Battery management device and method of operation thereof

Abstract

A battery management device according to one embodiment disclosed in this document may include a data management unit that calculates a plurality of average voltages for each of the plurality of batteries using the voltages of each of the plurality of batteries measured over a fixed period, and a controller that calculates a plurality of voltage deviations, which are deviations between the plurality of average voltages for each of the plurality of batteries, and diagnoses at least one of the plurality of batteries using the cosine similarity between the average value of the plurality of voltage deviations for each of the plurality of batteries and the plurality of voltage deviations for each of the plurality of batteries.

Description

[Technical Field]

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2023-0028077, filed March 2, 2023, the entire contents of which are incorporated herein by reference. SUMMARY OF THE INVENTION The embodiments disclosed herein relate to a battery management device and method of operation. [Background technology]

[0002] Electric vehicles generate power by charging battery cells with an external power supply and then driving a motor with the voltage charged in the battery cells. Among various types of battery cells, lithium battery cells, which use lithium ions for redox reactions, can cause venting due to the deposition of lithium on the battery cell electrodes depending on the charging and discharging environment. When venting occurs in a battery cell, it can cause direct problems for the battery cell, such as reduced performance and increased risk of fire due to electrolyte leakage. Therefore, a technology is needed to determine whether a battery cell is venting.

[0003] Conventional battery management devices diagnose voltage abnormalities caused by venting of battery cells by comparing the average voltage of the battery cells with the long-term moving average voltage or short-term moving average voltage of individual battery cells. However, this method is susceptible to noise and is unable to adjust the threshold used as the standard for diagnosing abnormal battery cells below a certain level, which means that it is unable to detect abnormal voltages in battery cells caused by minute disconnections that occur in electric vehicles. Summary of the Invention [Problem to be solved by the invention]

[0004] An object of the embodiments disclosed herein is to provide a battery management device and an operating method thereof that can diagnose abnormal battery cells early using deviations between average voltages of the battery cells.

[0005] 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 will be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0006] A battery management device according to one embodiment disclosed in this document may include a data management unit that calculates a plurality of average voltages for each of the plurality of batteries using the voltages of each of the plurality of batteries measured over a fixed period, and a controller that calculates a plurality of voltage deviations, which are deviations between the plurality of average voltages for each of the plurality of batteries, and diagnoses at least one of the plurality of batteries using the cosine similarity between the average value of the plurality of voltage deviations for each of the plurality of batteries and the plurality of voltage deviations for each of the plurality of batteries.

[0007] According to one embodiment, the battery may further include a memory that stores the voltage of each of the plurality of batteries and an average voltage of each of the plurality of batteries. According to one embodiment, the memory may periodically store the average voltage of each of the plurality of batteries in a circular queue.

[0008] According to one embodiment, the controller may divide the voltage deviations of each of the plurality of batteries based on the calculation time point, and generate a first average value that is the average value of the voltage deviations of each of the plurality of batteries calculated at the same time point.

[0009] According to one embodiment, the controller can calculate a cosine similarity for each of the plurality of batteries, which is the cosine similarity between the first average value and a plurality of voltage deviations for each of the plurality of batteries, and calculate a first value, which is the difference between a second average value, which is the average value of the cosine similarities for each of the plurality of batteries, and the cosine similarity for each of the plurality of batteries.

[0010] In one embodiment, the controller may increase a diagnostic count value of at least one battery among the plurality of batteries when a first value of the at least one battery is greater than or equal to a threshold value.

[0011] In one embodiment, the controller may diagnose at least one battery among the plurality of batteries when the diagnostic count value of the at least one battery is equal to or greater than a threshold count value.

[0012] An operating method of a battery management device according to one embodiment disclosed in this document includes the steps of: calculating a plurality of average voltages for each of the plurality of batteries using the voltages of each of the plurality of batteries measured over a fixed period; calculating a plurality of voltage deviations, which are deviations between the plurality of average voltages for each of the plurality of batteries; calculating an average value of the plurality of voltage deviations for each of the plurality of batteries; and diagnosing at least one of the plurality of batteries using a cosine similarity between the average value of the plurality of voltage deviations for each of the plurality of batteries and the plurality of voltage deviations for each of the plurality of batteries.

[0013] According to one embodiment, the step of calculating a plurality of average voltages for each of the plurality of batteries using the voltages of each of the plurality of batteries measured during the fixed period may store the average voltages of each of the plurality of batteries in a circular queue at fixed intervals.

[0014] According to one embodiment, the step of calculating the average value of the plurality of voltage deviations for each of the plurality of batteries may divide the plurality of voltage deviations for each of the plurality of batteries based on the calculation time point, and generate a first average value which is the average value of the voltage deviations for each of the plurality of batteries calculated at the same time point.

[0015] According to one embodiment, the step of diagnosing at least one battery among the plurality of batteries using the cosine similarity between the average value of the plurality of voltage deviations of each of the plurality of batteries and the plurality of voltage deviations of each of the plurality of batteries can calculate a cosine similarity for each of the plurality of batteries, which is the cosine similarity between the first average value and the plurality of voltage deviations of each of the plurality of batteries, and calculate a first value, which is the difference between a second average value, which is the average value of the cosine similarities of each of the plurality of batteries, and the cosine similarity for each of the plurality of batteries.

[0016] According to one embodiment, the step of diagnosing at least one battery among the plurality of batteries using the cosine similarity between the average value of the plurality of voltage deviations of each of the plurality of batteries and the plurality of voltage deviations of each of the plurality of batteries can increase the diagnostic count value of the at least one battery if the first value of the at least one battery among the plurality of batteries is greater than or equal to a threshold value.

[0017] According to one embodiment, the step of diagnosing at least one battery among the plurality of batteries using the cosine similarity between the average value of the plurality of voltage deviations of each of the plurality of batteries and the plurality of voltage deviations of each of the plurality of batteries can diagnose the at least one battery if the diagnostic count value of the at least one battery among the plurality of batteries is equal to or greater than a threshold count value. [Effects of the Invention]

[0018] According to an embodiment of a battery management device and an operating method thereof disclosed herein, deviations between average voltages of battery cells can be used to diagnose abnormal battery cells early. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 illustrates a battery pack according to one embodiment disclosed herein. [Figure 2] 1 is a block diagram showing the configuration of a battery management device according to an embodiment disclosed in this document. [Figure 3]1 is a graph illustrating the change in voltage of a battery cell according to an embodiment disclosed herein. [Figure 4a] 1 is a table illustrating average voltage data for battery cells according to one embodiment disclosed herein. [Figure 4b] 1 is a graph illustrating average voltage data for a battery cell according to an embodiment disclosed herein. [Figure 5a] 1 is a table illustrating voltage deviation data for battery cells according to one embodiment disclosed herein. [Figure 5b] 1 is a graph illustrating voltage deviation data for a battery cell according to an embodiment disclosed herein. [Figure 6a] 1 is a table illustrating cosine similarity data for battery cells according to one embodiment disclosed herein. [Figure 6b] 1 is a graph illustrating cosine similarity data for battery cells according to one embodiment disclosed herein. [Figure 7] 1 is a graph illustrating a ratio of a first value to a threshold value of a battery cell according to one embodiment disclosed herein. [Figure 8] 1 is a flowchart illustrating a method of operating a battery management device according to one embodiment disclosed herein. [Figure 9] FIG. 1 is a block diagram showing the hardware configuration of a computing system that implements an operation method of a battery management device according to an embodiment disclosed herein. DETAILED DESCRIPTION OF THE INVENTION

[0020] Some embodiments disclosed herein will be described in detail below with reference to exemplary drawings. When assigning reference numerals to components in each drawing, it should be noted that the same reference numerals are assigned to the same components as long as possible when they appear in other drawings. Furthermore, when describing the embodiments disclosed herein, if a detailed description of related known configurations or functions is deemed to hinder understanding of the embodiments disclosed herein, such detailed description will be omitted.

[0021] In describing components of the embodiments disclosed herein, terms such as first, second, A, B, (a), (b), etc. may be used. Such terms are merely used to distinguish the component from other components and do not limit the nature, order, or sequence of the components. Furthermore, unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the embodiments disclosed herein pertain. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the context of the relevant art and should not be interpreted in an idealized or overly formal sense unless expressly defined herein.

[0022] FIG. 1 is a diagram illustrating a battery pack according to one embodiment disclosed herein. 1 , a battery pack 1000 according to one embodiment disclosed herein may include a battery module 100, a battery management device 200, and a relay 300. According to various embodiments, the battery module 100 may be a battery cell, in which case the battery pack 1000 may have a cell-to-pack structure.

[0023] The battery module 100 may include a plurality of battery cells 110, 120, 130, and 140. Although the number of battery cells is shown as four in FIG. 1, the number is not limited to four, and the battery module 100 may include n (n is a natural number equal to or greater than 2) battery cells.

[0024] The battery module 100 can supply power to a target device (not shown). To this end, the battery module 100 can be electrically connected to the target device. Here, the target device can include an electrical, electronic, or mechanical device that operates by receiving power from a battery pack 1000 including a plurality of battery cells 110, 120, 130, and 140. For example, the target device can be, but is not limited to, an electric vehicle (EV) or an energy storage system (ESS).

[0025] The plurality of battery cells 110, 120, 130, 140 are basic units of a battery that can be used by charging and discharging electrical energy, and may be, but are not limited to, lithium ion (Li-ion) batteries, lithium ion polymer (Li-ion polymer) batteries, nickel cadmium (Ni-Cd) batteries, nickel metal hydride (Ni-MH) batteries, etc. Meanwhile, although Fig. 1 shows one battery module 100, according to an embodiment, a plurality of battery modules 100 may be configured.

[0026] The battery management unit 200 can manage and / or control the state and / or operation of the battery module 100. For example, the battery management unit 200 can manage and / or control the state and / or operation of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100. The battery management unit 200 can manage the charging and / or discharging of the battery module 100.

[0027] The battery management unit 200 can control the operation of the relay 300. For example, the battery management unit 200 can short-circuit the relay 300 to supply power to a target device. In addition, the battery management unit 200 can short-circuit the relay 300 when a charging device is connected to the battery pack 1000.

[0028] The battery management unit 200 can also monitor the voltage, current, temperature, etc. of the battery module 100 and / or each of the plurality of battery cells 110, 120, 130, and 140 included in the battery module 100. For monitoring via the battery management unit 200, sensors and various measurement modules (not shown) can be further provided in the battery module 100, a charge / discharge path, or any position on the battery module 100. The battery management unit 200 can calculate parameters indicating the state of the battery module 100, such as SOC (State of Charge) or SOH (State of Health), based on the measured values ​​of the monitored voltage, current, temperature, etc.

[0029] The battery management device 200 can diagnose whether or not at least one of the multiple battery cells 110, 120, 130, 140 has an abnormal voltage using the cumulative voltage of each of the multiple battery cells 110, 120, 130, 140 and an average voltage calculated based on the cumulative voltages.

[0030] The battery management unit 200 can calculate a plurality of average voltage data from the accumulated voltage data of each of the plurality of battery cells 110, 120, 130, and 140. The battery management unit 200 calculates a voltage deviation dV between the plurality of average voltage data of each of the plurality of battery cells 110, 120, 130, and 140, and can diagnose whether or not at least one of the plurality of battery cells 110, 120, 130, and 140 has an abnormal voltage using the cosine similarity between the voltage deviation of each of the plurality of battery cells 110, 120, 130, and 140 and the average value of the voltage deviations of the plurality of battery cells 110, 120, 130, and 140.

[0031] The battery management device 200 does not use a moving average voltage of the plurality of battery cells, but uses the voltage deviation of the plurality of battery cells 110, 120, 130, and 140, thereby preventing a distorted trend in the voltage data of the battery cells and enabling accurate diagnosis of the battery cells. In addition, the following operation of the battery management device 200 may be performed by various devices such as a server, a cloud, a charger, or a charger / discharger connected to the battery management device 200 or a vehicle equipped with the battery management device 200.

[0032] FIG. 2 is a block diagram showing the configuration of a battery management device according to an embodiment disclosed in this document. The configuration of the battery management unit 200 will be specifically described below with reference to FIG.

[0033] Referring to FIG. 2, the battery management device 200 may include a data management unit 210 , a controller 220 , and a memory 230 . The data management unit 210 can calculate a plurality of average voltages of each of the plurality of battery cells 110, 120, 130, and 140. First, the data management unit 210 can measure the voltage of each of the plurality of battery cells 110, 120, 130, and 140.

[0034] FIG. 3 is a graph showing the change in voltage of a battery cell according to one embodiment disclosed herein. 3, the data management unit 210 can measure the voltage of each of the plurality of battery cells 110, 120, 130, and 140 during a predetermined period. The data management unit 210 can measure the voltage of each of the plurality of battery cells 110, 120, 130, and 140 during the predetermined period and monitor changes in the voltage of each of the plurality of battery cells 110, 120, 130, and 140.

[0035] The data management unit 210 may store the voltages of each of the plurality of battery cells 110, 120, 130, and 140 in the memory 230. For example, the data management unit 210 may store the voltages of each of the plurality of battery cells 110, 120, 130, and 140 separately in the memory 230, or may store the voltages separately for each battery module 100 including the plurality of battery cells 110, 120, 130, and 140.

[0036] The data management unit 210 may accumulate the voltages of the battery cells 110, 120, 130, and 140 measured over a certain period. For example, the data management unit 210 may accumulate 200 voltage values ​​of the battery cells 110, 120, 130, and 140 measured over a certain period. For example, the data management unit 210 may measure the voltage of the first battery cell 110 and accumulate 200 voltage values ​​of the first battery cell 110 measured over a certain period. The data management unit 210 may repeatedly measure the voltages of the battery cells equal to the number of battery cells included in the battery module 100 and accumulate the voltage values ​​of the battery cells measured over a certain period.

[0037] The data management unit 210 can accumulate the voltages of the plurality of battery cells 110, 120, 130, and 140 and store the accumulated voltages in the memory 230. That is, the data management unit 210 can calculate the accumulated voltages of the plurality of battery cells 110, 120, 130, and 140.

[0038] The data management unit 210 can calculate the average voltage of each of the plurality of battery cells 110, 120, 130, and 140 by dividing the accumulated voltage value of each of the plurality of battery cells 110, 120, 130, and 140, which is measured and accumulated during a certain period, by the number of measurements. For example, the controller 220 can calculate the average voltage of the first battery cell 110 by dividing the 200 accumulated voltage values ​​of the first battery cell 110, which are measured and accumulated during a certain period, by 200.

[0039] The data management unit 210 can calculate a plurality of average voltages for each of the plurality of battery cells 110, 120, 130, and 140 and store them in the memory 230. Specifically, the data management unit 210 can repeatedly calculate the average voltage value for each of the plurality of battery cells 110, 120, 130, and 140 at regular intervals. For example, when the current time point is set to "T," the data management unit 210 can repeatedly calculate the average voltage value for each of the plurality of battery cells 110, 120, 130, and 140 at past time points "T-4," "T-3," "T-2," and "T-1," as well as at the current time point "T," and store the calculated average voltage values ​​in the memory 230.

[0040] FIG. 4a is a table showing average voltage data for battery cells according to one embodiment disclosed herein. Referring to FIG. 4a, when the current time point is set to "T", the data management unit 210 calculates a first average voltage V , which is an average voltage value calculated at time point "T-4" for each of the plurality of battery cells 110, 120, 130, and 140. T-4 , a second average voltage V , which is an average voltage value calculated at time “T-3” for each of the plurality of battery cells 110, 120, 130, and 140; T-3 , a third average voltage V , which is an average voltage value calculated at time “T-2” for each of the plurality of battery cells 110, 120, 130, and 140; T-2 , a fourth average voltage V , which is an average voltage value calculated at time “T−1” for each of the plurality of battery cells 110, 120, 130, and 140; T-1 , and a fifth average voltage V , which is an average voltage value calculated at time “T” for each of the plurality of battery cells 110, 120, 130, and 140. T can be calculated.

[0041] The data management unit 210 calculates the first average voltage V of each of the plurality of battery cells 110, 120, 130, and 140. T-4 , the second average voltage V T-3 , the third average voltage V T-2 , the fourth average voltage V T-1 , and the fifth average voltage V T can be stored in the memory 230 in chronological order.

[0042] The memory 230 may accumulate and store the voltages of the battery cells 110, 120, 130, and 140 measured by the data management unit 210. The memory 230 may store the voltages of the battery cells 110, 120, 130, and 140 separately, or may store the voltages of the battery modules 100 including the battery cells 110, 120, 130, and 140 separately.

[0043] The memory 230 may include a plurality of buffers capable of temporarily accumulating the voltages of the plurality of battery cells 110, 120, 130, and 140. The buffers have a limited capacity for storing data, and may temporarily store data. For example, the memory 230 may include a plurality of buffers capable of temporarily accumulating the voltage of any one of the plurality of battery cells 110, 120, 130, and 140. Here, each of the plurality of buffers may be set to a window size capable of accumulating the voltage of the corresponding battery cell a predetermined number of times. For example, each buffer may be set to a window size capable of accumulating the voltage of the battery cell measured 200 times.

[0044] The memory 230 may also include a plurality of circular queues capable of temporarily storing a plurality of average voltages of the plurality of battery cells 110, 120, 130, and 140. Here, a queue may be defined as a data structure that allocates contiguous space and in which data input first is output first. According to an embodiment, each of the plurality of circular queues may include a plurality of buffers. For example, the memory 230 may use a plurality of circular queues each including five buffers to temporarily store a first average voltage V T-4 , the second average voltage V T-3 , the third average voltage V T-2 , the fourth average voltage V T-1 , and the fifth average voltage V T can be stored continuously and temporarily.

[0045] The memory 230 can periodically temporarily store a plurality of average voltages of each of the plurality of battery cells 110, 120, 130, and 140. For example, the memory 230 can periodically store a first average voltage V T-4 , the second average voltage V T-3 , the third average voltage V T-2 , the fourth average voltage V T-1 , and the fifth average voltage V T can be updated.

[0046] FIG. 4b is a graph illustrating average voltage data for a battery cell according to one embodiment disclosed herein. Referring to FIG. 4b, the data management unit 210 can repeatedly calculate the average voltage of each of the plurality of battery cells 110, 120, 130, and 140 calculated using the cumulative voltage values ​​of each of the plurality of battery cells 110, 120, 130, and 140 measured during a certain period.

[0047] The controller 220 can calculate a plurality of voltage deviations, which are deviations between a plurality of average voltages of the plurality of battery cells 110, 120, 130, 140, respectively.

[0048] FIG. 5a is a table illustrating voltage deviation data for battery cells according to one embodiment disclosed herein. 5a, for example, the controller 220 calculates a first average voltage V , which is an average voltage value calculated at time “T-4” for each of the plurality of battery cells 110, 120, 130, and 140. T-4 and the second average voltage V, which is the average voltage value calculated at time "T-3". T-3 A first voltage deviation dV1, which is the deviation from the reference voltage dV1, can be calculated.

[0049] The controller 220 also calculates a second average voltage V T-3and the third average voltage V, which is the average voltage value calculated at time "T-2". T-2 A second voltage deviation dV2, which is the deviation from the reference voltage dV, can be calculated.

[0050] The controller 220 also calculates a third average voltage V T-2 and the fourth average voltage V, which is the average voltage value calculated at time "T-1". T-1 A third voltage deviation dV3, which is the deviation from the voltage Vcc, can be calculated.

[0051] The controller 220 also calculates a third average voltage V T-1 and the fifth average voltage V, which is the average voltage value calculated at time "T". T A fourth voltage deviation dV4, which is the deviation from the voltage Vcc, can be calculated.

[0052] That is, the controller 220 calculates a first average voltage V , which is a continuously calculated average voltage value, in order to analyze the short-term voltage behavior of each of the plurality of battery cells 110, 120, 130, and 140. T-4 and the second average voltage V T-3 deviation of the second average voltage V T-3 and the third average voltage V T-2 deviation of the third average voltage V T-2 and the fourth average voltage V T-1 deviation, and the fourth average voltage V T-1 and the fifth average voltage V T The deviation can be calculated.

[0053] The controller 220 may calculate the deviation between the continuously calculated average voltages to analyze the long-term voltage behavior of each of the plurality of battery cells 110, 120, 130, and 140. For example, the controller 220 may calculate a second average voltage V T-3 and the fifth average voltage V, which is the average voltage value calculated at time "T".T A fifth voltage deviation dV5, which is the deviation from

[0054] FIG. 5b is a graph illustrating voltage deviation data for a battery cell according to one embodiment disclosed herein. Referring to FIG. 5b, the controller 220 can continuously calculate the voltage deviation of each of the plurality of battery cells 110, 120, 130, and 140 at regular intervals.

[0055] 5A again, the controller 220 may classify the voltage deviations of the battery cells 110, 120, 130, and 140 based on the calculation time point. The controller 220 may generate a first average value AVG_1, which is the average value of the voltage deviations of the battery cells 110, 120, 130, and 140 calculated at the same calculation time point.

[0056] For example, the controller 220 may divide the voltage deviations of each of the plurality of battery cells 110, 120, 130, and 140 based on the calculation time point, and calculate a first average value AVG_1 of the first voltage deviation dV1, the first average value AVG_1 of the second voltage deviation dV2, the first average value AVG_1 of the third voltage deviation dV3, the first average value AVG_1 of the fourth voltage deviation dV4, and the first average value AVG_1 of the fifth voltage deviation dV5 of the plurality of battery cells 110, 120, 130, and 140 calculated at the same time point.

[0057] The controller 220 can calculate cosine similarities between the first average values ​​AVG_1 of the battery cells 110, 120, 130, and 140 and the voltage deviations of the battery cells 110, 120, 130, and 140. Here, the cosine similarity refers to the similarity between vectors measured using the cosine value of the angle between two vectors. The cosine similarity can determine the similarity in the direction of the vectors, rather than the magnitude of the vectors. Therefore, the controller 220 can determine abnormal behavior of the voltage of at least one of the battery cells 110, 120, 130, and 140 using the cosine similarity value, even when the noise level in the battery module 100 is high or the capacity of the battery module 100 is small, causing the voltage fluctuation amounts of the battery cells 110, 120, 130, and 140 to differ.

[0058] The controller 220 can calculate the cosine similarity between the plurality of first average values ​​AVG_1 and the plurality of voltage deviations of the plurality of battery cells 110, 120, 130, and 140, based on the following [Equation 1].

[0059] [Formula 1]

number

[0060] The controller 220 inputs multiple first average values ​​AVG_1 of the multiple battery cells 110, 120, 130, and 140 into "A" in the above [Equation 1], and inputs multiple voltage deviations of each of the multiple battery cells 110, 120, 130, and 140 into "B," and can calculate the cosine similarity of each of the multiple battery cells 110, 120, 130, and 140.

[0061] For example, the controller 220 can input into "A" of [Equation 1] [0.04, 0.0096, 0.004, 0.036, 0.004], which are the multiple first average values ​​AVG_1 of the multiple battery cells 110, 120, 130, 140, namely, the first average value AVG_1 of the first voltage deviation dV1, the first average value AVG_1 of the second voltage deviation dV2, the first average value AVG_1 of the third voltage deviation dV3, the first average value AVG_1 of the fourth voltage deviation dV4, and the first average value AVG_1 of the fifth voltage deviation dV5.

[0062] For example, the controller 220 can input, into "B" of [Equation 1], a first voltage deviation dV1, a second voltage deviation dV2, a third voltage deviation dV3, a fourth voltage deviation dV4, and a fifth voltage deviation dV5, which are the multiple voltage deviations of the multiple battery cells 110, 120, 130, and 140. For example, the controller 220 can input, into "B" of [Equation 1], [0.03, 0.006, 0.004, 0.04, 0.05], which are the multiple voltage deviations of the first battery cell 110, namely, the first voltage deviation dV1, the second voltage deviation dV2, the third voltage deviation dV3, the fourth voltage deviation dV4, and the fifth voltage deviation dV5.

[0063] FIG. 6a is a table illustrating cosine similarity data for battery cells according to one embodiment disclosed herein. Referring to FIG. 6a, the controller 220 can calculate the cosine similarity of each of the plurality of battery cells 110, 120, 130, and 140 using Equation 1.

[0064] Furthermore, according to the embodiment, the controller 220 can calculate a second average value AVG_2, which is the average value of the cosine similarities of the plurality of battery cells 110, 120, 130, and 140, respectively.

[0065] FIG. 6b is a graph illustrating cosine similarity data for battery cells according to one embodiment disclosed herein. Referring to FIG. 6b, the controller 220 can continuously calculate the cosine similarity of each of the plurality of battery cells 110, 120, 130, and 140 at regular intervals.

[0066] The controller 220 can diagnose at least one battery cell among the plurality of battery cells 110, 120, 130, and 140 using the second average value AVG_2 and the cosine similarity of each of the plurality of battery cells 110, 120, 130, and 140.

[0067] Specifically, the controller 220 can calculate a first value that is the difference between a second average value AVG_2, which is the average value of the cosine similarities of the multiple battery cells 110, 120, 130, and 140, and the cosine similarities of the multiple battery cells 110, 120, 130, and 140.

[0068] The controller 220 can determine whether the first value of at least one of the plurality of battery cells 110, 120, 130, and 140 is equal to or greater than a threshold.

[0069] FIG. 7 is a graph illustrating the ratio of a first value to a threshold value of a battery cell according to one embodiment disclosed herein. 7, the controller 220 can continuously calculate the ratio of each of the plurality of battery cells 110, 120, 130, and 140 to the first value threshold at regular intervals. That is, the controller 220 can continuously calculate the ratio of each of the plurality of battery cells 110, 120, 130, and 140 to the first value threshold at regular intervals, and analyze whether or not there is abnormal behavior of the voltage of each of the plurality of battery cells 110, 120, 130, and 140 relative to the overall voltage of the plurality of battery cells 110, 120, 130, and 140. That is, the controller 220 can continuously calculate the ratio of each of the plurality of battery cells 110, 120, 130, and 140 to the first value threshold at regular intervals, and analyze how much the voltage of each of the plurality of battery cells 110, 120, 130, and 140 differs from the voltage of a normal battery cell.

[0070] The controller 220 may increase the diagnostic count value of at least one battery cell among the plurality of battery cells 110, 120, 130, 140 when the first value of the at least one battery cell is greater than or equal to the threshold value.

[0071] When the diagnostic count value of at least one of the plurality of battery cells 110, 120, 130, 140 is equal to or greater than the threshold count value, the controller 220 can determine that at least one battery cell is an abnormal battery cell and perform a diagnosis. For example, when the diagnostic count value of at least one of the plurality of battery cells 110, 120, 130, 140 reaches the threshold count value of 100, the controller 220 can determine that the battery cell is an abnormal battery cell and perform a diagnosis.

[0072] If the diagnosis reveals that a battery cell is abnormal, the controller 220 can provide information about the abnormal battery cell to the user. For example, the controller 220 can provide information about the abnormal battery cell to the user terminal via a communication unit (not shown), and can also provide information about the abnormal battery cell via a display provided in the vehicle or a charger.

[0073] As described above, the battery management device 200 according to an embodiment disclosed herein can diagnose abnormal battery cells early using the deviation between the average voltages of the battery cells.

[0074] Conventional battery management devices use a moving average voltage, which has the problem of past values ​​having a continuous effect depending on the weight. However, the battery management device 200 according to one embodiment disclosed in this document can reflect undistorted voltage trends by using an arithmetic average of only the memory window size, and by using multiple arithmetic average values, a separate noise removal process is not required.

[0075] In addition, the battery management device 200 compares multiple voltage deviations dV for each of the multiple battery cells 110, 120, 130, and 140, and calculates not only the deviation between adjacent voltages but also the deviation between voltages that are distant from each other, and can analyze all the characteristics (features) of the short-term voltage behavior and long-term voltage behavior of the battery cells.

[0076] FIG. 8 is a flowchart illustrating a method of operating a battery management device according to one embodiment disclosed herein. The operation method of the battery management device 200 will be specifically described below with reference to FIGS.

[0077] The battery management unit 200 is substantially similar to the battery management unit 200 described with reference to FIGS. 1 to 7, and will be described briefly below to avoid duplication.

[0078] Referring to FIG. 8, the operating method of the battery management device 200 includes the steps of: calculating a plurality of average voltages for each of the plurality of batteries using the voltages of each of the plurality of batteries measured over a fixed period (S101); calculating a plurality of voltage deviations, which are deviations between the plurality of average voltages for each of the plurality of batteries (S102); calculating an average value of the plurality of voltage deviations for each of the plurality of batteries (S103); and diagnosing at least one of the plurality of batteries using the cosine similarity between the average value of the plurality of voltage deviations for each of the plurality of batteries and the plurality of voltage deviations for each of the plurality of batteries (S104).

[0079] Steps S101 to S104 will be specifically described below. In step S101, the data management unit 210 can calculate a plurality of average voltages of each of the plurality of battery cells 110, 120, 130, and 140. First, the data management unit 210 can measure the voltage of each of the plurality of battery cells 110, 120, 130, and 140.

[0080] In step S101, the data management unit 210 can measure the voltage of each of the plurality of battery cells 110, 120, 130, and 140 during a predetermined period. The data management unit 210 can measure the voltage of each of the plurality of battery cells 110, 120, 130, and 140 during the predetermined period and monitor changes in the voltage of each of the plurality of battery cells 110, 120, 130, and 140.

[0081] In step S101, the data management unit 210 may store the voltages of the plurality of battery cells 110, 120, 130, and 140 in the memory 230. In step S101, for example, the data management unit 210 may store the voltages of the plurality of battery cells 110, 120, 130, and 140 separately in the memory 230, or may store the voltages separately for each battery module 100 including the plurality of battery cells 110, 120, 130, and 140.

[0082] In step S101, the data management unit 210 may accumulate the voltages of the plurality of battery cells 110, 120, 130, and 140 measured during a certain period. In step S101, for example, the data management unit 210 may accumulate 200 voltage values ​​of the plurality of battery cells 110, 120, 130, and 140 measured during a certain period. In step S101, for example, the data management unit 210 may measure the voltage of the first battery cell 110 and accumulate the 200 voltage values ​​of the first battery cell 110 measured during a certain period. In step S101, the data management unit 210 may repeatedly measure the voltages of the battery cells equal to the number of battery cells included in the battery module 100 and accumulate the voltage values ​​of the battery cells measured during a certain period.

[0083] In step S101, the data management unit 210 can accumulate the voltages of the plurality of battery cells 110, 120, 130, and 140 and store the accumulated voltages in the memory 230. That is, the data management unit 210 can calculate the accumulated voltages of the plurality of battery cells 110, 120, 130, and 140.

[0084] In step S101, the data management unit 210 can calculate the average voltage of each of the multiple battery cells 110, 120, 130, and 140 by dividing the cumulative voltage value of each of the multiple battery cells 110, 120, 130, and 140 measured and accumulated over a fixed period by the number of measurements.

[0085] In step S101, the data management unit 210 can calculate a plurality of average voltages for each of the plurality of battery cells 110, 120, 130, and 140 and store them in the memory 230. In step S101, for example, the data management unit 210 can repeatedly calculate the average voltage value for each of the plurality of battery cells 110, 120, 130, and 140 at regular intervals. In step S101, for example, when the current time point is set to "T," the data management unit 210 can repeatedly calculate the average voltage value for each of the plurality of battery cells 110, 120, 130, and 140 at past time points "T-4," "T-3," "T-2," and "T-1," as well as at the current time point "T," and store the calculated average voltage values ​​in the memory 230.

[0086] In step S101, for example, when the current time point is set to "T", the data management unit 210 calculates a first average voltage V , which is an average voltage value calculated at time point "T-4" for each of the plurality of battery cells 110, 120, 130, and 140. T-4 , the second average voltage V, which is the average voltage value calculated at time "T-3" T-3 , the third average voltage V, which is the average voltage value calculated at time "T-2" T-2 The fourth average voltage V is the average voltage value calculated at time "T-1". T-1 , and the fifth average voltage V, which is the average voltage value calculated at time "T". T can be calculated.

[0087] In step S101, the data management unit 210 calculates the first average voltage V T-4 , the second average voltage V T-3 , the third average voltage V T-2, the fourth average voltage V T-1 , and the fifth average voltage V T can be stored in the memory 230 in chronological order.

[0088] In step S101, the memory 230 may accumulate and store the voltages of the plurality of battery cells 110, 120, 130, and 140 measured by the data management unit 210. The memory 230 may also store the voltages of the plurality of battery cells 110, 120, 130, and 140 separately, or may store the voltages of the plurality of battery cells 110, 120, 130, and 140 separately for each battery module 100 including the plurality of battery cells 110, 120, 130, and 140.

[0089] In step S101, the memory 230 may include a plurality of buffers capable of temporarily accumulating the voltages of the plurality of battery cells 110, 120, 130, and 140. For example, the memory 230 may include a plurality of buffers capable of temporarily accumulating the voltage of any one of the plurality of battery cells 110, 120, 130, and 140. Here, each of the plurality of buffers may be set to a window size capable of accumulating the voltage of the corresponding battery cell a predetermined number of times. For example, each buffer may be set to a window size capable of accumulating the voltage of the battery cell measured 200 times.

[0090] In step S101, the memory 230 may also include a plurality of circular queues capable of temporarily storing a plurality of average voltages of the plurality of battery cells 110, 120, 130, and 140. Here, a queue may be defined as a data structure that allocates contiguous space and in which data input first is output first. According to one embodiment, each of the plurality of circular queues may include a plurality of buffers.

[0091] In step S101, for example, the memory 230 uses a plurality of circular queues including five buffers to store the first average voltage VT-4 , the second average voltage V T-3 , the third average voltage V T-2 , the fourth average voltage V T-1 , and the fifth average voltage V T can be stored continuously and temporarily.

[0092] In step S101, the memory 230 can periodically temporarily store a plurality of average voltages of each of the plurality of battery cells 110, 120, 130, and 140. In step S101, for example, the memory 230 can periodically store a first average voltage V T-4 , the second average voltage V T-3 , the third average voltage V T-2 , the fourth average voltage V T-1 , and the fifth average voltage V T can be updated.

[0093] In step S101, the data management unit 210 can repeatedly calculate the average voltage of each of the multiple battery cells 110, 120, 130, and 140 calculated using the cumulative voltage values ​​of each of the multiple battery cells 110, 120, 130, and 140 measured over a fixed period.

[0094] In step S102, the controller 220 can calculate a plurality of voltage deviations, which are deviations between a plurality of average voltages of the plurality of battery cells 110, 120, 130, and 140, respectively.

[0095] In step S102, for example, the controller 220 calculates a first average voltage V , which is an average voltage value calculated for each of the plurality of battery cells 110, 120, 130, and 140 at time “T-4.” T-4 and the second average voltage V, which is the average voltage value calculated at time "T-3". T-3 A first voltage deviation dV1, which is the deviation from the reference voltage dV1, can be calculated.

[0096] In step S102, the controller 220 also calculates a second average voltage V , which is the average voltage value calculated for each of the plurality of battery cells 110, 120, 130, and 140 at time “T-3.” T-3 and the third average voltage V, which is the average voltage value calculated at time "T-2". T-2 A second voltage deviation dV2, which is the deviation from the reference voltage dV, can be calculated.

[0097] In step S102, the controller 220 also calculates a third average voltage V T-2 and the fourth average voltage V, which is the average voltage value calculated at time "T-1". T-1 A third voltage deviation dV3, which is the deviation from the voltage Vcc, can be calculated.

[0098] In step S102, the controller 220 also calculates a third average voltage V , which is the average voltage value calculated for each of the plurality of battery cells 110, 120, 130, and 140 at time “T−1.” T-1 and the fifth average voltage V, which is the average voltage value calculated at time "T". T A fourth voltage deviation dV4, which is the deviation from the voltage Vcc, can be calculated.

[0099] In step S102, the controller 220 calculates a first average voltage V, which is a continuously calculated average voltage value, to analyze the short-term voltage behavior of each of the battery cells 110, 120, 130, and 140. T-4 and the second average voltage V T-3 deviation of the second average voltage V T-3 and the third average voltage V T-2 deviation of the third average voltage V T-2 and the fourth average voltage V T-1 deviation, and the fourth average voltage V T-1 and the fifth average voltage V T The deviation can be calculated.

[0100] In step S102, the controller 220 may calculate the deviation between the continuously calculated average voltages to analyze the long-term voltage behavior of each of the plurality of battery cells 110, 120, 130, and 140. For example, the controller 220 may calculate a second average voltage V T-3 and the fifth average voltage V, which is the average voltage value calculated at time "T". T A fifth voltage deviation dV5, which is the deviation from

[0101] In step S103, the controller 220 may classify the voltage deviations of the battery cells 110, 120, 130, and 140 based on the calculation time point. In step S103, the controller 220 may generate a first average value AVG_1, which is the average value of the voltage deviations of the battery cells 110, 120, 130, and 140 calculated at the same calculation time point.

[0102] In step S103, for example, the controller 220 can divide the voltage deviations of each of the multiple battery cells 110, 120, 130, and 140 based on the calculation time point, and calculate a first average value AVG_1 of the first voltage deviation dV1, the first average value AVG_1 of the second voltage deviation dV2, the first average value AVG_1 of the third voltage deviation dV3, the first average value AVG_1 of the fourth voltage deviation dV4, and the first average value AVG_1 of the fifth voltage deviation dV5 of the multiple battery cells 110, 120, 130, and 140 calculated at the same time point.

[0103] In step S104, the controller 220 can calculate cosine similarities between the first average values ​​AVG_1 of the battery cells 110, 120, 130, and 140 and the voltage deviations of each of the battery cells 110, 120, 130, and 140. Here, the cosine similarity refers to the similarity between two vectors measured using the cosine value of the angle between the vectors.

[0104] In step S104, the controller 220 can calculate the cosine similarities between the plurality of first average values ​​AVG_1 and the plurality of voltage deviations of the plurality of battery cells 110, 120, 130, and 140, based on the following [Equation 2].

[0105] [Formula 2]

number

[0106] In step S104, the controller 220 inputs multiple first average values ​​AVG_1 of the multiple battery cells 110, 120, 130, and 140 into "A" in the above [Equation 2], inputs multiple voltage deviations of each of the multiple battery cells 110, 120, 130, and 140 into "B," and can calculate the cosine similarity of each of the multiple battery cells 110, 120, 130, and 140.

[0107] In step S104, the controller 220 can calculate the cosine similarity of each of the plurality of battery cells 110, 120, 130, and 140 using [Equation 2].

[0108] In step S104, according to the embodiment, the controller 220 can calculate a second average value AVG_2, which is the average value of the cosine similarities of the plurality of battery cells 110, 120, 130, and 140, respectively.

[0109] In step S104, the controller 220 can diagnose at least one of the plurality of battery cells 110, 120, 130, and 140 using the second average value AVG_2 and the cosine similarity of each of the plurality of battery cells 110, 120, 130, and 140.

[0110] Specifically, in step S104, the controller 220 can calculate a first value which is the difference between the second average value AVG_2, which is the average value of the cosine similarities of each of the multiple battery cells 110, 120, 130, and 140, and the cosine similarities of each of the multiple battery cells 110, 120, 130, and 140.

[0111] In step S104, the controller 220 can determine whether the first value of at least one of the plurality of battery cells 110, 120, 130, and 140 is equal to or greater than a threshold.

[0112] In step S104, the controller 220 can continuously calculate the ratio of each of the plurality of battery cells 110, 120, 130, and 140 to the first value threshold at regular intervals. In step S104, the controller 220 can continuously calculate the ratio of each of the plurality of battery cells 110, 120, 130, and 140 to the first value threshold at regular intervals, and analyze whether or not there is abnormal behavior of the voltage of each of the plurality of battery cells 110, 120, 130, and 140 relative to the overall voltage of the plurality of battery cells 110, 120, 130, and 140. In step S104, the controller 220 can continuously calculate the ratio of each of the plurality of battery cells 110, 120, 130, and 140 to the first value threshold at regular intervals, and analyze how much the voltage of each of the plurality of battery cells 110, 120, 130, and 140 differs from the voltage of a normal battery cell.

[0113] In step S104, when the first value of at least one of the plurality of battery cells 110, 120, 130, 140 is equal to or greater than the threshold value, the controller 220 can increase the diagnostic count value of at least one battery cell.

[0114] In step S104, if the diagnostic count value of at least one of the plurality of battery cells 110, 120, 130, 140 is equal to or greater than the threshold count value, the controller 220 can determine that at least one battery cell is an abnormal battery cell and perform diagnosis. In step S104, for example, if the diagnostic count value of at least one of the plurality of battery cells 110, 120, 130, 140 reaches the threshold count value of 100, the controller 220 can determine that the battery cell is an abnormal battery cell and perform diagnosis.

[0115] In step S104, if it is determined that the battery cell is abnormal as a result of the diagnosis, the controller 220 can provide information about the abnormal battery cell to the user. In step S104, for example, the controller 220 can provide information about the abnormal battery cell to the user terminal via a communication unit (not shown), and can also provide information about the abnormal battery cell via a display provided in the vehicle, a charger, or the like.

[0116] FIG. 9 is a block diagram showing the hardware configuration of a computing system that implements the method of operating a battery management device according to an embodiment disclosed herein.

[0117] Referring to FIG. 9, a computing system 2000 according to one embodiment disclosed herein may include an MCU 2100, a memory 2200, an input / output I / F 2300, and a communication I / F 2400.

[0118] The MCU 2100 may be a processor that executes various programs (e.g., a battery voltage change amount analysis program) stored in the memory 2200, processes various data through such programs, and performs the functions of the battery management device 200 shown in FIG. 1 described above.

[0119] The memory 2200 can store various programs related to the operation of the battery management unit 200. The memory 2200 can also store operation data of the battery management unit 200.

[0120] A plurality of such memories 2200 may be provided as necessary. The memories 2200 may be volatile memories or nonvolatile memories. The volatile memories 2200 may be RAM, DRAM, SRAM, etc. The nonvolatile memories 2200 may be ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc. The examples of the memories 2200 listed above are merely illustrative and are not limited to these examples.

[0121] The input / output I / F 2300 can provide an interface that connects input devices (not shown) such as a keyboard, mouse, or touch panel, and output devices such as a display (not shown), to the MCU 2100, enabling data to be sent and received.

[0122] The communication I / F 2400 is configured to be able to send and receive various data to and from a server, and may be any device that supports wired or wireless communication. For example, programs for resistance measurement and abnormality diagnosis, various data, and the like can be sent and received from a separately provided external server via the communication I / F 2400.

[0123] The above description merely exemplifies the technical concept of the present disclosure, and various modifications and variations are possible by a person having ordinary knowledge in the technical field to which the present disclosure pertains, without departing from the essential characteristics of the present disclosure.

[0124] Therefore, the embodiments disclosed in this disclosure are intended to illustrate, not limit, the technical idea of ​​the disclosure, and the scope of the technical idea of ​​the disclosure is not limited by such embodiments. The scope of protection of the disclosure should be interpreted by the claims below, and all technical ideas within the equivalent range should be interpreted as being included in the scope of rights of the disclosure. [Explanation of symbols]

[0125] 1000: Battery pack 100: Battery module 110: First battery cell 120: Battery cell 130: Battery cell 140: Battery cell 200:Battery management device 210: Data Management Department 220: Controller 230: Memory 300: Relay 2000: Computing Systems 2100:MCU 2200:Memory 2300: Input / output interface 2400:Communication I / F

Claims

1. a data management unit that calculates a plurality of average voltages of each of the plurality of batteries using the voltages of each of the plurality of batteries measured over a fixed period; a controller that calculates a plurality of voltage deviations, which are deviations between a plurality of average voltages of the plurality of batteries, and diagnoses at least one battery among the plurality of batteries using a cosine similarity between an average value of the plurality of voltage deviations of the plurality of batteries and the plurality of voltage deviations of the plurality of batteries; A battery management device comprising:

2. The battery management device according to claim 1 , further comprising a memory for storing the voltages of the respective batteries and an average voltage of the respective batteries.

3. The battery management device according to claim 2 , wherein the memory stores the average voltage of each of the plurality of batteries in a circular queue at regular intervals.

4. 4. The battery management device of claim 3, wherein the controller divides the voltage deviations of the plurality of batteries based on the calculation time point, and generates a first average value that is an average value of the voltage deviations of the plurality of batteries calculated at the same time point.

5. the controller calculates a cosine similarity between the first average value and each of the plurality of voltage deviations of the plurality of batteries, the cosine similarity being a cosine similarity between the first average value and each of the plurality of batteries; The battery management device according to claim 4 , further comprising: a first value that is a difference between a second average value that is an average value of the cosine similarities of the plurality of batteries and the cosine similarities of the plurality of batteries.

6. The battery management device according to claim 5 , wherein the controller increases the diagnostic count value of at least one battery among the plurality of batteries when the first value of the at least one battery is equal to or greater than a threshold value.

7. The battery management device according to claim 6 , wherein the controller diagnoses at least one battery when a diagnostic count value of at least one battery among the plurality of batteries is equal to or greater than a threshold count value.

8. calculating a plurality of average voltages of each of the plurality of batteries using the voltages of each of the plurality of batteries measured during a fixed period; calculating a plurality of voltage deviations, which are deviations between a plurality of average voltages of each of the plurality of batteries; calculating an average value of a plurality of voltage deviations for each of the plurality of batteries; diagnosing at least one battery among the plurality of batteries using a cosine similarity between an average value of a plurality of voltage deviations for each of the plurality of batteries and a plurality of voltage deviations for each of the plurality of batteries; A method of operating a battery management device, comprising:

9. 9. The method for operating a battery management device according to claim 8, wherein the step of calculating a plurality of average voltages of each of the plurality of batteries using the voltages of each of the plurality of batteries measured during the fixed period includes storing the average voltages of each of the plurality of batteries in a circular queue at fixed intervals.

10. 10. The method of claim 9, wherein the step of calculating an average value of the plurality of voltage deviations for each of the plurality of batteries comprises dividing the plurality of voltage deviations for each of the plurality of batteries based on a calculation time point, and generating a first average value that is an average value of the voltage deviations for each of the plurality of batteries calculated at the same time point.

11. the step of diagnosing at least one battery among the plurality of batteries using a cosine similarity between an average value of a plurality of voltage deviations of each of the plurality of batteries and a plurality of voltage deviations of each of the plurality of batteries, 11. The method for operating a battery management device according to claim 10, further comprising: calculating a cosine similarity for each of the plurality of batteries, which is the cosine similarity between the first average value and a plurality of voltage deviations for each of the plurality of batteries; and calculating a first value, which is the difference between a second average value, which is the average value of the cosine similarities for each of the plurality of batteries, and the cosine similarity for each of the plurality of batteries.

12. the step of diagnosing at least one battery among the plurality of batteries using a cosine similarity between an average value of a plurality of voltage deviations of each of the plurality of batteries and a plurality of voltage deviations of each of the plurality of batteries, The method of claim 11 , further comprising increasing a diagnostic count value of at least one battery among the plurality of batteries if the first value of the at least one battery is greater than or equal to a threshold value.

13. the step of diagnosing at least one battery among the plurality of batteries using a cosine similarity between an average value of a plurality of voltage deviations of each of the plurality of batteries and a plurality of voltage deviations of each of the plurality of batteries, The method of claim 12 , further comprising: diagnosing at least one battery among the plurality of batteries when the diagnostic count value of the at least one battery is equal to or greater than a threshold count value.

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