over time. Additionally and / or alternatively, in step 940, the battery diagnostic device 130 can diagnose the state of at least one or more battery cells based on one or more second deviations of the multiple battery cells, in addition to the multiple rates of change for multiple voltage deviations, or in the absence of multiple rates of change for multiple voltage deviations. For example, according to one embodiment, step 930 of calculating the multiple rates of change for voltage deviations can be skipped, and multiple second deviations can be calculated in step 920, which can be used in step 940 to diagnose at least one battery cell and even all battery cells.

[0122] According to one embodiment, the battery management and / or diagnostic method may further include taking further action in response to the diagnosis of one or more battery cells (e.g., when a low-voltage cell is identified, or when a cell is identified as abnormal). According to one embodiment, the controller may be configured to send a warning alarm to a user device and / or display terminal regarding at least one diagnosed cell, such as a user device and / or display terminal registered with and / or associated with the diagnosed cell. For example, in response to the warning alarm, a user may choose to stop or modify their use of the cell, or repair or replace the cell. In another embodiment, the controller may be configured to disconnect or cut off power to at least one diagnosed cell to prevent damage or harm from the diagnosed cell. In another embodiment, the controller may be configured to electrically ground at least one diagnosed cell, for example, by short-circuiting the cell to ground. According to another embodiment, the controller may be configured to limit or modify the performance, output, and / or operating mode of an electrical device (e.g., a consumer device, electric vehicle, etc.) using at least one diagnosed cell. According to another embodiment, the controller can be configured to send information about at least one diagnosed unit to an external server, for example, to enable the server to perform functions similar to those described above, thereby taking action in response to the identification of low voltage or other abnormal units.

[0123] According to an embodiment, the battery diagnostic method 900 can be implemented as a computer program stored in a computer-readable storage medium. That is, the computer program may include instructions for implementing the battery diagnostic method 900, and the instructions may be stored in a computer-readable storage medium. The computer program may include a mobile application.

[0124] According to one embodiment, the computer-readable storage medium may include hardware devices, such as magnetic media like hard disks, floppy disks, and magnetic tapes; optical media like CD-ROMs and DVDs; and magneto-optical media like optical-floppy disks, ROMs, RAMs, and flash memory. Specifically, the hardware devices are configured to store and execute computer program instructions. The computer program instructions may include machine code created by a compiler and high-level language code that can be executed by a computer using an interpreter, etc. According to one embodiment, the controller includes one or more processors and one or more computer-readable media storing computational instructions that, when executed on one or more processors, cause the one or more processors to perform the steps and / or implementations described herein.

[0125] Unless explicitly stated otherwise, terms such as “comprising,” “constituting,” or “having” as used above mean that the corresponding component can be included and should therefore be interpreted as capable of including other components rather than excluding them. Unless otherwise defined, all terms including technical or scientific terms have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments disclosed in this document pertain. Common terms, such as those defined in dictionaries, should be interpreted in accordance with the context of the relevant art and not in an idealized or overly formal sense, unless explicitly defined in this document.

[0126] The above description is merely an illustrative description of the technical ideas disclosed in this document, and those skilled in the art to which the embodiments disclosed in this document pertain will be able to make various modifications and variations without departing from the basic characteristics of the embodiments disclosed in this document. Therefore, the embodiments disclosed in this document are not intended to limit the technical ideas of the embodiments disclosed in this document, but rather to illustrate them, and the scope of the technical ideas disclosed in this document is not limited by these embodiments. The scope of protection of the technical ideas disclosed in this document should be interpreted in accordance with the appended claims, and all technical ideas within the equivalent scope of the appended claims should be interpreted as including within the scope of the rights of this document.

Claims

1. A battery management device, comprising: A controller, comprising one or more processors, and One or more computer-readable media storing computation instructions, which, when executed on the one or more processors, cause the one or more processors to perform: During the resting period after the charging or discharging of multiple battery cells is completed, multiple resting voltages are received from each of the multiple battery cells. Multiple voltage deviations for each of the plurality of battery cells are calculated based on the difference between each of the plurality of resting voltages and a representative value of the plurality of resting voltages. Calculate the rate of change of the plurality of voltage deviations for each of the plurality of battery cells, and The state of at least one battery cell is diagnosed based on the rate of change of at least one of the plurality of battery cells over time.

2. The battery management device according to claim 1, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: Calculate the average and standard deviation of the rate of change of the plurality of battery cells, and The presence of low-voltage cells among the plurality of battery cells is diagnosed based on the average value and the standard deviation.

3. The battery management device according to claim 2, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: A standard score is calculated for at least one of the plurality of battery cells based on the average value and the standard deviation. When the standard score of the at least one battery cell is lower than the lower threshold, the at least one battery cell is diagnosed as a low voltage cell.

4. The battery management device according to claim 1, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: A plurality of second deviations are calculated based on the difference between a representative value of the plurality of voltage deviations and each of the plurality of voltage deviations, and The presence of a low-voltage cell among the plurality of battery cells is diagnosed based on the rate of change of the plurality of second deviations and the plurality of voltage deviations of each of the plurality of battery cells.

5. The battery management device according to claim 4, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: The normal range of the plurality of battery cells is set based on the plurality of second deviations and the plurality of rates of change over time, and Battery cells exhibiting a second deviation or rate of change outside the normal range are diagnosed as low-voltage cells.

6. The battery management device according to claim 1, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: The plurality of voltage deviations for each of the plurality of battery cells are calculated based on the median of the plurality of resting voltages for each of the plurality of battery cells, and The slope of each of the plurality of rates of change for each of the plurality of battery cells is estimated by linear regression analysis.

7. The battery management device according to claim 1, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: Receive the plurality of static voltages. Specifically, the plurality of resting voltages are collected during a first time interval after a buffer period following the end of charging of the plurality of battery cells, and / or The plurality of resting voltages are collected during a second time period starting from the end of the discharge of the plurality of battery cells.

8. The battery management device according to claim 1, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: The rate of change of the plurality of voltage deviations for each of the plurality of battery cells is calculated by regression analysis.

9. The battery management device according to claim 1, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: The state of each of the plurality of battery cells is diagnosed based on the rate of change of the plurality of battery cells over time.

10. The battery management device of claim 1, further comprising a sensor configured to collect the plurality of resting voltages of each of the plurality of battery cells during the resting period following the completion of charging or discharging of the plurality of battery cells.

11. The battery management device according to claim 1, wherein, The battery management device further includes an interface configured to communicate with a sensor to receive the plurality of resting voltages of each of the plurality of battery cells, wherein the sensor is configured to collect the plurality of resting voltages of each of the plurality of battery cells during a resting period after charging or discharging of the plurality of battery cells has been completed.

12. The battery management device according to claim 1, wherein, The computation instructions, when executed on the one or more processors, cause the one or more processors to execute: Diagnose at least one of the plurality of battery cells as a low-voltage cell and / or an abnormal cell, and In response to the diagnosis, perform any of the following: i) send a warning alarm to at least one of the user device and the display terminal regarding at least one of the diagnosed units; ii) disconnect or cut off power to at least one of the diagnosed units; iii) electrically ground at least one of the diagnosed units; iv) limit or modify at least one of the performance, output, and operating modes of the electrical devices using at least one of the diagnosed units; and v) send information about at least one of the diagnosed units to an external server.

13. A battery management method, implemented via the execution of computational instructions configured to run on one or more processors, the battery management method comprising: During the resting period after the charging or discharging of multiple battery cells is completed, multiple resting voltages collected for each of the multiple battery cells are received. The plurality of voltage deviations for each of the plurality of battery cells are calculated based on the difference between each of the plurality of resting voltages for each of the plurality of battery cells and a representative value of the plurality of resting voltages. Calculate the rate of change of the plurality of voltage deviations for each of the plurality of battery cells; as well as The state of at least one battery cell is diagnosed based on the rate of change of at least one of the plurality of battery cells.

14. The battery management method according to claim 13, wherein, Diagnosing the state of at least one of the plurality of battery cells includes: Calculate the average and standard deviation of the rate of change of the plurality of battery cells; and The presence of low-voltage cells among the plurality of battery cells is diagnosed based on the average value and the standard deviation.

15. The battery management method according to claim 14, wherein, Diagnosing the state of at least one of the plurality of battery cells includes: A standard score is calculated for at least one of the plurality of battery cells based on the average value and the standard deviation; and When the standard score of the at least one battery cell is lower than the lower threshold, the at least one battery cell is diagnosed as a low voltage cell.

16. The battery management method according to claim 13, wherein, Diagnosing the state of at least one of the plurality of battery cells includes: A plurality of second deviations are calculated based on the difference between a representative value of the plurality of voltage deviations and each of the plurality of voltage deviations; and The presence of a low-voltage cell among the plurality of battery cells is diagnosed based on the rate of change of the plurality of second deviations and the plurality of voltage deviations of each of the plurality of battery cells.

17. The battery management method according to claim 16, wherein, Diagnosing the state of at least one of the plurality of battery cells includes: The normal range of the plurality of battery cells is set based on the plurality of second deviations and the plurality of rates of change over time; and Battery cells exhibiting a second deviation or rate of change outside the normal range are diagnosed as low-voltage cells.

18. The battery management method according to claim 13, wherein, Calculating the plurality of voltage deviations for each of the plurality of battery cells includes: The plurality of voltage deviations for each of the plurality of battery cells are calculated based on the median of the plurality of resting voltages, and The calculation of the multiple rates of change of the multiple voltage deviations includes: The slope of each of the plurality of rates of change for each of the plurality of battery cells is estimated by linear regression analysis.

19. The battery management method according to claim 13, wherein, Receiving the plurality of static voltages includes: Receive multiple resting voltages collected during a first time interval after a buffer period following the end of charging of the plurality of battery cells, and Receive multiple resting voltages collected during a second time period starting from the end time of discharge of the plurality of battery cells.

20. A battery management system, comprising the battery management device according to claim 1, wherein the battery management system comprises: A charger / discharger configured to charge or discharge a plurality of battery cells.

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