Battery management apparatus and method

Abstract

The present invention provides a battery management device and method capable of detecting abnormal battery cells more accurately and quickly by analyzing changes in capacity and self-discharge amount of battery cells. The battery management method according to the present embodiment may include: a step of generating a first classification result by classifying one or more battery cells exceeding a first threshold and a second threshold as battery cells with abnormal capacity through analysis of capacity changes for each battery cell; a step of generating a second classification result by classifying one or more battery cells exceeding a third threshold as battery cells with internal short circuits through analysis of self-discharge (SD) amount for one or more battery cells included in the first classification result; and a step of determining one or more battery cells included in the second classification result as battery cells with abnormal detected.

Description

Technology Field

[0001] The present invention relates to a battery management device and method. Background Technology

[0002] Battery packs can be configured in various forms, ranging from small electronic devices to electric vehicles. In particular, in high-voltage applications such as electric vehicles or large-scale energy storage systems, more than 100 battery cells are connected in series. In such battery packs, the capacity and self-discharge amount of each battery cell are used as important indicators to assess the health status of the battery.

[0003] Conventionally, abnormal battery cell detection has been performed based on the absolute change in battery cell capacity, the rate of change, or the magnitude of self-discharge; however, since these methods often fail to adequately consider the interactions between individual battery cells, there is a need for a more precise detection method.

[0004] The information described above disclosed in the background technology of this invention is intended only to enhance understanding of the background of the present invention and may therefore include information that does not constitute prior art. The problem to be solved

[0005] The problem that the present invention aims to solve is to provide a battery management device and method capable of detecting abnormal battery cells more accurately and quickly by analyzing changes in battery cell capacity and self-discharge amount.

[0006] However, the technical problems that the present invention aims to solve are not limited to those described above, and other unmentioned problems can be clearly understood by those skilled in the art from the description of the invention below. means of solving the problem

[0007] A battery management method according to one embodiment of the present invention is a battery management method performed by a processor of a battery management device, and may include: a step of generating a first classification result in which one or more battery cells exceeding a first threshold and a second threshold are classified as battery cells with abnormal capacity by analyzing a change in capacity for each battery cell included in a plurality of battery cells connected in series; a step of generating a second classification result in which one or more battery cells exceeding a third threshold are classified as battery cells with internal short circuits by analyzing a self-discharge amount (SD) for one or more battery cells included in the first classification result; and a step of determining one or more battery cells included in the second classification result as battery cells with abnormal detected.

[0008] A battery management device according to one embodiment of the present invention includes a processor and a memory that is operablely connected to the processor and stores at least one code executed by the processor. When the memory is executed through the processor, the processor may store a code that generates a primary classification result by analyzing the capacity change of each battery cell included in a plurality of battery cells connected in series, classifying one or more battery cells exceeding a first threshold and a second threshold as battery cells with abnormal capacity, generates a secondary classification result by analyzing the self-discharge (SD) of one or more battery cells included in the primary classification result, classifying one or more battery cells exceeding a third threshold as battery cells with internal short circuits, and causes one or more battery cells included in the secondary classification result to be determined as battery cells with abnormalities.

[0009] In addition to this, other methods for implementing the present invention, other systems, and computer-readable recording media storing a computer program for executing said methods may be further provided.

[0010] Other aspects, features, and advantages other than those described above will become clear from the following drawings, claims, and detailed description of the invention. Effects of the invention

[0011] According to the present invention, abnormal battery cells can be identified more accurately by comprehensively analyzing the capacity and self-discharge data of battery cells. This enables faster and more accurate identification of abnormal conditions in battery cells compared to existing methods, thereby contributing to enhancing the safety of battery packs and improving the overall efficiency and lifespan of the system.

[0012] Furthermore, accurately detecting early signs of anomalies can help reduce the costs and risks associated with failures and enhance user confidence. This approach can be integrated into battery management systems to effectively support battery pack operation and maintenance strategies.

[0013] However, the effects obtainable through the present invention are not limited to those described above, and other unmentioned technical effects will be clearly understood by those skilled in the art from the description of the invention below. Brief explanation of the drawing

[0014] The following drawings attached to this specification illustrate preferred embodiments of the present invention and serve to further enhance understanding of the technical concept of the present invention together with the detailed description of the invention provided below; therefore, the present invention should not be interpreted as being limited only to the matters described in such drawings. FIG. 1 illustrates the configuration of a battery pack including a battery management device according to one embodiment of the present invention. FIG. 2 is a graph illustrating the time of calculating the self-discharge amount and estimating the capacity of a battery cell according to one embodiment of the present invention. FIG. 3 is a flowchart illustrating a battery management method according to one embodiment of the present invention. FIG. 4 is a flowchart illustrating a method for generating a primary classification result among battery management methods according to one embodiment of the present invention. FIG. 5 is a flowchart illustrating a method for generating a secondary classification result among battery management methods according to one embodiment of the present invention. Specific details for implementing the invention

[0015] Preferred embodiments of the present invention will be described in detail below with reference to the attached drawings. Prior to this, terms and words used in this specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings. Instead, based on the principle that the inventor may appropriately define the concepts of terms to best describe his invention, they should be interpreted in a meaning and concept consistent with the technical spirit of the present invention. Therefore, it should be understood that the embodiments described in this specification and the configurations illustrated in the drawings are merely some of the most preferred embodiments of the present invention and do not represent all of the technical spirit of the present invention; thus, various equivalents and modifications that can replace them may exist at the time of filing this application. Furthermore, as used in this specification, "comprise" or "include" and / or "comprising" or "including" specify the presence of the mentioned features, numbers, steps, actions, parts, elements, and / or groups thereof, and do not exclude the presence or addition of one or more other features, numbers, actions, parts, elements, and / or groups. In addition, when describing embodiments of the present invention, "may" and "may be" may include "one or more embodiments of the present invention."

[0016] Additionally, to aid in understanding the invention, the attached drawings are not drawn to actual scale, and the dimensions of some components may be exaggerated. Furthermore, the same reference numerals may be assigned to identical components in different embodiments.

[0017] The statement that two subjects of comparison are "identical" means that they are "substantially identical." Therefore, substantial identity may include deviations considered low in the industry, for example, deviations within 5%. Additionally, the statement that a parameter is uniform in a given area may mean that it is uniform from an average perspective.

[0018] Although terms such as "first," "second," etc., are used to describe various components, it goes without saying that these components are not limited by these terms. These terms are used merely to distinguish one component from another, and unless specifically stated otherwise, the first component may also be the second component.

[0019] Throughout the specification, unless specifically stated otherwise, each component may be singular or plural.

[0020] The fact that any configuration is placed on the "upper (or lower)" of a component or on the "upper (or lower)" of a component may mean not only that any configuration is placed in contact with the upper (or lower) surface of said component, but also that another configuration may be interposed between said component and any configuration placed on (or below) said component.

[0021] Furthermore, where it is stated that one component is "connected," "coupled," or "connected" to another component, it should be understood that while said components may be directly connected or connected to each other, another component may be "interposed" between each component, or that each component may be "connected," "coupled," or "connected" through another component. Additionally, when it is stated that a part is electrically coupled with another part, this includes not only cases where they are directly connected but also cases where they are connected with another component in between.

[0022] Throughout the specification, "A and / or B" means A, B, or A and B unless specifically stated otherwise. That is, "and / or" includes any combination or any combination of the enumerated items. "C to D" means C or more and D or less, unless specifically stated otherwise.

[0023] FIG. 1 illustrates the configuration of a battery pack including a battery management device according to an embodiment of the present invention. Referring to FIG. 1, a battery pack (1) according to an embodiment of the present invention may include a battery module (100) including a plurality of battery cells (C) and a battery management system (BMS) (hereinafter referred to as BMS) (200) for controlling the charging and discharging operations of the battery module (100). In this embodiment, the BMS (200) may include a battery management device that performs the function of detecting abnormal battery cells.

[0024] A battery module (100) can be configured in a modular form by electrically connecting a plurality of battery cells (C) to provide high capacity and high output. When configuring the battery module (100), the battery cells (C) can be connected in parallel or in series. In applications requiring high voltage, such as electric vehicles (EVs) and energy storage systems (ESS), the battery cells (C) can be configured by mainly connecting them in series.

[0025] The battery cell (C) may include a secondary battery cell excluding a rechargeable lead-acid battery. For example, the battery cell (C) may include a nickel-cadmium battery cell, a nickel metal hydride battery (NiMH) cell, a lithium-ion battery cell, a lithium polymer battery cell, etc.

[0026] The BMS (200) can control the overall operation of the battery module (100). The BMS (200) is connected to the battery module (100) and can control at least one operation during the charging and discharging of the battery module (100).

[0027] The BMS (200) can perform overcharge protection, over-discharge protection, overcurrent protection, overvoltage protection, overheating protection, etc. to protect the battery module (100).

[0028] The BMS (200) monitors state information of a battery cell (C), including voltage, current, temperature, remaining power, lifespan, state of charging (SOC), state of health (SOH), etc., for each of the plurality of battery cells included in the battery module (100), and can control at least one operation during charging and discharging of the battery module (100) using the monitoring results.

[0029] The BMS (200) can perform cell balancing operations to balance the charge state between each battery cell (C). For example, the BMS (200) can perform cell balancing operations to discharge battery cells (C) with a relatively high charge state and charge battery cells (C) with a relatively low charge state.

[0030] The BMS (200) can monitor the capacity degradation of the battery cell (C) and detect the effects of various factors. These factors may include usage time, time elapsed since manufacturing, the magnitude of charging and discharging currents, temperature, etc. These factors can cause the capacity of the battery cell (C) to naturally decrease. Additionally, an internal short circuit may occur in the battery cell (C) due to external factors such as manufacturing defects or shock, in which case a sudden change may occur in the estimated capacity of the battery cell (C).

[0031] The BMS (200) can detect an abnormal battery cell (C) by analyzing two major phenomena that occur when an internal short circuit occurs. These phenomena may include an increase in charging capacity and an increase in self-discharge amount. During the analysis process, the BMS (200) compares the capacity change of each battery cell (C) with surrounding battery cells (C), and if the comparison result exceeds a predetermined threshold, it may suspect an internal short circuit. Additionally, the BMS (200) analyzes the self-discharge amount of each battery cell (C) during the idle period and compares the self-discharge amount with surrounding battery cells (C), and if the comparison result exceeds another predetermined threshold, it may determine that there is an internal short circuit.

[0032] Below, the operation of the BMS (200) for detecting abnormal battery cells (C) is described in detail.

[0033] The BMS (200) can monitor the self-discharge amount (self-SDischarge, natural discharge rate due to the internal resistance of each battery cell (C)) of each battery cell (C) during each idle period (see FIG. 2). The self-discharge amount can be calculated using voltage or capacity, etc. In one embodiment, the BMS (200) can measure the voltage of the battery cell (C) before the start of the idle period and after the idle period, and calculate the self-discharge amount through the voltage difference. The BMS (200) can calculate the self-discharge amount (SD) for each of the battery cells (C) and store this value in memory (211). The self-discharge amount stored in memory (211) is referenced when an abnormal battery cell (C) is detected, and the previously stored self-discharge amount is SD n-1 As, the currently calculated self-discharge amount is SD n It can be named as.

[0034] The BMS (200) is the current capacity (Q) of each battery cell (C) connected in series. n ) can be estimated. The BMS (200) can estimate the current capacity (Q) of the battery cell (C) based on the voltage and current of the battery cell (C). n) can be estimated. The BMS (200) can estimate the previous capacity (Q) of each battery cell (C) connected in series. n-1 The estimation result can be stored in memory (211).

[0035] FIG. 2 is a graph illustrating the timing of the self-discharge amount calculation and capacity estimation of a battery cell according to an embodiment of the present invention. Referring to FIG. 2, the BMS (200) can perform the self-discharge amount calculation and capacity estimation of the battery cell (C) at various times according to a software algorithm. For example, the BMS (200) can perform the self-discharge amount calculation and capacity estimation of the battery cell (C) during a rest period after charging. For another example, the BMS (200) can perform the self-discharge amount calculation and capacity estimation of the battery cell (C) during a rest period after discharging. Since the BMS (200) can apply a consistent detection method regardless of the calculation method and timing, the state of the battery cell can be consistently evaluated under various conditions.

[0036] The BMS (200) can calculate the change in capacity of each battery cell (C). The BMS (200) can calculate the change in capacity by measuring the difference between the capacity before charging and the capacity after charging, or by measuring the difference between the capacity before discharging and the capacity after discharging. In this case, the BMS (200) can exclude the battery cell (C) with the largest change in capacity and the battery cell (C) with the smallest change in capacity. This may be to prevent the battery cell (C) exhibiting extreme changes from distorting the average of the entire data.

[0037] The BMS (200) uses the remaining battery cells (C) excluding the excluded battery cells (C) to obtain the average value of the capacity change (Q davg It can calculate the average value of capacity change (Q davg ) can be represented as a positive value if the capacity increases and a negative value if it decreases. Average value of capacity change (Q davg) can reflect changes in expected capacity due to degradation or changes in operating environment that may occur in the battery cell (C).

[0038] In this embodiment, the average value of the capacity change (Q davg ) may be calculated as the capacity change rate of each battery cell (C). The BMS (200) can derive the actual capacity change amount of the battery cell (C) by multiplying the calculated capacity change rate by the current capacity of each battery cell (C).

[0039] The BMS (200) is the expected capacity (Q) of each battery cell (C). ex ) can be calculated. The BMS (200) can calculate the previous capacity (Q) for each battery cell (C). n-1 ) and average value of capacity change (Q davg The sum of ) for each battery cell (C) is the expected capacity (Q ex =Q n-1 +Q davg It can be calculated as ).

[0040] The BMS (200) has a current capacity (Q) for each battery cell (C). n ) and, average value of capacity change (Q davg ) and the expected capacity (Q) for each battery cell ex One or more battery cells (C) satisfying the first pre-set condition can be determined as battery cells (C) with a capacity greater than or equal to that of the first pre-set condition.

[0041] Specifically, to determine the battery cell (C) with the capacity exceeding a certain limit, the BMS (200) determines the current capacity (Q) for each battery cell (C). n ) and expected capacity (Q) for each battery cell (C) ex A first-1 condition can be evaluated to determine whether the difference of ) exceeds a first threshold value (C1, e.g., 1%). In this embodiment, the first threshold value (C1) may be changed differently depending on the capacity of the battery cell (C).

[0042] The BMS (200) has a current capacity (Q) for each battery cell (C). n) and previous capacity (Q) for each battery cell n-1 A first-2 condition can be evaluated to determine whether the difference of ) exceeds a second threshold (C2, e.g., 0.5%). In this embodiment, the second threshold (C2) may be changed differently depending on the capacity of the battery cell (C).

[0043] The BMS (200) can determine one or more battery cells (C) satisfying conditions 1-1 and 1-2 as battery cells with a capacity greater than or equal to the capacity. In this embodiment, satisfying condition 1-1 means the current capacity (Q) for each battery cell (C). n ) and expected capacity (Q) for each battery cell (C) ex It may include the difference of ) exceeding a first threshold value (C1). In the present embodiment, satisfying the first-2 condition means the current capacity (Q) for each battery cell (C). n ) and previous capacity (Q) for each battery cell n-1 It may include the difference of ) exceeding a second threshold (C2).

[0044] In this embodiment, the expected capacity (Q ex ) is a value that estimates the capacity the battery cell (C) should retain under normal usage conditions, and the current capacity (Q n ) and expected capacity (Q ex If the difference is large, it may suggest that the battery cell (C) has been overcharged, over-discharged, or has internal damage. Additionally, if the difference between the current capacity (Qn) and the previous capacity (Qn-1) of the battery cell (C) is large, it may suggest that the battery cell (C) has recently been exposed to an abnormal environment or has internal defects. By determining one or more battery cells (C) that satisfy conditions 1-1 and 1-2 as battery cells with excess capacity, the BMS (200) can detect and respond to performance degradation or potential problems of the battery pack (1) at an early stage.

[0045] As an optional embodiment, the BMS (200) may determine the battery cells (C) with a capacity greater than or equal to the capacity using a percentage rather than the absolute capacity value as described above. To this end, the BMS (200) determines the current capacity (Q) for each battery cell (C). n ) and expected capacity (Q) for each battery cell (C) ex The difference in ) for each battery cell (C) is the expected capacity (Q). ex A 1-1 condition can be evaluated to determine whether the result of dividing by ) exceeds a 1 threshold value (C1). The BMS (200) can evaluate the current capacity (Q) for each battery cell (C). n ) and previous capacity (Q) for each battery cell n-1 The difference in ) for each battery cell's previous capacity (Q n-1 A first-2 condition can be evaluated to determine whether the result of dividing by ) exceeds a second threshold value (C2). The BMS (200) can determine one or more battery cells (C) that satisfy the first-1 condition and the first-2 condition as battery cells with a capacity greater than or equal to the capacity. In this embodiment, satisfying the first-1 condition means the current capacity (Q) for each battery cell (C). n ) and expected capacity (Q) for each battery cell (C) ex The difference in ) for each battery cell (C) is the expected capacity (Q). ex It may include the result of dividing by ) exceeding the first threshold value (C1). In the present embodiment, satisfying the first-2 condition means the current capacity (Q) for each battery cell (C). n ) and previous capacity (Q) for each battery cell n-1 The difference in ) for each battery cell's previous capacity (Q n-1 The result of dividing by ) may include exceeding the second threshold (C2).

[0046] For a battery cell (C) determined to have a capacity greater than or equal to the capacity, the BMS (200) uses the self-discharge amount stored in the memory (211) to determine the self-discharge amount (SD) and the average self-discharge amount (SD). avgThe difference of ) can be calculated. In this embodiment, the self-discharge amount of the battery cell (C) determined to be greater than the capacity stored in the memory (211) is the previous self-discharge amount (SD n-1 ) and current self-discharge amount (SD n It may be at least one of ). In addition, the BMS (200) has an average self-discharge amount (SD) for the remaining battery cells (C) after excluding the battery cells (C) with a capacity exceeding the limit from the plurality of battery cells (C) connected in series. avg ) can be produced.

[0047] The BMS (200) determines the self-discharge amount (SD) of the battery cell (C) that is greater than the capacity and the average self-discharge amount (SD). avg ) can determine one or more battery cells (C) that satisfy the second set condition as internal short-circuit battery cells (C).

[0048] Specifically, to determine the internal short circuit battery cell (C), the BMS (200) determines the previous self-discharge amount (SD) of the battery cell (C) determined to be greater than the capacity. n-1 ) and average self-discharge amount (SD avg A 2-1 condition can be evaluated to determine whether the difference of ) exceeds a third threshold (C3, e.g., 1%). In this embodiment, the third threshold (C3) may be changed differently depending on the capacity of the battery cell (C).

[0049] The BMS (200) determines the current self-discharge amount (SD) of the battery cell (C) that is greater than the capacity. n ) and average self-discharge amount (SD avg A second-2 condition can be evaluated to determine whether the difference of ) exceeds a third threshold (C3).

[0050] The BMS (200) can determine a battery cell (C) satisfying at least one of condition 2-1 and condition 2-2 as an internal short-circuit battery cell (C). In this embodiment, satisfying condition 2-1 means the previous self-discharge amount (SD) of the battery cell (C) determined to be greater than or equal to the capacity. n-1 ) and average self-discharge amount (SD avg It may include the difference exceeding a third threshold value (C3). In this embodiment, satisfying the 2-2 condition means the current self-discharge amount (SD) of the battery cell (C) determined to be greater than or equal to the capacity. n ) and average self-discharge amount (SD avg It may include the difference of ) exceeding a third threshold (C3).

[0051] If an internal short circuit occurs, an abnormal electrical path may be formed inside the battery cell (C). This path significantly lowers the internal resistance of the battery cell (C), which can rapidly increase the self-discharge rate. The self-discharge amount (SD) reflects the self-discharge amount in the normal state before the internal short circuit occurs, and the average self-discharge amount (SDavg) may represent the average discharge state of normal battery cells (C). However, if an internal short circuit occurs, the self-discharge amount (SD) of the battery cell (C) becomes abnormally high compared to normal battery cells (C), and as a result, the difference may exceed the WP3 threshold.

[0052] The BMS (200) has a self-discharge amount (SD) and an average self-discharge amount (SD avg If the difference of ) does not exceed the third threshold value (C3), the next self-discharge amount (e.g., SD n+1 Measure the average self-discharge amount (SD). avg The difference from ) can be calculated. The BMS (200) can calculate the next self-discharge amount (e.g., SD n+1 Measure the average self-discharge amount (SD). avgIf the difference from ) exceeds the third threshold (C3), the battery cell (C) can be determined to be a battery cell (C) that has an internal short circuit. If this difference does not exceed the third threshold (C3), the BMS (200) can declassify the battery cell (C) as having an abnormal capacity.

[0053] The BMS (200) can classify one or more battery cells (C) that have a capacity abnormality among a plurality of battery cells (C) connected in series as a primary class, classify one or more battery cells (C) that have an internal short circuit among the one or more battery cells (C) classified as a primary class, and determine one or more battery cells (C) classified as a secondary class as an abnormal detection battery cell (C). That is, the BMS (200) can determine a battery cell (C) that has a capacity abnormality and an internal short circuit among a plurality of battery cells (C) connected in series as an abnormal detection battery cell (C).

[0054] In this embodiment, the BMS (200) for detecting an abnormal battery cell (C) may include a processor (210) and a memory (211).

[0055] The processor (210) can perform the operation of the BMS (200) described above. The processor (210) can process instructions of a computer program by performing basic arithmetic, logic, and input / output operations. Here, instructions may be provided from memory (211).

[0056] For example, the processor (210) may be implemented as an array of multiple logic gates, or as a combination of a general-purpose microprocessor and memory storing a program that can be executed on the microprocessor. For example, the processor may include a general-purpose processor, a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a controller, a microcontroller, a state machine, etc. In some environments, the processor (210) may include an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), etc. For example, the processor (210) may refer to a combination of processing devices such as a combination of a digital signal processor (DSP) and a microprocessor, a combination of multiple microprocessors, a combination of one or more microprocessors combined with a digital signal processor (DSP) core, or any other combination of such configurations.

[0057] The memory (211) is operably connected to the processor (210) and can store at least one code in connection with an operation performed by the processor (210). In the present embodiment, the memory (211) may be provided inside the processor (210) or outside the processor (210).

[0058] Additionally, the memory (211) can perform the function of temporarily or permanently storing data processed by the processor (210). Here, the memory (211) may include a magnetic storage medium or a flash storage medium, but the scope of the present invention is not limited thereto. Such memory (211) may include internal memory and / or external memory, and may include volatile memory such as DRAM, SRAM, or SDRAM, non-volatile memory such as OTPROM, PROM, EPROM, EEPROM, mask ROM, flash ROM, NAND flash memory, or NOR flash memory, flash drives such as SSD, CF card, SD card, Micro-SD card, Mini-SD card, xD card, or Memory Stick, or storage devices such as HDD.

[0059] FIG. 3 is a flowchart illustrating a battery management method according to an embodiment of the present invention. In the following description, parts that overlap with the description of FIG. 1 and FIG. 2 will be omitted. The battery management method according to the present embodiment will be described under the assumption that the BMS (200) performs the task at the processor (210) with the help of peripheral components.

[0060] Referring to FIG. 3, in step S310, the processor (210) can generate a primary classification result by analyzing the capacity change of each battery cell (C) included in a plurality of battery cells (C) connected in series, and classifying one or more battery cells (C) that exceed a first threshold value (C1) and a second threshold value (C2) as battery cells (C) with excess capacity.

[0061] In step S320, the processor (210) can generate a second classification result by analyzing the self-discharge amount (SD) of one or more battery cells (C) included in the first classification result, and classifying one or more battery cells (C) that exceed the third threshold (C3) as battery cells (C) that have an internal short circuit.

[0062] In step S330, the processor (210) can determine one or more battery cells (C) included in the secondary classification result as abnormal detection battery cells (C).

[0063] In this embodiment, prior to generating a second classification result, the processor (210) can calculate the self-discharge amount (SD) for each battery cell (C) included in a plurality of battery cells (C) connected in series. Here, "prior to generating a second classification result" may include either "prior to generating a first classification result" or "after generating a first classification result."

[0064] FIG. 4 is a flowchart illustrating a method for generating a primary classification result among battery management methods according to an embodiment of the present invention. In the following description, parts that overlap with the description of FIG. 1 to 3 will be omitted.

[0065] Referring to FIG. 4, in step S311, the processor (210) [calculates] the current capacity (Q) of the battery cell (C). n ) is updated, and the previous capacity (Q) of the corresponding battery cell (C) n-1 It can be determined whether ) is stored in memory (211).

[0066] In step S312, the processor (210) determines the current capacity (Q) of the battery cell (C). n ) is updated, and the previous capacity (Q) of the corresponding battery cell (C) n-1 If this is stored in memory (211), a primary classification can be initialized to classify whether the capacity of the battery cell (C) is abnormal.

[0067] In step S313, the processor (210) determines the average value of the capacity change (Q davg ) and expected capacity (Q ex ) can be produced.

[0068] In step S314, the processor (210) determines the current capacity (Q) for each battery cell (C). n ) and expected capacity (Q) for each battery cell (C) ex The difference ) exceeds the first threshold value (C1), and the current capacity (Q) for each battery cell (C) n ) and previous capacity (Q) for each battery cell n-1 It can determine whether the difference of ) exceeds the second threshold (C2).

[0069] In step S315, the processor (210) determines the current capacity (Q) for each battery cell (C). n ) and expected capacity (Q) for each battery cell (C) ex The difference ) exceeds the first threshold value (C1), and the current capacity (Q) for each battery cell (C) n ) and previous capacity (Q) for each battery cell n-1 If the difference of ) exceeds the second threshold value (C2), the battery cell (C) can be determined as a battery cell (C) with a capacity greater than or equal to the capacity.

[0070] FIG. 5 is a flowchart illustrating a method for generating a secondary classification result among battery management methods according to an embodiment of the present invention. In the following description, parts that overlap with the description of FIG. 1 to FIG. 4 will be omitted.

[0071] Referring to FIG. 5, in step S321, the processor (210) can determine whether there is a battery cell (C) with a capacity greater than 1.

[0072] In step S322, the processor (210), as there is a battery cell (C) with an excess capacity, determines the previous self-discharge amount (SD) for the battery cell (C) with an excess capacity. n-1It can determine whether ) is stored in memory (211).

[0073] In step S323, the processor (210) determines the previous self-discharge amount (SD) for the battery cell (C) with a capacity greater than 1. n-1 As ) is stored in memory (211), the previous self-discharge amount (SD) for the battery cell (C) with a capacity greater than ) is stored in memory (211). n-1 ) and average self-discharge amount (SD avg It can be determined whether the difference of ) exceeds the third threshold value (C3). In this embodiment, the average self-discharge amount (SD avg ) may be calculated for the remaining battery cells (C) after excluding the battery cells (C) with a capacity greater than 60 from the multiple battery cells (C) connected in series.

[0074] In step S324, the processor (210) determines the previous self-discharge amount (SD) for the battery cell (C) with a capacity greater than 1. n-1 ) and average self-discharge amount (SD avg As the difference of ) exceeds the third threshold (C3), the battery cell (C) can be determined as a battery cell (C) that has an internal short circuit.

[0075] In step S325, the previous self-discharge amount (SD) for the battery cell (C) with excess capacity n-1 ) and average self-discharge amount (SD avg As the difference of ) does not exceed the third threshold (C3), the processor (210) [determines] the current self-discharge amount (SD) for the battery cell (C) with excess capacity. n It can determine whether ) is stored in memory (211).

[0076] In step S326, the processor (210) determines the current self-discharge amount (SD) for the battery cell (C) with a capacity greater than 100%. n As ) is stored in memory (211), the current self-discharge amount (SD) for the battery cell (C) with a capacity greater than ) is stored in memory (211). n ) and average self-discharge amount (SD avgIt can determine whether the difference of ) exceeds a third threshold (C3). The processor (210) determines whether the current self-discharge amount (SD) for the battery cell (C) with excess capacity is greater than the current self-discharge amount (SD). n ) and average self-discharge amount (SD avg As the difference of ) exceeds the third threshold (C3), the battery cell (C) can be determined as a battery cell (C) that has an internal short circuit.

[0077] In step S327, the processor (210) determines the current self-discharge amount (SD) for the battery cell (C) with a capacity greater than 100%. n ) and average self-discharge amount (SD avg As the difference of ) does not exceed the third threshold (C3), a secondary classification can be initialized to classify whether there is an internal short circuit for the battery cell (C) with an overcapacity.

[0078] Although the present invention has been described above by limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical spirit of the present invention and the equivalent scope of the claims described below by those skilled in the art to which the present invention belongs. Explanation of the symbols

[0079] 1: Battery pack 100: Battery module 200: BMS 210: Processor 211: Memory

Claims

Claim 1 A battery management method performed by a processor of a battery management device, comprising: a step of generating a first classification result in which one or more battery cells exceeding a first threshold and a second threshold are classified as battery cells with abnormal capacity by analyzing a change in capacity for each battery cell included in a plurality of battery cells connected in series; a step of generating a second classification result in which one or more battery cells exceeding a third threshold are classified as battery cells with internal short circuits by analyzing a self-discharge amount (SD) for one or more battery cells included in the first classification result; and a step of determining one or more battery cells included in the second classification result as battery cells with abnormal detected. Claim 2 A battery management method according to claim 1, further comprising, prior to the step of generating the secondary classification result, a step of calculating the self-discharge amount (SD) for each battery cell included in the plurality of battery cells connected in series. Claim 3 In claim 1, the step of generating the primary classification result comprises the current capacity (Q) of each battery cell included in the plurality of battery cells connected in series. n A step of estimating ); an average value of capacity change (Q) for a plurality of battery cells connected in series. davg A step of calculating the expected capacity (Q) for each of the battery cells; ex A step of calculating ) and the current capacity (Q) for each of the battery cells; and n ) and the average value of the above capacity change (Q davg ) and the expected capacity (Q) for each of the above battery cells ex A battery management method comprising the step of determining one or more battery cells satisfying a first predetermined condition as battery cells with a capacity greater than or equal to that of a battery cell. Claim 4 In claim 3, the average value of the capacity change (Q davg The step of calculating ) comprises: excluding the battery cell with the largest capacity change value and the battery cell with the smallest capacity change value from the plurality of battery cells connected in series; and the average capacity change value (Q) for the remaining battery cells excluding the battery cell with the largest capacity change value and the battery cell with the smallest capacity change value. davg A battery management method comprising the step of calculating ). Claim 5 In claim 3, the above expected capacity (Q ex The step of calculating ) is the previous capacity (Q) for each of the battery cells. n-1 ) and the average value of the above capacity change (Q davg The sum of ) for each of the above battery cells is the expected capacity (Q ex A battery management method including a step of calculating as ). Claim 6 In claim 3, the step of determining a battery cell with a capacity greater than or equal to the above is the current capacity (Q) for each of the above battery cells. n ) and the expected capacity (Q) for each of the above battery cells ex A step of evaluating a 1-1 condition for determining whether the difference of ) exceeds the first threshold value; current capacity (Q) for each of the battery cells n ) and the previous capacity (Q) for each of the above battery cells n-1 A battery management method comprising: a step of evaluating a first-2 condition for determining whether the difference of ) exceeds a second threshold value; and a step of determining one or more battery cells satisfying the first-1 condition and the first-2 condition as battery cells with a capacity greater than or equal to the capacity. Claim 7 In claim 1, the step of generating the secondary classification result comprises the average self-discharge amount (SD) for each battery cell included in the plurality of battery cells connected in series. avg A step of calculating ); and the self-discharge amount (SD) and average self-discharge amount (SD) of the battery cells included in the first classification result. avg A battery management method comprising the step of determining one or more battery cells satisfying a second pre-set condition as internal short-circuit battery cells. Claim 8 In claim 7, the above average self-discharge amount (SD avg The step of calculating ) comprises: a step of excluding one or more battery cells included in the first classification result from the plurality of battery cells connected in series; and for the remaining battery cells excluding one or more battery cells included in the first classification result from the plurality of battery cells connected in series, an average self-discharge amount (SD avg A battery management method comprising the step of calculating ). Claim 9 In claim 7, the step of determining the internal short-circuit battery cell comprises the previous self-discharge amount (SD) of the battery cell included in the primary classification result. n-1 ) and the above average self-discharge amount (SD avg A step of evaluating a 2-1 condition for determining whether the difference of ) exceeds the third threshold; the current self-discharge amount (SD) of the battery cell included in the first classification result. n ) and the above average self-discharge amount (SD avg A battery management method comprising: a step of evaluating a second-2 condition for determining whether the difference of ) exceeds a third threshold value; and a step of determining a battery cell satisfying at least one of the second-1 condition and the second-2 condition as an internal short-circuit battery cell. Claim 10 A computer-readable recording medium storing a computer program for executing the method of claim 1 using a computer. Claim 11 A battery management device comprising: a processor; and a memory operably connected to the processor and storing at least one code executed by the processor, wherein the memory stores a code that, when executed through the processor, causes the processor to generate a primary classification result by analyzing a change in capacity for each battery cell included in a plurality of battery cells connected in series, classifying one or more battery cells exceeding a first threshold and a second threshold as battery cells with abnormal capacity, generates a secondary classification result by analyzing a self-discharge amount (SD) for one or more battery cells included in the primary classification result, classifying one or more battery cells exceeding a third threshold as battery cells with internal short circuits, and stores a code that causes one or more battery cells included in the secondary classification result to be determined as battery cells with abnormalities. Claim 12 A battery management device according to claim 11, wherein the memory further stores a code that causes the processor to calculate the self-discharge amount (SD) for each battery cell included in the plurality of battery cells connected in series before generating the secondary classification result. Claim 13 In claim 11, the memory enables the processor to generate the primary classification result, for each battery cell included in the plurality of battery cells connected in series, the current capacity (Q) of each battery cell. n Estimate ) and the average value of the capacity change (Q) for the plurality of battery cells connected in series. davg Calculate the expected capacity (Q) for each of the above battery cells, and ex Calculate the current capacity (Q) for each of the above battery cells, and n ) and the average value of the above capacity change (Q davg ) and the expected capacity (Q) for each of the above battery cells ex A battery management device that stores a code causing one or more battery cells satisfying a first preset condition to be determined as battery cells with a capacity greater than or equal to that of the battery cells. Claim 14 In claim 13, the memory enables the processor to... the average value of the capacity change (Q davg In calculating ), the battery cell with the largest capacity change value and the battery cell with the smallest capacity change value are excluded from the plurality of battery cells connected in series, and the average capacity change value (Q) for the remaining battery cells excluding the battery cell with the largest capacity change value and the battery cell with the smallest capacity change value is calculated. davg A battery management device that stores code causing ) to be produced. Claim 15 In claim 13, the memory enables the processor to, the expected capacity (Q ex In calculating the previous capacity (Q) for each of the above battery cells, n-1 ) and the average value of the above capacity change (Q davg The sum of ) for each of the above battery cells is the expected capacity (Q ex A battery management device that stores code causing to produce ). Claim 16 In claim 13, the memory enables the processor to determine the current capacity (Q) for each of the battery cells when determining the battery cell with a capacity greater than or equal to the above capacity. n ) and the expected capacity (Q) for each of the above battery cells ex Evaluating a 1-1 condition for determining whether the difference of ) exceeds the first threshold value, and the current capacity (Q) for each of the battery cells n ) and the previous capacity (Q) for each of the above battery cells n-1 A battery management device that evaluates a first-2 condition for determining whether the difference of ) exceeds the second threshold value, and stores a code that causes one or more battery cells satisfying the first-1 condition and the first-2 condition to be determined as battery cells with a capacity greater than or equal to the capacity. Claim 17 In claim 11, the memory enables the processor to generate the secondary classification result, the average self-discharge amount (SD) for each battery cell included in the plurality of battery cells connected in series. avg Calculate ), and the self-discharge amount (SD) and average self-discharge amount (SD) of the battery cells included in the above primary classification result. avg A battery management device that stores a code causing one or more battery cells satisfying a second preset condition to be determined as internally short-circuited battery cells. Claim 18 In claim 17, the memory enables the processor to, the average self-discharge amount (SD avg In calculating ), one or more battery cells included in the first classification result are excluded from the plurality of battery cells connected in series, and for the remaining battery cells excluding one or more battery cells included in the first classification result from the plurality of battery cells connected in series, the average self-discharge amount (SD) avg A battery management device that stores code causing ) to be produced. Claim 19 In claim 17, the memory enables the processor, in determining the internal short-circuit battery cell, the previous self-discharge amount (SD) of the battery cell included in the primary classification result. n-1 ) and the above average self-discharge amount (SD avg Evaluate the 2-1 condition for determining whether the difference of ) exceeds the 3rd threshold value, and the current self-discharge amount (SD) of the battery cell included in the 1st classification result. n ) and the above average self-discharge amount (SD avg A battery management device that evaluates a 2-2 condition for determining whether the difference of ) exceeds the 3rd threshold value, and stores a code that causes a battery cell satisfying at least one of the 2-1 condition and the 2-2 condition to be determined as an internally short-circuited battery cell.

Images