Battery management device and its operating method

Abstract

A battery management device according to one embodiment disclosed herein may include: a voltage measuring unit that measures the voltage of each of a plurality of battery cells; a controller that calculates a first deviation for each of the plurality of battery cells, which is the difference between the long-term moving average and the short-term moving average of the battery cell voltages; calculates a second deviation for each of the plurality of battery cells, which is the difference between the long-term moving average and the short-term moving average of the average voltage of the plurality of battery cells; calculates a first diagnostic deviation for each of the plurality of battery cells, which is the difference between the first deviation and the second deviation; and diagnoses each of the plurality of battery cells based on whether the final diagnostic deviation related to the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above the second threshold.

Description

Technical Field

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2023-0091278 filed on July 13, 2023, and all the contents disclosed in the literature of the patent application are incorporated herein by reference as part of this specification. 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 a battery cell, and then obtains power by driving a motor with the voltage charged in the battery cell. The battery cell undergoes internal deformation and denaturation due to various charge and discharges during the production and use stages, resulting in changes in physical and chemical properties, and may cause problems such as internal short circuits, external short circuits, venting due to lithium precipitation, or under-voltage failures where the voltage of the battery cell decreases below a certain level.

[0003] When a defect occurs inside the battery cell, the performance of the battery cell may deteriorate, and direct problems may occur in the battery cell, such as an increase in the possibility of ignition due to leakage of the electrolyte. Therefore, a technique for determining the presence or absence of abnormalities in the battery cell is required.

[0004] Conventional battery management devices have diagnosed voltage abnormalities in battery cells using the deviation of the voltage of individual battery cells with respect to the average voltage of the battery cells. However, such a method is vulnerable to noise and cannot adjust the threshold, which is the diagnostic criterion for abnormal battery cells, below a certain level, and has the limitation that it cannot detect abnormal voltages of battery cells due to fine disconnections occurring in electric vehicles.

Summary of the Invention

Problems to be Solved by the Invention

[0005] One objective of the embodiments disclosed in this document is to provide a battery management device and its operating method that can remove noise from the deviation between the long-term moving average and short-term moving average voltages of a battery cell and accurately diagnose abnormal battery cells.

[0006] Furthermore, one objective of the embodiments disclosed in this document is to provide a battery management device and its operating method that can distinguish voltage behavior caused by external resistance or the environment, rather than by internal cell causes.

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

[0008] A battery management device according to one embodiment disclosed herein may include: a voltage measuring unit that measures the voltage of each of a plurality of battery cells; a controller that calculates a first deviation for each of the plurality of battery cells, which is the difference between the long-term moving average and the short-term moving average of the battery cell voltages; calculates a second deviation for each of the plurality of battery cells, which is the difference between the long-term moving average and the short-term moving average of the average voltage of the plurality of battery cells; calculates a first diagnostic deviation for each of the plurality of battery cells, which is the difference between the first deviation and the second deviation; and diagnoses each of the plurality of battery cells based on whether the final diagnostic deviation related to the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above the second threshold.

[0009] In one embodiment, the controller determines a battery cell whose final diagnostic deviation is equal to or greater than the first threshold as a diagnostic battery cell, and if the final diagnostic deviation of the diagnostic battery cell is maintained at or greater than the second threshold within a first hour based on the time of diagnosis, the controller can diagnose the diagnostic battery cell as abnormal.

[0010] In one embodiment, if the final diagnostic deviation of the diagnostic battery cell is not maintained at or above the second threshold within the first hour based on the diagnostic time, it can be determined that the diagnostic battery cell has been misdiagnosed.

[0011] In one embodiment, the first time can be determined in relation to the time used to calculate the long-term moving average. In one embodiment, the second threshold is less than the first threshold, and the second threshold can be determined based on the first threshold.

[0012] In one embodiment, the controller can normalize the first diagnostic deviation of each of the plurality of battery cells to calculate a second diagnostic deviation for each of the plurality of battery cells, and calculate the second diagnostic deviation for each of the plurality of battery cells as the final diagnostic deviation.

[0013] The operation method of a battery management device according to one embodiment disclosed herein may include: measuring the voltage of each of a plurality of battery cells; calculating a first deviation for each of the plurality of battery cells, which is the difference between the long-term moving average and the short-term moving average of the battery cell voltages; calculating a second deviation for each of the plurality of battery cells, which is the difference between the long-term moving average and the short-term moving average of the average voltage of the plurality of battery cells; calculating a first diagnostic deviation for each of the plurality of battery cells, which is the difference between the first deviation and the second deviation; and diagnosing each of the plurality of battery cells based on whether the final diagnostic deviation related to the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above a second threshold.

[0014] In one embodiment, the operation of diagnosing each of the plurality of battery cells based on whether the final diagnostic deviation related to the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above a second threshold, may include the operation of determining a battery cell whose final diagnostic deviation is greater than or equal to the first threshold as a diagnostic battery cell, and the operation of determining that the diagnostic battery cell is abnormal if the final diagnostic deviation of the diagnostic battery cell is maintained at or above the second threshold for a first hour from the time of diagnosis, and determining that the diagnostic battery cell has been misdiagnosed if the final diagnostic deviation of the diagnostic battery cell is not maintained at or above the second threshold for a first hour from the time of diagnosis.

[0015] In one embodiment, the first time can be determined in relation to the time used to calculate the long-term moving average. In one embodiment, the second threshold is less than the first threshold, and the second threshold can be determined based on the first threshold.

[0016] In one embodiment, the operation of diagnosing each of the plurality of battery cells based on whether the final diagnostic deviation associated with the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above a second threshold, may include the operation of normalizing the first diagnostic deviation of each of the plurality of battery cells to calculate the second diagnostic deviation of each of the plurality of battery cells, and the operation of calculating the second diagnostic deviation of each of the plurality of battery cells as the final diagnostic deviation. [Effects of the Invention]

[0017] A battery management device and its operating method according to one embodiment disclosed herein can remove noise from the deviation between the long-term moving average value and the short-term moving average value of the battery cell voltage, and accurately diagnose abnormal battery cells.

[0018] In addition, the battery management device and its operation method according to an embodiment disclosed in this document can analyze the deviation results between the long-term moving average value and the short-term moving average value, and distinguish the voltage behavior of the battery cell due to the external environment from the voltage behavior due to actual abnormalities.

[0019] In addition, the battery management device and its operation method according to an embodiment disclosed in this document can reduce the misdiagnosis rate due to external factors. In addition, various effects that can be directly or indirectly grasped can be provided according to this document.

Brief Description of Drawings

[0020] [Figure 1] It is a diagram showing a battery cell pack according to an 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 graph showing the voltage of a battery cell according to an embodiment disclosed in this document. [Figure 4] It is a flowchart showing a method for diagnosing a battery cell of a controller according to an embodiment disclosed in this document. [Figure 5a] It is a diagram for explaining an example of distinguishing the voltage behavior of a battery cell due to the external environment from the voltage behavior due to actual abnormalities according to another embodiment disclosed in this document. [Figure 5b] It is a diagram for explaining an example of distinguishing the voltage behavior of a battery cell due to the external environment from the voltage behavior due to actual abnormalities according to another embodiment disclosed in this document. [Figure 5c] It is a diagram for explaining an example of distinguishing the voltage behavior of a battery cell due to the external environment from the voltage behavior due to actual abnormalities according to another embodiment disclosed in this document. [Figure 5d] It is a diagram for explaining an example of distinguishing the voltage behavior of a battery cell due to the external environment from the voltage behavior due to actual abnormalities according to another embodiment disclosed in this document. [Figure 5e]This is a diagram for explaining an example of distinguishing the voltage behavior of a battery cell according to the external environment in other embodiments disclosed in this document from the voltage behavior due to an actual abnormality. [Figure 6] This 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. **Embodiments for Carrying Out the Invention**

[0021] Hereinafter, some embodiments disclosed in this document will be described in detail with reference to exemplary drawings. It should be noted that when attaching reference numerals to the components of each drawing, the same components are given the same numerals as much as possible when displayed on other drawings. Also, when explaining the embodiments disclosed in this document, if a specific explanation of a related known configuration or function is judged to impede the understanding of the embodiments disclosed in this document, the detailed explanation thereof will be omitted.

[0022] When explaining 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 only for distinguishing the components from other components, and the essence, order, or sequence of the components are not limited by such terms. Also, unless otherwise defined, all terms used here, including technical or scientific terms, have the same meaning as generally 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 a meaning consistent with the meaning in the context of the related technology, and should not be interpreted in an ideal or overly formal sense unless clearly defined in this document.

[0023] FIG. 1 is a diagram showing a battery cell pack according to an embodiment disclosed in this document. Referring to Figure 1, a battery cell pack 1000 according to one embodiment disclosed herein may include a battery cell module 100, a battery management device 200, and a relay 300. According to various embodiments, the battery cell module 100 may be a battery cell, in which case the battery cell pack 1000 may have a cell-to-pack structure.

[0024] Although Figure 1 shows a single battery cell module 100, according to the embodiment, the battery cell module 100 may consist of multiple modules, and the battery cell pack 1000 may have multiple battery cell modules forming a stacked structure. The battery cell module 100 can include multiple battery cells 110, 120, 130, and 140. Although Figure 1 shows a configuration with four battery cells, the battery cell 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.

[0025] The battery cell module 100 can supply power to a target device (not shown). For this purpose, the battery cell 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 cell pack 1000 containing a plurality of battery cells 110, 120, 130, 140, for example, an electric vehicle (EV) or an energy storage system (ESS).

[0026] The multiple battery cells 110, 120, 130, and 140 are the basic units of a battery cell 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 the battery cell module 100 as a single unit, according to the embodiment, the battery cell module 100 may be composed of multiple units.

[0027] The Battery Management System (BMS) 200 can manage and / or control the state and / or operation of the battery cell 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 cell module 100. The Battery Management System 200 can manage the charging and / or discharging of the battery cell module 100.

[0028] 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 cell pack 1000.

[0029] Furthermore, the battery management device 200 can monitor the voltage, current, temperature, etc., of the battery cell module 100 and / or the multiple battery cells 110, 120, 130, and 140 contained within the battery cell module 100. In addition, for monitoring via the battery management device 200, sensors and various measurement modules (not shown) can be further installed at any location on the battery cell module 100, the charge / discharge path, or the battery cell module 100 itself. Based on the measured values ​​of voltage, current, temperature, etc., the battery management device 200 can calculate parameters indicating the state of the battery cell module 100, such as SOC (State of Charge) or SOH (State of Health).

[0030] Multiple battery cells 110, 120, 130, and 140 may experience various changes in their capacity and internal resistance as their 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 cells degrade.

[0031] Battery cells may experience faster and larger voltage changes compared to normal battery cells if they become defective due to various reasons such as defects during the production stage, internal deformation and modification due to multiple charge-discharge cycles, or external shocks. The battery management device 200 utilizes the phenomenon that battery cells with internal defects experience faster and larger voltage changes during the rest period compared to normal battery cells. By comparing the voltage data of multiple battery cells 110, 120, 130, and 140 during their rest period with the statistically normal voltage data of normal battery cells during their rest period, the device can diagnose abnormal battery cells among the multiple battery cells 110, 120, 130, and 140.

[0032] The battery management device 200 can calculate the average voltage of multiple battery cells 110, 120, 130, and 140, and the deviation (dV) between the average voltage of each of the multiple battery cells 110, 120, 130, and 140. Using the voltage deviations of each of the multiple battery cells 110, 120, 130, and 140, the battery management device 200 can determine abnormal voltage behavior in at least one of the multiple battery cells 110, 120, 130, and 140, and diagnose that battery cell.

[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 voltage measuring unit 210 and a controller 220. The voltage measurement unit 210 can calculate the voltage of each of the multiple battery cells 110, 120, 130, and 140. The voltage measurement unit 210 can calculate the voltage of each of the multiple battery cells 110, 120, 130, and 140 for each unit of time and can calculate time-series data of the voltage of each of the multiple battery cells 110, 120, 130, and 140. According to one embodiment, the voltage measurement unit 210 can continuously calculate the rise and fall of voltage during charging, the rest period after charging, discharging, and the rest period after discharging of the multiple battery cells 110, 120, 130, and 140, as well as long-term stabilization (relaxation) data.

[0036] Figure 3 is a graph showing the voltage of a battery cell according to one embodiment disclosed in this document. Referring to Figure 3, the voltage measurement unit 210 measures the voltage of multiple battery cells 110, 120, 130, and 140 during charging, the rest period after charging, discharging, and the rest period after discharging, and can calculate time-series data of the voltage of each of the multiple battery cells 110, 120, 130, and 140. The voltage measurement unit 210 measures the voltage of each of the multiple battery cells 110, 120, 130, and 140 at unit time intervals and can generate a graph showing the voltage changes of each of the multiple battery cells 110, 120, 130, and 140.

[0037] The controller 220 can calculate the moving average of the voltages of each of the multiple battery cells 110, 120, 130, and 140. Here, the moving average is the average of a portion of the total data extracted while moving through a window of a specific size. Here, the window is a reference interval from which a portion of the total data can be extracted to determine which data to use. The start time of the window is a reference time from the current time, and the end time of the window is the current time. For example, if the window is one week, the controller 220 can extract data from the total data acquired from the current time to the most recent week.

[0038] The controller 220 can calculate the moving average voltage of each of the multiple battery cells 110, 120, 130, and 140 by using voltage data extracted from the total voltage data of each of the multiple battery cells 110, 120, 130, and 140 while moving through the window. The controller 220 can also calculate the continuous moving average voltage of each of the multiple battery cells 110, 120, 130, and 140 by using voltage data continuously extracted from the total voltage data of each of the multiple battery cells 110, 120, 130, and 140 while moving through the window. For example, the controller 220 can apply one of the following methods to the total voltage data of each of the multiple battery cells 110, 120, 130, and 140: Simple Moving Average, Weighted Moving Average, or Exponential Moving Average (EMA), and calculate the moving average voltage of each of the multiple battery cells 110, 120, 130, and 140.

[0039] According to one embodiment, the controller 220 can apply an exponential moving average (EMA) to the total voltage data of each of the multiple battery cells 110, 120, 130, and 140 to calculate the exponential moving average value of the voltages of each of the multiple battery cells 110, 120, 130, and 140. The exponential moving average is a type of weighted moving average method that uses data from the entire past period and gives more weight to recent data.

[0040] The controller 220 can calculate multiple moving average values ​​with different window sizes using the voltage data of each of the multiple battery cells 110, 120, 130, and 140. According to one embodiment, the controller 220 can calculate a long moving average with a relatively long window length and a short moving average with a relatively short window length using the total voltage data of each of the multiple battery cells 110, 120, 130, and 140. For example, the window size of the long moving average may include 100 seconds, and the window size of the short moving average may include 10 seconds. For example, the controller 220 can calculate the long-term moving average of each of the multiple battery cells 110, 120, 130, and 140 based on the voltage data of each of the multiple battery cells 110, 120, 130, and 140, using the voltage data acquired in the most recent 100 seconds from the calculation point, and calculate the short-term moving average of each of the multiple battery cells 110, 120, 130, and 140 using the voltage data acquired in the most recent 10 seconds from the calculation point.

[0041] The controller 220 can analyze the long-term voltage change trend and short-term voltage change trend of multiple battery cells 110, 120, 130, and 140 using the continuous long-term moving average (V_LMA) and short-term moving average (V_SMA) of each of the multiple battery cells 110, 120, 130, and 140. The controller 220 can diagnose whether there are any abnormalities in the voltage of each of the multiple battery cells using the long-term moving average (V_LMA) and short-term moving average (V_SMA) of the voltage of each of the multiple battery cells 110, 120, 130, and 140.

[0042] Figure 4 is a flowchart showing a method for diagnosing a battery cell in a controller according to one embodiment disclosed in this document. The following section will specifically explain how to diagnose the battery cells of the controller, referring to Figure 4.

[0043] In operation S101, the controller 220 can calculate multiple first deviations (V_LMA-V_SMA), which are the deviations between the long-term moving average value (V_LMA) and the short-term moving average value (V_SMA) of the voltages of multiple battery cells 110, 120, 130, and 140. In operation S101, the controller 220 can continuously calculate the first deviations (V_LMA-V_SMA) for each of the multiple battery cells 110, 120, 130, and 140 calculated during a unit time. In operation S101, that is, the controller 220 can continuously calculate the deviations between the long-term and short-term behaviors of the voltages of multiple battery cells 110, 120, 130, and 140.

[0044] In operation S102, the controller 220 can calculate the long-term moving average and short-term moving average of the average voltage (V_avg) of the multiple battery cells 110, 120, 130, and 140. Here, the average voltage (V_avg) of the multiple battery cells 110, 120, 130, and 140 may include the mean or median of the voltages of the multiple battery cells 110, 120, 130, and 140.

[0045] In operation S102, the controller 220 continuously calculates the average voltage (V_avg) of multiple battery cells 110, 120, 130, and 140 at unit time intervals, and can use the average voltage (V_avg) of multiple battery cells 110, 120, 130, and 140 to calculate the long-term moving average value and short-term moving average value of the average voltage (V_avg) of multiple battery cells 110, 120, 130, and 140. Here, the window size of the long-term moving average value of the average voltage (V_avg) of multiple battery cells 110, 120, 130, and 140 may be the same as the window size of the long-term moving average value (V_LMA) of the voltage of each of the multiple battery cells 110, 120, 130, and 140. Furthermore, the window size of the short-term moving average value of the average voltage (V_avg) of multiple battery cells 110, 120, 130, and 140 may be the same as the window size of the short-term moving average value (V_SMA) of each of the multiple battery cells 110, 120, 130, and 140.

[0046] In operation S102, the controller 220 can calculate a second deviation, which is the difference between the long-term moving average and short-term moving average of the average voltage (V_avg) of multiple battery cells 110, 120, 130, and 140. In operation S102, the controller 220 can continuously calculate the second deviation of multiple battery cells 110, 120, 130, and 140 for each unit time. In other words, the controller 220 can calculate the difference between the long-term and short-term behavior of the average voltage (V_avg) of multiple battery cells 110, 120, 130, and 140.

[0047] In operation S103, the controller 220 can calculate the first diagnostic deviation (D1) for each of the multiple battery cells 110, 120, 130, and 140, which is the deviation of multiple first deviations (V_LMA-V_SMA) and second deviations.

[0048] In operation S103, specifically, the controller 220 can calculate the first diagnostic deviation (D1) for each of the multiple battery cells 110, 120, 130, and 140 based on [Equation 1].

[0049] [Formula 1] First diagnostic deviation (D1) = Second deviation - First voltage = (V avg_ LMA-V avg_ SMA)-(V_LMA-V_SMA)

[0050] Referring to [Equation 1], the controller 220 can calculate the deviations of multiple first deviations (V_LMA-V_SMA) and second deviations as the first diagnostic deviation (D1) for each of the multiple battery cells 110, 120, 130, and 140.

[0051] In operation S104, the controller 220 can normalize the first diagnostic deviation (D1) of each of the multiple battery cells 110, 120, 130, and 140 and calculate the second diagnostic deviation (D2) of each of the multiple battery cells 110, 120, 130, and 140. According to this embodiment, operation S104 may be omitted.

[0052] In operation S105, the controller 220 can diagnose each of the multiple battery cells based on whether the final diagnostic deviation associated with the first diagnostic deviation of each of the multiple battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above a second threshold.

[0053] According to the embodiment, the controller 220 can determine a battery cell whose final diagnostic deviation is greater than or equal to a first threshold as a diagnostic battery cell. For example, the final diagnostic deviation may be a value generated based on the first diagnostic deviation.

[0054] According to one embodiment, the controller 220 can diagnose a diagnostic battery cell as abnormal if the final diagnostic deviation of the diagnostic battery cell is maintained at or above a second threshold during the first hour based on the time of diagnosis. According to another embodiment, the controller 220 can determine that the diagnostic battery cell has been misdiagnosed if the final diagnostic deviation of the diagnostic battery cell is not maintained at or above a second threshold during the first hour based on the time of diagnosis.

[0055] In other words, the battery management device 200 according to one embodiment disclosed in this document can determine that a diagnosis is a misdiagnosis due to external factors if the final diagnostic deviation of the diagnostic battery cell is not maintained at or above a second threshold during the first hour based on the time of diagnosis. Furthermore, the battery management device 200 can determine that a diagnosis is a normal abnormality diagnosis, rather than a misdiagnosis due to external factors, if the final diagnostic deviation of the diagnostic battery cell is maintained at or above a second threshold during the first hour based on the time of diagnosis.

[0056] According to the embodiment, the first time can be determined in relation to the time used to calculate the long-term moving average. For example, the first time can be set to a value corresponding to 70% of the time used to calculate the long-term moving average, but is not limited to this.

[0057] According to the embodiment, the second threshold is less than the first threshold, and the second threshold can be determined based on the first threshold. For example, the second threshold can be set to half of the first threshold, but is not limited to this.

[0058] According to the embodiment, the controller 220 can normalize the first diagnostic deviation of each of the multiple battery cells and calculate the second diagnostic deviation of each of the multiple battery cells. For example, the controller 220 can calculate the second diagnostic deviation of each of the multiple battery cells as the final diagnostic deviation and compare the second diagnostic deviation with the first threshold and the second threshold.

[0059] In other words, according to various embodiments, in operation S105, the controller 220 can diagnose multiple battery cells based on a first or second diagnostic deviation to determine which battery cell is being diagnosed and calculate the final diagnostic deviation. Furthermore, it can determine whether a diagnostic battery cell has been diagnosed successfully based on the time during which the final diagnostic deviation of the diagnostic battery cell is maintained at or above a second threshold.

[0060] According to the embodiment, the controller 220 can check the time for which the first or second diagnostic deviation of the diagnostic battery cell is maintained above a second threshold, and determine whether the diagnostic battery cell has been successfully diagnosed based on the maintenance time. That is, the final diagnostic deviation may include the first or second diagnostic deviation.

[0061] After diagnosing at least one of the multiple battery cells 110, 120, 130, and 140, the controller 220 can track and monitor for defects such as internal short circuits, external short circuits, and lithium deposition within the battery cell.

[0062] Furthermore, if the controller 220 confirms, as a result of the diagnosis, that a defect has occurred inside the battery cell, it can provide information about the battery cell to the user. For example, the controller 220 can provide information about the battery cell that has experienced an internal short circuit to the user terminal via a communication unit (not shown), and it can also provide information about the battery cell via a display provided in the vehicle or charger, etc.

[0063] As described above, according to the battery management device 200 of one embodiment disclosed in this document, noise from the deviation between the long-term moving average value and the short-term moving average value of the battery cell voltage can be removed, and abnormal battery cells can be accurately diagnosed.

[0064] Conventional battery management devices use the deviation of the voltage of each battery cell relative to the average voltage of the battery cells, which can distort abnormal behavior signals of the voltage of each battery cell and lead to the possibility of misdiagnosis due to noise data. However, the battery management device 200 according to one embodiment disclosed in this document uses the deviation between the long-term moving average value and the short-term moving average value of the voltage of each battery cell, thereby minimizing the distortion of the voltage of the battery cells and improving the accuracy of diagnosis.

[0065] The battery management device 200 uses the deviation between the long-term moving average and short-term moving average voltages of the battery cells to diagnose battery cells exhibiting abnormal voltage behavior at an early stage, thereby ensuring the energy safety and reliability of the battery cells. Furthermore, because the battery management device 200 diagnoses battery cells exhibiting abnormal voltage behavior while they are installed in the vehicle, it eliminates the need for separate isolation of the battery cells, allowing for quick and easy diagnosis of the battery cells.

[0066] Figures 5a to 5e illustrate examples of how to distinguish the voltage behavior of a battery cell due to the external environment in other embodiments disclosed in this document from the voltage behavior due to actual abnormalities.

[0067] Referring to Figure 5a, the battery management device 200 can acquire the voltage behavior 705 of each of the multiple battery cells. In this case, the battery management device 200 can also acquire the voltage behavior 710 of the first battery cell.

[0068] Referring to Figure 5b, the battery management device 200 can calculate a long-term moving average and a short-term moving average 715 based on the voltage behavior 705 of each of the multiple battery cells. In this case, the battery management device 200 can calculate the long-term moving average and the short-term moving average 720 of the first battery cell.

[0069] Referring to Figure 5c, the battery management device 200 can calculate the deviation of 725 between the long-term moving average and short-term moving average values ​​of each of the multiple battery cells. In this case, the battery management device 200 can calculate the deviation of 730 between the long-term moving average and short-term moving average values ​​of the first battery cell. According to the embodiment, the battery management device 200 can compare the deviation of the long-term moving average and short-term moving average values ​​of each of the multiple battery cells with a first threshold value and determine that the first battery cell is a diagnostic battery cell.

[0070] Referring to Figure 5d, the battery management device 200 can calculate a normalized value 735 obtained by normalizing the deviation between the long-term moving average and short-term moving average values ​​of each of the multiple battery cells. In this case, the battery management device 200 can calculate a normalized value 740 obtained by normalizing the deviation between the long-term moving average and short-term moving average values ​​of the first battery cell. According to the embodiment, the battery management device 200 can compare the normalized value obtained by normalizing the deviation between the long-term moving average and short-term moving average values ​​of each of the multiple battery cells with a first threshold value and determine that the first battery cell is a diagnostic battery cell.

[0071] Referring to Figure 5e, if the first battery cell is determined to be a diagnostic battery cell, the battery management device 200 can confirm the time 745 during which the deviation 730 between the long-term moving average and short-term moving average of the first battery cell remains above the second threshold.

[0072] According to the embodiment, the battery management device 200 can also confirm the time 745 during which the normalized value 740 obtained by the deviation between the long-term moving average and short-term moving average values ​​of the first battery cell is maintained above a second threshold.

[0073] The battery management device 200 can determine that the first battery cell has been diagnosed normally if the time 745 that the temperature remains above the second threshold is 1 hour or longer. As another example, the battery management device 200 can determine that the first battery cell has been misdiagnosed if the time 745 that the temperature remains above the second threshold is less than 1 hour.

[0074] Figure 6 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.

[0075] Referring to Figure 6, 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.

[0076] The MCU2100 may be a processor that executes various programs stored in the memory 2200 (for example, a battery cell voltage deviation analysis program), processes various data through such programs, and performs the functions of the battery management device 200 shown in Figure 2 above.

[0077] 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.

[0078] 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.

[0079] 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.

[0080] 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, via the communication interface 2400, programs and various data for voltage deviation diagnosis, misdiagnosis determination, and anomaly diagnosis can be sent and received from a separately provided external server.

[0081] 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 variations without departing from the essential characteristics of this disclosure.

[0082] 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]

[0083] 1000: Battery Cell Pack 100: Battery cell module 110: Battery cell 120: Battery cell 130: Battery cell 140: Battery cell 200:Battery management device 210: Voltage measurement section 220: Controller 300: Relay 2000: Computing Systems 2100:MCU 2200: Memory 2300: Input / Output Interface 2400: Communication I / F

Claims

1. A voltage measuring unit that measures the voltage of each of multiple battery cells, For each of the plurality of battery cells, a first deviation is calculated, which is the difference between the long-term moving average and the short-term moving average of the battery cell voltage. A second deviation is calculated, which is the difference between the long-term moving average and the short-term moving average of the average voltage of the plurality of battery cells. For each of the plurality of battery cells, a first diagnostic deviation is calculated, which is the difference between the first deviation and the second deviation. A controller that diagnoses each of the plurality of battery cells based on whether the final diagnostic deviation related to the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above a second threshold, A battery management device, including a battery management device.

2. The aforementioned controller, A battery cell whose final diagnostic deviation is equal to or greater than the first threshold is determined to be a diagnostic battery cell. The battery management device according to claim 1, which diagnoses a diagnostic battery cell as abnormal if the final diagnostic deviation of the diagnostic battery cell is maintained at or above the second threshold within a first hour based on the time of diagnosis.

3. The battery management device according to claim 2, wherein if the final diagnostic deviation of the diagnostic battery cell is not maintained at or above the second threshold within a first hour based on the diagnostic time, it is determined that the diagnostic battery cell has been misdiagnosed.

4. The battery management device according to claim 3, wherein the first time is determined in relation to the time for calculating the long-term moving average value.

5. The second threshold is less than the first threshold. The battery management device according to any one of claims 1 to 4, wherein the second threshold is determined based on the first threshold.

6. The aforementioned controller, The first diagnostic deviation of each of the plurality of battery cells is normalized to calculate the second diagnostic deviation of each of the plurality of battery cells. The battery management device according to any one of claims 1 to 4, wherein the second diagnostic deviation of each of the plurality of battery cells is calculated as the final diagnostic deviation.

7. The operation of measuring the voltage of each of multiple battery cells, The operation involves calculating a first deviation for each of the plurality of battery cells, which is the difference between the long-term moving average and the short-term moving average of the battery cell voltages; calculating a second deviation, which is the difference between the long-term moving average and the short-term moving average of the average voltage of the plurality of battery cells; and calculating a first diagnostic deviation for each of the plurality of battery cells, which is the difference between the first deviation and the second deviation. An operation to diagnose each of the plurality of battery cells based on whether the final diagnostic deviation related to the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above a second threshold, A method for operating a battery management device, including the operation of the battery management device.

8. The operation of diagnosing each of the plurality of battery cells based on whether the final diagnostic deviation related to the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above a second threshold, is as follows: The operation of determining a battery cell in which the final diagnostic deviation is equal to or greater than the first threshold as a diagnostic battery cell, If the final diagnostic deviation of the diagnostic battery cell is maintained at or above the second threshold within the first hour based on the time of diagnosis, the diagnostic battery cell is diagnosed as abnormal. A method for operating a battery management device according to claim 7, comprising: an action to determine that the diagnostic battery cell has been misdiagnosed if the final diagnostic deviation of the diagnostic battery cell is not maintained at or above the second threshold within a first hour based on the diagnostic time.

9. The method of operating the battery management device according to claim 8, wherein the first time is determined in relation to the time for calculating the long-term moving average value.

10. The second threshold is less than the first threshold. The method of operating a battery management device according to any one of claims 7 to 9, wherein the second threshold is determined based on the first threshold.

11. The operation of diagnosing each of the plurality of battery cells based on whether the final diagnostic deviation related to the first diagnostic deviation of each of the plurality of battery cells is greater than or equal to a first threshold, and the time for which the final diagnostic deviation is maintained at or above a second threshold, is as follows: The operation involves normalizing the first diagnostic deviation of each of the plurality of battery cells and calculating the second diagnostic deviation of each of the plurality of battery cells, A method for operating a battery management device according to any one of claims 7 to 9, comprising the operation of calculating the second diagnostic deviation of each of the plurality of battery cells as the final diagnostic deviation.

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