Battery management device and method

Abstract

To provide a battery management device and method, which enable early prediction of a battery cell failure and thus accident prevention by diagnosing an unstable behavior of battery cells at an early stage and classifying the type of the unstable behavior.SOLUTION: A battery management device according to an embodiment disclosed herein may comprise: a measurement unit for measuring voltages and currents of battery cells; a computation unit configured to determine operation sections of the battery cells on the basis of the currents of the battery cells and compute a comparison value for each of the battery cells through a normalization operation of the voltages of the battery cells; and a diagnosis unit for diagnosing states of the battery cells by comparing the comparison values of the battery cells with a reference value.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2021-0002908 filed on January 8, 2021, and all the contents disclosed in the document of the Korean patent application are incorporated herein by reference in their entirety. The embodiments disclosed in this document relate to a battery management device and method.

Background Art

[0002] In recent years, research and development on secondary batteries have been actively conducted. Here, a secondary battery is a rechargeable battery, which includes both conventional Ni / Cd batteries, Ni / MH batteries, etc. and recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of much higher energy density compared to conventional Ni / Cd batteries, Ni / MH batteries, etc. In addition, since lithium-ion batteries can be manufactured in a small and lightweight manner, they are used as power sources for mobile devices. Also, the use range of lithium-ion batteries has been extended to power sources for electric vehicles and they have attracted attention as next-generation energy storage media.

[0003] In addition, secondary batteries are generally used as battery packs including battery modules in which a plurality of battery cells are connected in series and / or in parallel. And the battery pack is managed and controlled in terms of its state and operation by a battery management system.

[0004] In the case of such lithium-ion batteries, unstable behavior may be shown according to the charge and discharge state of the battery cell. Such unstable behavior occurring during charge and discharge of the battery cell may cause accidents such as fires if not diagnosed early. However, conventionally, there has been no clear criterion for classifying such abnormalities. Thus, diagnosing abnormal behavior of battery cells and classifying types for each abnormal behavior is an important issue.

Summary of the Invention

Problems to be Solved by the Invention

[0005] One object of the embodiments disclosed in this document is to provide a battery management apparatus and method that can early diagnose unstable behavior of a battery cell, classify the types of unstable behavior, and thus early predict a failure of the battery cell to prevent an accident.

[0006] The technical problems of the embodiments disclosed in this document are not limited to the technical problems 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 Problems

[0007] A battery management apparatus according to an embodiment disclosed in this document can include a measurement unit that measures the voltage and current of a battery cell, a calculation unit that determines an operating range of the battery cell based on the current of the battery cell and calculates a comparison value for each of the battery cells by performing a normalization operation on the voltage of the battery cell, and a diagnosis unit that diagnoses the state of the battery cell by comparing the comparison value of the battery cell with a reference value.

[0008] In one embodiment, the comparison value of the battery cell can include first data that is a value obtained by normalizing an average output value of voltages for each preset first interval for each of the battery cells, second data that is a change amount of the first data, and third data that is a value obtained by normalizing the second data. In one embodiment, the diagnosis unit can diagnose the state of the battery cell by comparing the first data, the second data, and the third data with a first reference value, a second reference value, and a third reference value, respectively.

[0009] In one embodiment, the comparison value of the battery cell can include fourth data that is a value obtained by normalizing an average output value with respect to a voltage change amount for each preset interval for each of the battery cells, fifth data that is a change amount of the fourth data, and sixth data that is a value obtained by normalizing an average of the fifth data. In one embodiment, the diagnosis unit can diagnose the state of the battery cell by comparing the fourth data, the fifth data, and the sixth data with a fourth reference value, a fifth reference value, and a sixth reference value, respectively.

[0010] In one embodiment, the state of the battery cell can include the rise and fall of voltage and the long-term stabilization (relaxation) in the charging, discharging, and resting intervals of the battery cell.

[0011] In one embodiment, the calculation unit can calculate the comparison value when the size of the section for performing the normalization operation on the voltage of the battery cell is less than the reference value.

[0012] In one embodiment, when the size of the section for performing the normalization operation on the voltage of the battery cell is greater than or equal to the reference value, the calculation unit can change the size of the section and recalculate the comparison value.

[0013] In one embodiment, the calculation unit can determine whether the operating interval of the battery cell is included in any one of the charging, discharging, or resting intervals based on the current of the battery cell.

[0014] In one embodiment, the battery cell can include a battery cell that has been previously diagnosed as abnormal by principal component analysis (PCA).

[0015] In one embodiment, the types of abnormalities of the battery cell can include lithium precipitation, internal short circuit, and disconnection of the battery tab. In one embodiment, when at least one of the voltage behaviors of the battery cell is a decrease in the charging voltage, a decrease in the resting voltage after charging, an increase in the discharging voltage, or an increase in the resting voltage after discharging, the diagnosis unit can classify it as lithium precipitation.

[0016] According to one embodiment, when the voltage behavior of the battery cell is at least one of a decrease in charge and discharge voltage and a decrease in rest voltage after charge and discharge, it can be classified as an internal short circuit.

[0017] According to one embodiment, when the voltage behavior of the battery cell is at least one of a decrease in discharge voltage and an increase in charge and discharge voltage, it can be classified as a disconnection of the battery tab.

[0018] The battery management method according to one embodiment disclosed in this document includes steps of measuring the voltage and current of a battery cell, determining the operating interval of the battery cell based on the current of the battery cell, performing a normalization operation on the voltage of the battery cell to calculate a comparison value for each battery cell, and diagnosing the state of the battery cell by comparing the comparison value of the battery cell with a reference value.

[0019] According to one embodiment, the comparison value of the battery cell can include first data which is a value obtained by normalizing the average output value of the voltage for each preset first interval for each battery cell, second data which is the change amount of the first data, and third data which is a value obtained by normalizing the second data.

[0020] According to one embodiment, the step of diagnosing the state of the battery cell can diagnose the state of the battery cell by comparing the first data, the second data, and the third data with a first reference value, a second reference value, and a third reference value respectively.

[0021] According to one embodiment, the comparison value of the battery cell can include fourth data which is a value obtained by normalizing the average output value with respect to the preset voltage change amount for each interval for each battery cell, fifth data which is the change amount of the fourth data, and sixth data which is a value obtained by normalizing the average of the fifth data.

[0022] According to one embodiment, the diagnosis unit can diagnose the state of the battery cell by comparing the fourth data, the fifth data, and the sixth data with a fourth reference value, a fifth reference value, and a sixth reference value, respectively.

Advantages of the Invention

[0023] The battery management device and method according to one embodiment disclosed in this document can diagnose unstable behavior of a battery cell at an early stage, classify the types of unstable behavior, predict a failure of the battery cell at an early stage, and prevent an accident.

Brief Description of the Drawings

[0024]

Figure 1

Figure 2

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Embodiments for Carrying Out the Invention

[0025] Hereinafter, various embodiments disclosed in this document will be described in detail with reference to the accompanying drawings. In this document, the same reference numerals are assigned to the same components in the drawings, and duplicate descriptions of the same components are omitted.

[0026] Regarding the various embodiments disclosed in this document, the specific structural or functional descriptions are merely exemplified for the purpose of explaining the embodiments, and the various embodiments disclosed in this document may be implemented in various forms and should not be construed as being limited to the embodiments described in this document.

[0027] Expressions such as "first", "second", "the first", or "the second" used in various embodiments may modify various components without regard to order and / or importance, and do not limit the components. For example, without departing from the scope of the rights of the embodiments disclosed in this document, the first component may be named the second component, and similarly, the second component may also be renamed the first component.

[0028] The terms used in this document are merely used to explain specific embodiments and are not intended to limit the scope of other embodiments. Singular expressions may include plural expressions unless the context clearly indicates otherwise.

[0029] All terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by a person having ordinary skill in the technical field of the embodiments disclosed in this document. Terms defined in commonly used dictionaries may be interpreted to have the same or similar meanings as their meanings in the context of the related art, and unless clearly defined in this document, they are not to be interpreted in an ideal or overly formal sense. In some cases, even terms defined in this document should not be interpreted in a way that excludes the embodiments disclosed in this document.

[0030] FIG. 1 is a diagram showing a battery control system including a battery management device according to an embodiment disclosed in this document. Specifically, FIG. 1 schematically shows a battery control system including a battery pack 1 according to an embodiment disclosed in this document and an upper controller 2 included in an upper system.

[0031] As shown in FIG. 1, the battery pack 1 can include a plurality of battery modules 10, a sensor 12, a switching unit 14, and a battery management system 20. At this time, the battery pack 1 can be provided with a plurality of battery modules 10, sensors 12, switching units 14, and battery management systems 20.

[0032] The plurality of battery modules 10 can each include at least one rechargeable battery cell. At this time, the plurality of battery modules 10 may be connected in series or in parallel. The sensor 12 can detect the current flowing through the battery pack 1. At this time, the detection signal can be transmitted to the battery management system 20.

[0033] The switching unit 14 is connected in series to the (+) terminal side or the (-) terminal side of the battery module 10 and can control the flow of the charge and discharge current of the battery module 10. For example, the switching unit 14 can use at least one relay, electromagnetic contactor, etc. according to the specifications of the battery pack 1.

[0034] The battery management system 20 can monitor the voltage, current, temperature, etc. of the battery pack 1, and perform control management to prevent overcharging, over-discharging, etc. For example, it can include an RBMS.

[0035] The battery management system 20 is an interface that receives the input of the measured values of the various parameters described above, and can include a plurality of terminals, and a circuit that is connected to these terminals and processes the received input values. In addition, the battery management system 20 can also control the ON / OFF of a switching unit 12, such as a relay or a contactor, is connected to the battery module 10, and can monitor the state of each battery module 10.

[0036] On the other hand, in the battery management system 20 disclosed in this document, as will be described later, a comparison value can be calculated by performing statistical analysis (such as normalization calculation, etc.) on the voltage of the battery cell measured through another program, and analyzing it to diagnose the state of the battery cell.

[0037] The upper controller 2 can transmit a control signal for controlling the battery module 10 to the battery management system 20. Thereby, the operation of the battery management system 20 can be controlled based on the control signal applied from the upper controller 2. In addition, the battery module 10 may be configured to be included in an ESS (Energy Storage System). In this case, the upper controller 2 may be a controller (BBMS) of a battery bank including a plurality of battery packs 1 or an ESS controller that controls the entire ESS including a plurality of banks. However, the battery pack 1 is not limited to such applications. Since the configurations of such a battery pack 1 and the battery management system 20 are known configurations, more specific descriptions will be omitted.

[0038] FIG. 2 is a block diagram showing the configuration of a battery management device according to an embodiment disclosed in this document. Referring to FIG. 2, the battery management device 100 disclosed in this document can include a measurement unit 110, a calculation unit 120, a diagnosis unit 130, and a storage unit 140.

[0039] The measurement unit 110 can measure the voltage and current of the battery cell. In this case, the measurement unit 110 can measure the voltage and current of the battery cell at a fixed period. The measurement unit 110 can store the measured voltage value and current value in the storage unit 140.

[0040] The calculation unit 120 can determine the operating range of the battery cell based on the current of the battery cell, perform a normalization operation on the voltage of the battery cell, and calculate a comparison value for each battery cell. In this case, the battery cell can include a battery cell that has been previously diagnosed as abnormal by principal component analysis (PCA).

[0041] Specifically, the calculation unit 120 can determine whether the operating range of the battery cell is included in any one of the charging, discharging, or resting ranges based on the current of the battery cell. For example, the calculation unit 120 can determine whether the battery cell is in a charging or discharging state according to the direction (+ / -) of the current of the battery cell, and can determine that it is a resting range when the current of the battery cell is 0.

[0042] The comparison values of the battery cells calculated via the calculation unit 120 can include first data which is a value obtained by normalizing the average output value of the voltage for each preset interval (window) for each battery cell, second data which is the amount of change of the first data, and third data which is a value obtained by normalizing the second data. Further, the comparison values of the battery cells calculated via the calculation unit 120 can include fourth data which is a value obtained by normalizing the average output value with respect to the amount of voltage change for each preset interval for each battery cell, fifth data which is the amount of change of the fourth data, and sixth data which is a value obtained by normalizing the average of the fifth data. For example, assuming that the measurement unit 110 measures the voltage of the battery cells at 1-second intervals for 1800 seconds, the interval (window) for performing the normalization operation is set to 200 seconds and can be divided into a total of 9 intervals. At this time, 200 voltage data can be included in the preset interval. However, it is not limited to this, and the above-mentioned preset interval can be arbitrarily determined by the user according to the need.

[0043] Further, when the size of the interval for performing the normalization operation on the voltage of the battery cell, that is, the size of the window, is less than the reference value, the calculation unit 120 can calculate the comparison value. This is because if the size of the window is excessively large, the calculation accuracy will decrease. Therefore, when the size of the window for performing the normalization operation on the voltage of the battery cell is greater than or equal to the reference value, the calculation unit 120 can recalculate the comparison value by changing the size of the interval. For example, the size of the window can be decreased by 10 each time.

[0044] The diagnosis unit 130 can diagnose the state of the battery cell by comparing the comparison value of the battery cell with the reference value. In this case, the diagnosis unit 130 can diagnose the state of the battery cell by comparing the first data to the third data calculated via the calculation unit 120 with the set first reference value to the third reference value respectively. Further, the diagnosis unit 130 can diagnose the state of the battery cell by comparing the fourth data to the sixth data with the fourth reference value to the sixth reference value respectively.

[0045] In addition, the voltage behavior of the battery cell that can be diagnosed via the diagnosis unit 130 can include the rise and fall of the voltage and the long-term stabilization (relaxation) of the voltage during the charging, discharging, and rest intervals of the battery cell. This will be described in detail later with reference to FIG. 9. The types of abnormalities of the battery cell that can be classified via such a diagnosis unit 130 can include lithium precipitation, internal short circuit, and disconnection of the battery tab.

[0046] For example, when at least one of the voltage drop during charging, the voltage drop during the rest after charging, the voltage rise during discharging, and the voltage rise during the rest after discharging is satisfied in the voltage behavior of the battery cell, the diagnosis unit 130 can classify it as lithium precipitation. Further, when at least one of the voltage drops during charging and discharging and the voltage drops during the rest after charging and discharging is satisfied in the voltage behavior of the battery cell, the diagnosis unit 130 can classify it as an internal short circuit. And when at least one of the voltage drop during discharging and the voltage rises during charging and discharging is satisfied in the voltage behavior of the battery cell, the diagnosis unit 130 can classify it as a disconnection of the battery tab. However, the types of abnormalities that can be classified via the battery management device 100 according to an embodiment disclosed in this document are not limited to this, and various types of abnormalities can be classified according to the voltage behavior of the battery cell.

[0047] The storage unit 140 can store measurement data such as the voltage and current of the battery cell. Further, the storage unit 140 can store comparison values calculated via the calculation unit 120, for example, the first data to the sixth data and the first reference value to the sixth reference value.

[0048] On the other hand, in FIG. 2, the battery management device 100 according to an embodiment disclosed in this document has been described as including the storage unit 140, but the battery management device 100 can include a communication unit (not shown) instead of the storage unit 140. In this case, the battery management device 100 can store various data such as comparison value data and reference values for the battery cell in an external server and operate in a manner of transmitting and receiving via the communication unit.

[0049] As described above, the battery management device according to one embodiment disclosed in this document can diagnose the unstable behavior of battery cells at an early stage, classify the types of unstable behavior, and thus predict the failure of battery cells at an early stage to prevent accidents.

[0050] FIG. 3 is a flowchart for explaining a battery management method according to one embodiment disclosed in this document. Referring to FIG. 3, the battery management method according to one embodiment disclosed in this document first diagnoses the presence or absence of abnormalities in battery cells by principal component analysis (PCA) (S110). That is, in step S110, battery cells determined to be abnormal by conventional principal component analysis techniques are extracted.

[0051] Then, the behavior of battery cells is analyzed by a normalized classifier to determine abnormal behavior (S120). At this time, as described with reference to FIG. 2, the normalized classifier calculates first data, which is a normalized value of the average output value of voltage for each preset interval (window) for each battery cell, second data, which is the amount of change in the first data, and third data, which is a normalized value of the second data, and can compare such first to third data with reference values.

[0052] If, in step S120, at least one of the first to third data is greater than the first to third reference values (that is, if abnormal behavior can be determined by the normalized classifier) (YES), the type of abnormality of the battery cell is diagnosed based on the measured current and voltage of the battery cell (S140). At this time, the abnormal behavior of the battery cell can be determined based on the current value (+, -, or 0) and voltage (+ or -) of the battery cell.

[0053] On the other hand, in step S120, if it is determined that at least one of the first to third data is smaller than the first to third reference values, or if the classification itself has not been performed (NO), the process proceeds to step S130. Further, in step S130, the behavior of the battery cell is analyzed based on the sigma delta function method to determine an abnormal behavior (S130).

[0054] At this time, as described with reference to FIG. 2, the sigma delta function method calculates fourth data, which is a value obtained by normalizing the average output value with respect to the voltage change amount for each preset section for each battery cell, fifth data, which is the change amount of the fourth data, and sixth data, which is a value obtained by normalizing the average of the fifth data, and such fourth to sixth data can be compared with reference values.

[0055] If, in step S130, at least one of the fourth to sixth data is greater than the fourth to sixth reference values (that is, if an abnormal behavior can be determined by the sigma delta function method) (YES), the type of abnormality of the battery cell is diagnosed based on the measured current and voltage of the battery cell (S140). At this time, the abnormal behavior of the battery cell can be determined based on the current value (+, −, or 0) and voltage (+ or −) of the battery cell.

[0056] On the other hand, in step S130, if it is determined that at least one of the fourth to sixth data is smaller than the fourth to sixth reference values, or if the classification itself has not been performed (NO), since the battery cell is normal, the procedure ends as it is.

[0057] FIG. 4 shows a diagnostic classification table indicating types that can be classified via the battery management device according to an embodiment disclosed in this document. Referring to FIG. 4, the voltage behaviors that can be classified via the battery management device according to an embodiment disclosed in this document can include a decrease in potential during charging and discharging, a decrease in resting potential after charging and discharging, an increase in potential during charging and discharging, an increase in resting potential after charging and discharging, and long-term stabilization.

[0058] At this time, when the voltage behavior of the battery cell belongs to one of 1. the decrease in charging potential, 3. the decrease in rest potential after charging, 6. the increase in discharging potential, and 8. the increase in rest potential after discharging, it can be classified as "lithium precipitation". Also, when the voltage behavior of the battery cell belongs to one of 1. the decrease in charging potential, 2. the decrease in discharging potential, 3. the decrease in rest potential after charging, and 4. the decrease in rest potential after discharging, it can be classified as "internal short circuit". And when the voltage behavior of the battery cell belongs to one of 2. the decrease in discharging potential, 5. the increase in charging potential, and 6. the increase in discharging potential, it can be classified as the disconnection of the battery tab. However, Fig. 4 is merely an illustration, and the types of abnormalities that can be classified via the battery management device according to an embodiment disclosed in this document are not limited to this, and various other types of abnormalities can be classified according to the voltage behavior of the battery cell.

[0059] Fig. 5 is a flowchart showing a battery management method according to an embodiment disclosed in this document. Referring to Fig. 5, it shows the normalization classification method described in Fig. 3 of the battery management method according to an embodiment disclosed in this document. Such a normalization classification method first measures the current and voltage of the battery cell (S210). In this case, in step S210, the current and voltage of the battery cell can be measured at a constant period (for example, 1 second) during a preset interval (for example, 1800 seconds).

[0060] Then, the average output of voltage for each window (interval) (WV1) is calculated (S220). In this case, the window is a non-overlap moving window, and for example, the size of the window may be 200 seconds.

[0061] Next, in step S230, the first data to the third data can be calculated. At this time, the first data (NV) may be a value obtained by normalizing the average output (WV1) of the voltage for each window calculated in step S220 (Normalization(WV1)). Also, the second data (dNV) may be the amount of change in the first data, for example, a value obtained by differentiating the first data (diff(NV)). And the third data (NV2) may be a value obtained by normalizing the second data again (Normalization(dNV)).

[0062] Then, the third data (NV2) is compared with the third reference value (S240). If the third data is greater than the third reference value (YES), the battery cell is determined to be an abnormal battery cell, and the type of abnormality is classified (S270). At this time, after determining the abnormal behavior based on the current and voltage measured in step S210, the type of abnormality can be classified according to the diagnostic classification table in FIG. 4 described above.

[0063] For example, after determining whether the battery cell is in a charging, discharging, or resting section according to whether the current value of the battery cell is +, -, or 0, it can be determined whether the voltage of the battery cell changes in the + or - direction, that is, whether the voltage of the battery cell rises or falls by detecting the voltage change of the battery cell.

[0064] Also, in step S240, if the third data is smaller than the third reference value (NO), the second data (dNV) is compared with the second reference value again (S250). If the second data is greater than the second reference value (YES), the battery cell is determined to be an abnormal battery cell, and the type of abnormality is classified (S270). Also in this case, after determining the abnormal behavior based on the current and voltage measured in step S210, the type of abnormality can be classified according to the diagnostic classification table in FIG. 4 described above.

[0065] Next, in step S250, if the second data is smaller than the second reference value (NO), the first data (NV) is compared with the first reference value again (S250). If the first data is larger than the first reference value (YES), the battery cell is determined to be an abnormal battery cell, and the type of abnormality is classified (S270). Similarly in this case, after determining the abnormal behavior based on the current and voltage measured in step S210, the type of abnormality can be classified according to the diagnostic classification table of FIG. 4 described above.

[0066] Also, in steps S240 to S260, the diagnosis is performed by sequentially comparing the third data to the first data with the third to first reference values. However, the battery management method disclosed in this document is not limited to this, and the analysis order of the first to third data may be changed. For example, the first to third reference values in steps S240 to S260 may be arbitrarily set by the user or values calculated via the battery management device.

[0067] FIG. 6 is a diagram showing a graph at the time of an increase in the discharge potential of a battery cell calculated by the battery management method according to an embodiment disclosed in this document. At this time, the horizontal axis of the graph (a) in FIG. 6 indicates time (seconds), and the vertical axis indicates the voltage (V) of the battery cell. The horizontal axes of the graphs (b) to (d) in FIG. 6 indicate the window number (n), and the vertical axes indicate the value normalized with respect to the voltage of the battery cell and its differential value.

[0068] First, referring to the graph (a) in FIG. 6, it can be seen that in the case of a battery cell in which an increase in the discharge potential has occurred, a general shape in which the voltage has increased by a certain magnitude after 600 seconds is shown. However, since the change in the general shape is not large, it is not easy to determine the abnormal behavior only from such a voltage graph of the battery cell.

[0069] Referring to the graph of (b) in FIG. 6, it shows the average voltage calculated for each window and normalized with respect to the measured voltage of the battery cell shown in (a) of FIG. 6 (first data). At this time, as shown in the graph of (b) in FIG. 6, it can be seen that in the case of a battery cell in which an increase in the discharge potential of the battery cell occurs, the change is remarkably shown compared to other battery cells.

[0070] And, the graph of (c) in FIG. 6 is the value obtained by differentiating the value of the graph of (b) (second data), and the graph of (d) shows the normalized graph of (c) (third data). In particular, referring to the graphs of (c) and (d) in FIG. 6, it can be seen that in the case of a battery cell in which an increase in the discharge potential occurs, a peak shape is shown in the 8th window and the 13th window, etc.

[0071] Thus, referring to the graphs of (a) to (d) in FIG. 6, it can be confirmed that, compared with the graph simply showing the measured voltage of the battery cell, in the case of the first to third data obtained by taking statistical values of the voltage of such a battery cell, the change in the profile of the battery cell in which an increase in the discharge potential occurs appears more remarkably. Therefore, by comparing the graphs of (b) to (d) regarding such first to third data with a reference value, the presence or absence of abnormality of the battery cell can be detected more easily and accurately.

[0072] FIG. 7 is a diagram showing a graph at the time of a decrease in the charging potential of a battery cell calculated by the battery management method according to an embodiment disclosed in this document. At this time, the horizontal axis of the graph of (a) in FIG. 7 indicates time (seconds), and the vertical axis indicates the voltage (V) of the battery cell. And, the horizontal axis of the graphs of (b) to (d) in FIG. 7 indicates the window number (n), and the vertical axis indicates the value normalized with respect to the voltage of the battery cell and its differential value.

[0073] First, referring to the graph of (a) in FIG. 7, it can be seen that in the case of a battery cell in which a decrease in the charging potential occurs, a profile in which the voltage decreases by a certain magnitude is shown at the point of about 1000 seconds. However, since the change in the profile is not large as in FIG. 6, it is not easy to determine an abnormal behavior only from such a voltage graph of the battery cell.

[0074] Also, referring to the graph of (b) in FIG. 7, it shows the average voltage calculated for each window and normalized with respect to the measured voltage of the battery cell shown in (a) of FIG. 7 (first data). At this time, as shown in the graph of (b) in FIG. 7, it can be seen that in the case of the battery cell in which the charging potential has dropped, the change is remarkably apparent compared to other battery cells.

[0075] And the graph of (c) in FIG. 7 is the value obtained by differentiating the value of the graph of (b) (second data), and the graph of (d) shows the normalized graph of (c) (third data). In particular, referring to the graphs of (c) and (d) in FIG. 6, it can be seen that in the case of the battery cell in which the charging potential has dropped, the general shape of the peak is shown in a number of windows.

[0076] Thus, referring to the graphs of (a) to (d) in FIG. 7, it can be confirmed that in the case of the first to third data obtained by taking statistical values of the voltage of such a battery cell, the change in the general shape of the battery cell in which the charging potential has dropped appears more remarkably compared to the graph simply showing the measured voltage of the battery cell. Therefore, by comparing the graphs of (b) to (d) regarding such first to third data with a reference value, it is possible to more easily and accurately detect the presence or absence of abnormalities in the battery.

[0077] FIG. 8 is a flowchart showing a battery management method according to an embodiment disclosed in this document. Referring to FIG. 8, it shows the sigma-delta function method described in FIG. 3 of the battery management method according to an embodiment disclosed in this document. Such a sigma-delta function method first measures the current and voltage of the battery cell (S310). In this case, in step S310, the current and voltage of the battery cell can be measured at a constant period (for example, 1 second) during a preset interval (for example, 1800 seconds).

[0078] Then, the average output (WV2) of the voltage change amount for each window (interval) is calculated (S320). In this case, the window is a non-overlap moving window, and for example, the size of the window may be 200 seconds.

[0079] Next, in step S330, the fourth data to the sixth data can be calculated. At this time, the fourth data (NV) may be a value obtained by normalizing the average output (WV2) of the voltage change for each window calculated in step S320 (Normalization(WV2)). Also, the fifth data (dNV) may be the change amount of the fourth data, for example, a value obtained by differentiating the fourth data (diff(NV)). And the sixth data (NV2) may be a value obtained by normalizing the fifth data again (Normalization(dNV)).

[0080] Then, the sixth data (NV2) is compared with the sixth reference value (S240). If the sixth data is greater than the sixth reference value (YES), the battery cell is determined to be an abnormal battery cell, and the type of abnormality is classified (S370). At this time, after determining the abnormal behavior based on the current and voltage measured in step S310, the type of abnormality can be classified according to the diagnostic classification table in FIG. 4 described above.

[0081] For example, after determining whether the battery cell is in a charging, discharging, or resting interval according to whether the current value of the battery cell is +, -, or 0, it can be determined whether the voltage of the battery cell changes in the + or - direction, that is, whether the voltage of the battery cell rises or falls by detecting the voltage change of the battery cell.

[0082] Also, in step S440, when the sixth data is smaller than the sixth reference value (NO), the fifth data (dNV) is compared with the fifth reference value again (S350). If the fifth data is larger than the fifth reference value (YES), the battery cell is determined to be an abnormal battery cell, and the type of abnormality is classified (S370). Similarly in this case, after determining the abnormal behavior based on the current and voltage measured in step S310, the type of abnormality can be classified according to the diagnostic classification table in FIG. 4 described above.

[0083] Next, in step S350, when the fifth data is smaller than the fifth reference value (NO), the fourth data (NV) is compared with the fourth reference value again (S350). If the fourth data is larger than the fourth reference value (YES), the battery cell is determined to be an abnormal battery cell, and the type of abnormality is classified (S370). Similarly in this case, after determining the abnormal behavior based on the current and voltage measured in step S310, the type of abnormality can be classified according to the diagnostic classification table in FIG. 4 described above.

[0084] Also, in steps S340 to S360, the diagnosis is performed by sequentially comparing the sixth data to the fourth data with the sixth to fourth reference values. However, the battery management method disclosed in this document is not limited to this, and the analysis order of the fourth to sixth data may be changed. For example, the fourth to sixth reference values in steps S340 to S360 may be arbitrarily set by the user or values calculated via the battery management device.

[0085] And in step S380, when no abnormal behavior of the battery cell is determined over steps S340 to S370, the window size (WS) can be compared with a reference value (TH_WS). If, in step S380, the window size is larger than the reference value, it is possible to return to step S320 to correct the window size. For example, the window size can be decreased by 10 each time. That is, if the window size is excessively large, the accuracy of the abnormal behavior determination decreases. Therefore, when no abnormal behavior is detected while proceeding to steps S340 to S370, the window size can be decreased to improve the accuracy of the abnormality diagnosis.

[0086] FIG. 9 is a diagram showing a graph at the time of a decrease in the discharge potential of a battery cell calculated by the battery management method according to an embodiment disclosed in this document. At this time, the horizontal axis of the graph (a) in FIG. 9 indicates time (seconds), and the vertical axis indicates the voltage (V) of the battery cell. And the horizontal axis of the graphs (b) and (c) in FIG. 9 indicates the window number (n), and the vertical axis indicates the value normalized with respect to the voltage change of the battery cell and its differential value. Also, the horizontal axis of the graph (d) in FIG. 9 indicates the battery cell number (#), and the vertical axis indicates the value obtained by normalizing the value of the graph (c).

[0087] First, referring to the graph (a) in FIG. 9, in the case of a battery cell in which a decrease in the discharge potential has occurred, it can be seen that after about 1500 seconds, a general form in which the voltage decreases by a certain magnitude is shown. However, since the change in the general form is not large, it is not easy to determine abnormal behavior only from such a voltage graph of the battery cell.

[0088] Also, referring to the graph (b) in FIG. 9, it shows the average of the voltage changes calculated for each window and normalized (fourth data) with respect to the measured voltage of the battery cell shown in FIG. 9(a). The graph (c) in FIG. 9 shows the value obtained by differentiating the value of the graph (b) (fifth data). At this time, as shown in the graphs (b) and (c) in FIG. 9, in the case of a battery cell in which a decrease in the discharge potential of the battery cell has occurred, it can be seen that a significant change in voltage appears in a specific window (around 12).

[0089] And the graph of (d) in FIG. 9 shows the graph obtained by normalizing the graph of (c) and comparing it between battery cells (the sixth data). In particular, referring to the graph of (d) in FIG. 9, it can be seen that in the case of the battery cell in which the discharge potential has decreased (generally cell No. 180), a general shape in which the value decreases relatively greatly when compared with other battery cells is shown.

[0090] Thus, referring to the graphs of (a) to (d) in FIG. 9, it can be confirmed that when comparing with the graph simply showing the measured voltage of the battery cell, in the case of the fourth to sixth data taking statistical values of the voltage of the battery cell, the change in the general shape of the battery cell in which the discharge potential has decreased appears more significantly. Therefore, by comparing the graphs of (b) to (d) in FIG. 9 regarding such fourth to sixth data with a reference value, the presence or absence of abnormality in the battery cell can be detected more easily and accurately.

[0091] FIG. 10 is a diagram showing a graph at the time of a decrease in the charging potential of a battery cell calculated by the battery management method according to an embodiment disclosed in this document. At this time, the horizontal axis of the graph of (a) in FIG. 10 indicates time (seconds), and the vertical axis indicates the voltage (V) of the battery cell. And the horizontal axes of the graphs of (b) and (c) in FIG. 10 indicate the window number (n), and the vertical axes indicate the value normalized with respect to the voltage change of the battery cell and its differential value, respectively. Also, the horizontal axis of the graph of (d) in FIG. 10 indicates the battery cell number (#), and the vertical axis indicates the value obtained by normalizing the value of the graph of (c).

[0092] First, referring to the graph of (a) in FIG. 10, it can be seen that in the case of the battery cell in which the charging potential has decreased, a general shape in which the voltage decreases by a certain magnitude after about 1000 seconds is shown. However, since the change in the general shape is not large, it is not easy to determine the abnormal behavior only from such a voltage graph of the battery cell.

[0093] Referring to the graph of (b) in Fig. 10, it shows the average voltage change calculated and normalized for each window with respect to the measured voltage of the battery cell shown in (a) of Fig. 10 (the fourth data). The graph of (c) in Fig. 10 shows the value obtained by differentiating the value of the (b) graph (the fifth data). At this time, as shown in the graphs of (b) and (c) in Fig. 10, it can be seen that in the case of the battery cell where the charging potential has dropped, a significant voltage change appears in a specific window (around about 4 - 5).

[0094] And the graph of (d) in Fig. 10 shows the result of normalizing the (c) graph and comparing it between battery cells (the sixth data). In particular, referring to the graph of (d) in Fig. 10, it can be seen that in the case of the battery cell where the charging potential has dropped (generally cell number 150), a general shape in which the value decreases relatively significantly when compared with other battery cells is shown.

[0095] In this way, referring to the graphs of (a) - (d) in Fig. 10, it can be confirmed that when comparing with the graph simply showing the measured voltage of the battery cell, in the case of the fourth to sixth data taking statistical values of the voltage of the battery cell, the change in the general shape of the battery cell where the charging potential has dropped appears more significantly. Therefore, by comparing the graphs of (b) - (d) in Fig. 10 regarding such fourth to sixth data with a reference value, the presence or absence of abnormalities in the battery cell can be detected more easily and accurately.

[0096] In this way, the battery management method according to an embodiment disclosed in this document can diagnose the unstable behavior of the battery cell at an early stage, classify the types of unstable behavior, and thus predict the failure of the battery cell at an early stage to prevent accidents.

[0097] Fig. 11 is a graph showing the types of abnormalities classified through the battery management device according to an embodiment disclosed in this document. Referring to Fig. 11, it shows the general shapes of voltage corresponding to (a) an increase in charging potential, (b) a decrease in charging potential, (c) a decrease in resting potential after charging, (d) an increase in discharging potential, (e) a decrease in discharging potential, (f) an increase in resting potential after discharging, and (g) voltage over time of long - term stabilization.

[0098] As shown in FIG. 11, in the case of abnormal voltage behavior of a battery cell, although there may be a difference in outline compared to other cells, it can be seen that most of them overlap with the outlines of other battery cells. Therefore, it is difficult to accurately judge abnormal behavior only by the outline of the voltage itself according to time.

[0099] Therefore, in the battery management device disclosed in this document, as described above, by performing normalization calculation and differentiation on the average value of the voltage and voltage change in a specific section (window) of the battery cell, the change corresponding to the abnormal behavior of the battery cell is maximized and shown, so that the abnormal behavior of the battery cell can be detected more accurately and easily, and based on this, it can be classified up to the type of abnormality.

[0100] FIG. 12 is a block diagram showing a computing system that executes a battery management method according to an embodiment disclosed in this document. Referring to FIG. 12, a computing system (battery management device or battery management system) 30 according to an embodiment disclosed in this document may include an MCU 32, a memory 34, an input / output I / F 36, and a communication I / F 38.

[0101] The MCU 32 may execute various programs (for example, a normalization calculation program, a differential value calculation program, an abnormal behavior diagnosis and abnormal type classification program, etc.) stored in the memory 34, and process various data including the voltage, current, etc. of the battery cell through such programs, and may be a processor that performs the functions of the battery management device shown in FIG. 2 described above.

[0102] The memory 34 can store various programs related to the normalization calculation, abnormal behavior, and type classification of the battery cell. In addition, the memory 34 can store various data such as the voltage and current values of each battery cell, and the normalization calculation and differential data thereof.

[0103] Such a memory 34 may be provided in plural if necessary. The memory 34 may be a volatile memory or a non-volatile memory. As the volatile memory, the memory 34 can be a RAM, a DRAM, an SRAM, etc. As the non-volatile memory, the memory 34 can be a ROM, a PROM, an EAROM, an EPROM, an EEPROM, a flash memory, etc. The examples of the memory 34 listed above are merely illustrative and are not limited to these examples.

[0104] The input / output I / F 36 can provide an interface that connects between an input device (not shown) such as a keyboard, a mouse, a touch panel, etc., an output device such as a display (not shown), and the MCU 32 so that data can be transmitted and received.

[0105] The communication I / F 38 is configured to be able to transmit and receive various data with a server, and may be various devices that can support wired or wireless communication. For example, via the communication I / F 38, it is possible to transmit and receive a normalization operation of a battery cell, a program for abnormal behavior and type classification, and various data from an externally provided external server.

[0106] As described above, the computer program according to one embodiment disclosed in this document may be recorded in the memory 34 and processed by the MCU 32, and may be realized as a module that performs each function shown in FIG. 2, for example.

[0107] Just because all the components constituting the embodiment disclosed in this document have been described as being combined or operating in combination into one, the embodiment disclosed in this document is not necessarily limited to such an embodiment. That is, within the scope of the object of the embodiment disclosed in this document, all of its components may be selectively combined and operate in one or more.

[0108] In addition, terms such as "including", "comprising", or "having" described above shall, unless otherwise stated to the contrary, be construed to mean that the component can be inherent, and thus shall not exclude other components, but may further include other components. All terms, including technical or scientific terms, shall have the same meaning as commonly understood by those having ordinary knowledge in the technical field to which the embodiments disclosed in this document belong, unless otherwise defined. Terms commonly used, such as those defined in a dictionary, shall be construed to be consistent with the meaning in the context of the related art, and shall not be construed in an ideal or overly formal sense unless clearly defined in this document.

[0109] The above description is merely an exemplary explanation of the technical idea disclosed in this document. Those having ordinary knowledge in the technical field to which the embodiments disclosed in this document belong can make various modifications and variations without departing from the essential characteristics of the embodiments disclosed in this document. Therefore, the embodiments disclosed in this document are for the purpose of explanation rather than for limiting the technical idea disclosed in this document, and the scope of the technical idea disclosed in this document is not limited by such embodiments. The protection scope of the technical idea disclosed in this document shall be construed according to the claims described below, and all technical ideas within the equivalent scope shall be construed to be included within the scope of rights of this document.

Explanation of Reference Numerals

[0110] 1: Battery pack 2: Upper controller 10: Plurality of battery modules 12: Sensor 14: Switching unit 20: Battery management system 30: Computing system, battery management device, battery management system 32: MCU 34: Memory 36: Input / output I / F 38: Communication I / F 100: Battery management device, battery management system (BMS) 110: Measurement unit 120: Calculation unit 130: Diagnosis unit 140: Storage unit

Claims

1. A measurement unit that measures the voltage and current of a battery cell; A calculation unit that determines the operating range of the battery cell based on the current of the battery cell, performs a normalization calculation on the voltage of the battery cell, and calculates a comparison value for each of the battery cells; A diagnosis unit that diagnoses the state of the battery cell by comparing the comparison value of the battery cell with a reference value; A battery management device comprising the above.

2. The comparison value of the battery cell includes first data which is a value obtained by normalizing the average output value of the voltage for each preset interval for each of the battery cells, second data which is the amount of change of the first data, and third data which is a value obtained by normalizing the second data. The battery management device according to claim 1.

3. The diagnosis unit diagnoses the state of the battery cell by comparing the first data, the second data, and the third data with a first reference value, a second reference value, and a third reference value respectively. The battery management device according to claim 2.

4. The comparison value of the battery cell includes fourth data which is a value obtained by normalizing the average output value with respect to the amount of voltage change for each preset interval for each of the battery cells, fifth data which is the amount of change of the fourth data, and sixth data which is a value obtained by normalizing the average of the fifth data. The battery management device according to any one of claims 1 to 3.

5. The diagnosis unit diagnoses the state of the battery cell by comparing the fourth data, the fifth data, and the sixth data with a fourth reference value, a fifth reference value, and a sixth reference value respectively. The battery management device according to claim 4.

6. The state of the battery cell includes the rise and fall of the voltage and the long-term stabilization in the charging, discharging, and resting intervals of the battery cell. The battery management device according to any one of claims 1 to 5.

7. The calculation unit calculates the comparison value when the size of the interval for performing the normalization calculation on the voltage of the battery cell is less than the reference value. The battery management device according to any one of claims 1 to 6.

8. When the size of the interval for performing the normalization calculation on the voltage of the battery cell is greater than or equal to the reference value, the calculation unit changes the size of the interval and recalculates the comparison value. The battery management device according to claim 7.

9. The calculation unit determines, based on the current of the battery cell, whether the operating interval of the battery cell is included in any one of a charging interval, a discharging interval, or a rest interval, according to any one of claims 1 to 8. The battery management device described.

10. The battery cell includes a battery cell that has been previously diagnosed as abnormal by principal component analysis, according to any one of claims 1 to 9. The battery management device described.

11. The types of abnormalities of the battery cell include lithium precipitation, internal short circuit, and disconnection of the battery tab, according to any one of claims 1 to 10. The battery management device described.

12. When at least one of the voltage behaviors of the battery cell is a decrease in the charging voltage, a decrease in the rest voltage after charging, an increase in the discharging voltage, or an increase in the rest voltage after discharging, the diagnosis unit classifies it as lithium precipitation. The battery management device described in claim 11.

13. When at least one of the voltage behaviors of the battery cell is a decrease in the charging and discharging voltages or a decrease in the rest voltages after charging and discharging, the diagnosis unit classifies it as an internal short circuit. The battery management device described in claim 11.

14. When at least one of the voltage behaviors of the battery cell is a decrease in the discharging voltage or an increase in the charging and discharging voltages, the diagnosis unit classifies it as a disconnection of the battery tab. The battery management device described in claim 11.

15. Steps of measuring the voltage and current of the battery cell, Steps of determining the operating interval of the battery cell based on the current of the battery cell, Steps of normalizing the voltage of the battery cell to calculate a comparison value for each battery cell, Steps of diagnosing the state of the battery cell by comparing the comparison value of the battery cell with a reference value, A battery management method including.

16. The comparison value of the battery cell is first data that is a value obtained by normalizing the average output value of the voltage for each preset first interval for each battery cell, second data that is the amount of change of the first data, and the second data. The battery management method described in claim 15, including third data that is a value obtained by normalizing the data.

17. The step of diagnosing the state of the battery cell diagnoses the state of the battery cell by comparing the first data, the second data, and the third data with a first reference value, a second reference value, and a third reference value, respectively. The battery management method described in claim 16.

18. The comparison value of the battery cell is fourth data which is a value obtained by normalizing an average output value with respect to a voltage change amount for each preset section for each of the battery cells, fifth data which is a change amount of the fourth data, and sixth data which is a value obtained by normalizing an average of the fifth data, according to the battery management method according to any one of claims 15 to 17.

19. The step of diagnosing the state of the battery cell diagnoses the state of the battery cell by comparing the fourth data, the fifth data, and the sixth data with a fourth reference value, a fifth reference value, and a sixth reference value, respectively, according to the battery management method according to claim 18.

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