Battery diagnostic device and method

Abstract

The present invention discloses a technology that can diagnose a battery with high accuracy despite using a Nyquist diagram. A battery diagnostic device according to one aspect of the present invention includes an impedance measurement module that measures impedance with respect to changes in frequency while applying an AC voltage to a target battery, a memory module that stores impedance reference values ​​for each frequency, and a processor that generates a Nyquist diagram for the impedance measurements of the target battery measured by the impedance measurement module, extracts inflection points from the generated Nyquist diagram, and compares values ​​within a predetermined frequency range centered on the extracted inflection points with the impedance reference values ​​for each frequency stored in the memory module to diagnose the target battery.

Description

[Technical field]

[0001] This application claims priority to Korean Patent Application No. 10-2020-0156002, filed on November 19, 2020, the entire contents of which are incorporated herein by reference in their entirety in the specification and drawings.

[0002] The present invention relates to a battery diagnostic technique, and more particularly to a battery diagnostic technique that can effectively diagnose the state of a battery through impedance measurements. [Background technology]

[0003] Currently, commercially available secondary batteries include nickel-cadmium batteries, nickel-metal hydride batteries, nickel-zinc batteries, and lithium secondary batteries. Of these, lithium secondary batteries are attracting attention due to the advantages they have over nickel-based secondary batteries, such as almost no memory effect, the ability to be charged and discharged freely, a very low self-discharge rate, and a high energy density.

[0004] Furthermore, secondary batteries are now widely used for driving and storing energy in medium- to large-sized devices such as electric vehicles and energy storage systems (ESS), etc. This has led to increased interest in secondary batteries, and related research and development has become more active.

[0005] In a lithium secondary battery, a lithium-based oxide and a carbon material are mainly used as a positive electrode active material and a negative electrode active material, respectively, and the lithium secondary battery includes an electrode assembly in which a positive electrode plate and a negative electrode plate, to which the positive electrode active material and the negative electrode active material are applied, are disposed with a separator sandwiched therebetween, and an exterior material, i.e., a battery case, that hermetically houses the electrode assembly together with an electrolyte.

[0006] Batteries generate electrical energy through electrochemical oxidation and reduction reactions. However, as batteries undergo repeated charge and discharge cycles, they may not continuously maintain their capacity at the time of manufacture, i.e., performance at the beginning of life (BOL), and may deteriorate over time. If the deterioration state of such a battery is not properly understood, it may be difficult to accurately predict the battery's state of charge (SOC), available time, lifespan, replacement time, etc. Furthermore, if predictions are not made accurately in this regard, unintended damage may occur to users and managers of the battery.

[0007] In recent years, there has also been an increase in the number of cases where batteries are recycled. In particular, when the performance of battery packs installed in electric vehicles deteriorates after a certain period of use, research and businesses are being actively conducted to reuse used battery packs in other applications, such as energy storage systems (ESS).

[0008] Thus, when recycling used batteries (scrap batteries) in other fields or in the same field, more accurate battery condition diagnosis is required. For example, in order to adopt an automobile battery pack in an energy storage system, it is necessary to determine whether the battery pack is recyclable or not. Various technologies have been proposed to diagnose battery cells, battery modules, battery packs, etc., but it is still difficult to say that they are performing satisfactorily in various aspects such as accuracy and speed.

[0009] In particular, one of the representative techniques for diagnosing such batteries is a method using electrochemical impedance spectroscopy (EIS). In this method, a Nyquist plot of EIS measurement data is used, and in this process, it is necessary to extract each element constant for the equivalent circuit model of the battery.

[0010] However, in the case of conventional techniques using such an equivalent circuit model, there is a limit in that a complete equivalent circuit model cannot be realized. In particular, when measuring EIS, it is difficult to distinguish the inductance and resistance components of the measurement probe and the contact resistance at the measurement point from the inductance and resistance components of the battery itself. In addition, the inductance component of the measurement probe has a large deviation (variation) for each measurement, so it has a large effect on the high frequency band, and in particular, it may have a large effect on the resistance component represented by the solid electrolyte interface (SEI: Solid Electrolyte Interphase).

[0011] Therefore, according to such conventional technology, it is difficult to ensure sufficient accuracy in battery diagnosis using the Nyquist diagram. If the battery state diagnosis is not performed accurately before reusing the battery, it may have a negative impact not only on the user who reuses the battery, but also on the device or system in which the battery is reused. Summary of the Invention [Problem to be solved by the invention]

[0012] Therefore, the present invention has been made in consideration of the above problems, and has an object to provide an apparatus and method capable of diagnosing a battery with high accuracy while using a Nyquist diagram.

[0013] Other objects and advantages of the present invention will be understood from the following description and will become more apparent from the embodiments of the present invention. Also, it will be easily understood that the objects and advantages of the present invention can be realized by the means and combinations thereof disclosed in the claims. [Means for solving the problem]

[0014] In order to achieve the above object, a battery diagnostic device according to one aspect of the present invention comprises: The battery diagnosis system includes an impedance measurement module that measures impedance according to changes in frequency while applying an AC voltage to a target battery; a memory module that stores impedance reference values ​​for each frequency; and a processor that generates a Nyquist diagram for impedance measurements of the target battery measured by the impedance measurement module, extracts an inflection point from the generated Nyquist diagram, and compares values ​​within a predetermined frequency range centered on the extracted inflection point with the impedance reference values ​​for each frequency stored in the memory module to diagnose the target battery.

[0015] Here, the processor may be configured to shift the generated Nyquist diagram so that the extracted inflection point becomes an origin, and compare the shifted Nyquist diagram with the impedance reference value for each frequency.

[0016] The processor may also be configured to diagnose the target battery using a magnitude and angle of the impedance measurement of the target battery.

[0017] Further, the memory module may be configured to store the impedance reference values ​​for each frequency in a classification for each of a plurality of battery levels, and the processor may be configured to classify the target battery level by matching the impedance measurement value of the target battery to the battery levels stored in the memory module.

[0018] Furthermore, the processor may be configured to extract, as the inflection point, a point at which a charge transfer resistance region is inflected by a diffusion resistance region in the generated Nyquist diagram.

[0019] Furthermore, the processor may be configured to extract the inflection point by searching the generated Nyquist diagram from a low frequency region in a direction toward higher frequencies.

[0020] Furthermore, the memory module may previously store preliminary frequency information relating to the inflection points.

[0021] Meanwhile, a battery pack according to another aspect of the present invention for achieving the above object includes a battery diagnostic device according to the present invention.

[0022] In accordance with another aspect of the present invention, an energy storage system includes a battery diagnostic device according to the present invention.

[0023] In order to achieve the above object, according to another aspect of the present invention, a battery diagnosis method includes the steps of: storing impedance reference values ​​for each frequency; measuring impedance due to a change in frequency while applying an AC voltage to a target battery; generating a Nyquist diagram for impedance measurement values ​​of the target battery measured in the measuring step; extracting an inflection point from the Nyquist diagram generated in the generating step; comparing impedance measurement values ​​within a predetermined frequency range centered on the inflection point extracted in the extracting step with the impedance reference values ​​for each frequency stored in the storing step; and diagnosing the target battery based on a result of the comparison in the comparing step. Effect of the Invention

[0024] According to the present invention, an effective battery diagnostic device is provided.

[0025] In particular, according to one aspect of the present invention, a battery is diagnosed using a Nyquist plot, but an equivalent circuit model is not used, so there is no need to extract various element constant values ​​related to the equivalent circuit model.

[0026] Therefore, according to this aspect of the present invention, it is possible to improve the accuracy and / or speed of battery diagnosis.

[0027] Furthermore, according to one aspect of the present invention, in the analysis of EIS measurement data, by using a low frequency range rather than a relatively high frequency range, the effects of the inductance and resistance components of the measurement probe can be minimized.

[0028] Therefore, according to this aspect of the present invention, the accuracy of battery diagnosis can be further improved.

[0029] Furthermore, the present invention can be easily applied to classifying levels (grades) of battery modules and battery packs when they are reused. [Brief description of the drawings]

[0030] The following drawings attached to this specification illustrate preferred embodiments of the present invention and, together with the detailed description of the invention described below, serve to further understand the technical ideas of the present invention. Therefore, the present invention should not be interpreted as being limited only to the matters depicted in such drawings.

[0031] [Figure 1] 1 is a block diagram illustrating a schematic configuration of a battery diagnostic device according to an embodiment of the present invention;

[0032] [Diagram 2] FIG. 2 is a schematic diagram illustrating impedance reference values ​​stored in a memory module according to an embodiment of the present invention. [Diagram 3]FIG. 2 illustrates an example of a Nyquist plot generated by a processor according to an embodiment of the present invention. [Figure 4] FIG. 4 is a diagram illustrating a schematic configuration in which an extracted inflection point is shifted to the origin with respect to the Nyquist diagram of FIG. 3. [Diagram 5] FIG. 13 is a graphical representation of magnitude and angle of impedance measurements according to one embodiment of the present invention. [Figure 6] FIG. 2 illustrates a portion of impedance reference value data stored in a memory module according to one embodiment of the present invention. [Figure 7] FIG. 11 is a diagram showing a portion of impedance reference value data stored in a memory module according to another embodiment of the present invention. [Figure 8] FIG. 1 is a diagram showing regions divided according to types of factors that affect impedance in a Nyquist diagram generated according to an embodiment of the present invention. [Figure 9] FIG. 2 is a diagram illustrating a schematic configuration in which an inflection point is extracted by a processor according to an embodiment of the present invention. [Figure 10] 2 is a flow chart illustrating a battery diagnostic method according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0033] Hereinafter, a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, the terms and words used in the specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings, but should be interpreted as having meanings and concepts that correspond to the technical ideas of the present invention, in accordance with the principle that the inventor himself can appropriately define the concepts of terms in order to best describe the invention.

[0034] Therefore, it should be understood that the embodiment described in this specification and the configurations shown in the drawings are merely the most preferred embodiment of the present invention and do not represent the entire technical idea of ​​the present invention, and that there may be various equivalents and modifications that can be substituted therefor at the time of this application.

[0035] FIG. 1 is a block diagram showing a schematic configuration of a battery diagnostic device according to an embodiment of the present invention.

[0036] Referring to FIG. 1, the battery diagnostic device according to the present invention includes an impedance measurement module 100, a memory module 200 and a processor 300.

[0037] The impedance measurement module 100 may be configured to measure impedance related to a target battery. In particular, the impedance measurement module 100 may measure the impedance of the target battery using electrochemical impedance spectroscopy (EIS). Here, the target battery refers to a battery to be diagnosed. For example, the target battery may be a battery module or a battery pack including a plurality of battery cells. Alternatively, the target battery may refer to a battery cell, i.e., one secondary battery.

[0038] The impedance measuring module 100 may be configured to apply an AC voltage to a target battery to measure the impedance of the target battery. For example, the impedance measuring module 100 may be configured to charge the target battery while applying an AC voltage and measure the internal impedance of the target battery during such charging process. In particular, the impedance measuring module 100 may be configured to apply an AC voltage while changing the frequency.

[0039] The impedance measurement module 100 may employ various impedance measurement configurations and techniques known at the time of filing of the present invention. For example, the impedance measurement module 100 may be configured to measure the internal impedance of a battery using a four-terminal pair method.

[0040] The impedance measuring module 100 may also include a plurality of components for measuring the internal impedance of a battery. For example, the impedance measuring module 100 may include a contact probe for contacting a terminal of a battery, a power supply unit for generating and supplying AC power, a power cable between the power supply unit and the contact probe, and a voltage sensor. As described above, the impedance measuring module 100 of the present invention can employ a conventionally known impedance measuring configuration, and therefore detailed description thereof will be omitted.

[0041] The memory module 200 stores an impedance reference value. Here, the impedance reference value is a value to be compared with the impedance measurement value of the target battery measured by the impedance measurement module 100, and may be stored in advance. In particular, the impedance reference value may be a value obtained in advance through multiple preliminary experiments on a reference battery having the same or similar specifications, type, characteristics, etc. as the target battery.

[0042] The impedance reference value may also be measured and stored in a manner identical or similar to the impedance measurement method used by the impedance measurement module 100. For example, the impedance reference value stored in the memory module 200 may be obtained by applying an AC voltage with the same or similar voltage magnitude and frequency as the voltage magnitude and frequency used when the impedance measurement module 100 measures the impedance of the target battery.

[0043] FIG. 2 is a schematic diagram illustrating impedance reference values ​​stored in a memory module 200 according to one embodiment of the present invention.

[0044] 2, the memory module 200 may store an impedance reference value for each frequency. That is, the memory module 200 may be configured in a form in which a predetermined frequency range is divided into a plurality of frequencies (f1, f2, f3, f4, f5, f6, f7, . . .) and impedance reference values ​​(Zre1, Zre2, Zre3, Zre4, Zre5, Zre6, Zre7, . . .) corresponding to each divided frequency are preset. For example, the memory module 200 may store in advance impedance reference values ​​corresponding to each of a plurality of frequencies included in 0.1 Hz to 10 Hz.

[0045] The memory module 200 may further store other components of the battery diagnostic device according to the present invention, such as an impedance measurement module and data and programs required for the processor 300 to execute its operations or functions.

[0046] The memory module 200 may be implemented as at least one of a flash memory type, a hard disk type, a solid state disk (SSD) type, a silicon disk drive (SDD) type, a multimedia card micro type, a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), and a programmable read-only memory (PROM), but the present invention is not necessarily limited to such a specific form of the memory module 200.

[0047] The processor 300 may be connected to the impedance measurement module 100 and configured to receive impedance measurements from the impedance measurement module. That is, when the impedance measurement module 100 measures the impedance of the target battery, the measurement result may be transmitted to the processor 300. The processor 300 may be configured to generate a Nyquist diagram (Nyquist plot) of the impedance measurements of the target battery based on the impedance measurement result thus transmitted from the impedance measurement module. In particular, the impedance measurement module 100 may measure the impedance by an EIS analysis method. Such EIS analysis data may be considered as a Nyquist plot.

[0048] FIG. 3 illustrates an example of a Nyquist plot generated by a processor 300 according to one embodiment of the present invention.

[0049] Referring to FIG. 3, a Nyquist diagram may be generated by the EIS measurement results of the target battery. In this Nyquist diagram, the horizontal axis may be the real component of impedance (Zreal), and the vertical axis may be the imaginary component of impedance (Zimag). The units of the horizontal and vertical axes may be mΩ or Ω. Each point may be an impedance measurement value corresponding to each frequency, i.e., an impedance point. Furthermore, each impedance point may have a frequency that gradually increases in the direction indicated by the arrow a1. In the Nyquist diagram, the real and imaginary values ​​of the impedance of the target battery change with the change in frequency, and the intersections between them may be displayed as points on the coordinate system, i.e., impedance points.

[0050] The processor 300 can generate such a Nyquist diagram based on the impedance measurement value transmitted from the impedance measurement module. In this case, the processor 300 can adopt a Nyquist diagram generation technique known at the time of filing of the present invention, and therefore, a detailed description thereof will be omitted in the present invention.

[0051] When the Nyquist diagram for the EIS measurement data is generated in this manner, the processor 300 may be configured to extract an inflection point from the generated Nyquist diagram. Here, an inflection point may mean a point where the direction of bending changes in the EIS Nyquist diagram. From the viewpoint of calculus, such an inflection point means a point where, when a graph of a twice differentiable function has a concave or convex shape of the function, the shape of the graph changes from an upward convex to a downward convex, or from a downward convex to an upward convex. That is, an inflection point means a point where the positive or negative (+, -) of the curvature changes in a plane curve. The processor 300 may be configured to extract such an inflection point from the EIS Nyquist diagram.

[0052] Thus, once an inflection point is extracted from the EIS Nyquist diagram, the processor 300 may select one or more values ​​that fall within a predetermined frequency range centered on the extracted inflection point. The processor 300 may further be configured to compare the selected values ​​centered on the inflection point with impedance reference values ​​for each frequency stored in the memory module 200.

[0053] For example, in the configuration of Fig. 3, when an inflection point is extracted as an impedance point indicated by f13 on the Nyquist diagram, the processor 300 may select an impedance point belonging to a portion indicated by b within a predetermined frequency range centered on the inflection point f13. In this case, the processor 300 can confirm the frequency and the impedance measurement value for each frequency for the impedance point in the portion indicated by b.

[0054] Furthermore, the processor 300 may check the impedance measurement value of the selected impedance point and the corresponding impedance reference value in the memory module 200. That is, the processor 300 may read out an impedance reference value corresponding to the same or similar frequency as the selected impedance point from the memory module 200. Furthermore, the processor 300 may compare the impedance reference value thus read out with the impedance measurement value of the selected impedance point.

[0055] For example, in the embodiment of Figure 3, if the frequencies of impedance points in region b centered around inflection point f13 correspond to frequencies f2 to f6 in the embodiment of Figure 2, the processor 300 can compare the impedance measurement values ​​of the impedance points in region b with impedance reference values, i.e. Zre2 to Zre6, corresponding to frequencies f2 to f6 of the memory module.

[0056] The processor 300 may also be configured to diagnose the target battery based on a comparison of such impedance measurements to impedance reference values.

[0057] For example, the processor 300 may diagnose that the target battery has an abnormality when the impedance measurement value falls outside the error range of the impedance reference value. In this case, the impedance reference value may be set as a reference value for determining whether an abnormality occurs in the target battery. As another example, the processor 300 may be configured to search for an impedance reference value that is the same as the impedance measurement value or within the error range. In this case, the memory module 200 may match and store various information capable of diagnosing the state of the target battery with each impedance reference value. For example, the memory module 200 may match and store battery State of Health (SOH) information with each impedance reference value. In addition, the processor 300 may diagnose the state of the target battery through information matched to the searched impedance reference value.

[0058] According to the above-mentioned configuration of the present invention, a battery can be diagnosed simply and accurately. In particular, according to the above-mentioned configuration of the present invention, when diagnosing a battery using EIS data, an equivalent circuit model for the battery is not required. Therefore, it is not necessary to extract various constant values ​​for the equivalent circuit model of the EIS Nyquist diagram in relation to the battery. Therefore, according to this aspect of the present invention, not only is the diagnosis process simple, but errors that occur in the process of extracting constant values ​​can also be eliminated. Therefore, in this case, efficient battery diagnosis using the EIS Nyquist diagram is possible.

[0059] Meanwhile, the processor 300 may selectively include or be expressed by a central processing unit (CPU), an application-specific integrated circuit (ASIC), a chipset, a logic circuit, a register, a communication modem, a data processing device, etc., as known in the art, in order to execute various control logics performed in the present invention. Also, when the control logic is realized by software, the processor 300 may be realized by a collection of program modules. In this case, the program modules may be stored in an internal memory or an external memory module 200, etc., and executed by the processor 300. The memory module 200 may be located inside or outside the processor 300, and may be connected to the processor 300 by various known means.

[0060] In particular, when the secondary battery diagnostic device according to the present invention is implemented in a form included in a battery pack, the battery pack may include a control device referred to by terms such as a microcontroller unit (MCU) or a battery management system (BMS), etc. In this case, the processor 300 may be implemented by components such as an MCU or a BMS provided in such a general battery pack.

[0061] Meanwhile, in this specification, terms such as "to perform" or "configured to perform" with respect to the operation or function of the processor 300 or the like may include the meaning of "programmed to perform."

[0062] Furthermore, when the processor 300 generates a Nyquist diagram by EIS measurement and extracts an inflection point, the processor 300 may shift the Nyquist diagram so that the extracted inflection point becomes the origin. The processor 300 may be configured to compare and analyze the Nyquist diagram in such a shifted state with an impedance reference value for each frequency. This will be described in more detail with reference to FIG. 4.

[0063] Fig. 4 is a diagram illustrating a configuration in which the extracted inflection point is shifted to the origin with respect to the Nyquist diagram of Fig. 3. However, in Fig. 4, for convenience of illustration, a part of the high frequency region is excluded from the Nyquist diagram of Fig. 3.

[0064] With reference to Fig. 4, the Nyquist diagram has been shifted so that the inflection point f13 extracted in the embodiment of Fig. 3 becomes the origin. In other words, the Nyquist diagram in Fig. 4 can be said to be a form in which the inflection point f13 is positioned at the origin by shifting the coordinate axes of the Nyquist diagram in Fig. 3 to the left and downward while maintaining the same coordinate axes.

[0065] The processor 300 may also be configured to compare impedance measurements within a given frequency, centered around the origin of such Nyquist plot, i.e., the inflection point f13, with an impedance reference value corresponding to that frequency.

[0066] According to this configuration of the present invention, the inflection point is located at the origin, so that the impedance measurement value and the impedance reference value can be compared more clearly. Furthermore, according to this embodiment, if the impedance reference value stored in the memory module 200 is stored in the form of a Nyquist diagram, the impedance measurement value and the impedance reference value can be compared more easily with the inflection point as the center. Furthermore, according to this embodiment, it is possible to more clearly and easily perform a comparison with a Nyquist diagram measured and generated at different times from the same battery, or a comparison with a Nyquist diagram measured and generated from another battery. Furthermore, according to the above embodiment, the outline of the Nyquist diagram around the inflection point can be compared and analyzed more clearly.

[0067] The processor 300 may also be configured to compare impedance measurement values ​​for a frequency region between a frequency higher by a first predetermined frequency and a frequency lower by a second predetermined frequency, centered on the extracted inflection point, with an impedance reference value. In particular, in a Nyquist diagram, impedance measurement values ​​at each frequency are indicated by impedance points. Therefore, the processor 300 may be configured to search for a predetermined number of impedance points in a high frequency direction and / or a low frequency direction from the inflection point, and compare the impedance measurement values ​​of the searched impedance points with the impedance reference value.

[0068] Here, the first and second predetermined frequencies may be configured to be the same as each other, that is, the processor 300 may be configured to search for the same number of impedance points in the high frequency direction and the low frequency direction around the extracted inflection point.

[0069] For example, in the embodiment of Fig. 4, the processor 300 may be configured to search for two impedance points in the low frequency direction and the high frequency direction, respectively, centered on the inflection point f13, and compare the impedance measurement values ​​of the searched impedance points with an impedance reference value. That is, the processor 300 may compare the impedance measurement values ​​for two points f14 and f15 in the low frequency direction (right direction) from the inflection point f13, and the impedance measurement values ​​for two points f11 and f12 in the high frequency direction (left direction) from the inflection point f13 with the impedance reference value corresponding to the same frequency as the frequency of each impedance point.

[0070] According to such a configuration of the present invention, by analyzing frequency information of the origin as well as frequency information and impedance measurement values ​​of other measurement points away from the origin, it is possible to more clearly grasp the impedance characteristics of the target battery centered on the inflection point.

[0071] The processor 300 may also be configured to diagnose the target battery using the magnitude and angle of the target battery's impedance measurements, as will be described in more detail with reference to FIG.

[0072] FIG. 5 is a graphical representation of magnitude and angle of impedance measurements according to one embodiment of the present invention.

[0073] More specifically, FIG. 5 can be said to be a diagram in which the Nyquist diagram of FIG. 4 is inverted with respect to the horizontal axis (Zreal) so that the positive imaginary part of the impedance (+Zimag) is located at the top. That is, FIG. 4 shows that the negative imaginary part of the impedance (-Zimag) is located in the first and second quadrants, whereas FIG. 5 shows that the negative imaginary part of the impedance (-Zimag) is located in the third and fourth quadrants. FIG. 5 also shows an enlarged view of a low-frequency region within a predetermined frequency range, i.e., a part of the first quadrant, centered on the origin. Therefore, FIG. 5 shows only points f14 and f15 out of the multiple impedance points.

[0074] 5, when examining point f14, which is the first point from the origin f13 in the low frequency direction (right direction), the magnitude is represented by r14 and the angle is represented by θ14. In this case, the magnitude r14 and the angle θ14 can be calculated as follows.

[0075] r14=(x14 2 +y14 2 ) 1 / 2 θ14=tan -1 (y14 / x14)

[0076] Here, x14 and y14 are respectively the x-axis component (real component of impedance) and y-axis component (imaginary component of impedance) at point f14. Similarly, the processor 300 can also calculate the magnitude r15 and angle θ15 of point f15, which is the second point from the origin f13 in the low frequency direction.

[0077] Although not shown in the figure, the processor 300 can also similarly calculate the magnitude and angle of a first point and a second point from the origin f13 in the high frequency direction (left direction).

[0078] In such an embodiment, the memory module 200 may store impedance magnitudes and angles as impedance reference values ​​corresponding to multiple frequencies, i.e., the impedance reference values ​​may also store respective magnitudes and angles for comparison by the processor 300 with the magnitudes and angles of the impedance measurements.

[0079] FIG. 6 is a diagram illustrating a portion of the impedance reference value data stored in memory module 200 according to one embodiment of the present invention.

[0080] 6, the memory module 200 stores impedance reference values ​​corresponding to a plurality of frequencies (2.154 Hz, 1.468 Hz, 1 Hz, 0.681 Hz, 0.464 Hz). In particular, the impedance reference values ​​stored in the memory module 200 have impedance magnitudes and angles for each frequency. For example, in FIG. 6, the magnitude and angle of the impedance reference value corresponding to the frequency of 1.468 Hz can be 0.39 mΩ and −141.7°, respectively. Also, the magnitude and angle of the impedance reference value corresponding to the frequency of 0.681 Hz can be 0.29 mΩ and −38.3°, respectively.

[0081] In particular, the memory module 200 may store the magnitude and angle of the impedance reference value for a specific frequency around a specific frequency, when the specific frequency is the origin. For example, as shown in Fig. 6, when a frequency point of 1 Hz is the origin, the memory module 200 may store the magnitude and angle of the impedance reference value for each of the surrounding frequencies (0.681 Hz, 0.464 Hz, 1.468 Hz, 2.154 Hz).

[0082] In such an implementation, the processor 300 may compare, at the same frequency, the magnitude and angle of the impedance measurement value of the target battery with the magnitude and angle of the impedance reference value stored in the memory module 200. The processor 300 may also diagnose the battery depending on the result of such comparison of the magnitude and angle.

[0083] In particular, the processor 300 may be configured to compare the impedance measurement value with an impedance reference value whose origin has the same frequency. For example, the impedance reference value shown in Fig. 6 is set for a case where the origin has a frequency of 1 Hz. In this case, in the embodiment of Fig. 4, when the inflection point f13 corresponds to a frequency of 1 Hz, the processor 300 may compare the impedance measurement value according to the embodiment of Fig. 4 with the impedance reference value according to the embodiment of Fig. 6 to diagnose the target battery.

[0084] More specifically, in the embodiment of Fig. 4, the points indicated by f11, f12, f14 and f15 may correspond to frequencies of 2.154 Hz, 1.468 Hz, 0.681 Hz and 0.464 Hz, respectively. In this case, the processor 300 may obtain the magnitude and angle of the impedance measurement value for each of the points f11, f12, f14 and f15, and compare the obtained magnitude and angle of each point with the magnitude and angle of the impedance reference value shown in Fig. 6. Here, the magnitude and angle of the impedance measurement value at each point may be obtained as described in the embodiment of Fig. 5.

[0085] Meanwhile, the memory module 200 may store the magnitude of impedance and the angle of impedance as impedance reference values ​​corresponding to various frequencies of the AC voltage applied by the impedance measuring module 100, i.e., corresponding to each frequency. In particular, the memory module 200 may store in advance impedance reference values ​​corresponding to all frequencies that can be used when the impedance measuring module 100 measures the impedance of the target battery. For example, when the impedance measuring module 100 is set to measure the impedance by applying an AC voltage while changing the frequency such as 2.154 Hz, 1.468 Hz, 1 Hz, 0.681 Hz, 0.464 Hz, etc., the memory module 200 may store in advance impedance reference values ​​corresponding to each of the same frequencies (2.154 Hz, 1.468 Hz, 1 Hz, 0.681 Hz, 0.464 Hz, etc.) as the set frequencies of the impedance measuring module 100.

[0086] Alternatively, the impedance measuring module 100 may be configured to change the frequency when applying the AC voltage in accordance with a frequency previously stored in the memory module 200. For example, when the impedance reference value is previously stored in the memory module 200 in the form shown in Fig. 6, the impedance measuring module 100 may be configured to apply the AC voltage while changing the frequency to 2.154 Hz, 1.468 Hz, 1 Hz, 0.681 Hz, and 0.464 Hz, and to obtain an impedance measurement value for each frequency.

[0087] In addition, in the embodiment of FIG. 6, the form of the impedance reference value centered on the case where the origin is 1 Hz is shown, but the origin may not be 1 Hz. Therefore, the memory module 200 may store the impedance reference value in the form shown in FIG. 6, or may also include data for some other cases where the origin is not 1 Hz. For example, the memory module 200 may store data on the magnitude and angle of the impedance reference value of the surrounding frequency points when the origin is 0.681 Hz or 1.468 Hz. In this case, the processor 300 may obtain impedance reference value data appropriate for the extracted inflection point from the memory module 200 depending on which frequency the extracted inflection point has, and compare the obtained impedance reference value data with the impedance measurement value.

[0088] The memory module 200 may store impedance reference values ​​for each frequency for each of a plurality of battery levels, which will be described in more detail with reference to FIG.

[0089] 7 is a diagram showing a portion of impedance reference value data stored in a memory module 200 according to another embodiment of the present invention. FIG. 7 will be described with emphasis on the differences from the embodiment of FIG.

[0090] 7, the memory module 200 stores the impedance reference values ​​for each frequency in the form of a table, and may store a plurality of tables, where each table can be considered as a group of impedance reference values ​​for each frequency corresponding to a different battery level.

[0091] More specifically, the memory module 200 may classify batteries into three battery levels, i.e., Level 1, Level 2, and Level 3, and store a group of impedance reference values ​​for each frequency for each battery level, where the frequency may be set to be the same for each battery level, and the magnitude and angle of the impedance reference value may be different for each battery level.

[0092] In such a configuration, the processor 300 may be configured to match the impedance measurements of the target battery to battery levels stored in the memory module 200. The processor 300 may also be configured to classify the level of the target battery in response to such matching.

[0093] In particular, the processor 300 may search for an impedance reference value group that is the same as or most similar to the impedance measurement value of the target battery from among the impedance reference value groups of a plurality of battery levels stored in the memory module 200, and confirm the corresponding battery level. Furthermore, the level of the target battery may be classified using the battery level thus confirmed. For example, if it is determined that the magnitude and angle of the impedance measurement value of the target battery are most similar to the magnitude and angle of the impedance reference value group set as Level 1 in FIG. 7, the processor 300 may classify the level of the target battery as Level 1. On the other hand, if it is determined that the magnitude and angle of the impedance measurement value of the target battery are most similar to the magnitude and angle of the impedance reference value group set as Level 2 or Level 3 in FIG. 7, the processor 300 may classify the level of the target battery as Level 2 or Level 3.

[0094] According to this configuration of the present invention, the level of the target battery can be effectively classified. In particular, according to this configuration of the present invention, when the battery is reused, the battery can be relatively simply and clearly classified according to the level, which is useful for determining the reusability, use, selling price, etc. of the battery. For example, this aspect of the present invention can be used to determine the use of a lithium ion battery pack that has reached the end of its life for an electric vehicle, how much life it has left, how much performance it can exhibit, etc.

[0095] In such an embodiment, various data match determination techniques known at the time of filing the present invention can be used to determine whether the impedance measurement value is the same as or similar to the impedance reference value. Furthermore, the present invention is not limited to a specific determination method, and various methods can be used to determine whether the impedance measurement value matches the impedance reference value.

[0096] In particular, the processor 300 may be configured to determine the State of Health (SOH) of the target battery according to the level of the battery. For example, in the embodiment of FIG. 7, the SOH corresponding to Level 1 may be 80%, the SOH corresponding to Level 2 may be 75%, and the SOH corresponding to Level 3 may be 70%. In this case, the processor 300 may estimate the SOH of the target battery by determining which level of impedance reference value the impedance measurement value is most similar to. In the event that it is determined that the impedance measurement value of the target battery is most similar to the impedance reference value group of Level 2, the processor 300 may estimate the SOH of the target battery as 75% corresponding to Level 2. According to such an embodiment, the processor 300 may easily grasp the SOH of the target battery.

[0097] Meanwhile, in the embodiment of FIG. 7, only three battery levels are shown, but this is merely for convenience of explanation, and the memory module 200 may store impedance reference values ​​for each frequency for four or more battery levels. In particular, the more the battery levels are subdivided, the more accurately the diagnosis and level classification of the target battery can be performed. For example, the memory module 200 may classify the SOH from 100% to 0% in 2.5% intervals, and store impedance reference value groups for each classified SOH for each frequency.

[0098] 6 and 7, the description is based on searching and comparing two impedance points in each of the high-frequency direction and the low-frequency direction with the impedance point for a frequency of 1 Hz as a reference. However, the number of impedance points compared with the origin as a reference is merely an example, and the present invention is not limited to this specific number. For example, it may be configured to compare three or four impedance points in each of the high-frequency direction and the low-frequency direction with the origin as a reference.

[0099] When a Nyquist plot of the impedance measurement value of the target battery is generated, the processor 300 may be configured to extract a point where the charge transfer resistance region is inflected by the diffusion resistance region in the generated Nyquist plot as an inflection point, which will be described in more detail with reference to FIG.

[0100] 8 is a diagram showing a Nyquist diagram generated according to an embodiment of the present invention, in which each region is divided according to the type of factor that affects the impedance. Since the basic content of FIG. 8 is the same as that of FIG. 3, the differences will be mainly described.

[0101] Referring to FIG. 8, the EIS Nyquist diagram is divided into four regions E1, E2, E3, and E4 according to factors that affect the impedance of the battery. First, the E1 region is the highest frequency band and may be determined mainly by the electrolyte resistance inside the target battery. Next, the E2 region is a frequency region lower than the E1 region but higher than the E3 region, and may be mainly affected by the solid electrolyte interphase (SEI) formed on the electrode particle surface of the target battery. Also, the E3 region is a frequency region lower than the E2 region and may be mainly affected by the charge transfer of the target battery. In particular, the E3 region may be determined by the Li-ion oxidation reaction and reduction reaction at the electrode material interface of the target battery. Such an E3 region may be called a charge transfer resistance region. Finally, the E4 region is the lowest frequency band and may be called a region mainly affected by diffusion. In particular, the E4 region may be determined by chemical diffusion due to intercalation into the inside of the particle crystal structure of the target battery. Such an E4 region can be said to be a diffusion resistor region. The memory module 200 may store information about such four regions, such as frequency information ranges, in advance.

[0102] The processor 300 may be configured to search for an inflection point in the charge transfer resistance region E3 among these four regions. In particular, in an EIS Nyquist diagram, the charge transfer resistance region E3 may be inflected by the diffusion resistance region E4. The processor 300 may extract a point at which the charge transfer resistance region E3 is inflected by the diffusion resistance region E4 as the above-mentioned inflection point. Furthermore, there may be two or more inflection points in the Nyquist diagram. In this case, the processor 300 may extract a point at which the charge transfer resistance region E3 is inflected by the diffusion resistance region E4 from the two or more inflection points, and perform the above-mentioned battery diagnosis and level classification process using the inflection point thus extracted.

[0103] For example, in the Nyquist diagram of Fig. 4, the processor 300 may extract a point f13 as a point where the charge transfer resistance region E3 is inflected by the diffusion resistance region E4. The processor 300 may also use such a point f13 as a final inflection point to diagnose the target battery.

[0104] According to the above-mentioned configuration of the present invention, when diagnosing a target battery using EIS data, the accuracy of battery diagnosis can be improved by using a low frequency region instead of a high frequency region. In particular, it can be said that a high frequency region such as the E1 region in FIG. 8 is a region that is greatly affected by the inductance and resistance components of the measurement probe. Therefore, when using a part that is greatly affected by the E1 region or an inflection point in the E1 region, the deviation becomes large and the accuracy may deteriorate. However, according to the above-mentioned embodiment, data of the E3 and E4 regions, which are low frequency regions that are not greatly affected by the E1 region, can be analyzed, and the battery can be diagnosed based on the data. Therefore, in this case, the influence of the inductance and resistance components of the measurement probe can be minimized, and the accuracy of battery diagnosis can be further improved.

[0105] The processor 300 may also be configured to extract an inflection point by searching the generated Nyquist diagram from a low frequency region in a direction toward higher frequencies. For example, the processor 300 may be configured to search for an inflection point while moving from a predetermined point on the right side of the Nyquist diagram toward the left side, as shown by the arrow a2 in the embodiment of FIG. 8. That is, the processor 300 may be configured to extract an inflection point while moving from a low frequency region to a high frequency region in the EIS Nyquist diagram.

[0106] In particular, the processor 300 may search for an inflection point while moving from the low frequency region to the high frequency region, and may extract a first inflection point that is initially searched for among the inflection points. The processor 300 may also execute the above-mentioned battery diagnosis process using the first inflection point thus searched for. In the case of a Nyquist diagram, a charge transfer resistance region and a diffusion resistance region may exist in the low frequency region as shown by E3 and E4 in FIG. 8. Therefore, the first inflection point searched for in the low frequency region may be a point where the charge transfer resistance region inflects into the diffusion resistance region.

[0107] Therefore, according to this embodiment, it is possible to easily grasp the point at which the charge transfer resistance region is inflected by the diffusion resistance region.

[0108] Such a configuration for extracting an inflection point will be described in more detail with reference to FIG.

[0109] 9 is a diagram illustrating a configuration for extracting an inflection point by a processor 300 according to an embodiment of the present invention. In particular, FIG. 9 can be said to be a graph showing an enlarged E3 region of FIG.

[0110] Referring to FIG. 9, the processor 300 can search for an inflection point by comparatively analyzing the slope of the EIS Nyquist diagram in the direction in which the frequency gradually increases, as indicated by the arrow.

[0111] More specifically, the slope for the impedance points measured at each frequency can be calculated as follows:

[0112] Slope = (EISi[i+1]-EISi[i]) / (EISr[i+1]-EISr[i])

[0113] Here, EISi[i] can be said to represent the imaginary component of impedance point i, and EISr[i] can be said to represent the real component of impedance point i.

[0114] For example, in the embodiment of FIG. 9, the processor 300 may calculate the slope C between impedance points f24 and f25 as follows:

[0115] Slope C=(EISi[f25]-EISi[f24]) / (EISr[f25]-EISr[f24])

[0116] Moreover, the processor 300 can thus obtain the gradient between each of the points, for example, between f23 and f24, between f22 and f23, between f21 and f22, etc. Furthermore, the processor 300 may extract, as an inflection point, a point where the magnitude (absolute value) of the gradient between such impedance points gradually increases in the direction of the arrow (high frequency direction) and then decreases again.

[0117] For example, in the embodiment of FIG. 9, assuming that the magnitude (absolute value) of the slope of the Nyquist diagram gradually increases from point f28 to point f23 and the slope decreases from point f23, the processor 300 may extract point f23 as an inflection point. That is, the processor 300 may extract a point where the absolute value of the slope increases and then decreases as an inflection point. Alternatively, the processor 300 may compare the change in slope while moving in the high frequency direction along the Nyquist diagram, and extract the first point where the change in slope changes from positive (+) to negative (-) as an inflection point. In particular, such an inflection point may be a point where the charge transfer resistance region inflects into the diffusion resistance region in the Nyquist diagram. In this case, the inflection point used for diagnosing and classifying the battery can be easily extracted.

[0118] In this embodiment, the processor 300 may obtain in advance information on a point at which to start searching for an inflection point on the Nyquist diagram. For example, the memory module 200 may store in advance impedance point information corresponding to a start point of the inflection point search, and the processor 300 may access the memory module 200 and check such impedance point information before extracting an inflection point. The processor 300 may be configured to search for an inflection point from the point based on the impedance point information checked through the memory module 200 in this manner.

[0119] 9, the memory module 200 may store in advance a point f27 as an impedance point for starting an inflection point search. The processor 300 may then confirm such information from the memory module 200 and search for an inflection point in a direction such as points f26, f25, f24, etc. from point f27.

[0120] Here, the impedance point information at the inflection point search start point may be frequency information. For example, the memory module 200 may store in advance frequency information corresponding to point f27 in the embodiment of Fig. 9. In this case, the processor 300 may grasp the gradient of the impedance diagram from the frequency corresponding to point f27 toward a gradually higher frequency direction and extract the inflection point.

[0121] Alternatively, the impedance point information regarding the inflection point search starting point may be information regarding the real part of the impedance. For example, the memory module 200 may store information regarding the real part of the impedance regarding the point f27 in advance.

[0122] Alternatively, the processor 300 may determine information regarding the inflection point search start point by itself, without obtaining the information from the memory module 200. In particular, the processor 300 may check minimum and maximum points from a low frequency portion toward a high frequency portion in the Nyquist diagram. The processor 300 may also be configured to extract an inflection point between the minimum and maximum points thus checked.

[0123] For example, referring to the embodiment of Fig. 8, the processor 300 may identify a portion d1 that is a minimum point and a portion d2 that is a maximum point in the Nyquist diagram, and may be configured to extract an inflection point in a region between the thus identified minimum point d1 and maximum point d2.

[0124] In this case, the point where the charge transfer resistance region is inflected by the diffusion resistance region can be easily confirmed on the Nyquist diagram.

[0125] On the other hand, the EIS Nyquist diagram may have two or more maximum and / or minimum points. In this case, the processor 300 may extract an inflection point between the maximum and / or minimum points by using the maximum and / or minimum point having the lowest frequency among the multiple maximum and / or minimum points. That is, the processor 300 may check the minimum and maximum points of the Nyquist diagram while moving in the direction indicated by the arrow a2 in the embodiment of FIG. 8, but may extract an inflection point between the minimum and maximum points that are checked first, and diagnose the battery using the extracted inflection point.

[0126] The memory module 200 may also store preliminary frequency information related to an inflection point in advance. Here, the preliminary frequency information related to an inflection point can be said to be information related to a frequency where an inflection point is estimated to exist. In particular, the memory module 200 may store, as such preliminary frequency information, information related to a frequency range where an inflection point may exist in advance.

[0127] For example, the memory module 200 may store in advance a preliminary frequency range of 0.4 Hz to 2.2 Hz as frequency information in which an inflection point may exist. In this case, the processor 300 may be configured to first search for an inflection point within such a preliminary frequency range of 0.4 Hz to 2.2 Hz.

[0128] According to such a configuration of the present invention, it is possible to reduce the range of search when the processor 300 extracts an inflection point, thereby improving the inflection point extraction speed of the processor 300 and reducing the computation load in the extraction process.

[0129] Also, the memory module 200 may store the spare frequency information in multiple stages. In this case, the processor 300 may sequentially use the spare frequency information stored in multiple stages. At this time, the order of the spare frequency information stored in multiple stages may be determined in advance. Furthermore, the processor 300 may be configured to search for the spare frequency information of the next order when an inflection point is not extracted from the searched spare frequency information of the first order after first searching for the first order frequency information from the spare frequency information stored in multiple stages.

[0130] For example, the memory module 200 may store first, second, and third spare frequency information. In this case, the first spare frequency information may be the highest priority, and the third spare frequency information may be the lowest priority. In this case, the processor 300 may first extract an inflection point within the range by referring to the first spare frequency information. Also, if an inflection point is not extracted from the first spare frequency information, the processor 300 may extract an inflection point within the range by referring to the second spare frequency information, and if an inflection point is still not extracted, the processor 300 may extract an inflection point by referring to the third spare frequency information.

[0131] According to such a configuration of the present invention, the speed and efficiency of extracting an inflection point can be further improved.

[0132] The memory module 200 may store preliminary frequency information regarding the inflection point in accordance with the magnitude of the AC voltage applied to the battery. That is, when the impedance measuring module 100 applies an AC voltage to the target battery and measures the impedance according to the change in frequency, the preliminary frequency information may be configured to change according to the magnitude of the applied AC voltage.

[0133] For example, the memory module 200 may store, as fp1, preliminary frequency information relating to a case where the impedance measuring module 100 measures the impedance of the target battery while applying an AC voltage of 0.5 V. The memory module 200 may also store, as fp2, preliminary frequency information relating to a case where the impedance measuring module 100 measures the impedance of the target battery while applying an AC voltage of 0.7 V. In this case, fp1 and fp2 may be set to different frequency values ​​or different frequency ranges.

[0134] According to this configuration of the present invention, when the processor 300 extracts an inflection point using the preliminary frequency information stored in the memory module 200, the inflection point can be extracted more effectively. In particular, the shape of the EIS Nyquist diagram may change depending on the magnitude of the applied voltage. Therefore, according to the above embodiment, the inflection point can be efficiently extracted by providing appropriate preliminary frequency information in consideration of such a change in the shape depending on the magnitude of the applied voltage.

[0135] The battery diagnostic device according to the present invention is applicable to a battery pack. That is, the battery pack according to the present invention may include the above-mentioned battery diagnostic device according to the present invention. Furthermore, the battery pack according to the present invention may further include components that are usually included in a battery pack, such as one or more secondary batteries, a battery management system (BMS), a current sensor, a relay, a fuse, and a pack case, in addition to the battery diagnostic device according to the present invention. In this case, the secondary battery included in the battery pack may be an object to be diagnosed by the battery diagnostic device according to the present invention, that is, a target battery. Furthermore, at least some of the components of the battery diagnostic device according to the present invention may be realized as conventional components included in a battery pack. For example, at least some of the functions and operations of the processor 300 of the battery diagnostic device according to the present invention may be realized by a BMS included in the battery pack.

[0136] Furthermore, the battery diagnostic device according to the present invention may be applied to an energy storage system (ESS). That is, the energy storage system according to the present invention may include the above-described battery diagnostic device according to the present invention. In particular, since an energy storage system does not require high output like an electric vehicle, it may be a representative application for recycling battery packs (waste batteries) that have been used in electric vehicles and have reached the end of their life. Before mounting such waste batteries, the energy storage system may diagnose or classify the batteries using the battery diagnostic technology according to the present invention, and then determine whether to mount the batteries and the degree of utilization.

[0137] 10 is a flow chart showing a battery diagnostic method according to an embodiment of the present invention. Each step in FIG. 10 may be executed by each component of the battery diagnostic device according to the present invention.

[0138] Referring to FIG. 10, the battery diagnosis method according to the present invention may include an impedance reference value storage step (S110), an impedance measurement step (S120), a Nyquist diagram generation step (S130), an inflection point extraction step (S140), a comparison step (S150), and a diagnosis step (S160).

[0139] The step S110 is a step of storing an impedance reference value for each frequency. For example, the step S110 may store impedance reference value information as shown in FIG. 6 or FIG. 7 by a pre-test.

[0140] The step S120 is a step of measuring impedance according to a change in frequency while applying an AC voltage to the target battery. The step S130 is a step of generating a Nyquist diagram for the impedance measurement value of the target battery measured in step S120. For example, the Nyquist diagram shown in FIG. 3 can be generated by step S130.

[0141] The step S140 is a step of extracting inflection points from the Nyquist diagram generated in step S130. For example, in step S140, the inflection points of the Nyquist diagram can be extracted as described in the embodiment of FIG.

[0142] The step S150 is a step of comparing values ​​within a predetermined frequency range centered around the inflection point extracted in the step S140 with the impedance reference values ​​for each frequency stored in the step S110.

[0143] Step S160 is a step of diagnosing the target battery based on the result of the comparison in step S150. For example, step S160 can classify the level of the target battery.

[0144] The battery diagnostic method according to the present invention can be applied in the same or similar manner to the above-mentioned battery diagnostic device, so a detailed description thereof will be omitted.

[0145] Although the present invention has been described above using limited embodiments and drawings, the present invention is not limited thereto, and it goes without saying that various modifications and variations can be made by a person having ordinary knowledge in the technical field to which the present invention pertains within the scope of the technical concept of the present invention and the scope of the claims. [Explanation of symbols]

[0146] 100 Impedance Measurement Module 200 Memory Modules 300 processors

Claims

1. an impedance measurement module that measures impedance due to frequency changes while applying an AC voltage to a target battery; a memory module that stores impedance reference values ​​for each frequency; A processor that generates a Nyquist diagram for impedance measurements of the target battery measured by the impedance measurement module, extracts an inflection point from the generated Nyquist diagram, and compares values ​​within a predetermined frequency range centered on the extracted inflection point with impedance reference values ​​for each frequency stored in the memory module to diagnose the target battery; A battery diagnostic device comprising:

2. 2 . The battery diagnostic device of claim 1 , wherein the processor shifts the generated Nyquist diagram so that the extracted inflection point becomes an origin, and compares the shifted Nyquist diagram with the impedance reference value for each frequency.

3. The battery diagnostic device according to claim 1 or 2, wherein the processor diagnoses the target battery using a magnitude and an angle of the impedance measurement value of the target battery.

4. the memory module stores the impedance reference value for each frequency in a manner that classifies the impedance reference value for each of a plurality of battery levels that indicate a grade related to the quality of the battery; 4. The battery diagnostic device according to claim 1, wherein the processor classifies the level of the target battery by matching an impedance measurement value of the target battery to battery levels stored in the memory module.

5. The battery diagnostic device according to claim 1 , wherein the processor extracts, as the inflection point, a point at which a charge transfer resistance region is inflected by a diffusion resistance region in the generated Nyquist diagram.

6. The battery diagnostic device according to claim 1 , wherein the processor extracts the inflection point by searching the generated Nyquist diagram from a low frequency region in a direction toward higher frequencies.

7. 7. The battery diagnostic device according to claim 1, wherein the memory module prestores preliminary frequency information regarding the inflection point, and the processor first searches frequencies of the preliminary frequency information to extract the inflection point.

8. A battery pack comprising the battery diagnostic device according to any one of claims 1 to 7.

9. An energy storage system comprising the battery diagnostic device according to any one of claims 1 to 7.

10. A battery diagnostic method executed by a battery diagnostic device, comprising: storing an impedance reference value for each frequency; A step of measuring impedance due to a change in frequency while applying an AC voltage to the target battery; generating a Nyquist diagram for impedance measurements of the target battery measured in the measuring step; extracting an inflection point from the Nyquist diagram generated in the generating step; A step of comparing impedance measurement values ​​within a predetermined frequency range centered on the inflection point extracted in the extracting step with impedance reference values ​​for each frequency stored in the storing step; diagnosing the target battery based on the results of the comparing step; A battery diagnostic method comprising:

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