Diagnosis Method and Device for Battery Cell

Abstract

The present invention relates to a method and device for diagnosing a battery cell. In the method for diagnosing a battery cell of the present invention, a diagnosis device applies an activation waveform having a predetermined frequency to a battery cell in an activation process, performs EIS measurement during a charging stage of the activation process, calculates a slope of the reactance of the battery cell in a voltage section of a predetermined range based on the EIS measurement, and diagnoses the battery cell based on the slope.

Description

Technical Field

[0001] Cross - Reference to Related Applications This application claims the benefit of priority based on Korean Patent Application No. 10 - 2021 - 0174607, filed on Dec. 8, 2021, and all of the contents disclosed in the literature of the Korean patent application are incorporated herein by reference in their entirety.

[0002] The present invention relates to a method and apparatus for diagnosing a battery cell.

Background Art

[0003] An electric vehicle or a hybrid vehicle is a vehicle that mainly uses a battery as a power source to drive a motor, and research is actively conducted because it can be an alternative to solve the pollution and energy problems of internal combustion engine vehicles. In addition, rechargeable batteries are used in various external devices other than electric vehicles.

[0004] Among batteries, in the case of a lithium - ion battery that uses lithium ions in a redox reaction, lithium may be deposited on the electrode depending on the charging and discharging usage environment. Since lithium deposition is one of the direct causes of battery ignition problems, a diagnostic method for detecting lithium deposition is required. In particular, since it is difficult to detect lithium deposition after a battery has been manufactured and sold, a diagnostic method for detecting lithium deposition in the battery production process is required.

Summary of the Invention

Problems to be Solved by the Invention

[0005] Some embodiments of the present invention can provide a method and apparatus for diagnosing a battery cell that can detect lithium deposition in an activation process.

Means for Solving the Problems

[0006] According to an embodiment of the present invention, a method for diagnosing a battery cell may be provided. The diagnosis method may include applying an activation waveform having a predetermined frequency to the battery cell in an activation step, performing electrochemical impedance spectroscopy (EIS) measurement in a charging step of the activation step, calculating a slope of reactance of the battery cell in a predetermined voltage range based on the EIS measurement, and diagnosing the battery cell based on the slope.

[0007] According to another embodiment of the present invention, a diagnostic device for a battery cell may be provided. The diagnostic device may include a charger, an EIS measuring device, and a processor. The charger applies an activation waveform having a predetermined frequency to the battery cell in an activation step, and the EIS measuring device can perform EIS measurement in a charging step of the activation step. The processor can calculate a slope of reactance of the battery cell in a predetermined voltage range based on the EIS measurement and diagnose the battery cell based on the slope.

[0008] In an embodiment, the diagnostic device may further include a memory that stores information on the reactance slope of a normal cell and information on the reactance slope of a defective cell for each frequency. The processor acquires information on the reactance slope of a normal cell and information on the reactance slope of a defective cell corresponding to the predetermined frequency from the memory, diagnoses the battery cell as a normal cell when the slope of the reactance in the predetermined voltage range is included in the reactance slope of the normal cell, and can diagnose the battery cell as a defective cell when the slope of the reactance in the predetermined voltage range is included in the reactance slope of the defective cell.

[0009] According to another embodiment of the present invention, a computer program executed by a computing device and stored in a recording medium may be provided. The computer program causes the computing device to calculate a slope of reactance of the battery cell in a predetermined voltage range based on EIS measurement performed in a charging stage of an activation step of applying an activation waveform having a predetermined frequency to the battery cell, and to diagnose the battery cell based on the slope.

[0010] In one embodiment, the step of diagnosing the battery cell may include diagnosing the battery cell as a defective cell when the slope is less than or equal to a critical value.

[0011] In one embodiment, the critical value may be -8.2.

[0012] In one embodiment, the critical value may be -8.

[0013] In one embodiment, the predetermined frequency may be 25 Hz or less.

[0014] In one embodiment, the predetermined frequency may be 1 Hz or more and 25 Hz or less.

[0015] In one embodiment, the voltage range may include a range between 3.5 V and 3.8 V.

Advantages of the Invention

[0016] According to one embodiment, it is possible to diagnose a defective cell in which lithium precipitation has occurred based on the reactance slope.

Brief Description of the Drawings

[0017]

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Embodiments for Carrying Out the Invention

[0018] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings so that those having ordinary knowledge in the technical field to which the present invention pertains can easily implement it. However, the present invention can be realized in various different forms and is not limited to the embodiments described here. Also, in the drawings, in order to clearly explain the present invention, unnecessary parts for explanation are omitted, and similar parts throughout the specification are given similar drawing reference numerals.

[0019] When a component is referred to as being "connected to" another component, it should be understood that it can be directly connected to the other component, but other components can also be present in between. On the contrary, when a component is referred to as being "directly connected to" another component, it should be understood that no other components are present in between.

[0020] In the following description, expressions described in the singular can be interpreted as singular or plural as long as no explicit expressions such as "one" or "single" are used.

[0021] In the flowchart described with reference to the drawings, the order of operations may be changed, many operations may be combined, some operations may be divided, and specific operations may not be performed.

[0022] FIG. 1 is a drawing showing an example of a battery diagnostic device according to an embodiment of the present invention.

[0023] The battery diagnostic device 100 is connected to the battery cell 10 and diagnoses defective cells in which lithium precipitation occurs in the battery cell 10. In an embodiment, the battery diagnostic device 100 can be connected to a plurality of battery cells 10 to diagnose the plurality of battery cells 10. In an embodiment, the battery cell 10 can be a lithium battery such as a lithium ion battery or a lithium ion polymer battery, for example.

[0024] The battery diagnostic device 100 includes a charger 110, an electrochemical impedance spectroscopy (EIS) measuring device 120, and a processor 130. In an embodiment, the processor 130 can be provided by a computing device.

[0025] In one embodiment, the battery cell 10 can be manufactured by injecting an electrolytic solution into an electrode assembly including a negative electrode, a positive electrode, and a separator membrane. Such a battery cell 10 can function as a battery through activation via charge and discharge, and such a process is referred to as an activation process. The charger / discharger 110 can charge or discharge the battery cell 10 by applying an activation waveform to the battery cell 10 in the activation process. The activation waveform can be an alternating potential having a predetermined frequency. In one embodiment, the charger / discharger 110 can apply an activation waveform to the positive electrode terminal of the battery cell 10 with the negative electrode terminal of the battery cell 10 connected to the ground terminal. In one embodiment, the charger / discharger 110 has a plurality of channels to which a plurality of battery cells 10 are respectively connected, and can charge or discharge the plurality of battery cells 10 by applying an activation waveform to each of the plurality of channels.

[0026] The EIS measuring device 120 performs an EIS measurement on the battery cell 10 while the battery cell 10 is being charged or discharged. In one embodiment, the EIS measuring device 120 can perform in-situ EIS measurement. The EIS measuring device 120 measures the response of the battery cell 10 while applying an activation waveform, and measures the imaginary component of the impedance of the battery cell 10, that is, the reactance, based on the activation waveform and the response of the battery cell 10. In one embodiment, the EIS measuring device 120 can measure the alternating current response (that is, the output current) of the battery cell 10 while applying an activation waveform (alternating potential), and measure the reactance of the battery cell 10 based on the alternating potential and the output current. In one embodiment, the EIS measuring device 120 can measure the reactance of the battery cell 10 by determining the phase shift and amplitude change of the output current based on the alternating current response. Further, the EIS measuring device 120 can measure the voltage (that is, the charging voltage) of the battery cell 10 at the charging stage of the battery cell 10 while applying an activation waveform.

[0027] The processor 130 calculates the slope (change) of the reactance in a predetermined voltage range based on the measurement results of the EIS measuring device 120, and diagnoses whether the battery cell 10 is a defective cell or a normal cell based on the slope of the reactance. In one embodiment, the processor 130 can diagnose whether the battery cell 10 is a defective cell or a normal cell based on the slope of the reactance of the battery cell 10 due to the voltage of the battery cell 10 in a predetermined voltage range among the voltages of the battery cell 10 in the charging stage. In one embodiment, when the slope of the reactance of the battery cell 10 due to the voltage increase of the battery cell 10 in a predetermined voltage range is equal to or less than a critical value, the processor 130 can diagnose the battery cell 10 as a defective cell.

[0028] Next, with reference to FIGS. 2 to 19, a predetermined frequency and a predetermined voltage range used in the battery diagnostic apparatus according to an embodiment of the present invention will be described.

[0029] FIGS. 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, and 19 are drawings showing the results of analyzing the voltage and reactance of a battery cell measured in the charging stage of the activation process while changing the frequency of the activation waveform. In FIGS. 2 to 19, the horizontal axis represents voltage (mV), and the vertical axis represents reactance (mΩ).

[0030] Figure 2 shows the case where the frequency is 55.3 Hz, Figure 3 shows the case where the frequency is 43.9 Hz, Figure 4 shows the case where the frequency is 34.3 Hz, Figure 5 shows the case where the frequency is 26.7 Hz, Figure 6 shows the case where the frequency is 24.8 Hz, Figure 7 shows the case where the frequency is 22.9 Hz, Figure 8 shows the case where the frequency is 21.0 Hz, Figure 9 shows the case where the frequency is 19.1 Hz, Figure 10 shows the case where the frequency is 17.2 Hz, Figure 11 shows the case where the frequency is 15.3 Hz, Figure 12 shows the case where the frequency is 13.4 Hz, Figure 13 shows the case where the frequency is 11.4 Hz, Figure 14 shows the case where the frequency is 9.5 Hz, Figure 15 shows the case where the frequency is 7.6 Hz, Figure 16 shows the case where the frequency is 5.7 Hz, Figure 17 shows the case where the frequency is 3.8 Hz, Figure 18 shows the case where the frequency is 1.9 Hz, and Figure 19 shows the case where the frequency is 1.0 Hz.

[0031] In each of Figures 2 to 19, the first group A is a group of reactance graphs for each of a plurality of normal cells, and the second group B is a group of reactance graphs for each of a plurality of defective cells. In each of Figures 2 to 19, the reactance graphs for each of the plurality of normal cells and the plurality of defective cells overlap each other in some sections. That is, in some sections, the graphs may be difficult to distinguish from each other. However, the first group A can be distinguished in light gray and the second group B in black. On the other hand, although the boundary between the first group A and the second group B may be unclear in some voltage sections, the data required in the present invention are disclosed in Table 1 below.

[0032] According to the embodiment, in the charging voltage range between 3.5V and 3.8V shown in FIGS. 2 to 19, the reactance slope for a predetermined battery cell 10 can be calculated based on the difference between a first reactance value corresponding to 3.5V and a second reactance value corresponding to 3.8V. That is, even when the reactance value shows a graph form of rising or falling above the first reactance value or the second reactance value in the charging voltage range between 3.5V and 3.8V, the reactance slope can be calculated based on the first reactance value and the second reactance value. However, it is not limited to this, and according to various embodiments, the reactance slope can be calculated in the charging voltage range between 3.5V and 3.8V.

[0033] Referring to FIG. 2, "SL_1" can be the reactance slope for a normal cell, and "SL_2" can be the reactance slope for a defective cell. Also, the reactance slopes SL_1 and SL_2 can be graphs corresponding to the maximum value among a plurality of reactance slopes corresponding to the first group A or the second group B. However, it is not limited to this, and the reactance slopes SL_1 and SL_2 can display the minimum value or the average value among a plurality of reactance slopes corresponding to the first group A or the second group B.

[0034] Referring to FIGS. 2 to 19, in the case of a defective cell, it can be seen that the reactance decreases rapidly due to an increase in the charging voltage in a predetermined voltage range. In particular, when using an activation waveform having a predetermined frequency, it can be seen that the reactance slope due to an increase in the charging voltage of the defective cell is distinguishable from the reactance slope of the normal cell.

[0035] As shown in FIGS. 2 to 19, it can be seen that the magnitude (absolute value) of the reactance slope in the section where the charging voltage is 3.5V or more and 3.8V or less is larger than the magnitude of the reactance slope in other charging voltage ranges. Also, as shown in FIGS. 6 to 19, when using an activation waveform having a frequency of 1Hz or more and 25Hz or less, it can be seen that the magnitude of the reactance slope of the defective cell is large enough to be distinguishable from the magnitude of the reactance slope of the normal cell.

[0036] As shown on the reverse side, in FIGS. 2 to 5 and FIG. 19, when using an activation waveform having a frequency higher than 25 Hz, it can be seen that it is difficult to compare the magnitude of the reactance slope of defective cells with the magnitude of the reactance slope of normal cells.

[0037] Specifically, if the reactance slopes in the charging voltage range between 3.5 V and 3.8 V shown in FIGS. 2 to 19 are quantified, they are given as shown in Table 1. Information on the reactance slopes of normal cells and information on the reactance slopes of defective cells for each frequency as shown in Table 1 can be stored in the memory (not shown) of the battery diagnostic device (100 in FIG. 1).

[0038] Since the reactance slope of the battery cell can vary depending on the state of the battery cell, the maximum value, minimum value, and average value of the reactance slope are shown in Table 1. Specifically, for each frequency of the activation waveform, among the plurality of reactance slopes belonging to the first group A, the maximum value, minimum value, and average value are shown in Table 1. Also, for each frequency of the activation waveform, among the plurality of reactance slopes belonging to each of the second group B, the maximum value, minimum value, and average value are shown in Table 1. At this time, the first group A is a group of reactance graphs for each of a plurality of normal cells, and the second group B is a group of reactance graphs for each of a plurality of defective cells.

[0039] Referring to Table 1, when the frequency of the activation waveform is greater than 25 Hz, since the section of the reactance slope of the defective cell and the section of the reactance slope of the normal cell partially overlap, it may be difficult to distinguish between the reactance slopes of the defective cell and the normal cell. For example, when the frequency of the activation waveform is 55.3 Hz, the reactance slope of the defective cell has a value between -6.03 and -5.00, and the reactance slope of the normal cell has a value between -6.85 and -3.26. Therefore, when the reactance slope of a certain battery cell is measured to be -6.00, it is impossible to distinguish whether the battery cell is a normal cell or a defective cell. Similarly, when the frequency of the activation waveform is 26.7 Hz, the reactance slope of the defective cell has a value between -9.40 and -7.51, and the reactance slope of the normal cell has a value between -7.54 and -2.40. Therefore, when the reactance slope of a certain battery cell is measured to be -7.52, it is impossible to distinguish whether the battery cell is a normal cell or a defective cell.

[0040] However, when the frequency of the activation waveform is 25 Hz or less, since the section of the reactance slope of the defective cell and the section of the reactance slope of the normal cell do not overlap, the reactance slopes of the defective cell and the normal cell can be distinguished. For example, when the frequency of the activation waveform is 24.8 Hz, the reactance slope of the defective cell has a value between -10.86 and -8.20, and the reactance slope of the normal cell has a value between -6.91 and -2.45. Therefore, when the reactance slope of a certain battery cell is measured to be a value of -8.20 or less, the battery cell can be determined to be a defective cell. Similarly, when the frequency of the activation waveform is 1.0 Hz, 1.9 Hz, 3.6 Hz, 5.7 Hz, 7.6 Hz, 9.5 Hz, 11.4 Hz, 13.4 Hz, 15.3 Hz, 17.2 Hz, 19.1 Hz, 21 Hz or 22.9 Hz, since the section of the reactance slope of the defective cell and the section of the reactance slope of the normal cell do not overlap, the normal cell and the defective cell can be distinguished by the reactance slope.

[0041]

Table 1

[0042] As described above, when the frequency of the activation waveform is 25 Hz or less, normal cells and defective cells can be distinguished by the reactance slope in the charging voltage range between 3.5 V and 3.8 V. In particular, as shown in Table 1, when the frequency of the activation waveform is 25 Hz or less, the smallest value among the maximum values of the reactance slope in the charging voltage range between 3.5 V and 3.8 V is -8.2. Therefore, in a certain embodiment, a discharge cell with a reactance slope of -8.2, that is, a reactance slope below the critical value, can be determined as a defective cell. By setting the smallest value among the maximum values of the reactance slope as the critical value, it is possible to prevent normal cells from being determined as defective cells.

[0043] In a certain embodiment, since the minimum value of the reactance slope of normal cells is -6.91 at 24.8 Hz, the critical value can also be set to -8, which is greater than -8.2, taking into account the measurement error.

[0044] FIG. 20 is a flowchart showing an example of a diagnostic method of a battery diagnostic device according to an embodiment of the present invention.

[0045] Referring to FIG. 20, the battery diagnostic device applies an activation waveform having a predetermined frequency to the battery cell to perform an activation process (S210). In a certain embodiment, the predetermined frequency can be 25 Hz or less. In a certain embodiment, the predetermined frequency can be 1 Hz or more and 25 Hz or less. The battery diagnostic device performs EIS measurement on the battery cell in the charging stage of the activation process to measure the reactance and charging voltage of the battery cell (S220).

[0046] The battery diagnostic device calculates the reactance slope of the battery cell based on the voltage of the battery cell within a charging voltage range of a predetermined range (S230). In an embodiment, the charging voltage range of the predetermined range can be -3.5V or more and -3.8V or less. The battery diagnostic device compares the reactance slope with a critical value (S240), and when the reactance slope is less than or equal to the critical value, diagnoses the corresponding battery cell as a defective cell (S250). In an embodiment, the battery diagnostic device can diagnose the battery cell as a defective cell in which lithium precipitation has occurred. When the reactance slope is greater than the critical value, the battery diagnostic device diagnoses the battery cell as a normal cell (S260). In an embodiment, the critical value can be -8. In an embodiment, the critical value can be -8.2.

[0047] In an embodiment, the battery diagnostic device can obtain information on the reactance slope of a normal cell corresponding to a predetermined frequency and information on the reactance slope of a defective cell from the memory, and compare the calculated reactance slope with the reactance slope obtained from the memory (S240). When the calculated reactance slope is included in the reactance slope of the defective cell, the battery diagnostic device can diagnose the battery cell as a defective cell (S250). When the calculated reactance slope is included in the reactance slope of the normal cell, the battery diagnostic device can diagnose the battery cell as a normal cell (S260).

[0048] According to an embodiment described above, it is possible to diagnose a defective cell in which lithium precipitation has occurred based on the reactance slope.

[0049] In one embodiment, a computing device (or a processor) can perform operations on a computer program for executing the above-described diagnostic method. The computer program for executing the diagnostic method can be loaded into a memory. When the computer program is loaded into the memory, it can include instruction words that cause the computing device to perform the diagnostic method. In one embodiment, the computer program calculates the slope of the reactance of the battery cell in a predetermined voltage range based on the EIS measurement performed in the charging stage of the activation step in which the computing device applies an activation waveform having a predetermined frequency to the battery cell, and can be configured to execute a step of diagnosing the battery cell based on the slope.

[0050] Although the embodiments of the present invention have been described in detail above, the scope of the rights of the present invention is not limited thereto, and various modifications and improvements by those skilled in the art using the basic concept of the present invention defined in the claims also belong to the scope of the rights of the present invention.

Claims

1. A method for diagnosing a battery cell, comprising: applying an activation waveform having a predetermined frequency to the battery cell in an activation step; performing an electrochemical impedance spectroscopy (EIS) measurement in a charging stage of the activation step; calculating a slope of a reactance of the battery cell in a predetermined voltage range based on the electrochemical impedance spectroscopy (EIS) measurement; and diagnosing the battery cell based on the slope, wherein the diagnosing the battery cell includes diagnosing the battery cell as a defective cell when the slope is equal to or less than a critical value; wherein the critical value is -8.2 or -8; and wherein the predetermined frequency is equal to or greater than 13.4 Hz and equal to or less than 25 Hz.

2. The diagnosing method according to claim 1, wherein the voltage range includes a range between 3.5 V and 3.8 V.

3. A diagnosing apparatus for a battery cell, comprising: a charger that applies an activation waveform having a predetermined frequency to the battery cell in an activation step; an EIS measuring device that performs an electrochemical impedance spectroscopy (EIS) measurement in a charging stage of the activation step; and a processor that calculates a slope of a reactance of the battery cell in a predetermined voltage range based on the electrochemical impedance spectroscopy (EIS) measurement and diagnoses the battery cell based on the slope, wherein the processor diagnoses the battery cell as a defective cell when the slope is equal to or less than a critical value; wherein the critical value is -8.2 or -8; and wherein the predetermined frequency is equal to or greater than 13.4 Hz and equal to or less than 25 Hz.

4. The diagnosing apparatus according to claim 3, wherein the voltage range includes a range between 3.5 V and 3.8 V.

5. further comprising a memory that stores information on a reactance slope of a normal cell and information on a reactance slope of a defective cell for each frequency, wherein the processor: obtains information on a reactance slope of a normal cell and information on a reactance slope of a defective cell corresponding to the predetermined frequency from the memory; diagnoses the battery cell as a normal cell when the slope of the reactance in the predetermined voltage range is included in the reactance slope of the normal cell; and diagnoses the battery cell as a defective cell when the slope of the reactance in the predetermined voltage range is included in the reactance slope of the defective cell.

6. A computer program executed by a computing device and stored on a recording medium, the computer program causes the computing device to calculate the slope of the reactance of the battery cell in a predetermined voltage range based on electrochemical impedance spectroscopy (EIS) measurements performed in the charging stage of an activation step of applying an activation waveform having a predetermined frequency to the battery cell, and diagnose the battery cell based on the slope, the step of diagnosing the battery cell includes diagnosing the battery cell as a defective cell when the slope is less than or equal to a critical value, the critical value is -8.2 or -8, the predetermined frequency is 13.4 Hz or more and 25 Hz or less. A computer program.

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