Battery abnormality diagnosis device and operation method thereof

Abstract

A battery abnormality diagnosis device according to one embodiment disclosed in this document may include a data acquisition unit that acquires a plurality of discharge profiles of a battery unit during a specified period of time, a data processing unit that acquires a plurality of voltage-capacity profiles that indicate the relationship between the voltage change amount and the capacity change amount of the battery unit based on the discharge profiles, a peak value acquisition unit that acquires a peak value of the battery unit during the specified period of time based on the plurality of voltage-capacity profiles, and a diagnosis unit that determines the possibility of the battery unit catching fire based on the peak value.

Description

[Technical Field]

[0001] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2023-0005734, filed on January 13, 2023, the entire contents of which are incorporated herein by reference.

[0002] SUMMARY OF THE INVENTION The embodiments disclosed herein relate to a battery abnormality diagnosis device and an operation method thereof. [Background technology]

[0003] In recent years, research and development into secondary batteries has been actively pursued. Here, secondary batteries are batteries that can be charged and discharged, and include both conventional Ni / Cd batteries, Ni / MH batteries, and more recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of having a much higher energy density than conventional Ni / Cd batteries, Ni / MH batteries, and other batteries. Furthermore, because lithium-ion batteries can be manufactured to be compact and lightweight, they are used as power sources for mobile devices. Furthermore, lithium-ion batteries have been expanding their scope of use to include power sources for electric vehicles, and are attracting attention as a next-generation energy storage medium.

[0004] Furthermore, the secondary battery can generally be used as a battery pack including a battery module in which a plurality of battery cells are connected in series and / or parallel, and can also be used as a battery rack including a plurality of battery modules and a rack frame for accommodating such battery modules.

[0005] Such battery cells, battery modules, battery packs, or battery racks can be used in a variety of devices. For example, the batteries can be used in mobile devices such as mobile phones, laptop computers, smartphones, and smart pads, as well as in fields such as electrically powered automobiles (EVs, HEVs, and PHEVs) and large-capacity energy storage systems (ESS).

[0006] Such batteries can be managed and controlled in status and operation by a battery management system (BMS), which can be included with the batteries in a device, or which can manage and control the batteries remotely from the device containing the batteries. Summary of the Invention [Problem to be solved by the invention]

[0007] If a short circuit or other type of failure occurs within the battery, the likelihood of damage to the device (e.g., EV, ESS) containing the battery may increase. Therefore, there is a need for a method that can detect abnormal battery conditions and reduce the possibility of damage to the device containing the battery.

[0008] The technical problems of the embodiments disclosed in this document are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0009] A battery abnormality diagnosis device according to one embodiment disclosed in this document may include a data acquisition unit that acquires a plurality of discharge profiles of a battery unit during a specified period of time, a data processing unit that acquires a plurality of voltage-capacity profiles that indicate the relationship between the voltage change amount and the capacity change amount of the battery unit based on the discharge profiles, a peak value acquisition unit that acquires a peak value of the battery unit during the specified period of time based on the plurality of voltage-capacity profiles, and a diagnosis unit that determines the possibility of the battery unit catching fire based on the peak value.

[0010] An operating method of a battery abnormality diagnosis device according to one embodiment disclosed herein may include the following operations: acquiring a plurality of discharge profiles of a battery unit during a specified period; acquiring a plurality of voltage-capacity profiles indicating the relationship between the voltage change amount and the capacity change amount of the battery unit based on the discharge profiles; acquiring a peak value of the battery unit during the specified period based on the plurality of voltage-capacity profiles; and determining the possibility of ignition of the battery unit based on the peak value. [Effects of the Invention]

[0011] The battery abnormality diagnosis device and its operation method according to various embodiments disclosed herein can detect the possibility of a battery ignition. The battery abnormality diagnosis device and its operating method according to various embodiments disclosed herein can provide a user with information about a battery that has been detected as having a risk of ignition.

[0012] The effects of the battery abnormality diagnosis device and its operating method disclosed in this document are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the disclosure of this document. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a block diagram of a battery abnormality diagnosis device according to an embodiment of the present disclosure. [Figure 2] 1 shows an example of a voltage-capacity profile according to an embodiment of the present disclosure. [Figure 3] 1 illustrates an example of peak values ​​during a specified period of time according to one embodiment of the present disclosure. [Figure 4] 10 illustrates an example of a polynomial for peak values ​​according to an embodiment of the present disclosure. [Figure 5] 10 illustrates another example of a polynomial of peak values ​​according to an embodiment of the present disclosure. [Figure 6]10 is a flowchart illustrating an operation method of a battery abnormality diagnosis device according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0014] Embodiments of the present invention will now be described with reference to the accompanying drawings, although it should be understood that this is not intended to limit the present invention to the particular embodiments, but rather to include various modifications, equivalents, and / or alternatives to the embodiments of the present invention.

[0015] The embodiments and terms used in this document are not intended to limit the technical features described in this document to a specific embodiment, but should be understood to include various modifications, equivalents, or alternatives of the embodiment. In connection with the description of the drawings, like reference numerals may be used for like or related components. The singular form of a noun corresponding to an item may include one or more of the said item unless the relevant context clearly dictates otherwise.

[0016] In this document, each phrase such as "A or B," "at least one of A and B," "at least one of A or B," "A, B, or C," "at least one of A, B, and C," and "at least one of A, B, or C" may include any one or all possible combinations of the items listed with that phrase. Terms such as "first," "second," "first," "second," "A," "B," "(a)," or "(b)" may be used simply to distinguish that element from other elements and do not limit that element in other respects (e.g., importance or order) unless specifically stated to the contrary.

[0017] In this document, when a (e.g., first) component is referred to as being "coupled," "coupled," or "connected" to another (e.g., second) component, with or without the terms "functionally" or "communicatively," or when a reference is made to "coupled" or "connected," this means that the component may be connected to the other component directly (e.g., by wire or wirelessly) or indirectly (e.g., through a third component).

[0018] Methods according to various embodiments disclosed herein may be provided in a computer program product. The computer program product may be traded between a seller and a buyer as a commodity. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory, CD-ROM) or distributed online (e.g., downloaded or uploaded) via an application store or directly between two user devices. In the case of online distribution, at least a portion of the computer program product may be at least temporarily stored or temporarily generated on a machine-readable storage medium such as the memory of a manufacturer's server, an application store server, or an intermediary server.

[0019] According to the embodiments disclosed herein, each of the aforementioned components (e.g., modules or programs) may include one or more entities, and some of the entities may be located separately in other components. According to the embodiments disclosed herein, one or more of the aforementioned components or operations may be omitted, or one or more other components or operations may be added. Alternatively or additionally, multiple components (e.g., modules or programs) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the respective components of the multiple components before the integration. According to the embodiments disclosed herein, operations performed by modules, programs, or other components may be performed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be performed in a different order, omitted, or one or more other operations may be added.

[0020] FIG. 1 is a block diagram of a battery abnormality diagnosis device 101 according to an embodiment of the present disclosure. FIG. 2 shows an example of a voltage-capacity profile according to an embodiment of the present disclosure. FIG. 3 shows an example of peak values ​​during a specified period according to an embodiment of the present disclosure. FIG. 4 shows an example of a polynomial of peak values ​​according to an embodiment of the present disclosure. FIG. 5 shows another example of a polynomial of peak values ​​according to an embodiment of the present disclosure.

[0021] Referring to FIG. 1, a battery abnormality diagnosis device 101 can be connected to battery units 111, 113, 115 and a user terminal 105 via wired and / or wireless connections.

[0022] In one embodiment, the connection (104) between the battery abnormality diagnosis device 101 and the battery units 111, 113, 115 may be a communication connection via a wired and / or wireless network. In one embodiment, the wired network may be based on a local area network (LAN) communication or a power line communication. In one embodiment, the wireless network may be based on a local area network (e.g., Bluetooth, WiFi (wireless fidelity), or IrDA (infrared data association)) or a wide area network (e.g., a cellular network, a 4G network, or a 5G network).

[0023] In other embodiments, the connection (104) between the battery abnormality diagnosis device 101 and the battery units 111, 113, 115 may be a connection via a communication method between devices (e.g., a bus, a GPIO (general purpose input and output), an SPI (serial peripheral interface), or a MIPI (mobile industry processor interface)).

[0024] In one embodiment, the connection (106) between the battery abnormality diagnosis device 101 and the user terminal 105 may be a communication connection via a wired and / or wireless network.

[0025] In one embodiment, each of the one or more battery units 111, 113, and 115 may be a battery cell, a battery module, a battery pack, or a battery rack. In one embodiment, each of the battery units 111, 113, and 115 may be installed in a mobile device (e.g., a mobile phone, a laptop computer, a smartphone, or a smart pad), an electric vehicle (e.g., an electric vehicle (EV), a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicle (PHEV), or a fuel cell electric vehicle (FCEV)), an energy storage system (ESS), or a battery swapping system (BSS). In this case, the battery abnormality diagnosis device 101 may be included in the mobile device (e.g., a mobile phone, a laptop computer, a smartphone, or a smart pad), an electric vehicle (e.g., an EV, a HEV, a PHEV, or a FCEV), an energy storage system (ESS), or a battery swapping system (BSS).

[0026] In one embodiment, the user terminal 105 may be a mobile device (eg, a mobile phone, a laptop computer, a smart phone, a smart pad) or a personal computer (PC).

[0027] In one embodiment, the battery abnormality diagnosis device 101 may include a communication circuit 120, a sensor 130, a memory 140, and a processor 150. According to an embodiment, the battery abnormality diagnosis device 101 shown in Fig. 2 may further include at least one component (e.g., a display, an input device, or an output device) other than the components shown in Fig. 2.

[0028] In one embodiment, the communication circuit 120 can establish a wired communication channel and / or a wireless communication channel between the battery abnormality diagnosis device 101 and the battery units 111, 113, 115 and / or the user terminal 105, and transmit and receive data with the battery units 111, 113, 115 and / or the user terminal 105 via the established communication channel.

[0029] In one embodiment, the sensor 130 may obtain a value related to the status of the battery units 111, 113, 115 of the electronic device 103. In one embodiment, the value related to the status may indicate one or more values ​​for the voltage, current, resistance, state of charge (SOC), state of health (SOH), temperature, or a combination thereof, of the battery units 111, 113, 115. Hereinafter, the value related to the status may be referred to as a "status value."

[0030] In one embodiment, memory 140 may include volatile memory and / or non-volatile memory. In one embodiment, the memory 140 can store data used by at least one component (e.g., the processor 150) of the battery abnormality diagnosis device 101. For example, the data can include software (or instructions associated therewith), input data, or output data. In one embodiment, the instructions, when executed by the processor 150, can cause the battery abnormality diagnosis device 101 to perform the operation defined by the instructions.

[0031] In one embodiment, memory 140 may include one or more pieces of software (eg, an acquisition unit 141, an identification unit 143, a diagnosis unit 145, and an anomaly handler 147).

[0032] In one embodiment, processor 150 may include a central processing unit, an application processor, a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor.

[0033] In one embodiment, the processor 150 executes software (e.g., the data processing unit 143, the peak value acquisition unit 145, and the diagnosis unit 147), can control at least one other component (e.g., a hardware or software component) of the battery abnormality diagnosis device 101 connected to the processor 150, and can perform various data processing or calculations.

[0034] Hereinafter, a method for diagnosing abnormalities in battery units 111, 113, and 115 by battery abnormality diagnostic device 101 via data acquisition section 141, data processing section 143, peak value acquisition section 145, and diagnosis section 147 will be described with reference to FIGS.

[0035] In one embodiment, the data acquisition unit 141 can acquire discharge profiles of the multiple battery units 111, 113, and 115. In one embodiment, the discharge profile can indicate the relationship between the voltage (e.g., OCV (open circuit voltage)) and SOC (or charge, current) of a battery unit (e.g., battery unit 111).

[0036] In one embodiment, the data acquisition unit 141 can acquire the discharge profile from the plurality of battery units 111, 113, 115 connected via a wired and / or wireless network. In another embodiment, the data acquisition unit 141 can acquire the voltage, current, temperature, or a combination thereof of the plurality of battery units 111, 113, 115 using a sensor 130, and generate the discharge profile based on the acquired voltage, current, temperature, or a combination thereof.

[0037] In one embodiment, the data acquisition unit 141 may acquire multiple discharge profiles for each of the battery units 111, 113, and 115 during a specified period. Here, the specified period may be one day or more. The multiple discharge profiles for each of the battery units 111, 113, and 115 may be acquired during different periods. For example, the multiple discharge profiles for each of the battery units 111, 113, and 115 may be acquired on different dates.

[0038] In one embodiment, the data acquisition unit 141 can acquire multiple discharge profiles for each of the multiple battery units 111, 113, and 115 during a specified period according to the discharge profile acquisition cycle. For example, if the specified period is 30 days and the discharge profile acquisition cycle is 1 day, the data acquisition unit 141 can acquire 30 discharge profiles for each of the multiple battery units 111, 113, and 115.

[0039] In one embodiment, the data processing unit 143 can acquire a voltage-capacity profile that indicates the relationship between the amount of change in voltage and the amount of change in capacity of a battery unit (e.g., battery unit 111) based on the discharge profile. In one embodiment, the data processing unit 143 can acquire the voltage-capacity profile by differentiating the discharge profile of the battery unit (e.g., battery unit 111). Here, the data processing unit 143 can acquire the voltage-capacity profile by acquiring the amount of minute change (dV) in voltage (V) relative to the amount of minute change (dQ) in charge (Q) from the discharge profile of the battery unit (e.g., battery unit 111).

[0040] In one embodiment, the data processing unit 143 can obtain a voltage-capacity profile by obtaining a differential value (dV / dQ) for each SOC section. Fig. 2 illustrates an example of a voltage-capacity profile 200 obtained by the data processing unit 143 from a discharge profile obtained at a certain point in time.

[0041] In one embodiment, the data processing unit 143 can acquire a voltage-capacity profile for each of the multiple discharge profiles of the multiple battery units 111, 113, and 115. In one embodiment, the data processing unit 143 can process each discharge profile into a voltage-capacity profile. As a result, if 30 discharge profiles are acquired for each of the multiple battery units 111, 113, and 115, the data processing unit 143 can acquire 30 voltage-capacity profiles.

[0042] In one embodiment, the peak value acquisition unit 145 may acquire a peak value of a battery unit (e.g., the battery unit 111) based on a plurality of voltage-capacity profiles of the battery unit. In one embodiment, the peak value of the battery unit may be acquired from a voltage-capacity profile according to each discharge profile acquired during the specified period. Here, the peak value may be a local maximum value of the voltage-capacity profile.

[0043] In one embodiment, the peak value acquiring unit 145 can acquire one peak value from one or more peak values ​​from each of a plurality of voltage-capacity profiles of a battery unit (e.g., battery unit 111). For example, if 30 voltage-capacity profiles are acquired for each of the plurality of battery units 111, 113, and 115, the peak value acquiring unit 145 can acquire 30 peak values.

[0044] In one embodiment, the peak value acquisition unit 145 may acquire one peak value from one or more peak values ​​from each of the plurality of voltage-capacity profiles based on a peak value selection criterion. For example, the peak value acquisition unit 145 may acquire a peak value adjacent to a designated capacity from one or more candidate peak values ​​from each of the plurality of voltage-capacity profiles. Here, the designated capacity may correspond to a capacity at which the SOC is 100%.

[0045] 2, the voltage-capacity profile 200 may include one or more peak values ​​210, 220. The peak value acquisition unit 145 may select the peak value 220 adjacent to 100% SOC from the one or more peak values ​​210, 220.

[0046] In one embodiment, the diagnosis unit 147 can determine the possibility of a battery unit (for example, the battery unit 111) catching fire based on the peak value. In one embodiment, the diagnosis unit 147 can determine a polynomial (or coefficients of the polynomial) indicating a peak value of a battery unit (e.g., battery unit 111) based on a regression analysis algorithm. In one embodiment, the diagnosis unit 147 can determine the possibility of a battery unit (e.g., battery unit 111) catching fire using the determined polynomial. For example, the specified polynomial can be a cubic polynomial.

[0047] Referring to Figure 3, lines 310, 320, and 330 may represent peak values ​​of each of the battery units 111, 113, and 115 during a specified period. In one embodiment, the diagnostic unit 147 may determine a polynomial by performing a regression analysis on the lines 310, 320, and 330. Referring to Figure 4, lines 410, 420, and 430 may represent polynomials determined based on the lines 310, 320, and 330.

[0048] In one embodiment, the diagnosis unit 147 may correct a determined polynomial by setting the initial value of the polynomial to a specified value. Referring to Figure 5, lines 510, 520, and 530 may represent lines obtained by moving the initial values ​​of lines 410, 420, and 430 to the specified values.

[0049] In one embodiment, the diagnosis unit 147 can determine the likelihood of a battery unit (e.g., battery unit 111) igniting using the modified polynomial. For example, the specified polynomial may be a cubic polynomial. Here, the specified value may be an initial value (e.g., 0) of a reference polynomial. Here, the reference polynomial may be a polynomial experimentally obtained in advance to determine the likelihood of a battery unit igniting. Line 540 in FIG. 5 may be a line representing the reference polynomial. In an embodiment, line 540 can be obtained from line 440 representing a polynomial obtained by performing regression analysis on line 340 representing the peak value of a battery unit that has not ignited.

[0050] In one embodiment, the diagnosis unit 147 can determine that the battery unit (e.g., battery unit 111) has a high likelihood of ignition if a value during a specified time period identified according to a modified polynomial of the battery unit is higher than a value during a specified time period identified according to a reference polynomial. For example, when the modified polynomial is F1 and the reference polynomial is F2, the diagnosis unit 147 can determine that the battery unit has a high likelihood of ignition if F1-F2 is greater than or equal to 0 during the specified time period. As another example, the diagnosis unit 147 can determine that the battery unit has a low likelihood of ignition if there is one or more time points during the specified time period where F1-F2 is less than 0. The battery abnormality diagnosis device 101 according to the embodiment described above can detect the possibility of a battery unit catching fire.

[0051] In another embodiment, the diagnosis unit 147 may determine the amount of change in the peak value during the specified period, compare the amount of change in the battery unit with a reference amount of change, and determine the likelihood of the battery unit catching fire. Here, the amount of change may be the amount of change in the peak value from an initial point in time to a current point in time. Here, the reference amount of change may be a change amount experimentally obtained in advance to determine the likelihood of the battery unit catching fire. For example, line 340 in FIG. 3 may be a line indicating the reference amount of change.

[0052] For example, when the amount of change is V1 and the reference amount of change is V2, if V1-V2 is equal to or greater than 0 during a specified time, the diagnosis unit 147 can determine that the battery unit is highly likely to ignite. As another example, if there is one or more time points during a specified time where V1-V2 is less than 0, the diagnosis unit 147 can determine that the battery unit is highly unlikely to ignite.

[0053] 6 is a flowchart showing an operation method of the battery abnormality diagnosis device 101 according to an embodiment of the present disclosure. FIG. 6 will be described with reference to the configuration of FIG. 6, in operation 610, the battery abnormality diagnosis device 101 can acquire a discharge profile. In one embodiment, the battery abnormality diagnosis device 101 can acquire a plurality of discharge profiles during a specified period for each of the plurality of battery units 111, 113, and 115. In one embodiment, the discharge profile can indicate the relationship between the voltage (e.g., OCV (open circuit voltage)) and SOC (or charge, current) of a battery unit (e.g., battery unit 111).

[0054] In operation 620, the battery abnormality diagnosis device 101 can acquire a voltage change amount-capacity change amount profile. In one embodiment, the battery abnormality diagnosis device 101 can acquire a voltage-capacity profile that indicates the relationship between the voltage change amount and the capacity change amount of a battery unit (e.g., the battery unit 111) based on the discharge profile. Here, the battery abnormality diagnosis device 101 can acquire the voltage-capacity profile by acquiring the minute change amount (dV) of voltage (V) relative to the minute change amount (dQ) of charge (Q) from the discharge profile of the battery unit (e.g., the battery unit 111).

[0055] In operation 630, the battery abnormality diagnosis device 101 can acquire a peak value. In one embodiment, the battery abnormality diagnosis device 101 can acquire a peak value of a battery unit (e.g., battery unit 111) based on a plurality of voltage-capacity profiles of the battery unit. In one embodiment, the peak value of the battery unit can be acquired from a voltage-capacity profile according to each discharge profile acquired during the specified period. Here, the peak value may be a local maximum value of the voltage-capacity profile.

[0056] In operation 640, the battery abnormality diagnosis device 101 can determine the possibility of fire based on the peak value. In one embodiment, the battery abnormality diagnosis device 101 can determine a polynomial (or coefficients of the polynomial) indicating a peak value of a battery unit (e.g., battery unit 111) based on a regression analysis algorithm. In one embodiment, the battery abnormality diagnosis device 101 can determine the possibility of a battery unit (e.g., battery unit 111) catching fire using the determined polynomial. For example, the specified polynomial may be a cubic expression.

[0057] In one embodiment, the battery abnormality diagnosis device 101 can correct a determined polynomial by setting an initial value of the polynomial to a specified value. In one embodiment, the battery abnormality diagnosis device 101 can determine the possibility of a battery unit (e.g., battery unit 111) catching fire using the corrected polynomial.

[0058] In one embodiment, the battery abnormality diagnosis device 101 can determine that the battery unit (e.g., battery unit 111) has a high likelihood of ignition if a value during a specified time period identified according to a modified polynomial of the battery unit is higher than a value during a specified time period identified according to a reference polynomial. For example, when the modified polynomial is F1 and the reference polynomial is F2, if F1-F2 is greater than or equal to 0 during a specified time period, the battery abnormality diagnosis device 101 can determine that the battery unit has a high likelihood of ignition. As another example, if there is one or more time periods during a specified time period where F1-F2 is less than 0, the battery abnormality diagnosis device 101 can determine that the battery unit has a low likelihood of ignition.

[0059] In another embodiment, the battery abnormality diagnosis device 101 determines the amount of change in the peak value during the specified period, compares the amount of change in the battery unit with a reference amount of change, and determines the possibility of ignition of the battery unit. Here, the amount of change may be the amount of change in the peak value from an initial point in time to a current point in time.

Claims

1. a data acquisition unit that acquires a plurality of discharge profiles of the battery unit during a specified period; a data processing unit that acquires a plurality of voltage-capacity profiles that indicate the relationship between the voltage change amount and the capacity change amount of the battery unit based on the discharge profile; a peak value acquisition unit that acquires a peak value of the battery unit during the specified period based on the plurality of voltage-capacity profiles; a diagnosis unit that determines the possibility of ignition of the battery unit based on the peak value; Including, The peak value is a peak value adjacent to a specified capacity among two or more candidate peak values ​​identified from each of the plurality of voltage-capacity profiles.

2. The diagnostic unit determining a change in the peak value during the specified period; The battery abnormality diagnosis device according to claim 1 , wherein the change amount of the battery unit is compared with a reference change amount to determine the possibility of the battery unit catching fire.

3. 3. The battery abnormality diagnosis device according to claim 2, wherein the reference change amount is determined by a change amount of a peak value of a reference battery unit.

4. The diagnostic unit determining coefficients of a specified polynomial based on the peak value during the specified period; The battery abnormality diagnosis device according to claim 1 , wherein the possibility of the battery unit catching fire is determined based on the specified polynomial in which the coefficients are determined.

5. The diagnostic unit The battery abnormality diagnosis device according to claim 4 , wherein the specified polynomial, the coefficients of which are determined for the battery unit, is compared with a reference polynomial to determine the possibility of ignition of the battery unit.

6. 6. The battery abnormality diagnosis device according to claim 5, wherein the specified polynomial is a cubic polynomial.

7. 6. The battery abnormality diagnosis device according to claim 5, wherein an initial value of the specified polynomial is 0.

8. The battery abnormality diagnosis device according to claim 1 , wherein the battery unit is any one of a battery cell, a battery module, a battery pack, and a battery rack.

9. obtaining a plurality of discharge profiles for a specified period of time of the battery unit; an operation of acquiring a plurality of voltage-capacity profiles that indicate a relationship between a voltage change amount and a capacity change amount of the battery unit based on the discharge profile; obtaining a peak value of the battery unit during the specified period based on the plurality of voltage-capacity profiles; an operation of determining the possibility of ignition of the battery unit based on the peak value; Including, The method for operating a battery abnormality diagnosis device, wherein the peak value is a peak value adjacent to a specified capacity among two or more candidate peak values ​​identified from each of the plurality of voltage-capacity profiles.

10. The operation of determining the possibility of ignition includes: determining a change in the peak value during the specified period; The operating method according to claim 9 , further comprising: comparing the amount of change in the battery unit with a reference amount of change to determine the possibility of ignition of the battery unit.

11. The operating method of claim 10 , wherein the reference variation is determined by a variation of a peak value of a reference battery unit.

12. The operation of determining the possibility of ignition includes: determining a change in the peak value during the specified period; determining coefficients of a designated polynomial based on the amount of change in the battery unit; The operating method according to claim 9 , further comprising: determining the likelihood of the battery unit catching fire based on the specified polynomial whose coefficients have been determined.

13. The operation of determining the possibility of ignition includes: The operating method according to claim 12 , further comprising the step of comparing the designated polynomial, the coefficients of which are determined for the battery unit, with a reference polynomial to determine the likelihood of the battery unit catching fire.

14. The method of claim 13 wherein the specified polynomial is a cubic polynomial.

15. The method of claim 13 , wherein the initial value of the specified polynomial is zero.

Images