Battery management apparatus and operation method thereof

Abstract

A battery management apparatus according to one embodiment of the present document may comprise: a voltage acquisition unit for acquiring voltage data of each of a plurality of battery cells over time; and a controller, which calculates a first value related to the voltage behavior of each of the plurality of battery cells in each of a plurality of cycles on the basis of the voltage data acquired during the plurality of cycles, calculates a second value through normalization of first values in each of the plurality of cycles, calculates time-series data of the second value of each of the plurality of battery cells for the plurality of cycles, and analyzes the trend of pieces of time-series data of the plurality of battery cells so as to detect an abnormal battery cell.

Description

Battery management device and its operating method

[0001] Cross-citation with related applications

[0002] This application claims the benefit of priority from Republic of Korea Patent Application No. 10-2024-0021752, filed February 15, 2024, the entire contents of which are incorporated herein by reference.

[0003] Technology field

[0004] The embodiments disclosed in this document relate to a battery management device and a method of operating the same.

[0005] Recently, research and development on secondary batteries has been actively underway. Here, secondary batteries are defined as rechargeable and dischargeable batteries, encompassing both conventional Ni / Cd and Ni / MH batteries, as well as more recent lithium-ion batteries. Recently, their use has expanded to include power sources for electric vehicles, attracting attention as a next-generation energy storage medium.

[0006] Electric vehicles receive external electricity to charge battery cells and modules, which are then discharged to power the motor. During production and use, battery cells and modules undergo internal deformation and transformation through various charging and discharging cycles, altering their physical and chemical properties. This degradation and deterioration of batteries necessitates the development of technologies to manage the operation of battery cells and modules.

[0007] Charge-discharge tests can be performed on batteries for various purposes, such as performance diagnosis and condition analysis. For example, a test voltage can be applied to the battery, and a test voltage can be measured in response to the test voltage. However, if conventional techniques for diagnosing batteries based on momentary voltage fluctuations are applied to long-term voltage fluctuations, the accuracy of diagnosing abnormal batteries can be reduced. Therefore, a technology capable of analyzing long-term voltage fluctuations and detecting voltage fluctuations is needed.

[0008] One purpose of the embodiments disclosed in this document is to provide a battery management device and an operating method thereof capable of managing an abnormal battery cell based on voltage data obtained from a plurality of battery cells included in a battery pack.

[0009] One object of the embodiments disclosed in this document is to provide a battery management device and an operating method thereof based on a data processing algorithm for analyzing long-term behavior of voltage data.

[0010] The technical problems of the embodiments disclosed in this document are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the descriptions below.

[0011] A battery management device according to one embodiment of the present document may include a voltage acquisition unit that acquires voltage data of each of a plurality of battery cells over time; and a controller that calculates a first value regarding voltage behavior of each of the plurality of battery cells in each of the plurality of cycles based on the voltage data acquired during a plurality of cycles, calculates a second value through normalization of the first values ​​in each of the plurality of cycles, calculates time series data of the second values ​​of each of the plurality of battery cells for the plurality of cycles, and trend-analyzes the time series data of the plurality of battery cells to detect an abnormal battery cell.

[0012] According to an embodiment, each of the plurality of cycles may include a period between a charging start time and a discharging start time of the plurality of battery cells.

[0013] According to an embodiment, the controller may calculate a first vector, a second vector, and a third vector representing voltage behavior between two different points in time among a charging start time, a charging end time, and a discharging start time of each of the plurality of battery cells, and may preprocess the first vector, the second vector, and the third vector to calculate the first value, which is a scalar value.

[0014] According to an embodiment, the start point of the first vector may be the charging start point and the end point may be the charging end point, the start point of the second vector may be the charging start point and the end point may be the discharging start point, and the start point of the third vector may be the charging end point and the end point may be the discharging start point.

[0015] According to an embodiment, the controller may project the first vector onto the second vector to produce a projection vector, produce a perpendicular vector which is a difference between the first vector and the projection vector, and produce the first value which is a magnitude of a vector produced by projecting the third vector onto the perpendicular vector.

[0016] According to an embodiment, the controller may normalize the first value based on an average and a standard deviation of the first values ​​in each of the plurality of cycles to produce the second value.

[0017] According to an embodiment, the controller may decompose the time series data of the second values ​​of each of the plurality of battery cells into a trend component and a remain component based on at least one of a Hodrick-Prescott (HP) filter and a Baxter-King (BK) filter.

[0018] According to an embodiment, the controller can detect the abnormal battery cell based on the size of the remaining component of each of the plurality of battery cells.

[0019] According to an embodiment, the controller may compare the size of the remaining component with a first threshold value, and if the size of the remaining component exceeds the first threshold value, the controller may detect the battery cell corresponding to the remaining component as an abnormal battery cell.

[0020] An operating method of a battery management device according to one embodiment of the present document may include: acquiring voltage data of each of a plurality of battery cells over time; calculating a first value regarding voltage behavior of each of the plurality of battery cells in each of the plurality of cycles based on the voltage data acquired during each of the plurality of cycles; calculating a second value by normalizing the first values ​​in each of the plurality of cycles; calculating time series data of the second values ​​of each of the plurality of battery cells for each of the plurality of cycles; and performing trend analysis on the time series data of the plurality of battery cells to detect an abnormal battery cell.

[0021] According to an embodiment, each of the plurality of cycles may include a period between a charging start time and a discharging start time of the plurality of battery cells.

[0022] According to an embodiment, the step of calculating the first value may include the step of calculating a first vector, a second vector, and a third vector representing voltage behavior between two different points in time among a charging start time, a charging end time, and a discharging start time of each of the plurality of battery cells; and the step of preprocessing the first vector, the second vector, and the third vector to calculate the first value, which is a scalar value.

[0023] According to an embodiment, the start point of the first vector may be the charging start point and the end point may be the charging end point, the start point of the second vector may be the charging start point and the end point may be the discharging start point, and the start point of the third vector may be the charging end point and the end point may be the discharging start point.

[0024] According to an embodiment, the preprocessing may include: a step of projecting the first vector onto the second vector to produce a projection vector; a step of producing a perpendicular vector which is a difference between the first vector and the projection vector; and a step of producing the first value which is a magnitude of a vector produced by projecting the third vector onto the perpendicular vector.

[0025] According to an embodiment, the step of calculating the second value may calculate the second value by normalizing the first value based on the average and standard deviation of the first values ​​in each of the plurality of cycles.

[0026] According to an embodiment, trend analysis of the time series data of the plurality of battery cells may include decomposing the time series data of the second value of each of the plurality of battery cells into a trend component and a remain component based on at least one of a Hodrick-Prescott (HP) filter and a Baxter-King (BK) filter.

[0027] According to an embodiment, the step of detecting the abnormal battery cell may detect the abnormal battery cell based on the size of the remaining component of each of the plurality of battery cells.

[0028] According to an embodiment, the step of detecting the abnormal battery cell may include the step of comparing the size of the remaining component with a first threshold value, and detecting the battery cell corresponding to the remaining component as an abnormal battery cell if the size of the remaining component exceeds the first threshold value.

[0029] The battery management device and its operating method disclosed in this document can manage abnormal battery cells based on voltage data obtained from a plurality of battery cells included in a battery pack.

[0030] In addition, various effects may be provided, either directly or indirectly, through this document.

[0031] FIG. 1 is a drawing showing a battery pack according to one embodiment disclosed in this document.

[0032] FIG. 2 is a block diagram showing a battery management device according to one embodiment disclosed in this document.

[0033] FIG. 3 is a graph showing the voltage of a battery cell according to one embodiment disclosed in this document.

[0034] FIG. 4 is a graph showing a process for calculating a first value according to one embodiment disclosed in this document.

[0035] FIG. 5 is a graph showing time series data of a second value according to one embodiment disclosed in this document.

[0036] FIG. 6 is a graph showing the results of trend analysis of time series data of a second value according to one embodiment disclosed in this document.

[0037] FIG. 7 is a flowchart showing the operation of a battery management device according to one embodiment disclosed in this document.

[0038] FIG. 8 is a block diagram showing the hardware configuration of a computing system for performing an operating method of a battery management device according to one embodiment disclosed in this document.

[0039] Hereinafter, various embodiments of the present invention will be described with reference to the accompanying drawings. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that the present invention encompasses various modifications, equivalents, and / or alternatives of the embodiments.

[0040] The various embodiments and terminology used in this document are not intended to limit the technical features described in this document to specific embodiments, but should be understood to encompass various modifications, equivalents, or alternatives of the embodiments. In connection with the description of the drawings, similar reference numerals may be used to refer to similar or related components. The singular form of a noun corresponding to an item may include one or more of the items, unless the context clearly indicates otherwise.

[0041] In this document, the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" can each include any one of the items listed together in that phrase, or all possible combinations thereof. Terms such as "first", "second", "first", "second", "A", "B", "(a)", or "(b)" may be used merely to distinguish the corresponding element from other corresponding elements, and do not limit the corresponding elements in any other respect (e.g., importance or order) unless specifically stated otherwise.

[0042] In this document, whenever a component (e.g., a first component) is referred to as being “connected,” “coupled,” or “connected,” with or without the terms “functionally” or “communicatively,” or “coupled” or “connected,” it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or via a third component.

[0043] According to one embodiment, the method according to various embodiments disclosed in this document may be provided as a computer program product. The computer program product may be traded as a commodity between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) through an application store or directly between two user devices. In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0044] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0045] FIG. 1 is a diagram showing a battery pack according to one embodiment disclosed in this document. FIG. 1 schematically illustrates a battery control system including a battery pack (1) and an upper controller (2) included in an upper system.

[0046] Referring to FIG. 1, a battery pack (1) may include a plurality of battery cells (10), a sensor unit (14), a switching unit (16), and a battery management system (BMS) (20). At this time, the battery pack (1) may be equipped with a plurality of battery cells (10), a sensor unit (14), a switching unit (16), and a battery management system (20).

[0047] According to an embodiment, a plurality of battery cells (10) can supply power to a target device (not shown). To this end, the plurality of battery cells (10) can be electrically connected to the target device. Here, the target device can include an electrical, electronic, or mechanical device that operates by receiving power from the battery pack (1). For example, the target device can be, but is not limited to, an electric vehicle (EV) or an energy storage system (ESS).

[0048] According to an embodiment, the plurality of battery cells (10) may include at least one battery cell (12) that is rechargeable and dischargeable. Here, the battery cell (12) may be a basic unit of a battery cell that can charge and discharge electric energy. For example, the battery cell (12) may be a lithium-ion (Li-ion) battery, a lithium-ion polymer (Li-ion polymer) battery, a nickel-cadmium (Ni-Cd) battery, a nickel-metal hydride (Ni-MH) battery, etc., but is not limited thereto.

[0049] According to an embodiment, a plurality of battery cells (10) may be connected in series or in parallel. For example, the plurality of battery cells (10) may be a battery module, a battery bank, or a collection of battery cells (cell-to-pack structure). According to an embodiment, the plurality of battery cells (10) may include a first battery cell (cell1), a second battery cell (cell2), ..., an Nth battery cell (cellN), where N may be an integer greater than or equal to 2.

[0050] According to an embodiment, the sensor unit (14) can obtain information related to a plurality of battery cells (10). According to an embodiment, the sensor unit (14) can obtain values ​​(or information) related to the state of each of the plurality of battery cells (10). In one embodiment, the values ​​related to the state may include one or more values ​​for voltage, current, resistance, state of charge (SOC), state of health (SOH), or temperature of the battery cell (12), or a combination thereof.

[0051] According to an embodiment, the sensor unit (14) can provide information on each of a plurality of battery cells (10) to the battery management system (20).

[0052] According to an embodiment, the switching unit (16) can switch the connection between the battery pack (1) and an external device. For example, the switching unit (16) can switch the electrical connection between other components included in the battery pack (1) (e.g., a plurality of battery cells (10), a battery cell (12), a sensor unit (14), and a BMS (20)) for connection between the battery pack (1) and an external device.

[0053] According to an embodiment, the switching unit (16) may include a device for controlling the current flow for charging or discharging a plurality of battery cells (10). For example, the switching unit (16) may include at least one relay and / or magnetic contactor, etc., depending on the specifications of the battery pack (1).

[0054] According to an embodiment, a battery management system (BMS (Battery Management System) (20) can control or manage the battery pack (1) to prevent overcharge, overdischarge, etc. by monitoring the voltage, current, temperature, etc. of the battery pack (1). For example, the battery management system (20) may include a plurality of terminals as an interface for receiving values ​​measured from the various parameters described above, and a circuit connected to these terminals to process the input values. In addition, the battery management system (20) may control the sensor unit (14) and / or the switching unit (16). For example, the battery management system (20) may be connected to a plurality of battery cells (10) to monitor the status of each of the plurality of battery cells (10) and control ON / OFF of a relay or a contactor, etc.

[0055] According to an embodiment, the operation of the battery management system (20) may be performed by a BMS (Battery Management System) in the vehicle, as well as by various devices such as a server, cloud, charger, or charger / discharger.

[0056] The upper controller (2) can transmit control signals for a plurality of battery cells (10) to the battery management system (20). Accordingly, the battery management system (20) can be controlled for operation based on the signals received from the upper controller (2).

[0057] According to an embodiment, the battery management system (20) may include the battery management device (100, see FIG. 2) of FIG. 2. According to another embodiment, the battery management system (20) may be a different system from the battery management device (100) of FIG. 2. That is, the battery management device (100) of FIG. 2 may be included in the battery pack (1) or may be configured as another device external to the battery pack (1). In addition, the operation of the battery management device (100) described below may be performed by an in-vehicle BMS (Battery Management System), as well as by various devices such as a server, a cloud, a charger, or a charger / discharger.

[0058] The upper controller (2) can transmit control signals for a plurality of battery cells (10) to the battery management system (20). Accordingly, the battery management system (20) can be controlled for operation based on the signals received from the upper controller (2).

[0059] FIG. 2 is a block diagram illustrating a battery management device according to one embodiment disclosed in this document. FIG. 3 is a graph illustrating the voltage of a battery cell according to one embodiment disclosed in this document. The operation of the battery management device (100) illustrated in FIG. 2 will be described in detail with reference to FIGS. 3 to 6 below.

[0060] First, referring to FIG. 2, a battery management device (100) can manage the status of each of a plurality of battery cells (10, see FIG. 1). As the usage period or number of uses of the plurality of battery cells (10) increases, the capacity of the plurality of battery cells (10) may decrease and the internal resistance may increase. The battery management device (100) can diagnose anomalies within the plurality of battery cells (10) based on data on the changing status of the battery cells as they deteriorate.

[0061] According to various embodiments, if a battery cell experiences an abnormality due to various causes, such as a defect during the production stage, internal deformation and degeneration through multiple charging and discharging cycles, or external impact, the voltage of the battery cell may change more rapidly and significantly than that of a normal battery cell. Here, the voltage behavior of the battery cell may include information related to the resistance or capacity of the battery cell, and may also include information regarding the state of the battery cell. Accordingly, if an abnormality, such as lithium deposition, open circuit, or short circuit, occurs in the battery cell, the voltage of the abnormal battery cell may exhibit a different pattern than that of a normal battery cell.

[0062] According to various embodiments, the battery management device (100) can detect abnormalities in a battery cell based on the voltage behavior of the battery cell. Here, the voltage behavior of the battery cell may refer to the amount of voltage change of the battery cell over time. However, conventional technologies have detected abnormal voltage changes that occur in a short period of time or detected abnormal voltage changes based on the voltage during the discharge period and the rest period after discharge of the battery.

[0063] In contrast, the battery management device (100) according to the embodiment can detect abnormalities in a battery cell based on the long-term voltage behavior of the battery cell. Here, the long-term voltage behavior may refer to a trend in the voltage behavior of the battery cell over multiple charge / discharge cycles. Through this, the battery management device (100) can detect abnormal voltage behavior and detect abnormal battery cells based on the long-term voltage behavior trend.

[0064] Additionally, the battery management device (100) according to the embodiment can detect abnormalities in battery cells based on the voltage during the charging period and the resting period after the charging period. Through this, the battery management device (100) can detect abnormal voltage behavior related to changes in the capacity of battery cells during the charging period and the resting period after the charging period, and detect abnormal battery cells.

[0065] According to an embodiment, the voltage acquisition unit (110) can acquire the voltage of each of the plurality of battery cells (10). The voltage acquisition unit (110) can acquire the voltage of each of the plurality of battery cells (10) per unit time. According to one embodiment, the voltage acquisition unit (110) can continuously acquire voltage data in a charging period, a post-charge rest period, a discharging period, and / or a post-discharging rest period of the plurality of battery cells over time. According to an embodiment, the voltage acquisition unit (110) can include a voltage monitoring circuit or sensor.

[0066] Referring to FIG. 3, the voltage acquisition unit (110) obtains the voltage (V) of each of the plurality of battery cells (cell1, cell2, ..., cellN) in a plurality of cycles (cycle1, cycle2, ..., and cycleM). cellN,cycleM ) can be obtained. Here, the cycle may include at least one of a charging cycle in which the battery cell is charged and a discharging cycle in which the battery cell is discharged. In FIG. 3, two cycles are illustrated for convenience of explanation, but the plurality of cycles may include M cycles (M is an integer greater than or equal to 2). According to an embodiment, the plurality of cycles may include 10 or more cycles or 20 or more cycles, but is not limited thereto. In addition, as the number of cycles increases, the battery management device (100) can clearly analyze the trend of long-term voltage behavior over a plurality of cycles and reduce diagnostic errors when diagnosing abnormal battery cells.

[0067] According to an embodiment, each of the plurality of cycles may include a period between a charging start time (A) and a discharging start time (C) of the battery cell. In another aspect, the cycle may include a charging period (A to B) and a post-charging rest period (B to C) of the battery cell. Accordingly, the battery management device (100) may analyze the voltage behavior of the battery cell in the charging period (A to B) and the pre-discharging rest period (B to C) based on the voltages obtained in the plurality of cycles. Through this, the battery management device (100) may detect an abnormal voltage behavior related to a capacity change of the battery cell in the charging period (A to B) and the rest period (B to C) after the charging period, and may detect an abnormal battery cell, compared to when analyzing the voltage behavior of the discharge period (C to D) and the rest period (not shown) after the discharging period.

[0068] Referring back to FIG. 2, the controller (120) can control the operations of the battery management device (100). In addition, the controller (120) can manage each of the plurality of battery cells. According to an embodiment, the controller (120) can analyze the voltage behavior based on the voltage data of each of the plurality of battery cells (10) acquired from the voltage acquisition unit (110) to determine whether each of the plurality of battery cells (10) is abnormal and diagnose its status.

[0069] According to an embodiment, if the diagnosis results indicate that a battery cell is abnormal, the controller (120) may provide information about the abnormal battery cell to the user. For example, the controller (120) may provide information about the abnormal battery cell to the user terminal via a communication circuit (not shown), and may also provide information about the abnormal battery cell via a display provided in a vehicle or charger.

[0070] According to an embodiment, the battery management device (100) may calculate a value related to the voltage behavior of the battery cell in order to analyze the trend of the voltage behavior of the battery cell. Here, the trend may mean a continuous and consistent direction of time-series data over time. In addition, the value related to the voltage behavior of the battery cell may include time-series data of a first value, a second value, and the second value. According to an embodiment, the controller (120) may calculate time-series data in which the first value related to the voltage behavior of each of the plurality of battery cells (10) in each of the plurality of cycles, the second value normalized by the first values ​​of each of the plurality of battery cells (10), and the second value of each of the plurality of battery cells (10) are listed for each of the plurality of cycles.

[0071] Referring to FIG. 3, the controller (120) may calculate a first value regarding the voltage behavior of each of the plurality of battery cells (cell1, cell2, ..., cellN) in each of the plurality of cycles (cycle1, cycle2, ..., and cycleM) based on voltage data acquired during the plurality of cycles (cycle1, cycle2, ..., and cycleM). Here, the first value may mean an index representing the voltage behavior of the battery cell in the first cycle (e.g., cycle1) including the charging section (A to B) and the resting section (B to C) after charging.

[0072] According to an embodiment, the controller (120) can calculate a first value based on voltage changes of the battery cell in the charging section (A to B) and the post-charge rest section (B to C). Here, the post-charge rest section (B to C) in the charging section (A to B) can include a charging start point (A), a charging end point (B), and a discharge start point (C).

[0073] According to an embodiment, the controller (120) can produce a first vector, a second vector, and a third vector representing voltage behavior between two different points in time among a charging start point (A), a charging end point (B), and a discharging start point (C). In addition, the controller (120) can preprocess the first vector, the second vector, and the third vector to produce a first value, which is a scalar value. Here, the controller (120) can produce a vector having the charging start point (A) as a start point and the charging end point (B) as an end point as a first vector (v1), a vector having the charging start point (A) as a start point and the discharging start point (C) as an end point as a second vector (v2), and a vector having the charging end point (B) as a start point and the discharging start point (C) as an end point as a third vector (v3).

[0074] For example, the controller (120) can produce a first vector (v1cell1,cycle1), a second vector (v2cell1,cycle1), and a third vector (v3cell1,cycle1) in the first cycle (cycle1) of the first battery cell (cell1), as illustrated in FIG. 3.

[0075] According to an embodiment, the controller (120) can determine any point in time between the charging sections (A to B) as the start point of the first vector (v1) and the second vector (v2). For example, the controller (120) can determine the point in time when the voltage of the battery cell is a specific voltage (e.g., 0.5 V) as the start point of the first vector (v1) and the second vector (v2). In addition, for example, the controller (120) can determine the point in time when the SOC of the battery cell is a specific SOC (e.g., 10%) as the start point of the first vector (v1) and the second vector (v2). Through this, the controller (120) can calculate the voltage behavior of the battery cell by compensating for the influence of deterioration and degradation of each of the plurality of battery cells (10).

[0076] FIG. 4 is a graph showing a process for calculating a first value according to one embodiment disclosed in this document.

[0077] Referring to FIG. 4, the controller (120) can preprocess a first vector (v1), a second vector (v2), and a third vector (v3) to produce a first value. Here, the preprocessing may refer to a process of calculating three vectors (v1, v2, and v3) to derive a first value, which is a component constituting a trend of voltage behavior, and the first value may refer to a scalar value. Through this preprocessing process, the controller (120) can produce a first value representing a geometric relationship between the first vector (v1), the second vector (v2), and the third vector (v3). Accordingly, the controller (120) can produce a first value, which is an indicator of the voltage behavior of a battery cell between a charging section (A to B) and a resting section (B to C) after charging.

[0078] According to an embodiment, the preprocessing by the controller (120) may include the following first to third preprocessing steps. According to an embodiment, the controller (120) projects the first vector (v1) onto the second vector (v2) in the first preprocessing step to obtain the projection vector (v proj ) can be produced. For example, the controller (120) can produce a projection vector (v) based on the following <Mathematical Formula 1> proj ) can be produced.

[0079] <Mathematical Formula 1>

[0080]

[0081] In <Mathematical Formula 1>, v1 represents the first vector, v2 represents the second vector, and v proj can mean a projection vector that projects the first vector onto the second vector.

[0082] According to the embodiment, the controller (120) in the second preprocessing step generates a first vector (v1) and a projection vector (v proj ) is the difference between the perpendicular vector (v) perp ) can be produced.

[0083] For example, the controller (120) calculates the perpendicular vector (v) based on the following <Mathematical Formula 2> perp ) can be produced.

[0084] <Mathematical Formula 2>

[0085]

[0086] In <Mathematical Formula 2>, v1 represents the first vector, v proj is the projection vector, v perp can mean a perpendicular vector.

[0087] According to the embodiment, the controller (120) converts the third vector (v3) into a perpendicular vector (v) in the third preprocessing step. perp ) can be calculated by calculating the magnitude of the vector produced by projection onto the first value.

[0088] For example, the controller (120) can calculate the first value based on the following <Mathematical Formula 3>.

[0089] <Mathematical Formula 3>

[0090]

[0091] In <Mathematical Formula 3>, v3 represents the third vector, v perp may mean a perpendicular vector. Accordingly, the controller (120) may, through the first to third preprocessing steps, calculate a first value representing the geometric relationship between the first vector (v1), the second vector (v2), and the third vector (v3). Accordingly, the controller (120) may calculate a first value, which is an indicator of the voltage behavior between the charging section (A to B) of the battery cell and the resting section (B to C) after charging.

[0092] According to an embodiment, the controller (120) may calculate the first value of each of a plurality of battery cells (e.g., cell1, cell2, ..., cellN) for each cycle. In another aspect, the controller (120) may calculate the first value of the first battery cell (cell1), the first value of the second battery cell (cell2), ..., the first value of the Nth battery cell (cellN) in the Mth cycle (cycleM). Accordingly, the first values ​​calculated in the Mth cycle (cycleM) may exist as many as the number of battery cells (e.g., N). In this way, the N first values ​​calculated in the Mth cycle (cycleM) may have different ranges (or scales). Accordingly, the controller (120) may normalize the first values ​​in each of the plurality of cycles to standardize the ranges (or scales) of the first values.

[0093] According to an embodiment, the controller (120) may calculate the second value by normalizing the first values ​​in each of the plurality of cycles. Here, the controller (120) may normalize the first value based on the average and the standard deviation of the first values ​​in each of the plurality of cycles. According to an embodiment, the controller (120) may calculate the average and the standard deviation of the N first values ​​calculated in the first cycle (cycle1). In addition, the controller (120) may divide the difference between the first value and the average of each of the plurality of battery cells (e.g., cell1, cell2, ..., cellN) by the standard deviation to calculate the second value of each of the plurality of battery cells (e.g., cell1, cell2, ..., cellN). Through this, the controller (120) may detect an abnormal battery cell by converting the first values ​​of different ranges (or scales) into a similar scale.

[0094] FIG. 5 is a graph showing time series data of a second value according to one embodiment disclosed in this document.

[0095] Referring to FIG. 5, the controller (120) can produce time series data of the second values ​​of each of the plurality of battery cells (cell1, cell2, ..., cellN) for a plurality of cycles (cycle1, cycle2, ..., and cycleM). Here, the time series data of the battery cell (e.g., cellN) can mean data that expresses the second values ​​of the battery cell (e.g., cellN) for a plurality of cycles (cycle1, cycle2, ..., and cycleM) as a function.

[0096] For example, the graph illustrated in FIG. 5 may be a function representing time series data of the second value of each of a plurality of battery cells (e.g., cell1, cell2, ..., cellN). Here, the x-axis of the graph may represent cycles (unit: number of times), and the y-axis may represent the second value. According to an embodiment, as illustrated in FIG. 5, as the number of cycles increases, the trend between the time series data of the second value may change irregularly and with a larger deviation. Therefore, the controller (120) may more accurately detect an abnormal battery cell by calculating the time series data of the second value based on voltage data acquired in a larger number of cycles.

[0097] FIG. 6 is a graph showing the results of trend analysis of time series data of a second value according to one embodiment disclosed in this document.

[0098] Referring to FIG. 6, the controller (120) can detect an abnormal battery cell by trend-analyzing the time-series data of a plurality of battery cells (cell1, cell2, ..., cellN). Here, the trend may mean a continuous and consistent direction of the time-series data over time. According to an embodiment, the controller (120) can analyze the trend of the time-series data through a time-series data decomposition method. For example, the controller can separate the time-series data into a trend component and a remaining (remain or residual) component through various time-series data decomposition methods. Through this, the controller (120) can individually analyze each of the trend component and the remaining component constituting the time-series data of a plurality of battery cells (cell1, cell2, ..., cellN), and can detect the status (abnormal or normal) of the battery cells.

[0099] According to an embodiment, the controller (120) may decompose the time series data of the second values ​​of each of the plurality of battery cells (cell1, cell2, ..., cellN) into a trend component (a) and a remainder component (b) based on at least one of a Hodrick-Prescott (HP) filter and a Baxter-King (BK) filter. For example, the controller (120) may decompose the time series data of the second values ​​into a trend component (a) and a remainder component (b) as shown in FIG. 6 by applying a Hodrick-Prescott (HP) filter to the time series data of the second values ​​as shown in FIG. 5.

[0100] According to an embodiment, the trend component (a) may represent a long-term trend (e.g., an increase or decrease, etc.) of the time series data of the second value, and the remaining component (b) may represent a trend (e.g., a periodic trend, noise, or random fluctuation, etc.) excluding the long-term trend in the time series data of the second value. Accordingly, the controller (120) may detect a specific voltage fluctuation of an abnormal battery cell in terms of long-term voltage behavior by analyzing the remaining component (b) of the time series data of the second value.

[0101] According to an embodiment, the controller (120) can detect an abnormal battery cell based on the remaining component (b) of each of a plurality of battery cells (cell1, cell2, ..., cellN). According to an embodiment, the controller (120) can compare the size of the remaining component (b) with a first threshold value. Here, the first threshold value can mean a reference value for distinguishing between an abnormal battery cell and a normal battery cell. In addition, the controller (120) can set the first threshold value according to the specification of the battery cell and the degree of detection of the abnormal cell. According to an embodiment, the first threshold value can be 1 or more, or 2 or more, but is not limited thereto. According to an embodiment, the greater the controller (120) sets the first threshold value, the more severely the abnormal battery cell can be detected.

[0102] According to an embodiment, the controller (120) can detect a battery cell corresponding to the remaining component (b) as an abnormal battery cell when the size of the remaining component exceeds a first threshold value. For example, when the controller (120) sets the first threshold value to 2, the controller (120) can detect a battery cell (e.g., cell1) in which the remaining component (b) exceeds 2 or is less than -2 as an abnormal battery cell. Through this, the controller (120) can detect an abnormal battery cell in terms of long-term voltage behavior based on the remaining component (b) of the time series data of the second values ​​of a plurality of battery cells (cell1, cell2, ..., cellN).

[0103] FIG. 7 is a flowchart showing the operation of a battery management device according to one embodiment disclosed in this document.

[0104] Referring to FIG. 7, the battery management device (100) obtains voltage data of each of a plurality of battery cells over time (S101), calculates a first value regarding voltage behavior of each of the plurality of battery cells in each of the plurality of cycles based on the voltage data obtained during the plurality of cycles (S102), calculates a second value through normalization of the first values ​​in each of the plurality of cycles (S103), calculates time series data of the second values ​​of each of the plurality of battery cells for the plurality of cycles (S104), and trend-analyzes the time series data of the plurality of battery cells to detect an abnormal battery cell (S105).

[0105] In step S101, the voltage acquisition unit (110) of the battery management device (100) can acquire voltage data of each of a plurality of battery cells over time (S101).

[0106] In step S102, the controller (120) of the battery management device (100) can calculate a first value regarding the voltage behavior of each of the plurality of battery cells in each of the plurality of cycles based on the voltage data acquired during the plurality of cycles (S102). According to an embodiment, the controller (120) can calculate a first vector, a second vector, and a third vector representing the voltage behavior between two different points in time among a charging start time (A), a charging end time (B), and a discharging start time (C). In addition, the controller (120) can preprocess the first vector, the second vector, and the third vector to calculate a first value, which is a scalar value.

[0107] According to an embodiment, the preprocessing by the controller (120) may include a step of projecting the first vector onto the second vector to produce a projection vector, a step of producing a perpendicular vector which is a difference between the first vector and the projection vector, and a step of producing the first value which is a magnitude of a vector produced by projecting the third vector onto the perpendicular vector.

[0108] In step S103, the controller (120) can calculate the second value by normalizing the first values ​​in each of the plurality of cycles (S103). Here, the controller (120) can calculate the second value by normalizing the first value based on the average and standard deviation of the first values ​​in each of the plurality of cycles.

[0109] At step S104, the controller (120) can produce time series data of the second values ​​of each of the plurality of battery cells for a plurality of cycles (S104).

[0110] In step S105, the controller (120) can trend-analyze the time series data of the plurality of battery cells to detect an abnormal battery cell (S105). According to an embodiment, the controller (120) can decompose the time series data of the second value of each of the plurality of battery cells (cell1, cell2, ..., cellN) into a trend component (a) and a remaining component (b) based on a time series data decomposition method. In addition, the controller (120) can detect an abnormal battery cell based on the remaining component of each of the plurality of battery cells (cell1, cell2, ..., cellN).

[0111] FIG. 8 is a block diagram showing the hardware configuration of a computing system for performing an operating method of a battery management device according to one embodiment disclosed in this document.

[0112] Referring to FIG. 8, a computing system (200) according to one embodiment disclosed in the present document may include an MCU (210), a memory (220), an input / output I / F (230), and a communication I / F (240).

[0113] The MCU (210) may be a processor that executes various programs stored in the memory (220) (e.g., a battery cell data collection program, a graph generation program, a data analysis program, a data decomposition algorithm, a normalization program, a battery cell diagnosis program, etc.), processes various information including battery cell characteristic data and latent variables through these programs, and performs the functions of the battery management device (100) shown in the aforementioned FIGS. 1 to 7.

[0114] The memory (220) can store various programs such as a battery cell data collection program, a graph generation program, a data analysis program, a data decomposition algorithm, a normalization program, and a battery cell diagnosis program.

[0115] Such memories (220) may be provided in multiple numbers as needed. The memories (220) may be volatile memories or non-volatile memories. As volatile memories (220), RAM, DRAM, SRAM, etc. may be used. As non-volatile memories (220), ROM, PROM, EAROM, EPROM, EEPROM, flash memories, etc. may be used. The examples of the memories (220) listed above are merely examples and are not limited to these examples.

[0116] The input / output I / F (230) can provide an interface that enables data transmission and reception between an input device (not shown) such as a keyboard, mouse, or touch panel, and an output device (not shown) such as a display and the MCU (210).

[0117] The communication I / F (240) is a component capable of transmitting and receiving various data with the server, and may be any device capable of supporting wired or wireless communication. For example, the battery management device (100) can transmit and receive various types of information, including battery cell shape models, from a separately provided external server via the communication I / F (240).

[0118] In this way, a computer program according to one embodiment disclosed in this document may be implemented as a module that performs each function illustrated in FIG. 2, for example, by being recorded in a memory (220) and processed by an MCU (210).

[0119] Although all components constituting the embodiments disclosed in this document have been described as being combined or operating in combination as one, the embodiments disclosed in this document are not necessarily limited to such embodiments. That is, within the scope of the purpose of the embodiments disclosed in this document, all of the components may be selectively combined and operated one or more times.

[0120] In addition, terms such as "include," "comprise," or "have" described above, unless specifically stated otherwise, mean that the corresponding component can be included, and therefore should be interpreted to include other components rather than excluding other components. All terms, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the embodiments disclosed in this document belong, unless otherwise defined. Commonly used terms, such as terms defined in a dictionary, should be interpreted to be consistent with the contextual meaning of the relevant technology, and shall not be interpreted in an idealized or overly formal sense, unless explicitly defined in this document.

[0121] The foregoing disclosure outlines features of several embodiments to enable those skilled in the art to better understand the aspects of the present disclosure. Those skilled in the art will readily appreciate that the present disclosure can be readily used as a basis for designing or modifying other structures to achieve the same purposes or advantages of the embodiments introduced herein. Furthermore, those skilled in the art will recognize that such equivalent structures do not depart from the scope of the present disclosure, and that various changes, substitutions, and modifications can be made herein without departing from the scope of the present disclosure.

[0122] [Explanation of symbols]

[0123] 1: Battery pack

[0124] 2: Upper controller

[0125] 10: Multiple battery cells

[0126] 12: Battery cell

[0127] 14: Sensor section

[0128] 16: Switching section

[0129] 20: BMS

[0130] 100: Battery management device

[0131] 110: Voltage acquisition unit

[0132] 120: Controller

[0133] 200: Computing Systems

[0134] 210: MCU

[0135] 220: Memory

[0136] 230: Input / Output I / F

[0137] 240: Communication I / F

Claims

1. A voltage acquisition unit that acquires voltage data of each of multiple battery cells over time; and Based on the voltage data acquired during a plurality of cycles, a first value regarding the voltage behavior of each of the plurality of battery cells is calculated in each of the plurality of cycles, In each of the above plurality of cycles, a second value is calculated by normalizing the first values, Calculating time series data of the second value of each of the plurality of battery cells for the plurality of cycles, A battery management device including a controller that analyzes time series data of the plurality of battery cells to detect abnormal battery cells.

2. In claim 1, A battery management device wherein each of the plurality of cycles includes a period between the start of charging and the start of discharging of the plurality of battery cells.

3. In claim 1, The above controller, A first vector, a second vector, and a third vector representing voltage behavior between two different points in time among the start of charging, the end of charging, and the start of discharging of each of the plurality of battery cells are calculated, A battery management device that preprocesses the first vector, the second vector, and the third vector to produce the first value, which is a scalar value.

4. In claim 3, The start point of the first vector is the charging start point and the end point is the charging end point, The start point of the above second vector is the charging start point and the end point is the discharging start point, A battery management device in which the start point of the third vector is the charging end point and the end point is the discharging start point.

5. In claim 4, The above controller, Projecting the first vector onto the second vector to produce a projection vector, Calculate the perpendicular vector which is the difference between the first vector and the projection vector, A battery management device that calculates the first value, which is the magnitude of a vector calculated by projecting the third vector onto the perpendicular vector.

6. In claim 1, The above controller, A battery management device that normalizes the first value based on the average and standard deviation of the first values ​​in each of the plurality of cycles to produce the second value.

7. In claim 1, The above controller, A battery management device that decomposes time series data of the second values ​​of each of the plurality of battery cells into a trend component and a remain component based on at least one of a Hodrick-Prescott (HP) filter and a Baxter-King (BK) filter.

8. In claim 7, The above controller, A battery management device that detects the abnormal battery cell based on the size of the remaining components of each of the plurality of battery cells.

9. In claim 8, The above controller, A battery management device that compares the size of the remaining component with a first threshold value and detects a battery cell corresponding to the remaining component as an abnormal battery cell if the size of the remaining component exceeds the first threshold value.

10. A step of acquiring voltage data of each of a plurality of battery cells over time; A step of calculating a first value regarding the voltage behavior of each of the plurality of battery cells in each of the plurality of cycles based on the voltage data acquired during the plurality of cycles; A step of calculating a second value by normalizing the first values ​​in each of the plurality of cycles; A step of producing time series data of the second values ​​of each of the plurality of battery cells for the plurality of cycles; and An operating method of a battery management device, comprising a step of trend analyzing time series data of the plurality of battery cells to detect an abnormal battery cell.

11. In claim 10, A method of operating a battery management device, wherein each of the plurality of cycles includes a period between the start of charging and the start of discharging of the plurality of battery cells.

12. In claim 10, The step of calculating the above first value is: A step of calculating a first vector, a second vector, and a third vector representing voltage behavior between two different points in time among the charging start time, the charging end time, and the discharge start time of each of the plurality of battery cells; and An operating method of a battery management device, comprising a step of preprocessing the first vector, the second vector, and the third vector to produce the first value, which is a scalar value.

13. In claim 12, The start point of the first vector is the charging start point and the end point is the charging end point, The start point of the above second vector is the charging start point and the end point is the discharging start point, An operating method of a battery management device in which the start point of the third vector is the charging end point and the end point is the discharging start point.

14. In claim 13, The above preprocessing is, A step of projecting the first vector onto the second vector to produce a projection vector; A step of calculating a perpendicular vector which is the difference between the first vector and the projection vector; and An operating method of a battery management device, comprising a step of calculating the first value, which is the magnitude of a vector calculated by projecting the third vector onto the perpendicular vector.

15. In claim 10, The step of calculating the above second value is: An operating method of a battery management device that normalizes the first value based on the average and standard deviation of the first values ​​in each of the plurality of cycles to produce the second value.

16. In claim 10, Trend analysis of the time series data of the above multiple battery cells is performed. An operating method of a battery management device, wherein the time series data of the second values ​​of each of the plurality of battery cells is decomposed into a trend component and a remaining component based on at least one of a Hodrick-Prescott (HP) filter and a Baxter-King (BK) filter.

17. In claim 16, The step of detecting the above-mentioned abnormal battery cell is: An operating method of a battery management device for detecting an abnormal battery cell based on the size of the remaining components of each of the plurality of battery cells.

18. In claim 17, The step of detecting the above-mentioned abnormal battery cell is: An operating method of a battery management device, comprising the step of comparing the size of the remaining component with a first threshold value and detecting a battery cell corresponding to the remaining component as an abnormal battery cell if the size of the remaining component exceeds the first threshold value.

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