HEALTH STATE PREDICTION DEVICE (SOH) AND METHODS OF OPERATING THIS DEVICE
Patent Information
- Authority / Receiving Office
- VN · VN
- Patent Type
- Applications
- Current Assignee / Owner
- LG ENERGY SOLUTION LTD
- Filing Date
- 2024-09-03
- Publication Date
- 2026-07-01
AI Technical Summary
Existing battery life prediction methods for secondary batteries, particularly lithium-ion batteries, are inefficient and require extensive data collection, making it challenging to accurately predict State of Health (SOH) without significant time and resource investment.
A SOH prediction device and method that utilizes Electrochemical Impedance Spectroscopy (EIS) data to identify feature points, calculate an angle parameter associated with the impedance, and predict SOH based on temperature and angle parameter correlations, reducing the need for extensive data collection.
The proposed solution enables efficient prediction of battery SOH by leveraging EIS data and angle parameters, thereby reducing the time and resources required for data collection and analysis, while providing accurate SOH predictions.
Smart Images
Figure VN1202603462_0
Abstract
Description
SOH prediction device and its operating method
[0001] Cross-citation with related applications
[0002] This invention claims the benefit of priority to Korean Patent Application No. 10-2023-0148220, filed October 31, 2023, the entire contents of which are incorporated herein by reference.
[0003] Technology field
[0004] The embodiments disclosed in this document relate to an SOH prediction device and an operating method thereof.
[0005] Research and development on secondary batteries has been actively conducted recently. Here, the term "secondary battery" refers to a rechargeable battery, encompassing both conventional Ni / Cd and Ni / MH batteries, as well as more recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of a much higher energy density than conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in a compact and lightweight form, making them a popular power source for mobile devices. Recently, their use has expanded to include power sources for electric vehicles, drawing attention as a next-generation energy storage medium.
[0006] Battery exchange systems exist as a service related to these secondary batteries. These systems can provide users with a service that exchanges discharged batteries for charged ones.
[0007] Such battery replacement systems may utilize methods for predicting the lifespan of batteries used in service. For example, electrochemical impedance spectroscopy (EIS) may be used to measure battery lifespan.
[0008] According to one embodiment disclosed in the present document, an SOH prediction device and an operating method thereof for predicting the SOH of a battery pack based on an angular parameter related to the impedance of the battery pack are provided.
[0009] 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 to which the present invention pertains from the description below.
[0010] An SOH prediction device according to an embodiment disclosed in the present document may include: a battery pack; an EIS data acquisition unit that acquires EIS (Electrochemical Impedance Spectroscopy) data of the battery pack; a feature identification unit that identifies a plurality of feature points based on the EIS data; an angle parameter calculation unit that calculates an angle parameter related to an impedance of the battery pack based on impedances related to the plurality of feature points; and an SOH prediction unit that predicts an SOH corresponding to the calculated angle parameter based on relationship data between a temperature at which the EIS data was acquired, the angle parameter, and the SOH of the battery pack.
[0011] According to one embodiment, the EIS data includes data regarding an EIS graph that depicts the impedance of the battery pack by dividing it into a real part and an imaginary part, and among the plurality of characteristic points, a first characteristic point and a second characteristic point may be related to whether an inflection point exists in the EIS graph in a reference frequency range greater than a frequency corresponding to a maximum point among a plurality of points identified based on the EIS graph.
[0012] According to one embodiment, when there is no inflection point in the reference frequency region, the first characteristic point may be associated with a point having a smallest real value of impedance among a plurality of points identified based on the EIS graph, and the second characteristic point may be associated with a point having a imaginary value of impedance of 0 among a plurality of points identified based on the EIS graph or a point having a frequency smaller than a frequency corresponding to a point having a imaginary value of 0.
[0013] According to one embodiment, when there is no inflection point in the reference frequency region, the first characteristic point may be associated with a point among a plurality of points identified based on the EIS graph having an imaginary value of impedance of 0, and the second characteristic point may be associated with a point among a plurality of points identified based on the EIS graph having a frequency lower than a frequency corresponding to the first characteristic point.
[0014] According to one embodiment, when an inflection point exists in the reference frequency region, the first characteristic point may be related to a point having a smallest real value of impedance among a plurality of points identified based on the EIS graph, and the second characteristic point may be related to a point having a frequency smaller than the inflection point or a frequency corresponding to the inflection point among a plurality of points identified based on the EIS graph.
[0015] According to one embodiment, when an inflection point exists in the reference frequency region, the first characteristic point may be related to the inflection point, and the second characteristic point may be related to points corresponding to a frequency lower than the frequency corresponding to the inflection point.
[0016] According to one embodiment, when an inflection point exists in the reference frequency region, the first characteristic point may be associated with a point among a plurality of points identified based on the EIS graph where the imaginary value of the impedance is 0, and the second characteristic point may be associated with points corresponding to the inflection point or a frequency lower than the frequency corresponding to the inflection point.
[0017] In one embodiment, the angle parameter may be related to an angle between a straight line connecting the second feature point and the first feature point and one of the coordinate axes of the EIS graph.
[0018] According to one embodiment, the EIS data may include data regarding an EIS graph shown in a frequency region corresponding to the second feature point and a frequency region greater than the frequency corresponding to the second feature point.
[0019] An SOH prediction device according to one embodiment further includes a relationship data generation unit for generating the relationship data; and a memory for storing the relationship data; wherein the relationship data can be generated based on first EIS data acquired from a reference battery pack of a first temperature under a preset first condition and second EIS data acquired from a reference battery pack of a reference SOH under a preset second condition.
[0020] According to one embodiment, the first preset condition may include a specified SoC (State of Charge) condition and a specified SoH (State of Health) condition in the rest period of the reference battery pack, and the second preset condition may include a specified SoC condition and a specified temperature condition in the rest period of the reference battery pack.
[0021] According to one embodiment, the relationship data generation unit can generate a function representing a tendency 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.
[0022] According to one embodiment, the relationship data generation unit may obtain an angle parameter corresponding to each of a plurality of temperatures included in the first temperature and a plurality of SOHs included in the reference SOH based on the first EIS data and the second EIS data, and generate a function indicating a tendency between the angle parameter and the plurality of SOHs at the first temperature.
[0023] An operating method of an SOH prediction device according to an embodiment disclosed in the present document may include the steps of: obtaining EIS data of a battery pack; identifying a plurality of feature points based on the EIS data; calculating an angular parameter related to an impedance of the battery pack based on an impedance related to the plurality of feature points; and predicting an SOH corresponding to the calculated angular parameter based on relationship data between a temperature at which the EIS data was obtained, the angular parameter, and the SOH of the battery pack.
[0024] According to one embodiment, the EIS data includes data regarding an EIS graph that divides the impedance of the battery pack into a real part and an imaginary part, and the first and second characteristic points among the plurality of characteristic points may be related to whether an inflection point exists in the EIS graph in a reference frequency range greater than a frequency corresponding to a maximum point among the plurality of points identified based on the EIS graph.
[0025] According to one embodiment, when there is no inflection point in the reference frequency region, the first characteristic point may be associated with a point having a smallest real value of impedance among a plurality of points identified based on the EIS graph, the second characteristic point may be associated with a point having a zero imaginary value of impedance or a frequency smaller than a frequency corresponding to a point having a zero imaginary value, among a plurality of points identified based on the EIS graph, and when there is an inflection point in the reference frequency region, the first characteristic point may be associated with a point having a smallest real value of impedance among a plurality of points identified based on the EIS graph, and the second characteristic point may be associated with a point having a frequency smaller than the inflection point or a frequency corresponding to the inflection point, among a plurality of points identified based on the EIS graph.
[0026] In one embodiment, the angle parameter may be related to an angle between a straight line connecting the second feature point and the first feature point and one of the coordinate axes of the EIS graph.
[0027] According to one embodiment, the relationship data may be generated based on first EIS data obtained from a reference battery pack at a specified State of Charge (SoC) condition, a specified State of Health (SoH) condition, and a first temperature in a rest period of the reference battery pack, and second EIS data obtained from a reference battery pack at a specified SoC condition, a specified temperature condition, and a reference SOH in a rest period of the reference battery pack.
[0028] According to one embodiment, the step of predicting the SOH may include: generating a function representing a tendency between a plurality of temperatures included in the first temperature and an angular parameter corresponding to each of the plurality of temperatures based on the first EIS data; obtaining an angular parameter corresponding to each of the plurality of temperatures included in the first temperature and a plurality of SOHs included in the reference SOH based on the first EIS data and the second EIS data; and generating a function representing a tendency between the angular parameter and the plurality of SOHs at the first temperature.
[0029] An SOH prediction device according to an embodiment disclosed in this document can predict an SOH according to an angular parameter without collecting angular parameters corresponding to each SOH.
[0030] An SOH prediction device according to an embodiment disclosed in this document can obtain an angular parameter by approximating it through the shape and coordinates of EIS data.
[0031] The effects according to the embodiments disclosed in this document are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art according to the disclosure of this document.
[0032] FIG. 1 is a drawing for explaining an SOH prediction device according to an embodiment disclosed in this document.
[0033] FIGS. 2 to 5 are diagrams for explaining EIS data and a plurality of feature points acquired based on EIS data according to one embodiment disclosed in this document.
[0034] FIG. 6 is a diagram for explaining relationship data according to one embodiment disclosed in this document.
[0035] FIG. 7 is a diagram for explaining the relationship between angle parameter-temperature and angle parameter-temperature according to one embodiment disclosed in this document.
[0036] FIG. 8 is a flowchart for explaining the operation of an SOH prediction device according to an embodiment disclosed in this document.
[0037] FIG. 9 is a flowchart for explaining the operation of an SOH prediction device according to an embodiment disclosed in this document.
[0038] Hereinafter, embodiments disclosed in this document will be described in detail with reference to exemplary drawings. When designating components in each drawing, it should be noted that, where possible, identical components are given identical reference numerals, even if they appear in different drawings. Furthermore, when describing embodiments disclosed in this document, detailed descriptions of related known structures or functions will be omitted if they are deemed to hinder understanding of the embodiments disclosed in this document.
[0039] In describing the components of the embodiments disclosed in this document, terms such as first, second, A, B, (a), (b), etc. may be used. These terms are only intended to distinguish the components from other components and do not limit the nature, order, or sequence of the components. In addition, 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 in this document belong. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning they have in the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense unless explicitly defined in this application.
[0040] FIG. 1 is a drawing for explaining an SOH prediction device according to an embodiment disclosed in this document.
[0041] The battery pack (100) may include a plurality of battery modules (110, 120, 130). Referring to FIG. 1, the battery pack (100) is illustrated as including three battery modules (110, 120, 130), but is not limited thereto, and the battery pack (100) may be configured to include n (n is a natural number) battery modules. Each of the plurality of battery modules (110, 120, 130) may include a plurality of battery cells (not shown). The plurality of battery cells (not shown) may be, but are not limited to, lithium ion (Li-ion) batteries, nickel-hydrogen (Ni-H) batteries, etc.
[0042] The battery pack (100) may be configured to supply power to a target device (not shown), and for this purpose, the battery pack (100) may be electrically connected to the target device (not shown). Here, the target device (not shown) may include an electrical, electronic, or mechanical device that operates by receiving power from the battery pack (100). For example, the target device (not shown) may be, but is not limited to, a two-wheeled electric vehicle such as an electric vehicle (EV) or an electric scooter. In addition, when the target device is a two-wheeled electric vehicle such as an electric scooter, the battery pack (100) mounted on the two-wheeled electric vehicle may be replaceable through a battery swapping station (BSS).
[0043] The SOH prediction device (200) can predict the SOH (State of Health) of the battery pack (100) based on an angular parameter related to the impedance of the battery pack (100). Referring to FIG. 1, the SOH prediction device (200) can include an EIS data acquisition unit (210), a feature point identification unit (220), an angular parameter calculation unit (230), an SOH prediction unit (240), a relationship data generation unit (250), and a memory (260).
[0044] The EIS data acquisition unit (210) can acquire EIS data obtained as a result of EIS (Electrochemical Impedance Spectroscopy) measurement of the battery pack (100). According to an embodiment, the EIS measurement may include an operation of measuring the impedance of the battery pack (100) by applying an AC voltage to the battery pack (100).
[0045] According to one embodiment, the EIS data may include data regarding an EIS graph. For example, the EIS graph may be a Nyquist plot that divides the impedance of a battery pack (100) measured by varying the frequency of an AC voltage into a real part and an imaginary part.
[0046] According to one embodiment, the EIS data acquisition unit (210) may 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.
[0047] According to one embodiment, the EIS data acquisition unit (210) may 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) via wires and / or wirelessly.
[0048] The feature point identification unit (220) can identify a plurality of feature points based on the acquired EIS data. According to an embodiment, the feature point identification unit (220) can identify at least two feature points among the plurality of feature points identified based on the EIS graph included in the EIS data.
[0049] According to an embodiment, among the plurality of feature points, the first feature point and the second feature point may be related to the deformation of the EIS graph in a reference frequency region, which is a frequency region greater than a frequency corresponding to a maximum point among the plurality of points identified based on the EIS graph.
[0050] The angle parameter calculation unit (230) can calculate an angle parameter related to the impedance of the first feature point and the second feature point among the plurality of feature points. According to an embodiment, the angle parameter can be defined as an angle between a straight line connecting the first feature point and the second feature point and a coordinate axis of the EIS graph. For example, when the x-axis corresponding to the coordinate axis representing the real part among the coordinate axes of the EIS graph is used as a reference, the angle parameter can include data related to the angle between the straight line connecting the first feature point and the second feature point and the x-axis, and when the y-axis corresponding to the coordinate axis representing the imaginary part among the coordinate axes of the EIS graph is used as a reference, the angle parameter can include data related to the angle between the y-axis and the straight line connecting the first feature point and the second feature point.
[0051] The SOH prediction unit (240) can predict the SOH of the battery pack (100) based on the angle parameter 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 relationship data between the temperature at which the EIS data was acquired, the angle parameter corresponding to the temperature at which the EIS data was acquired, and the SOH.
[0052] The relationship data generation unit (250) can generate relationship data. The process of generating relationship data is described in detail in the description of FIGS. 3 and 4.
[0053] The memory (260) can store the relationship data generated by the relationship data generation unit (250). According to an embodiment, the memory (260) can include a volatile memory device such as a static random access memory (SRAM) or a dynamic random access memory (DRAM), or a non-volatile memory device such as a read only memory (ROM), a programmable ROM (PROM), or a flash memory.
[0054] Referring to FIG. 1, the memory (260) is illustrated as being 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).
[0055] According to an embodiment, the feature point identification unit (220), the angle parameter calculation unit (230), the SOH prediction unit (240), and the relationship data generation unit (250) may be implemented as one processor or as separate processors. Here, the processor may execute software to control at least one other component (e.g., hardware or software) of the SOH prediction device (200), or perform operations such as processing and / or calculating various data.
[0056] According to an embodiment, the SOH prediction device (200) may be formed integrally with the battery pack (100). In this case, the SOH prediction device (200) may be included in the BMS (Battery Management System) of the battery pack (100).
[0057] According to an embodiment, the SOH prediction device (200) may be formed separately from the battery pack (100). In this case, the SOH prediction device (200) may be connected to the battery pack (100) via a wired and / or wireless network, etc. In this case, the SOH prediction device (200) may be implemented via a cloud server.
[0058] According to an embodiment, the SOH prediction device (200) can transmit the relationship data generated by the relationship data generation unit (250) and / or the SOH of the battery pack (100) predicted by the SOH prediction unit (240) to an external source (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 can include a terminal such as a personal computer (PC) or a smartphone.
[0059] According to an embodiment, the SOH prediction device (200) may be included in a BSS (Battery Swapping System). The BSS may be a system having a slot into which a battery pack (100) can be inserted and capable of charging the inserted battery pack (100).
[0060] FIGS. 2 to 5 are diagrams for explaining EIS data and a plurality of feature points acquired based on EIS data according to one embodiment disclosed in this document.
[0061] First, referring to FIG. 2, an EIS graph included in EIS data according to one embodiment disclosed in this document is schematically illustrated.
[0062] As described above in the detailed description of FIG. 1, the EIS data may include data regarding an EIS graph that divides the impedance of the battery pack (100, see FIG. 1) into a real part (Re(Z)) and an imaginary part (Im(Z)) and shows the impedance of the battery pack (100) measured while changing the frequency of the AC power applied to the battery pack. According to an embodiment, the horizontal axis of the EIS graph may be a coordinate axis corresponding to the real part (Re(Z)), and the vertical axis may be a coordinate axis corresponding to the imaginary part (Im(Z)). In addition, as described above in the description of FIG. 1, among the plurality of characteristic points, the first characteristic point and the second characteristic point may be related to the shape of the EIS graph in a reference frequency region, which is a frequency region greater than a frequency corresponding to a maximum point among the plurality of points identified based on the EIS graph.
[0063] According to an embodiment, the first characteristic point and the second characteristic point may be related to the deformation of the EIS graph in the reference frequency region (220a), which is a region corresponding to a maximum point (205) and a frequency greater than the maximum point (205). For example, the first characteristic point and the second characteristic point may differ depending on whether there is no inflection point among a plurality of points identified based on the deformation of the EIS graph in the reference frequency region (220a), as illustrated in FIG. 2, or whether there is an inflection point (205) among a plurality of points identified based on the deformation of the EIS graph in the reference frequency region (220a), as illustrated in FIGS. 3 to 5.
[0064] Referring again to FIG. 2, an example is illustrated in which no inflection point exists in the reference frequency range (220a). The feature point identification unit (220, see FIG. 1) can identify a first feature point (210) and a second feature point (220) among a plurality of feature points identified based on the EIS graph.
[0065] According to an embodiment, the first characteristic point (210) may be related to a point in the EIS graph where the real part of the impedance of the battery pack (100) has the smallest value or a point where the real part has the smallest value. For example, the first characteristic point (210) may correspond to a point in the EIS graph where the real part of the impedance has the smallest value or a point located within a preset range from the point where the real part has the smallest value. In addition, the second characteristic point (220) may be any one of a point in the EIS graph where the imaginary part of the impedance has a value of 0 or a point having a frequency lower than a frequency corresponding to a point where the imaginary part value has 0.
[0066] According to one embodiment, the first characteristic point may be related to a point in the EIS graph where the imaginary value of the impedance of the battery pack (100) is 0. For example, the first characteristic point may correspond to a point in the EIS graph where the imaginary value of the impedance is 0 or a point located within a preset range from the point where the imaginary value is 0. In addition, the second characteristic point may be related to a point corresponding to a frequency lower than the frequency corresponding to the first characteristic point. That is, the second characteristic point may be any one of points having a frequency lower than the frequency corresponding to a point where the imaginary value of the impedance is 0 or a point located within a preset range from the point where the imaginary value is 0. Here, the preset range may be variously set and changed.
[0067] In the following, for convenience of explanation, it is assumed that the first characteristic point (210) is the point where the real value of the impedance of the battery pack (100) is the smallest, and the second characteristic point (205) is the maximum point (205) among points having a frequency smaller than the point where the imaginary value of the impedance is 0. However, the present invention is not limited to these embodiments.
[0068] 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) and the second feature point (205) and the coordinate axis of the EIS graph. In the following, for the convenience of explanation, the standard for calculating the angle parameter (230) is assumed to be the horizontal axis, but the present invention is not limited thereto.
[0069] For example, in the case of using the horizontal axis corresponding to the coordinate axis (Re(Z)) representing the real part among the coordinate axes of the EIS graph as a reference, the angle parameter (230) may include data related to the angle between the horizontal axis and the straight line (215) connecting the first feature point (210) and the second feature point (205).
[0070] As another example, when the vertical axis corresponding to the coordinate axis (Im(Z)) representing the imaginary part of the coordinate axes of the EIS graph is used as a reference, 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) and the second feature point (205).
[0071] According to an embodiment, the angle parameter calculation unit (230) can calculate the angle parameter through a calculation process utilizing the size of the impedance calculated based on the difference in impedance of each of the first feature point (210) and the second feature point (205) and various trigonometric functions, but is not limited to this example.
[0072] Referring to FIGS. 3 to 5, an EIS graph included in EIS data according to an embodiment disclosed in the present document is schematically illustrated.
[0073] As described above in the description of FIG. 1, among the plurality of characteristic points, the first characteristic point and the second characteristic point may be related to the shape of the EIS graph in the reference frequency range (220a), which is a frequency range greater than the frequency corresponding to the maximum point (220) among the plurality of points identified based on the EIS graph. Here, the EIS graphs illustrated in FIGS. 3 to 5 may each include various embodiments in which an inflection point exists in the reference frequency range (220a). First, referring to FIG. 3, an inflection point (240) exists in the reference frequency range (220a). Here, the inflection point may correspond to a point at which the shape of the EIS graph changes.
[0074] According to one embodiment, when an inflection point (240) exists in the reference frequency range (220a), the first characteristic point (210) may be associated with a point having the smallest real part value of impedance among a plurality of points identified based on the EIS graph. For example, the first characteristic point (210) may correspond to any one of the points having the smallest real part value of impedance or points located within a preset range from the point having the smallest real part value. Here, the preset range may be variously changed and applied, and may be determined, for example, as a point located within a preset range of frequencies or a preset range on the graph based on an allowable error, etc. in the process of analyzing the EIS graph, but is not limited to these examples.
[0075] According to one embodiment, when an inflection point (240) exists in the reference frequency range (220a), the second feature point (240) may be related to the inflection point (240). For example, the second feature point (240) may correspond to the inflection point (240) or may correspond to any one of the points having a frequency lower than the frequency corresponding to the inflection point (240). In the following description, for convenience of explanation, it is assumed that the first feature point (210) is the point where the real part value of the impedance is the smallest, and the second feature point (240) corresponds to the inflection point, but the present invention is not limited to such examples.
[0076] The angle parameter calculation unit (230, see FIG. 1) can calculate the angle parameter (230) 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) and the second feature point (240) and the coordinate axis of the EIS graph. In the following, for the convenience of explanation, the standard for calculating the angle parameter (230) is assumed to be the horizontal axis, but the present invention is not limited thereto.
[0077] For example, in the case of using the horizontal axis corresponding to the coordinate axis (Re(Z)) representing the real part among the coordinate axes of the EIS graph as a reference, the angle parameter (230) may include data related to the angle between the horizontal axis and the straight line (215) connecting the first feature point (210) and the second feature point (240).
[0078] As another example, when the vertical axis corresponding to the coordinate axis (Im(Z)) representing the imaginary part of the coordinate axes of the EIS graph is used as a reference, 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) and the second feature point (240).
[0079] According to an embodiment, the angle parameter calculation unit (230) can calculate the angle parameter through a calculation process utilizing the size of the impedance calculated based on the difference in impedance of each of the first feature point (210) and the second feature point (240) and various trigonometric functions, but is not limited to this example.
[0080] Referring to Fig. 4, as illustrated in Fig. 3, an inflection point (240) exists in the reference frequency range (220a). Here, the inflection point (240) may correspond to a point where the shape of the EIS graph changes.
[0081] According to one embodiment, when an inflection point (240) exists in the reference frequency domain (220a), the first characteristic point (240) may be related to the inflection point (240) among a plurality of points identified based on the EIS graph. For example, the first characteristic point (240) may correspond to any one of the inflection point (240) at which the shape of the EIS graph changes and the points located within a preset range from the inflection point (240). Here, the inflection point (240) may correspond to the inflection point (240) at which the shape of the EIS graph changes among the points corresponding to a higher frequency than the maximum point (220) among the plurality of inflection points identified on the EIS graph. In addition, the preset range may be set and applied in various ways.
[0082] According to one embodiment, when an inflection point (240) exists in the reference frequency domain (220a), the second feature point (250) may be related to the inflection point (240). For example, the second feature point (250) may correspond to any one of the points having a frequency lower than the frequency corresponding to the inflection point (240). That is, the second feature point (250) may correspond to any one of the points having a frequency lower than the first feature point (240). In the following description, for convenience of explanation, it is assumed and described that the first feature point (240) corresponds to the inflection point and the second feature point (240) corresponds to any point having a frequency lower than the inflection point, but the present invention is not limited to this example.
[0083] The angle parameter calculation unit (230, see FIG. 1) can calculate the angle parameter (230) 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) and the second feature point (250) and the coordinate axis of the EIS graph. In the following, for the convenience of explanation, the standard for calculating the angle parameter (230) is assumed to be the horizontal axis, but the present invention is not limited thereto.
[0084] For example, in the case of using the horizontal axis corresponding to the coordinate axis (Re(Z)) representing the real part among the coordinate axes of the EIS graph as a reference, the angle parameter (230) may include data related to the angle between the horizontal axis and the straight line (215) connecting the first feature point (240) and the second feature point (250).
[0085] As another example, when the vertical axis corresponding to the coordinate axis (Im(Z)) representing the imaginary part of the coordinate axes of the EIS graph is used as a reference, the angle parameter may include data related to the angle between the vertical axis and the straight line (215) connecting the first feature point (240) and the second feature point (250).
[0086] According to an embodiment, the angle parameter calculation unit (230) can calculate the angle parameter through a calculation process utilizing the size of the impedance calculated based on the difference in impedance of each of the first feature point (240) and the second feature point (250) and various trigonometric functions, but is not limited to this example.
[0087] Referring to Fig. 5, as illustrated in Fig. 3, an inflection point (240) exists in the reference frequency range (220a). Here, the inflection point (240) may correspond to a point where the shape of the EIS graph changes.
[0088] According to one embodiment, when an inflection point (240) exists in the reference frequency region (220a), the first characteristic point (210) may be associated with a point among a plurality of points identified based on the EIS graph where the imaginary value of the impedance is 0. For example, the first characteristic point (210) may correspond to any one of the points among the plurality of points identified based on the graph where the imaginary value of the impedance is 0 or points located within a preset range from the point (210) where the imaginary value of the impedance is 0. Here, the preset range may be set and applied in various ways.
[0089] According to one embodiment, when an inflection point (240) exists in the reference frequency range (220a), the second characteristic point (240) may be related to the inflection point. For example, the second characteristic point (240) may correspond to any one of the points having a frequency lower than the inflection point (240) or the frequency corresponding to the inflection point (240). Hereinafter, for convenience of explanation, the first characteristic point (210) is described as a point among a plurality of points identified based on the EIS graph where the imaginary part value of the impedance is 0, and the second characteristic point (240) corresponds to the inflection point, but is not limited to this example.
[0090] The angle parameter calculation unit (230, see FIG. 1) can calculate the angle parameter (230) 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) and the second feature point (240) and the coordinate axis of the EIS graph. In the following, for the convenience of explanation, the standard for calculating the angle parameter (230) is assumed to be the horizontal axis, but the present invention is not limited thereto.
[0091] For example, in the case of using the horizontal axis corresponding to the coordinate axis (Re(Z)) representing the real part among the coordinate axes of the EIS graph as a reference, the angle parameter (230) may include data related to the angle between the horizontal axis and the straight line (215) connecting the first feature point (210) and the second feature point (240).
[0092] As another example, when the vertical axis corresponding to the coordinate axis (Im(Z)) representing the imaginary part of the coordinate axes of the EIS graph is used as a reference, 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) and the second feature point (240).
[0093] According to an embodiment, the angle parameter calculation unit (230) can calculate the angle parameter through a calculation process utilizing the size of the impedance calculated based on the difference in impedance of each of the first feature point (210) and the second feature point (240) and various trigonometric functions, but is not limited to this example.
[0094]
[0095] FIG. 6 is a diagram for explaining relationship data according to an embodiment disclosed in this document, and FIG. 7 is a diagram for explaining a relationship between an angular parameter-temperature and an angular parameter-temperature according to an embodiment disclosed in this document.
[0096] The relationship data generation unit (250) can generate relationship data (261) as illustrated in FIG. 6. The relationship data generation unit (250) can generate relationship data (261) based on EIS data of a reference battery pack. Here, the reference battery pack may be a battery pack of the same type as the battery pack (100, see FIG. 1). According to an embodiment, the relationship data (261) may include data indicating a correspondence relationship between temperature, SOH, and angle parameters, and the relationship data (261) may be stored in the memory (260) in the form of a look-up table as illustrated in FIG. 6.
[0097] According to an embodiment, the relationship data generation unit (250) may generate relationship data (261a) between the first temperature (T1 to T5) and the angle parameters (Angle11 to Angle51) corresponding to each of the first temperatures based on the first EIS data corresponding to each of the first temperatures (T1 to T5) under the preset first condition. Here, the preset first condition may include a designated SoC condition and a designated SoH condition in a reference battery pack in an idle state.
[0098] For example, the relationship data generation unit (250) can generate relationship data (261a) by changing the temperature of the reference battery pack corresponding to the first SoH condition to the first temperature (T1 to T5) under the specified SoC condition. In addition, the relationship data generation unit (250) can generate relationship data by changing the temperature of the reference battery pack corresponding to the second SoH condition to the first temperature (T1 to T5) under the specified SoC condition.
[0099] According to an embodiment, a trend may exist between temperature and angle parameters. Referring to FIG. 4, a graph is shown between angle parameters (Angle11 to Angle51) corresponding to each of the first temperatures (T1 to T5). The relational data generation unit (250) may generate a function representing the trend between the 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).
[0100] According to an embodiment, the relationship data generation unit (250) can calculate an angular parameter corresponding to each temperature based on a function representing a trend between the temperature and the angular parameter. The relationship data generation unit (250) can supplement the relationship data (261) based on the angular parameter calculated by substituting different temperatures into the function representing the trend between the temperature and the angular parameter.
[0101] Referring back to FIG. 3, the relationship data generation unit (250) can generate relationship data (261b) between the reference SOH (the first SOH to the Nth SOH) and the angle parameters (Angle11 to Angle 1N) corresponding to each of the reference SOHs based on the second EIS data corresponding to each of the reference SOHs (the first SOH to the Nth SOH) under the preset second condition. Here, the preset second condition can include a designated SoC condition and a designated temperature condition in the reference battery pack in the resting state.
[0102] For example, the relationship data generation unit (250) can generate relationship data (261b) based on angle parameters (Angle 11 to Angle 1N) obtained by changing the SOH of the reference battery pack corresponding to the specified temperature condition (T1) to the reference SOH (the first SOH to the Nth SOH) under the specified SoC condition. In addition, the relationship data generation unit (250) can generate relationship data based on angle parameters (Angle 21 to Angle 2N) obtained by changing the SOH of the reference battery pack corresponding to the specified temperature condition (T2) to the reference SOH (the first SOH to the Nth SOH) under the specified SoC condition.
[0103] According to an embodiment, a trend may exist between the SOH and the angular parameter. Referring again to FIG. 7, a graph is shown between the reference SOH (the first SOH to the Nth SOH) corresponding to each of the angular parameters (Angle 11 to Angel 1N). The relational data generation unit (250) may generate a function representing the trend between the angular parameter and the SOH of the reference battery pack based on the angular parameter (Angle 11 to Angel 1N) and the reference SOH (the first SOH to the Nth SOH) corresponding to each of the angular parameters (Angle 11 to Angel 1N).
[0104] In an embodiment, the function representing the tendency between the angular parameter and the SOH may include a polynomial function. For example, the function representing the tendency between the angular parameter and the SOH may be expressed in the form of a linear function representing a linear relationship between the angular parameter and the SOH, but is not limited thereto.
[0105] According to an embodiment, the relational data generation unit (250) can calculate an SOH corresponding to each angular parameter based on a function indicating a tendency between the angular parameter and the SOH. The relational data generation unit (250) can supplement the relational data (261) based on the SOH calculated by substituting different angular parameters into the function indicating a tendency between the angular parameter and the SOH.
[0106] Predicting battery pack lifespan through EIS analysis requires repeatedly collecting EIS data under varying conditions (e.g., temperature, SOC, SOH). However, this process of repeatedly collecting EIS data can be time-consuming. Furthermore, measuring battery pack impedance through EIS analysis tends to take longer in the low-frequency region than in the high-frequency region.
[0107] An SOH prediction device according to an embodiment disclosed in the present document can predict the SOH of a battery pack based on a function obtained by changing conditions under which trends exist, without having to collect EIS data under various conditions (e.g., all temperatures or all SOHs). In addition, since the SOH prediction device according to an embodiment disclosed in the present document can predict the SOH based on an angular parameter between a first feature point and a second feature point, the SOH of the battery pack can be predicted without having to measure the impedance of the battery pack at a frequency lower than that of the second feature point.
[0108] FIG. 8 is a flowchart for explaining the operation of an SOH prediction device according to an embodiment disclosed in this document.
[0109] In step S801, the SOH prediction device (200, see FIG. 1) can obtain EIS data of the battery pack (100, see FIG. 1). According to an embodiment, the EIS data may include data regarding an EIS graph that divides the impedance of the battery pack (100) into real and imaginary parts.
[0110] In step S803, the SOH prediction device (200) can identify a plurality of characteristic points based on the EIS data. According to an embodiment, a first characteristic point among the plurality of characteristic points may correspond to a point in the EIS graph where the real part value of the impedance of the battery pack (100) is the smallest or a point where the imaginary part value of the impedance of the battery pack (100) is 0. In addition, a second characteristic point among the plurality of characteristic points may be any one of a local maximum point in the EIS graph and / or points having a frequency lower than a frequency corresponding to a local maximum point.
[0111] In step S805, the SOH prediction device (200) may calculate an angular parameter of the battery pack (100) based on an impedance associated with a plurality of feature points. According to an embodiment, the angular parameter may include data regarding an angle between a straight line connecting the second feature point and the first feature point and one of the coordinate axes of the EIS graph.
[0112] At step S807, the SOH prediction device (200) can predict the SOH of the battery pack (100) based on the temperature at which the EIS data was acquired, the calculated angle parameter, and the relationship data between the angle parameter and the SOH of the battery pack (100).
[0113] According to an embodiment, the relationship data may be generated based on first EIS data obtained from a reference battery pack at a specified State of Charge (SoC) condition, a specified State of Health (SoH) condition, and a first temperature in an idle period of the reference battery pack, and second EIS data obtained from a reference battery pack at a specified SoC condition, a specified temperature condition, and a first SOH in an idle period of the reference battery pack. Here, the reference battery pack may be a battery pack of the same type as the battery pack (100).
[0114] FIG. 9 is a flowchart for explaining the operation of an SOH prediction device according to an embodiment disclosed in this document.
[0115] Referring to FIG. 9, step S807 illustrated in FIG. 8 is specifically described.
[0116] In step S901, the SOH prediction device (200, see FIG. 1) can obtain first EIS data from a reference battery pack at a first temperature under a first condition, and in step S903, the SOH prediction device (200) can obtain second EIS data from a reference battery pack at a reference SOH under a second condition.
[0117] According to an embodiment, the first condition may include a specified State of Charge (SoC) condition and a specified State of Health (SoH) condition in the rest period of the reference battery pack, and the second condition may include a specified SoC condition and a specified temperature condition in the rest period of the reference battery pack.
[0118] In step S905, the SOH prediction device (200) can generate a function representing a tendency between a plurality of temperatures included in the first temperature and an angular parameter corresponding to each of the plurality of temperatures. In addition, in step S907, the SOH prediction device (200) can generate a function representing a tendency between a plurality of SOHs included in the reference SOH and an angular parameter corresponding to each of the plurality of SOHs.
[0119] In step S909, the SOH prediction device (200) can generate relationship data between temperature, angle parameter, and SOH based on each function generated in steps S905 and S907.
[0120] In the above, all components constituting the embodiments have been described as being combined or operating in combination as one. However, this is not necessarily limited to such embodiments, and within the scope of the purpose, all components may be selectively combined and operated in one or more combinations. Furthermore, terms such as "include," "comprise," or "have" described above, unless specifically stated to the contrary, imply that the corresponding component may be inherent, and therefore should be interpreted to include other components rather than excluding other components.
[0121] The above description is merely an example of the technical idea disclosed in this document, and those skilled in the art to which the embodiments disclosed in this document pertain may make various modifications and variations without departing from the essential characteristics of the embodiments disclosed in this document.
[0122] Accordingly, the embodiments disclosed in this document are intended to illustrate, rather than limit, the technical concepts disclosed in this document, and the scope of the technical concepts disclosed in this document is not limited by these embodiments. The scope of protection of the technical concepts disclosed in this document should be interpreted by the claims below, and all technical concepts within the equivalent scope should be interpreted as being included within the scope of the rights of this document.
[0123] [Explanation of symbols]
[0124] 100: Battery pack
[0125] 110, 120, 130: Battery module
[0126] 200: SOH prediction device
[0127] 210: EIS data acquisition unit
[0128] 220: Feature point identification section
[0129] 230: Angle parameter calculation unit
[0130] 240: SOH Prediction Department
[0131] 250: Relationship data generation section
[0132] 260: Memory
Claims
1. Battery pack; An EIS data acquisition unit for acquiring EIS (Electrochemical Impedance Spectroscopy) data of the above battery pack; A feature point identification unit that identifies a plurality of feature points based on the above EIS data; An angle parameter calculation unit that calculates an angle parameter related to the impedance of the battery pack based on the impedance related to the plurality of feature points; and An SOH prediction device including an SOH prediction unit that predicts an SOH corresponding to the calculated angle parameter based on relationship data between the temperature at which the EIS data is acquired, the angle parameter, and the SOH of the battery pack.
2. In paragraph 1, The above EIS data includes data regarding an EIS graph that depicts the impedance of the battery pack divided into real and imaginary parts, An SOH prediction device that is related to whether or not an inflection point exists in the EIS graph in a reference frequency range greater than a frequency corresponding to a maximum point among a plurality of points identified based on the EIS graph, wherein the first and second feature points among the plurality of feature points are identified based on the EIS graph.
3. In the second paragraph, if there is no inflection point in the reference frequency range, The above first characteristic point is related to the point with the smallest real value of impedance among the multiple points identified based on the EIS graph, The above second characteristic point is an SOH prediction device related to a point among a plurality of points identified based on the EIS graph, where the imaginary part value of the impedance is 0 or where the frequency is lower than the frequency corresponding to the point where the imaginary part value is 0.
4. In the second paragraph, if there is no inflection point in the reference frequency range, The above first characteristic point is related to a point among a plurality of points identified based on the EIS graph where the imaginary value of the impedance is 0, The above second feature point is an SOH prediction device related to a point having a frequency lower than a frequency corresponding to the first feature point among a plurality of points identified based on the EIS graph.
5. In the second paragraph, if an inflection point exists in the reference frequency range, The above first characteristic point is related to the point with the smallest real value of impedance among the multiple points identified based on the EIS graph, The above second characteristic point is an SOH prediction device related to a point having a frequency lower than the inflection point or a frequency corresponding to the inflection point among a plurality of points identified based on the EIS graph.
6. In the second paragraph, if an inflection point exists in the reference frequency range, The above first characteristic point is related to the above inflection point, The above second feature point is an SOH prediction device related to points corresponding to a frequency lower than the frequency corresponding to the inflection point.
7. In the second paragraph, if an inflection point exists in the reference frequency range, The above first characteristic point is related to a point among a plurality of points identified based on the EIS graph where the imaginary value of the impedance is 0. The above second characteristic point is an SOH prediction device related to points corresponding to the inflection point or a frequency smaller than the frequency corresponding to the inflection point.
8. In the second paragraph, the angle parameter is An SOH prediction device related to the angle between a straight line connecting the second feature point and the first feature point and one of the coordinate axes of the EIS graph.
9. In paragraph 2, An SOH prediction device wherein the EIS data includes data regarding an EIS graph shown in a frequency region corresponding to the second feature point and a frequency region greater than the frequency corresponding to the second feature point.
10. In paragraph 1, A relational data generation unit that generates the above relational data; and further comprising a memory for storing the above relationship data; The above relationship data is, An SOH prediction device 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.
11. In paragraph 10, The above-described first condition includes a specified SoC (State of Charge) condition and a specified SoH (State of Health) condition in the rest period of the reference battery pack, The above-described second condition is an SOH prediction device including a specified SoC condition and a specified temperature condition in the rest period of the reference battery pack.
12. In the 11th paragraph, the relationship data generation unit, An SOH prediction device that generates a function representing a trend between a plurality of temperatures included in the first temperature and an angular parameter corresponding to each of the plurality of temperatures based on the first EIS data.
13. In the 11th paragraph, the relationship data generation unit, An SOH prediction device that obtains angle parameters corresponding to each of a plurality of temperatures included in the first temperature and a plurality of SOHs included in the reference SOH based on the first EIS data and the second EIS data, and generates a function representing a trend between the angle parameters and the plurality of SOHs at the first temperature.
14. Step of obtaining EIS data of battery pack; A step of identifying a plurality of feature points based on the above EIS data; A step of calculating an angular parameter related to the impedance of the battery pack based on the impedance associated with the plurality of feature points; and An operating method of an SOH prediction device, comprising: a step of predicting an SOH corresponding to the calculated angle parameter based on relationship data between the temperature at which the EIS data is acquired, the angle parameter, and the SOH of the battery pack.
15. In paragraph 14, The above EIS data includes data regarding an EIS graph that divides the impedance of the battery pack into real and imaginary parts, A method of operating an SOH identification device, wherein among the plurality of characteristic points, the first characteristic point and the second characteristic point are related to whether an inflection point exists in the EIS graph in a reference frequency range greater than a frequency corresponding to a maximum point among the plurality of points identified based on the EIS graph.
16. In paragraph 15, If there is no inflection point in the above reference frequency range, The above first characteristic point is related to the point with the smallest real value of impedance among the multiple points identified based on the EIS graph, The second characteristic point is related to a point among a plurality of points identified based on the EIS graph where the imaginary value of the impedance is 0 or a point having a frequency lower than the frequency corresponding to the point where the imaginary value is 0. If an inflection point exists in the above reference frequency range, The above first characteristic point is related to the point with the smallest real value of impedance among the multiple points identified based on the EIS graph, The above second characteristic point is an operating method of an SOH identification device related to a point having a frequency lower than the inflection point or a frequency corresponding to the inflection point among a plurality of points identified based on the EIS graph.
17. In the 15th paragraph, the angle parameter is An operating method of an SOH prediction device related to an angle between a straight line connecting the second feature point and the first feature point and one of the coordinate axes of the EIS graph.
18. In paragraph 14, the relationship data is: An operating method of an SOH prediction device generated based on first EIS data obtained from a reference battery pack at a specified SoC (State of Charge) condition, a specified SoH (State of Health) condition, and a first temperature in a resting period of a reference battery pack, and second EIS data obtained from a reference battery pack at a specified SoC condition, a specified temperature condition, and a reference SOH in a resting period of the reference battery pack.
19. In the 18th paragraph, the step of predicting the SOH is: A step of generating a function representing a trend between a plurality of temperatures included in the first temperature and an angular parameter corresponding to each of the plurality of temperatures based on the first EIS data; A step of obtaining angle parameters corresponding to each of a plurality of temperatures included in the first temperature and a plurality of SOHs included in the reference SOH based on the first EIS data and the second EIS data; and A method of operating an SOH prediction device, comprising: generating a function representing a tendency between the angular parameter and the plurality of SOHs at the first temperature.