Battery management device and operating method thereof

Abstract

Aspects of the disclosed technology include techniques, mechanisms, and battery management devices for diagnosing battery cells experiencing undervoltage. The battery management device may determine a cumulative balance time for each of a plurality of battery cells included in a battery pack. The battery management apparatus may determine whether the battery pack is abnormal by comparing a median of accumulated balance times of each of the plurality of battery cells with a first reference time. When the mid-value exceeds a first reference time, the battery management device may compare a cumulative balance time of each of the plurality of battery cells with a second reference time to identify at least one under-voltage battery cell among the plurality of battery cells.

Description

Technical Field

[0001] Cross - Reference to Related Applications

[0002] This application claims priority to Korean Patent Application No. 10 - 2023 - 0180590, filed on December 13, 2023, and Korean Patent Application No. 10 - 2022 - 0178734, filed on December 19, 2022, the entire disclosures of which are incorporated herein by reference. Technical Field

[0004] Embodiments disclosed herein relate to a battery management device and an operation method thereof. Background Art

[0005] An electric vehicle is powered from the outside to charge battery cells, and then a motor is driven by the voltage charged in the battery cells to obtain power. The battery cells of an electric vehicle are manufactured by accommodating an electrode assembly in a battery case and injecting an electrolyte into the battery case.

[0006] The battery cells may experience an under - voltage failure in which the voltage of the battery cells drops to a predetermined level or lower due to reasons such as foreign substances, folding of a separator, internal short - circuit, etc. The under - voltage battery cells may not experience a self - discharge event of voltage drop during their initial production, so it is difficult to detect them during the production process. If an internal short - circuit occurs due to the vehicle using the battery after the under - voltage battery cells are installed in the vehicle, the voltage may change due to the self - discharge current of the battery. However, it may be difficult for the battery management device to individually measure the self - discharge rate of the under - voltage battery cells, making it difficult to diagnose the under - voltage battery cells. Summary of the Invention

[0007] Technical Problem

[0008] Aspects of the disclosed technology include a battery management device and method in which early diagnosis of under - voltage battery cells is performed by using the cumulative balancing time of the battery cells, thereby ensuring the stability and reliability of battery energy.

[0009] The technical problems of the examples disclosed herein are not limited to the above - mentioned technical problems, and other unmentioned technical problems can be clearly understood by those of ordinary skill in the art from the following description.

[0010] Technical Solution

[0011] A battery management device according to some embodiments disclosed herein includes: a data management unit configured to calculate an accumulated balancing time for each of a plurality of battery cells included in a battery pack; and a controller configured to determine whether the battery pack is abnormal by comparing a median value of the accumulated balancing times of each of the plurality of battery cells with a first reference time, and when the median value exceeds the first reference time, diagnose at least one of the plurality of battery cells by comparing the accumulated balancing time of each of the plurality of battery cells with a second reference time.

[0012] According to some examples, the data management device may further include a memory, wherein the data management unit is further configured to record the accumulated balancing time in the memory by accumulating the balancing time for each of the plurality of battery cells.

[0013] According to some examples, the controller may further be configured to calculate a first balancing time by dividing a capacity deviation of the plurality of battery cells by a balancing capacity of the plurality of battery cells, calculate a second balancing time by multiplying the number of days of use of the battery pack by a value obtained by dividing a state of charge (SoC) deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells, and calculate a first reference time by multiplying a first threshold by a reference balancing time obtained by adding the first balancing time and the second balancing time.

[0014] According to some examples, the controller may further be configured to determine the battery pack as an abnormal battery pack when the median value exceeds the first reference time.

[0015] According to some examples, the controller may further be configured to list the plurality of battery cells based on the accumulated balancing time and extract a plurality of battery cells within a threshold rank, calculate a standard deviation of the accumulated balancing times of each of the plurality of battery cells within the threshold rank, and calculate the second reference time by subtracting a value obtained by multiplying a second threshold by the standard deviation from the median value.

[0016] According to some examples, the controller may further be configured to diagnose the battery cell when the accumulated balancing time of any one of the plurality of battery cells is less than the second reference time.

[0017] The operation method of a battery management device according to some examples disclosed in this document includes the following steps: calculating the cumulative balancing time of each battery cell among a plurality of battery cells included in a battery pack; calculating the median of the cumulative balancing time of each battery cell among the plurality of battery cells; determining whether the battery pack is abnormal by comparing the median with a first reference time; and when the median exceeds the first reference time, diagnosing at least one battery cell among the plurality of battery cells by comparing the cumulative balancing time of each battery cell among the plurality of battery cells with a second reference time.

[0018] According to some examples, the step of calculating the cumulative balancing time of each battery cell among a plurality of battery cells included in a battery pack may include: accumulating the balancing time of each battery cell among the plurality of battery cells and recording the cumulative balancing time in the memory.

[0019] According to some examples, the step of determining whether the battery pack is abnormal by comparing the median with the first reference time may include: calculating a first balancing time by dividing the capacity deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells; calculating a second balancing time by multiplying the number of days of use of the battery pack by a value obtained by dividing the state of charge (SoC) deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells; and calculating a first reference time by multiplying a first threshold by a reference balancing time obtained by adding the first balancing time and the second balancing time.

[0020] According to some examples, the step of determining whether the battery pack is abnormal by comparing the median with the first reference time may include: determining the battery pack as an abnormal battery pack when the median exceeds the first reference time.

[0021] According to some examples, when the median exceeds the first reference time, the step of diagnosing at least one battery cell among the plurality of battery cells by comparing the cumulative balancing time of each battery cell among the plurality of battery cells with a second reference time may include: listing the plurality of battery cells based on the cumulative balancing time and extracting a plurality of battery cells within the threshold rank; calculating the standard deviation of the cumulative balancing time of each battery cell among the plurality of battery cells within the threshold rank; and calculating the second reference time by subtracting a value obtained by multiplying a second threshold by the standard deviation from the median.

[0022] According to some examples, when the median value exceeds the first reference time, the step of diagnosing at least one of the plurality of battery cells by comparing the cumulative equalization time of each battery cell in the plurality of battery cells with a second reference time may include: diagnosing the battery cell when the cumulative equalization time of any one of the plurality of battery cells is less than the second reference time.

[0023] One aspect of the present disclosure provides a battery management device, the battery management device including: one or more processors configured to: compare a median value of cumulative equalization times of each battery cell in a plurality of battery cells included in a battery pack with a first reference time; based on the comparison, determine whether the battery pack is abnormal, wherein when the median value of the cumulative equalization times of each battery cell in the plurality of battery cells exceeds the first reference time, the battery pack is abnormal; and based on determining that the battery pack is abnormal, identify at least one abnormal battery cell among the plurality of battery cells based on determining that the cumulative equalization time of the at least one abnormal battery cell is less than a second reference time; and output a signal to a target device, wherein the signal identifies the at least one abnormal battery cell.

[0024] According to some examples, the one or more processors are further configured to calculate the cumulative equalization time of each battery cell in the plurality of battery cells.

[0025] According to some examples, the battery management device further includes a memory, wherein the one or more processors are further configured to store the cumulative equalization time in the memory by accumulating the equalization time of each battery cell in the plurality of battery cells.

[0026] According to some examples, the one or more processors are further configured to: calculate a first equalization time by dividing a capacity deviation of the plurality of battery cells by a balanced capacity of the plurality of battery cells; calculate a second equalization time by multiplying the number of days of use of the battery pack by a value obtained by dividing a state of charge (SoC) deviation of the plurality of battery cells by the balanced capacity of the plurality of battery cells; and calculate the first reference time by multiplying a first threshold by a reference equalization time obtained by adding the first equalization time and the second equalization time.

[0027] According to some examples, the one or more processors are further configured to: list the plurality of battery cells based on the cumulative balance time and extract a plurality of battery cells having respective cumulative balance times within a threshold rank; calculate a standard deviation of the cumulative balance time of each battery cell among the plurality of battery cells having respective cumulative balance times within the threshold rank; and calculate the second reference time by subtracting a value obtained by multiplying the second threshold by the standard deviation from the median.

[0028] Another aspect of the present disclosure provides a battery management method, the battery management method including the steps of: retrieving the cumulative balance time of each battery cell among the plurality of battery cells included in the battery pack from a memory; determining a median of the cumulative balance time of each battery cell among the plurality of battery cells; determining whether the battery pack is abnormal by comparing the median with a first reference time; based on determining that the median exceeds the first reference time, comparing the cumulative balance time of each battery cell among the plurality of battery cells with a second reference time; identifying at least one abnormal battery cell among the plurality of battery cells based on the comparison with the second reference time; and outputting a signal to a target device, wherein the signal identifies the at least one abnormal battery cell.

[0029] According to some examples, the step of determining the median of the cumulative balance time includes: recording the cumulative balance time in the memory by accumulating the balance time of each battery cell among the plurality of battery cells.

[0030] According to some examples, the step of determining whether the battery pack is abnormal includes: calculating a first balance time by dividing a capacity deviation of the plurality of battery cells by a balance capacity of the plurality of battery cells; calculating a second balance time by multiplying the number of days of use of the battery pack by a value obtained by dividing a state of charge (SoC) deviation of the plurality of battery cells by the balance capacity of the plurality of battery cells; and calculating the first reference time by multiplying a first threshold by a reference balance time obtained by adding the first balance time and the second balance time.

[0031] According to some examples, the step of determining whether the battery pack is abnormal includes: determining the battery pack as an abnormal battery pack when the median exceeds the first reference time.

[0032] According to some examples, the step of identifying the at least one abnormal battery cell includes: listing the plurality of battery cells based on the cumulative equalization time and extracting a plurality of battery cells within a threshold rank; calculating a standard deviation of the cumulative equalization time of each battery cell among the plurality of battery cells within the threshold rank; and calculating the second reference time by subtracting a value obtained by multiplying the second threshold by the standard deviation from the median.

[0033] According to some examples, the step of identifying the at least one abnormal battery cell includes: when the cumulative equalization time of a first battery cell among the plurality of battery cells is less than the second reference time, diagnosing the first battery cell as an abnormal battery cell.

[0034] Another aspect of the present disclosure may provide a non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform the following operations: comparing a median of the cumulative equalization time of each battery cell included in a battery pack with a first reference time; based on the comparison, determining whether the battery pack is abnormal, wherein when the median of the cumulative equalization time of each battery cell among the plurality of battery cells exceeds the first reference time, the battery pack is abnormal; based on determining that the battery pack is abnormal, identifying the at least one abnormal battery cell among the plurality of battery cells based on determining that the cumulative equalization time of the at least one abnormal battery cell is less than a second reference time; and outputting a signal to a target device, wherein the signal identifies the at least one abnormal battery cell.

[0035] According to some examples, the one or more processors are further configured to calculate the cumulative equalization time of each battery cell among the plurality of battery cells.

[0036] According to some examples, the one or more processors are further configured to: calculate a first equalization time by dividing a capacity deviation of the plurality of battery cells by an equalization capacity of the plurality of battery cells; calculate a second equalization time by multiplying the number of days of use of the battery pack by a value obtained by dividing a state of charge (SoC) deviation of the plurality of battery cells by the equalization capacity of the plurality of battery cells; and calculate the first reference time by multiplying a first threshold by a reference equalization time obtained by adding the first equalization time and the second equalization time.

[0037] According to some examples, the operation of determining whether the battery pack is abnormal includes: determining the battery pack as an abnormal battery pack when the median exceeds the first reference time.

[0038] According to some examples, the one or more processors are further configured to: list the plurality of battery cells based on the cumulative balancing time and extract a plurality of battery cells having respective cumulative balancing times within a threshold rank; calculate a standard deviation of the cumulative balancing time of each battery cell among the plurality of battery cells having respective cumulative balancing times within the threshold rank; and calculate the second reference time by subtracting a value obtained by multiplying a second threshold by the standard deviation from the median.

[0039] According to some examples, the operation of identifying the at least one abnormal battery cell includes: diagnosing the first battery cell as an abnormal battery cell when the cumulative balancing time of the first battery cell among the plurality of battery cells is less than the second reference time.

[0040] According to some examples, the instructions further cause the one or more processors to perform the following operation: record the cumulative balancing time in the memory by accumulating the balancing time of each battery cell among the plurality of battery cells.

[0041] Advantageous Effects

[0042] With the battery management device and its operation method according to some embodiments disclosed herein, early diagnosis of undervoltage battery cells can be performed by using the cumulative balancing time of battery cells, thereby ensuring the stability and reliability of battery energy. Early diagnosis can be performed before the undervoltage abnormal battery cells degrade the performance and safety of the battery pack. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 FIG. shows an example battery pack according to aspects of the present disclosure.

[0044] Figure 2 is a block diagram of an example configuration of a battery management device according to aspects of the present disclosure.

[0045] Figure 3 is an example graph showing the cumulative balancing time of a battery cell according to aspects of the present disclosure.

[0046] Figures 4a to 4c is an example table showing the state of charge (SoC) data of a battery cell according to aspects of the present disclosure.

[0047] Figure 5a is an example table showing the characteristic data of a battery cell according to aspects of the present disclosure.

[0048] Figure 5b is an example table showing the usage data of a battery cell according to aspects of the present disclosure.

[0049] Figure 6An example diagnosis of an under-voltage battery cell of a controller in accordance with aspects of the present disclosure.

[0050] Figure 7 A flowchart of an example method for diagnosing an under-voltage battery cell in accordance with aspects of the present disclosure.

[0051] Figure 8 A block diagram of an example computing system for performing an operational method for diagnosing an under-voltage battery cell in accordance with aspects of the present disclosure. DETAILED DESCRIPTION

[0052] The examples disclosed herein will be described in detail with reference to the accompanying drawings. When adding reference numerals to the components of each drawing, it should be noted that the same components are given the same reference numerals, even if they are shown in different drawings.

[0053] It should be understood that phrases such as "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" may include any one of the items listed together in the corresponding phrase among these phrases, or all possible combinations of these items. Terms such as "first", "second", "the first", "the second", "A", "B", "(a)", or "(b)" may simply be used to distinguish the corresponding components from other corresponding components, and do not otherwise limit the corresponding components (e.g., in terms of importance or order) unless otherwise explicitly stated.

[0054] It should be understood that the embodiments of the present disclosure and the terms used therein are not intended to limit the technical features described herein to a particular embodiment, and include various changes, equivalents, or substitutions of the corresponding embodiments. Regarding the description of the drawings, like reference numerals may be used to refer to like or related elements. It is to be understood that unless the relevant context clearly indicates otherwise, the singular form of a noun corresponding to an item may include one or more things.

[0055] It should be understood that if a certain (e.g., first) element is referred to as being "linked", "combined", "accessed", or "connected" or "coupled" to another (e.g., second) component, whether or not the term "functionally" or "communicatively" is used, this means that the certain component can be directly (e.g., in a wired manner), wirelessly, or through a third component connected to the other component. When a part is referred to as being "connected" to another part, it is not limited to the case where they are "directly connected", but also includes the case where they are "indirectly connected" by another element interposed therebetween. When a part is referred to as "including" or "containing" any element, this means that the part may further include other elements, without excluding other elements, unless otherwise specifically stated.

[0056] The methods according to various embodiments of the present disclosure may be included in a computer program product and provided as a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disc read-only memory (CD-ROM)), or distributed online through an app store (e.g., downloaded or uploaded), or directly distributed between two user devices. If distributed online, at least a part of the computer program product may be temporarily generated or at least temporarily stored in a machine-readable storage medium, such as the memory of a manufacturer's server, an app store's server, or a relay server.

[0057] Figure 1 An example battery pack according to aspects of the present disclosure is shown.

[0058] Referring Figure 1 , the battery pack 1000 may include a battery module 100, a battery management device 200, and a relay 300. In some embodiments, the battery module 100 may be a battery cell, and in such embodiments, the battery pack 1000 may have a cell-to-battery-pack structure.

[0059] The battery module 100 may include a plurality of battery cells 110, 120, 130, and 140. Although Figure 1 four battery cells are shown, the battery module 100 may include more or fewer than four battery cells. Showing four battery cells is for illustrative purposes only and not limiting.

[0060] The battery module 100 may supply power to a target device (not shown). To this end, the battery module 100 may be electrically connected to the target device. The target device may include an electrical, electronic, or mechanical device that operates by receiving power from the battery pack 1000 including a plurality of battery cells 110, 120, 130, and 140. In some cases, the target device may be, for example, an electric vehicle (EV) or an energy storage system (ESS), but the present disclosure is not limited thereto.

[0061] Each of the plurality of battery cells 110, 120, 130, and 140 may be a basic unit of a battery that can be used by charging and discharging electrical energy, and may be a lithium-ion (Li-ion) battery, a lithium-ion polymer battery, a nickel-cadmium (Ni-Cd) battery, a nickel-metal hydride (Ni-MH) battery, etc. Although Figure 1 a single battery module within the battery pack 1000 is shown, the battery pack 1000 may include more than one battery module.

[0062] The battery pack 1000 may include the battery management device 200 discussed in detail below. The battery management device 200 may be configured as a hardware component, a software program, an application specific integrated circuit (ASIC), etc., or any combination thereof. The battery management device 200 may manage and / or control the state and / or operation of the battery module 100. For example, the battery management device 200 may manage and / or control the state and / or operation of the plurality of battery cells 110, 120, 130, and 140 included in the battery module 100. The battery management device 200 may charge and / or discharge the battery module 100.

[0063] The battery management device 200 may control the operation of the relay 300. For example, the battery management device 200 may short-circuit the relay 300 to supply power to the target device. When a charging device is connected to the battery pack 1000, the battery management device 200 may short-circuit the relay 300.

[0064] In addition, the battery management device 200 may monitor the voltage, current, temperature, etc. of the battery module 100 and / or each of the plurality of battery cells 110, 120, 130, and 140 included in the battery module 100. For monitoring by the battery management device 200, sensors or various measurement modules (not shown) may be installed in the battery module 100, the charge / discharge path, any location of the battery module 100, etc. The battery management device 200 may calculate a parameter indicating the state of the battery module 100, such as the state of charge (SoC), based on measurement values such as the monitored voltage, current, or temperature.

[0065] The battery management device 200 may include a balancing circuit (not shown). The balancing circuit may include resistors and switching elements connected to both ends of each of the plurality of battery cells 110, 120, 130, and 140. The battery management device 200 may send a control signal to the balancing circuit to turn on / off the switching elements. The battery management device 200 may control the connection of the resistors by turning on / off the switching elements of the balancing circuit to consume the balancing current of the battery cells and reduce the voltage, thereby regulating the voltage of each battery cell to be the same.

[0066] More specifically, when the voltage deviation (e.g., SoC deviation) between the multiple battery cells 110, 120, 130, and 140 of the battery management device 200 is greater than or equal to a specific level, a balancing circuit can be used to balance the voltages of the multiple battery cells 110, 120, 130, and 140. For example, when the difference between the maximum voltage and the minimum voltage of the multiple battery cells 110, 120, 130, and 140 is greater than or equal to a preset threshold level, the battery management device 200 can balance the battery cell corresponding to the maximum voltage. The battery management device 200 can set the target voltage for balancing the battery cells and can send a control signal to the balancing circuit to terminate the balancing when the voltage of the battery cell reaches the target voltage.

[0067] The battery management device 200 can calculate the balancing time for each of the multiple battery cells 110, 120, 130, and 140. The balancing time can be defined as the time required to balance the battery cell. For example, the battery management device 200 can calculate the balancing time based on the SoC, battery capacity, and balancing efficiency of each of the multiple battery cells 110, 120, 130, and 140.

[0068] The battery management device 200 can diagnose undervoltage of at least one of the multiple battery cells 110, 120, 130, and 140 based on the cumulative balancing time of each of the multiple battery cells 110, 120, 130, and 140. For an undervoltage battery cell, over time, due to the self-discharge characteristic, an SoC deviation from a normal battery cell may occur. Therefore, a battery pack including an undervoltage battery cell can perform balancing on the battery cells by using the balancing circuit to solve the SoC deviation between the battery cells, thereby increasing the cumulative balancing time of the battery pack. In this case, the balancing circuit can perform balancing on the battery cell with the highest SoC instead of the battery cell with the lowest SoC, such that the balancing time of the undervoltage battery cell included in the battery pack is recorded as shorter than the balancing time of other normal battery cells.

[0069] Therefore, when the balancing time of a battery pack including an undervoltage battery cell increases and when the balancing time of the undervoltage battery cell is shorter than the balancing time of other normal battery cells, the battery management device 200 can diagnose the undervoltage battery cell. First, the battery management device 200 can compare the median of the cumulative balancing times of the multiple battery cells included in the battery pack with the median of the cumulative balancing times of a battery pack including normal battery cells to identify the battery pack suspected of having an abnormal voltage.

[0070] The battery management device 200 can identify a battery pack suspected of having an abnormal voltage, and can diagnose an under-voltage battery cell by using the deviation of the cumulative balancing time of a plurality of battery cells included in the battery pack. The battery management device 200 can diagnose an under-voltage battery cell by the relative balancing time deviation of a plurality of battery cells included in the battery pack.

[0071] Figure 2 is a block diagram of an example configuration of a battery management device according to aspects of the present disclosure.

[0072] The battery management device 200 may include a data management unit 210, a controller 220, and a memory 230.

[0073] The data management unit 210 may record the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 in the memory 230. The data management unit 210 may calculate the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 based on the SoC, battery capacity, and balancing efficiency of each of the plurality of battery cells 110, 120, 130, and 140. For example, the data management unit 210 may calculate the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 by measuring the time for performing balancing on each battery cell when the switching element of the balancing circuit connected to each of the battery cells 110, 120, 130, and 140 is turned on.

[0074] The data management unit 210 may record the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 in the memory 230 at a preset interval. For example, the data management unit 210 may store the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 individually, or store the balancing time of each battery module 100 including the plurality of battery cells 110, 120, 130, and 140 individually.

[0075] The data management unit 210 may accumulate the recorded balancing time of each of the plurality of battery cells 110, 120, 130, and 140 in the memory 230 to calculate the cumulative balancing time of each of the plurality of battery cells 110, 120, 130, and 140.

[0076] The controller 220 may be implemented as a processor for arithmetic processing and instruction execution, an interface circuit for interacting with other components of the target device, a battery pack, etc. According to some embodiments, the communication scheme of the interface circuit may be a device-to-device communication scheme, such as a bus, general-purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI).

[0077] The controller 220 may execute instructions that implement processes inside the target device including the device 100 or the battery pack. The controller 220 may be implemented as a general-purpose microprocessor or a plurality of logic gate arrays for processing various operations, and may be composed of a single processor or multiple processors. For example, the controller 220 may be implemented in the form of a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), an application processor (AP), an application-specific integrated circuit (ASIC), or a combination thereof.

[0078] The memory 230 may accumulate and store the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 measured by the data management unit 210. The memory 230 may be implemented in the form of, for example, an electrically erasable programmable read-only memory (EEPROM).

[0079] The memory 230 may store various data, instructions, mobile applications, computer programs, etc. For example, the memory 230 may be implemented as a non-volatile memory such as ROM, PROM, EPROM, EEPROM, flash memory, PRAM, MRAM, RRAM, FRAM, etc., or a volatile memory such as DRAM, SRAM, SDRAM, PRAM, RRAM, FeRAM, etc., or may be implemented in the form of an HDD, SSD, SD, micro SD, etc., or a combination thereof.

[0080] Figure 3 is an example diagram showing the cumulative balancing time of battery cells according to aspects of the present disclosure.

[0081] Refer to Figure 3, the data management unit 210 can separately distinguish and manage the cumulative equalization time of each of the plurality of battery cells 110, 120, 130, and 140 based on the battery cell numbers of each of the plurality of battery cells 110, 120, 130, and 140. According to some examples, the data management unit 210 can manage the cumulative equalization time separately for each battery module based on the battery module number of the battery module 100 including each of the plurality of battery cells 110, 120, 130, and 140. For example, when the battery pack 1000 includes a total of 8 battery modules and each battery module includes 12 battery cells, the data management unit 210 can separately manage the cumulative equalization time of the 96 battery cells based on the battery cell numbers of each of the 96 battery cells and the battery module numbers of the battery modules including each battery cell.

[0082] The controller 220 can diagnose undervoltage of at least one of the plurality of battery cells 110, 120, 130, and 140 based on the cumulative equalization time of each of the plurality of battery cells 110, 120, 130, and 140. More specifically, the controller 220 can determine whether the battery pack 1000 including the plurality of battery cells 110, 120, 130, and 140 is abnormal based on the cumulative equalization time of each of the plurality of battery cells 110, 120, 130, and 140. When the battery pack includes a battery cell with a high self-discharge rate, the battery pack may be abnormal. Whether the self-discharge rate is high can depend on the cumulative equalization time. According to some examples, if the battery pack has an abnormal cell, the battery pack is abnormal. The normal equalization time can include an equalization time close to the median. Based on determining that the battery pack 1000 is abnormal, the controller 220 can diagnose undervoltage of at least one of the plurality of battery cells 110, 120, 130, and 140 included in the battery pack 1000.

[0083] First, the controller 220 can calculate the median of the cumulative equalization times of the plurality of battery cells 110, 120, 130, and 140. In some embodiments, the cumulative equalization times of the plurality of battery cells 110 to 140 can correspond to the average equalization time among the plurality of battery cells 110 to 140. The controller 220 can use the median (or average value) of the cumulative equalization times of the plurality of battery cells 110, 120, 130, and 140 included in the battery pack 1000 to determine whether the battery pack 1000 is abnormal. Each time the cell equalization is performed, the median of the cumulative equalization time can be determined. The cell equalization can be performed at a predetermined time interval, such as once a day, twice a day, etc. When the battery pack is not in use, such as when the battery pack is turned off, additional cell equalization can be performed.

[0084] The controller 220 can determine whether the battery pack 1000 is abnormal by comparing the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 with a preset first reference time T1. The preset reference time, also known as the T value, can be based on patterns observed during previous cell balancing implementations. The T value can remain constant over time unless one or more conditions trigger the need for a new T value. For example, when the battery pack ages, when the number of abnormal battery cells within the battery pack is equal to or greater than 2, etc., a new T value may be required. The first reference time T1 can be a criterion for determining whether the battery pack 1000 is "abnormal". In addition, the first reference time T1 can indicate the degree of difference between the balancing time of the battery pack 1000 and the balancing time of a normal battery pack.

[0085] When the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 exceeds the preset first reference time T1, the controller 220 can identify the battery pack 1000 as an abnormal battery pack by determining that the total cumulative balancing time of the multiple battery cells 110, 120, 130, and 140 included in the battery pack 1000 exceeds a predetermined level.

[0086] The controller 220 can determine the first reference time T1 by using Equation 1 below.

[0087] [Equation 1]

[0088] First reference time (T1) = Reference balancing time (T0) * First threshold

[0089] In Equation 1, the reference balancing time T0 can represent the balancing time of the battery pack 1000 that can be obtained when the battery pack 1000 is being driven normally. That is, the reference balancing time T0 can represent a predicted value of the cumulative balancing time of the battery cells included in a normal battery pack 1000 that does not include under-voltage battery cells.

[0090] The controller 220 can generate the first reference time T1 by multiplying the reference balancing time T0 by the first threshold. The first threshold can be set considering the deviation of the usage time for each SoC region of the battery pack 1000 and the errors that may occur during the calculation of the balancing time of the battery cells. In some cases, the usage time for each SoC region may be based on a comparison of the usage time at low SoC and the usage time at high SoC, from which the deviation can be determined. In addition, cell balancing can be performed based on the estimated cell SoC. Since the estimation may result in inaccurate cell SoC, the balancing time error is considered. For example, the controller 220 can set the first threshold to "3". The controller 220 can generate the first reference time T1 by multiplying the reference balancing time T0 by the first threshold "3".

[0091] The reference balance time T0 will be described below with reference to Equation 2.

[0092] [Equation 2]

[0093] Reference balance time (T0) = First balance time (t1) + Second balance time (t2)

[0094]

[0095] Referring to Equation 2, the reference balance time T0 can be calculated by adding the first balance time t1 and the second balance time t2.

[0096] The first balance time t1 can be the balance time caused by the capacity deviation of the battery cells, and the second balance time t2 can be the balance time caused by the self-discharge rate deviation of the battery cells. The factors that cause the SoC deviation between the battery cells can include the capacity deviation of the battery cells and the self-discharge rate deviation of the battery cells. The controller 220 can calculate each of the first balance time t1 caused by the capacity deviation of the battery cells and the second balance time t2 caused by the self-discharge rate deviation of the battery cells.

[0097] The first balance time t1 can be the deviation caused during the manufacturing process of the battery cells and can change according to the usage pattern of the battery. The controller 220 can calculate the first balance time t1 by dividing the capacity deviation of the plurality of battery cells 110, 120, 130, and 140 by the balance capacity of the plurality of battery cells 110, 120, 130, and 140.

[0098] The second balance time t2 can be the SoC deviation caused by the self-discharge rate deviation of the battery cells and may be caused by the reduction in the discharge rate of the battery cells within a specific time. The controller 220 can calculate the second balance time t2 by multiplying the number of days of use of the battery pack 1000 by the value obtained by dividing the SoC deviation caused by the self-discharge rate of the plurality of battery cells 110, 120, 130, and 140 by the balance capacity of the plurality of battery cells 110, 120, 130, and 140. The SoC deviation caused by the self-discharge rate of the plurality of battery cells 110, 120, 130, and 140 can vary according to the average temperature of the plurality of battery cells 110, 120, 130, and 140 and the initial SoC of the plurality of battery cells 110, 120, 130, and 140.

[0099] Figures 4a to 4c is an example table showing the SoC data of the battery cells according to aspects of the present disclosure.

[0100] Figure 4a A table showing the SoC based on the temperature and time of the battery cells when the initial SoC of the battery cells is 20%.Figure 4b A table showing the SoC based on the temperature and time of the battery cell when the initial SoC of the battery cell is 50%. Figure 4c A table showing the SoC based on the temperature and time of the battery cell when the initial SoC of the battery cell is 80%.

[0101] The controller 220 can calculate the second balancing time t2 by using Figures 4a to 4c The controller 220 can calculate the SoC deviation caused by the self-discharge rate of the battery cell by using Figures 4a to 4c with respect to the initial SoC of the battery cell and the average temperature of the battery cell. The controller 220 can calculate the second balancing time t2 by using the SoC deviation caused by the self-discharge rate of the battery cell. For example, when the initial SoC of the battery cell is 20% and the average temperature of the battery cell is 60 °C, the controller 220 can use Figure 4a the shown table to use a battery cell with an SoC of 17.5% after 90 days.

[0102] The controller 220 can calculate a reference balancing time T0 by using battery characteristic data including the capacity, capacity deviation, balancing current, and balancing capacity corresponding to the characteristics of the battery cell and multiple battery cells 110, 120, 130, and 140. The battery cell capacity can indicate the capacity of the battery cell. The battery cell capacity deviation can indicate the deviation between the capacity of the battery cell and the median of the capacitances of all battery cells. When performing cell balancing, the balancing current can measure the current flowing through the cell. The battery cell balancing capacity can indicate the amount of cell capacity that the battery cell imparts to other cells in one day.

[0103] Figure 5a is an example table showing the characteristic data of the battery cell according to aspects of the present disclosure.

[0104] Referring to Figure 5a the controller 220 can calculate a first balancing time t1 and a second balancing time t2 by using the capacity, capacity deviation, balancing current, and balancing capacity data corresponding to the characteristics of the multiple battery cells 110, 120, 130, and 140 of the multiple battery cells 110, 120, 130, and 140.

[0105] For example, referring to Figure 5a the controller 220 can obtain "1 Ah" as the capacity deviation of the multiple battery cells 110, 120, 130, and 140, and "1.2 Ah / day" as the balancing capacity of the multiple battery cells 110, 120, 130, and 140. The controller 220 can divide the capacity deviation of the multiple battery cells 110, 120, 130, and 140 by the balancing capacity to calculate the first balancing time t1 as "0.83 days".

[0106] For example, referring to Figure 5a , the controller 220 may obtain "1.2 Ah / day" as the equalization capacity of the plurality of battery cells 110, 120, 130, and 140, and use the equalization capacity to calculate a second equalization time t2 of the plurality of battery cells 110, 120, 130, and 140.

[0107] The controller 220 may also calculate a reference equalization time T0 by using battery cell usage data generated from the usage of the plurality of battery cells 110, 120, 130, and 140, where the battery cell usage data includes the number of days of use of the battery pack, the average temperature of the battery cells, the average SoC, the self-discharge rate of the battery cells, the self-discharge rate deviation, and the SoC deviation caused by the self-discharge rate.

[0108] Figure 5b is an example table showing the usage data of battery cells according to aspects of the present disclosure. The number of days of use of the battery pack may indicate the number of days the battery pack is used per year. The average temperature of the battery cells may indicate the average temperature of the plurality of battery cells within a preset period (year, month, day, etc.). The average SoC of the battery cells may indicate the average SoC of the battery cells within a preset period (year, month, day, etc.). The self-discharge rate may indicate the amount of self-discharge of the battery cells within 30 days. The self-discharge rate deviation may indicate the deviation between the self-discharge of a battery cell and the median of the self-discharge of all battery cells. The SoC deviation caused by the self-discharge rate may indicate the amount of SoC deviation of a battery cell due to self-discharge in one day.

[0109] For example, referring to Figure 5b , the controller 220 may obtain "365 days" as the number of days of use of the battery pack 1000, obtain "0.00667" as the SoC deviation caused by the self-discharge rate of the plurality of battery cells 110, 120, 130, and 140, and calculate the second equalization time t2 as "1.01389 days" by multiplying the number of days of use of the battery pack 1000 by a value obtained by dividing the SoC deviation caused by the self-discharge rate by the equalization capacity of the plurality of battery cells 110, 120, 130, and 140 obtained through Figure 5a .

[0110] The controller 220 may calculate a first equalization time t1 and a second equalization time t2 respectively, and add the first equalization time t1 and the second equalization time t2 to calculate the reference equalization time T0. For example, the controller 220 may calculate the first equalization time t1 as "0.83 days", calculate the second equalization time t2 as "1.01389 days", and add the first equalization time t1 and the second equalization time t2 to calculate the reference equalization time T0 as "1.84722 days".

[0111] The controller 220 can also generate a first reference time T1 by multiplying the generated reference balancing time T0 by a first threshold. For example, the controller 220 can calculate the reference balancing time T0 as "1.84722 days" and multiply the reference balancing time T0 by the first threshold "3" to calculate the first reference time T1 as "5.54167 days".

[0112] When the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 exceeds the first reference time T1, the controller 220 can determine that the battery pack 1000 is abnormal. For example, when the controller 220 calculates the first reference time T1 as "5.54167 days" and calculates the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 as "51.6826 days", the controller 220 can determine that the battery pack 1000 is abnormal.

[0113] In some embodiments, based on determining that the battery pack 1000 is abnormal, the controller 220 can send an output signal to an external device or a target device. The signal can identify at least one battery cell among the multiple battery cells 110 to 140 that may experience undervoltage. The external device or the target device can use the received signal to balance the multiple battery cells 110 to 140. In some cases, the external device or the target device can be a vehicle, such as an electric vehicle (EV), a hybrid electric vehicle (HEV), an electric bicycle (e-bike), etc. The signal can notify the driver of the vehicle of the detected battery problem and can limit further battery performance.

[0114] For example, when the controller 220 calculates the first reference time T1 as "5.54167 days" and calculates the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 as "3.88300 days", the controller 220 can determine that the battery pack 1000 is normal.

[0115] When the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 exceeds the first reference time T1, the controller 220 can compare the cumulative balancing time of each battery cell among the multiple battery cells 110, 120, 130, and 140 with a second reference time T2 and can diagnose at least one battery cell among the multiple battery cells 110, 120, 130, and 140.

[0116] According to some embodiments, the controller 220 may list the plurality of battery cells 110, 120, 130, and 140 based on their cumulative balancing times, and may extract the battery cells within the threshold ranking from among the plurality of battery cells 110, 120, 130, and 140. The threshold may be determined experimentally and may exclude potential balancing time outliers. If necessary, the threshold may be changed when a decrease in the performance of an abnormal cell is detected.

[0117] For example, the controller 220 may list the plurality of battery cells 110, 120, 130, and 140 based on their cumulative balancing times, and extract the battery cells corresponding to the top 10% and bottom 10%. As described above, the battery module 100 may include more or fewer than four battery cells 110, 120, 130, and 140. Thus, the battery cells that may be extracted may be Figure 1 additional battery cells not shown in. For example, in an embodiment where the battery pack 1000 includes 8 battery modules, each of which includes 12 battery cells, the controller 220 may list each of the 96 battery cells and their corresponding balancing times. Among the 96 battery cells, the controller 220 may extract the balancing cells within the top 10% of the balancing times and the balancing cells within the bottom 10% of the balancing times. In some embodiments, the battery pack 1000 may include more or fewer than 96 battery cells. The 96 battery cells are discussed herein by way of example only and not limitation.

[0118] The controller 220 may calculate the standard deviation σ of the cumulative balancing times of each battery cell within the threshold ranking. For example, the controller 220 may list the plurality of battery cells 110, 120, 130, and 140 based on their cumulative balancing times and calculate the standard deviation σ of the cumulative balancing times of the remaining battery cells excluding the top 10% cells and the bottom 10% cells as "0.72210", which may include Figure 1 additional battery cells not shown in the battery module 100.

[0119] The controller 220 may calculate a second reference time T2 by using the median of the cumulative balancing times of the plurality of battery cells 110, 120, 130, and 140 and the standard deviation σ. The second reference time T2 may be a criterion for diagnosing a battery cell as an undervoltage battery cell. The second reference time T2 may indicate the degree of difference between the balancing time of a battery cell and the balancing time of a normal battery pack.

[0120] The controller 220 may generate the second reference time T2 based on Equation 3 below.

[0121] [Equation 3]

[0122] Second reference time (T2) = Median - Standard deviation (σ) * Second threshold

[0123] The controller 220 can calculate the second reference time T2 by subtracting the product of the standard deviation σ and the second threshold from the median of the cumulative balancing times of the plurality of battery cells 110, 120, 130, and 140.

[0124] For example, the controller 220 can calculate the median of the cumulative balancing times of the plurality of battery cells 110, 120, 130, and 140 as "51.6826 days", calculate the standard deviation σ of the cumulative balancing times of the plurality of battery cells 110, 120, 130, and 140 as "0.72210 days", and subtract the product "8.9693 days" of the standard deviation σ and the second threshold "10" from the median, thereby calculating the second reference time T2 as "42.7133 days".

[0125] When the cumulative balancing time of any one of the plurality of battery cells 110, 120, 130, and 140 is less than the second reference time T2, the controller 220 can diagnose the battery cell as an under-voltage battery cell. In this case, the controller 220 can send an output signal to an external device or a target device. The signal can identify at least one battery cell that may experience under-voltage. The external device or the target device can use the received signal to balance the plurality of battery cells. In some cases, the external device or the target device can be a vehicle, such as an electric vehicle (EV), a hybrid electric vehicle (HEV), an electric bicycle (e-bike), etc. The signal can notify the driver of the vehicle of the detected battery problem and can limit further battery performance.

[0126] Figure 6 This is an example diagnosis of an under-voltage battery cell of a controller according to aspects of the present disclosure.

[0127] The controller 220 can calculate the second reference time T2 by subtracting the product of the standard deviation σ and the second threshold from the median of the cumulative balancing times of the plurality of battery cells 110, 120, 130, and 140. The controller 220 can compare the second reference time T2 with the cumulative balancing time, and based on determining that the cumulative balancing time is less than the second reference time T2, the controller 220 can diagnose the battery cell as an under-voltage battery cell.

[0128] The controller 220 can identify an under-voltage battery cell among the plurality of battery cells 110, 120, 130, and 140 by comparing the differences in the cumulative balancing times between the plurality of battery cells 110, 120, 130, and 140.

[0129] According to some embodiments disclosed herein, the battery management device 200 may perform early diagnosis of under-voltage battery cells by using the cumulative balancing time of the battery cells, thereby ensuring the stability and reliability of battery energy.

[0130] In addition, since it is not necessary to remove the battery to diagnose battery cells with a high self-discharge rate in the state of the battery mounted on a vehicle, the battery management device 200 can quickly and conveniently diagnose under-voltage battery cells.

[0131] Figure 7 is a flowchart of an example method for diagnosing under-voltage battery cells according to aspects of the present disclosure.

[0132] Referring to Figure 7 , the operation method may be performed by the battery management device 200 and may include the following operations: operation S101, calculating the cumulative balancing time of each of the plurality of battery cells 110, 120, 130, and 140 included in the battery pack 1000; operation S102, calculating the median of the cumulative balancing times of each of the plurality of battery cells 110, 120, 130, and 140; operation S103, determining whether the battery pack 1000 is abnormal by comparing the median with a first reference time T1; and operation S104, diagnosing at least one of the plurality of battery cells 110, 120, 130, and 130 by comparing the cumulative balancing time of each of the plurality of battery cells 110, 120, 130, and 140 with a second reference time T2.

[0133] In block S101, the data management unit 210 may record the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 in the memory 230. The data management unit 210 may calculate the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 based on the SoC, battery capacity, and balancing efficiency of each of the plurality of battery cells 110, 120, 130, and 140. For example, the data management unit 210 may calculate the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 by measuring the time for performing balancing on each battery cell when the switching element of the balancing circuit connected to each of the battery cells 110, 120, 130, and 140 is turned on.

[0134] The data management unit 210 may store the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 in the memory 230 at a preset interval. The preset interval may indicate the completion of each iteration of cell balancing. After each iteration is completed (or at each preset interval), the balancing time and its median value may be stored. For example, the data management unit 210 may store the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 individually, or store the balancing time of each battery module 100 including the plurality of battery cells 110, 120, 130, and 140 individually.

[0135] The data management unit 210 may accumulate the balancing time of each of the plurality of battery cells 110, 120, 130, and 140, and may calculate the accumulated balancing time of each of the plurality of battery cells 110, 120, 130, and 140. The accumulated balancing time may refer to the balancing time of a single battery cell over time.

[0136] The memory 230 may store the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 measured by the data management unit 210. The memory 230 may accumulate and store the balancing time of each of the plurality of battery cells 110, 120, 130, and 140 for each battery cell.

[0137] The data management unit 210 may store the accumulated balancing time of each battery cell individually based on the battery cell number of each of the plurality of battery cells 110, 120, 130, and 140. According to some embodiments, the data management unit 210 may manage the accumulated balancing time of each battery module individually based on the battery module number of the battery module 100 including each of the plurality of battery cells 110, 120, 130, and 140.

[0138] In block S102, the controller 220 may calculate the median (or average value) of the accumulated balancing time of the plurality of battery cells 110, 120, 130, and 140. The controller 220 may use the median of the accumulated balancing time of the plurality of battery cells 110, 120, 130, and 140 to determine whether the battery pack 1000 is abnormal.

[0139] In block S103, the controller 220 may determine whether the battery pack 1000 is abnormal by comparing the median of the accumulated balancing time of the plurality of battery cells 110, 120, 130, and 140 with a preset first reference time T1. The first reference time T1 may indicate the degree of difference between the balancing time of the battery pack 1000 and the balancing time of a normal battery pack.

[0140] The controller 220 may determine that the battery pack 1000 is an abnormal battery pack based on the cumulative balancing time of the plurality of battery cells 110, 120, 130, and 140 exceeding a preset first reference time T1.

[0141] The controller 220 may generate the first reference time T1 by using Equation 4 below.

[0142] [Equation 4]

[0143] First reference time (T1) = Reference balancing time (T0) × First threshold

[0144] In Equation 4, the reference balancing time T0 may represent the balancing time of the battery pack 1000 that can be obtained when the battery pack 1000 is normally driven. That is, the reference balancing time T0 may represent a predicted value of the cumulative balancing time of the battery cells included in the normal battery pack 1000 excluding the under-voltage battery cells.

[0145] The controller 220 may generate the first reference time T1 by multiplying the reference balancing time T0 by the first threshold. The first threshold may be set in consideration of the deviation of the usage time with respect to each SoC region of the battery pack 1000 and the error that may occur during the calculation of the balancing time of the battery cells. For example, the controller 220 may set the first threshold to "3". That is, the controller 220 may generate the first reference time T1, which is three times the reference balancing time T0, by multiplying the reference balancing time T0 by the first threshold "3".

[0146] The reference balancing time T0 will be described below with reference to Equation 5.

[0147] [Equation 5]

[0148] Reference balancing time (T0) = First balancing time (t1) + Second balancing time (t2)

[0149]

[0150]

[0151] Referring to Equation 5, the reference balancing time T0 may be calculated by adding the first balancing time t1 and the second balancing time t2.

[0152] The first balancing time t1 may be the balancing time caused by the capacity deviation of the battery cells, and the second balancing time t2 may be the balancing time caused by the self-discharge rate deviation of the battery cells. The factors causing the SoC deviation between the battery cells may include the capacity deviation of the battery cells and the self-discharge rate deviation of the battery cells.

[0153] The controller 220 may calculate each of a first equalization time t1 caused by a capacity deviation of the battery cells and a second equalization time t2 caused by a self-discharge rate deviation of the battery cells. The first equalization time t1 may be a deviation caused during the manufacturing process of the battery cells and may vary according to the usage pattern of the battery.

[0154] The controller 220 may calculate the first equalization time t1 by dividing the capacity deviation of the plurality of battery cells 110, 120, 130, and 140 by the equalization capacity of the plurality of battery cells 110, 120, 130, and 140. The second equalization time t2 may be an SoC deviation caused by a self-discharge rate deviation of the battery cells and may be caused by a decrease in the discharge rate of the battery cells within a specific time.

[0155] The controller 220 may calculate the second equalization time t2 by multiplying the number of days of use of the battery pack 1000 by a value obtained by dividing the SoC deviation caused by the self-discharge rate of the plurality of battery cells 110, 120, 130, and 140 by the equalization capacity of the plurality of battery cells 110, 120, 130, and 140. The SoC deviation caused by the self-discharge rate of the plurality of battery cells 110, 120, 130, and 140 may vary according to the average temperature of the plurality of battery cells 110, 120, 130, and 140 and the initial SoC of the plurality of battery cells 110, 120, 130, and 140.

[0156] The controller 220 may calculate a reference equalization time T0 by using battery characteristic data including the capacity, capacity deviation, equalization current, and equalization capacity of the battery cells corresponding to the characteristics of the plurality of battery cells 110, 120, 130, and 140 during their manufacturing process.

[0157] The controller 220 may calculate the first equalization time t1 and the second equalization time t2 by using the capacity, capacity deviation, equalization current, and equalization capacity data of the plurality of battery cells 110, 120, 130, and 140 corresponding to the characteristics of the plurality of battery cells 110, 120, 130, and 140 during their manufacturing process.

[0158] The controller 220 may also calculate the reference equalization time T0 by using battery cell usage data generated according to the usage of the plurality of battery cells 110, 120, 130, and 140, where the battery cell usage data includes the number of days of use of the battery pack, the average temperature of the battery cells, the average SoC, the self-discharge rate of the battery cells, the self-discharge rate deviation, and the SoC deviation caused by the self-discharge rate.

[0159] The controller 220 may calculate a first balancing time t1 and a second balancing time t2 by using the number of days of use of the battery pack 1000 generated from the use of multiple battery cells 110, 120, 130, and 140, the average temperature of the multiple battery cells 110, 120, 130, and 140, the average SoC and self-discharge rate of the battery cells, the self-discharge rate deviation, and the SoC deviation caused by the self-discharge rate of the multiple battery cells 110, 120, 130, and 140.

[0160] The controller 220 may calculate the first balancing time t1 and the second balancing time t2 respectively, and add the first balancing time t1 and the second balancing time t2 to calculate a reference balancing time T0.

[0161] The controller 220 may also generate a first reference time T1 by multiplying the generated reference balancing time T0 by a first threshold.

[0162] When the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 exceeds the first reference time T1, the controller 220 may determine that the battery pack 1000 is abnormal. For example, the controller 220 may calculate the first reference time T1 as "5.54167 days" and calculate the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 as "51.6826 days". Since the median of the cumulative balancing time is greater than T1, the controller 220 may determine that the battery pack 1000 is abnormal.

[0163] For example, the controller 220 may calculate the first reference time T1 as "5.54167 days" and calculate the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 as "3.88300 days". Since the median of the cumulative balancing time is less than T1, the controller 220 may determine that the battery pack 1000 is normal.

[0164] In block S104, based on determining that the median of the cumulative balancing times of the multiple battery cells 110, 120, 130, and 140 exceeds the first reference time T1, the controller 220 may compare the cumulative balancing time of each battery cell among the multiple battery cells 110, 120, 130, and 140 with a second reference time T2.

[0165] According to some embodiments, the controller 220 may list the plurality of battery cells 110, 120, 130, and 140 based on the cumulative balancing time of the plurality of battery cells 110, 120, 130, and 140, and may extract the battery cells within the threshold rank from among the plurality of battery cells 110, 120, 130, and 140. For example, the controller 220 may list the plurality of battery cells 110, 120, 130, and 140 based on the cumulative balancing time of the plurality of battery cells 110, 120, 130, and 140, and may extract the battery cells corresponding to the top 10% and the bottom 10%, which may include the plurality of battery cells 110, 120, 130, and 140 and additional battery cells within the battery module 100 ( Figure 1 not shown in

[0166] The controller 220 may calculate the standard deviation σ of the cumulative balancing time of each battery cell within the threshold rank. For example, the controller 220 may list the plurality of battery cells 110, 120, 130, and 140 based on the cumulative balancing time of the plurality of battery cells 110, 120, 130, and 140, and may calculate the standard deviation σ of the cumulative balancing time of the plurality of other battery cells 110, 120, 130, and 140 except for the plurality of battery cells 110, 120, 130, and 140 corresponding to the top 10% and the bottom 10% as "0.72210". According to some embodiments, 100 battery cells may each have 100 cumulative balancing times. When arranged in ascending order, the 100 cumulative balancing times may be {0.1, 50.0357, 50.0991, 50.1008, 50.1615,..., 52.9335, 52.9363, 52.9591, 52.9706, 52.9988}. In this example, the battery cell with a cumulative balancing time of 0.1 may be determined to be abnormal at a later stage. To calculate the standard deviation σ, the top 10% and the bottom 10% of the 100 battery cells are excluded so that potential outliers such as 0.1 are not considered. When arranged in ascending order, the remaining 80 cumulative balancing times may be {50.3109, 50.3477, 50.3749, 50.4425, 50.4914,..., 52.6868, 52.7014, 52.7290, 52.7344, 52.7462}. For example, based on the remaining 80 cumulative balancing times, the standard deviation σ may be calculated as "0.72210". Meanwhile, if the top 10% and the bottom 10% of the 100 battery cells are not excluded, the standard deviation σ of the 100 battery cells may be "5.54167" because outliers such as "0.1" are considered, which may lead to inaccurate diagnosis of abnormal battery cells.

[0167] The controller 220 may calculate a second reference time T2 by using the median and the standard deviation σ of the cumulative balancing times of the plurality of battery cells 110, 120, 130, and 140. The second reference time T2 may be used to diagnose a battery cell as an undervoltage battery cell. That is, the second reference time T2 may indicate the degree of difference between the balancing time of the battery cell and the balancing time of a normal battery pack.

[0168] The controller 220 may generate the second reference time T2 based on Equation 6 below.

[0169] [Equation 6]

[0170] Second reference time (T2) = Median - Standard deviation (σ) * Second threshold

[0171] The controller 220 may calculate the second reference time T2 by subtracting the product of the standard deviation σ and the second threshold from the median of the cumulative balancing times of the plurality of battery cells 110, 120, 130, and 140.

[0172] When the cumulative balancing time of any one of the plurality of battery cells 110, 120, 130, and 140 is less than the second reference time T2, the controller 220 may diagnose the battery cell as an undervoltage battery cell.

[0173] The controller 220 may identify an undervoltage battery cell among the plurality of battery cells 110, 120, 130, and 140 by comparing the differences in the cumulative balancing times between the plurality of battery cells 110, 120, 130, and 140.

[0174] Figure 8 is a block diagram of an example computing system for performing an operational method of diagnosing an undervoltage battery cell according to aspects of the present disclosure.

[0175] A computing system 2000 according to some embodiments disclosed herein may include an MCU 2100, a memory 2200, an input / output I / F 2300, and a communication I / F 2400.

[0176] The MCU 2100 may be a processor that executes various programs (such as a battery voltage change analysis program, etc.) stored in the memory 2200. The MCU 2100 may be configured to process various data through these programs and perform Figure 1 the above functions of the battery management device 200 shown. According to some embodiments, the MCU 2100 may execute processing functions associated with the data management unit 210 and the controller 220 of the battery management device 200.

[0177] The memory 2200 may store various programs regarding the operation of the battery management device 200. In addition, the memory 2200 may store the operation data of the battery management device 200. According to some embodiments, the memory 2200 may perform storage, recording, and / or caching functions associated with the controller 220 and the memory 230 of the battery management device 200.

[0178] Although Figure 8 a single memory unit is shown, the computing system 2000 may also include one or more memory units. The memory 2200 may be a volatile memory or a non-volatile memory. As a volatile memory, the memory 2200 may be a random access memory (RAM), a dynamic RAM (DRAM), a static RAM (SRAM), etc. As a non-volatile memory, the memory 2200 may be a read-only memory (ROM), a programmable ROM (PROM), an electrically variable ROM (EAROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), a flash memory, etc. The above examples of the memory 2200 are merely examples and are not limited thereto.

[0179] The input / output I / F 2300 may provide an interface for sending and receiving data by connecting input devices such as a keyboard, a mouse, a touch screen, etc. (not shown) and output devices such as a display (not shown) to the MCU 2100.

[0180] The communication I / F 2400 may be configured to send various data to a server and receive various data from the server. The communication I / F 2400 may include various devices capable of supporting wired or wireless communication. For example, a program for resistance measurement and abnormal diagnosis of battery cells or various data may be sent to a separately provided external server and received from the separately provided external server through the communication I / F 2400.

[0181] The above description only illustrates the technical idea of the present disclosure, and those of ordinary skill in the art to which the present disclosure pertains may make various modifications and variations without departing from the present disclosure.

[0182] Therefore, the embodiments disclosed in the present disclosure are intended to describe rather than limit the present disclosure, and the scope of the present disclosure is not limited by these embodiments.

[0183] [Description of reference numerals]

[0184] 1000: Battery pack

[0185] 100: Battery module

[0186] 110: First battery cell

[0187] 120: Second battery cell

[0188] 130: Third battery cell

[0189] 140: Fourth battery cell

[0190] 200: Battery management device

[0191] 210: Data management unit

[0192] 220: Controller

[0193] 230: Memory

[0194] 300: Relay

[0195] 2000: Computing system

[0196] 2100: MCU

[0197] 2200: Memory

[0198] 2300: Input / output I / F

[0199] 2400: Communication I / F

[0200] t1: First balancing time

[0201] t2: Second balancing time

[0202] T0: Reference balancing time

[0203] T1: First reference time

[0204] T2: Second reference time

Claims

1. A battery management device, the battery management device comprising: One or more processors configured to: Compare the median of the cumulative balancing times of each battery cell included in a battery pack with a first reference time; Based on the comparison, determine whether the battery pack is abnormal, wherein when the median of the cumulative balancing times of each battery cell among the plurality of battery cells exceeds the first reference time, the battery pack is abnormal; Based on determining that the battery pack is abnormal, and based on determining that the cumulative balancing time of at least one abnormal battery cell is less than a second reference time, identify the at least one abnormal battery cell among the plurality of battery cells; and Output a signal to a target device, wherein the signal identifies the at least one abnormal battery cell.

2. The battery management device according to claim 1, wherein, The one or more processors are further configured to calculate the cumulative balancing time of each battery cell among the plurality of battery cells.

3. The battery management device according to claim 1, the battery management device further comprising a memory, Among them, The one or more processors are further configured to store the cumulative balancing time in the memory by accumulating the balancing times of each battery cell among the plurality of battery cells.

4. The battery management device according to claim 1, wherein, The one or more processors are further configured to: Calculate a first balancing time by dividing the capacity deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells; Calculate a second balancing time by multiplying the number of days of use of the battery pack by a value obtained by dividing the state of charge (SoC) deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells; And Calculate the first reference time by multiplying a first threshold by a reference balancing time obtained by adding the first balancing time and the second balancing time.

5. The battery management device according to claim 1, wherein, The one or more processors are further configured to: List the plurality of battery cells based on the cumulative balancing time and extract a plurality of battery cells having respective cumulative balancing times within a threshold rank; Calculate the standard deviation of the cumulative balancing time of each battery cell among the plurality of battery cells having respective cumulative balancing times within the threshold rank; And Calculate the second reference time by subtracting a value obtained by multiplying a second threshold by the standard deviation from the median.

6. A battery management method, the battery management method comprising the following steps: Retrieve from a memory the cumulative balancing time of each battery cell included in a battery pack; Determine the median of the cumulative balancing times of each battery cell among the plurality of battery cells; Determine whether the battery pack is abnormal by comparing the median with a first reference time; Based on determining that the median exceeds the first reference time, compare the cumulative balancing time of each battery cell among the plurality of battery cells with a second reference time; Based on the comparison with the second reference time, identify at least one abnormal battery cell among the plurality of battery cells; And Output a signal to a target device, where the signal identifies the at least one abnormal battery cell.

7. The battery management method according to claim 6, wherein, The step of determining the median of the cumulative balancing time includes: Recording the cumulative balancing time in the memory by cumulatively calculating the balancing time of each battery cell in the plurality of battery cells.

8. The battery management method according to claim 6, wherein, The step of determining whether the battery pack is abnormal includes: Calculating a first balancing time by dividing the capacity deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells; Calculating a second balancing time by multiplying the number of days of use of the battery pack by a value obtained by dividing the state of charge (SoC) deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells; and Calculating the first reference time by multiplying a first threshold by a reference balancing time obtained by adding the first balancing time and the second balancing time.

9. The battery management method according to claim 8, wherein, The step of determining whether the battery pack is abnormal includes: When the median exceeds the first reference time, determining the battery pack as an abnormal battery pack.

10. The battery management method according to claim 9, wherein, The step of identifying the at least one abnormal battery cell includes: Listing the plurality of battery cells based on the cumulative balancing time and extracting a plurality of battery cells within the threshold rank; Calculating the standard deviation of the cumulative balancing time of each battery cell in the plurality of battery cells within the threshold rank; and Calculating the second reference time by subtracting a value obtained by multiplying a second threshold by the standard deviation from the median.

11. The battery management method according to claim 10, wherein, The step of identifying the at least one abnormal battery cell includes: When the cumulative balancing time of a first battery cell in the plurality of battery cells is less than the second reference time, diagnosing the first battery cell as an abnormal battery cell.

12. A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform the following operations: Comparing the median of the cumulative balancing time of each battery cell included in the battery pack with a first reference time; Based on the comparison, it is determined whether the battery pack is abnormal, wherein, When the median of the cumulative balancing time of each battery cell in the plurality of battery cells exceeds the first reference time, the battery pack is abnormal; Based on determining that the battery pack is abnormal, identifying the at least one abnormal battery cell among the plurality of battery cells based on determining that the cumulative balancing time of the at least one abnormal battery cell is less than a second reference time; And Output a signal to a target device, where the signal identifies the at least one abnormal battery cell.

13. The non-transitory computer-readable storage medium according to claim 12, wherein, The instructions further cause the one or more processors to perform the following operations: Calculating the cumulative balancing time of each battery cell in the plurality of battery cells.

14. The non-transitory computer-readable storage medium according to claim 12, wherein, The instructions further cause the one or more processors to perform the following operations: Calculating a first balancing time by dividing the capacity deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells; Calculating a second balancing time by multiplying the number of days of use of the battery pack by a value obtained by dividing the state of charge (SoC) deviation of the plurality of battery cells by the balancing capacity of the plurality of battery cells; and calculate the first reference time by multiplying a first threshold by a reference balance time obtained by adding the first balance time and the second balance time.

15. The non-transitory computer-readable storage medium according to claim 14, wherein, The operation of determining whether the battery pack is abnormal includes: when the median exceeds the first reference time, determine the battery pack as an abnormal battery pack.

16. The non-transitory computer-readable storage medium according to claim 14, wherein, The instructions further cause the one or more processors to perform the following operations: list the plurality of battery cells based on the cumulative balance time and extract a plurality of battery cells having respective cumulative balance times within a threshold rank; calculate a standard deviation of the cumulative balance time of each battery cell among the plurality of battery cells having respective cumulative balance times within the threshold rank; and calculate the second reference time by subtracting a value obtained by multiplying a second threshold by the standard deviation from the median.

17. The non-transitory computer-readable storage medium according to claim 12, wherein, The operation of identifying the at least one abnormal battery cell includes: when the cumulative balance time of a first battery cell among the plurality of battery cells is less than the second reference time, diagnose the first battery cell as an abnormal battery cell.

18. The non-transitory computer-readable storage medium according to claim 12, wherein, The instructions further cause the one or more processors to perform the following operations: accumulate the balance time of each battery cell among the plurality of battery cells and record the cumulative balance time in a memory.

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