Method for detecting connection failure of battery module, and apparatus for diagnosing battery module

Abstract

A method for detecting a connection failure of a battery module and an apparatus for diagnosing a battery module are disclosed. The apparatus for diagnosing a battery module measures a first impedance for a battery module, calculates a second impedance by summing impedances measured for each of a plurality of cell modules, and detects whether there is a connection failure of the battery module on the basis of the difference between the first impedance and the second impedance.

Description

Method for detecting battery module connection failure and battery module diagnostic device

[0001] The present invention relates to a method for detecting a connection failure in a battery module and a battery module diagnostic device, and more specifically, to a method for detecting a connection failure caused by various causes, such as a welding failure between cell modules constituting a battery module, and a device therefor.

[0002] This application was supported by the Ministry of SMEs and Startups' Regulatory Free Zone Project (Project Number: P0023243, Project Unique Number: 1425182671, Research Management Specialist Organization: Korea Institute for Advancement of Technology, Research Project Name: Verification of Driving Stability of Modified Electric Vehicles).

[0003] Electrochemical Impedance Spectroscopy (EIS) is a method for analyzing resistance characteristics by applying AC electrical signals of various frequencies to a battery and measuring its response. The time required to analyze resistance characteristics is inversely proportional to the frequency, and particularly at low frequencies (below a few Hz), analysis of resistance characteristics can take considerable time.

[0004] Another battery testing method is alternating current internal resistance (AC-IR). AC-IR typically measures the battery's response to a 1 kHz AC signal, without changing the frequency.

[0005] As battery applications expand from small devices to electric vehicles, the electrical capacity of battery systems is steadily increasing. Consequently, individual battery cells are being designed with low internal resistance and high energy capacity. As battery design trends evolve and diversify, the existing AC internal resistance measurement method, measuring at 1 kHz, struggles to accurately determine the characteristics of large-capacity batteries. Impedance spectroscopy, due to its long inspection time, struggles to meet the demands of battery measurement.

[0006] Defects in battery modules containing multiple cells can be broadly divided into defects in the cells themselves and defects in the electrical connections between cells. Conventional methods such as impedance spectroscopy and AC internal resistance measurement can only identify defects in the cells themselves, but are limited in identifying defects in the connections between cells.

[0007] The technical problem to be achieved by an embodiment of the present invention is to provide a method and device for easily identifying connection failures due to various causes, such as welding failures, in a battery module including a plurality of cell modules.

[0008] In order to achieve the above technical task, an example of a method for detecting a connection failure according to an embodiment of the present invention includes a method for detecting a connection failure of a battery module in which a plurality of cell modules are connected in series, the method comprising: a step of measuring a first impedance of the battery module; a step of calculating a second impedance by adding the impedances measured for each of the plurality of cell modules; and a step of detecting whether the battery module has a connection failure based on a difference between the first impedance and the second impedance.

[0009] In order to achieve the above technical task, an example of a battery module diagnostic device according to an embodiment of the present invention includes a first measuring unit that determines a first impedance of a battery module in which a plurality of cell modules are connected in series; a second measuring unit that determines a second impedance by adding the impedances measured for each of the plurality of cell modules; and a diagnostic unit that determines whether there is a connection failure of the battery module based on the difference between the first impedance and the second impedance.

[0010] According to an embodiment of the present invention, a connection fault between cell modules within a battery module can be quickly and accurately identified. Since the impedance measurement values ​​of each cell module and the entire battery module are used to identify a connection fault, the measured impedance values ​​can be utilized to identify the state of the battery module or cell module (e.g., State of Health (SOH), State of Charge (SOC), etc.).

[0011] FIG. 1 is a drawing showing an example of a battery module diagnostic device according to an embodiment of the present invention;

[0012] FIG. 2 is a drawing showing an example of a battery module according to an embodiment of the present invention;

[0013] FIG. 3 is a diagram illustrating an example of a method for measuring impedance of a battery module according to an embodiment of the present invention.

[0014] FIG. 4 is a flowchart illustrating an embodiment of a method for detecting a connection failure of a battery module according to an embodiment of the present invention.

[0015] FIG. 5 is a diagram illustrating an example of a method for determining impedance by frequency according to an embodiment of the present invention.

[0016] Figure 6 is a graph showing the impedance measurement values ​​of a battery module with a poor connection.

[0017] Figure 7 is a graph showing the impedance measurement values ​​of a normal battery module.

[0018] Fig. 8 is a graph showing some of the impedance measurement values ​​of Figs. 6 and 7 together.

[0019] Figure 9 is a graph showing the sum of the battery module impedance and the cell module impedance for a battery module in a normal state.

[0020] Figure 10 is a graph showing the sum of the battery module impedance and the cell module impedance for a battery module in a poor connection state.

[0021] FIG. 11 is a graph showing the distribution of the difference between the sum of the battery module impedance and the cell module impedance by frequency according to an embodiment of the present invention.

[0022] Figure 12 is a diagram showing a regression analysis graph for the distribution of impedance difference values ​​of a normal state battery module.

[0023] Figure 13 is a diagram showing a regression analysis graph for the distribution of impedance difference values ​​of a battery module in a poorly connected state, and

[0024] FIG. 14 is a diagram illustrating an example configuration of a battery module diagnostic device according to an embodiment of the present invention.

[0025] Hereinafter, a method for detecting a connection failure of a battery module and a battery module diagnostic device according to an embodiment of the present invention will be described in detail with reference to the attached drawings.

[0026] FIG. 1 is a drawing illustrating an example of a battery module diagnostic device according to an embodiment of the present invention.

[0027] Referring to Fig. 1, a battery module diagnostic device (100) (hereinafter referred to as “diagnostic device”) receives an impedance measured by applying a frequency to a battery module (110), analyzes the impedance, and outputs an electrical connection failure (140) of the battery module (110). The electrical connection failure (140) may be caused by various reasons, such as poor welding between cell modules.

[0028] The battery module (110) includes a plurality of cell modules. The cell module includes at least one battery cell connected in series and / or parallel. An example of a cell module in which two battery cells are configured in parallel is illustrated in FIG. 3. A plurality of cell modules may be connected in series or parallel to form the battery module (110). The connection between the plurality of cell modules may be made through various methods, such as welding or a busbar. An example of a battery module (110) in which a plurality of cell modules are connected by a method, such as welding, is illustrated in FIG. 2.

[0029] By applying an AC signal of a certain frequency to each of the battery module (110) and multiple cell modules within the battery module, the impedance of each cell module (i.e., cell module impedance (120)) and the impedance of the entire battery module (i.e., battery module impedance (130)) can be measured. An example of a method for measuring cell module impedance (120) and battery module impedance (130) will be reviewed again in FIG. 3.

[0030] FIG. 2 is a drawing illustrating an example of a battery module according to an embodiment of the present invention.

[0031] Referring to FIG. 2, a battery module (200, 210) includes a plurality of cell modules. The present embodiment illustrates a battery module (200) in which a plurality of cell modules are connected by welding (A, B, C, D) and a battery module (210) in which a plurality of cell modules are connected using bus bars (A', B', C', D'). A connection failure in the battery modules (200, 210) may be a connection defect such as a welding defect or a bus bar defect between the cell modules. In addition, electrical connection defects in the battery module may occur for various reasons. The present embodiment is merely an example to help understanding, and the connection between the cell modules may be made in various ways and is not limited to the present embodiment.

[0032] FIG. 3 is a diagram illustrating an example of a method for measuring impedance of a battery module according to an embodiment of the present invention.

[0033] Referring to FIG. 3, the battery module (300) is configured with a plurality of cell modules (310) connected in series. In the present embodiment, the cell module (310) includes two battery cells connected in parallel. The battery module (300) of the present embodiment is merely an example to aid understanding and may be modified in various ways depending on the embodiment.

[0034] The diagnostic device (100) measures the impedance of the entire battery module (300) and the impedance of each cell module (310) constituting the battery module. The diagnostic device (100) can measure the impedance of the battery module (300) by connecting probes to each of the two terminals (e.g., + terminal and - terminal) of the battery module (300) and applying a predefined measurement frequency to the battery module (300). In another embodiment, the diagnostic device (100) can measure the impedance for each frequency by applying a plurality of different measurement frequencies to the battery module (300). The range of the measurement frequency for impedance measurement may be variously modified depending on the embodiment. For example, the frequency used in electrochemical impedance spectroscopy may be used as the measurement frequency in the present embodiment.

[0035] The diagnostic device (100) measures the impedance of each cell module (310) constituting the battery module (300) while applying a measurement frequency to the module. For example, in the case of FIG. 2, the diagnostic device (100) can measure the impedance of each cell module by connecting probes to the positive and negative poles of each cell module (e.g., A and B, B and C, C and D in FIG. 2) and applying a measurement frequency thereto. The measurement frequency used for measuring the cell module may be the same as the measurement frequency used for measuring the battery module (300). For example, if three different measurement frequencies of F1, F2, and F3 are used for measuring the impedance of the battery module (300), three different measurement frequencies of F1, F, and F3 may also be used for measuring the impedance of each cell module.

[0036] In one embodiment, the diagnostic device (100) may connect probes to the positive and negative poles of the battery module (300) and to the positive and negative poles of each cell module (310). The diagnostic device (100) may measure the impedance of the battery module (300) and the impedance of each cell module (310) simultaneously by applying a measurement frequency. This embodiment illustrates an example in which the diagnostic device (100) includes six sensing channels in order to measure six cell modules (310) simultaneously. In another embodiment, the diagnostic device (100) may measure the impedance of the battery module and the impedance of each cell module separately.

[0037] FIG. 4 is a flowchart illustrating one embodiment of a method for identifying a connection failure of a battery module according to an embodiment of the present invention.

[0038] Referring to FIGS. 1 and 4 together, the diagnostic device (100) measures the first impedance (i.e., battery module impedance (130)) for the battery module (110) (S400). For example, the diagnostic device (100) can measure the first impedance while applying an AC signal of at least one predefined measurement frequency to the battery module (110).

[0039] The diagnostic device (100) measures the impedance (i.e., cell module impedance) of each of a plurality of cell modules connected in series within the battery module (110) and calculates the second impedance by adding them up (S410). For example, the diagnostic device (100) measures the impedance of each cell module while applying an AC signal of at least one predefined measurement frequency to each cell module, and then calculates the second impedance by adding up the impedances of each cell module. An example of calculating the second impedance by frequency is illustrated in FIG. 5.

[0040] The diagnostic device (100) determines whether there is an electrical connection failure of the battery module (110) based on the difference between the first impedance (battery module impedance) and the second impedance (sum of cell module impedances). In one embodiment, the diagnostic device (100) can determine a connection failure if the difference between the first impedance and the second impedance for each measurement frequency deviates from a predefined reference value. Alternatively, the diagnostic device (100) can determine whether there is a connection failure through statistical analysis or regression analysis of the difference between the first impedance and the second impedance for each measurement frequency. Various methods for determining whether there is a connection failure will be reviewed again in FIG. 6 and below.

[0041] FIG. 5 is a diagram illustrating an example of a method for determining impedance by frequency according to an embodiment of the present invention.

[0042] Referring to FIG. 5, the diagnostic device (100) can measure the battery module impedance (510) for each frequency by applying a plurality of predefined measurement frequencies to the battery module (500). In addition, the diagnostic device can measure the cell module impedance (520) for each frequency by applying a plurality of predefined measurement frequencies to each cell module.

[0043] For example, the diagnostic device (100) can measure the impedance of each cell module by applying a first measurement frequency to each cell module in the battery module. As in the example of FIG. 3, if the battery module (300) is composed of six cell modules (310), the diagnostic device (100) can measure six impedances (Ch1, Ch2, Ch3, Ch4, Ch5, Ch6) for the six cell modules (310) through six channels. The diagnostic device (100) calculates the second impedance C1 for the first measurement frequency by adding up all impedances of the six cell modules (Ch1+Ch2+Ch3+Ch4+Ch5+Ch6). In addition, the diagnostic device (100) applies the second measurement frequency to each cell module to obtain the impedance values ​​of the six channels and adds them to produce the second impedance C2 for the second measurement frequency. In this way, the diagnostic device (100) can obtain the second impedance (C1, C2, ... CN) for each frequency from the first measurement frequency to the Nth measurement frequency.

[0044] Fig. 6 is a graph showing the impedance measurement values ​​of a battery module with a faulty connection, and Fig. 7 is a graph showing the impedance measurement values ​​of a normal battery module. Fig. 8 is a graph showing some of the impedance measurement values ​​of Figs. 6 and 7 together.

[0045] Referring to FIGS. 6 to 8 together, cell module impedance measurement values ​​for each frequency for a battery module including six cell modules, as in FIG. 3, are illustrated. Ch1, Ch2, ... Ch6, etc. represent impedance measurement values ​​of each cell module. Looking at FIG. 8, it can be seen that there is a difference between the cell module impedance of a battery module in a normal state (FIG. 7) and the cell module impedance of a battery module in a faulty connection state (FIG. 6). This embodiment is only one example to show that there is a difference in the cell module impedance of a battery module in a normal state and a battery module in a faulty connection state, and is not limited to this embodiment. In addition, the measurement frequency range may vary depending on the embodiment, and if the type of battery module or the measurement frequency range changes, the shape of the graphs of FIGS. 6 to 8 may also change.

[0046] In one embodiment, the diagnostic device (100) can measure the cell module impedance of a target battery module to be determined to be defective and then compare it with the cell module impedance of a previously measured normal battery module to determine whether the target battery module is poorly connected. In this case, in order to determine whether the battery module is poorly connected, the cell module impedance value of a normal battery module must be known in advance.

[0047] For example, if a user inspects a battery module for a connection defect through various conventional inspection methods such as visual inspection or inspection using various other equipment, and if the connection is normal, the cell module impedance of the battery module can be measured and stored to measure the cell module impedance of the battery module in a normal state as shown in Fig. 7. Afterwards, the cell module impedance of the same battery module is measured and compared with the cell module impedance in a normal state that has been determined in advance to determine whether there is a defect.

[0048] In another embodiment, a connection failure of a battery module can be detected without prior measurement of the impedance of a battery module in a normal state, such as in FIG. 7, and this will be discussed in FIG. 9 and below.

[0049] Fig. 9 is a graph showing the sum of the battery module impedance and the cell module impedance for a battery module in a poor connection state, and Fig. 10 is a graph showing the sum of the battery module impedance and the cell module impedance for a battery module in a normal state.

[0050] Referring to FIGS. 9 and 10, there is a difference (A) between the frequency-dependent battery module impedance (i.e., frequency-dependent first impedance) and the frequency-dependent cell module impedance sum (i.e., frequency-dependent second impedance) for a battery module in a poor connection state. In addition, there is a difference (B) between the frequency-dependent battery module impedance (i.e., frequency-dependent first impedance) and the frequency-dependent cell module impedance sum (i.e., frequency-dependent second impedance) for a battery module in a normal state.

[0051] It can be seen that the impedance difference shape (A) of the battery module in a poor connection state and the impedance difference shape (B) of the battery module in a normal state are different from each other. Using these characteristics, the diagnostic device (100) can determine that there is a poor connection if the difference between the first impedance and the second impedance for each frequency deviates from a predefined reference value. For example, in the example of FIG. 5, the diagnostic device (100) can obtain the difference (B1-C1) between the first impedance and the second impedance for the first measurement frequency, and can also obtain 'B2-C2' for the second measurement frequency. In this way, the diagnostic device (100) can obtain the difference between the first impedance and the second impedance for the first to Nth measurement frequencies. The diagnostic device (100) can determine whether there is a connection failure by comparing the difference values ​​obtained for each measurement frequency with a pre-defined reference value through statistical analysis (e.g., average, variance, maximum difference, minimum difference, etc.). For example, the diagnostic device (100) can determine that there is a connection failure if the average of the difference values ​​for each measurement frequency deviates from the pre-defined reference value. The reference value can be determined in advance through various methods such as experiments and stored in the diagnostic device (100).

[0052] In another embodiment, the diagnostic device (100) can determine whether there is a connection failure by using only the difference between the first impedance and the second impedance corresponding to a section of a part of the frequency range, not the entire measurement frequency. Referring again to FIGS. 9 and 10, the degree of change in a certain section (900, 1000) where the degree of change in the imaginary value is large compared to the same real value on the Nyquist plot can be used to determine the connection failure. For example, by specifying a certain range (e.g., 2.0 to 2.2) of the real axis (Zreal), the section (900, 1000) of the frequency range to be used for determining the connection failure can be determined.

[0053] Fig. 11 is a graph illustrating the distribution of the difference between the sum of the impedance of the battery module and the impedance of the cell module by frequency according to an embodiment of the present invention. Fig. 12 is a diagram illustrating a regression analysis graph for the distribution of the difference in impedance of a battery module in a normal state, and Fig. 13 is a diagram illustrating a regression analysis graph for the distribution of the difference in impedance of a battery module in a faulty connection state.

[0054] Referring to Fig. 11, it can be seen that the distribution of the impedance difference value (= first impedance - second impedance) for a battery module in a normal state and the distribution of the impedance difference value (= first impedance - second impedance) for a battery module in a faulty connection state are different from each other. Accordingly, the diagnostic device (100) can determine that there is a faulty connection if the distribution of the impedance difference value for the battery module deviates from a predefined reference value.

[0055] Referring to FIGS. 12 and 13, the diagnostic device (100) can obtain a linear graph for the distribution of difference values ​​through linear regression analysis on the distribution of difference values ​​between the first impedance and the second impedance by frequency. FIGS. 12 and 13 illustrate the analysis results of linear regression analysis on the distribution of difference values ​​of the existing frequency impedances in some areas (900, 1000) of FIGS. 9 and 10.

[0056] The diagnostic device (100) can determine a connection failure if the slope of the linear graph is lower than a predefined reference value (e.g., 2.0), or can determine a connection failure if the coefficient of determination (R-Square) of the linear graph is higher than a predefined reference value (e.g., 0.95). The reference value for determining a connection failure can be determined in advance through various experiments, etc. For example, the distribution of impedance difference values ​​and prior regression analysis values ​​for a plurality of normal battery modules can be determined through experiments, and then the reference value within the normal range can be defined in advance and used.

[0057] FIG. 14 is a diagram illustrating an example configuration of a battery module diagnostic device according to an embodiment of the present invention.

[0058] Referring to FIG. 14, the battery module diagnostic device (100) includes a first measuring unit (1400), a second measuring unit (1410), and a diagnostic unit (1420). In one embodiment, the battery module diagnostic device (100) may be a type of computing device that receives and processes an impedance value measured by the method of FIG. 3 and may include a memory, a processor, and an input / output device. In another embodiment, the battery module may be a device that includes a measuring module that applies a frequency and measures the impedance in order to measure the battery module impedance and cell module impedance by the measuring method of FIG. 3. Hereinafter, the battery module diagnostic device will be described assuming that it includes a module that directly measures the impedance.

[0059] The first measuring unit (1400) determines the first impedance (battery module impedance) of a battery module in which multiple cell modules are connected in series. If a separate measuring module exists, the first measuring unit (1400) can receive a measured value of the battery module impedance from the separate measuring module. If the measuring module is included internally, the first measuring unit (1400) can directly measure the impedance of the battery module while applying at least one measuring frequency to the battery module.

[0060] The second measuring unit (1410) measures the cell module impedance for each of the plurality of cell modules and calculates the second impedance by adding the cell module impedances. If a separate measuring module exists, the second measuring unit (1410) can receive the cell module impedance from the separate measuring module. If the measuring module is included internally, the second measuring unit (1410) can directly determine the cell module impedance by applying at least one measuring frequency to each cell module.

[0061] The diagnostic unit (1420) determines whether there is a connection failure in the battery module based on the difference between the first impedance and the second impedance. In one embodiment, the diagnostic unit (1420) determines a linear graph through regression analysis of the difference between the first impedance and the second impedance by frequency, and if the slope or coefficient of determination of the linear graph deviates from a predefined standard, it can determine a connection failure. In addition, various examples of determining whether there is a connection failure are illustrated in FIGS. 6 to 14.

[0062] The present invention can also be implemented as computer-readable program code on a computer-readable recording medium. Computer-readable recording media include all types of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, and optical data storage devices. Furthermore, computer-readable recording media can be distributed across network-connected computer systems, allowing computer-readable code to be stored and executed in a distributed manner.

[0063] The present invention has been described above, focusing on preferred embodiments thereof. Those skilled in the art will appreciate that the present invention can be implemented in modified forms without departing from its essential characteristics. Therefore, the disclosed embodiments should be considered illustrative rather than limiting. The scope of the present invention is set forth in the claims, not the foregoing description, and all differences within the scope equivalent thereto should be construed as being encompassed by the present invention.

Claims

1. A method for identifying a connection failure in a battery module in which multiple cell modules are connected in series, A step of measuring a first impedance for the above battery module; A step of calculating a second impedance by adding the impedance measured for each of the plurality of cell modules; and A method for detecting a connection failure of a battery module, characterized by including a step of detecting whether the battery module is connected poorly based on the difference between the first impedance and the second impedance.

2. In paragraph 1, The step of measuring the first impedance includes a step of inputting a plurality of different measurement frequencies into the battery module and determining the first impedance for each measured frequency. A method for detecting a connection failure in a battery module, characterized in that the step of calculating the second impedance includes a step of determining the second impedance for each frequency by adding the measured impedances by inputting the plurality of different measurement frequencies to the plurality of cell modules, respectively.

3. In the second paragraph, the step of determining whether there is a connection failure is: A step of identifying a linear graph through regression analysis of the difference between the first impedance and the second impedance by frequency; and A method for detecting a connection failure in a battery module, characterized by including a step of determining a connection failure if the slope or coefficient of determination of the linear graph deviates from a predefined standard.

4. A first measuring unit for determining the first impedance of a battery module in which multiple cell modules are connected in series; A second measuring unit that determines a second impedance by adding the impedance measured from each of the plurality of cell modules; and A battery module diagnostic device characterized by including a diagnostic unit that determines whether there is a connection failure of the battery module based on the difference between the first impedance and the second impedance.

5. In paragraph 4, The above first measuring unit inputs a plurality of different measurement frequencies into the battery module and determines the first impedance for each measured frequency, A battery module diagnostic device characterized in that the second measuring unit inputs the plurality of different measurement frequencies to the plurality of cell modules, measures the impedances, and adds them to determine the second impedance for each frequency.

6. In paragraph 5, the diagnostic unit, A battery module diagnostic device characterized in that a linear graph is identified through regression analysis of the difference between the first impedance and the second impedance by frequency, and if the slope or coefficient of determination of the linear graph deviates from a predefined standard, a connection failure is identified.

7. A computer-readable recording medium having recorded thereon a computer program for performing the method described in paragraph 1.

Images