Battery management device and operating method thereof

Abstract

A battery management apparatus according to an embodiment disclosed in this document may include: a voltage measurement unit that measures a voltage of each of a plurality of battery cells; and a controller that calculates, for each of the plurality of battery cells, a first deviation that is a deviation between a long-term moving average value and a short-term moving average value of a battery cell voltage, calculates a second deviation that is a deviation between a long-term moving average value and a short-term moving average value of an average voltage of the plurality of battery cells, a first diagnostic deviation that is a difference between the first deviation and the second deviation is calculated for each of the plurality of battery cells, at least one battery cell among the plurality of battery cells is diagnosed based on the first diagnostic deviation of each of the plurality of battery cells, and a diagnostic battery cell is set. The first diagnostic deviation of the diagnostic battery cell is compared with the first diagnostic deviation of the battery cell having the maximum value among the first diagnostic deviations of the battery cells different from the diagnostic battery cell, and whether the diagnostic battery cell is normally diagnosed is determined.

Description

Technical Field

[0001] Cross-references to related applications

[0002] This application claims priority and benefit to Korean Patent Application No. 10-2023-0059022, filed with the Korean Intellectual Property Office on May 8, 2023, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The embodiments disclosed herein relate to a battery management device and its operating method. Background Technology

[0004] Electric vehicles are powered externally to charge their battery cells, which then drive a motor using the voltage supplied to the cells. During production and use, battery cells undergo internal deformation and degradation through various charging and discharging cycles, altering their physical / chemical properties. This can lead to gas discharge due to internal or external short circuits, lithium deposition, or undervoltage defects that cause the battery cell voltage to drop below a certain level.

[0005] When defects occur inside a battery cell, direct problems may arise, such as deterioration of the cell's performance and an increased risk of fire due to electrolyte leakage. Therefore, a technology is needed to determine whether a battery cell is abnormal.

[0006] Traditional battery management devices can diagnose abnormal battery cell voltages by using the voltage deviation of each battery cell relative to the average voltage of the battery cells. However, due to its susceptibility to noise, this method cannot adjust the threshold used as a standard for diagnosing abnormal battery cells below a certain level, and it cannot detect abnormal battery cell voltages caused by micro-disconnections that occur in electric vehicles. Summary of the Invention

[0007] Technical issues

[0008] The embodiments disclosed herein aim to provide a battery management device and its operating method, wherein noise from the deviation between the long moving average and short moving average of the voltage of a battery cell can be removed to accurately diagnose abnormal battery cells.

[0009] The embodiments disclosed herein also aim to provide a battery management device and a method of operation thereof, wherein over-checking due to voltage inflection points (inflection points of open-circuit voltage) can be prevented during the detection of abnormal voltage behavior.

[0010] The technical problems of the embodiments disclosed herein are not limited to those described above, and those skilled in the art will clearly understand from the following description other unmentioned technical problems.

[0011] Technical solution

[0012] A battery management device according to an embodiment disclosed herein includes: a voltage measurement unit configured to measure the voltage of each of a plurality of battery cells; and a controller configured to: calculate, for each of the plurality of battery cells, a first deviation as a deviation between a long-moving average and a short-moving average of the battery cell voltage; calculate, for the average voltage of the plurality of battery cells, a second deviation as a deviation between a long-moving average and a short-moving average of the average voltage of the plurality of battery cells; and calculate, for each of the plurality of battery cells, a first diagnostic deviation as a difference between the first deviation and the second deviation; set a diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on the first diagnostic deviation of each of the plurality of battery cells; and determine whether the diagnostic battery cell is properly diagnosed by comparing the first diagnostic deviation of the battery cell having the maximum value among the first diagnostic deviations of battery cells different from the diagnostic battery cell with the first diagnostic deviation of the diagnostic battery cell.

[0013] In an implementation, the controller may also be configured to: determine that the diagnostic battery cell is being diagnosed normally when the product of the first diagnostic deviation of the diagnostic battery cell and a set value exceeds the first diagnostic deviation of the battery cell having the maximum value; and determine that the diagnostic battery cell is being misdiagnosed when the product of the first diagnostic deviation of the diagnostic battery cell and the set value is less than or equal to the first diagnostic deviation of the battery cell having the maximum value.

[0014] In an implementation, the controller may also be configured to: calculate a first diagnostic deviation for each of the plurality of battery cells at each reference time; and update the first diagnostic deviation of the battery cell having the maximum value among the first diagnostic deviations of battery cells different from the diagnosed battery cells at each reference time.

[0015] In an implementation, the controller may also be configured to: calculate the first diagnostic deviation of each of the diagnostic battery cells at each reference time; and update the maximum value of the first diagnostic deviation of the diagnostic battery cells at each reference time.

[0016] In an implementation, the controller may also be configured to determine that the diagnostic battery cell is being diagnosed normally when the minimum of the voltages of the plurality of battery cells is greater than the voltage at which the diagnostic battery cell is being diagnosed and the diagnosis of the diagnostic battery cell is not determined to be a misdiagnosis.

[0017] In an implementation, the controller may also be configured to: update the maximum value of the first diagnostic deviation of battery cells different from the diagnostic battery cell at each reference time; and determine whether the diagnostic battery cell is properly diagnosed by comparing the updated maximum value with the first diagnostic deviation of the diagnostic battery cell.

[0018] In an implementation, the controller may also be configured to: calculate a second diagnostic deviation for each of the plurality of battery cells based on a reference value obtained by multiplying the second deviation of the first diagnostic deviation of each of the plurality of battery cells by a threshold constant; and set the diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on the second diagnostic deviation of each of the plurality of battery cells.

[0019] In an implementation, the controller may further be configured to: set the reference value as the maximum value of the value obtained by multiplying the second deviation by a first threshold constant and the second threshold constant; calculate a second diagnostic deviation for each of the plurality of battery cells by excluding first diagnostic deviations less than or equal to the reference value from the first diagnostic deviations of each of the plurality of battery cells; calculate a third diagnostic deviation for each of the plurality of battery cells by performing normalization by dividing the second diagnostic deviation of each of the plurality of battery cells by the maximum value of the value obtained by multiplying the second deviation by a third threshold constant and a fourth threshold constant; calculate a skewness for each of the plurality of battery cells by dividing the value obtained by adding the minimum value of the third diagnostic deviations of each of the plurality of battery cells to the third diagnostic deviation of each of the plurality of battery cells by the third diagnostic deviation; calculate a fourth diagnostic deviation for each of the plurality of battery cells by multiplying the skewness by the third diagnostic deviation of each of the plurality of battery cells; and set the diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on whether the fourth diagnostic deviation of each of the plurality of battery cells exceeds a threshold.

[0020] An operating method of a battery management device according to an embodiment disclosed herein includes: measuring the voltage of each of a plurality of battery cells; calculating, for each of the plurality of battery cells, a first deviation as a deviation between a long-moving average and a short-moving average of the battery cell voltage, calculating, for each of the plurality of battery cells, a second deviation as a deviation between a long-moving average and a short-moving average of the average voltage of the plurality of battery cells, and calculating, for each of the plurality of battery cells, a first diagnostic deviation as the difference between the first deviation and the second deviation; setting a diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on the first diagnostic deviation of each of the plurality of battery cells; and determining whether the diagnostic battery cell is properly diagnosed by comparing the first diagnostic deviation of the battery cell having the maximum value among the first diagnostic deviations of battery cells different from the diagnostic battery cell.

[0021] In one embodiment, the step of determining whether a diagnostic battery cell is being diagnosed correctly by comparing the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of battery cells different from the diagnostic battery cell with the first diagnostic deviation of the diagnostic battery cell may include the following steps: when the product of the first diagnostic deviation of the diagnostic battery cell and a set value exceeds the first diagnostic deviation of the battery cell with the maximum value, the diagnostic battery cell is determined to be being diagnosed correctly; and when the product of the first diagnostic deviation of the diagnostic battery cell and the set value is less than or equal to the first diagnostic deviation of the battery cell with the maximum value, the diagnostic battery cell is determined to be being misdiagnosed.

[0022] In an implementation, the method may further include the following steps: calculating a first diagnostic deviation for each of the plurality of battery cells at each reference time; and updating the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of battery cells different from the diagnosed battery cells at each reference time.

[0023] In an implementation, the method may further include the following steps: calculating a first diagnostic deviation for each of the diagnostic battery cells at each reference time; and updating the maximum value of the first diagnostic deviation of the diagnostic battery cells at each reference time.

[0024] In one implementation, the step of determining whether a diagnostic battery cell is being properly diagnosed by comparing the first diagnostic deviation of a battery cell that has the maximum value among the first diagnostic deviations of battery cells that are different from the diagnostic battery cell with the first diagnostic deviation of the diagnostic battery cell may include the following steps: updating the maximum value among the first diagnostic deviations of battery cells that are different from the diagnostic battery cell at each reference time; and determining whether the diagnostic battery cell is being properly diagnosed by comparing the updated maximum value with the first diagnostic deviation of the diagnostic battery cell.

[0025] In one implementation, the step of setting up a diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on a first diagnostic deviation of each of the plurality of battery cells may include the following steps: calculating a second diagnostic deviation of each of the plurality of battery cells based on a reference value obtained by multiplying a second deviation of the first diagnostic deviation of each of the plurality of battery cells by a threshold constant; and setting up the diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on the second diagnostic deviation of each of the plurality of battery cells.

[0026] In an implementation, the step of setting the diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on a second diagnostic deviation of each of the plurality of battery cells may include the following steps: setting the reference value as the maximum of a value obtained by multiplying the second deviation by a first threshold constant and a second threshold constant; calculating the second diagnostic deviation of each of the plurality of battery cells by excluding first diagnostic deviations less than or equal to the reference value from the first diagnostic deviations of each of the plurality of battery cells; and dividing the second diagnostic deviation of each of the plurality of battery cells by a value obtained by multiplying the second deviation by a third threshold constant and a fourth threshold constant. The maximum value in the range is used to perform normalization to calculate the third diagnostic deviation of each of the plurality of battery cells; the skewness of each of the plurality of battery cells is calculated by dividing the value obtained by adding the minimum of the third diagnostic deviations of each of the plurality of battery cells to the third diagnostic deviation of each of the plurality of battery cells by the third diagnostic deviation; the fourth diagnostic deviation of each of the plurality of battery cells is calculated by multiplying the skewness by the third diagnostic deviation of each of the plurality of battery cells; and the diagnostic battery cell is set by diagnosing at least one of the plurality of battery cells based on whether the fourth diagnostic deviation of each of the plurality of battery cells exceeds a threshold.

[0027] Beneficial effects

[0028] The battery management device and its operating method according to the embodiments disclosed herein can accurately diagnose abnormal battery cells by removing noise from the deviation between the long moving average and short moving average of the battery cell voltage.

[0029] Furthermore, the battery management device and its operating method according to the embodiments disclosed herein can prevent over-checking based on the voltage inflection points of multiple battery cells, detect minute signals by lowering the threshold, and filter noise, thereby improving the detection rate and reducing the over-checking rate.

[0030] Furthermore, the battery management device and its operating method according to the embodiments disclosed herein can distinguish between voltage inflection points that typically occur based on the characteristics of the battery cell and voltage inflection points caused by defects, thereby preventing over-inspection and improving the diagnostic rate.

[0031] In addition, various effects that can be directly or indirectly understood from this disclosure may be provided. Attached Figure Description

[0032] Figure 1 A battery cell pack according to an embodiment disclosed herein is shown.

[0033] Figure 2 This is a block diagram illustrating the configuration of a battery management device according to an embodiment disclosed herein.

[0034] Figure 3 It is a graph showing the voltage of a battery cell according to the embodiments disclosed herein.

[0035] Figure 4 This is a flowchart illustrating a method for diagnosing the battery cells of a controller according to an embodiment disclosed herein.

[0036] Figure 5a This is a graph showing the first diagnostic deviation of a battery cell according to the embodiments disclosed herein.

[0037] Figure 5b This is a graph showing the third diagnostic deviation of the battery cell according to the embodiments disclosed herein.

[0038] Figure 5c It is a graph showing the skewness of the third diagnostic deviation of the battery cell according to the embodiments disclosed herein.

[0039] Figure 5d This is a graph showing the fourth diagnostic deviation of the battery cell according to the embodiments disclosed herein.

[0040] Figure 6 This is a flowchart of a battery management device according to another embodiment disclosed herein.

[0041] Figure 7 This is a schematic diagram illustrating the difference in voltage inflection points among multiple battery cells according to another embodiment disclosed herein.

[0042] Figure 8a and Figure 8b This is a view illustrating the difference in the first diagnostic deviation based on the difference in the voltage inflection point between battery cells according to another embodiment disclosed herein.

[0043] Figure 9 and Figure 10 This is a view illustrating a method for detecting misdiagnosis of a battery management device according to another embodiment disclosed herein.

[0044] Figure 11 This is a view illustrating a method of operating a battery management device according to another embodiment disclosed herein.

[0045] Figure 12 This is a view that describes in detail the operation method of a battery management device according to another embodiment disclosed herein.

[0046] Figure 13 This is a block diagram illustrating the hardware configuration of a computing system for performing an operation method of a battery management device according to an embodiment disclosed herein. Detailed Implementation

[0047] In the following, some embodiments disclosed in this document will be described in detail with reference to the exemplary accompanying drawings. When adding reference numerals to components in each drawing, it should be noted that the same components are given the same reference numerals even when indicating the same components in different drawings. Furthermore, in describing the embodiments disclosed in this document, detailed descriptions of related known configurations or functions will be omitted if it is determined that such detailed descriptions would interfere with the understanding of the embodiments disclosed in this document.

[0048] To describe the components of the embodiments disclosed herein, terms such as first, second, A, B, (a), (b), etc., may be used. These terms are used only to distinguish one component from another and do not limit the components in terms of their nature, order, sequence, etc. The terms used herein (including technical and scientific terms) have the same meaning as those commonly understood by those skilled in the art, provided that no different definitions are given for these terms. Generally, terms defined in general dictionaries should be interpreted as having the same meaning as in the context of the relevant art and should not be interpreted as having an ideal or exaggerated meaning unless clearly defined in this document.

[0049] Figure 1 A battery cell pack according to an embodiment disclosed herein is shown.

[0050] Reference Figure 1 The battery cell pack 1000 according to the embodiments 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, and in this case, the battery cell pack 1000 may have a cell-to-pack structure.

[0051] At the same time, despite Figure 1 A battery cell module 100 is shown, but according to embodiments, the battery cell module 100 can be configured as a plurality of modules, and the battery cell assembly 1000 can have a stacked structure of multiple battery cell modules. The battery cell module 100 may include multiple battery cells 110, 120, 130, and 140. Although multiple battery cells... Figure 1 The diagram shows four cells, but this disclosure is not limited thereto, and the battery cell module 100 may include n battery cells (n is a natural number equal to or greater than 2).

[0052] 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. In this document, the target device may include, but is not limited to, electrical, electronic, or mechanical devices that operate by receiving power from a battery cell bank 1000 comprising a plurality of battery cells 110, 120, 130, and 140, and may be, for example, an electric vehicle (EV) or an energy storage system (ESS).

[0053] As basic units of battery cells, each capable of being charged and released electrical energy, the multiple battery cells 110, 120, 130, and 140 can be lithium-ion (Li-ion) batteries, Li-ion polymer batteries, nickel-cadmium (Ni-Cd) batteries, nickel-metal hydride (Ni-MH) batteries, and are not limited to these. Meanwhile, although in Figure 1 The image shows a battery cell module 100, but according to an embodiment, the battery cell module 100 can be configured as a plurality of modules.

[0054] The battery management device (or 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 device 200 can manage and / or control the state and / or operation of multiple battery cells 110, 120, 130, and 140 included in the battery cell module 100. The battery management device 200 can manage the charging and / or discharging of the battery cell module 100.

[0055] 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. When the charging device is connected to the battery cell pack 1000, the battery management device 200 can short-circuit the relay 300.

[0056] Furthermore, the battery management device 200 can monitor the voltage, current, temperature, etc. of each of the battery cell module 100 and / or the plurality of battery cells 110, 120, 130, and 140 included in the battery cell module 100. Sensors or various measurement modules (not shown) for monitoring performed by the battery management device 200 can be additionally mounted in the battery cell module 100, the charging / discharging path, any location of the battery cell module 100, etc. The battery management device 200 can calculate parameters indicating the state of the battery cell module 100, such as state of charge (SoC), state of health (SoH), etc., based on the monitored measurements such as voltage, current, temperature, etc.

[0057] For the multiple battery cells 110, 120, 130, and 140, as the usage time or number of uses increases, the battery capacity may decrease, the internal resistance may increase, and various factors may change. The battery management device 200 can diagnose abnormalities within the multiple battery cells 110, 120, 130, and 140 based on data on various factors that change as the battery cells deteriorate.

[0058] When defects occur in a battery cell due to various reasons such as defects during the manufacturing process, internal deformation and degradation through repeated charging and discharging, or external impacts, voltage changes may occur more quickly and significantly compared to normal battery cells. By utilizing the phenomenon that voltage changes in battery cells with internal defects are faster and more significant than those in normal battery cells during idle periods, the battery management device 200 can compare the voltage data of each of the multiple battery cells 110, 120, 130, and 140 during idle periods with the statistically normal voltage data of normal battery cells during idle periods to diagnose abnormal battery cells among the multiple battery cells 110, 120, 130, and 140.

[0059] Specifically, in abnormal battery cells, compared to normal battery cells, the voltage drops during the idle period after charging, and there is a greater deviation in voltage behavior compared to the voltage behavior of normal battery cells, causing the voltage behavior to be biased to one side, resulting in a greater skewness. The battery management device 200 can determine whether there is an abnormal battery cell among the plurality of battery cells 110, 120, 130, and 140 by using the greater deviation and greater skewness of the voltage behavior of the abnormal battery cell compared to the voltage behavior of the normal battery cell.

[0060] According to an embodiment, the battery management device 200 can determine whether there is an abnormal battery cell based on the voltage deviation of multiple battery cells 110, 120, 130, and 140 during charging. In this case, the battery management device 200 can determine whether there is an abnormal battery cell by jointly considering the voltage deviation of multiple battery cells 110, 120, 130, and 140 and whether the multiple battery cells 110, 120, 130, and 140 have passed a voltage inflection point, and when there is a misdiagnosed battery cell when it passes a voltage inflection point, the battery management device 200 can determine that it is a misdiagnosis.

[0061] The battery management device 200 can calculate the average voltage of a plurality of battery cells 110, 120, 130, and 140, as well as the voltage deviation dV of each of the plurality of battery cells 110, 120, 130, and 140. The battery management device 200 can determine abnormal voltage behavior of at least one of the plurality of battery cells 110, 120, 130, and 140 by using the voltage deviation of each of the plurality of battery cells 110, 120, 130, and 140, thereby diagnosing the corresponding battery cell.

[0062] The battery management device 200 can diagnose battery cells by using voltage deviation data from each of the multiple battery cells 110, 120, 130, and 140 (excluding noise voltage data suspected of being noise data among the voltage deviations of each of the multiple battery cells 110, 120, 130, and 140). After excluding noise voltage data among the voltage deviations of the multiple battery cells 110, 120, 130, and 140, the battery management device 200 can amplify the voltage deviation data from each of the multiple battery cells 110, 120, 130, and 140. The battery management device 200 can diagnose abnormal battery cells suspected of being at abnormal voltages by using the amplified voltage deviation data from each of the multiple battery cells 110, 120, 130, and 140.

[0063] The following operations of the battery management device 200 can also be performed in the battery management device 200 or in various devices (e.g., servers, cloud, chargers, chargers / dischargers, etc.) connected to the vehicle on which the battery management device 200 is installed.

[0064] Figure 2 This is a block diagram illustrating the configuration of a battery management device according to an embodiment disclosed herein.

[0065] In the following text, reference will be made to Figure 2 The configuration of the battery management device 200 is described in detail.

[0066] Reference Figure 2The battery management device 200 may include a voltage measurement unit 210 and a controller 220.

[0067] The voltage measurement unit 210 can calculate the voltage of each of the plurality of battery cells 110, 120, 130, and 140. The voltage measurement unit 210 can calculate the voltage of each of the plurality of battery cells 110, 120, 130, and 140 per unit time, thereby calculating the time-series data of the voltage of each of the plurality of battery cells 110, 120, 130, and 140. According to an embodiment, the voltage measurement unit 210 can continuously calculate the voltage rise, voltage fall, and long-term relaxation data of the plurality of battery cells 110, 120, 130, and 140 during charging, idle periods after charging, discharging, and idle periods after discharging.

[0068] Figure 3 It is a graph showing the voltage of a battery cell according to the embodiments disclosed herein.

[0069] Reference Figure 3 The voltage measurement unit 210 can calculate the timing data of the voltage of each of the multiple battery cells 110, 120, 130, and 140 by measuring the voltage of each of the multiple battery cells 110, 120, 130, and 140 during charging, idle periods after charging, discharging, and idle periods after discharging. The voltage measurement unit 210 can generate a graph indicating the voltage change of each of the multiple battery cells 110, 120, 130, and 140 by measuring the voltage of each of the multiple battery cells 110, 120, 130, and 140 per unit time.

[0070] Controller 220 can calculate a moving average of the voltage of each of the multiple battery cells 110, 120, 130, and 140. Here, the moving average can be the average of a subset of data extracted while moving a window of a specific size across the entire dataset. In this context, the window can be a reference period used to determine the subset of data extracted for use from the entire dataset. The starting point of the window can be a reference time point counting backwards from the current time, and the ending point of the window can be the current time. For example, when the window corresponds to a week, controller 220 can extract data from the entire dataset for the most recent week starting from the current time.

[0071] Controller 220 can calculate the moving average of the voltage of each of the multiple battery cells 110, 120, 130, and 140 by using voltage data extracted through a moving window from all voltage data of each of the multiple battery cells 110, 120, 130, and 140. Controller 220 can also calculate the continuous moving average of the voltage of each of the multiple battery cells 110, 120, 130, and 140 by using voltage data extracted continuously through a moving window from all voltage data of each of the multiple battery cells 110, 120, 130, and 140. For example, controller 220 can calculate the moving average of the voltage of each of the multiple battery cells 110, 120, 130, and 140 by applying any of a simple moving average, a weighted moving average, or an exponential moving average (EMA) to all voltage data of each of the multiple battery cells 110, 120, 130, and 140.

[0072] According to one implementation, the controller 220 can calculate the EMA of the voltage of each of the plurality of battery cells 110, 120, 130, and 140 by applying the EMA to the entire voltage data of each of the plurality of battery cells 110, 120, 130, and 140. EMA refers to a weighted moving average method in which a higher weight value is applied to the most recent data while using data from all past periods.

[0073] The controller 220 can calculate multiple moving averages with different window sizes using voltage data from each of the multiple battery cells 110, 120, 130, and 140. According to an embodiment, the controller 220 can calculate a long moving average with a long window length and a short moving average with a short window length using all voltage data from each of the multiple battery cells 110, 120, 130, and 140. For example, the window size for the long moving average may include 100 seconds, while the window size for the short moving average may include 10 seconds. For example, the controller 220 can calculate the long moving average of each of the multiple battery cells 110, 120, 130, and 140 using voltage data obtained within the most recent 100 seconds since the calculation of the voltage data from each of the multiple battery cells 110, 120, 130, and 140, and calculate the short moving average of each of the multiple battery cells 110, 120, 130, and 140 using voltage data obtained within the most recent 10 seconds since the calculation.

[0074] The controller 220 can analyze the long-term and short-term voltage variation trends of each of the multiple battery cells 110, 120, 130, and 140 using the continuous long-term moving average V_LMA and short-term moving average V_SMA. The controller 220 can also diagnose whether the voltage of each of the multiple battery cells is abnormal by using the long-term moving average V_LMA and short-term moving average V_SMA.

[0075] Figure 4 This is a flowchart illustrating a method for diagnosing the battery cells of a controller according to an embodiment disclosed herein.

[0076] In the following text, reference will be made to Figure 4 Describe in detail the battery cell diagnostic methods for the controller.

[0077] 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 V_LMA and the short-term moving average V_SMA of the voltage of each of the multiple battery cells 110, 120, 130, and 140. In operation S101, the controller 220 can continuously calculate the first deviations V_LMA-V_SMA of each of the multiple battery cells 110, 120, 130, and 140 calculated over a unit time period. That is, in operation S101, the controller 220 can continuously calculate the deviations between the long-term and short-term behaviors of each of the multiple battery cells 110, 120, 130, and 140.

[0078] In operation S102, the controller 220 can calculate the long moving average (V_avg) of the average voltage of multiple battery cells 110, 120, 130, and 140. avg LMA and short moving average (V avg (SMA). In this document, the average voltage V_avg of the multiple battery cells 110, 120, 130 and 140 may include the average or median voltage of the multiple battery cells 110, 120, 130 and 140.

[0079] In operation S102, the controller 220 can continuously calculate the average voltage V_avg of multiple battery cells 110, 120, 130, and 140 per unit time, and calculate the long moving average (V_avg) of the average voltage V_avg of multiple battery cells 110, 120, 130, and 140 using the average voltage V_avg of multiple battery cells 110, 120, 130, and 140. avg LMA and short moving average (Vavg SMA). In this paper, the long moving average (V_avg) of the average voltage of multiple battery cells 110, 120, 130 and 140 is used. avg The window size of LMA can be equal to the window size of the long moving average (LMA) of the voltages of each of the multiple battery cells 110, 120, 130, and 140. In this paper, the short moving average (V_avg) of the average voltages of the multiple battery cells 110, 120, 130, and 140 is used. avg The window size of SMA can be equal to the window size of the short moving average of the voltages of each of the multiple battery cells 110, 120, 130 and 140, V_SMA.

[0080] In operation S102, controller 220 can calculate the second deviation (V). avg LMA-V avg SMA is the long-moving average of the average voltage V_avg of multiple battery cells 110, 120, 130, and 140. avg LMA and short moving average (V avg The deviation between SMAs. In operation S102, the controller 220 can continuously calculate the second deviation (V) between multiple battery cells 110, 120, 130 and 140 per unit time. avg LMA-V avg In other words, controller 220 can calculate the deviation between the long-term and short-term behavior of the average voltage V_avg of multiple battery cells 110, 120, 130 and 140.

[0081] In operation S103, the controller 220 can calculate the first diagnostic deviation D1 for each of the plurality of battery cells 110, 120, 130, and 140, which is a plurality of first deviations V LMA-L SMA and second deviations (V avg LMA-V avg Deviation between SMA).

[0082] In operation S103, specifically, the controller 220 can calculate the first diagnostic deviation D1 of each of the plurality of battery cells 110, 120, 130 and 140 based on Equation 1.

[0083] [Equation 1]

[0084] First diagnostic deviation D1 = Second deviation - First voltage

[0085] =(V avE _LMA-V avg _SMA)-(V_LMA-V_SMA)

[0086] Referring to Equation 1, controller 220 can calculate multiple first deviations VLMA - VSMA and second deviations (VLMA - VSMA). avg LMA-V avg The deviation between SMAs is used as the first diagnostic deviation D1 for each of the multiple battery cells 110, 120, 130 and 140.

[0087] Figure 5a This is a graph showing the first diagnostic deviation of a battery cell according to the embodiments disclosed herein.

[0088] Reference Figure 5a The controller 220 can continuously calculate the first diagnostic deviation D1 of each of the plurality of battery cells 110, 120, 130 and 140 per unit time to generate a graph indicating the change of the first diagnostic deviation D1 of each of the plurality of battery cells 110, 120, 130 and 140.

[0089] In other words, the controller 220 can calculate a first diagnostic deviation D1 for each of the plurality of battery cells 110, 120, 130 and 140 to compare the deviation between the long-term and short-term behavior of the voltage of each of the plurality of battery cells 110, 120, 130 and 140 with the deviation between the long-term and short-term behavior of the average voltage V_avg of the plurality of battery cells 110, 120, 130 and 140.

[0090] Return to reference Figure 4 In operation S104, the controller 220 can calculate the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130 and 140 by removing noise data from the first diagnostic deviation D1 of each of the plurality of battery cells 110, 120, 130 and 140.

[0091] Specifically, in operation S104, the controller 220 may set a reference value for the noise used to determine the first diagnostic deviation D1 of each of the plurality of battery cells 110, 120, 130 and 140 based on Equation 2.

[0092] [Equation 2]

[0093] Reference value = Max[|V avg -LMA-V avg -SMA|*C1,C2]

[0094] In operation S104, controller 220 can transmit the second deviation (V) avg LMA-V avg The value obtained by multiplying the absolute value of SMA by the first threshold constant C1 is |V avg LMA-Vavg The maximum value Max in SMA|×C1) and the second threshold constant C2 is set as a reference value for each of the plurality of battery cells 110, 120, 130, and 140. In this document, the first threshold constant C1 may include "0.1", and the second threshold constant C2 may include "0.4". The first threshold constant C1 and the second threshold constant C2 may be varied according to the magnitude and characteristics of the voltage data of each of the plurality of battery cells 110, 120, 130, and 140.

[0095] In operation S104, the controller 220 can determine the first diagnostic deviation D1 of each of the plurality of battery cells 110, 120, 130, and 140 that is less than or equal to a reference value as noise data. In operation S104, the controller 220 can calculate the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130, and 140 by excluding the first diagnostic deviation D1 that is less than or equal to the reference value from the first diagnostic deviation D1 of each of the plurality of battery cells 110, 120, 130, and 140.

[0096] In operation S105, the controller 220 can calculate the third diagnostic deviation D3 by normalizing the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130 and 140.

[0097] Specifically, in operation S105, the controller 220 can calculate the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140 by normalizing the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130 and 140 based on the following equation 3.

[0098] [Equation 3]

[0099] Third diagnostic bias = Second diagnostic bias / Max[|V] avg -LMA-V avg -SMA|*C3,C4]

[0100] In operation S105, controller 220 can calculate the absolute value of the second deviation (|V) by... avg LMA-V avg The value obtained by multiplying SMA| by the third threshold constant C3 is (|V) avg LMA-V avg The controller 220 can use the maximum value of the fourth threshold constant C4 (Max[|V)) obtained by multiplying the absolute value of the second deviation by the third threshold constant and the maximum value of the fourth threshold constant C4 (Max[|V)). avg LMA-Vavg The second diagnostic deviation D2 is normalized for each of the multiple battery cells 110, 120, 130, and 140 using [SMA|XC3, C4]). In this document, the third threshold constant C3 may include "0.1", and the fourth threshold constant C4 may include "0.1", and the third threshold constant C3 and the fourth threshold constant C4 may vary depending on the magnitude and characteristics of the voltage data for each of the multiple battery cells 110, 120, 130, and 140. In operation S105, the controller 220 may calculate the second deviation (V_avg) by using the behavior of the average voltage V_avg of the multiple battery cells 110, 120, 130, and 140. avg LMA-V avg The value obtained by normalizing the second diagnostic bias D2 of each of the multiple battery cells 110, 120, 130 and 140 using SMA is used as the third diagnostic bias D3 of each of the multiple battery cells 110, 120, 130 and 140.

[0101] In operation S105, according to the embodiment, the controller 220 can normalize the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130 and 140 by logarithmic operation. That is, the controller 220 can calculate the value obtained by normalizing the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130 and 140 by logarithmic operation as the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140.

[0102] In operation S105, according to the embodiment, the controller 220 can set the average value D2_avg of the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130, and 140 as a normalization reference value. In operation S105, by using the average value D2_avg of the second diagnostic deviation as the normalization reference value, the controller 220 can perform normalization by dividing the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130, and 140 by the average value D2_avg of the second diagnostic deviation. That is, the controller 220 can calculate the value obtained by normalizing by dividing the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130, and 140 by the average value D2_avg of the second diagnostic deviation as the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130, and 140.

[0103] Figure 5b This is a graph showing the third diagnostic deviation D3 of the battery cell according to the embodiments disclosed herein.

[0104] Reference Figure 5b According to various embodiments, the controller 220 can calculate the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140 by normalizing the second diagnostic deviation D2 of each of the plurality of battery cells 110, 120, 130 and 140.

[0105] The controller 220 can continuously calculate the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140 per unit time to generate a graph indicating the change of the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140.

[0106] For example, controller 220 can use a second deviation (V_avg) indicating the behavior of the average voltage V_avg of multiple battery cells 110, 120, 130, and 140. avg LMA-V avg SMA) is used to normalize the second diagnostic bias D2 for each of the multiple battery cells 110, 120, 130 and 140.

[0107] Return to reference Figure 4 In operation S106, the controller 220 can calculate the skewness of the third diagnostic deviation D3 for each of the plurality of battery cells 110, 120, 130 and 140. Specifically, in operation S106, the controller 220 can calculate the skewness of the third diagnostic deviation D3 for each of the plurality of battery cells 110, 120, 130 and 140 based on the following equation 4.

[0108] [Equation 4]

[0109] Skewness = (Third Diagnostic Deviation D3 + Min[Third Diagnostic Deviation D3]) / Third Diagnostic Deviation D3

[0110] In operation S106, referring to Equation 4, the controller 220 can calculate the skewness of each of the plurality of battery cells 110, 120, 130 and 140 by dividing the value obtained by adding the minimum value (MIN[third diagnostic deviation D3]) of the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140 to the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140 by the third diagnostic deviation D3.

[0111] Figure 5c It is a graph showing the skewness of the third diagnostic deviation of the battery cell according to the embodiments disclosed herein.

[0112] Reference Figure 5cThe controller 220 can continuously calculate the skewness of the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140 per unit time to generate a graph indicating the change in the skewness of the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140.

[0113] Return to reference Figure 4 In operation S106, the controller 220 can calculate a fourth diagnostic deviation D4 for each of the plurality of battery cells 110, 120, 130, and 140 by reflecting the skewness to each of them. More specifically, the controller 220 can calculate the fourth diagnostic deviation D4 for each of the plurality of battery cells 110, 120, 130, and 140 based on Equation 5.

[0114] [Equation 5]

[0115] Fourth diagnostic bias D4 = Third diagnostic bias D3 * skewness

[0116] In operation S106, the controller 220 can calculate the fourth diagnostic deviation D4 of each of the plurality of battery cells 110, 120, 130 and 140 by multiplying the third diagnostic deviation D3 of each of the plurality of battery cells 110, 120, 130 and 140 by the skewness.

[0117] Figure 5d This is a graph showing the fourth diagnostic deviation of the battery cell according to the embodiments disclosed herein.

[0118] Reference Figure 5d The controller 220 can continuously calculate the fourth diagnostic deviation D4 of each of the plurality of battery cells 110, 120, 130 and 140 per unit time to generate a graph indicating the change of the fourth diagnostic deviation D4 of each of the plurality of battery cells 110, 120, 130 and 140.

[0119] Return to reference Figure 4 In operation S107, controller 220 can determine whether the fourth diagnostic deviation D4 of each of the plurality of battery cells 110, 120, 130, and 140 exceeds a threshold. In this document, because of the extreme output results, the threshold can be defined as a criterion for determining "abnormality." That is, the threshold can be defined as a criterion indicating the degree to which data contradicts a particular statistical model. For a battery cell among the plurality of battery cells 110, 120, 130, and 140 whose fourth diagnostic deviation D4 exceeds the threshold, controller 220 can determine that the battery cell has abnormal voltage behavior.

[0120] In operation S108, controller 220 can diagnose at least one of the plurality of battery cells 110, 120, 130, and 140 based on whether the fourth diagnostic deviation D4 of each of the plurality of battery cells 110, 120, 130, and 140 exceeds a threshold. In operation S108, controller 220 can diagnose the battery cell when the fourth diagnostic deviation D4 of at least one of the plurality of battery cells 110, 120, 130, and 140 exceeds the threshold.

[0121] In operation S108, according to an embodiment, when the fourth diagnostic deviation D4 of at least one of the plurality of battery cells 110, 120, 130 and 140 exceeds a threshold, the controller 220 may increase the diagnostic count value of at least one battery cell.

[0122] In operation S108, according to the embodiment, when the diagnostic count value of at least one of the plurality of battery cells 110, 120, 130 and 140 is greater than or equal to a threshold, the controller 220 can diagnose at least one battery cell.

[0123] After diagnosing at least one of the multiple battery cells 110, 120, 130 and 140, the controller 220 can track and monitor whether the battery cells have defects, such as internal short circuits, external short circuits, lithium deposition, etc.

[0124] As a diagnostic result, when the controller 220 determines that a defect exists in the battery cell, the controller 220 can provide information about the battery cell to the user. For example, the controller 220 can provide information about the battery cell with an 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 installed in the vehicle, charger, etc.

[0125] As described above, the battery management device 200 according to the embodiments disclosed herein can accurately diagnose abnormal battery cells by removing noise from the deviation between the long moving average and short moving average of the battery cell voltage.

[0126] In conventional battery management devices, the deviation of each battery cell's voltage from the average voltage of the battery cells distorts the abnormal behavior signal of each battery cell's voltage, and there is a possibility of misdiagnosis due to noisy data. However, the battery management device 200 according to the embodiments disclosed herein can minimize the voltage distortion of the battery cells by using the deviation of the long moving average and short moving average of the voltage of each battery cell, remove noisy data, and amplify the voltage behavior of abnormal battery cells by applying the voltage skewness of the battery cells, thereby improving the accuracy of diagnosis.

[0127] The battery management device 200 can diagnose battery cells exhibiting abnormal voltage behavior at an early stage by using the deviation between the long-term and short-term moving averages of the battery cell voltage, thereby ensuring the safety and reliability of the battery cell energy. Furthermore, the battery management device 200 can diagnose battery cells exhibiting abnormal voltage behavior while the battery cells are installed in the vehicle, without requiring the battery cells to be removed, thus enabling quick and convenient battery cell diagnosis.

[0128] Figure 6 This is a flowchart of a battery management device according to another embodiment disclosed herein. Figure 6 The operation shown can be performed by Figure 2 The battery management device 200 is executed.

[0129] Reference Figure 6 In operation S201, the voltage measurement unit 210 can measure the voltage of each of the multiple battery cells.

[0130] In operation S202, the controller 220 can calculate a first deviation, which is the deviation between the long-moving average and the short-moving average of the voltage of each of the multiple battery cells. For example, operation S202 can be compared with... Figure 4 The operation of S102 is basically the same.

[0131] In operation S203, the controller 220 can calculate a second deviation, which is the deviation between the long-moving average and the short-moving average of the average voltage of multiple battery cells. For example, operation S203 can be compared with... Figure 4 The operation of S103 is basically the same.

[0132] In operation S204, the controller 220 can calculate a first diagnostic deviation, which is the difference between a first deviation and a second deviation for each of the plurality of battery cells. For example, operation S204 can be compared with... Figure 4 The operation is basically the same as S104.

[0133] In operation S205, the controller 220 can diagnose at least one of the plurality of battery cells based on a first diagnostic deviation of each of the plurality of battery cells, thereby setting a diagnostic battery cell. For example, the controller 220 can set a battery cell with a first diagnostic deviation greater than or equal to a predetermined value as a diagnostic battery cell.

[0134] According to the implementation, the controller 220 can calculate the second diagnostic deviation of each of the plurality of battery cells based on a reference value obtained by multiplying the second deviation of the first diagnostic deviation of each of the plurality of battery cells by a threshold constant, and diagnose at least one of the plurality of battery cells based on the second diagnostic deviation of each of the plurality of battery cells, thereby setting the diagnostic battery cell.

[0135] According to the implementation, the controller 220 can set the maximum value of the second threshold constant and the value obtained by multiplying the second deviation by the first threshold constant as a reference value, and exclude first diagnostic deviations less than or equal to the reference value from the first diagnostic deviations of each of the plurality of battery cells, thereby calculating the second diagnostic deviation of each of the plurality of battery cells. The controller 220 can perform normalization by dividing the second diagnostic deviation of each of the plurality of battery cells by the maximum value of the value obtained by multiplying the second deviation by the third threshold constant and the fourth threshold constant, thereby calculating the third diagnostic deviation of each of the plurality of battery cells. The controller 220 can calculate the skewness of each of the plurality of battery cells by dividing the value obtained by adding the minimum value of the third diagnostic deviation of each of the plurality of battery cells to the third diagnostic deviation of each of the plurality of battery cells by the third diagnostic deviation, calculate the fourth diagnostic deviation of each of the plurality of battery cells by multiplying the third diagnostic deviation of each of the plurality of battery cells by the skewness, and diagnose at least one of the plurality of battery cells based on whether the fourth diagnostic deviation of each of the plurality of battery cells exceeds a threshold, thereby setting the diagnostic battery cell.

[0136] In other words, according to various embodiments, in operation S205, the controller 220 can diagnose multiple battery cells based on a first diagnostic deviation or any one of a second, third, or fourth diagnostic deviation based on the first diagnostic deviation, so as to set up diagnostic battery cells.

[0137] In operation S206, controller 220 can determine whether the diagnostic battery cell has been correctly diagnosed by comparing the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of battery cells different from the diagnosed battery cell. For example, when the product of the first diagnostic deviation of the diagnosed battery cell and a set value exceeds the first diagnostic deviation of the battery cell with the maximum value, controller 220 can determine that the diagnosed battery cell has been correctly diagnosed. In another example, when the product of the first diagnostic deviation of the diagnosed battery cell and a set value is less than or equal to the first diagnostic deviation of the battery cell with the maximum value, controller 220 can determine that the diagnosed battery cell has been misdiagnosed.

[0138] According to the implementation, the controller 220 can update the maximum value of the first diagnostic deviation of the battery cell that is different from the diagnosed battery cell in each reference time. For example, the controller 220 can calculate the first diagnostic deviation of each of a plurality of battery cells in each reference time, and update the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of the battery cells that are different from the diagnosed battery cell in each reference time. That is, the controller 220 can use the previously stored maximum value and the maximum value among the newly calculated first diagnostic deviations to update the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations.

[0139] According to an embodiment, the controller 220 may also store the voltage of the battery cell with the maximum value among the first diagnostic deviations of battery cells that are different from the diagnosed battery cell. For example, when the first battery cell is different from the diagnosed battery cell and the first diagnostic deviation of the first battery cell has a maximum value, the controller 220 may store the first diagnostic deviation of the first battery cell and the voltage of the first battery cell correspondingly. Furthermore, the controller 220 may further store the identification information of the first battery cell accordingly.

[0140] According to the implementation, when the stored voltage of the first battery cell is less than the voltage of the battery cell with the lowest voltage among the plurality of battery cells, the controller 220 can initialize the stored value. For example, when the stored voltage of the first battery cell is less than the voltage of the battery cell with the lowest voltage among the plurality of battery cells, this corresponds to the case where all battery cells have passed the voltage inflection point, allowing the controller 220 to initialize the stored value at the voltage inflection point and store the new maximum value of the first diagnostic deviation.

[0141] According to an embodiment, the controller 220 can calculate a first diagnostic deviation of the diagnostic battery cell at each reference time, and update the maximum value of the first diagnostic deviation of the diagnostic battery cell at each reference time. For example, the controller 220 can update the maximum value of the first diagnostic deviation of the diagnostic battery cell at each reference time to update the maximum value of the first diagnostic deviation calculated for the diagnostic battery cell. According to an embodiment, the controller 220 can store the maximum value of the first diagnostic deviation of the diagnostic battery cell and the voltage of the diagnostic battery cell at the corresponding point in a corresponding manner. In addition, the controller 220 can further store the identification information of the diagnostic battery cell in a corresponding manner.

[0142] According to the implementation, when the minimum value among the voltages of multiple battery cells is greater than the voltage at which the diagnostic battery cell is diagnosed and the diagnosis of the diagnostic battery cell is not determined to be a misdiagnosis, the controller 220 can determine that the diagnostic battery cell is being diagnosed normally.

[0143] According to the implementation, the controller 220 can determine whether the diagnostic battery cell is being diagnosed normally by updating the maximum value of the first diagnostic deviation of the battery cell that is different from the diagnostic battery cell in each unit time and comparing the updated maximum value with the first diagnostic deviation of the diagnostic battery cell.

[0144] Figure 7 This is a graph illustrating the difference in voltage inflection points among multiple battery cells according to another embodiment disclosed herein.

[0145] Reference Figure 7 Multiple battery cells may have different voltages during charging. In this case, it is possible that multiple battery cells have the same voltage at different times during charging, causing the times at which the multiple battery cells pass the voltage inflection point to be different. This could lead to the battery management device 200, which performs deviation-based diagnosis, misdiagnosing the battery at the point where the voltage inflection point has passed.

[0146] Figure 8a and Figure 8b This is a view illustrating the difference in the first diagnostic deviation based on the difference in the voltage inflection point between battery cells according to another embodiment disclosed herein.

[0147] Reference Figure 8a When multiple battery cells are being charged, a voltage deviation may occur between the battery cell 805 with the highest voltage and another battery cell 810.

[0148] Reference Figure 8b The battery cell 805 with the highest voltage may have a higher first diagnostic deviation 815. In this case, another battery cell 810 may not have reached the voltage inflection point, thus having a lower first diagnostic deviation 820. Therefore, the battery management device 200, which diagnoses battery cells based on the first diagnostic deviation, can diagnose an anomaly in the battery cell 805 with the highest voltage.

[0149] However, when another battery cell 810 passes through a voltage inflection point over time, the battery cell 810 exhibits a first diagnostic deviation similar to the higher first diagnostic deviation 815. In other words, the battery management device 200 according to another embodiment of this disclosure can provide a diagnostic method capable of preventing misdiagnosis due to voltage inflection points.

[0150] Figure 9 and Figure 10 This is a view illustrating a method for detecting misdiagnosis of a battery management device according to another embodiment disclosed herein.

[0151] Reference Figure 9According to another embodiment of the battery management device 200 disclosed herein, the controller 220 can store the maximum value of the first diagnostic deviation among each of a plurality of battery cells. For example, the controller 220 can store the maximum value of the first diagnostic deviation among each of the plurality of battery cells in each reference time period. According to an embodiment, the controller 220 can alternately store the maximum value of the first diagnostic deviation among each of the plurality of battery cells in time slot 1 and time slot 2. That is, when a first diagnostic deviation higher than the value stored in time slot 1 and time slot 2 is calculated, the controller 220 can update the time slot with the lower first diagnostic deviation among the first diagnostic deviations stored in time slot 1 and time slot 2. Figure 9 In the graph shown, time slot 1 = [2.0, 3.93] can represent a first diagnostic deviation of 2.0 and a voltage of 3.93. That is, the controller 220 can store the first diagnostic deviation and the battery cell voltage with the maximum value at the corresponding point in each time slot.

[0152] The controller 220 of the battery management device 200 can configure diagnostic battery cells. In this case, the controller 220 can store a first diagnostic deviation and the voltage of the diagnosed battery cell. Since the first diagnostic deviation of the diagnosed battery cell is greater than the first diagnostic deviation of other battery cells that are different from the diagnosed battery cell, the first diagnostic deviation of the diagnosed battery cell can be stored in either of the two time slots, and the maximum value of the first diagnostic deviations of the battery cells that are different from the diagnosed battery cell can be stored in the other time slot.

[0153] The controller 220 of the battery management device 200 can determine whether the diagnosed battery cell has been correctly diagnosed based on the maximum value of the first diagnostic deviation of the diagnosed battery cell and the first diagnostic deviation of a battery cell different from the diagnosed battery cell. For example, if the maximum value of the first diagnostic deviation of the battery cell different from the diagnosed battery cell (2.5) is greater than the product of the first diagnostic deviation of the diagnosed battery cell (3.2) and the set value (0.72) (3.2*0.72=2.304<2.5), then the controller 220 can determine that the diagnosed battery cell has been misdiagnosed.

[0154] In other words, the controller 200 can store the maximum value among the first diagnostic deviations of multiple battery cells at each reference time, and determine whether the battery cell has been misdiagnosed by comparing the stored maximum value with the first diagnostic deviation of the battery cell.

[0155] Although Figure 9The diagram shows a misdiagnosis of a battery cell based on the maximum value of the first diagnostic deviation before the time the battery cell is diagnosed. However, even when it is determined that the battery cell has been misdiagnosed, the battery management device 200 can continuously calculate the first diagnostic deviation of multiple battery cells at each reference time and update the maximum value to retain the data.

[0156] Reference Figure 10 According to another embodiment of the battery management device 200 disclosed herein, the controller 220 can store the maximum value of the first diagnostic deviation of each of the plurality of battery cells.

[0157] The controller 220 can determine whether a battery cell has been correctly diagnosed by comparing a first diagnostic deviation of the diagnosed battery cell with the maximum value of the first diagnostic deviation of a battery cell that is different from the diagnosed battery cell. In this case, the controller 220 can first compare the maximum value of the first diagnostic deviation before the time the diagnosed battery cell was diagnosed with the first diagnostic deviation of the diagnosed battery cell, and when it is not determined that the diagnosed battery cell has been misdiagnosed, it waits for the diagnosis of the diagnosed battery cell to be determined, and then compares the maximum value of the first diagnostic deviation after the time the diagnosed battery cell was diagnosed.

[0158] The controller 220 may wait for confirmation of the diagnosis of the diagnostic battery cell until the minimum value among the voltages of the multiple battery cells is higher than the voltage at the time of diagnosis. According to one embodiment, when the minimum value among the voltages of the multiple battery cells is higher than the voltage at the time of diagnosis and it is not determined that the diagnostic battery cell has been misdiagnosed, the controller 220 may determine that the diagnostic battery cell has been correctly diagnosed. According to another embodiment, the controller 220 may wait for confirmation of the diagnosis of the diagnostic battery cell until the minimum value among the voltages of the multiple battery cells is higher than a set voltage value.

[0159] When the minimum voltage among multiple battery cells is greater than or equal to the voltage at which the battery cell is being diagnosed, the controller 220 can store the maximum value among the first diagnostic deviations of the battery cells that are different from the diagnosed battery cell at each reference time.

[0160] The controller 220 can determine whether a battery cell has been properly diagnosed by comparing the maximum value of the first diagnostic deviations of battery cells different from the diagnosed battery cell within each reference time period with the first diagnostic deviation of the diagnosed battery cell. That is, in Figure 10In a state where the minimum voltage among multiple battery cells (3.98V) is less than the voltage (4.1V) at which the diagnostic battery cell is diagnosed, the maximum value (2.4) of the first diagnostic deviation of the battery cell that is different from the diagnostic battery cell is calculated. This value is greater than the product of the first diagnostic deviation of the diagnostic battery cell (3.2) and the set value (0.72), so that the controller 220 can determine that the diagnostic battery cell has been misdiagnosed.

[0161] Therefore, the battery management device 200 according to another embodiment disclosed herein can distinguish between voltage inflection points that typically occur based on the characteristics of the battery cell and voltage inflection points caused by defects, thereby preventing over-inspection and improving the diagnostic rate.

[0162] Figure 11 This is a view illustrating a method of operating a battery management device according to another embodiment disclosed herein. Figure 11 The operation shown can be performed by Figure 2 The battery management device 200 is executed.

[0163] According to the embodiment, before operating S301, the measuring unit 210 can measure the voltage of each of the plurality of battery cells. For example, when the plurality of battery cells are being charged, the measuring unit 210 can measure the voltage of each of the plurality of battery cells at each reference time.

[0164] Reference Figure 11 In operation S301, the controller 220 can calculate a first deviation, which is the deviation between the long moving average and the short moving average of the battery voltage of each of the plurality of battery cells.

[0165] In operation S302, the controller 220 can calculate a second deviation, which is the deviation between the long moving average and the short moving average of the average voltage of the multiple batteries.

[0166] In operation S303, the controller 220 can calculate a first diagnostic deviation, which is the difference between a first deviation and a second deviation for each of the plurality of battery cells.

[0167] In operation S304, the controller 220 can calculate the second diagnostic deviation of each of the multiple battery cells by removing noise from the first diagnostic deviation of each of the multiple battery cells.

[0168] In operation S305, controller 220 can calculate the third diagnostic deviation of each of the multiple battery cells by normalizing the second diagnostic deviation of each of the multiple battery cells.

[0169] In operation S306, the controller 220 can calculate the fourth diagnostic deviation of each of the multiple battery cells by multiplying the third diagnostic deviation of each of the multiple battery cells by the skewness.

[0170] In operation S307, controller 220 can compare the fourth diagnostic deviation of each of the multiple battery cells with a threshold.

[0171] According to the implementation method, operations S304 to S307 may be omitted, and operation S308 may be performed instead.

[0172] In operation S308, controller 220 can configure diagnostic battery cells. According to one embodiment, controller 220 can configure diagnostic battery cells based on a first diagnostic deviation. According to another embodiment, controller 220 can configure diagnostic battery cells based on any one of a second to a fourth diagnostic deviation.

[0173] In operation S309, the controller 220 can determine whether the diagnosed battery cell has been correctly diagnosed by comparing the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of battery cells different from the diagnosed battery cell. According to the embodiment, in operation S309, when the product of the first diagnostic deviation of the diagnosed battery cell and the set value exceeds the first diagnostic deviation of the battery cell with the maximum value, the controller 220 can determine that the diagnosed battery cell has been correctly diagnosed; and when the product of the first diagnostic deviation of the diagnosed battery cell and the set value is less than the first diagnostic deviation of the battery cell with the maximum value, the controller 220 can determine that the diagnosed battery cell has been misdiagnosed.

[0174] Figure 12 This is a view that describes in detail the operation method of a battery management device according to another embodiment disclosed herein. Figure 12 The operation shown can be performed by Figure 2 The battery management device 200 is executed.

[0175] Reference Figure 12 In operation S401, the controller 220 can calculate the first diagnostic deviation of each of the multiple battery cells at each reference time.

[0176] In operation S402, the controller 220 can update the first diagnostic deviation of the battery cell that has the maximum value among the first diagnostic deviations of the battery cells that are different from the diagnosed battery cell at each reference time. That is, the controller 220 can update and store the maximum value among the first diagnostic deviations of the battery cells that are different from the diagnosed battery cell before or after the time when the diagnosed battery cell was diagnosed.

[0177] In operation S403, the controller 220 can calculate the first diagnostic deviation of the diagnostic battery cell at each reference time.

[0178] In operation S404, the controller 220 can update the maximum value of the first diagnostic deviation of the diagnostic battery cell at each reference time.

[0179] Figure 13 This is a block diagram illustrating the hardware configuration of a computing system for performing an operation method of a battery management device according to an embodiment disclosed herein.

[0180] Reference Figure 13 The computing system 2000 according to the embodiments disclosed herein may include an MCU 2100, a memory 2200, an input / output I / F 2300, and a communication I / F 2400.

[0181] The MCU 2100 can be a processor that executes various programs stored in the memory 2200 (e.g., a battery voltage deviation analysis program, etc.), processes various data through these programs, and performs other tasks. Figure 2 The battery management device 200 shown above performs the aforementioned functions.

[0182] The memory 2200 can store various programs related to the operation of the battery management device 200. Furthermore, the memory 2200 can store operational data of the battery management device 200.

[0183] Multiple memories 2200 can be provided as needed. Memory 2200 can be volatile or non-volatile memory. For memory 2200 as volatile memory, random access memory (RAM), dynamic RAM (DRAM), static RAM (SRAM), etc., can be used. For memory 2200 as non-volatile memory, read-only memory (ROM), programmable ROM (PROM), electrically rewritable ROM (EAROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), flash memory, etc., can be used. The above examples of memory 2200 are merely examples and are not limited to these.

[0184] The Input / Output I / F 2300 provides an interface for sending and receiving data by connecting input devices (not shown) such as a keyboard, mouse, touchpad, etc., and output devices such as a display (not shown) to the MCU 2100.

[0185] The Communication I / F2400, which is a component capable of sending and receiving various types of data to and from a server, can be a variety of devices capable of supporting wired or wireless communication. For example, programs or various data used for voltage deviation diagnosis, misdiagnosis determination, and anomaly diagnosis can be sent to or received from a separately provided external server via the Communication I / F2400.

[0186] The above description is merely an illustration of the technical concept of this disclosure, and various modifications and variations can be made by those skilled in the art without departing from the essential characteristics of this disclosure.

[0187] Therefore, the embodiments disclosed herein are intended to describe, and not limit, the technical spirit of this disclosure, and the scope of the technical spirit of this disclosure is not limited by these embodiments. The scope of protection of this disclosure should be interpreted through the appended claims, and all technical spirit within the same scope should be understood to be included within the scope of this disclosure.

Claims

1. A battery management device, the battery management device comprising: A voltage measurement unit configured to measure the voltage of each of a plurality of battery cells; as well as The controller is configured to: For each of the plurality of battery cells, a first deviation is calculated as the deviation between the long moving average and the short moving average of the battery cell voltage; a second deviation is calculated as the deviation between the long moving average and the short moving average of the average voltage of the plurality of battery cells; and a first diagnostic deviation is calculated for each of the plurality of battery cells as the difference between the first deviation and the second deviation. A diagnostic battery cell is set up by diagnosing at least one of the plurality of battery cells based on the first diagnostic deviation of each of the plurality of battery cells; and Whether the diagnostic battery cell is properly diagnosed is determined by comparing the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of battery cells that are different from the diagnostic battery cell.

2. The battery management device according to claim 1, wherein, The controller is also configured to: When the product of the first diagnostic deviation of the diagnosed battery cell and a set value exceeds the first diagnostic deviation of the battery cell having the maximum value, it is determined that the diagnosed battery cell is being diagnosed normally; and When the product of the first diagnostic deviation of the diagnostic battery cell and the set value is less than or equal to the first diagnostic deviation of the battery cell having the maximum value, it is determined that the diagnostic battery cell has been misdiagnosed.

3. The battery management device according to claim 1, wherein, The controller is also configured to: Calculate the first diagnostic deviation for each of the plurality of battery cells at each reference time; as well as The first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of the battery cells that are different from the diagnosed battery cells is updated at each reference time.

4. The battery management device according to claim 1, wherein, The controller is also configured to: Calculate the first diagnostic deviation for each of the diagnostic battery cells at each reference time; and The maximum value of the first diagnostic deviation of the diagnostic battery cell is updated at each reference time.

5. The battery management device according to claim 1, wherein, The controller is further configured to determine that the diagnostic battery cell is being diagnosed normally when the minimum value among the voltages of the plurality of battery cells is greater than the voltage at which the diagnostic battery cell is diagnosed and the diagnosis of the diagnostic battery cell is not determined to be a misdiagnosis.

6. The battery management device according to claim 1, wherein, The controller is also configured to: Update the maximum value of the first diagnostic deviation among battery cells that are different from the diagnosed battery cell at each reference time; and Whether the diagnostic battery cell is properly diagnosed is determined by comparing the updated maximum value with the first diagnostic deviation of the diagnostic battery cell.

7. The battery management device according to claim 1, wherein, The controller is also configured to: The second diagnostic deviation of each of the plurality of battery cells is calculated based on a reference value obtained by multiplying the second deviation of the first diagnostic deviation of each of the plurality of battery cells by a threshold constant; and The diagnostic battery cell is configured by diagnosing at least one of the plurality of battery cells based on a second diagnostic deviation of each of the plurality of battery cells.

8. The battery management device according to claim 7, wherein, The controller is also configured to: The reference value is set as the maximum value between the value obtained by multiplying the second deviation by the first threshold constant and the second threshold constant. The second diagnostic deviation of each of the plurality of battery cells is calculated by excluding the first diagnostic deviations that are less than or equal to the reference value from the first diagnostic deviations of each of the plurality of battery cells; The third diagnostic deviation of each of the plurality of battery cells is calculated by performing normalization by dividing the second diagnostic deviation of each of the plurality of battery cells by the maximum value of the value obtained by multiplying the second deviation by a third threshold constant and a fourth threshold constant. The skewness of each of the plurality of battery cells is calculated by adding the minimum of the third diagnostic deviations of each of the plurality of battery cells to the third diagnostic deviation of each of the plurality of battery cells and dividing the value obtained by the third diagnostic deviation. The fourth diagnostic deviation of each of the plurality of battery cells is calculated by multiplying the skewness by the third diagnostic deviation of each of the plurality of battery cells; as well as The diagnostic battery cell is set by diagnosing at least one of the plurality of battery cells based on whether a fourth diagnostic deviation of each of the plurality of battery cells exceeds a threshold.

9. A method of operating a battery management device, the method comprising the following steps: Measure the voltage of each of multiple battery cells; For each of the plurality of battery cells, a first deviation is calculated as the deviation between the long moving average and the short moving average of the battery cell voltage; a second deviation is calculated as the deviation between the long moving average and the short moving average of the average voltage of the plurality of battery cells; and a first diagnostic deviation is calculated for each of the plurality of battery cells as the difference between the first deviation and the second deviation. A diagnostic battery cell is set up by diagnosing at least one of the plurality of battery cells based on a first diagnostic deviation of each of the plurality of battery cells; and The first diagnostic deviation of the battery cell that has the maximum value among the first diagnostic deviations of battery cells that are different from the diagnostic battery cell is compared with the first diagnostic deviation of the diagnostic battery cell to determine whether the diagnostic battery cell is properly diagnosed.

10. The operating method according to claim 9, wherein, The step of determining whether the diagnostic battery cell has been properly diagnosed by comparing the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of battery cells that are different from the diagnostic battery cell with the first diagnostic deviation of the diagnostic battery cell includes the following steps: When the product of the first diagnostic deviation of the diagnosed battery cell and a set value exceeds the first diagnostic deviation of the battery cell having the maximum value, it is determined that the diagnosed battery cell is being diagnosed normally; and When the product of the first diagnostic deviation of the diagnosed battery cell and the set value is less than or equal to the first diagnostic deviation of the battery cell with the maximum value, it is determined that the diagnosed battery cell has been misdiagnosed.

11. The operating method according to claim 9, further comprising the following steps: Calculate the first diagnostic deviation for each of the plurality of battery cells at each reference time; as well as The first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of the battery cells that are different from the diagnosed battery cells is updated at each reference time.

12. The operating method according to claim 9, further comprising the following steps: Calculate the first diagnostic deviation for each of the diagnostic battery cells at each reference time; as well as The maximum value of the first diagnostic deviation of the diagnostic battery cell is updated at each reference time.

13. The operating method according to claim 9, wherein, The step of determining whether the diagnostic battery cell has been properly diagnosed by comparing the first diagnostic deviation of the battery cell with the maximum value among the first diagnostic deviations of battery cells that are different from the diagnostic battery cell with the first diagnostic deviation of the diagnostic battery cell includes the following steps: Update the maximum value of the first diagnostic deviation among battery cells that are different from the diagnosed battery cell at each reference time; and Whether the diagnostic battery cell is properly diagnosed is determined by comparing the updated maximum value with the first diagnostic deviation of the diagnostic battery cell.

14. The operating method according to claim 9, wherein, The step of setting up a diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on a first diagnostic deviation of each of the plurality of battery cells includes the following steps: The second diagnostic deviation of each of the plurality of battery cells is calculated based on a reference value obtained by multiplying the second deviation of the first diagnostic deviation of each of the plurality of battery cells by a threshold constant; and The diagnostic battery cell is configured by diagnosing at least one of the plurality of battery cells based on a second diagnostic deviation of each of the plurality of battery cells.

15. The operating method according to claim 14, wherein, The step of setting up the diagnostic battery cell by diagnosing at least one of the plurality of battery cells based on a second diagnostic deviation of each of the plurality of battery cells includes the following steps: The reference value is set as the maximum value between the value obtained by multiplying the second deviation by the first threshold constant and the second threshold constant. The second diagnostic deviation of each of the plurality of battery cells is calculated by excluding the first diagnostic deviations that are less than or equal to the reference value from the first diagnostic deviations of each of the plurality of battery cells; The third diagnostic deviation of each of the plurality of battery cells is calculated by performing normalization by dividing the second diagnostic deviation of each of the plurality of battery cells by the maximum value of the value obtained by multiplying the second deviation by a third threshold constant and a fourth threshold constant. The skewness of each of the plurality of battery cells is calculated by adding the minimum of the third diagnostic deviations of each of the plurality of battery cells to the third diagnostic deviation of each of the plurality of battery cells and dividing the value obtained by the third diagnostic deviation. The fourth diagnostic deviation of each of the plurality of battery cells is calculated by multiplying the skewness by the third diagnostic deviation of each of the plurality of battery cells; and The diagnostic battery cell is set by diagnosing at least one of the plurality of battery cells based on whether a fourth diagnostic deviation of each of the plurality of battery cells exceeds a threshold.

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