Health status prediction device and its operation method

Abstract

A SOH prediction device according to one embodiment disclosed in this document may include: a battery pack; an electrochemical impedance spectroscopy (EIS) data acquisition unit that acquires EIS data of the battery pack; a feature point identification unit that identifies multiple feature points based on the EIS data; an angle parameter calculation unit that calculates an angle parameter related to the impedance of the battery pack based on the impedance associated with the multiple feature points; and an SOH prediction unit that predicts the SOH corresponding to the calculated angle parameter based on the relationship data between the temperature at which the acquired EIS data is located, the angle parameter, and the SOH of the battery pack.

Description

Technical Field

[0001] Cross-references to related applications

[0002] This application claims priority and benefit to Korean Patent Application No. 10-2023-0148220, filed with the Korean Intellectual Property Office on October 31, 2023, the entire contents of which are incorporated herein by reference.

[0004] The embodiments disclosed herein relate to a state of health (SOH) prediction device and a method of operating the SOH prediction device. Background Technology

[0005] Recently, research and development of rechargeable batteries have been actively underway. Here, a rechargeable battery is a battery capable of being charged and discharged, and includes conventional Ni / Cd batteries, Ni / MH batteries, and all of the more recent lithium-ion batteries. Among rechargeable batteries, lithium-ion batteries have the following advantages: they have a much higher energy density than conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured to be smaller and lighter, and are therefore being used as power sources for mobile devices. Recently, lithium-ion batteries have attracted attention as a next-generation energy storage medium due to their expanding applications as power sources for electric vehicles.

[0006] Battery swapping systems exist as a service associated with these secondary batteries. These systems provide users with the service of exchanging discharged batteries for rechargeable batteries.

[0007] Such battery exchange systems can use methods to predict the lifespan of the batteries used for servicing. For example, electrochemical impedance spectroscopy (EIS) can be used as a method to measure battery lifespan. Summary of the Invention

[0008] Technical issues

[0009] One embodiment disclosed herein relates to providing a state of health (SOH) prediction device for predicting the state of health (SOH) of a battery pack based on angular parameters related to the impedance of the battery pack, and a method for operating the SOH prediction device.

[0010] The embodiments disclosed herein are not limited to the purposes described above, and other purposes not described will be clearly understood by those skilled in the art based on the following description.

[0011] Technical solutions

[0012] A state of health (SOH) prediction device according to one embodiment disclosed herein may include: a battery pack; an electrochemical impedance spectroscopy (EIS) data acquisition unit configured to acquire EIS data of the battery pack; a feature point identification unit configured to identify multiple feature points based on the EIS data; an angle parameter calculation unit configured to calculate an angle parameter related to the impedance of the battery pack based on the impedance associated with the multiple feature points; and an SOH prediction unit configured to predict the SOH corresponding to the calculated angle parameter based on the relationship data between the temperature at which the EIS data was acquired, the angle parameter, and the SOH of the battery pack.

[0013] According to one implementation, the EIS data includes data relating to an EIS plot shown by dividing the impedance of the battery pack into real and imaginary parts, and a first feature point and a second feature point among a plurality of feature points may be associated with whether there is an inflection point in the EIS plot in a reference frequency region at a frequency higher than the frequency corresponding to the maximum point among the plurality of points identified based on the EIS plot.

[0014] According to one implementation, in the absence of an inflection point in the reference frequency region, a first feature point may be associated with the point with the smallest real part of impedance among a plurality of points identified based on the EIS plot, and a second feature point may be associated with a point among the plurality of points identified based on the EIS plot where the imaginary part of impedance is zero or a point with a frequency lower than the frequency corresponding to the point with the imaginary part of zero.

[0015] According to one implementation, in the absence of an inflection point in the reference frequency region, a first feature point may be associated with a point among a plurality of points identified based on an EIS plot where the imaginary part of the impedance is zero, and a second feature point may be associated with a point among the plurality of points identified based on an EIS plot where the frequency is lower than the frequency corresponding to the first feature point.

[0016] According to one implementation, when an inflection point exists in the reference frequency region, the first feature point can be associated with the point with the smallest real part of impedance among a plurality of points identified based on the EIS plot, and the second feature point can be associated with an inflection point or a point with a frequency lower than the frequency corresponding to the inflection point among a plurality of points identified based on the EIS plot.

[0017] According to one implementation, when an inflection point exists in the reference frequency region, a first feature point may be associated with the inflection point, and a second feature point may be associated with a point corresponding to a frequency lower than the frequency corresponding to the inflection point.

[0018] According to one implementation, in the case of an inflection point in the reference frequency region, a first feature point may be associated with a point among a plurality of points identified based on an EIS plot where the imaginary part of the impedance is zero, and a second feature point may be associated with the inflection point or with a point corresponding to a frequency lower than the frequency corresponding to the inflection point.

[0019] According to one implementation, the angle parameter can be related to the angle between the straight line connecting the second feature point to the first feature point and any coordinate axis of the EIS plot.

[0020] According to one implementation, the EIS data may include data relating to an EIS plot shown at a frequency corresponding to the second feature point and in a frequency region higher than the frequency corresponding to the second feature point.

[0021] According to one embodiment, the SOH prediction device may further include: a relational data generation unit configured to generate relational data; and a memory configured to store the relational data, wherein the relational data can be generated based on first EIS data obtained from a reference battery pack at a first temperature under a preset first condition and second EIS data obtained from a reference battery pack at a reference SOH under a preset second condition.

[0022] According to one embodiment, the preset first condition includes a specified state of charge (SOC) condition and a specified state of harmonics (SOH) condition in the idle range of the reference battery pack, and the preset second condition may include a specified SOC condition and a specified temperature condition in the idle range of the reference battery pack.

[0023] According to one implementation, the relational data generation unit can generate a function representing the trend between a plurality of temperatures included in the first temperature and an angle parameter corresponding to each of the plurality of temperatures, based on the first EIS data.

[0024] According to one embodiment, the relational data generation unit can obtain an angle parameter corresponding to each of the plurality of temperatures included in the first temperature and the plurality of SOHs included in the reference SOH based on the first EIS data and the second EIS data, and generate a function representing the trend between the angle parameter at the first temperature and the plurality of SOHs.

[0025] A method for predicting the state of operational health (SOH) according to one embodiment of the present invention may include: acquiring electrochemical impedance spectroscopy (EIS) data of a battery pack; identifying multiple feature points based on the EIS data; calculating an angle parameter related to the impedance of the battery pack based on the impedance associated with the multiple feature points; and predicting the SOH corresponding to the calculated angle parameter based on the relationship data between the temperature at which the EIS data is acquired, the angle parameter, and the SOH of the battery pack.

[0026] According to one implementation, the EIS data includes data relating to an EIS plot shown by dividing the impedance of the battery pack into real and imaginary parts, and a first feature point and a second feature point among a plurality of feature points may be associated with whether there is an inflection point in the EIS plot in a reference frequency region at a frequency higher than the frequency corresponding to the maximum point among the plurality of points identified based on the EIS plot.

[0027] According to one embodiment, when there is no inflection point in the reference frequency region, the first feature point can be associated with the point with the smallest real part of impedance among a plurality of points identified based on the EIS plot, and the second feature point can be associated with the point with the imaginary part of impedance being zero or the point with a frequency lower than the frequency corresponding to the point with the imaginary part being zero among the plurality of points identified based on the EIS plot. Furthermore, when there is an inflection point in the reference frequency region, the first feature point can be associated with the point with the smallest real part of impedance among a plurality of points identified based on the EIS plot, and the second feature point can be associated with the inflection point or the point with a frequency lower than the frequency corresponding to the inflection point among the plurality of points identified based on the EIS plot.

[0028] According to one implementation, the angle parameter can be related to the angle between the straight line connecting the second feature point to the first feature point and any coordinate axis of the EIS plot.

[0029] According to one implementation, relational data can be generated based on first EIS data obtained from a reference battery pack at a first temperature under specified state of charge (SOC) conditions and specified state of equilibrium (SOH) conditions in the idle interval of the reference battery pack, and second EIS data obtained from a reference battery pack at a reference SOH under specified SOC conditions and specified temperature conditions in the idle interval of the reference battery pack.

[0030] According to one embodiment, the step of predicting SOH may include: generating a function representing the trend between a plurality of temperatures included in a first temperature and an angle parameter corresponding to each of the plurality of temperatures, based on first EIS data; obtaining an angle parameter corresponding to each of the plurality of temperatures included in the first temperature and a plurality of SOHs included in a reference SOH, based on first EIS data and second EIS data; and generating a function representing the trend between the angle parameter at the first temperature and the plurality of SOHs.

[0031] Beneficial effects

[0032] According to one embodiment of the present invention, the SOH prediction device can predict SOH based on angle parameters without collecting angle parameters corresponding to each of all SOHs.

[0033] According to one embodiment disclosed herein, the SOH prediction device can approximate the angle parameters by using the pattern and coordinates of EIS data to obtain approximate angle parameters.

[0034] The effects of one embodiment disclosed herein are not limited to those described above, and other effects not described will be readily understood by those skilled in the art based on the disclosure of this document. Attached Figure Description

[0035] Figure 1 This is a view used to describe a health status (SOH) prediction device according to one embodiment disclosed herein.

[0036] Figures 2 to 5 It is a view used to describe EIS data and multiple feature points obtained based on EIS data according to one embodiment disclosed herein.

[0037] Figure 6 It is a view used to describe relational data according to one embodiment disclosed herein.

[0038] Figure 7 This is a view used to describe the angle parameters and temperature, and the relationship between the angle parameters and temperature, of one embodiment disclosed herein.

[0039] Figure 8 This is a flowchart describing the operation of an SOH prediction device according to one embodiment of the present document.

[0040] Figure 9 This is a flowchart describing the operation of an SOH prediction device according to one embodiment of the present document. Detailed Implementation

[0041] In the following, embodiments disclosed herein will be described in detail with reference to exemplary accompanying drawings. When adding reference numerals to components in each drawing, it should be noted that they will, as far as possible, have the same reference numerals even when the same components are shown in different drawings. Furthermore, in describing embodiments disclosed herein, detailed descriptions of related known configurations or functions will be omitted when it is determined that a detailed description obscures the understanding of the disclosed embodiments.

[0042] Terms such as first, second, A, B, (a), and (b) may be used to describe components of the embodiments disclosed in this document. These terms are used only to distinguish one component from another, and the nature, order, sequence, etc., of the corresponding components are not limited by the terms. Furthermore, unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments disclosed herein pertain. Unless expressly defined in this application, terms defined in commonly used dictionaries should be interpreted as meanings that correspond to the meanings of terms from the context of the relevant art, and should not be interpreted as ideal or overly formal meanings.

[0043] Figure 1 This is a view used to describe a health status (SOH) prediction device according to one embodiment disclosed herein.

[0044] Battery pack 100 may include multiple battery modules 110, 120, and 130. (See reference...) Figure 1 The diagram shows a battery pack 100 comprising three battery modules 110, 120, and 130, but is not limited thereto, and the battery pack 100 may include n (n is a natural number) battery modules. Each of the plurality of battery modules 110, 120, and 130 may include a plurality of battery cells (not shown). The plurality of battery cells (not shown) may be lithium-ion (Li-ion) batteries, nickel-metal hydride (Ni-H) batteries, etc., but is not limited thereto.

[0045] The battery pack 100 can be configured to supply power to a target device (not shown), and for this purpose, the battery pack 100 can be electrically connected to the target device (not shown). Here, the target device (not shown) can include an electrical, electronic, or mechanical device that operates by receiving power from the battery pack 100, and for example, the target device (not shown) can be a two-wheeled electric vehicle such as an electric vehicle (EV) or an electric scooter, but is not limited thereto. Furthermore, when the target device is a two-wheeled electric vehicle such as an electric scooter, the battery pack 100 installed on the two-wheeled electric vehicle can be replaced via a battery swapping station (BSS).

[0046] The SOH prediction device 200 can predict the SOH of the battery pack 100 based on angle parameters related to the impedance of the battery pack 100. (Refer to...) Figure 1 The SOH prediction device 200 may include an electrochemical impedance spectroscopy (EIS) data acquisition unit 210, a feature point identification unit 220, an angle parameter calculation unit 230, an SOH prediction unit 240, a relational data generation unit 250, and a memory 260.

[0047] The EIS data acquisition unit 210 can acquire EIS data as a result of EIS measurements of the battery pack 100. According to an embodiment, the EIS measurement may include measuring the impedance of the battery pack 100 by applying an AC voltage to the battery pack 100.

[0048] According to the implementation, the EIS data may include data about the EIS plot. For example, the EIS plot may be a Nyquist plot, which is shown by dividing the impedance of the battery pack 100, measured by changing the frequency of the AC voltage, into real and imaginary parts.

[0049] According to one embodiment, the EIS data acquisition unit 210 can acquire EIS data by directly applying voltage and / or current to the battery pack 100. In this case, the EIS data acquisition unit 210 may include various circuits for applying voltage and / or current to the battery pack 100 and a processor for processing the acquired EIS data.

[0050] According to one embodiment, the EIS data acquisition unit 210 can indirectly acquire EIS data from the battery pack 100. In this case, the EIS data acquisition unit 210 may include a communication module for communicating with the battery pack 100 in a wired and / or wireless manner.

[0051] The feature point recognition unit 220 can identify multiple feature points based on the acquired EIS data. According to one embodiment, the feature point recognition unit 220 can identify at least two feature points among multiple feature points identified based on the EIS map included in the EIS data.

[0052] According to the implementation method, the first and second feature points among the plurality of feature points can be correlated with the pattern of the EIS map in a reference frequency region, which is a frequency region with a higher frequency than the frequency corresponding to the largest point among the plurality of points identified based on the EIS map.

[0053] The angle parameter calculation unit 230 can calculate angle parameters related to the impedance of a first feature point and a second feature point among a plurality of feature points. According to an embodiment, the angle parameter can be defined as the angle between the straight line connecting the first feature point to the second feature point and the coordinate axis of the EIS plot. For example, based on the x-axis corresponding to the axis representing the real part of the coordinate system in the EIS plot, the angle parameter can include data related to the angle between the straight line connecting the first feature point to the second feature point and the x-axis; and based on the y-axis corresponding to the axis representing the imaginary part of the coordinate system in the EIS plot, the angle parameter can include data related to the angle between the straight line connecting the first feature point to the second feature point and the y-axis.

[0054] The SOH prediction unit 240 can predict the SOH of the battery pack 100 based on the angle parameters calculated by the angle parameter calculation unit 230. According to an embodiment, the SOH prediction unit 240 can predict the SOH of the battery pack 100 based on the temperature at which the EIS data is acquired and the relationship data between the angle parameters corresponding to the temperature at which the EIS data is acquired and the SOH.

[0055] The relational data generation unit 250 can generate relational data. (This will be...) Figure 3 and Figure 4 The description details the process of generating relational data.

[0056] The memory 260 may store relational data generated by the relational data generation unit 250. According to an embodiment, the memory 260 may include a volatile memory device such as static random access memory (SRAM) or dynamic random access memory (DRAM), or a non-volatile memory device such as read-only memory (ROM), programmable ROM (PROM), or flash memory.

[0057] Reference Figure 1 The diagram shows that the memory 260 is included in the SOH prediction device 200, but is not limited thereto, and the memory 260 may be located outside the SOH prediction device 200.

[0058] According to the implementation, the feature point recognition unit 220, the angle parameter calculation unit 230, the SOH prediction unit 240, and the relational data generation unit 250 can be implemented as a single processor or a separate processor. Here, the processor can execute software to control at least one other component (e.g., hardware or software) of the SOH prediction device 200 or perform operations to process and / or calculate various data.

[0059] According to one embodiment, the SOH prediction device 200 can be integrated with the battery pack 100. In this case, the SOH prediction device 200 can be included in the battery management system (BMS) of the battery pack 100.

[0060] According to one embodiment, the SOH prediction device 200 can be formed separately from the battery pack 100. In this case, the SOH prediction device 200 can be connected to the battery pack 100 via wired and / or wireless networks, etc. In this case, the SOH prediction device 200 can be implemented via a cloud server.

[0061] According to an implementation, the SOH prediction device 200 can send relational data generated by the relational data generation unit 250 and / or the SOH of the battery pack 100 predicted by the SOH prediction unit 240 to an external device (e.g., a cloud server or a user terminal). The cloud server can be configured to provide the predicted SOH of the battery pack 100 to each of a plurality of users, and the user terminal may include a terminal such as a personal computer (PC) or a smartphone.

[0062] According to one embodiment, the SOH prediction device 200 may be included in a BSS. The BSS may be a system that has a slot into which a battery pack 100 can be inserted and charges the inserted battery pack 100.

[0063] Figures 2 to 5 It is a view used to describe EIS data and multiple feature points obtained based on EIS data according to one embodiment disclosed herein.

[0064] First refer to Figure 2 The diagram illustrates an EIS graph included in EIS data according to one embodiment disclosed herein.

[0065] As mentioned above Figure 1 As described in the detailed description, the EIS data may include data relating to an EIS diagram shown by dividing the impedance of the battery pack 100 into the real part Re(Z) and the imaginary part Im(Z), which is obtained by changing the impedance applied to the battery pack 100 (see [reference]). Figure 1 The frequency of the AC power is measured. According to the implementation, the horizontal axis of the EIS graph can be the coordinate axis corresponding to the real part Re(Z), and the vertical axis can be the coordinate axis corresponding to the imaginary part Im(Z). Furthermore, as mentioned above... Figure 1 As described in the description, the first and second feature points among a plurality of feature points can be correlated with the pattern of an EIS map in a reference frequency region, which is a frequency region with a higher frequency than the frequency corresponding to the largest point among the plurality of points identified based on the EIS map.

[0066] According to the implementation, the first feature point and the second feature point can be associated with the pattern of the EIS plot in the maximum point 205 and the reference frequency region 220a, which corresponds to a frequency higher than the maximum point 205. For example, the first feature point and the second feature point can vary according to each of the following cases: Figure 2 The example shown illustrates the case where no inflection point exists among multiple points in the pattern recognition based on the EIS map within the reference frequency region 220a; and as shown... Figures 3 to 5 The example shown illustrates the case where an inflection point 205 exists among multiple points in the pattern recognition based on the EIS map within the reference frequency region 220a.

[0067] Return to reference Figure 2 This illustrates an implementation where no inflection point exists in the reference frequency region 220a. Feature point recognition unit 220 (see...) Figure 1 It can identify the first feature point 210 and the second feature point 220 among multiple feature points identified based on the EIS map.

[0068] According to the implementation, the first feature point 210 may be the point where the real part of the impedance of the battery pack 100 is the smallest in the EIS diagram, or may be associated with the point where the real part is the smallest. For example, the first feature point 210 may correspond to the point where the real part of the impedance is the smallest in the EIS diagram, or a point located within a preset range from the point where the real part is the smallest. Furthermore, the second feature point 220 may be any one of the points where the imaginary part of the impedance is zero in the EIS diagram, or a point having a frequency lower than the frequency corresponding to the point where the imaginary part is zero.

[0069] According to one embodiment, the first feature point can be associated with a point in the EIS diagram where the imaginary part of the impedance of the battery pack 100 is zero. For example, the first feature point can correspond to a point in the EIS diagram where the imaginary part of the impedance is zero or a point located within a preset range from the point where the imaginary part is zero. Furthermore, the second feature point can be associated with a point corresponding to a frequency lower than the frequency corresponding to the first feature point. That is, the second feature point can be either a point where the imaginary part of the impedance is zero, or a point with a frequency lower than the frequency corresponding to a point located within a preset range from the point where the imaginary part is zero. Here, the preset range can be set and changed in various ways.

[0070] For ease of description, the following description will assume that the first feature point 210 is the point with the smallest real part of the impedance of the battery pack 100 and the second feature point 205 is the largest point 205 among the points with a lower frequency compared to the point with a zero imaginary part of the impedance, but this document is not limited to this embodiment.

[0071] The angle parameter calculation unit 230 can calculate the angle parameter 230 based on the first feature point 210 and the second feature point 205. According to an embodiment, the angle parameter can be defined as the angle between the straight line 215 connecting the first feature point 210 to the second feature point 205 and the coordinate axis of the EIS plot. For ease of description, it will be assumed that the reference used to calculate the angle parameter 230 is the horizontal axis in the following description, but this document is not limited thereto.

[0072] For example, based on the horizontal axis corresponding to the coordinate axis Re(Z) representing the real part in the EIS graph, the angle parameter 230 may include data related to the angle between the straight line 215 connecting the first feature point 210 to the second feature point 205 and the horizontal axis.

[0073] As another example, based on the vertical axis corresponding to the coordinate axis Im(Z) representing the real part in the EIS graph, the angle parameter may include data related to the angle between the vertical axis and the straight line 215 connecting the first feature point 210 to the second feature point 205.

[0074] According to the implementation, the angle parameter calculation unit 230 can calculate the angle parameter by using the magnitude of the impedance calculated based on the difference in impedance between the first feature point 210 and the second feature point 205, various trigonometric functions, etc., but is not limited to this example.

[0075] Reference Figures 3 to 5 The diagram illustrates an EIS graph included in EIS data according to one embodiment disclosed herein.

[0076] As mentioned above Figure 1 As described in the description, the first and second feature points among a plurality of feature points can be correlated with the pattern of an EIS map in a reference frequency region 220a, which is a frequency region higher than the frequency corresponding to the maximum point 220 among the plurality of points identified based on the EIS map. Here, Figures 3 to 5 The EIS diagrams shown can each include various implementations where inflection points exist within the reference frequency region 220a. First, refer to... Figure 3 There is an inflection point 240 in the reference frequency region 220a. Here, the inflection point can correspond to the point where the pattern of the EIS plot changes.

[0077] According to one embodiment, when an inflection point 240 exists in the reference frequency region 220a, the first feature point 210 can be associated with the point among a plurality of points identified based on the EIS plot that has the smallest real part of the impedance. For example, the first feature point 210 can correspond to either the point with the smallest real part of the impedance or any point within a preset range from the point with the smallest real part. Here, the preset range can be changed and applied in various ways, and for example, it can be determined during the analysis of the EIS plot based on allowable errors, along with points at frequencies within a specific range, points within a specific range on the plot, etc., but is not limited to this example.

[0078] According to one embodiment, when an inflection point 240 exists in the reference frequency region 220a, the second feature point 240 can be associated with the inflection point 240. For example, the second feature point 240 can correspond to either the inflection point 240 or a point having a frequency lower than the frequency corresponding to the inflection point 240. For ease of description, it will be assumed that the first feature point 210 corresponds to the point where the real part of the impedance is minimized and the second feature point 240 corresponds to the inflection point in the following description, but this document is not limited to this example.

[0079] Angle parameter calculation unit 230 (see) Figure 1 The angle parameter 230 can be calculated based on the first feature point 210 and the second feature point 240. According to an embodiment, the angle parameter can be defined as the angle between the straight line 215 connecting the first feature point 210 to the second feature point 240 and the coordinate axis of the EIS plot. For ease of description, it will be assumed that the reference used to calculate the angle parameter 230 is the horizontal axis in the following description, but this document is not limited thereto.

[0080] For example, based on the horizontal axis corresponding to the coordinate axis Re(Z) representing the real part in the coordinate axis of the EIS plot, the angle parameter 230 may include data related to the angle between the straight line 215 connecting the first feature point 210 to the second feature point 240 and the horizontal axis.

[0081] As another example, based on the vertical axis corresponding to the imaginary axis Im(Z) in the coordinate system of the EIS plot, the angle parameter may include data related to the angle between the vertical axis and the straight line 215 that connects the first feature point 210 to the second feature point 240.

[0082] According to the implementation, the angle parameter calculation unit 230 can calculate the angle parameter by using the magnitude of the impedance calculated based on the difference in impedance between the first feature point 210 and the second feature point 240, various trigonometric functions, etc., but is not limited to this example.

[0083] Reference Figure 4 ,like Figure 3 As shown, there is an inflection point 240 in the reference frequency region 220a. Here, the inflection point 240 can correspond to the point where the pattern of the EIS plot changes.

[0084] According to one embodiment, when an inflection point 240 exists in the reference frequency region 220a, the first feature point 240 can be associated with an inflection point 240 among a plurality of points identified based on the EIS chart. For example, the first feature point 240 can correspond to an inflection point 240 where the EIS chart pattern changes, or to any point located within a preset range from the inflection point 240. Here, the inflection point 240 can correspond to an inflection point 240 where the EIS chart pattern changes among a plurality of inflection points identified on the EIS chart and a point corresponding to a frequency higher than the maximum point 220. Furthermore, the preset range can be set and applied in various ways.

[0085] According to one embodiment, when an inflection point 240 exists in the reference frequency region 220a, the second feature point 250 can be associated with the inflection point 240. For example, the second feature point 250 can correspond to any point with a frequency lower than the frequency corresponding to the inflection point 240. That is, the second feature point 250 can correspond to any point with a frequency lower than the first feature point 240. For ease of description, the following description will assume that the first feature point 240 corresponds to the inflection point and the second feature point 240 corresponds to any point with a frequency lower than the inflection point, but this document is not limited to this example.

[0086] Angle parameter calculation unit 230 (see) Figure 1 The angle parameter 230 can be calculated based on the first feature point 240 and the second feature point 250. According to an embodiment, the angle parameter can be defined as the angle between the straight line 215 connecting the first feature point 240 to the second feature point 250 and the coordinate axis of the EIS plot. For ease of description, it will be assumed that the reference used to calculate the angle parameter 230 is the horizontal axis in the following description, but this document is not limited thereto.

[0087] For example, based on the horizontal axis corresponding to the coordinate axis Re(Z) representing the real part in the EIS graph, the angle parameter 230 may include data related to the angle between the straight line 215 connecting the first feature point 240 to the second feature point 250 and the horizontal axis.

[0088] As another example, based on the vertical axis corresponding to the imaginary axis Im(Z) in the coordinate system of the EIS plot, the angle parameter may include data related to the angle between the vertical axis and the straight line 215 that connects the first feature point 240 to the second feature point 250.

[0089] According to the implementation, the angle parameter calculation unit 230 can calculate the angle parameter by using the magnitude of the impedance calculated based on the difference in impedance between the first feature point 240 and the second feature point 250, various trigonometric functions, etc., but is not limited to this example.

[0090] Reference Figure 5 ,like Figure 3 As shown, there is an inflection point 240 in the reference frequency region 220a. Here, the inflection point 240 can correspond to the point where the pattern of the EIS plot changes.

[0091] According to one embodiment, when an inflection point 240 exists in the reference frequency region 220a, the first feature point 210 can be associated with a point among a plurality of points identified based on the EIS diagram where the imaginary part of the impedance is zero. For example, the first feature point 210 can correspond to either a point 210 among the plurality of points identified based on the diagram where the imaginary part of the impedance is zero, or any point located within a preset range from the point where the imaginary part of the impedance is zero. Here, the preset range can be set and applied in various ways.

[0092] According to one embodiment, when an inflection point 240 exists in the reference frequency region 220a, the second feature point 240 may be associated with the inflection point. For example, the second feature point 240 may correspond to either the inflection point 240 or a point having a frequency lower than that corresponding to the inflection point 240. For ease of description, it will be assumed that the first feature point 210 corresponds to a point among a plurality of points identified based on the EIS plot where the imaginary part of the impedance is zero and the second feature point 240 corresponds to the inflection point in the following description, but this document is not limited to this example.

[0093] Angle parameter calculation unit 230 (see) Figure 1 The angle parameter 230 can be calculated based on the first feature point 210 and the second feature point 240. According to an embodiment, the angle parameter can be defined as the angle between the straight line 215 connecting the first feature point 210 to the second feature point 240 and the coordinate axis of the EIS plot. For ease of description, it will be assumed that the reference used to calculate the angle parameter 230 is the horizontal axis in the following description, but this document is not limited thereto.

[0094] For example, based on the horizontal axis corresponding to the coordinate axis Re(Z) representing the real part in the coordinate axis of the EIS plot, the angle parameter 230 may include data related to the angle between the straight line 215 connecting the first feature point 210 to the second feature point 240 and the horizontal axis.

[0095] As another example, based on the vertical axis corresponding to the imaginary axis Im(Z) in the coordinate system of the EIS plot, the angle parameter may include data related to the angle between the vertical axis and the straight line 215 that connects the first feature point 210 to the second feature point 240.

[0096] According to the implementation, the angle parameter calculation unit 230 can calculate the angle parameter by using the magnitude of the impedance calculated based on the difference in impedance between the first feature point 210 and the second feature point 240, various trigonometric functions, etc., but is not limited to this example.

[0097] Figure 6 It is a view used to describe relational data according to one embodiment disclosed herein, and Figure 7It is a view used to describe the angle parameter and temperature, and the relationship between the angle parameter and temperature, according to one embodiment disclosed herein.

[0098] Relational data generation unit 250 can generate data such as... Figure 6 The relational data 261 is shown. The relational data generation unit 250 can generate the relational data 261 based on the EIS data of the reference battery pack. Here, the reference battery pack can be the same as that of battery pack 100 (see reference). Figure 1 (The same type of battery pack.) According to an embodiment, the relationship data 261 may include data indicating the correspondence between temperature, SOH, and angle parameters, and the relationship data 261 may be in the form of, for example... Figure 6 The lookup table shown is stored in memory 260.

[0099] According to the implementation, the relational data generation unit 250 can generate relational data 261a between the first temperatures T1 to T5 and the angle parameters Angle 11 to Angle 51 corresponding to each of the first temperatures, based on the first EIS data corresponding to each of the first temperatures T1 to T5 under preset first conditions. Here, the preset first conditions may include a specified state of charge (SOC) condition and a specified state of harmonics (SOH) condition in a reference battery pack in an idle state.

[0100] For example, the relational data generation unit 250 can generate relational data 261a by changing the temperature of a reference battery pack corresponding to the first SOH condition to a first temperature T1 to T5 under a specified SOC condition. Furthermore, the relational data generation unit 250 can generate relational data by changing the temperature of a reference battery pack corresponding to the second SOH condition to a first temperature T1 to T5 under a specified SOC condition.

[0101] According to the implementation method, there may be a trend between temperature and angle parameters. (Refer to...) Figure 4 The graph shows the relationship between the angle parameters Angle11 to Angle51 corresponding to each of the first temperatures T1 to T5. The relational data generation unit 250 can generate a function representing the trend between temperature and angle parameters based on the first temperatures T1 to T5 and the angle parameters Angle11 to Angle51 corresponding to each of the first temperatures T1 to T5.

[0102] According to the implementation, the relational data generation unit 250 can calculate the angle parameter corresponding to each temperature based on a function representing the trend between temperature and angle parameters. The relational data generation unit 250 can supplement the relational data 261 based on the angle parameters calculated by substituting different temperatures into the function representing the trend between temperature and angle parameters.

[0103] Return to reference Figure 3 The relational data generation unit 250 can generate relational data 261b between the reference SOH, the first SOH to the Nth SOH, and the angle parameters Angle11 to Angle1N corresponding to the reference SOH, based on the second EIS data corresponding to each of the reference SOH, the first SOH to the Nth SOH, under a preset second condition. Here, the preset second condition may include a specified SOC condition and a specified temperature condition in the reference battery pack in an idle state.

[0104] For example, the relational data generation unit 250 can generate relational data 261b based on angle parameters Angle11 to Angle1N obtained by changing the SOH of a reference battery pack corresponding to a specified temperature condition T1 to a reference SOH, a first SOH to an Nth SOH under a specified SOC condition. Furthermore, the relational data generation unit 250 can generate relational data based on angle parameters Angle21 to Angle2N obtained by changing the SOH of a reference battery pack corresponding to a specified temperature condition T2 to a reference SOH, a first SOH to an Nth SOH under a specified SOC condition.

[0105] According to the implementation method, there may be a trend between SOH and the angle parameter. (Return to reference) Figure 7 The diagram shows curves between the reference SOH and the first SOH to the Nth SOH, corresponding to angle parameters Angle 11 to Angle 1N, respectively. The relational data generation unit 250 can generate a function representing the trend between the SOH of the reference battery pack and the angle parameters based on the angle parameters Angle 11 to Angle 1N and the reference SOH and the first SOH to the Nth SOH corresponding to the angle parameters Angle 11 to Angle 1N, respectively.

[0106] According to the implementation, the function representing the trend between the angle parameter and SOH can include a polynomial function. For example, the function representing the trend between the angle parameter and SOH can be represented as a linear function that represents the linear relationship between the angle parameter and SOH, but is not limited thereto.

[0107] According to the implementation, the relational data generation unit 250 can calculate the SOH corresponding to each angle parameter based on a function representing the trend between the angle parameter and SOH. The relational data generation unit 250 can supplement the relational data 261 based on the SOH calculated by substituting different angle parameters into the function representing the trend between the angle parameter and SOH.

[0108] To predict battery pack lifespan through EIS analysis, EIS data needs to be repeatedly collected by varying various conditions (e.g., temperature, SOC, and SOH). However, as mentioned above, the process of repeatedly collecting EIS data can be time-consuming. Furthermore, the process of measuring battery pack impedance through EIS analysis tends to take more time in the low-frequency region compared to the high-frequency region.

[0109] The SOH prediction device according to the embodiments disclosed herein can predict the SOH of the battery pack based on a function obtained by changing the conditions where a trend exists, without having to collect EIS data under various conditions (e.g., all temperatures or all SOHs). Furthermore, because the SOH prediction device according to one embodiment disclosed herein can predict SOH based on the angle parameter between a first feature point and a second feature point, the SOH of the battery pack can be predicted without measuring the impedance of the battery pack at frequencies below the second feature point.

[0110] Figure 8 This is a flowchart describing the operation of an SOH prediction device according to one embodiment of the present document.

[0111] In operation S801, the SOH prediction device 200 (see...) Figure 1 You can get a battery pack of 100 (see) Figure 1 The EIS data may include data relating to an EIS diagram showing the impedance of the battery pack 100 divided into real and imaginary parts, according to an embodiment.

[0112] In operation S803, the SOH prediction device 200 can identify multiple feature points based on EIS data. According to an embodiment, a first feature point among the multiple feature points may correspond to the point where the real part of the impedance of the battery pack 100 is minimum or the point where the imaginary part of the impedance of the battery pack 100 is zero in the EIS diagram. Furthermore, a second feature point among the multiple feature points may be any one of the maximum point in the EIS diagram and / or a point with a frequency lower than that corresponding to the maximum point.

[0113] In operation S805, the SOH prediction device 200 can calculate the angle parameters of the battery pack 100 based on the impedance associated with multiple feature points. According to an embodiment, the angle parameters may include data relating to the angle between the straight line connecting the second feature point to the first feature point and any coordinate axis of the EIS plot.

[0114] In operation S807, the SOH prediction device 200 can predict the SOH of the battery pack 100 based on the temperature at which the EIS data is acquired, the calculated angle parameters, and the relationship between the angle parameters and the SOH of the battery pack 100.

[0115] According to the implementation, relational data can be generated based on first EIS data obtained from a reference battery pack at a first temperature under specified SOC and SOH conditions within the idle range of the reference battery pack, and second EIS data obtained from a reference battery pack at the first SOH under specified SOC and temperature conditions within the idle range of the reference battery pack. Here, the reference battery pack may be a battery pack of the same type as battery pack 100.

[0116] Figure 9 This is a flowchart describing the operation of an SOH prediction device according to one embodiment of the present document.

[0117] Reference Figure 9 , will describe in detail Figure 8 The operation S807 is shown in the figure.

[0118] In operation S901, the SOH prediction device 200 (see...) Figure 1 The first EIS data can be obtained from the reference battery pack at the first temperature under the first condition, and in operation S903, the SOH prediction device 200 can obtain the second EIS data from the reference battery pack at the reference SOH under the second condition.

[0119] According to the implementation, the first condition may include a specified SOC condition and a specified SOH condition in the idle range of the reference battery pack, and the second condition may include a specified SOC condition and a specified temperature condition in the idle range of the reference battery pack.

[0120] In operation S905, the SOH prediction device 200 can generate a function representing the trend between the plurality of temperatures included in the first temperature and the angle parameter corresponding to each of the plurality of temperatures. Furthermore, in operation S907, the SOH prediction device 200 can generate a function representing the trend between the plurality of SOHs included in the reference SOH and the angle parameter corresponding to each of the plurality of SOHs.

[0121] In operation S909, the SOH prediction device 200 can generate data on the relationship between temperature, angle parameters and SOH based on each function generated in operations S905 and S907.

[0122] All components constituting an embodiment are described above as operating as one or by means of coupling, but are not necessarily limited to these embodiments, and within the scope of this purpose, one or more of all components may operate by selective coupling. Furthermore, unless otherwise stated, terms such as “comprising,” “constituting,” or “having” described above mean that the corresponding component may be inherent and should therefore be interpreted as including other components rather than excluding them.

[0123] The above description is merely an exemplary description of the technical spirit disclosed herein, and those skilled in the art to which the embodiments disclosed herein pertain will be able to make various modifications and changes to the embodiments without departing from the basic characteristics of the embodiments disclosed herein.

[0124] Therefore, the embodiments disclosed herein are not intended to limit the technical spirit disclosed herein, but rather to describe the technical spirit disclosed herein, and the scope of the technical spirit disclosed herein is not limited by these embodiments. The scope of the technical spirit disclosed herein should be interpreted by the appended claims, and all technical spirit within the equivalent scope should be interpreted as included within the scope of this document.

[0125] Description of reference numerals in the attached figures

[0126] 100: Battery pack

[0127] 110, 120, 130: Battery Module

[0128] 200: SOH Prediction Device

[0129] 210: EIS Data Acquisition Unit

[0130] 220: Feature Point Recognition Unit

[0131] 230: Angle Parameter Calculation Unit

[0132] 240: SOH Prediction Unit

[0133] 250: Relational Data Generation Unit

[0134] 260: Memory

Claims

1. A health status (SOH) prediction device, comprising: Battery pack; An electrochemical impedance spectroscopy (EIS) data acquisition unit is configured to acquire EIS data of the battery pack. A feature point recognition unit, configured to recognize multiple feature points based on the EIS data; An angle parameter calculation unit is configured to calculate an angle parameter related to the impedance of the battery pack based on the impedance associated with the plurality of feature points. as well as The SOH prediction unit is configured to predict the SOH corresponding to the calculated angle parameter based on the relationship data between the temperature at which the EIS data is obtained, the angle parameter, and the SOH of the battery pack.

2. The SOH prediction device according to claim 1, wherein, The EIS data includes data relating to an EIS diagram shown by dividing the impedance of the battery pack into real and imaginary parts, and The first and second feature points among the plurality of feature points are related to whether there is an inflection point in the EIS map in a reference frequency region that is higher than the frequency corresponding to the largest point among the plurality of points identified based on the EIS map.

3. The SOH prediction device according to claim 2, wherein, In the absence of the inflection point in the reference frequency region The first feature point is associated with the point among the plurality of points identified based on the EIS map that has the smallest real part of the impedance, and The second feature point is associated with a point among the plurality of points identified based on the EIS plot whose imaginary part of impedance is zero or whose frequency is lower than the frequency corresponding to the point whose imaginary part is zero.

4. The SOH prediction device according to claim 2, wherein, In the absence of the inflection point in the reference frequency region The first feature point is associated with the point among the plurality of points identified based on the EIS map where the imaginary part of the impedance is zero, and The second feature point is associated with a point among the plurality of points identified based on the EIS map whose frequency is lower than that corresponding to the first feature point.

5. The SOH prediction device according to claim 2, wherein, When the inflection point exists in the reference frequency region. The first feature point is associated with the point among the plurality of points identified based on the EIS map that has the smallest real part of the impedance, and The second feature point is associated with an inflection point or a point with a frequency lower than the frequency corresponding to the inflection point among the plurality of points identified based on the EIS map.

6. The SOH prediction device according to claim 2, wherein, When the inflection point exists in the reference frequency region. The first feature point is related to the inflection point, and The second feature point is associated with a point corresponding to a frequency lower than the frequency corresponding to the inflection point.

7. The SOH prediction device according to claim 2, wherein, When the inflection point exists in the reference frequency region. The first feature point is associated with the point among the plurality of points identified based on the EIS map where the imaginary part of the impedance is zero, and The second feature point is associated with an inflection point or a point corresponding to a frequency lower than the frequency corresponding to the inflection point.

8. The SOH prediction device according to claim 2, wherein, The angle parameter is related to the angle between the straight line connecting the second feature point to the first feature point and any coordinate axis of the EIS graph.

9. The SOH prediction device according to claim 2, wherein, The EIS data includes data relating to the EIS plot shown at the frequency corresponding to the second feature point and in a frequency region higher than the frequency corresponding to the second feature point.

10. The SOH prediction device according to claim 1, further comprising: A relational data generation unit, configured to generate the relational data; as well as A memory, configured to store the relational data, The relationship data is generated based on first EIS data obtained from a reference battery pack at a first temperature under a preset first condition and second EIS data obtained from the reference battery pack at a reference SOH under a preset second condition.

11. The SOH prediction device according to claim 10, wherein, The preset first condition includes a specified state of charge (SOC) condition and a specified state of harmonics (SOH) condition in the idle range of the reference battery pack, and The preset second condition includes a specified SOC condition and a specified temperature condition in the idle range of the reference battery pack.

12. The SOH prediction device according to claim 11, wherein, The relational data generation unit generates a function based on the first EIS data, representing the trend between the plurality of temperatures included in the first temperature and the angle parameter corresponding to each of the plurality of temperatures.

13. The SOH prediction device according to claim 11, wherein, The relational data generation unit obtains an angle parameter corresponding to each of the plurality of temperatures included in the first temperature and the plurality of SOHs included in the reference SOH based on the first EIS data and the second EIS data, and generates a function representing the trend between the angle parameter and the plurality of SOHs at the first temperature.

14. A method for predicting operating health status (SOH) of a device, the method comprising: Steps for obtaining electrochemical impedance spectroscopy (EIS) data of a battery pack; The steps for identifying multiple feature points based on the EIS data; The step of calculating the angle parameters related to the impedance of the battery pack based on the impedance associated with the plurality of feature points; as well as The step of predicting the SOH corresponding to the calculated angle parameters based on the relationship data between the temperature at which the EIS data is obtained, the angle parameters, and the SOH of the battery pack.

15. The method of the operating health status (SOH) prediction device according to claim 14, wherein, The EIS data includes data relating to an EIS diagram shown by dividing the impedance of the battery pack into real and imaginary parts, and The first and second feature points among the plurality of feature points are related to whether there is an inflection point in the EIS map in a reference frequency region that is higher than the frequency corresponding to the largest point among the plurality of points identified based on the EIS map.

16. The method of the operating health status (SOH) prediction device according to claim 15, wherein, In the absence of the inflection point in the reference frequency region The first feature point is associated with the point among the plurality of points identified based on the EIS map that has the smallest real part of the impedance, and The second feature point is associated with a point among the plurality of points identified based on the EIS plot where the imaginary part of the impedance is zero, or a point whose frequency is lower than the frequency corresponding to the point where the imaginary part is zero. When the inflection point exists in the reference frequency region. The first feature point is associated with the point among the plurality of points identified based on the EIS map that has the smallest real part of the impedance, and The second feature point is associated with the inflection point or the point with a frequency lower than the frequency corresponding to the inflection point among the plurality of points identified based on the EIS map.

17. The method of the operating health status (SOH) prediction device according to claim 15, wherein, The angle parameter is related to the angle between the straight line connecting the second feature point to the first feature point and any coordinate axis of the EIS graph.

18. The method of the operating health status (SOH) prediction device according to claim 14, wherein, The relationship data is generated based on first EIS data obtained from the reference battery pack at a first temperature under specified state of charge (SOC) and specified state of equilibrium (SOH) conditions in the idle range of the reference battery pack, and second EIS data obtained from the reference battery pack at the reference SOH under specified SOC and specified temperature conditions in the idle range of the reference battery pack.

19. The method of the operating health status (SOH) prediction device according to claim 18, wherein, The steps for predicting the SOH include: Based on the first EIS data, the step of generating a function representing the trend between the plurality of temperatures included in the first temperature and the angle parameter corresponding to each of the plurality of temperatures; Based on the first EIS data and the second EIS data, the step of obtaining an angle parameter corresponding to each of the plurality of temperatures included in the first temperature and the plurality of SOHs included in the reference SOH; and The step of generating a function representing the trend between the angle parameter and the plurality of SOHs at the first temperature.

Images