Battery management device and its operating method

Abstract

A battery management device according to one embodiment disclosed herein may include a sensor that acquires the voltage of a battery unit, and a controller that generates a differential profile with respect to a first differential value which is the change in the voltage with respect to the change in the SOC of the battery unit, based on the SOC of the battery unit and the voltage, detects the SOC corresponding to each of the second differential values ​​obtained by differentiating the differential profile that are included in a threshold range, detects the peak value of the differential profile from the first differential values ​​corresponding to the detected SOC from the differential profile, and determines the state of the battery unit based on the peak value of the differential profile.

Description

Technical Field

[0001] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2023-0101824 filed on August 3, 2023, and all the contents disclosed in the literature of the Korean patent application are incorporated herein by reference in their entirety. The embodiments disclosed in this document relate to a battery management device and an operating method thereof.

Background Art

[0002] In recent years, research and development on secondary batteries have been actively conducted. Here, a secondary battery is a battery capable of charging and discharging, and can be interpreted to include all conventional Ni / Cd batteries, Ni / MH batteries, etc., and recent lithium-ion batteries. In recent years, its scope of use has been extended to the power source of electric vehicles, and it has attracted attention as a next-generation energy storage medium.

[0003] Battery cells / modules of electric vehicles undergo internal deformation and denaturation due to various charging and discharging during production and use stages, and their physicochemical properties change. There is a need for a technology to manage the state of such battery cells / modules due to degradation and aging.

[0004] A charge / discharge test can be performed on a battery for purposes such as state management of the battery. Based on the current and voltage obtained from the charge / discharge test, a profile of the open circuit voltage (OCV) with respect to the state of charge (SOC) of the battery can be estimated. However, since the actually measured OCV profile contains noise and errors, there is a problem that data for managing the state of the battery cannot be clearly analyzed. Therefore, a method capable of accurately analyzing the OCV profile containing noise and errors is needed.

Summary of the Invention

Problems to be Solved by the Invention

[0005] One objective of the embodiments disclosed in this document is to provide a battery management device and a method for operating the same that can manage the state of a battery unit based on the state of charge (SOC) and voltage profile of the battery unit included in a battery pack.

[0006] One object of the embodiments disclosed in this document is to provide a battery management device and a method of operating the same, which includes a data processing algorithm for reducing the effects of noise included in the SOC and voltage profiles of a battery unit.

[0007] The technical problems of the embodiments disclosed in this document are not limited to those mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0008] A battery management device according to the embodiment disclosed herein may include a sensor that acquires the voltage of a battery unit, and a controller that generates a differential profile with respect to a first differential value which is the change in the voltage with respect to the change in the SOC of the battery unit, based on the SOC of the battery unit and the voltage, detects the SOC corresponding to each of the second differential values ​​obtained by differentiating the differential profile that are included in a threshold range, detects the peak value of the differential profile from the first differential values ​​corresponding to the detected SOC from the differential profile, and determines the state of the battery unit based on the peak value of the differential profile.

[0009] According to one embodiment, the voltage may include an open-circuit voltage (OCV). According to the embodiment, the controller can compare the absolute value of the second derivative with a predetermined threshold and detect the SOC corresponding to each second derivative within the threshold range.

[0010] According to the embodiment, the controller can determine the state of the battery unit based on a first peak value and a second peak value, which are peak values ​​included in the region of interest among the detected peak values ​​of the differential profile.

[0011] According to the embodiment, the controller can manage the state of the battery unit based on the deviation between the SOCs corresponding to the first peak value and the second peak value, respectively.

[0012] According to the embodiment, the controller can determine that the degradation of the battery unit has progressed further the smaller the deviation between the SOCs corresponding to the first peak value and the second peak value, respectively.

[0013] A battery management method according to one embodiment disclosed herein may include the steps of: generating a differential profile for a first differential value which is the change in voltage with respect to the change in SOC of a battery unit, based on the SOC and voltage of the battery unit; detecting the SOC corresponding to each of the second differential values ​​obtained by differentiating the differential profile that fall within a threshold range; detecting the peak value of the differential profile from the differential profile among the first differential values ​​corresponding to the detected SOC; and determining the state of the battery unit based on the peak value of the differential profile.

[0014] According to one embodiment, the voltage may include an open-circuit voltage (OCV). According to one embodiment, the step of detecting the SOC corresponding to each second derivative value included in the threshold range may include the step of comparing the absolute value of the second derivative with a predetermined threshold to detect the SOC corresponding to each second derivative value included in the threshold range.

[0015] According to one embodiment, the step of determining the state of the battery unit may include determining the state of the battery unit based on a first peak value and a second peak value, which are peak values ​​of the detected differential profile that fall within the region of interest.

[0016] According to one embodiment, the step of determining the state of the battery unit may include the step of managing the state of the battery unit based on the deviation between the SOCs corresponding to the first peak value and the second peak value, respectively.

[0017] According to one embodiment, the step of determining the state of the battery unit may include determining that the smaller the deviation between the SOCs corresponding to the first peak value and the second peak value, the more advanced the degradation of the battery unit. [Effects of the Invention]

[0018] The battery management device and its operating method according to the embodiments disclosed herein can manage the state of a battery unit based on the state of charge (SOC) and voltage profile of the battery unit included in the battery pack.

[0019] The battery management device and its operating method according to the embodiments disclosed herein may include a data processing algorithm for reducing the influence of noise included in the state of charge (SOC) and voltage profile of the battery unit. In addition, this document can provide various effects that can be understood directly or indirectly. [Brief explanation of the drawing]

[0020] [Figure 1] This figure shows a battery pack according to one embodiment disclosed in this document. [Figure 2] This is a block diagram showing a battery management device according to one embodiment disclosed in this document. [Figure 3a]A diagram showing a profile according to an embodiment disclosed in this document. [Figure 3b] A diagram showing a first derivative profile according to an embodiment disclosed in this document. [Figure 3c] A diagram showing a second derivative profile according to an embodiment disclosed in this document. [Figure 3d] A diagram showing a second derivative profile according to other embodiments disclosed in this document. [Figure 3e] A diagram showing a first derivative profile according to other embodiments disclosed in this document. [Figure 3f] A diagram showing a first derivative profile according to still other embodiments disclosed in this document. [Figure 4] A flowchart of the operation of a battery management device according to an embodiment disclosed in this document. [Figure 5] A flowchart of the operation of a battery management device according to other embodiments disclosed in this document. [Figure 6] A block diagram showing the hardware configuration of a computing system for performing the operation method of a battery management device according to an embodiment disclosed in this document.

Embodiments for Carrying Out the Invention

[0021] 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 to include various modifications, equivalents, and / or alternatives of the embodiments of the present invention.

[0022] The various embodiments and the terminology used herein are not intended to limit the technical features described herein to any particular embodiment, but should be understood to include various modifications, equivalents, or substitutes of such embodiments. In relation to the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more such items unless the context clearly indicates otherwise.

[0023] In this document, each phrase such as “A or B,” “at least one of A and B,” “at least one of A or B,” “A, B, or C,” “at least one of A, B, and C,” and “at least one of A, B, or C” may include any one of the items listed together with the applicable phrase, or any possible combination thereof. Terms such as “first,” “second,” “first,” “second,” “A,” “B,” “(a),” or “(b)” may be used merely to distinguish one component from other components and, unless otherwise stated, do not limit the component in any other respect (e.g., importance or order).

[0024] Wherever a component (e.g., the first) is referred to as being "coupled," "joined," or "connected" to another component (e.g., the second) with or without such terms, it means that the first component may be connected to the other component directly (e.g., by wire), wirelessly, or via the third component.

[0025] According to one embodiment, the methods according to the various embodiments disclosed herein may be provided in 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 an instrument-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or online (e.g., download or upload) via 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 at least temporarily stored or temporarily generated in an instrument-readable storage medium such as the memory of a manufacturer's server, an application store server, or an intermediary server.

[0026] According to various embodiments, each of the aforementioned components (e.g., a module or a program) may include one or more individuals, and some of the individuals may be separated and arranged in other components. According to various embodiments, one or more of the aforementioned components or operations may be omitted, or one or more other components or operations may be added. Alternatively or additionally, multiple components (e.g., a module or a program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the components of the multiple components before the integration. According to various embodiments, 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.

[0027] Figure 1 shows a battery pack according to one embodiment disclosed in this document. Referring to Figure 1, the battery pack 1000 may include a higher-level battery unit 100 and a battery management device 200. The higher-level battery unit 100 may include a plurality of battery units 110, 120, ..., 130. According to the embodiment, the higher-level battery unit 100 may be a battery module included in a battery pack for mounting inside an electric vehicle and providing power to the electric vehicle. If the higher-level battery unit 100 is a battery module, the plurality of battery units 110, 120, ..., 130 may be a plurality of battery cells. Although Figure 1 shows the higher-level battery unit 100 as a single unit, the battery pack 1000 may be configured to include n (n is a natural number greater than or equal to 2) higher-level battery units. Furthermore, some components may be omitted from the battery pack 1000, and other general-purpose components may be further included in the battery pack 1000.

[0028] The upper battery unit 100 can supply power to the target device (not shown). For this purpose, the upper battery unit 100 can be electrically connected to the target device. Here, the target device may include electrical, electronic, or mechanical devices that operate on power supplied from the battery pack 1000, which includes the upper battery unit 100. For example, the target device may be, but is not limited to, an electric vehicle (EV) or an energy storage system (ESS).

[0029] The higher-level battery unit 100 may include a plurality of battery units 110, 120, ..., 130. According to the embodiment, the plurality of battery units 110, 120, ..., 130 may be the basic units of a battery cell that can be used by charging and discharging electrical energy. For example, they may be, but are not limited to, lithium-ion (Li-ion) batteries, lithium-ion polymer (Li-ion polymer) batteries, nickel-cadmium (Ni-Cd) batteries, nickel-metal hydride (Ni-MH) batteries, etc. Figure 1 shows three plurality of battery units 110, 120, ..., 130, but is not limited to this, and the higher-level battery unit 100 can be composed of n (n is a natural number of 2 or more) battery units. Also, some configurations may be omitted from the higher-level battery unit 100 and / or the plurality of battery units 110, 120, ..., 130, and other general configurations may be further included in the higher-level battery unit 100 and / or the plurality of battery units 110, 120, ..., 130.

[0030] The Battery Management System (BMS) 200 can manage and / or control the state and / or operation of the upper battery unit 100 and / or multiple battery units 110, 120, ..., 130. According to the embodiment, the Battery Management System 200 can determine the state of the upper battery unit 100 and / or multiple battery units 110, 120, ..., 130 and manage the state of the upper battery unit 100 and / or multiple battery units 110, 120, ..., 130 based on that determination. According to the embodiment, the Battery Management System 200 can control the operation of the upper battery unit 100 and / or multiple battery units 110, 120, ..., 130 and manage the operation of the upper battery unit 100 and / or multiple battery units 110, 120, ..., 130 based on that determination.

[0031] Furthermore, the battery management device 200 can monitor the voltage, current, and / or temperature of the upper battery unit 100 and / or the multiple battery units 110, 120, ..., 130. In addition, for monitoring via the battery management device 200, sensors and various measurement modules (not shown) can be further installed at any location on the upper battery unit 100, the charge / discharge path, or the multiple battery units 110, 120, ..., 130 included in the upper battery unit 100.

[0032] The battery management device 200 can calculate parameters indicating the state of each of the upper battery unit 100 and / or multiple battery units 110, 120, ..., 130, such as SOC (State of Charge) or SOH (State of Health), based on measured values ​​such as monitored voltage, current, and temperature. According to the embodiment, the battery management device 200 can diagnose or determine the state of the upper battery unit 100 and / or multiple battery units 110, 120, ..., 130 based on measured values ​​and / or calculated values ​​obtained from the upper battery unit 100 and / or multiple battery units 110, 120, ..., 130.

[0033] The following operations of the battery management device 200 can be performed by various devices such as a server, cloud, charger, or charger / discharger connected to the battery management device 200 or a vehicle equipped with the battery management device 200.

[0034] Figure 2 is a block diagram showing a battery management device according to one embodiment disclosed in this document. Referring to Figure 2, the battery management device 200 may include a sensor 210 and a controller 220. However, it is not limited to these, and some components may be omitted from the battery management device 200, and other general-purpose components may be further included in the battery management device 200.

[0035] Sensor 210 can acquire information from the upper battery unit 100 and / or from each of the multiple battery units 110, 120, ..., 130. Sensor 210 can acquire the voltage, current, and / or temperature of each of the upper battery unit 100 and / or the multiple battery units 110, 120, ..., 130 during the charging and / or discharging process.

[0036] For the sake of explanation, the following description assumes that the upper battery unit 100 is a battery module, and each of the multiple battery units 110, 120, ..., 130 is a battery cell. Also, for the sake of explanation, the description will use battery unit 110 as an example, but the same principles can be applied to the other battery units 120, ..., 140.

[0037] According to the embodiment, the sensor 210 can acquire the voltage across the battery unit 110 during charging and discharging. The sensor 210 can also acquire the current applied to the battery unit 110 and the charging time during charging and discharging.

[0038] According to the embodiment, the sensor 210 can acquire the open-circuit voltage (OCV) of the battery unit 110. OCV may mean the no-load voltage (OCV), which is the voltage obtained by subtracting the voltage drop due to the internal resistance of the battery unit 110 from the output voltage of the battery unit 110 and then eliminating the effect of the battery current.

[0039] The controller 220 can manage and / or control the operation of the battery unit 110. The controller 220 can manage the operation of the battery unit 110 based on information acquired via the sensor 210.

[0040] According to the embodiment, the controller 220 can perform algebraic and / or statistical operations based on information acquired via the sensor 210. For example, the controller 220 can calculate the capacity and / or State of Charge (SOC) of the battery unit 110 based on the current and charging time of the battery unit 110 acquired via the sensor 210. The controller 220 can also generate a function and / or profile (hereinafter referred to as the OCV profile) related to the open-circuit voltage (OCV) of the battery unit 110 corresponding to the SOC of the battery unit 110 based on the voltage of the battery unit 110 acquired via the sensor 210.

[0041] According to the embodiment, the controller 220 can perform algebraic and / or statistical operations on the generated OCV profile. For example, the controller 220 can perform various operations such as differentiating or integrating the OCV profile, clustering the values ​​of the OCV profile, and calculating deviations. The operations that the controller 220 can perform are not limited to these, and the controller 220 can process the data using various data processing methods and / or algorithms. The controller 220 can determine or manage the state of the battery unit 110 based on the processed information.

[0042] According to the embodiment, the internal resistance of the battery unit 110 increases with use, which can lead to a decrease in output and a reduction in charging capacity. Furthermore, electrochemical changes may occur within the battery unit 110 during the charging and discharging process.

[0043] For example, if the battery unit 110 is a lithium-ion battery cell, the amount of active material present in the electrodes of the battery cell may decrease depending on the use of the battery cell. The active material may be a substance that reacts with lithium ions. For example, the active material may include substances such as LFP, NCM, LMO, and combinations thereof. If the amount of active material in the battery unit 110 decreases, the open-circuit voltage (OCV) may change during the charging and discharging process of the battery unit 110. Therefore, depending on the use of the battery unit 110, such changes in the active material may change the characteristics of the OCV profile of the battery unit 110.

[0044] Therefore, the controller 220 can compare the OCV profile of the battery unit 110 during the changed charge-discharge process with the OCV profile of the battery unit 110 at the beginning of production to determine the current state of the battery unit 110. According to the embodiment, the controller 220 can analyze the OCV data of the battery unit 110 against the State of Charge (SOC) to determine the degradation state of the battery unit 110. By such OCV profile analysis against SOC, the controller 220 can determine the degradation state of the battery unit 110 in a non-destructive manner without physically destroying the battery unit 110.

[0045] The following describes an embodiment in which the controller 220 analyzes the OCV profile and determines the state of the battery unit 110, with reference to Figures 3a to 3e.

[0046] According to the embodiment, Figures 3a to 3e are diagrams showing the operation sequence of the controller 220. However, some operations may be omitted from Figures 3a to 3e, and other general operations may be included between Figures 3a to 3e.

[0047] Figure 3a shows a profile according to one embodiment disclosed in this document. Figure 3b shows a first derivative profile according to one embodiment disclosed in this document. Figure 3c shows a second derivative profile according to one embodiment disclosed in this document. Figure 3d shows a second derivative profile according to another embodiment disclosed in this document. Figure 3e shows a first derivative profile according to another embodiment disclosed in this document. Figure 3f shows a first derivative profile according to yet another embodiment disclosed in this document.

[0048] First, referring to Figure 3a, the controller 220 can generate a profile (P0) based on information about the battery unit 110 acquired via the sensor 210 during charging and discharging of the battery unit 110. According to one embodiment, the controller 220 can generate a profile (P0) relating to the voltage (V, unit: V) of the battery unit 110 corresponding to the capacity (Q, unit: Ah) of the battery unit 110. According to another embodiment, the controller 220 may generate a profile (P0) based on the voltage of the battery unit 110 corresponding to the SOC (State of Charge, unit: %) of the battery unit 110, instead of the capacity (Q). Here, the SOC may be the value obtained by dividing the capacity (Q) of the battery unit 110 by the constant value of the maximum capacity (QMAX). For the sake of explanation, below, SOC (unit: %) will be used as an independent variable and voltage (unit: V) as a dependent variable for the profile (P0).

[0049] According to one embodiment, in profile (P0), the voltage of the battery unit 110 may be the open-circuit voltage (OCV). According to another embodiment, the no-load voltage (OCV) of the battery unit 110 may be data that better reflects the state of the battery unit 110. Therefore, the controller 220 can accurately analyze the state of the battery unit 110 by analyzing the profile (P0) generated based on the OCV.

[0050] According to the embodiment, the OCV profile (P0) may be an XY graph where SOC is set as the independent variable X and OCV is set as the dependent variable Y. That is, the OCV profile (P0) can be defined as a graph that shows the one-to-one relationship between OCV and SOC in the form of a function. According to the embodiment, the entire interval of SOC in the OCV profile (P0) may be from 0% to 100%.

[0051] The controller 220 can detect inflection points in the OCV profile (P0). Furthermore, it can determine the state of the battery unit 110 based on the detected inflection points. According to the embodiment, an inflection point may be a point where the instantaneous rate of change of the second derivative is zero, and where the sign of the instantaneous rate of change of the second derivative changes. A point where the sign of the instantaneous rate of change of the second derivative changes may mean a point where the concavity and / or convexity of the original function changes. For example, an inflection point may mean a point where the graph of the function changes from an upwardly convex state to a downwardly convex state, or from a downwardly convex state to an upwardly convex state.

[0052] According to the embodiment, the controller 220 can set the OCV profile (P0), which shows the correspondence between SOC and OCV, as a function of f(x), and calculate the second derivative f''(x) of the OCV profile (P0) (i.e., the second derivative profile (P2)) by differentiating the f(x) function twice. Here, it is assumed that the f(x) function is a continuous function that can be differentiated twice. The controller 220 can then determine an inflection point where f''(SOC) = 0 in the second derivative f''(x), and where the sign of f''(x) changes from positive to negative or from negative to positive with respect to f''(SOC).

[0053] In other respects, the controller 220 can detect inflection points of the OCV profile (P0) by the local extreme points of the function f'(x) obtained by first differentiating the OCV profile (P0) (i.e., the first derivative profile (P1)). The local extreme points may be the points where the instantaneous rate of change of the first derivative function is 0. The term "local extreme points" may also include local maximums and local minimums. Local maximums may be the points with the largest function value in any interval, and local minimums may be the points with the smallest function value in any interval. The controller 220 can determine local maximums as the points where f'(SOC)=0 in the first derivative f'(x) (i.e., the first derivative profile (P1)) and the sign of f''(x) changes from positive to negative, and local minimums as the points where f'(SOC)=0 in the first derivative f'(x) and the sign of f''(x) changes from negative to positive.

[0054] The inflection points of the OCV profile (P0) can include information about various state changes of the battery unit 110. According to one embodiment, the inflection points of the OCV profile (P0) corresponding to a specific SOC interval can include information about chemical reactions that occur during charging and discharging of the battery unit 110. Therefore, the controller 220 can detect the inflection points of the OCV profile (P0) that are located in a specific SOC interval and determine the state of the battery unit 110.

[0055] According to the embodiment, some of the maximum points (peak points) of the first derivative profile (P1) can contain information related to the degradation state of the battery unit 110. Therefore, the controller 220 can detect the peak points of the first derivative profile (P1) of the OCV profile (P0) and determine which SOC value of the battery unit 110 corresponds to the chemical reaction related to the degradation state of the battery unit 110. On the other hand, the details related to the peak points will be explained later with reference to Figures 3b to 3f.

[0056] According to the embodiment, the OCV profile (P0) acquired during the charge-discharge time of the battery unit 110 may include noise. For example, the OCV profile (P0) may include noise measured from the positive or negative terminal of the battery unit 110, and / or noise measured from various components connected to the battery unit 110. Furthermore, the OCV profile (P0) may include noise corresponding to the driving conditions of the vehicle containing the battery unit 110. For example, the OCV profile (P0) may include noise corresponding to driving conditions such as sudden braking, sudden acceleration, or regenerative braking of the vehicle. As a result, when the controller 220 analyzes the OCV profile (P0) which contains noise, it may not be able to accurately determine the state of the battery unit 110.

[0057] Therefore, the controller 220 can cluster the OCV profile (P0) using the second derivative profile (P2), which is obtained by differentiating the OCV profile (P0) twice, and based on the clustered data, it can detect peak values ​​from the first derivative profile (P1), which is obtained by differentiating the OCV profile (P0) once. This allows the controller 220 to determine the state of the battery unit 110 without interference from noise during actual driving and / or charging / discharging. Furthermore, the controller 220 can detect the inflection point of the OCV profile (P0) (i.e., the peak point of the first derivative profile (P1)) without smoothing the data of the OCV profile (P0) which contains noise. Based on the detected inflection point of the OCV profile (P0) (i.e., the peak point of the first derivative profile (P1)), the controller 220 can accurately determine the degradation state of the battery unit 110.

[0058] Referring to Figure 3b, the controller 220 can generate a profile obtained by first differentiating the OCV profile (P0) of the battery unit 110 (i.e., a first derivative profile (P1)). The first derivative profile (P1) may be a function of the change in the voltage of the battery unit 110 with respect to the change in the SOC of the battery unit 110.

[0059] According to one embodiment, the first derivative profile (P1) may be an XY graph obtained by setting SOC as the variable X and setting the change in OCV with respect to the change in SOC as the variable Y. According to one embodiment, the entire interval of SOC in the first derivative profile (P1) may be from 0% to 100%. According to one embodiment, the function value of the first derivative profile (P1) may be the first derivative value.

[0060] According to the embodiment, the first differential profile (P1) may include multiple poles. These poles may be points where the instantaneous rate of change of the first differential profile (P1) is zero.

[0061] The controller 220 can detect the inflection point of the OCV profile (P0) by determining the peak point of the function f'(x) obtained by first differentiating the OCV profile (P0) (i.e., the first derivative profile (P1)). The controller 220 can determine the peak point as the peak where the instantaneous rate of change of the first derivative profile (P1) is 0 and the differential voltage is the largest.

[0062] As described above, some of the peak points of the first derivative profile (P1) may contain information related to the degradation state of the battery unit 110. According to the embodiment, the controller 220 can determine and manage the state of the battery unit 110 based on the peak points located in the region of interest related to the degradation state of the battery unit. According to the embodiment, the controller 220 can detect a first peak value (PK1) and a second peak value (PK2) located in the region of interest on the first derivative profile (P1).

[0063] According to the embodiment, the region of interest may include a specific state of charge (SOC) interval related to the degradation state of the battery unit 110. For example, the region of interest may be a region in the battery unit 110 where chemical reactions occur during charging and discharging. The chemical reactions occurring in the battery unit 110 may occur in a specific SOC interval. Such chemical reactions may, but are not limited to, those caused by changes in the active material present in the electrodes within the battery unit 110.

[0064] According to one embodiment, the region of interest may be the portion where the SOC of the battery unit 110 is between 10% and 90% of the total length. According to another embodiment, the region of interest may be the portion where the SOC of the battery unit 110 is between 15% and 80% of the total length.

[0065] According to the embodiment, the controller 220 can determine a region of interest including a first SOC interval and a second SOC interval. The first SOC interval is a capacity interval in which a first peak (PK1) is expected to be included and can be set to a specific interval considering the capacity of the battery unit 110. Similarly, the second SOC interval is a capacity interval in which a second peak (PK2) is expected to be included and can be set to a constant interval considering the capacity of the battery unit 110. The first peak (PK1) and / or the second peak (PK2) may be related to the staging phenomenon in which lithium ions are desorbed during the charge-discharge process of the battery unit 110.

[0066] According to the embodiments shown in Figures 3a to 3f, the first SOC interval can be set to an SOC interval of 10% to 30% of the total SOC interval of the battery unit 110. The second SOC interval can be set to an SOC interval of 60% to 80% of the total SOC interval of the battery unit 110. According to the embodiments, the controller 220 can detect peak points in the SOC of the battery unit 110 when it is around 20% and / or around 75% of the total SOC interval.

[0067] The controller 220 can detect a first peak value (PK1) and a second peak value (PK2) located in the region of interest on the first derivative profile (P1). According to one embodiment, the controller 220 can detect the first peak value (PK1) when the SOC of the battery unit 110 is around 20% of the total interval, and the second peak value (PK2) when the SOC is around 80% of the total interval. According to another embodiment, the controller 220 can detect the first peak value (PK1) when the SOC of the battery unit 110 is around 15% of the total interval, and the second peak value (PK2) when the SOC is around 75% of the total interval.

[0068] The controller 220 cannot accurately detect peak values ​​in the region of interest due to noise included in the first derivative profile (P1). Therefore, a method for more accurately detecting peak values ​​in the region of interest will be explained with reference to Figures 3c to 3f.

[0069] Referring to Figure 3c, the controller 220 can generate a second derivative profile (P2) of the profile obtained by differentiating the first derivative profile (P1). The second derivative profile (P2) may be a function of the change in the first derivative value with respect to the change in the SOC of the battery unit 110. The controller 220 can use the second derivative profile (P2) to detect inflection points in the OCV profile (P0).

[0070] According to one embodiment, the second derivative profile (P2) may be an XY graph obtained by setting SOC as the variable X and setting the change in the first derivative with respect to the change in SOC as the variable Y. According to one embodiment, the entire interval of SOC in the second derivative profile (P2) may be from 0% to 100%. According to one embodiment, the function value of the second derivative profile (P2) may be the second derivative value.

[0071] The controller 220 can detect points where the second derivative value of the second derivative profile (P2) is within a threshold range, and can detect inflection points of the OCV profile (P0). According to one embodiment, the threshold range may be a predetermined range that includes points where the second derivative value is 0. According to another embodiment, the threshold range may include a range where the absolute value of the second derivative value is near 0.

[0072] According to the embodiment, the controller 220 can detect an inflection point in the OCV profile (P0) by comparing the absolute value of the second derivative with a predetermined threshold. For example, the predetermined threshold may be a constant that is infinitesimally greater than 0.

[0073] The first derivative profile (P1), like the OCV profile (P0), can contain noise during actual driving and / or charging / discharging. Therefore, multiple points unrelated to the chemical reactions occurring within the battery unit 110 can be detected as inflection points in the OCV profile (P0). The controller 220 can detect points that may be inflection points in a noisy OCV profile by detecting second derivative values ​​within a threshold range, i.e., inflection points in the OCV profile.

[0074] Referring to Figure 3d, the controller 220 can perform clustering using the second derivative profile (P2). According to the embodiment, clustering may be an algorithm for classifying distributed data into specific groups. For example, the clustering algorithm may include known clustering algorithms such as k-means clustering, density-based clustering, and Gaussian clustering.

[0075] The controller 220 can cluster second derivative values ​​within a threshold range detected from the second derivative profile (P2). According to the embodiment, the controller 220 can cluster second derivative values ​​within a threshold range based on the SOC of the battery unit 110.

[0076] The second derivative profile (P2), like the OCV profile (P0) and the first derivative profile (P1), can contain noise during actual driving and / or charging / discharging. Therefore, multiple points unrelated to the chemical reactions occurring within the battery unit 110 can be detected as inflection points in the OCV profile (P0). The controller 220 can detect points that could be inflection points in the OCV profile (P0) using a clustering algorithm and reduce the impact of such noise. Furthermore, the controller 220 can detect inflection points in the OCV profile (P0) (i.e., peak points in the first derivative profile (P1)) without smoothing the OCV data of the battery unit 110.

[0077] According to the embodiment, the controller 220 can detect a representative value that is representative of each clustered SOC group. For example, the representative value may be the average SOC value of the clustered SOC group. The controller 220 can classify the clustered SOC groups based on the detected representative value.

[0078] Referring to Figure 3e, the controller 220 can detect the function value of the first derivative profile (P1) corresponding to the clustered SOC group.

[0079] The controller 220 can detect the first derivative value on the first derivative profile (P1) corresponding to each clustered SOC group. According to the embodiment, since the second derivative value corresponding to each clustered SOC group is close to 0, it may be difficult for the controller 220 to detect the peak value of the first derivative profile (P1) if it only detects the second derivative value from the second derivative profile (P2). Therefore, the controller 220 can detect the corresponding first derivative value from the first derivative profile (P1) based on the SOC groups clustered in the second derivative profile (P2). This allows the controller 220 to accurately determine the state of the battery unit 110.

[0080] Referring to Figure 3f, the controller 220 can detect the peak value based on the detected first derivative value. According to the embodiment, the controller 220 can detect the peak value among the detected first derivative values.

[0081] According to the embodiment, the controller 220 can detect a first peak value (PK1) and a second peak value (PK2) included in the region of interest based on the detected peak values. The process for detecting the peak values ​​included in the region of interest is as described in Figure 3b and will not be repeated here.

[0082] The controller 220 can accurately detect peak values ​​from a noisy first derivative profile (P1) by detecting the peak values ​​of the first derivative profile (P1) through clustering. The controller 220 can accurately detect the first peak value (PK1) and the second peak value (PK2) located in the region of interest through clustering. Therefore, the controller 220 can detect the first peak value (PK1) and the second peak value (PK2) related to the chemical reaction occurring within the battery unit 110 without data smoothing.

[0083] According to the embodiment, the controller 220 can manage the state of the battery unit 110 based on a first peak value (PK1) and a second peak value (PK2). The controller 220 can determine the degree of aging and / or degradation of the battery unit 110 based on the deviation between the SOCs corresponding to the first peak value (PK1) and the second peak value (PK2), respectively.

[0084] The controller 220 can determine that the degradation of the battery unit 110 has progressed further as the SOC deviation between the SOC corresponding to the first peak value (PK1) and the SOC corresponding to the second peak value (PK2) narrows. According to the embodiment, the amount of active material that can react with Li ions may decrease during the repeated charging and discharging of the battery unit 110. For example, the decrease in reactive active material can appear as a decrease in the interval between inflection points in the OCV profile (P0) of the battery unit 110. Therefore, the controller 220 can determine the degradation state of the battery unit 110 in a non-destructive manner by the SOC deviation of the peak values ​​on the first derivative profile (P1) of the OCV profile (P0).

[0085] The controller 220 described with reference to Figures 2 and 3a to 3f is not limited to the configuration described above, and the controller 220 may have additional or omitted general configurations necessary for the operation of the battery management device 200. According to the embodiment, the controller 220 can provide information about the battery unit 110 to a user terminal via a communication unit (not shown), and can also provide information about the battery unit 110 via a display provided in the vehicle or charger, etc.

[0086] Figure 4 is an operation flowchart of a battery management device according to one embodiment disclosed in this document. The operation shown in Figure 4 can be performed via the battery management device 200 shown in Figure 2.

[0087] In operation S101, the controller 220 can generate a profile (P0) based on the SOC and voltage of the battery unit 110. The generated profile (P0) may be an OCV profile (P0) for the SOC of the battery unit 110.

[0088] In operation S102, the controller 220 can generate a first derivative profile (P1). According to the embodiment, the controller 220 can generate a first derivative profile (P1) by differentiating the OCV profile (P0). For example, the first derivative profile (P1) may be a derivative profile with respect to the first derivative value, which is the change in voltage with respect to the change in the SOC of the battery unit 110.

[0089] In operation S103, the controller 220 can generate a second derivative profile (P2). According to the embodiment, the controller 220 can generate a second derivative profile (P2) by differentiating the first derivative profile (P1). For example, the second derivative profile (P2) may be a derivative profile with respect to the second derivative value, which is the change in the first derivative value with respect to the change in the SOC of the battery unit 110.

[0090] In operation S104, the controller 220 can cluster SOC values ​​that fall within the threshold range in the second derivative profile (P2). According to the embodiment, the controller 220 can detect the SOC corresponding to each second derivative value that falls within the threshold range. The controller 220 can cluster the second derivative values ​​based on the detected SOCs. The controller 220 can detect a representative value for the clustered SOC group.

[0091] In operation S105, the controller 220 can detect peak values ​​from the first derivative profile (P1) based on the clustered SOC. According to the embodiment, the controller 220 can detect the peak value of the first derivative profile (P1) from the first derivative profile (P1) among the first derivative values ​​corresponding to the detected SOC. In other words, the controller 220 can detect the peak value of the first derivative profile (P1) from the first derivative profile (P1) among the first derivative values ​​corresponding to the detected representative value.

[0092] Figure 5 is an operation flowchart of a battery management device according to another embodiment disclosed in this document. The operation shown in Figure 5 can be performed via the battery management device 200 shown in Figure 2.

[0093] In the S201 operation, the controller 220 can determine the first peak value (PK1) and the second peak value (PK2) from among the peak values ​​of the first derivative profile (P1). According to the embodiment, the controller 220 can determine the first peak value (PK1) and the second peak value (PK2) from among the peak values ​​of the detected first derivative profile (P1) that are included in the region of interest.

[0094] In S202 operation, the controller 220 can determine the deviation between the SOCs corresponding to the first peak value (PK1) and the second peak value (PK2), respectively. According to the embodiment, the controller 220 can calculate the deviation based on the difference between the SOC corresponding to the first peak value (PK1) and the SOC corresponding to the second peak value (PK2).

[0095] In operation S203, the controller 220 can manage the state of the battery unit 110 based on the SOC deviation. According to the embodiment, the smaller the SOC deviation between the first peak value (PK1) and the second peak value (PK2), the more advanced the degradation of the battery unit 110 is.

[0096] Figure 6 is a block diagram showing the hardware configuration of a computing system for performing the operation method of the battery management device 200 according to one embodiment disclosed in this document.

[0097] Referring to Figure 6, the computing system 2000 according to one embodiment disclosed in this document may include an MCU 2010, memory 2020, input / output interface 2030, and communication interface 2040.

[0098] The MCU2010 may be a processor that executes various programs stored in memory 2020 (for example, a battery cell characteristic data acquisition program, a latent variable extraction program, a distribution map generation program, a battery cell diagnostic program, etc.), processes various information including battery cell characteristic data and latent variables through such programs, and performs the functions of the controller 220 included in the battery management device 200 shown in Figures 1 to 5 above.

[0099] Memory 2020 can store various programs, such as a battery cell characteristic data acquisition program, a latent variable extraction program, a distribution map generation program, and a battery cell diagnostic program. Furthermore, Memory 2020 can store various information, including battery cell characteristic data and latent variables.

[0100] Multiple such memory 2020s may be provided as needed. Memory 2020 may be volatile memory or non-volatile memory. As volatile memory, RAM, DRAM, SRAM, etc., can be used for memory 2020. As non-volatile memory, ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc., can be used for memory 2020. The examples of memory 2020 listed above are merely illustrative and are not limiting.

[0101] The Input / Output I / F 2030 can provide an interface that connects input devices (not shown), such as keyboards, mice, and touch panels, with output devices (not shown), such as displays, and the MCU 2010, enabling data transmission and reception.

[0102] The communication interface 2040 is configured to send and receive various data with the server and may be various devices that support wired or wireless communication. For example, the battery management device 200 can send and receive various information, including the SOC, OCV, and parameters of the battery cells, from a separately provided external server via the communication interface 2040.

[0103] Thus, the computer program according to one embodiment disclosed in this document may be stored in memory 2020 and processed by the MCU 2010 to be implemented as a module that performs, for example, the functions shown in Figure 2.

[0104] Although all components constituting the embodiments disclosed in this document have been described as operating either as a single unit or in combination, 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 components may operate in combination of one or more units.

[0105] Furthermore, terms such as “includes,” “constitutes,” or “possesses,” as described above, mean that they may contain the component in question, and not exclude other components, unless otherwise specified. All terms, including technical or scientific terms, have the same meaning as those generally understood by a person of ordinary skill in the art to which the embodiments disclosed herein belong, unless otherwise specified. Commonly used terms, such as those defined in dictionaries, should be interpreted to be consistent with their meaning in the context of the relevant technology, and not to be interpreted in an ideal or overly formal sense unless explicitly defined herein.

[0106] The aforementioned disclosures outline the features of several embodiments so that those skilled in the art may better understand the aspects of this disclosure. Those skilled in the art will understand that this disclosure can be readily used as a basis for designing or modifying other structures to achieve the same purpose or benefits as the embodiments introduced herein. Furthermore, those skilled in the art will recognize that such equivalent configurations do not deviate from the scope of this disclosure, and that various changes, substitutions, and modifications are possible within this specification without departing from the scope of this disclosure.

Claims

1. A sensor that acquires the voltage of the battery unit, Based on the SOC of the battery unit and the voltage, a differential profile is generated for the first differential value, which is the change in the voltage with respect to the change in the SOC of the battery unit. The SOC corresponding to each of the second derivative values ​​obtained by differentiating the aforementioned differential profile that falls within the threshold range is detected. From the aforementioned differential profile, the peak value of the differential profile is detected among the first differential values ​​corresponding to the detected SOC. A controller that determines the state of the battery unit based on the peak value of the differential profile, A battery management device, including a battery management device.

2. The battery management device according to claim 1, wherein the voltage includes the open-circuit voltage.

3. The aforementioned controller, The battery management device according to claim 1, which compares the absolute value of the second derivative with a predetermined threshold and detects the SOC corresponding to each second derivative value that falls within the threshold range.

4. The aforementioned controller, A battery management device according to any one of claims 1 to 3, wherein the state of the battery unit is determined based on a first peak value and a second peak value, which are peak values ​​included in the region of interest among the peak values ​​of the detected differential profile.

5. The aforementioned controller, The battery management device according to claim 4, which manages the state of the battery unit based on the deviation between the SOCs corresponding to the first peak value and the second peak value, respectively.

6. The aforementioned controller, The battery management device according to claim 5, wherein the smaller the deviation between the SOCs corresponding to the first peak value and the second peak value, the more advanced the deterioration of the battery unit is determined to be.

7. A step of generating a differential profile for a first differential value which is the change in the voltage with respect to the change in the SOC of the battery unit, based on the SOC and voltage of the battery unit, The steps include detecting the SOC corresponding to each of the second derivative values ​​obtained by differentiating the aforementioned differential profile that falls within the threshold range, From the aforementioned differential profile, the step of detecting the peak value of the differential profile among the first differential values ​​corresponding to the detected SOC, The steps include determining the state of the battery unit based on the peak value of the differential profile, Battery management methods, including those mentioned above.

8. The battery management method according to claim 7, wherein the voltage includes the open-circuit voltage.

9. The step of detecting the SOC corresponding to each second derivative value included in the threshold range is: The battery management method according to claim 7, comprising the step of comparing the absolute value of the second derivative with a predetermined threshold and detecting the SOC corresponding to each second derivative value that falls within the threshold range.

10. The step of determining the state of the battery unit is: A battery management method according to any one of claims 7 to 9, comprising the step of determining the state of the battery unit based on a first peak value and a second peak value, which are peak values ​​of the detected differential profile that fall within the region of interest.

11. The step of determining the state of the battery unit is: The battery management method according to claim 10, further comprising the step of managing the state of the battery unit based on the deviation between the SOCs corresponding to the first peak value and the second peak value, respectively.

12. The step of determining the state of the battery unit is: The battery management method according to claim 11, further comprising the step of determining that the smaller the deviation between the SOCs corresponding to the first peak value and the second peak value, the more advanced the deterioration of the battery unit.

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