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) of each of a plurality of batteries; and a controller that identifies a plurality of target batteries based on a first value which is the deviation of the state of health of each of the plurality of batteries from the average value of the state of health of the plurality of batteries, divides the plurality of target batteries into a plurality of groups based on their state of health, and diagnoses at least one target battery based on the deviation of the open-circuit voltage (OCV) between the plurality of target batteries included in each of the plurality of groups.

Description

Technical Field

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2023-0042995 filed on March 31, 2023, and all the contents disclosed in the literature of the 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] An electric vehicle receives electrical supply from the outside to charge battery cells, and then obtains power by driving a motor with the voltage charged in the battery cells. Battery cells may undergo internal deformation and denaturation due to various charge and discharge cycles during production and use, resulting in changes in their physicochemical properties and possible internal short circuits. When an internal short circuit occurs in a battery cell, a low voltage (Under Voltage) fault may occur where the voltage of the battery cell decreases below a certain level, and direct problems may occur in the battery cell, such as an increased risk of ignition. Therefore, a technique for determining the presence or absence of an internal short circuit in a battery cell is necessary.

[0003] Conventional battery management devices diagnose internal short circuits by determining relative voltage deviations according to the connection order of battery cells without considering the difference in the degree of degradation (SOH) of each battery cell in a battery system where a plurality of battery cells are combined. Such a method has limitations in that it cannot consider capacity deviations due to cumulative use and natural degradation of battery cells and cannot detect voltage fluctuations in battery cells caused by actual internal short circuits.

Summary of the Invention

Problems to be Solved by the Invention

[0004] An object of an embodiment disclosed in this document is to provide a battery management device and an operating method thereof 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) of each of a plurality of batteries; and a controller that identifies a plurality of target batteries based on a first value which is the deviation of the state of health of each of the plurality of batteries from the average value of the state of health of the plurality of batteries, divides the plurality of target batteries into a plurality of groups based on their state of health, and diagnoses at least one target battery based on the deviation of the open-circuit voltage (OCV) between the plurality of target batteries included in each of the plurality of groups.

[0007] According to one embodiment, the controller can identify among the plurality of batteries that have a first value less than a threshold as the plurality of target batteries.

[0008] According to one embodiment, the controller can divide the plurality of target batteries into a plurality of groups according to the order in which they are arranged from most to least degraded.

[0009] According to one embodiment, the controller can calculate the deviation of the open-circuit voltage of each of the multiple target batteries included in each of the multiple groups from the average value of the open-circuit voltages of the multiple target batteries included in each of the multiple groups, and can calculate the amount of change in the open-circuit voltage deviation of each of the multiple target batteries included in each of the multiple groups.

[0010] 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.

[0011] 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.

[0012] 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) of each of a plurality of batteries; calculating a first value which is the deviation of the state of health of each of the plurality of batteries from the average value of the state of health of the plurality of batteries; identifying a plurality of target batteries based on the first value of each of the plurality of batteries; dividing the plurality of target batteries into a plurality of groups based on their state of health; and diagnosing at least one target battery based on the deviation of the open-circuit voltage (OCV) between the plurality of target batteries included in each of the plurality of groups.

[0013] According to one embodiment, the step of identifying a plurality of target batteries based on the first value of each of the plurality of batteries allows for the identification of batteries among the plurality of batteries whose first value is less than a threshold as the plurality of target batteries.

[0014] According to one embodiment, the step of dividing the plurality of target batteries into a plurality of groups based on their degree of degradation can be performed by dividing the plurality of target batteries into a plurality of groups in order of decreasing degree of degradation.

[0015] According to one embodiment, the step of diagnosing at least one target battery based on the deviation of open-circuit voltages between multiple target batteries included in each of the multiple groups can be performed by calculating the deviation of the open-circuit voltage of each of the multiple target batteries with respect to the average value of the open-circuit voltages of the multiple target batteries included in each of the multiple groups, and by calculating the amount of change in the open-circuit voltage deviation of each of the multiple target batteries included in each of the multiple groups.

[0016] According to one embodiment, the step of diagnosing at least one target battery based on the open-circuit voltage deviation between a plurality of target batteries included in each of the plurality of groups 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.

[0017] According to one embodiment, the step of diagnosing at least one target battery based on the deviation of open-circuit voltages between a plurality of target batteries included in each of the plurality of groups can diagnose the at least one target battery 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]

[0018] 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]

[0019] [Figure 1] This figure shows a battery pack according to one embodiment disclosed in this document. [Figure 2]It is a block diagram showing the configuration of a battery management device according to an embodiment disclosed in this document. [Figure 3] It is a table showing the degree of deterioration of battery cells according to an embodiment disclosed in this document. [Figure 4] It is a table showing the first value of battery cells according to an embodiment disclosed in this document. [Figure 5] It is a table in which target battery cells according to an embodiment disclosed in this document are arranged in descending order based on the degree of deterioration. [Figure 6] It is a flowchart showing a method for diagnosing target battery cells of a controller according to an embodiment disclosed in this document. [Figure 7] It is a flowchart showing an operation method of a battery management device according to an embodiment disclosed in this document. [Figure 8] It is a block diagram showing the hardware configuration of a computing system that realizes the operation method of a battery management device according to an embodiment disclosed in this document.

Modes for Carrying Out the Invention

[0020] Hereinafter, some embodiments disclosed in this document will be described in detail with reference to exemplary drawings. It should be noted that when assigning reference numerals to the components of each drawing, the same components are assigned the same numerals as much as possible when they are shown on other drawings. Also, in describing the embodiments disclosed in this document, if a specific description of a related known configuration or function is determined to interfere with the understanding of the embodiments disclosed in this document, the detailed description thereof will be omitted.

[0021] In describing the components of the embodiments disclosed in this document, terms such as first, second, A, B, (a), (b), etc. may be used. Such terms are merely for distinguishing the components from other components, and the essence, sequence, or order of the components is not limited by such terms. Also, unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by those with ordinary knowledge in the technical field to which the embodiments disclosed in this document belong. Terms defined in commonly used dictionaries should be interpreted as having meanings consistent with the context of the related art, and should not be interpreted in an ideal or overly formal sense unless clearly defined in this document.

[0022] FIG. 1 is a diagram showing a battery pack according to an embodiment disclosed in this document. Referring to FIG. 1, a battery pack 1000 according to an embodiment disclosed in this document can 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, and in this case, the battery pack 1000 may have a cell-to-pack structure.

[0023] Although only one battery module 100 is shown in FIG. 1, the battery pack 1000 can have a stacked structure formed by a plurality of battery modules. The battery module 100 can include a plurality of battery cells 110, 120, 130, 140. Although FIG. 1 shows that there are four battery cells, it is not limited thereto, and the battery module 100 can be configured to include n (n is a natural number greater than or equal to 2) battery cells.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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).

[0029] Multiple battery cells 110, 120, 130, and 140 may experience a decrease in capacity, an increase in internal resistance, and changes in various battery characteristics as their usage period or number of uses increases. The battery management device 200 can diagnose abnormal phenomena within the multiple battery cells 110, 120, 130, and 140 based on data of various factors that change as the battery deteriorates.

[0030] 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.

[0031] 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.

[0032] First, the battery management device 200 compares the average state of health (SOH) of multiple battery cells 110, 120, 130, and 140 contained in the battery pack 1000 with the state of health of each of the multiple battery cells 110, 120, 130, and 140, and can identify multiple target battery cells, excluding those suspected of having noise voltage. After identifying the multiple target battery cells, the battery management device 200 can diagnose battery cells that have experienced an internal short circuit using the change in the open-circuit voltage deviation (dV) of the multiple target battery cells contained in the battery pack 1000.

[0033] 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.

[0034] 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.

[0035] 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) of each of the multiple battery cells 110, 120, 130, and 140. The 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). The end of life of a battery can also 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 state of health (SOH) of the multiple battery cells 110, 120, 130, and 140 based on at least one of the following factors that change as the multiple battery cells 110, 120, 130, and 140 degrade: internal resistance, impedance, conductance, capacity, voltage, self-discharge current, charging performance, and charge / discharge cycles.

[0036] 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 can calculate OCV_A, which is the open-circuit voltage before charging, and OCV_B, which is the open-circuit voltage after charging, for multiple battery cells 110, 120, 130, and 140.

[0037] The data management unit 210 can calculate SOC_A and SOC_B by converting OCV_A and OCV_B, respectively, into charge amounts, i.e., State of Charge (SOC), based on the open-circuit voltage table (OCV Table). 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].

[0038] [Formula 1] SOHC=I / ((SOC_B-SOC_A) / 100*X)*100

[0039] 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 1], 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.

[0040] Figure 3 is a table showing the degree of degradation of a battery cell according to one embodiment disclosed in this document. Referring to Figure 3, the data management unit 210 can calculate the individual state of health (SOH), or SOHC, of ​​multiple battery cells.

[0041] According to the embodiment, the battery pack 1000 has a stacked structure in which four battery modules 100 are arranged, and each of the multiple battery modules 100 can have 10 battery cells connected to each other in series or in parallel. That is, the battery pack 1000 can contain, for example, 40 battery cells, and each of the four battery modules can be assigned a unique battery module number, and each of the 40 battery cells contained in the battery modules can be assigned a unique battery cell number. The data management unit 210 can calculate the individual state of health (SOH), i.e., SOHC, of ​​the 40 battery cells contained in the battery pack 1000.

[0042] The controller 220 can diagnose at least one of the multiple battery cells 110, 120, 130, and 140 based on the individual degradation level (SOHC) of each of the multiple battery cells 110, 120, 130, and 140.

[0043] First, the controller 220 can identify multiple target battery cells based on the degradation levels of multiple battery cells 110, 120, 130, and 140.

[0044] Figure 4 is a table showing first values ​​for a battery cell according to one embodiment disclosed in this document. Referring to Figure 4, for example, the controller 220 can calculate the average degradation level of the 40 battery cells contained in the battery module 100. For example, the controller 220 can calculate the average value of the individual degradation levels (SOH), i.e., SOHC, of ​​the 40 battery cells contained in the battery module 100 as "98.39%".

[0045] The controller 220 can calculate a first value, which is the deviation of the degradation level of each battery cell from the average degradation level of multiple battery cells. For example, if the individual degradation level (SOHC) of battery cell number 1 is "98.83%", the controller 220 can calculate the first value of battery cell number 1 as "-0.44%".

[0046] The controller 220 can identify multiple battery cells 110, 120, 130, and 140 in which the first value is below a threshold as target battery cells. Here, the threshold can be defined as the criterion by which an extreme result occurs and can be judged as "abnormal." In other words, the threshold can be defined as the criterion that indicates how much the data contradicts a particular statistical model. If a battery cell in which the first value exceeds the threshold is identified as a noisy battery cell among the multiple battery cells 110, 120, 130, and 140, the controller 220 can remove the data from the noisy battery cell and identify the battery cell from which the noisy battery cell has been removed as a target battery cell.

[0047] For example, the controller 220 can exclude three noisy battery cells out of 40 battery cells, where the first value, which is the deviation of the battery cell degradation degree from the average degradation degree of the battery cells "98.39%", exceeds the threshold "2%", and identify the remaining 37 battery cells as target battery cells.

[0048] Figure 5 is a table showing target battery cells according to one embodiment disclosed in this document, arranged in descending order based on their degree of degradation. Referring to Figure 5, the controller 220 can divide multiple target battery cells into multiple groups based on their degree of degradation. Specifically, the controller 220 can arrange multiple target battery cells based on their degree of degradation and divide them into multiple groups according to the order in which the multiple target battery cells are arranged.

[0049] The controller 220 can sort multiple target battery cells in descending order of degradation level. In other words, the controller 220 can sort multiple target battery cells in descending order based on their degradation level. For example, the controller 220 can sort 37 target battery cells out of 100 battery cells in the battery pack 1000, excluding noise battery cells, in descending order based on the degradation level of the battery cells.

[0050] The controller 220 can sort multiple target battery cells in descending order of degradation and divide battery cells with similar degradation levels into multiple groups for diagnosis. For example, the controller 220 can sort 37 target battery cells based on their degradation level and divide them into four groups, each containing 8 to 10 battery cells.

[0051] The controller 220 can diagnose at least one target battery cell based on the deviation of the open-circuit voltage (OCV) between multiple target battery cells included in each of the multiple groups.

[0052] Figure 6 is a flowchart showing a method for diagnosing a target battery cell of a controller according to one embodiment disclosed in this document. Referring to Figure 6, a method for diagnosing at least one target battery cell based on the deviation of the open-circuit voltage (OCV) between target battery cells in the controller 220 will be specifically described.

[0053] In step S101, the controller 220 can determine whether the multiple target battery cells included in each of the multiple groups are in an open-circuit voltage (OCV) relaxation state. Here, voltage relaxation refers to the phenomenon in which, when the 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 target battery cells included in each of the multiple groups has a voltage jitter of 20mV or less for 4 hours under no load, the controller 220 can determine that the multiple target battery cells are in a voltage relaxation state.

[0054] In step S101, the controller 220 can check whether a certain period of time has elapsed since the multiple target battery cells included in each of the multiple groups were determined to be in a voltage relaxation state. For example, in step S101, the controller 220 can check whether 10 days have elapsed since the multiple target battery cells included in each of the multiple groups were determined to be in a voltage relaxation state.

[0055] In step S102, the controller 220 can measure the open-circuit voltage of each of the multiple target battery cells included in each of the multiple groups after a set period of time has elapsed.

[0056] In step S102, the controller 220 can calculate the average value of the open-circuit voltages of multiple target battery cells included in each of the multiple groups. In step S102, the controller 220 can calculate the average value of the open-circuit voltages for each of the multiple groups formed by dividing multiple target battery cells with similar degradation levels. In step S102, for example, the controller 220 can classify 37 target battery cells into a first group (G1), a second group (G2), a third group (G3), and a fourth group (G4), and calculate the average value of the open-circuit voltages for the first group (G1) (Vavg_1), the second group (G2) (Vavg_2), the third group (G3) (Vavg_3), and the fourth group (G4) (Vavg_4), respectively.

[0057] In step S103, 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 S103, for example, the controller 220 can calculate the deviation of the open-circuit voltage of each of the multiple target battery cells included in the first group (G1) relative to the average value (Vavg_1) of the open-circuit voltage of the first group (G1).

[0058] In step S103, 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 S103, the controller 220 can calculate the first open-circuit voltage deviation (dV_"T-4"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T-4'; the second open-circuit voltage deviation (dV_"T-3"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T-3'; the third open-circuit voltage deviation (dV_"T-2"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T-2'; the fourth open-circuit voltage deviation (dV_"T-1"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T-1'; and the fifth open-circuit voltage deviation (dV_"T"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T'.

[0059] In step S104, the controller 220 can calculate the change in open-circuit voltage deviation (△dV) for each of the multiple target battery cells included in each of the multiple groups. Specifically, in step S104, the controller 220 can continuously calculate the open-circuit voltage for each of the multiple target battery cells at regular intervals and calculate the change in open-circuit voltage deviation (△dV) for each of the multiple target battery cells calculated in the current period relative to the open-circuit voltage deviation for each of the multiple target battery cells calculated in the previous period.

[0060] In step S104, the controller 220 can continuously calculate the change in the open-circuit voltage deviation (△dV) of each of the multiple target battery cells at a constant period.

[0061] In step S104, for example, the controller 220 can calculate the first voltage deviation change (△dV_"T-3"), which is the change in the second open-circuit voltage deviation (dV_"T-3") calculated at 'T-3', relative to the first open-circuit voltage deviation (dV_"T-4"), which is the open-circuit voltage deviation calculated at 'T-3' for each of the multiple target battery cells.

[0062] In step S104, for example, the controller 220 can calculate the second voltage deviation change amount (△dV_"T-2"), which is the change in the third open-circuit voltage deviation (dV_"T-2") calculated at time 'T-2' relative to the second open-circuit voltage deviation (dV_"T-3"), which is the open-circuit voltage deviation calculated at time 'T-3' for each of the multiple target battery cells.

[0063] In step S104, for example, the controller 220 can calculate the change in the third voltage deviation (△dV_"T-1"), which is the change in the fourth open-circuit voltage deviation (dV_"T-1") calculated at time 'T-1', relative to the third open-circuit voltage deviation (dV_"T-2"), which is the open-circuit voltage deviation calculated at time 'T-2' for each of the multiple target battery cells.

[0064] In step S104, for example, the controller 220 can calculate the fourth voltage deviation change amount (△dV_"T"), which is the change in the fifth open-circuit voltage deviation (dV_"T") calculated at time 'T', relative to the fourth open-circuit voltage deviation (dV_"T-1"), which is the open-circuit voltage deviation calculated at time 'T-1' for each of the multiple target battery cells.

[0065] In step S105, the controller 220 can calculate the pattern of the open-circuit voltage deviation change for each of the multiple target battery cells. In step S105, for example, the controller 220 can calculate the pattern of the open-circuit voltage deviation change for each of the multiple target battery cells using the first voltage deviation change (△dV_"T-3"), which is the change in the open-circuit voltage deviation for each of the multiple target battery cells calculated at 'T-3', the second voltage deviation change (△dV_"T-2"), which is the change in the open-circuit voltage deviation for each of the multiple target battery cells calculated at 'T-2', the third voltage deviation change (△dV_"T-1"), which is the change in the open-circuit voltage deviation for each of the multiple target battery cells calculated at 'T-1', and the fourth voltage deviation change (△dV_"T"), which is the change in the open-circuit voltage deviation for each of the multiple target battery cells calculated at 'T'.

[0066] In step S106, 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 S106, 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.

[0067] In step S106, 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 change (dV) of the target battery cells.

[0068] 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.

[0069] 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.

[0070] 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.

[0071] 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 improve the accuracy of internal short-circuit diagnosis by relatively comparing battery cells with similar levels of degradation.

[0072] 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.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] Referring to Figure 6, the operation method of the battery management device may include the steps of: calculating the state of health (SOH) of each of the multiple batteries (S201); calculating a first value which is the deviation of the state of health of each of the multiple batteries from the average value of the state of health of the multiple batteries (S202); identifying multiple target battery cells based on the first value of each of the multiple batteries (S203); dividing the multiple target battery cells into multiple groups based on their state of health (S204); and diagnosing at least one target battery cell based on the deviation of the open-circuit voltage (OCV) between the multiple target batteries included in each of the multiple groups (S205).

[0077] The following provides a detailed explanation of steps S201 through S205. In step S201, the data management unit 210 can calculate the state of health (SOH) of each of the multiple battery cells 110, 120, 130, and 140. The state of health (SOH) is an indicator that can show the health or lifespan of the battery in its current state relative to its initial state. In step S201, 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 of the following factors that change as the multiple battery cells 110, 120, 130, and 140 degrade: internal resistance, impedance, conductance, capacity, voltage, self-discharge current, charging performance, and charge / discharge cycles.

[0078] In step S201, 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.

[0079] In step S201, specifically, the battery management device 200 can calculate OCV_A, which is the open-circuit voltage before charging, and OCV_B, which is the open-circuit voltage after charging, for multiple battery cells 110, 120, 130, and 140. In step S201, the data management unit 210 can calculate SOC_A and SOC_B by converting OCV_A and OCV_B, respectively, into charge amounts, i.e., SOC, based on the open-circuit voltage table (OCV Table). 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].

[0080] [Formula 1] SOHC=I / ((SOC_B-SOC_A) / 100*X)*100

[0081] 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. In step S201, 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 based on [Equation 1].

[0082] In step S201, the data management unit 210 can calculate the individual state of health (SOH), or SOHC, of ​​multiple battery cells. In step S201, according to the embodiment, the battery pack 1000 has a stacked structure in which four battery modules 100 are arranged, and each of the multiple battery modules 100 can have 10 battery cells connected to each other in series or in parallel. That is, the battery pack 1000 can contain, for example, 40 battery cells, each of the four battery modules can be assigned a unique battery module number, and each of the 40 battery cells contained in the battery modules can be assigned a unique battery cell number. In step S201, the data management unit 210 can calculate the individual state of health (SOH), i.e., SOHC, of ​​the 40 battery cells contained in the battery pack 1000.

[0083] In step S202, the controller 220 can calculate the average value of the degradation levels of the 40 battery cells included in the battery module 100.

[0084] In step S202, the controller 220 can calculate a first value, which is the deviation of the degradation degree of each of the multiple battery cells from the average value of the degradation degrees of the multiple battery cells.

[0085] In step S203, the controller 220 can identify several battery cells 110, 120, 130, and 140 in which the first value is less than the threshold as multiple target battery cells.

[0086] In step S203, the controller 220 can determine from among the multiple battery cells 110, 120, 130, and 140 that any battery cell whose first value exceeds a threshold is a noisy battery cell, remove the data from the noisy battery cell, and identify the battery cell from which the noisy battery cell has been removed as the target battery cell.

[0087] In step S203, for example, the controller 220 can exclude three noisy battery cells out of the 40 battery cells, where the first value, which is the deviation of the battery cell degradation degree from the average degradation degree of the battery cells "98.39%", exceeds the threshold "2%", and identify the remaining 37 battery cells as target battery cells.

[0088] In step S204, the controller 220 can divide the multiple target battery cells into multiple groups based on their degree of degradation. Specifically, in step S204, the controller 220 can arrange the multiple target battery cells based on their degree of degradation and divide them into multiple groups according to the order in which the multiple target battery cells are arranged. In step S204, according to the embodiment, the controller 220 can arrange the multiple target battery cells in descending order of their degree of degradation. That is, the controller 220 can arrange the multiple target battery cells in descending order based on their degree of degradation.

[0089] In step S204, the controller 220 can arrange multiple target battery cells based on their degradation level and divide battery cells with similar degradation levels into multiple groups for diagnosis. In step S204, for example, the controller 220 can arrange 37 target battery cells based on their degradation level and divide them into four groups, each containing 8 to 10 battery cells.

[0090] In step S205, the controller 220 can diagnose at least one target battery cell based on the deviation of the open-circuit voltage (OCV) between multiple target battery cells, each included in a group.

[0091] In step S205, the controller 220 can determine whether the multiple target battery cells included in each of the multiple groups are in an open-circuit voltage (OCV) relaxation state. Here, voltage relaxation refers to the phenomenon in which, when the 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.

[0092] In step S205, the controller 220 can check whether a certain period of time has elapsed since the multiple target battery cells included in each of the multiple groups were determined to be in a voltage relaxation state. For example, in step S205, the controller 220 can check whether 10 days have elapsed since the multiple target battery cells included in each of the multiple groups were determined to be in a voltage relaxation state.

[0093] In step S205, the controller 220 can measure the open-circuit voltage of each of the multiple target battery cells included in each of the multiple groups after a predetermined period of time has elapsed.

[0094] In step S205, the controller 220 can calculate the average value of the open-circuit voltages of multiple target battery cells included in each of the multiple groups. That is, the controller 220 can calculate the average value of the open-circuit voltages for each of the multiple groups into which multiple target battery cells with similar degradation levels are divided. In step S205, for example, the controller 220 can classify 37 target battery cells into a first group (G1), a second group (G2), a third group (G3), and a fourth group (G4), and calculate the average value of the open-circuit voltage for the first group (G1) (Vavg_1), the average value of the open-circuit voltage for the second group (G2) (Vavg_2), the average value of the open-circuit voltage for the third group (G3) (Vavg_3), and the average value of the open-circuit voltage for the fourth group (G4) (Vavg_4), respectively.

[0095] In step S205, 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 S205, for example, the controller 220 can calculate the deviation of the open-circuit voltage of each of the multiple target battery cells included in the first group (G1) relative to the average value (Vavg_1) of the open-circuit voltage of the first group (G1).

[0096] In step S205, the controller 220 can calculate the change in open-circuit voltage deviation (△dV) for each of the multiple target battery cells included in each of the multiple groups. In step S205, the controller 220 can continuously calculate the open-circuit voltage for each of the multiple target battery cells at regular intervals and calculate the change in open-circuit voltage deviation (△dV) for each of the multiple target battery cells calculated in the current period relative to the open-circuit voltage deviation for each of the multiple target battery cells calculated in the previous period. In step S205, the controller 220 can continuously calculate the change in open-circuit voltage deviation (△dV) for each of the multiple target battery cells at regular intervals.

[0097] In step S205, 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'.

[0098] In step S205, the controller 220 can calculate the first open-circuit voltage deviation (dV_"T-4"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T-4'; the second open-circuit voltage deviation (dV_"T-3"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T-3'; the third open-circuit voltage deviation (dV_"T-2"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T-2'; the fourth open-circuit voltage deviation (dV_"T-1"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T-1'; and the fifth open-circuit voltage deviation (dV_"T"), which is the deviation of the open-circuit voltage of each target battery cell calculated at time 'T'.

[0099] In step S205, the controller 220 can calculate the first voltage deviation change (△dV_"T-3"), which is the change in the second open-circuit voltage deviation (dV_"T-3") calculated at 'T-3', relative to the first open-circuit voltage deviation (dV_"T-4"), which is the open-circuit voltage deviation calculated at 'T-3' for each of the multiple target battery cells.

[0100] In step S205, the controller 220 can calculate the second voltage deviation change (△dV_"T-2"), which is the change in the third open-circuit voltage deviation (dV_"T-2") calculated at time 'T-2', relative to the second open-circuit voltage deviation (dV_"T-3"), which is the open-circuit voltage deviation calculated at time 'T-3' for each of the multiple target battery cells.

[0101] In step S205, the controller 220 can calculate the change in the third voltage deviation (△dV_"T-1"), which is the change in the fourth open-circuit voltage deviation (dV_"T-1") calculated at time 'T-1', relative to the third open-circuit voltage deviation (dV_"T-2"), which is the open-circuit voltage deviation calculated at time 'T-2' for each of the multiple target battery cells.

[0102] In step S205, the controller 220 can calculate the fourth voltage deviation change amount (△dV_"T"), which is the change in the fifth open-circuit voltage deviation (dV_"T") calculated at time 'T', relative to the fourth open-circuit voltage deviation (dV_"T-1"), which is the open-circuit voltage deviation calculated at time 'T-1' for each of the multiple target battery cells.

[0103] In step S205, the controller 220 can calculate the pattern of open-circuit voltage deviation changes for each of the multiple target battery cells. For example, the controller 220 can calculate the pattern of open-circuit voltage deviation changes for each of the multiple target battery cells using the first voltage deviation change (△dV_"T-3"), which is the change in open-circuit voltage deviation for each of the multiple target battery cells calculated at 'T-3', the second voltage deviation change (△dV_"T-2"), which is the change in open-circuit voltage deviation for each of the multiple target battery cells calculated at 'T-2', the third voltage deviation change (△dV_"T-1"), which is the change in open-circuit voltage deviation for each of the multiple target battery cells calculated at 'T-1', and the fourth voltage deviation change (△dV_"T"), which is the change in open-circuit voltage deviation for each of the multiple target battery cells calculated at 'T'.

[0104] 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 the open-circuit voltage deviation change for each of the multiple target battery cells, the sum of the open-circuit voltage deviation changes, or the magnitude.

[0105] 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 change (dV) of the target battery cells.

[0106] In step S205, 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.

[0107] In step S205, 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. In step S205, 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, etc.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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]

[0117] 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 degree of degradation of each of the multiple batteries, Multiple target batteries are identified based on a first value which is the deviation of the degradation degree of each of the multiple batteries from the average value of the degradation degrees of the multiple batteries. The aforementioned multiple target batteries are divided into multiple groups based on their degree of degradation, A controller that diagnoses at least one target battery based on the deviation of open-circuit voltages between multiple target batteries included in each of the aforementioned multiple groups, A battery management device, including a battery management device.

2. The battery management device according to claim 1, wherein the controller identifies among the plurality of batteries that have a first value less than a threshold as the plurality of target batteries.

3. The battery management device according to claim 2, wherein the controller divides the plurality of target batteries into a plurality of groups according to an order in which they are arranged in descending order of degradation.

4. The battery management device according to claim 3, wherein the controller calculates the deviation of the open-circuit voltage of each of the multiple target batteries included in each of the multiple groups from the average value of the open-circuit voltages of the multiple target batteries included in each of the multiple groups, and calculates the amount of change in the open-circuit voltage deviation of each of the multiple target batteries included in each of the multiple groups.

5. The battery management device according to claim 4, wherein the controller calculates the amount of change in the open-circuit voltage deviation of each of the plurality of target batteries at regular intervals, calculates the pattern of the amount of change in the open-circuit voltage deviation of each of the plurality of target batteries, compares 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 diagnoses at least one target battery.

6. The battery management device according to claim 5, wherein the controller diagnoses 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 plurality of target batteries corresponds to one of the plurality of diagnostic patterns.

7. A step to calculate the degree of degradation of each of the multiple batteries, A step of calculating a first value which is the deviation of the degradation degree of each of the plurality of batteries from the average value of the degradation degrees of the plurality of batteries, A step of identifying a plurality of target batteries based on the first value of each of the plurality of batteries, The steps include dividing the aforementioned multiple target batteries into multiple groups based on their degree of degradation, A step of diagnosing at least one target battery based on the deviation of open-circuit voltages between multiple target batteries included in each of the aforementioned multiple groups, A method for operating a battery management device, including the operation of the battery management device.

8. The method for operating a battery management device according to claim 7, wherein the step of identifying a plurality of target batteries based on the first value of each of the plurality of batteries is to identify the batteries among the plurality of batteries whose first value is less than a threshold as the plurality of target batteries.

9. The method of operating the battery management device according to claim 8, wherein the step of dividing the plurality of target batteries into a plurality of groups based on their degree of degradation is to divide the plurality of target batteries into a plurality of groups according to the order in which they are arranged in descending order of their degree of degradation.

10. The method for operating a battery management device according to claim 9, comprising the step of diagnosing at least one target battery based on the deviation of open-circuit voltages between multiple target batteries included in each of the multiple groups, the calculation of the deviation of the open-circuit voltage of each of the multiple target batteries with respect to the average value of the open-circuit voltages of the multiple target batteries included in each of the multiple groups, and the calculation of the amount of change in the open-circuit voltage deviation of each of the multiple target batteries included in each of the multiple groups.

11. The method for operating a battery management device according to claim 10, comprising the steps of diagnosing at least one target battery based on the deviation of open-circuit voltages between a plurality of target batteries included in each of the plurality of groups, 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.

12. The method of operating a battery management device according to claim 11, wherein the step of diagnosing at least one target battery based on the deviation of open-circuit voltages between a plurality of target batteries included in each of the plurality of groups is to diagnose the at least one target battery 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.

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