Battery diagnosis device and operating method thereof

Abstract

A battery diagnosis device according to one embodiment disclosed in the present document may comprise: an acquisition unit for acquiring pack data related to a state of a battery pack and cell data related to states of a plurality of battery cells included in the battery pack; an identification unit for identifying, on the basis of the pack data, a first open circuit voltage (OCV) section in which the voltage standard score (Z-score) difference between the plurality of battery cells decreases as the OCV of the battery pack increases, and a second OCV section in which the voltage standard score difference between the plurality of battery cells increases as the OCV of the battery pack increases; an extraction unit for extracting a diagnosis feature value from voltage standard scores of the plurality of battery cells corresponding to each of the first OCV section and the second OCV section; and a diagnosis unit for diagnosing an abnormality of the battery pack on the basis of the extracted diagnosis feature value.

Description

Battery diagnostic device and its operating method

[0001] Cross-citation with related applications

[0002] This invention claims the benefit of priority from Korean Patent Application No. 10-2024-0021601, filed February 15, 2024, the entire contents of which are incorporated herein by reference.

[0003] Technology field

[0004] The embodiments disclosed in this document relate to a battery diagnostic device and an operating method thereof.

[0005] Research and development on secondary batteries has been actively conducted recently. The term "secondary battery" refers to a rechargeable battery, encompassing both conventional Ni / Cd and Ni / MH batteries, as well as more recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries boast a significantly higher energy density than conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in a compact and lightweight form, making them ideal power sources for mobile devices. Recently, their use has expanded to include power sources for electric vehicles, drawing attention as a next-generation energy storage medium.

[0006] Additionally, secondary batteries can be utilized as battery packs, which typically include battery modules in which multiple battery cells are connected in series and / or parallel. Furthermore, secondary batteries can be utilized as battery racks, which include multiple battery modules and a rack frame that accommodates these battery modules.

[0007] Battery cells, battery modules, battery packs, or battery racks like these can be utilized in a variety of devices. For example, batteries can be used in mobile devices such as cell phones, laptops, smartphones, and tablets, as well as in electric vehicles (EVs, HEVs, PHEVs) and large-capacity energy storage systems (ESS).

[0008] These batteries can have their status and operation managed and controlled by a battery management system (BMS). The BMS can be included with the batteries in a single device.

[0009] Additionally, the battery management system can manage and control the battery while being separated from the device containing the battery. For example, the battery management system can be implemented as a separate server device. In this case, the battery management system can collect battery data and vehicle data from vehicles and other devices, and utilize the collected data to manage and control the battery.

[0010] Meanwhile, if a battery is defective, the risk of damage to devices containing the battery (e.g., EVs, ESS) may increase. Therefore, a method is needed to detect abnormal battery conditions and reduce the risk of damage to devices containing the battery.

[0011] Embodiments disclosed in this document can provide a battery diagnostic device and an operating method thereof capable of extracting diagnostic feature values ​​used to diagnose an abnormality of a battery pack based on a battery cell voltage standard score for each OCV section of the battery pack.

[0012] 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 descriptions below.

[0013] According to an embodiment disclosed in the present document, a battery diagnosis device may include an acquisition unit that acquires pack data related to a state of a battery pack and cell data related to states of a plurality of battery cells included in the battery pack, an identification unit that identifies, based on the pack data, a first OCV section in which a difference in voltage standard scores (Z-Scores) between the plurality of battery cells decreases as an OCV (Open Circuit Voltage) of the battery pack increases and a second OCV section in which a difference in voltage standard scores between the plurality of battery cells increases as the OCV of the battery pack increases, an extraction unit that extracts, based on the cell data, a diagnostic feature value from the voltage standard scores of the plurality of battery cells corresponding to each of the first OCV section and the second OCV section, and a diagnostic unit that diagnoses an abnormality of the battery pack based on the extracted diagnostic feature value.

[0014] In a battery diagnostic device according to an embodiment disclosed in this document, the pack data may include a graph representing an OCV for a SOC (State of Charge) of the battery pack, and the cell data may include a graph representing a voltage standard score of the plurality of battery cells for the OCV of the battery pack.

[0015] In a battery diagnostic device according to an embodiment disclosed in this document, the identification unit can identify the first OCV section and the second OCV section based on a slope of the pack data.

[0016] In a battery diagnostic device according to an embodiment disclosed in this document, the identification unit can identify an OCV section in which the slope of the pack data is less than or equal to a specified value and the slope continuously changes as the first OCV section, and can identify an OCV section in which the slope of the pack data exceeds the specified value and the slope continuously changes as the second OCV section.

[0017] In a battery diagnosis device according to an embodiment disclosed in this document, the extraction unit may calculate a voltage standard score difference between the plurality of battery cells in the first OCV section, select a target battery cell having the largest voltage standard score difference from the remaining battery cells based on the calculated voltage standard score difference, and extract the diagnostic feature value based on the voltage standard score of the target battery cell in the second OCV section.

[0018] In a battery diagnostic device according to an embodiment disclosed in this document, the extraction unit can extract the diagnostic feature value based on the following equation 1.

[0019] [Formula 1]

[0020]

[0021] (In the above formula 1, F is the diagnostic feature value, OCV min is the minimum OCV value of the second OCV section, OCV max is the maximum OCV value of the second OCV section, Z1 is the first voltage standard score of the target battery cell corresponding to the minimum OCV value, and Z2 is the second voltage standard score of the target battery cell corresponding to the maximum OCV value.)

[0022] In a battery diagnostic device according to an embodiment disclosed in this document, the diagnostic unit can diagnose an abnormality in the battery pack by comparing the diagnostic feature value with a threshold value.

[0023] A battery diagnostic device according to an embodiment disclosed in this document further includes an abnormality processing unit that performs an abnormality processing function based on an abnormality diagnosis result of the battery pack, and the abnormality processing function may include a notification function or a short circuit function.

[0024] An operating method of a battery diagnosis device according to an embodiment disclosed in the present document may include an operation of acquiring pack data related to a state of a battery pack and cell data related to states of a plurality of battery cells included in the battery pack, an operation of identifying, based on the pack data, a first OCV section in which a difference in voltage standard scores (Z-Scores) between the plurality of battery cells decreases as an OCV (Open Circuit Voltage) of the battery pack increases and a second OCV section in which a difference in voltage standard scores between the plurality of battery cells increases as the OCV of the battery pack increases, an operation of extracting, based on the cell data, a diagnostic feature value from the voltage standard scores of the plurality of battery cells corresponding to each of the first OCV section and the second OCV section, and an operation of diagnosing an abnormality of the battery pack based on the extracted diagnostic feature value.

[0025] In an operating method of a battery diagnostic device according to an embodiment disclosed in this document, the pack data may include a graph representing an OCV for a SOC (State of Charge) of the battery pack, and the cell data may include a graph representing a voltage standard score of the plurality of battery cells for the OCV of the battery pack.

[0026] In the operating method of the battery diagnosis device according to one embodiment disclosed in this document, the operation of identifying the first OCV section and the second OCV section may include an operation of identifying the first OCV section and the second OCV section based on a slope of the pack data.

[0027] In the operating method of the battery diagnosis device according to one embodiment disclosed in the present document, the operation of identifying the first OCV section and the second OCV section may include an operation of identifying an OCV section in which the slope of the pack data is less than or equal to a specified value and the slope continuously changes as the first OCV section, and an operation of identifying an OCV section in which the slope of the pack data exceeds the specified value and the slope continuously changes as the second OCV section.

[0028] In an operating method of a battery diagnosis device according to an embodiment disclosed in the present document, the operation of extracting the diagnostic feature value may include an operation of calculating a voltage standard score difference between the plurality of battery cells in the first OCV section, an operation of selecting a target battery cell having the largest voltage standard score difference from the remaining battery cells based on the calculated voltage standard score difference, and an operation of extracting the diagnostic feature value based on a voltage standard score of the target battery cell in the second OCV section.

[0029] In the operating method of the battery diagnostic device according to one embodiment disclosed in this document, the operation of extracting the diagnostic feature value may be based on the above equation 1.

[0030] In the operating method of the battery diagnostic device according to one embodiment disclosed in this document, the operation of diagnosing an abnormality in the battery pack may include an operation of diagnosing an abnormality in the battery pack by comparing the diagnostic feature value with a threshold value.

[0031] According to the embodiments disclosed in this document, the diagnosis accuracy can be improved by diagnosing an abnormality of a battery pack using a diagnostic feature value extracted based on a battery cell voltage standard score for each OCV section of the battery pack.

[0032] In addition, various effects may be provided, either directly or indirectly, through this document.

[0033] FIG. 1 is a block diagram of a battery diagnostic device according to one embodiment.

[0034] FIG. 2 is a graph showing pack data related to the state of a battery pack acquired by a battery diagnostic device according to one embodiment.

[0035] FIG. 3 is a graph showing cell data related to the status of a plurality of battery cells acquired by a battery diagnostic device according to one embodiment.

[0036] Figure 4 is a flowchart illustrating the operation of a battery diagnostic device according to one embodiment.

[0037] Hereinafter, various embodiments of the present invention will be described with reference to the attached drawings. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that the present invention encompasses various modifications, equivalents, and / or alternatives of the embodiments.

[0038] The various embodiments and terminology used in this document are not intended to limit the technical features described in this document to specific embodiments, but should be understood to encompass various modifications, equivalents, or alternatives of the embodiments. In connection with the description of the drawings, similar reference numerals may be used to refer to similar or related components. The singular form of a noun corresponding to an item may include one or more of the items, unless the context clearly indicates otherwise.

[0039] In this document, the phrases "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" can each include any one of the items listed together in that phrase, or all possible combinations thereof. Terms such as "first", "second", "first", "second", "A", "B", "(a)", or "(b)" may be used merely to distinguish the corresponding element from other corresponding elements, and do not limit the corresponding elements in any other respect (e.g., importance or order) unless specifically stated otherwise.

[0040] In this document, whenever a component (e.g., a first component) is referred to as being “connected,” “coupled,” or “connected,” with or without the terms “functionally” or “communicatively,” or “coupled” or “connected,” it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or via a third component.

[0041] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0042] FIG. 1 is a block diagram of a battery diagnostic device according to one embodiment.

[0043] The battery diagnostic device (101) described below can be implemented as a BMS (Battery Management System) in an electronic device (102), but can also be implemented as various external devices such as a server, cloud, charger, or charger / discharger.

[0044] Referring to FIG. 1, a battery diagnostic device (101) can be connected to an electronic device (102) and a user terminal (104) via wires and / or wirelessly.

[0045] According to one embodiment, the connection (103) between the battery diagnostic device (101) and the electronic device (102) 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 short-range communication network (e.g., Bluetooth, wireless fidelity (WiFi), or infrared data association (IrDA)) or a wide-range communication network (cellular network, 4G network, 5G network).

[0046] According to another embodiment, the connection (103) between the battery diagnostic device (101) and the electronic device (102) may be a connection via a device-to-device communication method (e.g., a bus, a general purpose input and output (GPIO), a serial peripheral interface (SPI), or a mobile industry processor interface (MIPI)).

[0047] According to one embodiment, the electronic device (102) may be a mobile device (e.g., a mobile phone, a laptop computer, a smart phone, a smart pad), an electric vehicle (e.g., an electric vehicle (EV), a hybrid EV (HEV), a plug-in HEV (PHEV), a fuel cell EV (FCEV)), an energy storage system (ESS), or a battery swapping system (BSS).

[0048] According to one embodiment, the electronic device (102) may include a plurality of battery packs (150, 160, 170). The plurality of battery packs (150, 160, 170) may each include a plurality of battery cells (151, 152, 153, 161, 162, 163, 171, 172, 173). Here, each of the battery cells (151, 152, 153, 161, 162, 163, 171, 172, 173) may be a single battery cell, or may be a cell group in which at least two or more battery cells are connected in parallel within the arranged battery pack (150, 160, or 170).

[0049] According to one embodiment, the connection (105) between the battery diagnostic device (101) and the user terminal (104) may be a communication connection via a wired and / or wireless network.

[0050] According to one embodiment, the user terminal (104) may be a mobile device (e.g., a mobile phone, a laptop computer, a smart phone, a smart pad), or a personal computer (PC). According to one embodiment, the battery diagnostic device (101) may provide information related to the diagnostic results of the battery unit (151, 153, or 155) to the user terminal (104).

[0051] According to one embodiment, the battery diagnostic device (101) may include a communication circuit (110), a sensor (120), a memory (130), and a processor (140). According to an embodiment, the battery diagnostic device (101) illustrated in FIG. 1 may further include at least one component (e.g., a display, an input device, or an output device) other than the components illustrated in FIG. 1, or may omit at least one component (e.g., a sensor (120)) among the components illustrated in FIG. 1. For example, when the battery diagnostic device (101) is implemented as an external electronic device separate from the electronic device (102), such as a server or cloud, the battery diagnostic device (101) can obtain status information of a plurality of battery packs (150, 160, 170) and / or a plurality of battery cells (151, 152, 153, 161, 162, 163, 171, 172, 173) using a communication circuit (110). In this case, the battery diagnostic device (101) may not include a sensor (120).

[0052] According to one embodiment, the communication circuit (110) can establish a wired communication channel and / or a wireless communication channel between the battery diagnostic device (101) and the electronic device (102) and / or the user terminal (104), and transmit and receive data with the electronic device (102) and / or the user terminal (104) through the established communication channel.

[0053] According to one embodiment, the sensor (120) can measure information (e.g., voltage, current, temperature, etc.) related to the status of a plurality of battery packs (150, 160, 170) and / or a plurality of battery cells (151, 152, 153, 161, 162, 163, 171, 172, 173) of the electronic device (102). For example, when the battery diagnostic device (101) is implemented as a BMS (Battery Management System) (e.g., pack BMS and / or cell BMS) in the electronic device (102), the battery diagnostic device (101) can directly measure the status values ​​of a plurality of battery packs (150, 160, 170) and / or a plurality of battery cells (151, 152, 153, 161, 162, 163, 171, 172, 173) using a sensor (120).

[0054] According to one embodiment, the memory (130) may include volatile memory and / or non-volatile memory.

[0055] According to one embodiment, the memory (130) may store data used by at least one component (e.g., processor (140)) of the battery diagnosis device (101). For example, the data may include software (or instructions related thereto), input data, or output data. In one embodiment, the instructions, when executed by the processor (140), may cause the battery abnormality diagnosis device (101) to perform operations defined by the instructions.

[0056] According to one embodiment, the memory (130) may include one or more software (e.g., an acquisition unit (131), an identification unit (132), an extraction unit (133), a diagnosis unit (134), and an anomaly processing unit (135)).

[0057] According to one embodiment, the processor (140) 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.

[0058] According to one embodiment, the processor (140) may execute software (e.g., acquisition unit (131), identification unit (132), extraction unit (133), diagnosis unit (134), and abnormality processing unit (135)) stored in the memory (130) to control at least one other component (e.g., hardware or software component) of the battery diagnostic device (101) connected to the processor (140) and perform various data processing or operations.

[0059] Hereinafter, with reference to FIGS. 2 and 3, a method for diagnosing an abnormality of one battery pack (150) among a plurality of battery packs (150, 160, 170) through an acquisition unit (131), an identification unit (132), an extraction unit (133), a diagnosis unit (134), and an abnormality processing unit (135) by a battery diagnosis device (101) will be described. The abnormality diagnosis method of a battery pack (150) to be described below can be equally applied to all battery packs (150, 160, 170) included in an electronic device (102).

[0060] FIG. 2 is a graph showing pack data related to the state of a battery pack acquired by a battery diagnostic device according to an embodiment. FIG. 3 is a graph showing cell data related to the state of a plurality of battery cells acquired by a battery diagnostic device according to an embodiment.

[0061] According to one embodiment, the acquisition unit (131) may acquire pack data related to the state of the battery pack (150). Here, the pack data may include a graph representing OCV against SOC of the battery pack (150). In addition, the pack data may include a graph representing SOC-OCV in one charge / discharge cycle among multiple charge / discharge cycles of the battery pack (150).

[0062] For example, the acquisition unit (131) can acquire pack data such as the graph (200) of Fig. 2. In the graph (200), the X-axis can represent the SOC (State of Charge) of the battery pack (150), and the Y-axis can represent the OCV (Open Circuit Voltage) of the battery pack (150).

[0063] According to one embodiment, the acquisition unit (131) may acquire cell data related to the states of a plurality of battery cells (151, 152, 153) included in a battery pack (150). Here, the cell data may include a graph representing voltage standard scores (Z-scores) of the plurality of battery cells (151, 152, 153) with respect to the OCV of the battery pack (150). In addition, the cell data may include a graph representing pack OCV-cell voltage standard scores in each of a plurality of charge / discharge cycles of the plurality of battery cells (151, 152, 153).

[0064] For example, the acquisition unit (131) can acquire cell data representing the pack OCV-cell voltage standard score in each of a plurality of charge / discharge cycles, as in the graph (300) of Fig. 3. In the graph (300), the X-axis can represent the OCV of the battery pack (150), and the Y-axis can represent the voltage standard score of the plurality of battery cells (151, 152, 153).

[0065] According to one embodiment, the identification unit (132) may identify a first OCV section and a second OCV section of the battery pack (150) based on the pack data acquired by the acquisition unit (131). Here, the first OCV section may mean a section in which the voltage standard score difference between the plurality of battery cells (151, 152, 153) decreases as the OCV of the battery pack (150) increases. In addition, the second OCV section may mean a section in which the voltage standard score difference between the plurality of battery cells (151, 152, 153) increases as the OCV of the battery pack (150) increases.

[0066] According to one embodiment, the identification unit (132) can identify the first OCV section and the second OCV section based on the slope of the pack data. For example, the identification unit (132) can identify an OCV section in which the slope of the SOC-OCV graph included in the pack data is less than or equal to a specified value and the slope continuously changes as the first OCV section. In addition, the identification unit (132) can identify an OCV section in which the slope exceeds a specified value and the slope continuously changes as the second OCV section.

[0067] According to one embodiment, the identification unit (132) can identify the first OCV section and the second OCV section based on the first differential data and the second differential data of the pack data. The first differential data may be data indicating the first differential value (dOCV / dSOC) obtained by differentiating the OCV of the battery pack (150) with respect to the SOC with respect to the SOC. In addition, the second differential data may be data indicating the second differential value (d) obtained by differentiating the first differential value (dOCV / dSOC) of the battery pack (150) with respect to the SOC. 2 OCV / dSOC 2 ) may be data representing SOC.

[0068] For example, the identification unit (132) can identify a first SOC section in which the first derivative value (dOCV / dSOC) of the battery pack (150) is less than or equal to a specified value based on the first derivative data. The identification unit (132) can identify a second derivative value (d) of the battery pack (150) among the first SOC sections based on the second derivative data. 2 OCV / dSOC 2 ) can identify a second SOC section that is not 0. The identification unit (132) can identify the OCV section corresponding to the second SOC section in the pack data as the first OCV section.

[0069] As another example, the identification unit (132) can identify a third SOC section in which the first derivative value (dOCV / dSOC) of the battery pack (150) exceeds a specified value based on the first derivative data. The identification unit (132) can identify a second derivative value (d) of the battery pack (150) among the third SOC sections based on the second derivative data. 2 OCV / dSOC 2 ) can identify a fourth SOC section that is not 0. The identification unit (132) can identify the OCV section corresponding to the fourth SOC section in the pack data as the second OCV section.

[0070] According to one embodiment, the identification unit (132) may identify a third OCV section of the battery pack (150) based on pack data. Here, the third OCV section may mean a section in which the voltage standard score difference between the plurality of battery cells (151, 152, 153) is constant as the OCV of the battery pack (150) increases.

[0071] According to one embodiment, the identification unit (132) can identify the third OCV section based on the slope of the pack data. For example, the identification unit (132) can identify an OCV section in which the slope of the SOC-OCV graph included in the pack data is maintained as the third OCV section.

[0072] According to one embodiment, the identification unit (132) can identify the third OCV section based on the second differential data of the pack data. For example, the identification unit (132) can identify the second differential value (d) of the battery pack (150) based on the second differential data. 2 OCV / dSOC 2 ) can identify the fifth SOC section in which the value becomes 0. The identification unit (132) can identify the OCV section corresponding to the fifth SOC section in the pack data as the third OCV section.

[0073] Referring to FIG. 2, the identification unit (132) can identify a first OCV section (R1) in which the slope of the graph (200) is less than or equal to a specified value and continuously changes, a second OCV section (R2) in which the slope is greater than or equal to a specified value and continuously changes, and / or a third OCV section (R3) in which the slope is constant.

[0074] The OCV sections (R1, R2, R3) shown in the graph (300) of FIG. 3 may be a first OCV section (R1), a second OCV section (R2), and a third OCV section (R3) identified by the identification unit (132). Referring to FIG. 3, it can be confirmed that in the first OCV section (R1) of the graph (300), the voltage standard score difference between the plurality of battery cells (151, 152, 153) decreases, in the second OCV section (R2), the voltage standard score difference between the plurality of battery cells (151, 152, 153) increases, and in the third OCV section (R3), the voltage standard score difference between the plurality of battery cells (151, 152, 153) is constant.

[0075] Referring back to FIG. 1, the extraction unit (133) can extract diagnostic feature values ​​based on the cell data acquired by the acquisition unit (131). According to one embodiment, the extraction unit (133) can extract diagnostic feature values ​​from voltage standard scores of a plurality of battery cells (151, 152, 153) corresponding to each of the first OCV section and the second OCV section identified by the identification unit (132).

[0076] Referring to FIG. 3, the extraction unit (133) can calculate the voltage standard score difference between a plurality of battery cells (151, 152, 153) in the first OCV section (R1). Based on the calculated voltage standard score difference, the extraction unit (133) can select a target battery cell (e.g., 151) having the largest voltage standard score difference from the remaining battery cells (e.g., 152, 153).

[0077] According to one embodiment, the extraction unit (133) may extract the diagnostic feature value based on the voltage standard score in the second OCV section (R2) of the target battery cell (e.g., 151). Specifically, the extraction unit (133) may extract the diagnostic feature value based on the first voltage standard score (Z1) and the second voltage standard score (Z2) in the second OCV section (R2) of the target battery cell (e.g., 151).

[0078] According to one embodiment, the extraction unit (133) can extract diagnostic feature values ​​based on the following equation 1.

[0079] [Formula 1]

[0080]

[0081] In the above formula 1, F is the diagnostic feature value, OCV min is the minimum OCV value of the second OCV section (R2), OCV maxis the maximum OCV value of the second OCV section (R2), Z1 is the first voltage standard score of the target battery cell (e.g., 151) corresponding to the minimum OCV value, and Z2 is the second voltage standard score of the target battery cell (e.g., 151) corresponding to the maximum OCV value.

[0082] Referring again to FIG. 1, the diagnostic unit (134) can diagnose an abnormality in the battery pack (150) based on the diagnostic feature values ​​extracted by the extraction unit (133).

[0083] According to one embodiment, the diagnostic unit (134) can diagnose an abnormality in the battery pack (150) by comparing the diagnostic feature value with a preset threshold value. For example, the diagnostic unit (134) can diagnose the battery pack (150) as an abnormal battery pack if the diagnostic feature value is equal to or greater than the preset threshold value.

[0084] According to another embodiment, the diagnostic unit (134) can diagnose an abnormality in the battery pack (150) by comparing the absolute value of the diagnostic feature value with a preset threshold value. For example, the diagnostic unit (134) can diagnose the battery pack (150) as an abnormal battery pack if the absolute value of the diagnostic feature value is equal to or greater than the preset threshold value.

[0085] According to one embodiment, the abnormality processing unit (135) may perform an abnormality processing function based on the abnormality diagnosis result of the battery pack (150). Here, the abnormality processing function may include a notification function or a short circuit function.

[0086] According to one embodiment, the abnormality processing unit (135) can transmit the abnormality diagnosis result of the battery pack (150) to a user terminal (104) connected via a wired and / or wireless network.

[0087] According to one embodiment, the abnormality processing unit (135) may isolate the abnormal battery pack (150) from the electronic device (102) based on the abnormality diagnosis result of the battery pack (150). Here, the isolation may include electrical and / or mechanical isolation.

[0088] Fig. 4 is a flowchart illustrating the operation of a battery diagnostic device according to one embodiment. Fig. 4 can be explained using the configurations of Fig. 1.

[0089] The embodiment illustrated in FIG. 4 is only one embodiment, and the order of steps according to various embodiments of the present invention may be different from that illustrated in FIG. 4, and some of the steps illustrated in FIG. 4 may be omitted, the order between steps may be changed, or steps may be merged.

[0090] Referring to FIG. 4, in operation 405, the battery diagnostic device (101) can obtain pack data related to the state of the battery pack (150) and cell data related to the state of a plurality of battery cells (151, 152, 153) included in the battery pack (150).

[0091] For example, the pack data may include a graph representing OCV versus SOC of the battery pack (150). Additionally, the pack data may include a graph representing SOC-OCV in one of a plurality of charge / discharge cycles of the battery pack (150).

[0092] For example, the cell data may include a graph representing a voltage standard score (Z-score) of a plurality of battery cells (151, 152, 153) against an OCV of the battery pack (150). Additionally, the cell data may include a graph representing a pack OCV-cell voltage standard score for each of a plurality of charge / discharge cycles of the plurality of battery cells (151, 152, 153).

[0093] In operation 410, the battery diagnostic device (101) may identify a first OCV section and a second OCV section of the battery pack (150) based on the pack data acquired in operation 405. Here, the first OCV section may mean a section in which the voltage standard score difference between the plurality of battery cells (151, 152, 153) decreases as the OCV of the battery pack (150) increases. In addition, the second OCV section may mean a section in which the voltage standard score difference between the plurality of battery cells (151, 152, 153) increases as the OCV of the battery pack (150) increases.

[0094] According to one embodiment, the battery diagnosis device (101) can identify a first OCV section and a second OCV section based on the slope of the pack data. For example, the battery diagnosis device (101) can identify an OCV section in which the slope of the SOC-OCV graph included in the pack data is lower than or equal to a specified value and the slope continuously changes as the first OCV section. In addition, the battery diagnosis device (101) can identify an OCV section in which the slope exceeds the specified value and the slope continuously changes as the second OCV section.

[0095] According to one embodiment, the battery diagnostic device (101) can identify a first OCV section and a second OCV section based on the first differential data and the second differential data of the pack data. The first differential data may be data indicating the first differential value (dOCV / dSOC) obtained by differentiating the OCV of the battery pack (150) with respect to the SOC with respect to the SOC. In addition, the second differential data may be data indicating the second differential value (d) obtained by differentiating the first differential value (dOCV / dSOC) of the battery pack (150) with respect to the SOC. 2 OCV / dSOC 2 ) may be data representing SOC.

[0096] For example, the battery diagnostic device (101) can identify a first SOC section in which the first derivative value (dOCV / dSOC) of the battery pack (150) is less than or equal to a specified value based on the first derivative data. The battery diagnostic device (101) can identify a second derivative value (d) of the battery pack (150) among the first SOC sections based on the second derivative data. 2 OCV / dSOC 2 ) can identify a second SOC section that is not 0. The battery diagnostic device (101) can identify the OCV section corresponding to the second SOC section in the pack data as the first OCV section.

[0097] As another example, the battery diagnostic device (101) can identify a third SOC section in which the first derivative value (dOCV / dSOC) of the battery pack (150) exceeds a specified value based on the first derivative data. The battery diagnostic device (101) can identify a second derivative value (d) of the battery pack (150) among the third SOC sections based on the second derivative data. 2 OCV / dSOC 2 ) can identify a fourth SOC section that is not 0. The battery diagnostic device (101) can identify the OCV section corresponding to the fourth SOC section in the pack data as the second OCV section.

[0098] According to one embodiment, the battery diagnostic device (101) may identify a third OCV section of the battery pack (150) based on pack data. Here, the third OCV section may mean a section in which the voltage standard score difference between the plurality of battery cells (151, 152, 153) is constant as the OCV of the battery pack (150) increases.

[0099] According to one embodiment, the battery diagnostic device (101) can identify the third OCV section based on the slope of the pack data. For example, the battery diagnostic device (101) can identify the OCV section in which the slope of the SOC-OCV graph included in the pack data is maintained as the third OCV section.

[0100] According to one embodiment, the battery diagnostic device (101) can identify the third OCV section based on the second differential data of the pack data. For example, the battery diagnostic device (101) can identify the second differential value (d) of the battery pack (150) based on the second differential data. 2 OCV / dSOC 2 ) can identify the fifth SOC section in which the voltage becomes 0. The battery diagnostic device (101) can identify the OCV section corresponding to the fifth SOC section in the pack data as the third OCV section.

[0101] In operation 415, the battery diagnostic device (101) may extract diagnostic feature values ​​based on the cell data acquired in operation 405. According to one embodiment, the battery diagnostic device (101) may extract diagnostic feature values ​​from voltage standard scores of a plurality of battery cells (151, 152, 153) corresponding to each of the first OCV section and the second OCV section identified in operation 410.

[0102] According to one embodiment, the battery diagnostic device (101) can calculate a voltage standard score difference between a plurality of battery cells (151, 152, 153) in a first OCV section. Based on the calculated voltage standard score difference, the battery diagnostic device (101) can select a target battery cell (e.g., 151) having the largest voltage standard score difference from the remaining battery cells (e.g., 152, 153).

[0103] According to one embodiment, the battery diagnostic device (101) can extract diagnostic feature values ​​based on a voltage standard score in the second OCV section of the target battery cell (e.g., 151).

[0104] According to one embodiment, the battery diagnostic device (101) can extract diagnostic feature values ​​based on the above equation 1.

[0105] In operation 420, the battery diagnostic device (101) can diagnose an abnormality in the battery pack (150) based on the diagnostic feature values ​​extracted in operation 415.

[0106] According to one embodiment, the battery diagnostic device (101) can diagnose an abnormality in the battery pack (150) by comparing a diagnostic characteristic value with a preset threshold value. For example, the battery diagnostic device (101) can diagnose the battery pack (150) as an abnormal battery pack if the diagnostic characteristic value is equal to or greater than the preset threshold value.

[0107] According to another embodiment, the battery diagnostic device (101) can diagnose an abnormality in the battery pack (150) by comparing the absolute value of the diagnostic feature value with a preset threshold value. For example, the battery diagnostic device (101) can diagnose the battery pack (150) as an abnormal battery pack if the absolute value of the diagnostic feature value is equal to or greater than the preset threshold value.

[0108] According to one embodiment, the battery diagnostic device (101) may perform an abnormality processing function based on the abnormality diagnosis result of the battery pack (150). Here, the abnormality processing function may include a notification function or a short circuit function.

[0109] According to one embodiment, the battery diagnostic device (101) can transmit abnormal diagnosis results of the battery pack (150) to a user terminal (104) connected via a wired and / or wireless network.

[0110] According to one embodiment, the battery diagnostic device (101) can isolate the abnormal battery pack (150) from the electronic device (102) based on the abnormal diagnosis result of the battery pack (150). Here, the isolation may include electrical and / or mechanical isolation.

[0111] The terms "include," "comprise," or "have" used herein, unless otherwise specifically stated, imply that the corresponding component may be included, and therefore should be interpreted to include other components rather than to exclude other components. All terms, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the embodiments disclosed in this document pertain, unless otherwise defined. Commonly used terms, such as terms defined in dictionaries, should be interpreted to be consistent with their meaning in the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense, unless explicitly defined in this document.

Claims

1. An acquisition unit that acquires pack data related to the state of a battery pack and cell data related to the state of a plurality of battery cells included in the battery pack; An identification unit that identifies a first OCV section in which a voltage standard score (Z-Score) difference between the plurality of battery cells decreases as the OCV (Open Circuit Voltage) of the battery pack increases based on the pack data, and a second OCV section in which a voltage standard score difference between the plurality of battery cells increases as the OCV of the battery pack increases; An extraction unit that extracts diagnostic feature values ​​from voltage standard scores of the plurality of battery cells corresponding to each of the first OCV section and the second OCV section based on the cell data; and A battery diagnostic device including a diagnostic unit that diagnoses an abnormality in the battery pack based on the extracted diagnostic feature values.

2. In claim 1, The above pack data includes a graph showing the OCV for the SOC (State of Charge) of the battery pack, A battery diagnostic device, wherein the cell data includes a graph representing voltage standard scores of the plurality of battery cells for the OCV of the battery pack.

3. In claim 2, A battery diagnostic device, wherein the identification unit identifies the first OCV section and the second OCV section based on the slope of the pack data.

4. In claim 3, The above identification part is, The OCV section in which the slope of the above pack data is less than or equal to a specified value and the slope continuously changes is identified as the first OCV section, A battery diagnostic device that identifies an OCV section in which the slope of the pack data exceeds the specified value and the slope continuously changes as the second OCV section.

5. In claim 2, The above extraction unit, Calculate the voltage standard score difference between the plurality of battery cells in the first OCV section, Based on the voltage standard score difference calculated above, the target battery cell with the largest voltage standard score difference from the remaining battery cells is selected, A battery diagnostic device that extracts the diagnostic feature value based on the voltage standard score in the second OCV section of the target battery cell.

6. In claim 5, A battery diagnostic device, wherein the above extraction unit extracts the diagnostic feature value based on the following equation 1. [Formula 1] (In the above formula 1, F is the diagnostic feature value, OCV min is the minimum OCV value of the second OCV section, OCV max is the maximum OCV value of the second OCV section, Z1 is the first voltage standard score of the target battery cell corresponding to the minimum OCV value, and Z2 is the second voltage standard score of the target battery cell corresponding to the maximum OCV value.) 7. In claim 1, The above diagnostic unit is a battery diagnostic device that diagnoses an abnormality in the battery pack by comparing the diagnostic feature value and a threshold value.

8. In claim 1, Further comprising an abnormality processing unit that performs an abnormality processing function based on the abnormality diagnosis result of the above battery pack, A battery diagnostic device, wherein the above abnormality handling function includes a notification function or a short circuit function.

9. An operation of acquiring pack data related to the state of a battery pack and cell data related to the state of a plurality of battery cells included in the battery pack; An operation of identifying a first OCV section in which a voltage standard score (Z-Score) difference between the plurality of battery cells decreases as the OCV (Open Circuit Voltage) of the battery pack increases based on the pack data, and a second OCV section in which a voltage standard score difference between the plurality of battery cells increases as the OCV of the battery pack increases; An operation of extracting diagnostic feature values ​​from voltage standard scores of the plurality of battery cells corresponding to each of the first OCV section and the second OCV section based on the cell data; and An operating method of a battery diagnostic device, comprising an operation of diagnosing an abnormality of the battery pack based on the extracted diagnostic feature values.

10. In claim 9, The above pack data includes a graph showing the OCV for the SOC (State of Charge) of the battery pack, A method of operating a battery diagnostic device, wherein the cell data includes a graph representing voltage standard scores of the plurality of battery cells for the OCV of the battery pack.

11. In claim 10, A method for operating a battery diagnostic device, wherein the operation of identifying the first OCV section and the second OCV section includes an operation of identifying the first OCV section and the second OCV section based on a slope of the pack data.

12. In claim 11, The operation of identifying the first OCV section and the second OCV section is as follows: An operation of identifying an OCV section in which the slope of the pack data is less than or equal to a specified value and in which the slope continuously changes as the first OCV section, and An operating method of a battery diagnostic device, comprising an operation of identifying an OCV section in which the slope of the pack data exceeds the specified value and the slope continuously changes as the second OCV section.

13. In claim 9, The operation of extracting the above diagnostic feature values ​​is as follows: An operation of calculating a voltage standard score difference between the plurality of battery cells in the first OCV section; An operation of selecting a target battery cell having the largest voltage standard score difference from the remaining battery cells based on the voltage standard score difference calculated above, and An operating method of a battery diagnostic device, comprising an operation of extracting the diagnostic feature value based on a voltage standard score in the second OCV section of the target battery cell.

14. In claim 13, An operation of extracting the above diagnostic feature value is an operation method of a battery diagnostic device based on the following equation 1. [Formula 1] (In the above formula 1, F is the diagnostic feature value, OCV min is the minimum OCV value of the second OCV section, OCV max is the maximum OCV value of the second OCV section, Z1 is the first voltage standard score of the target battery cell corresponding to the minimum OCV value, and Z2 is the second voltage standard score of the target battery cell corresponding to the maximum OCV value.) 15. In claim 9, A method for operating a battery diagnostic device, wherein the operation of diagnosing an abnormality in the battery pack includes an operation of diagnosing an abnormality in the battery pack by comparing the diagnostic characteristic value with a threshold value.

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