Battery management device and its operating method

Abstract

A battery management device according to one embodiment disclosed herein may include: a data management unit that calculates the state of health (SOH) or open-circuit voltage (OCV) of each of a plurality of batteries; a controller that determines at least one noisy battery based on the state of health or open-circuit voltage of each of the plurality of batteries, determines at least one abnormal battery based on the state of health or open-circuit voltage of each of the at least one noisy battery and the service life of each of the at least one noisy battery, and diagnoses at least one target battery based on the deviation of open-circuit voltages among a plurality of target batteries excluding the at least one noisy battery.

Description

[Technical Field]

[0001] This application claims priority under Republic of Korea Patent Application No. 10-2023-0043045 dated March 31, 2023, and all content disclosed in the said patent application is incorporated herein by reference. The embodiments disclosed herein relate to a battery management device and a method for operating the same. [Background technology]

[0002] Electric vehicles obtain power by receiving an external electricity supply to charge battery cells, and then using the voltage stored in the battery cells to drive the motor. During production and use, battery cells undergo internal deformation and modification due to various charge and discharge cycles, changing their physicochemical properties and potentially causing internal short circuits. When an internal short circuit occurs in a battery cell, an undervoltage failure can occur, where the battery cell's voltage drops below a certain level, potentially increasing the risk of fire and causing other direct problems with the battery cell. Therefore, technology is needed to determine whether or not an internal short circuit has occurred in a battery cell.

[0003] Conventional battery management devices, in battery systems where multiple battery cells are coupled together, diagnose internal short circuits by determining the relative voltage deviation according to the coupling order of the battery cells, without considering the differences in the degree of degradation (SOH) of each battery cell. This method has limitations in that it cannot take into account the capacity deviation due to the cumulative use and natural degradation of the battery cells, and therefore cannot detect the voltage fluctuations of the battery cells caused by actual internal short circuits. [Overview of the project] [Problems that the invention aims to solve]

[0004] One objective of the embodiments disclosed in this document is to provide a battery management device and its operating method that can accurately diagnose abnormal battery cells by reflecting voltage deviations due to differences in the degree of degradation of battery cells.

[0005] 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]

[0006] A battery management device according to one embodiment disclosed herein may include: a data management unit that calculates the state of health (SOH) or open-circuit voltage (OCV) of each of a plurality of batteries; a controller that determines at least one noisy battery based on the state of health or open-circuit voltage of each of the plurality of batteries, determines at least one abnormal battery based on the state of health or open-circuit voltage of each of the at least one noisy battery and the service life of each of the at least one noisy battery, and diagnoses at least one target battery based on the deviation of open-circuit voltages among a plurality of target batteries excluding the at least one noisy battery.

[0007] According to one embodiment, the controller can determine that at least one of the plurality of batteries whose degree of degradation or open-circuit voltage is outside the first threshold range is a noise battery.

[0008] According to one embodiment, the controller can determine that at least one of the noise batteries is an abnormal battery if its service life falls within the middle of life (MOL) and its degradation level or open-circuit voltage is outside the second threshold range.

[0009] According to one embodiment, the controller can set the first threshold range by reflecting a value obtained by multiplying the average value of the degradation levels of the plurality of batteries by the standard deviation of the degradation levels of the plurality of batteries and a first weight.

[0010] According to one embodiment, the controller can set the second threshold range by reflecting a value obtained by multiplying the average value of the degradation levels of the plurality of batteries by the standard deviation of the degradation levels of the plurality of batteries and a second weight.

[0011] According to one embodiment, the controller can calculate a first value which is the deviation of the change in the open-circuit voltage of each of the plurality of batteries with respect to the change in the average value of the open-circuit voltages of the plurality of batteries, and set the first threshold range by reflecting a value obtained by multiplying the average of the first values ​​of the plurality of batteries by the standard deviation of the first values ​​of the plurality of batteries and a first weight.

[0012] According to one embodiment, the controller can set the second threshold range by reflecting a value obtained by multiplying the average value of the first values ​​of the plurality of batteries by the standard deviation of the first values ​​of the plurality of batteries and a second weight.

[0013] According to one embodiment, the controller can calculate the deviation of the open-circuit voltage of each of the multiple target batteries from the average value of the open-circuit voltages of the multiple target batteries, and calculate the amount of change in the open-circuit voltage deviation of each of the multiple target batteries.

[0014] According to one embodiment, the controller calculates the amount of change in the open-circuit voltage deviation of each of the multiple target batteries at regular intervals, calculates the pattern of the amount of change in the open-circuit voltage deviation of each of the multiple target batteries, compares the pattern of the amount of change in the open-circuit voltage deviation of each of the multiple target batteries with a plurality of diagnostic patterns, and can diagnose at least one target battery.

[0015] According to one embodiment, the controller can diagnose at least one of the plurality of target batteries if the pattern of the open-circuit voltage deviation change of at least one of the target batteries corresponds to one of the plurality of diagnostic patterns.

[0016] A method for operating a battery management device according to one embodiment disclosed herein may include the steps of: calculating the state of health (SOH) or open-circuit voltage (OCV) of each of a plurality of batteries; determining at least one noisy battery based on the state of health or open-circuit voltage of each of the plurality of batteries; determining at least one abnormal battery based on the state of health or open-circuit voltage of each of the at least one noisy battery and the service life of each of the at least one noisy battery; and diagnosing at least one target battery based on the deviation of open-circuit voltages among a plurality of target batteries, excluding the at least one noisy battery.

[0017] According to one embodiment, the step of determining at least one noise battery based on the degree of degradation or open-circuit voltage of each of the plurality of batteries can determine that the battery whose degree of degradation or open-circuit voltage is outside the first threshold range is the at least one noise battery.

[0018] According to one embodiment, the step of determining at least one abnormal battery based on the degree of degradation or open-circuit voltage of each of the at least one noise battery and the service life of each of the at least one noise battery can determine that the at least one abnormal battery is a noise battery whose service life falls within the middle of life (MOL) and whose degree of degradation or open-circuit voltage is outside the second threshold range.

[0019] According to one embodiment, the step of determining at least one noise battery based on the degradation degree or open-circuit voltage of each of the plurality of batteries can be used to set the first threshold range by reflecting a value obtained by multiplying the average value of the degradation degrees of the plurality of batteries by the standard deviation of the degradation degrees of the plurality of batteries and a first weight.

[0020] According to one embodiment, the step of determining at least one abnormal battery based on the degradation degree or open-circuit voltage of each of the at least one noise battery and the service life of each of the at least one noise battery can be used to set the second threshold range by reflecting a value obtained by multiplying the average value of the degradation degrees of the plurality of batteries by the standard deviation of the degradation degrees of the plurality of batteries and a second weight.

[0021] According to one embodiment, the step of determining at least one noise battery based on the degree of degradation or open-circuit voltage of each of the plurality of batteries can be performed by calculating a first value which is the deviation of the change in the open-circuit voltage of each of the plurality of batteries with respect to the change in the average value of the open-circuit voltage of the plurality of batteries, and setting the first threshold range by reflecting a value obtained by multiplying the average of the first values ​​of the plurality of batteries by the standard deviation of the first values ​​of the plurality of batteries and a first weight.

[0022] According to one embodiment, the step of determining at least one abnormal battery based on the degree of degradation or open-circuit voltage of each of the at least one noise battery and the service life of each of the at least one noise battery can be used to set the second threshold range by reflecting a value obtained by multiplying the average value of the first values ​​of the plurality of batteries by the standard deviation of the first values ​​of the plurality of batteries and a second weight.

[0023] According to one embodiment, the step of diagnosing at least one target battery based on the deviation of open-circuit voltages among the multiple target batteries, excluding the at least one noise battery, can be performed by calculating the deviation of the open-circuit voltage of each of the multiple target batteries from the average value of the open-circuit voltages of the multiple target batteries, and calculating the amount of change in the open-circuit voltage deviation of each of the multiple target batteries.

[0024] According to one embodiment, the step of diagnosing at least one target battery based on the deviation of open-circuit voltages among the plurality of target batteries, excluding the at least one noise battery, involves calculating the amount of change in the open-circuit voltage deviation of each of the plurality of target batteries at regular intervals, calculating the pattern of the amount of change in the open-circuit voltage deviation of each of the plurality of target batteries, comparing the pattern of the amount of change in the open-circuit voltage deviation of each of the plurality of target batteries with a plurality of diagnostic patterns, and diagnosing at least one target battery.

[0025] According to one embodiment, the step of diagnosing at least one target battery based on the deviation of open-circuit voltages among the plurality of target batteries, excluding the at least one noise battery, is that the at least one target battery can be diagnosed if the pattern of the change in the open-circuit voltage deviation of at least one of the plurality of target batteries corresponds to one of the plurality of diagnostic patterns. [Effects of the Invention]

[0026] According to one embodiment of the battery management device and its operating method disclosed in this document, it is possible to accurately diagnose abnormal battery cells by reflecting voltage deviations due to differences in the degree of degradation of battery cells. [Brief explanation of the drawing]

[0027] [Figure 1] This figure shows a battery pack according to one embodiment disclosed in this document. [Figure 2] This is a block diagram showing the configuration of a battery management device according to one embodiment disclosed in this document. [Figure 3] This is a graph showing the threshold range according to one embodiment disclosed in this document. [Figure 4] This is a flowchart showing a method for identifying a target battery cell of a controller according to one embodiment disclosed in this document. [Figure 5]This is a flowchart showing a method for diagnosing a target battery cell of a controller according to one embodiment disclosed in this document. [Figure 6] This is a flowchart showing the operation method of a battery management device according to one embodiment disclosed in this document. [Figure 7] This is a block diagram showing the hardware configuration of a computing system that implements the operating method of a battery management device according to one embodiment disclosed in this document. [Modes for carrying out the invention]

[0028] Some embodiments disclosed in this document will be described in detail below with reference to illustrative drawings. It should be noted that, when assigning reference numerals to components in each drawing, the same reference numerals will be used for the same components whenever possible when they appear in other drawings. Furthermore, when describing the embodiments disclosed in this document, if a specific description of a related known configuration or function is deemed to hinder understanding of the embodiments disclosed in this document, such detailed description will be omitted.

[0029] In describing the components of the embodiments disclosed herein, terms such as First, Second, A, B, (a), (b), etc., may be used. Such terms are merely for distinguishing a component from other components and do not limit the nature, order, or sequence of the component. Furthermore, unless otherwise defined, all terms used herein, 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. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology and should not be interpreted in an ideal or overly formal sense unless explicitly defined herein.

[0030] Figure 1 shows a battery pack according to one embodiment disclosed in this document. Referring to Figure 1, a battery pack 1000 according to one embodiment disclosed herein may include a battery module 100, a battery management device 200, and a relay 300. According to various embodiments, the battery module 100 may be a battery cell, in which case the battery pack 1000 may have a cell-to-pack structure.

[0031] Although Figure 1 shows a single battery module 100, according to the embodiment, the battery module 100 may consist of multiple modules, and the battery pack 1000 may have a stacked structure of multiple battery modules. The battery module 100 can include multiple battery cells 110, 120, 130, and 140. Although Figure 1 shows a configuration with four battery cells, the battery module 100 is not limited to this and can consist of n (where n is a natural number greater than or equal to 2) battery cells.

[0032] The battery module 100 can supply power to a target device (not shown). For this purpose, the battery module 100 can be electrically connected to the target device. Here, the target device may include an electrical, electronic, or mechanical device that operates on power supplied from a battery pack 1000 including a plurality of battery cells 110, 120, 130, 140, for example, an electric vehicle (EV) or an energy storage system (ESS).

[0033] The multiple battery cells 110, 120, 130, and 140 are the basic units of a battery that can be used by charging and discharging electrical energy, and 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. On the other hand, although Figure 1 shows that there is one battery module 100, according to the embodiment, the battery module 100 may be composed of multiple units.

[0034] The Battery Management System (BMS) 200 can manage and / or control the state and / or operation of the battery module 100. For example, the Battery Management System 200 can manage and / or control the state and / or operation of multiple battery cells 110, 120, 130, and 140 contained in the battery module 100. The Battery Management System 200 can manage the charging and / or discharging of the battery module 100.

[0035] The battery management device 200 can control the operation of the relay 300. For example, the battery management device 200 can short-circuit the relay 300 to supply power to the target device. The battery management device 200 can also short-circuit the relay 300 when a charging device is connected to the battery pack 1000.

[0036] Furthermore, the battery management device 200 can monitor the voltage, current, temperature, etc., of the battery module 100 and / or the multiple battery cells 110, 120, 130, and 140 contained within the battery module 100. In addition, for monitoring via the battery management device 200, sensors and various measuring modules (not shown) can be further installed in the battery module 100, the charge / discharge path, or at any other location on the battery module 100. Based on the measured values ​​of voltage, current, temperature, etc., the battery management device 200 can calculate parameters indicating the state of the battery module 100, such as SOC (State of Charge) or SOH (State of Health).

[0037] Multiple battery cells 110, 120, 130, and 140 may experience changes in various battery factors, such as decreased capacity and increased internal resistance, as the usage period or number of uses increases. The battery management device 200 can diagnose abnormal phenomena inside the multiple battery cells 110, 120, 130, and 140 based on data of various factors that change as the battery deteriorates.

[0038] Specifically, the battery management device 200 can determine abnormal voltages inside multiple battery cells 110, 120, 130, and 140 based on data of various factors that change as multiple battery cells 110, 120, 130, and 140 deteriorate, and can determine whether or not there are abnormal battery cells inside multiple battery banks 110, 120, 130, and 140.

[0039] For example, the battery management device 200 can calculate the deviation (dV) of the open-circuit voltage (OCV) of multiple battery cells 110, 120, 130, and 140 using the open-circuit voltage (OCV) data of multiple battery cells 110, 120, 130, and 140. Using the average value of the open-circuit voltage deviations of the multiple battery cells 110, 120, 130, and 140, and the individual open-circuit voltage deviations of each of the multiple battery cells 110, 120, 130, and 140, the battery management device 200 can diagnose whether an internal short circuit has occurred in at least one of the multiple battery cells 110, 120, 130, and 140. In the case of a battery cell where an internal short circuit has occurred, a voltage deviation phenomenon compared to a normal battery cell may occur over time due to self-discharge.

[0040] The battery management device 200 compares the average of the state of health (SOH) or open-circuit voltage (OCV) of multiple battery cells 110, 120, 130, and 140 contained in the battery pack 1000 with the state of health or open-circuit voltage (OCV) of each of the multiple battery cells 110, 120, 130, and 140, and can identify multiple target battery cells by excluding noise battery cells suspected of being noise data. After identifying multiple target battery cells, the battery management device 200 can diagnose battery cells where an internal short circuit has occurred using the change in the open-circuit voltage deviation (dV) of the multiple target battery cells contained in the battery pack 1000. In addition, the battery management device 200 can identify abnormal battery cells among the noise battery cells that are suspected of being defective due to abnormal voltage.

[0041] Furthermore, the operation 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.

[0042] Figure 2 is a block diagram showing the configuration of a battery management device according to one embodiment disclosed in this document. The configuration of the battery management device 200 will be described in detail below with reference to Figure 2.

[0043] Referring to Figure 2, the battery management device 200 may include a data management unit 210 and a controller 220. The data management unit 210 can calculate the state of health (SOH) or open-circuit voltage (OCV) for each of the multiple battery cells 110, 120, 130, and 140.

[0044] Here, open-circuit voltage (OCV) refers to the voltage measured when no current flows through the battery. In other words, the open-circuit voltage (OCV) is the voltage between the anode and cathode of the battery when they are not electrically connected. According to Ohm's law, as the resistance of the battery increases infinitely, the current approaches "0", allowing for accurate measurement of the battery voltage. Therefore, the data management unit 210 can measure the open-circuit voltage (OCV) of multiple battery cells 110, 120, 130, and 140 for accurate electrochemical analysis of multiple battery cells 110, 120, 130, and 140.

[0045] State of Health (SOH) is an index that can indicate the health or lifespan of a battery in its current state relative to its initial state. The moment when the SOH reaches 0% can be defined as the End of Life (EOL). Alternatively, the End of Life of a battery can be defined as the point at which the battery capacity falls below the guaranteed capacity. For example, the data management unit 210 can calculate the SOH of multiple battery cells 110, 120, 130, and 140 based on at least one factor among the internal resistance, impedance, conductance, capacity, voltage, self-discharge current, charging performance, and charge / discharge cycles of the multiple battery cells 110, 120, 130, and 140, which change as the multiple battery cells 110, 120, 130, and 140 degrade.

[0046] For example, the data management unit 210 can utilize the open-circuit voltage (OCV) and integrated current values ​​of multiple battery cells 110, 120, 130, and 140 to calculate the individual state of health (SOH), or SOHC, for each battery cell. Specifically, the battery management device 200 uses the open-circuit voltage (OCV) of multiple battery cells 110, 120, 130, and 140 before charging. A , and the open-circuit voltage (OCV) after charging. B It is possible to calculate this.

[0047] The data management unit 210 processes the Open Circuit Voltage Table (OCV Table) based on the OCV A and OCV B Each is converted to a charge amount, i.e., SOC, and then SOC A and SOC B The battery management device 200 can calculate the individual degradation levels of multiple battery cells 110, 120, 130, and 140 based on the following [Equation 1].

[0048] [Formula 1]

number

[0049] Here, (SOC B -SOCA ) represents the SOC deviation, I represents the cumulative charging current, and X represents the capacity of the conventional battery cell. Based on [Equation 1], the data management unit 210 can calculate the individual state of health (SOH) for each of the multiple battery cells 110, 120, 130, and 140.

[0050] The controller 220 can determine at least one noisy battery cell among the multiple battery cells 110, 120, 130, and 140 based on the individual degradation level (SOHC) or open-circuit voltage (OCV) of each of the multiple battery cells 110, 120, 130, and 140. After determining at least one noisy battery cell based on the individual degradation level (SOHC) or open-circuit voltage (OCV) of each of the multiple battery cells 110, 120, 130, and 140, the controller 220 can identify multiple target battery cells excluding at least one noisy battery cell among the multiple battery cells 110, 120, 130, and 140. The controller 220 can diagnose at least one target battery cell based on the deviation of open-circuit voltage (OCV) between the multiple target battery cells. Furthermore, the controller 220 can determine which of the at least one noise battery cell is abnormal based on the state of health (SOH) or open-circuit voltage (OCV) of each noise battery cell and the service life of each noise battery cell.

[0051] First, we will specifically explain how the controller 220 determines a noisy battery cell based on the degradation level or open-circuit voltage of multiple battery cells 110, 120, 130, and 140. The controller 220 can set a threshold range for identifying a target battery cell from among the multiple battery cells 110, 120, 130, and 140 using the mean and standard deviation (σ) of the degradation level or open-circuit voltage of the multiple battery cells 110, 120, 130, and 140. Here, the threshold range can be defined as a reference range where extreme results occur and can be judged as "abnormal." In other words, the threshold range can be defined as a standard that shows how much the data contradicts a particular statistical model. If a battery cell among the multiple battery cells 110, 120, 130, and 140 has a degradation level or open-circuit voltage that exceeds the threshold range, the controller 220 determines it to be a noisy battery cell, removes the data for the noisy battery cell, and identifies the battery cell from which the noisy battery cell has been removed as the target battery cell.

[0052] Figure 3 is a graph showing the threshold range according to one embodiment disclosed in this document. Referring to Figure 3, the threshold range set by the controller 220 will be explained in detail.

[0053] The controller 220 can set a threshold range using the mean (m) and standard deviation (σ) of the degradation degree or open-circuit voltage of multiple battery cells 110, 120, 130, and 140 contained in the battery module 100. The battery module can form a stacked structure with multiple battery modules inside the battery pack 1000. Each of the multiple battery modules can contain multiple battery cells, and the controller 220 can calculate the mean of the degradation degree or open-circuit voltage of the multiple battery cells contained in each of the multiple battery modules. That is, the controller 220 can set a threshold range on a battery module basis and identify a target battery cell on a battery module basis. According to various embodiments, the battery module 100 may be a battery pack, a battery bank, or a battery cell group, and may include a physical, electrical assembly unit package in which two or more battery cells are coupled in series or parallel. That is, the controller 220 can set a threshold range for a battery package in which two or more battery cells are coupled and identify a target battery cell contained in the battery package.

[0054] The controller 220 can use the mean (m) and standard deviation (σ) of the degradation degree or open-circuit voltage of the multiple battery cells 110, 120, 130, and 140 contained in the battery module 100 to set a first threshold range for determining whether multiple battery cells 110, 120, 130, and 140 are noise battery cells, and a second threshold range for determining whether at least one noise battery cell is an abnormal battery cell. For example, the controller 220 can use the mean (m) and standard deviation (σ) of the degradation degree or open-circuit voltage of the multiple battery cells 110, 120, 130, and 140 contained in the battery module 100 to set the first and second threshold ranges in the form of a normal distribution.

[0055] According to one embodiment, the controller 220 can set a first threshold range and a second threshold range using the average value (m) of the degradation degree of multiple battery cells 110, 120, 130, and 140 included in the battery module 100, and the standard deviation (σ) of the degradation degree of multiple battery cells 110, 120, 130, and 140. Specifically, the controller 220 can set the first threshold range by reflecting the value obtained by multiplying the average value (m) of the degradation degree of multiple battery cells 110, 120, 130, and 140 by the standard deviation (σ) of the degradation degree of multiple battery cells 110, 120, 130, and 140 and a first weight (k). For example, the controller 220 can set the first threshold range from "m-kσ," which is obtained by subtracting the value (kσ) obtained by multiplying the standard deviation (σ) of the degradation of multiple battery cells 110, 120, 130, and 140 by a first weight (k) from the average value (m) of the degradation of multiple battery cells 110, 120, 130, and 140, to "m+kσ," which is obtained by adding the value (kσ) obtained by multiplying the standard deviation (σ) of the degradation of multiple battery cells 110, 120, 130, and 140 by a first weight (k) from the average value (m) of the degradation of multiple battery cells 110, 120, 130, and 140.

[0056] Furthermore, the controller 220 can set a second threshold range by reflecting a value obtained by multiplying the average value (m) of the degradation levels of multiple battery cells 110, 120, 130, and 140 by the standard deviation (σ) of the degradation levels of multiple battery cells 110, 120, 130, and 140 and a second weight (k'). For example, the controller 220 can set the second threshold range from "m-k'σ," which is obtained by subtracting the value (k'σ) obtained by multiplying the standard deviation (σ) of the degradation of multiple battery cells 110, 120, 130, and 140 by a second weight (k') from the average value (m) of the degradation of multiple battery cells 110, 120, 130, and 140, to "m+k'σ," which is obtained by adding the value (k'σ) obtained by multiplying the standard deviation (σ) of the degradation of multiple battery cells 110, 120, 130, and 140 by a second weight (k') from the average value (m) of the degradation of multiple battery cells 110, 120, 130, and 140.

[0057] According to one embodiment, the controller 220 can set a first threshold range and a second threshold range using the open circuit voltage data of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100. Hereinafter, the operation of setting the first threshold range and the second threshold range using the open circuit voltage data of the plurality of battery cells 110, 120, 130, 140 of the controller 220 will be specifically described.

[0058] First, the controller 220 can calculate the average value (OCV avg ) of the open circuit voltages of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100. The controller 220 can calculate the change amount (dOCV avg ) of the average value (OCV avg ) of the open circuit voltages of the plurality of battery cells 110, 120, 130, 140. For example, the change amount (dOCV avg ) of the average value of the open circuit voltages of the plurality of battery cells 110, 120, 130, 140 may be a change amount per unit time (h). Also, the controller 220 can calculate the voltage of the open circuit voltage of each of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100, and calculate the change amount (dOCV cell ) of the open circuit voltage of each of the plurality of battery cells 110, 120, 130, 140. For example, the change amount (dOCV cell ) of the open circuit voltage of each of the plurality of battery cells 110, 120, 130, 140 may be a change amount per unit time (h).

[0059] The controller 220 can calculate the deviation (ΔdV avg ) of the change amount (dOCV cell ) of the open circuit voltage of each of the plurality of battery cells 110, 120, 130, 140 with respect to the change amount (dOCV cell ) of the average value of the open circuit voltages of the plurality of battery cells 110, 120, 130, 140. Hereinafter, the deviation (ΔdV cell ) of the change amount (dOCVcell The controller 220 describes the first value (ΔdV) of each of the multiple battery cells 110, 120, 130, and 140. cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The first threshold range can be set by reflecting the value obtained by multiplying the standard deviation (σ) of the first weight (k) of the multiple battery cells 110, 120, 130, and 140. For example, the controller 220 can set the first value (ΔdV) of the multiple battery cells 110, 120, 130, and 140. cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The first value (ΔdV) of multiple battery cells 110, 120, 130, and 140 is obtained by subtracting the value (kσ) obtained by multiplying the standard deviation (σ) of ) by the first weight (k) from "m-kσ". cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The first threshold range can be set to "m+kσ", which is obtained by adding the value (kσ) obtained by multiplying the standard deviation (σ) of ) by the first weight (k).

[0060] Furthermore, the controller 220 measures the first value (ΔdV) of multiple battery cells 110, 120, 130, and 140. cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The second threshold range can be set by reflecting the value obtained by multiplying the standard deviation (σ) of the first value (ΔdV) of the multiple battery cells 110, 120, 130, and 140. cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The first value (ΔdV) of multiple battery cells 110, 120, 130, and 140 is obtained by subtracting the value (k'σ) obtained by multiplying the standard deviation (σ) of ) by the second weight (k') from "m-k'σ". cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cellThe second threshold range can be set to "m+k'σ", which is obtained by adding the value (k'σ) obtained by multiplying the standard deviation (σ) of ) by the second weight (k').

[0061] The controller 220 can use a first threshold range to identify noisy battery cells among multiple battery cells 110, 120, 130, and 140. The controller 220 can exclude noisy battery cells from the multiple battery cells 110, 120, 130, and 140 and identify the remaining battery cells as target battery cells. Furthermore, the controller 220 can use a second threshold range to identify abnormal battery cells among at least one noisy battery cell. Specifically, the controller 220 can use a second threshold range to identify abnormal battery cells among the multiple battery cells 110, 120, 130, and 140 based on their degree of degradation or first value (ΔdV cell Battery cells whose performance exceeds the first threshold range can be identified as noisy battery cells. The controller 220 can exclude the noisy battery cells from among the multiple battery cells 110, 120, 130, and 140, and identify the remaining battery cells as target battery cells.

[0062] Figure 4 is a flowchart showing a method for identifying a target battery cell of a controller according to one embodiment disclosed in this document. The method for identifying the target battery cell of the controller 220 will be described in detail below with reference to Figure 4.

[0063] In step S101, the controller 220 can determine whether the multiple battery cells 110, 120, 130, and 140 contained in the battery module 100 are in an open-circuit voltage (OCV) relaxation state. Here, voltage relaxation refers to the phenomenon in which, when a battery is idle or unloaded, a potential difference is generated between multiple positive electrode materials, this potential difference causes the movement of working ions between the positive electrode materials, and the potential difference is resolved over time. In step S101, for example, if the voltage of the multiple battery cells 110, 120, 130, and 140 has a voltage jitter of 20mV or less for 4 hours under no load, the controller 220 can determine that the multiple battery cells 110, 120, 130, and 140 are in a voltage relaxation state.

[0064] In step S102, the controller 220 can check whether a certain amount of time has elapsed since the multiple battery cells 110, 120, 130, and 140 were determined to be in a voltage relaxation state. For example, in step S102, the controller 220 can check whether 10 days have elapsed since the multiple battery cells 110, 120, 130, and 140 were determined to be in a voltage relaxation state.

[0065] In step S103, the controller 220 can measure the degree of degradation or open-circuit voltage of each of the multiple battery cells 110, 120, 130, and 140 after a set period of time has elapsed.

[0066] In step S104, the controller 220 determines the degree of degradation or first value (ΔdV) of the multiple battery cells 110, 120, 130, and 140. cell It is possible to determine whether ) is within the first threshold range.

[0067] In step S104, according to one embodiment, the controller 220 can determine whether the degradation level of each of the multiple battery cells 110, 120, 130, and 140 is within a first threshold range. Here, the first threshold range can be defined as ranging from "m-kσ," obtained by subtracting the value (kσ) obtained by multiplying the standard deviation (σ) of the degradation levels of the multiple battery cells 110, 120, 130, and 140 by a first weight (k) from the average value (m) of the degradation levels of the multiple battery cells 110, 120, 130, and 140's degradation levels, to "m+kσ," obtained by adding the value (kσ) obtained by multiplying the standard deviation (σ) of the degradation levels of the multiple battery cells 110, 120, 130, and 140's degradation levels by a first weight (k) from the average value (m) of the degradation levels of the multiple battery cells 110, 120, 130, and 140's degradation levels. In step S104, the controller 220 can determine whether each of the multiple battery cells 110, 120, 130, and 140 is a noise battery cell based on whether the degradation level of each of the multiple battery cells 110, 120, 130, and 140 is within a first threshold range.

[0068] In step S104, according to one embodiment, the controller 220 measures the first value (ΔdV) of each of the multiple battery cells 110, 120, 130, and 140. cell It is possible to determine whether the value is within the first threshold range. Here, the first threshold range is the first value (ΔdV) of each of the multiple battery cells 110, 120, 130, and 140. cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The first value (ΔdV) of multiple battery cells 110, 120, 130, and 140 is obtained by subtracting the value (kσ) obtained by multiplying the standard deviation (σ) of ) by the first weight (k) from "m-kσ". cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell It can be defined as up to "m+kσ", which is the sum of the value (kσ) obtained by multiplying the standard deviation (σ) of the first weight (k) of each of the battery cells 110, 120, 130, and 140. In step S104, the controller 220 calculates the first value (ΔdV) of each of the multiple battery cells 110, 120, 130, and 140. cellBased on whether or not the value is within the first threshold range, it is possible to determine whether or not each of the multiple battery cells 110, 120, 130, and 140 is a noisy battery cell.

[0069] In step S105, the controller 220 determines the degree of degradation or first value (ΔdV) of at least one of the multiple battery cells 110, 120, 130, and 140. cell If the value is within the first threshold range, the battery cell can be identified as a target battery cell.

[0070] In step S106, the controller 220 determines the degree of degradation or first value (ΔdV) of at least one of the multiple battery cells 110, 120, 130, and 140. cell If the value is outside the first threshold range, the battery cell can be determined to be a noisy battery cell.

[0071] In step S107, the controller 220 determines the degree of degradation or first value (ΔdV) of the multiple battery cells 110, 120, 130, and 140. cell It is possible to determine whether the value exceeds the second threshold range, and whether the service life of each of the multiple battery cells 110, 120, 130, and 140 falls within the middle of life (MOL) period.

[0072] In step S107, according to one embodiment, the controller 220 can determine whether the degradation level of each of the multiple battery cells 110, 120, 130, and 140 exceeds the second threshold range. Here, the second threshold range can be defined as ranging from "m-k'σ," obtained by subtracting the value (k'σ) obtained by multiplying the standard deviation (σ) of the degradation levels of the multiple battery cells 110, 120, 130, and 140 by a second weight (k') from the average value (m) of the degradation levels of the multiple battery cells 110, 120, 130, and 140, to "m+k'σ," obtained by adding the value (k'σ) obtained by multiplying the standard deviation (σ) of the degradation levels of the multiple battery cells 110, 120, 130, and 140 by a second weight (k') from the average value (m) of the degradation levels of the multiple battery cells 110, 120, 130, and 140. In step S107, the controller 220 can determine whether each of the battery cells 110, 120, 130, and 140 is an abnormal battery cell based on whether the degradation level of each of the battery cells 110, 120, 130, and 140 exceeds the second threshold range, and whether the service life of each of the battery cells 110, 120, 130, and 140 falls within the middle of life (MOL) period.

[0073] In step S107, according to one embodiment, the controller 220 measures the first value (ΔdV) of each of the multiple battery cells 110, 120, 130, and 140. cell It is possible to determine whether the value exceeds the second threshold range. Here, the second threshold range is the first value (ΔdV) of each of the multiple battery cells 110, 120, 130, and 140. cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The first value (ΔdV) of multiple battery cells 110, 120, 130, and 140 is obtained by subtracting the value (k'σ) obtained by multiplying the standard deviation (σ) of ) by the second weight (k') from "m-k'σ". cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cellIt can be defined as up to "m+k'σ", which is the sum of the value obtained by multiplying the standard deviation (σ) of the battery cells (ΔdV) by the second weight (k'). In step S107, the controller 220 calculates the first value (ΔdV) of each of the multiple battery cells 110, 120, 130, and 140. cell Based on whether the value exceeds the second threshold range and whether the service life of each of the multiple battery cells 110, 120, 130, and 140 falls within the middle of life (MOL), it is possible to determine whether each of the multiple battery cells 110, 120, 130, and 140 is an abnormal battery cell.

[0074] In step S108, the controller 220 determines the degradation degree or first value (ΔdV) of at least one of the multiple battery cells 110, 120, 130, and 140. cell If the ΔdV exceeds the second threshold range and the battery cell's service life is at the medium life (MOL) stage, the battery cell can be determined to be an abnormal battery cell. In other words, the controller 220 determines the degree of degradation or first value (ΔdV) of at least one of the multiple battery cells 110, 120, 130, and 140. cell If the value exceeds the second threshold range and the battery cell's service life is at its medium life (MOL) level, it can be determined that the battery cell has undergone abnormal degradation due to a defect.

[0075] In step S109, the controller 220 can diagnose at least one target battery cell based on the deviation of open-circuit voltages between multiple target battery cells.

[0076] Figure 5 is a flowchart showing a method for diagnosing a target battery cell of a controller according to one embodiment disclosed in this document. The following describes in detail, with reference to Figure 5, how to diagnose at least one target battery cell based on the deviation of the open-circuit voltage (OCV) between target battery cells in the controller 220.

[0077] In step S201, the controller 220 can measure the open-circuit voltage of each of the multiple target battery cells after a predetermined period of time has elapsed.

[0078] In step S202, the controller 220 can calculate the average value of the open-circuit voltages of multiple target battery cells. In step S202, the controller 220 can calculate the deviation (dV) of the open-circuit voltage of each of the multiple target battery cells relative to the average value of the open-circuit voltages of each of the multiple groups. In step S202, for example, the controller 220 can calculate the deviation of the open-circuit voltage of each of the multiple target battery cells relative to the average value (Vavg) of the open-circuit voltages of the multiple target battery cells included in the battery module 100.

[0079] In step S202, for example, if the controller 220 sets the current time to 'T', it can calculate the deviation (dV) of the open-circuit voltage of each of the multiple target battery cells at the current time 'T' compared to past time points 'T-4', 'T-3', 'T-2', and 'T-1'. In step S202, the controller 220 calculates the first open-circuit voltage deviation (dV) of each target battery cell, which is the deviation of the open-circuit voltage of each target battery cell calculated at 'T-4'. T-4 ), the second open-circuit voltage deviation (dV), which is the deviation of the open-circuit voltage of each target battery cell calculated at 'T-3'. T-3 ), the third open-circuit voltage deviation (dV), which is the deviation of the open-circuit voltage of each target battery cell calculated at 'T-2'. T-2 ), the fourth open-circuit voltage deviation (dV), which is the deviation of the open-circuit voltage of each target battery cell calculated at 'T-1'. T-1 ), and the fifth open-circuit voltage deviation (dV) which is the open-circuit voltage deviation of each target battery cell calculated at time 'T'. T It is possible to calculate ).

[0080] In step S203, the controller 220 can calculate the change in the open-circuit voltage deviation (ΔdV) of each of the multiple target battery cells. Specifically, in step S203, the controller 220 can continuously calculate the open-circuit voltage of each of the multiple target battery cells at regular intervals and calculate the change in the open-circuit voltage deviation (ΔdV) of each of the multiple target battery cells calculated in the current period relative to the open-circuit voltage deviation of each of the multiple target battery cells calculated in the previous period.

[0081] In step S203, the controller 220 can continuously calculate the change in the open-circuit voltage deviation (ΔdV) of each of the multiple target battery cells at regular intervals.

[0082] In step S203, for example, the controller 220 calculates the first open-circuit voltage deviation (dV) which is the open-circuit voltage deviation calculated at time 'T-4' for each of the multiple target battery cells. T-4 The second open-circuit voltage deviation (dV) is the open-circuit voltage deviation calculated at 'T-3' relative to ). T-3 The first voltage deviation change (ΔdV) is the amount of change in ) T-3 It is possible to calculate ).

[0083] In step S203, for example, the controller 220 calculates the second open-circuit voltage deviation (dV), which is the open-circuit voltage deviation calculated at time 'T-3' for each of the multiple target battery cells. T-3 The third open-circuit voltage deviation (dV) is the open-circuit voltage deviation calculated at time 'T-2' relative to ). T-2 The second voltage deviation change (ΔdV) is the amount of change in ). T-2 It is possible to calculate ).

[0084] In step S203, for example, the controller 220 calculates the third open-circuit voltage deviation (dV), which is the open-circuit voltage deviation calculated at time 'T-2' for each of the multiple target battery cells. T-2 The fourth open-circuit voltage deviation (dV) is the open-circuit voltage deviation calculated at time 'T-1' relative to ). T-1The third voltage deviation change (ΔdV) is the amount of change in ). T-1 It is possible to calculate ).

[0085] In step S203, for example, the controller 220 calculates the fourth open-circuit voltage deviation (dV), which is the open-circuit voltage deviation calculated at time 'T-1' for each of the multiple target battery cells. T-1 The fifth open-circuit voltage deviation (dV) is the open-circuit voltage deviation calculated at time 'T' relative to ). T The fourth voltage deviation change (ΔdV) is the amount of change in ). T It is possible to calculate ).

[0086] In step S204, the controller 220 can calculate the pattern of open-circuit voltage deviation changes for each of the multiple target battery cells. In step S204, for example, the controller 220 calculates the first voltage deviation change (ΔdV) which is the change in the open-circuit voltage deviation for each of the multiple target battery cells calculated at time 'T-3'. T-3 ), the second voltage deviation change (ΔdV), which is the change in the open-circuit voltage deviation of each of the multiple target battery cells calculated at 'T-2'. T-2 ), the third voltage deviation change (ΔdV), which is the change in the open-circuit voltage deviation of each of the multiple target battery cells calculated at 'T-1'. T-1 ), and the fourth voltage deviation change (ΔdV), which is the change in the open-circuit voltage deviation of each of the multiple target battery cells calculated at time 'T'. T Using this method, the pattern of open-circuit voltage deviation change for each of multiple target battery cells can be calculated.

[0087] In step S205, the controller 220 can diagnose at least one target battery cell using the pattern of open-circuit voltage deviation changes for each of the multiple target battery cells. Specifically, in step S205, the controller 220 can diagnose at least one target battery cell based on at least one of the following: the pattern of open-circuit voltage deviation changes for each of the multiple target battery cells, the sum of the open-circuit voltage deviation changes, or the magnitude.

[0088] In step S205, according to the embodiment, the controller 220 can diagnose at least one target battery cell by comparing the pattern of open-circuit voltage deviation change for each of the multiple target battery cells with a plurality of already stored diagnostic patterns. Here, the plurality of already stored diagnostic patterns may include a pattern that diagnoses the state of a battery cell based on the sum of the open-circuit voltage deviation changes (dV) of the target battery cells, a pattern that diagnoses the state of a battery cell based on the magnitude of each open-circuit voltage deviation change (dV) of the target battery cells, a pattern that diagnoses the state of a battery cell based on the maximum or minimum magnitude of the open-circuit voltage deviation change (dV) of the target battery cells, and a pattern that diagnoses the state of a battery cell based on the increasing or decreasing trend of the open-circuit voltage deviation changes (dV) of the target battery cells.

[0089] The controller 220 can diagnose that an internal short circuit has occurred in at least one of the target battery cells if the pattern of the open-circuit voltage deviation change in that target battery cell corresponds to one of several diagnostic patterns.

[0090] Furthermore, if the controller 220 confirms that an internal short circuit has occurred in a cell as a result of the diagnosis, it can provide information about the battery cell to the user. For example, the controller 220 can provide information about the battery cell with the internal short circuit to the user terminal via a communication unit (not shown), and can also provide information about the battery cell via a display provided in the vehicle or charger.

[0091] As described above, according to the battery management device 200 of one embodiment disclosed in this document, it is possible to accurately diagnose battery cells in which an internal short circuit has occurred by reflecting the voltage deviation due to the difference in the degree of degradation of the battery cells.

[0092] Conventional battery management devices do not take into account differences in the degree of degradation between battery cells, which can lead to misdiagnosis of battery cells where voltage deviations occur due to differences in degradation. However, the battery management device 200 according to one embodiment disclosed in this document can classify battery cells with differences in degradation into noisy battery cells and improve the accuracy of internal short-circuit diagnosis by relatively comparing target battery cells with similar degradation levels.

[0093] Furthermore, the battery management device 200 can compare the changes in multiple open-circuit voltage deviations for each of the multiple battery cells and analyze both the short-term and long-term voltage behavior characteristics (features) of the battery cells.

[0094] The battery management device 200 can diagnose battery cells experiencing internal short circuits early by using the change in the open-circuit voltage deviation of the battery cells, thereby ensuring the safety and reliability of the battery's energy. Furthermore, since the battery management device 200 diagnoses battery cells experiencing internal short circuits while the battery is installed in the vehicle, separate battery isolation is unnecessary, allowing for quick and easy diagnosis of battery cells.

[0095] Figure 6 is a flowchart showing the operation method of a battery management device according to one embodiment disclosed in this document. The operation method of the battery management device 200 will be explained in detail below with reference to Figures 1 to 5.

[0096] Since the battery management device 200 is substantially the same as the battery management device 200 described with reference to Figures 1 to 5, a brief description will be given below to avoid repetition.

[0097] Referring to Figure 6, the operation method of the battery management device may include the steps of: calculating the state of health (SOH) or open-circuit voltage (OCV) of each of the multiple batteries (S301); determining at least one noisy battery based on the state of health or open-circuit voltage of each of the multiple batteries (S302); determining at least one abnormal battery based on the open-circuit voltage or state of health and service life of each of the at least one noisy battery (S303); and diagnosing at least one target battery based on the deviation of the open-circuit voltage (OCV) between the multiple target batteries (S304).

[0098] The following provides a detailed explanation of steps S301 through S304. In step S301, the data management unit 210 can calculate the state of health (SOH) or open-circuit voltage (OCV) for each of the multiple battery cells 110, 120, 130, and 140.

[0099] Here, open-circuit voltage (OCV) refers to the voltage measured when no current flows through the battery. In other words, the open-circuit voltage (OCV) is the voltage between the anode and cathode of the battery when they are not electrically connected. According to Ohm's law, as the resistance of the battery increases infinitely, the current approaches "0", and the accurate battery voltage can be measured. In step S301, therefore, the data management unit 210 can measure the open-circuit voltage (OCV) of multiple battery cells 110, 120, 130, and 140 for accurate electrochemical analysis of the multiple battery cells 110, 120, 130, and 140.

[0100] State of Health (SOH) is an index that can indicate the health or lifespan of a battery in its current state relative to its initial state. The moment when the state of health reaches 0% can be defined as the end of life (EOL). Alternatively, the end of life of a battery can be defined as the point at which the battery capacity falls below the guaranteed capacity. In step S301, for example, the data management unit 210 can calculate the state of health (SOH) of the multiple battery cells 110, 120, 130, and 140 based on at least one factor among the internal resistance, impedance, conductance, capacity, voltage, self-discharge current, charging performance, and charge / discharge cycles of the multiple battery cells 110, 120, 130, and 140, which change as the multiple battery cells 110, 120, 130, and 140 degrade.

[0101] In step S301, for example, the data management unit 210 can utilize the open-circuit voltage (OCV) and integrated current values ​​of multiple battery cells 110, 120, 130, and 140 to calculate the individual state of health (SOH), i.e., SOHC, for each battery cell. Specifically in step S301, the battery management device 200 uses the open-circuit voltage (OCV) of multiple battery cells 110, 120, 130, and 140 before charging. A , and the open-circuit voltage (OCV) after charging. B It is possible to calculate this.

[0102] In step S301, the data management unit 210 uses the open-circuit voltage table (OCV Table) to determine the OCV A and OCV B Each is converted to a charge amount, i.e., SOC, and then SOC A and SOC B The following can be calculated. In step S301, the battery management device 200 can calculate the individual degradation levels of multiple battery cells 110, 120, 130, and 140 based on the following [Equation 2].

[0103] [Formula 2]

number

[0104] Here, (SOC B -SOC A ) represents the SOC deviation, I represents the cumulative charging current, and X represents the capacity of the conventional battery cell. Based on [Equation 2], the data management unit 210 can calculate the individual state of health (SOH), i.e., SOHC, for each of the multiple battery cells 110, 120, 130, and 140.

[0105] In step S302, the controller 220 can determine at least one noisy battery cell among the multiple battery cells 110, 120, 130, and 140 based on the individual degradation level (SOHC) or open-circuit voltage (OCV) of each of the multiple battery cells 110, 120, 130, and 140. In step S302, after determining at least one noisy battery cell based on the individual degradation level (SOHC) or open-circuit voltage (OCV) of each of the multiple battery cells 110, 120, 130, and 140, the controller 220 can identify multiple target battery cells excluding at least one noisy battery cell among the multiple battery cells 110, 120, 130, and 140.

[0106] In step S302, the controller 220 can set a threshold range for identifying the target battery cell among the multiple battery cells 110, 120, 130, and 140, using the mean and standard deviation (σ) of the degradation degree or open-circuit voltage of the multiple battery cells 110, 120, 130, and 140.

[0107] In step S302, the controller 220 can set a first threshold range using the mean (m) and standard deviation (σ) of the degradation degree or open-circuit voltage of the multiple battery cells 110, 120, 130, and 140 contained in the battery module 100. The battery module can form a stacked structure with multiple battery modules inside the battery pack 1000. Each of the multiple battery modules may contain multiple battery cells, and the controller 220 can calculate the mean of the degradation degree or open-circuit voltage of the multiple battery cells contained in each of the multiple battery modules. According to various embodiments, the battery module 100 may be a battery pack, a battery bank, or a battery cell group, and may include a physical and electrical assembly unit package in which two or more battery cells are connected in series or parallel.

[0108] In step S302, according to one embodiment, the controller 220 can set a first threshold range using the average value (m) of the degradation levels of the multiple battery cells 110, 120, 130, and 140 included in the battery module 100, and the standard deviation (σ) of the degradation levels of the multiple battery cells 110, 120, 130, and 140. Specifically, in step S302, the controller 220 can set a first threshold range by reflecting the value obtained by multiplying the average value (m) of the degradation levels of the multiple battery cells 110, 120, 130, and 140 by the standard deviation (σ) of the degradation levels of the multiple battery cells 110, 120, 130, and 140 by a first weight (k). In step S302, for example, the controller 220 can set the first threshold range from "m-kσ," which is obtained by subtracting the value (kσ) obtained by multiplying the standard deviation (σ) of the degradation of multiple battery cells 110, 120, 130, and 140 by a first weight (k) from the average value (m) of the degradation of multiple battery cells 110, 120, 130, and 140, to "m+kσ," which is obtained by adding the value (kσ) obtained by multiplying the standard deviation (σ) of the degradation of multiple battery cells 110, 120, 130, and 140 by a first weight (k) from the average value (m) of the degradation of multiple battery cells 110, 120, 130, and 140.

[0109] In step S302, according to one embodiment, the controller 220 can set a first threshold range using the open circuit voltage data of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100. In step S302, first, the controller 220 calculates the average value (OCV avg ) of the open circuit voltages of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100. In step S302, the controller 220 can calculate the change amount (dOCV avg ) of the average value (OCV avg ) of the open circuit voltages of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100. In step S302, the controller 220 calculates the voltage of the open circuit voltage of each of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100, and can calculate the change amount (dOCV cell ) of the open circuit voltage of each of the plurality of battery cells 110, 120, 130, 140.

[0110] In step S302, the controller 220 calculates the deviation (ΔdV avg ) of the change amount (dOCV cell ) of the open circuit voltage of each of the plurality of battery cells 110, 120, 130, 140 with respect to the change amount (dOCV cell ) of the average value of the open circuit voltages of the plurality of battery cells 110, 120, 130, 140. Hereinafter, the deviation (ΔdV cell ) of the change amount (dOCV cell ) of the open circuit voltage of each of the plurality of battery cells 110, 120, 130, 140 will be described as the first value. In step S302, the controller 220 adds the average value (m) of the first values (ΔdV cell ) of each of the plurality of battery cells 110, 120, 130, 140 to the first values (ΔdV cellThe first threshold range can be set by reflecting the value obtained by multiplying the standard deviation (σ) of the first weight (k). In step S302, for example, the controller 220 sets the first value (ΔdV) of the multiple battery cells 110, 120, 130, 140. cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The first value (ΔdV) of multiple battery cells 110, 120, 130, and 140 is obtained by subtracting the value (kσ) obtained by multiplying the standard deviation (σ) of ) by the first weight (k) from "m-kσ". cell The average value (m) of multiple battery cells 110, 120, 130, and 140 is used, and the first value (ΔdV) of those cells is used. cell The first threshold range can be set to "m+kσ", which is obtained by adding the value (kσ) obtained by multiplying the standard deviation (σ) of ) by the first weight (k).

[0111] In step S302, the controller 220 can determine which of the multiple battery cells 110, 120, 130, and 140 are noisy battery cells using a first threshold range. In step S302, the controller 220 can exclude the noisy battery cells from the multiple battery cells 110, 120, 130, and 140 and identify the remaining battery cells as target battery cells. Specifically in step S302, the controller 220 can determine which of the multiple battery cells 110, 120, 130, and 140 have a degradation degree or a first value (ΔdV cell Battery cells whose performance exceeds the first threshold range can be identified as noisy battery cells. The controller 220 can exclude the noisy battery cells from among the multiple battery cells 110, 120, 130, and 140, and identify the remaining battery cells as target battery cells.

[0112] In step S303, the controller 220 can use the second threshold range to determine which of the noise battery cells is abnormal.

[0113] In step S303, the controller 220 can set the second threshold range by reflecting a value obtained by multiplying the average value (m) of the degradation degrees of the plurality of battery cells 110, 120, 130, 140 by the standard deviation (σ) of the degradation degrees of the plurality of battery cells 110, 120, 130, 140 and the second weight (k'). In step S303, for example, the controller 220 subtracts a value (k'σ) obtained by multiplying the standard deviation (σ) of the degradation degrees of the plurality of battery cells 110, 120, 130, 140 and the second weight (k') from the average value (m) of the degradation degrees of the plurality of battery cells 110, 120, 130, 140 to get "m - k'σ", and sets the range from "m - k'σ" to "m + k'σ", which is obtained by adding the value (k'σ) obtained by multiplying the standard deviation (σ) of the degradation degrees of the plurality of battery cells 110, 120, 130, 140 and the second weight (k') to the average value (m) of the degradation degrees of the plurality of battery cells 110, 120, 130, 140 as the second threshold range.

[0114] In step S303, the controller 220 uses the average value (m) of the first values (ΔdV cell ) of the plurality of battery cells 110, 120, 130, 140, and can set the second threshold range by reflecting a value obtained by multiplying the standard deviation (σ) of the first values (ΔdV cell ) of the plurality of battery cells 110, 120, 130, 140 and the second weight (k'). In step S303, for example, the controller 220 subtracts a value (k'σ) obtained by multiplying the standard deviation (σ) of the first values (ΔdV cell ) of the plurality of battery cells 110, 120, 130, 140 and the second weight (k') from the average value (m) of the first values (ΔdV cell ) of the plurality of battery cells 110, 120, 130, 140 to get "m - k'σ", and sets the range from "m - k'σ" to "m + k'σ", which is obtained by adding the value (k'σ) obtained by multiplying the standard deviation (σ) of the first values (ΔdV cell ) of the plurality of battery cells 110, 120, 130, 140 and the second weight (k') to the average value (m) of the first values (ΔdV cell ) of the plurality of battery cells 110, 120, 130, 140 as the second threshold range.

[0115] In step S303, the controller 220 determines the degree of degradation or first value (ΔdV) of the multiple battery cells 110, 120, 130, and 140. cell The controller 220 can determine whether the degradation or first value (ΔdV) of at least one of the battery cells 110, 120, 130, and 140 exceeds the second threshold range, and whether the service life of each of the multiple battery cells 110, 120, 130, and 140 falls within the middle of life (MOL). In step S303, the controller 220 determines whether the degradation or first value (ΔdV) of at least one of the multiple battery cells 110, 120, 130, and 140 cell If the ΔdV exceeds the second threshold range and the battery cell's service life is at the medium life (MOL) stage, the battery cell can be determined to be an abnormal battery cell. In other words, the controller 220 determines the degree of degradation or first value (ΔdV) of at least one of the multiple battery cells 110, 120, 130, and 140. cell If the value exceeds the second threshold range and the battery cell's service life is at its medium life (MOL) level, it can be determined that the battery cell has undergone abnormal degradation due to a defect.

[0116] In step S304, the controller 220 can diagnose at least one target battery cell based on the deviation of open-circuit voltages between multiple target battery cells.

[0117] In step S304, the controller 220 can determine whether the multiple battery cells 110, 120, 130, and 140 included in the battery module 100 are in an open-circuit voltage (OCV) relaxation state.

[0118] In step S304, the controller 220 can diagnose at least one target battery cell based on the deviation of open-circuit voltages among multiple target battery cells. In step S304, the controller 220 can calculate the average value of the open-circuit voltages of the multiple target battery cells. In step S304, the controller 220 can calculate the deviation (dV) of the open-circuit voltage of each of the multiple target battery cells relative to the average value of the open-circuit voltages of each of the multiple groups. In step S304, for example, the controller 220 can calculate the deviation of the open-circuit voltage of each of the multiple target battery cells relative to the average value (Vavg) of the open-circuit voltages of the multiple target battery cells included in the battery module 100.

[0119] In step S304, for example, if the controller 220 sets the current time to 'T', it can calculate the deviation (dV) of the open-circuit voltage of each of the multiple target battery cells at the current time 'T' compared to past time points 'T-4', 'T-3', 'T-2', and 'T-1'. In step S304, the controller 220 calculates the first open-circuit voltage deviation (dV) of each target battery cell, which is the deviation of the open-circuit voltage of each target battery cell calculated at 'T-4'. T-4 ), the second open-circuit voltage deviation (dV), which is the deviation of the open-circuit voltage of each target battery cell calculated at 'T-3'. T-3 ), the third open-circuit voltage deviation (dV), which is the deviation of the open-circuit voltage of each target battery cell calculated at 'T-2'. T-2 ), the fourth open-circuit voltage deviation (dV), which is the deviation of the open-circuit voltage of each target battery cell calculated at 'T-1'. T-1 ), and the fifth open-circuit voltage deviation (dV) which is the open-circuit voltage deviation of each target battery cell calculated at time 'T'. T It is possible to calculate ).

[0120] In step S304, the controller 220 can calculate the change in the open-circuit voltage deviation (ΔdV) of each of the multiple target battery cells. Specifically, in step S304, the controller 220 can continuously calculate the open-circuit voltage of each of the multiple target battery cells at regular intervals and calculate the change in the open-circuit voltage deviation (ΔdV) of each of the multiple target battery cells calculated in the current period relative to the open-circuit voltage deviation of each of the multiple target battery cells calculated in the previous period.

[0121] In step S304, the controller 220 can continuously calculate the change in the open-circuit voltage deviation (ΔdV) of each of the multiple target battery cells at a constant period.

[0122] In step S304, for example, the controller 220 calculates the first open-circuit voltage deviation (dV) which is the open-circuit voltage deviation calculated at time 'T-4' for each of the multiple target battery cells. T-4 The second open-circuit voltage (dV) is the open-circuit voltage deviation calculated at time 'T-3' relative to ). T-3 The first voltage deviation change (ΔdV) is the amount of change in ) T-3 It is possible to calculate ).

[0123] In step S304, for example, the controller 220 calculates the second open-circuit voltage deviation (dV), which is the open-circuit voltage deviation calculated at time 'T-3' for each of the multiple target battery cells. T-3 The third open-circuit voltage deviation (dV) is the open-circuit voltage deviation calculated at time 'T-2' relative to ). T-2 The second voltage deviation change (ΔdV) is the amount of change in ). T-2 It is possible to calculate ).

[0124] In step S304, for example, the controller 220 calculates the third open-circuit voltage deviation (dV), which is the open-circuit voltage deviation calculated at time 'T-2' for each of the multiple target battery cells. T-2 The fourth open-circuit voltage deviation (dV) is the open-circuit voltage deviation calculated at time 'T-1' relative to ). T-1The third voltage deviation change (ΔdV) is the amount of change in ). T-1 It is possible to calculate ).

[0125] In step S304, for example, the controller 220 calculates the fourth open-circuit voltage deviation (dV), which is the open-circuit voltage deviation calculated at time 'T-1' for each of the multiple target battery cells. T-1 The fifth open-circuit voltage deviation (dV) is the open-circuit voltage deviation calculated at time 'T' relative to ). T The fourth voltage deviation change (ΔdV) is the amount of change in ). T It is possible to calculate ).

[0126] In step S304, the controller 220 can calculate the pattern of open-circuit voltage deviation changes for each of the multiple target battery cells. In step S304, for example, the controller 220 calculates the first voltage deviation change (ΔdV) which is the change in the open-circuit voltage deviation for each of the multiple target battery cells calculated at time 'T-3'. T-3 ), the second voltage deviation change (ΔdV), which is the change in the open-circuit voltage deviation of each of the multiple target battery cells calculated at 'T-2'. T-2 ), the third voltage deviation change (ΔdV), which is the change in the open-circuit voltage deviation of each of the multiple target battery cells calculated at 'T-1'. T-1 ), and the fourth voltage deviation change (ΔdV), which is the change in the open-circuit voltage deviation of each of the multiple target battery cells calculated at time 'T'. T Using this method, the pattern of open-circuit voltage deviation change for each of multiple target battery cells can be calculated.

[0127] In step S304, the controller 220 can diagnose at least one target battery cell using the pattern of open-circuit voltage deviation changes for each of the multiple target battery cells. Specifically, in step S304, the controller 220 can diagnose at least one target battery cell based on at least one of the following: the pattern of open-circuit voltage deviation changes for each of the multiple target battery cells, the sum of the open-circuit voltage deviation changes, or the magnitude.

[0128] In step S304, according to the embodiment, the controller 220 can diagnose at least one target battery cell by comparing the pattern of open-circuit voltage deviation change for each of the multiple target battery cells with a plurality of already stored diagnostic patterns. Here, the plurality of already stored diagnostic patterns may include a pattern that diagnoses the state of a battery cell based on the sum of the open-circuit voltage deviation changes (dV) of the target battery cells, a pattern that diagnoses the state of a battery cell based on the magnitude of each open-circuit voltage deviation change (dV) of the target battery cells, a pattern that diagnoses the state of a battery cell based on the maximum or minimum magnitude of the open-circuit voltage deviation change (dV) of the target battery cells, and a pattern that diagnoses the state of a battery cell based on the increasing or decreasing trend of the open-circuit voltage deviation changes (dV) of the target battery cells.

[0129] In step S304, the controller 220 can diagnose that an internal short circuit has occurred in at least one of the target battery cells if the pattern of the open-circuit voltage deviation change of that target battery cell corresponds to one of a plurality of diagnostic patterns.

[0130] Figure 7 is a block diagram showing the hardware configuration of a computing system that implements the operation method of a battery management device according to one embodiment disclosed in this document.

[0131] Referring to Figure 7, the computing system 2000 according to one embodiment disclosed in this document may include an MCU 2100, a memory 2200, an input / output I / F 2300, and a communication I / F 2400.

[0132] The MCU2100 may be a processor that executes various programs stored in the memory 2200 (for example, a battery voltage change analysis program), processes various data through such programs, and performs the functions of the battery management device 200 shown in Figure 1 above.

[0133] The memory 2200 can store various programs related to the operation of the battery management device 200. The memory 2200 can also store the operation data of the battery management device 200.

[0134] Multiple such memory 2200s may be provided as needed. The memory 2200 may be volatile or non-volatile. As volatile memory, RAM, DRAM, SRAM, etc., can be used. As non-volatile memory, ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc., can be used. The examples of memory 2200 listed above are merely illustrative and the system is not limited to these examples.

[0135] The I / O I / F 2300 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 2100, enabling data transmission and reception.

[0136] The communication interface 2400 is configured to send and receive various data with the server and may be various devices that support wired or wireless communication. For example, programs for resistance measurement and anomaly diagnosis, as well as various data, can be sent and received from a separately provided external server via the communication interface 2400.

[0137] The above description is merely illustrative of the technical concept of this disclosure, and any person with ordinary skill in the art to which this disclosure belongs can make various modifications and alterations without departing from the essential characteristics of this disclosure.

[0138] Therefore, the embodiments disclosed herein are for illustrative purposes only, and not to limit the technical concept of the disclosure, and such embodiments do not limit the scope of the technical concept of the disclosure. The scope of protection of this disclosure must be interpreted in accordance with the claims set forth below, and all technical concepts within an equivalent scope should be interpreted as being included in the scope of rights of this disclosure. [Explanation of Symbols]

[0139] 1000: Battery pack 100: Battery Module 110: Battery cell 120: Battery cell 130: Battery cell 140: Battery cell 200:Battery management device 210: Data Management Department 220: Controller 300: Relay 2000: Computing Systems 2100:MCU 2200: Memory 2300: Input / Output Interface 2400: Communication I / F

Claims

1. A data management unit that calculates the degradation level or open-circuit voltage of each of the multiple batteries, Based on the degree of degradation or open-circuit voltage of each of the aforementioned multiple batteries, at least one noise battery is identified. Based on the degree of degradation or open-circuit voltage of each of the at least one noise battery and the service life of each of the at least one noise battery, at least one abnormal battery is identified. A controller that diagnoses at least one target battery based on the deviation of open-circuit voltages among the multiple target batteries, excluding at least one noise battery, A battery management device, including a battery management device.

2. The battery management device according to claim 1, wherein the controller determines that at least one of the plurality of batteries whose degree of degradation or open-circuit voltage is outside the first threshold range is a noise battery.

3. The battery management device according to claim 2, wherein the controller determines that at least one of the noise batteries whose service life falls within the medium-term lifespan and whose degree of degradation or open-circuit voltage is outside the second threshold range is an abnormal battery.

4. The battery management device according to claim 3, wherein the controller sets the first threshold range by reflecting a value obtained by multiplying the average value of the degradation levels of the plurality of batteries by the standard deviation of the degradation levels of the plurality of batteries and a first weight.

5. The battery management device according to claim 4, wherein the controller sets the second threshold range by reflecting a value obtained by multiplying the average value of the degradation levels of the plurality of batteries by the standard deviation of the degradation levels of the plurality of batteries and a second weight.

6. The controller calculates a first value which is the deviation of the change in the open-circuit voltage of each of the multiple batteries from the change in the average value of the open-circuit voltages of the multiple batteries, The battery management device according to claim 3, wherein the first threshold range is set by reflecting a value obtained by multiplying the average value of the plurality of batteries by the standard deviation of the plurality of batteries' first values ​​and a first weight.

7. The battery management device according to claim 6, wherein the controller sets the second threshold range by reflecting a value obtained by multiplying the average value of the first values ​​of the plurality of batteries by the standard deviation of the first values ​​of the plurality of batteries and a second weight.

8. The battery management device according to any one of claims 3 to 7, wherein the controller calculates the deviation of the open-circuit voltage of each of the multiple target batteries from the average value of the open-circuit voltages of the multiple target batteries, and calculates the amount of change in the open-circuit voltage deviation of each of the multiple target batteries.

9. The controller calculates the change in the open-circuit voltage deviation of each of the multiple target batteries at regular intervals, and calculates the pattern of the change in the open-circuit voltage deviation of each of the multiple target batteries. The battery management device according to claim 8, which compares the pattern of open-circuit voltage deviation change for each of the plurality of target batteries with a plurality of diagnostic patterns and diagnoses at least one of the target batteries.

10. The battery management device according to claim 9, wherein the controller diagnoses at least one of the target batteries if the pattern of the open-circuit voltage deviation change of at least one of the target batteries corresponds to any one of the multiple diagnostic patterns.

11. A step of calculating the degree of degradation or open-circuit voltage of each of the multiple batteries, The steps include determining at least one noise battery based on the degree of degradation or open-circuit voltage of each of the plurality of batteries, A step of determining at least one abnormal battery based on the degree of degradation or open-circuit voltage of each of the at least one noise battery and the service life of each of the at least one noise battery, A step of diagnosing at least one target battery based on the deviation of open-circuit voltages among the multiple target batteries, excluding the at least one noise battery, A method for operating a battery management device, including the operation of the battery management device.

12. The step of determining at least one noise battery based on the degree of degradation or open-circuit voltage of each of the plurality of batteries is: A method for operating a battery management device according to claim 11, wherein, among the plurality of batteries, any battery whose degree of degradation or open-circuit voltage is outside the first threshold range is determined to be the at least one noise battery.

13. The step of determining at least one abnormal battery based on the degree of degradation or open-circuit voltage of each of the at least one noise battery and the service life of each of the at least one noise battery is: A method for operating a battery management device according to claim 12, wherein, among the at least one noise battery, the noise battery whose service life falls within the medium-term lifespan and whose degree of degradation or open-circuit voltage is outside the second threshold range is determined to be the at least one abnormal battery.

14. The step of determining at least one noise battery based on the degree of degradation or open-circuit voltage of each of the plurality of batteries is: A method for operating a battery management device according to claim 13, wherein the first threshold range is set by reflecting a value obtained by multiplying the average value of the degradation levels of the plurality of batteries by the standard deviation of the degradation levels of the plurality of batteries and a first weight.

15. The step of determining at least one abnormal battery based on the degree of degradation or open-circuit voltage of each of the at least one noise battery and the service life of each of the at least one noise battery is: The method for operating the battery management device according to claim 14, wherein the second threshold range is set by reflecting a value obtained by multiplying the average value of the degradation levels of the plurality of batteries by the standard deviation of the degradation levels of the plurality of batteries and a second weight.

16. The step of determining at least one noise battery based on the degree of degradation or open-circuit voltage of each of the plurality of batteries is: A first value is calculated, which is the deviation of the change in the open-circuit voltage of each of the plurality of batteries from the change in the average value of the open-circuit voltages of the plurality of batteries. A method for operating a battery management device according to claim 13, wherein the first threshold range is set by reflecting a value obtained by multiplying the average value of the multiple batteries by the standard deviation of the multiple batteries' first values ​​and a first weight.

17. The step of determining at least one abnormal battery based on the degree of degradation or open-circuit voltage of each of the at least one noise battery and the service life of each of the at least one noise battery is: The method for operating the battery management device according to claim 16, wherein the second threshold range is set by reflecting a value obtained by multiplying the average value of the first values ​​of the plurality of batteries by the standard deviation of the first values ​​of the plurality of batteries and a second weight.

18. The step of diagnosing at least one target battery based on the deviation of open-circuit voltages among the multiple target batteries, excluding the at least one noise battery, is: A method for operating a battery management device according to any one of claims 13 to 17, comprising calculating the deviation of the open-circuit voltage of each of the multiple target batteries from the average value of the open-circuit voltages of the multiple target batteries, and calculating the amount of change in the open-circuit voltage deviation of each of the multiple target batteries.

19. The step of diagnosing at least one target battery based on the deviation of open-circuit voltages among the multiple target batteries, excluding the at least one noise battery, is: The amount of change in the open-circuit voltage deviation of each of the multiple target batteries is calculated at regular intervals, and the pattern of the open-circuit voltage deviation change of each of the multiple target batteries is calculated. A method for operating a battery management device according to claim 18, comprising comparing the pattern of open-circuit voltage deviation change for each of the plurality of target batteries with a plurality of diagnostic patterns, and diagnosing at least one of the target batteries.

20. The step of diagnosing at least one target battery based on the deviation of open-circuit voltages among the multiple target batteries, excluding the at least one noise battery, is: A method for operating a battery management device according to claim 19, wherein if the pattern of the open-circuit voltage deviation change amount of at least one of the plurality of target batteries corresponds to one of the plurality of diagnostic patterns, the at least one target battery is diagnosed.

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