Battery abnormality diagnosis device and method

Abstract

The provided device is a battery anomaly diagnostic apparatus, comprising: a voltage acquisition unit that acquires the voltage of a single battery cell; an analysis unit that calculates estimation information for estimating the battery voltage by analyzing the voltage of the single battery cell; and a diagnostic unit that diagnoses anomalies of the single battery cell by analyzing the estimation information.

Description

Technical Field

[0001] Cross-reference to related applications

[0002] This application claims priority and benefit to Korean Patent Application No. 10-2020-0100131, filed on August 10, 2020, with the Korean Intellectual Property Office, the entire contents of which are incorporated herein by reference. Technical Field

[0004] This invention relates to a battery anomaly diagnosis apparatus and method for diagnosing battery anomalies during idle periods. Background Technology

[0005] Recently, research and development of rechargeable batteries have been actively pursued. In this paper, rechargeable batteries, as rechargeable / dischargeable batteries, can include all conventional nickel (Ni) / cadmium (Cd) batteries, Ni / metal hydride (MH) batteries, and more recently, lithium-ion batteries. Among rechargeable batteries, lithium-ion batteries have a significantly higher energy density than conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured to be small and lightweight, making them suitable for use as power sources in mobile devices. Additionally, lithium-ion batteries are attracting attention as a next-generation energy storage medium as their applications expand to power electric vehicles.

[0006] In addition, secondary batteries are often used as battery packs, which consist of multiple battery cells connected in series and / or in parallel. The battery pack can be managed and controlled in terms of state and operation by a battery management system.

[0007] Additionally, secondary batteries in energy storage systems (ESS) typically include a diagnostic checklist for making diagnoses before a fire occurs. Such checklists include values ​​for voltage, current, temperature, power, etc., to help prevent fires, and the secondary batteries primarily perform diagnoses for overvoltage or undervoltage.

[0008] However, in secondary batteries, anomalies can occur almost anywhere outside the voltage peaks or troughs. For example, a fire can occur even when no warnings for overvoltage or undervoltage are generated. Therefore, new diagnostic programs are needed to address both fire and overvoltage / undervoltage issues. Summary of the Invention

[0009] [Technical Issues]

[0010] The present invention has been designed to solve the above-mentioned problems and aims to provide a battery anomaly diagnosis device and method. Through this battery anomaly diagnosis device and method, the unstable voltage behavior of the battery during idle periods can be diagnosed by regression analysis, and the anomaly types during the battery idle periods can be classified.

[0011] [Technical Solution]

[0012] A battery anomaly diagnostic apparatus according to an embodiment disclosed in this document includes: a voltage acquisition unit that acquires the voltage of a single battery cell; an analysis unit that calculates estimation information for estimating the battery voltage by analyzing the voltage of the single battery cell; and a diagnostic unit that diagnoses anomalies of the single battery cell by analyzing the estimation information.

[0013] In an embodiment, the estimation information may include a voltage estimation equation related to the voltage of a battery cell, and the diagnostic unit may diagnose abnormalities of a battery cell based on the slope difference relative to time in the voltage estimation equation.

[0014] In this embodiment, the diagnostic unit can diagnose a battery cell as having an abnormal long-term idle relaxation when the slope difference is less than a preset first reference value, and diagnose a battery cell as having an abnormal idle voltage after charging or discharging when the slope difference is greater than or equal to the first reference value.

[0015] In one embodiment, the first reference value may be determined based on the standard deviation of the slope difference of the voltage estimation equations for the multiple battery cells included in the battery rack.

[0016] In an embodiment, when the slope difference is greater than or equal to the first reference value, the diagnostic unit can diagnose the battery cell as having an abnormal idle voltage after charging when the starting voltage of the battery cell during the idle period is greater than a preset second reference value, and diagnose the battery cell as having an abnormal idle voltage after discharging when the starting voltage of the battery cell during the idle period is less than or equal to the second reference value.

[0017] In an embodiment, the second reference value can be determined as the voltage corresponding to a state of charge (SOC) of 50% for a single battery cell.

[0018] In an embodiment, when the slope difference is greater than or equal to the first reference value, the diagnostic unit can diagnose the battery cell as having an abnormal idle voltage after charging when the current of the battery cell flows in the first direction, and diagnose the battery cell as having an abnormal idle voltage after discharging when the current of the battery cell flows in the second direction opposite to the first direction.

[0019] In this embodiment, the analysis unit can calculate the voltage estimation equation during the idle period after the battery cell has been charged or discharged.

[0020] In an embodiment, the battery anomaly diagnostic device may further include a notification unit that generates a warning notification when the diagnostic unit determines that an anomaly has occurred in a battery cell.

[0021] A battery anomaly diagnosis method according to an embodiment disclosed in this document includes: obtaining the voltage of a battery cell; calculating estimation information for estimating the battery voltage by analyzing the voltage of the battery cell; and diagnosing anomalies of the battery cell by analyzing the estimation information.

[0022] In an embodiment, the estimation information may include a voltage estimation equation related to the voltage of a battery cell, and the diagnosis of anomalies in a battery cell may include diagnosing the anomaly of a battery cell based on the slope difference of the voltage estimation equation relative to time.

[0023] In an embodiment, the diagnosis of abnormalities in a single battery cell may include: diagnosing the battery cell as having an abnormal long-term idle relaxation when the slope difference is less than a first reference value; and diagnosing the battery cell as having an abnormal idle voltage after charging or discharging when the slope difference is greater than or equal to the first reference value.

[0024] In an embodiment, the diagnosis of abnormalities in a battery cell may include: when the slope difference is greater than or equal to a first reference value, diagnosing the battery cell as having an abnormal idle voltage after charging when the starting voltage of the battery cell during its idle period is greater than a preset second reference value, and diagnosing the battery cell as having an abnormal idle voltage after discharging when the starting voltage of the battery cell during its idle period is less than or equal to the second reference value.

[0025] In an embodiment, the diagnosis of abnormalities in a battery cell may include: when the slope difference is greater than or equal to a first reference value, diagnosing the battery cell as having an abnormal idle voltage after charging when the current of the battery cell flows in a first direction, and diagnosing the battery cell as having an abnormal idle voltage after discharging when the current of the battery cell flows in a second direction opposite to the first direction.

[0026] [Beneficial Effects]

[0027] According to the battery anomaly diagnosis apparatus and method of the present invention, unstable voltage behavior of the battery during idle periods is diagnosed by regression analysis, and the anomaly types during the battery idle periods can be classified. Attached Figure Description

[0028] Figure 1 This is a block diagram of a typical battery holder.

[0029] Figure 2 This is a block diagram illustrating the structure of a battery malfunction diagnostic device according to an embodiment of the present invention.

[0030] Figures 3a to 3cThis illustrates idle long-duration relaxation as classified by a battery anomaly diagnostic device according to an embodiment of the present invention.

[0031] Figures 4a to 4c This illustrates a post-charge idle voltage anomaly classified by a battery anomaly diagnostic device according to an embodiment of the present invention.

[0032] Figure 5 This is a flowchart illustrating a battery anomaly diagnosis method according to an embodiment of the present invention.

[0033] Figure 6 This is a block diagram illustrating the hardware structure of a battery malfunction diagnostic device according to an embodiment of the present invention. Detailed Implementation

[0034] In the following, various embodiments of the invention will be described in detail with reference to the accompanying drawings. Throughout this document, the same reference numerals will be used for the same components in the drawings, and the same components will be described without redundancy.

[0035] The specific structural or functional descriptions of the various embodiments of the present invention disclosed in this document are merely illustrative for the purpose of describing embodiments of the present invention, and the various embodiments of the present invention can be implemented in various forms and should not be construed as limited to the embodiments described in this document.

[0036] As used in various embodiments, the term "first (1)" st )", "No. 2(2 nd The terms “first,” “second,” etc., can modify various components regardless of their importance and do not limit the components. For example, without departing from the scope of this disclosure, a first component can be named a second component, and similarly, a second component can be named a first component.

[0037] The terminology used in this document is intended to describe only certain exemplary embodiments of this disclosure and is not intended to limit the scope of other exemplary embodiments of this disclosure. It should be understood that, unless the context clearly specifies otherwise, the singular form includes plural references.

[0038] All terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art. It should be further understood that, unless expressly defined herein, terms such as those defined in common dictionaries should be interpreted as having the same meaning as they have in the context of the relevant art, and not in an idealized or overly formal sense. In some cases, terms defined herein may be interpreted as excluding embodiments of this disclosure.

[0039] Figure 1This is a block diagram of a typical battery holder.

[0040] refer to Figure 1 The diagram schematically illustrates a battery control system according to an embodiment of the present invention, including a battery holder 1 and a higher-level controller 2 included in a higher-level system.

[0041] like Figure 1 As shown, the battery rack 1 may include: a battery module 10, which includes one or more battery cells and is rechargeable / dischargeable; a switching unit 14, which is connected in series to the positive (+) terminal or negative (-) terminal of the battery module 10 to control the charging / discharging current flow of the battery module 10; and a battery management system (e.g., RBMS) 20, for controlling and managing the battery rack 1 by monitoring the voltage, current, temperature, etc., to prevent overcharging and over-discharging. The battery rack 1 may include multiple battery modules 10, sensors 12, switching units 14, and battery management system 20.

[0042] In this document, the switching unit 14, which is used as an element for controlling the current flow for charging or discharging multiple battery modules 10, may, for example, use at least one relay, magnetic contactor, etc., depending on the specifications of the battery rack 1.

[0043] The battery management system 20, which serves as an interface for receiving measured values ​​of the various parameters mentioned above, may include multiple terminals and circuitry connected thereto for processing input values. The battery management system 20 can control the on / off state of switching units 14, such as relays and contactors, and can be connected to battery modules 10 to monitor the status of each battery module 10.

[0044] Meanwhile, the battery management system 20 according to the present invention can perform regression analysis on the voltage of individual battery cells via a separate program, as will be described below. The calculated regression equations can be used to classify the anomaly types of the battery cells.

[0045] The upper-level controller 2 can send control signals regarding the battery module 10 to the battery management system 20. Therefore, the battery management system 20 can also be controlled in its operation based on signals applied from the upper-level controller 2. Simultaneously, individual battery cells according to the invention can be included in the battery module 10 for an energy storage system (ESS). In this case, the upper-level controller 2 can be a battery bank controller (BBMS) comprising multiple racks or an ESS controller for controlling the entire ESS comprising multiple racks. However, the battery rack 1 is not limited to such purposes.

[0046] Such configurations of the battery holder 1 and the battery management system 20 are well-known and will not be described in detail.

[0047] Figure 2This is a block diagram illustrating the structure of a battery malfunction diagnostic device according to an embodiment of the present invention.

[0048] Figure 2 The battery anomaly diagnostic device 200 can be included in a BMS that manages the battery module 10, a BMS that manages the battery rack 1, or a system controller that manages the entire ESS, and can diagnose anomalies by collecting voltage data of each battery module from multiple rack BMSs included in multiple libraries. For example, Figure 2 The battery malfunction diagnostic device 200 can be included in the above. Figure 1 In the battery management system 20 or the upper-level controller 2.

[0049] The classification of abnormality types of battery cells performed by the battery anomaly diagnostic device 200 according to an embodiment of the present invention can be a process after an anomaly in a battery cell has been determined by an anomaly detection algorithm for the battery cell (e.g., principal component analysis, etc.). That is, the following description of the battery anomaly diagnostic device 200 according to the present invention is made under the assumption that abnormal behavior in a battery cell has already been detected through a series of processes. However, this is merely an example, and the invention is not limited thereto. Furthermore, the battery anomaly diagnostic device 200 according to the present invention can classify anomaly types by analyzing data in real time, regardless of whether abnormal behavior has been detected.

[0050] refer to Figure 2 According to an embodiment of the present invention, the battery abnormality diagnosis device 200 may include a voltage acquisition unit 210, an analysis unit 220, a diagnosis unit 230, and a notification unit 240.

[0051] The voltage acquisition unit 210 can acquire the voltage of a single battery cell. For example, the voltage acquisition unit 210 can measure the voltage of a single battery cell at specific time intervals. According to an embodiment, the voltage acquisition unit 210 can receive the measured voltage of a single battery cell from another device. Additionally, the voltage acquisition unit 210 can measure the current flowing in the single battery cell.

[0052] Analysis unit 220 can calculate estimation information related to the voltage of a battery cell by analyzing the voltage of the obtained battery cell. According to an embodiment, the estimation information may include a voltage estimation equation related to the voltage of the battery cell. According to an embodiment, analysis unit 220 can calculate the voltage estimation equation of a battery cell by performing regression analysis on the obtained battery cell voltage. In this case, analysis unit 220 can calculate the voltage estimation equation during an idle period after the battery cell has been charged or discharged. Analysis unit 220 can calculate the voltage estimation equation related to the voltage of the battery cell relative to a set window size (e.g., 30 minutes). For example, analysis unit 220 can calculate the voltage estimation equation as follows.

[0053] y = aX Ts-Te +b- Equation (1),

[0054] (Where Ts indicates the start time of the idle period, Te indicates the end time of the idle period, and X indicates the voltage of the individual battery cell.)

[0055] The diagnostic unit 230 can diagnose abnormalities in individual battery cells by analyzing the voltage estimation equation calculated by the analysis unit 220. For example, the diagnostic unit 230 can calculate the slope 'a' and the slope difference (a0) of the voltage estimation equation. t+1 -a t These are used to diagnose anomalies in individual battery cells. The time interval for the slope difference can be the sampling time (e.g., 1 second).

[0056] More specifically, when the standard deviation of the slope difference of the voltage estimation equation is less than a preset first reference value, the diagnostic unit 230 can diagnose the battery cell as having an abnormal long-term idle relaxation. In this case, the first reference value can be determined for multiple battery cells included in the battery rack based on a multiple of the standard deviation σ of the slope difference of the voltage estimation equation. For example, the first reference value could be 6σ.

[0057] In this paper, prolonged idle relaxation of a battery cell can be defined as an anomaly in which a battery cell takes longer than other cells to reach a steady state after being in an idle state. When such prolonged idle relaxation occurs, it may indicate a lack of smooth operation between the anode and cathode in the battery cell, thus causing problems with battery performance.

[0058] Furthermore, when the slope difference of the voltage estimation equation is greater than or equal to the first reference value, the diagnostic unit 230 can diagnose a battery cell as having an abnormal idle voltage after charging or discharging. An abnormal idle voltage after charging or discharging of a battery cell indicates an anomaly where the voltage is unstable rather than gradually increasing or decreasing during the idle period after charging or discharging. For example, in the case of an abnormal idle voltage after charging or discharging of a battery cell, the slope of the battery cell's voltage may change outside of a certain Σ level.

[0059] More specifically, when the slope difference of the voltage estimation equation is greater than or equal to the first reference value, the diagnostic unit 230 can diagnose the battery cell as having an abnormal idle voltage after charging when the initial voltage of the battery cell during its idle period is greater than a preset second reference value, and diagnose the battery cell as having an abnormal idle voltage after discharging when the initial voltage of the battery cell during its idle period is less than or equal to the second reference value. For example, the second reference value can be determined as the voltage corresponding to a state of charge (SOC) of 50% for the battery cell.

[0060] When the slope difference of the voltage estimation equation is greater than or equal to the first reference value, the diagnostic unit 230 can diagnose the battery cell as having an abnormal idle voltage after charging when the current of the battery cell flows in the first direction, and diagnose the battery cell as having an abnormal idle voltage after discharging when the current of the battery cell flows in the second direction opposite to the first direction. In this case, the direction of the current can be indicated by (+) or (-).

[0061] The notification unit 240 can generate a warning notification when the diagnostic unit 230 determines that an abnormality has occurred in a battery cell. In this case, the notification unit 240 can generate different warning notifications for each of three battery abnormality types—namely, prolonged idle relaxation, abnormal idle voltage after charging, and abnormal idle voltage after discharging—to allow the user to identify each abnormality type. For example, the notification unit 240 may include a light, a speaker, etc.

[0062] At the same time, although Figure 2 As not shown, the battery anomaly diagnostic device 200 according to an embodiment of the present invention may include a storage unit. In this case, the storage unit may store various data such as voltage and current data obtained by the voltage acquisition unit 210, voltage estimation equations and graphs calculated by the analysis unit 220, standard deviations of the slope differences of the voltage estimation equations, etc. The battery anomaly diagnostic device 200 according to an embodiment of the present invention can operate by sending and receiving the above data through communication with an external server via a communication unit (not shown) instead of including a storage unit.

[0063] Furthermore, despite Figure 2 The diagram illustrates a battery anomaly diagnosis device 200 according to an embodiment of the present invention, which classifies battery cells into types such as long-term idle relaxation, abnormal idle voltage after charging, and abnormal idle voltage after discharging. However, the present invention is not limited to these types, and it is possible to classify them into various anomaly types using statistical methods.

[0064] The methods used to classify battery cells as anomalous types can also be used to make diagnoses using a variety of other statistical methods, not limited to those mentioned above. For example, the slope of the voltage estimation equation can be used instead of the slope difference of the voltage estimation equation, and other data such as differential data can be used.

[0065] Therefore, by using the battery anomaly diagnosis device 200 according to an embodiment of the present invention, the anomaly type during the battery's idle period can be classified by diagnosing the unstable voltage behavior during the battery's idle period.

[0066] Figures 3a to 3c The battery malfunction diagnostic device according to an embodiment of the present invention classifies long periods of idle relaxation.

[0067] refer to Figures 3a to 3c This shows an example of an ESS battery library 1 / rack 6 / module 13 / cell 8. More specifically, Figure 3a The voltage estimation equation for the voltage of a single battery cell is presented as a curve. Figure 3b Show Figure 3a The slope of the curve, and Figure 3c Show Figure 3b The slope difference. In each curve in Figure 3, the x-axis indicates time m. Figure 3a The y-axis indicates the voltage V. Figure 3b The y-axis indicates the slope 'a' of the voltage estimation equation, and Figure 3c The y-axis indicates the slope difference diff(a).

[0068] like Figure 3c As shown, when Figure 3a When the standard deviation of the slope difference of the voltage estimation equation calculated as shown is less than the first reference value (6σ in Figure 3), the battery anomaly diagnosis device 200 according to an embodiment of the present invention can diagnose a battery cell as having an abnormal idle long-term relaxation. That is, the reference... Figure 3c The portion of the curve region included in 6σ (i.e., the bolded portion of the curve) can indicate abnormal long-term idle relaxation of a single cell.

[0069] Figures 4a to 4c The abnormal idle voltage after charging is shown to be classified by the battery abnormality diagnostic device according to an embodiment of the present invention.

[0070] refer to Figures 4a to 4c This shows an example of an ESS battery library 1 / rack 6 / module 13 / cell 8. Similar to Figure 3, Figure 4a The voltage estimation equation for the voltage of a single battery cell is presented as a curve. Figure 4b Show Figure 4a The slope of the curve, and Figure 4c Show Figure 4b The difference in slopes. In each curve in Figure 4, the x-axis indicates time m. Figure 4a The y-axis indicates the voltage V. Figure 4b The y-axis indicates the slope 'a' of the voltage estimation equation, and Figure 4c The y-axis indicates the slope difference diff(a).

[0071] like Figure 4c As shown, when Figure 4a When the slope difference of the calculated voltage estimation equation is greater than or equal to the first reference value (6σ in Figure 4), the battery anomaly diagnosis device 200 according to an embodiment of the present invention can diagnose a single battery cell as having an abnormal idle voltage after charging or discharging. That is, the reference... Figure 4cThe portion outside the 6σ curve region (i.e., the bolded portion of the curve) can indicate abnormal idle voltage of a battery cell after charging or discharging.

[0072] More specifically, in Figure 4c If the slope difference of the voltage estimation equation is greater than or equal to the first reference value, the battery cell can be diagnosed as having an abnormal idle voltage after charging when the starting voltage of the battery cell during the idle period is greater than the second reference value (e.g., 3.8V), and the battery cell can be diagnosed as having an abnormal idle voltage after discharging when the starting voltage of the battery cell during the idle period is less than or equal to the second reference value.

[0073] At the same time, Figure 4c When the slope difference of the voltage estimation equation is greater than or equal to the first reference value, the battery cell can be diagnosed as having an abnormal idle voltage after charging when the current of the battery cell flows in the first direction (e.g., the (+) direction), and the battery cell can be diagnosed as having an abnormal idle voltage after discharging when the current of the battery cell flows in the second direction (e.g., the (-) direction).

[0074] Figure 5 This is a flowchart illustrating a battery anomaly diagnosis method according to an embodiment of the present invention.

[0075] refer to Figure 5 According to an embodiment of the battery anomaly diagnosis method, the voltage X of a single battery cell is measured in operation S510. In this case, the voltage of the single battery cell can be measured at specific time intervals in operation S510. Additionally, the current flowing in the single battery cell can also be measured.

[0076] In operation S520, the voltage of a single battery cell can be analyzed to calculate estimated information related to the voltage during the idle period (Ts-Te) of the battery cell. For example, the estimated information may include a voltage estimation equation related to the voltage of the battery cell. The voltage estimation equation for the battery cell voltage can be calculated relative to a set window size (e.g., 30 minutes). For example, the voltage estimation equation for the battery cell may be equation (1) as described above.

[0077] In operation S530, the slope difference diff(a) of slope a can be calculated. In this case, the slope difference of slope a can be expressed as a t+1 -a t The time interval for the slope difference can be the sampling time (e.g., 1 second).

[0078] Next, in operation S540, it is determined whether the slope difference (e.g., absolute value) of the voltage estimation equation is greater than or equal to a preset first reference value. Figure 5(6σ in the equation). When the slope difference of the voltage estimation equation is less than the first reference value (no), the battery cell can be identified as having an abnormal long-term idle relaxation in operation S550.

[0079] Simultaneously, when the slope difference of the voltage estimation equation is greater than or equal to the first reference value (yes), the process proceeds to operation S560. In operation S560, the starting voltage X of the battery cell during the idle period is determined. Ts Is it greater than the preset second reference value? Figure 5 (3.8V in the middle).

[0080] When the starting voltage X of the battery cell during the idle period Ts If the voltage is less than or equal to the second reference value (No), in operation S570, the battery cell can be identified as having an abnormal idle voltage after discharge. Simultaneously, when the starting voltage X of the battery cell's idle period... Ts When the voltage is greater than the second reference value (yes), the battery cell can be identified as having an abnormal idle voltage after charging in operation S580.

[0081] Meanwhile, instead of the methods of operating S560 to S580, when the current of the battery cell flows in the first direction (e.g., the (+) direction), the battery cell can be diagnosed as having an abnormal idle voltage after charging, and when the current of the battery cell flows in the second direction (e.g., the (-) direction) opposite to the first direction, the battery cell can be diagnosed as having an abnormal idle voltage after discharging.

[0082] Therefore, by using the battery anomaly diagnosis method according to an embodiment of the present invention, the anomaly types during the battery's idle period can be classified by analyzing the unstable voltage behavior during the battery's idle period.

[0083] Figure 6 This is a block diagram illustrating the hardware structure of a battery malfunction diagnostic device according to an embodiment of the present invention.

[0084] refer to Figure 6 According to an embodiment of the present invention, the battery fault diagnosis device 600 may include a microcontroller unit (MCU) 610, a memory 620, an input / output interface (I / F) 630, and a communication I / F 640.

[0085] The MCU 610 can run various programs stored in the memory 620 (e.g., regression analysis programs, battery anomaly type classification programs, etc.), process various data through these programs to perform regression analysis of battery cells, anomaly type classification, etc., and run... Figure 2 The processor that performs the aforementioned functions.

[0086] The memory 620 can store various programs related to regression analysis and anomaly classification of individual battery cells. Furthermore, the memory 620 can store various data, such as measured voltage and current data of individual battery cells, graphs corresponding to voltage estimation equations, slope data, etc.

[0087] Depending on the needs, multiple memories 620 can be configured. Memory 620 can be volatile or non-volatile. For memory 620 as volatile memory, random access memory (RAM), dynamic RAM (DRAM), static RAM (SRAM), etc., can be used. For memory 620 as non-volatile memory, read-only memory (ROM), programmable ROM (PROM), electrically changeable ROM (EAROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), flash memory, etc., can be used. The examples of memory 620 listed above are merely examples and are not limited to these.

[0088] The Input / Output I / F 630 can provide an interface for sending and receiving data by connecting input devices (not shown) such as a keyboard, mouse, touch panel, etc., and output devices such as a display (not shown) to the MCU 610.

[0089] The Communication I / F 640, as a component capable of sending and receiving various types of data to and from a server, can be various types of devices capable of supporting wired or wireless communication. For example, the Communication I / F 640 can send programs or various data for voltage estimation and anomaly type diagnosis of individual battery cells to and receive programs or various data for voltage estimation and anomaly type diagnosis of individual battery cells from and from a separately located external server.

[0090] Therefore, the computer program according to an embodiment of the present invention can be recorded in the memory 620 and processed by the MCU 610, and thus implemented to execute. Figure 2 The module of the function block shown.

[0091] Even though all components constituting the embodiments of the present invention have been described above as operating in combination or in combination, the present invention is not necessarily limited to these embodiments. That is, within the scope of the present invention, all components can be operated by being selectively combined into one or more.

[0092] Furthermore, terms such as “comprising,” “constituting,” or “having” as described above may mean that the corresponding component is inherent unless otherwise stated, and should therefore be interpreted as further including rather than excluding other components. Unless otherwise defined, all terms including technical or scientific terms have the same meaning as commonly understood by one of ordinary skill in the art. Terms in common use, as defined in dictionaries, should be interpreted as having the same meaning as in the context of the relevant art, and should not be interpreted as having an ideal or overly formal meaning, unless they are clearly defined in this invention.

[0093] The above description merely illustrates the technical concept of the present invention, and those skilled in the art will be able to make various modifications and variations without departing from the essential characteristics of the invention. Therefore, the embodiments disclosed in this invention are intended for descriptive purposes only and do not limit the technical spirit of the invention, nor is the scope of the technical spirit of the invention limited by these embodiments. The scope of protection of this invention should be interpreted through the following claims, and all technical spirit within the same scope should be understood to be included within the scope of this invention.

Claims

1. A battery malfunction diagnostic device, comprising: A voltage acquisition unit, wherein the voltage acquisition unit acquires the voltage of a single battery cell; An analysis unit calculates estimation information for estimating the voltage of the battery by analyzing the voltage of the individual battery cells, wherein the estimation information includes a voltage estimation equation related to the voltage of the individual battery cells, and wherein the analysis unit calculates the voltage estimation equation by performing regression analysis on the obtained voltage of the individual battery cells; and A diagnostic unit diagnoses abnormalities in the battery cell based on the slope difference relative to time in the voltage estimation equation. Specifically, the diagnostic unit diagnoses the battery cell as having an abnormal long-term idle relaxation when the slope difference is less than a preset first reference value, and diagnoses the battery cell as having an abnormal idle voltage after charging or discharging when the slope difference is greater than or equal to the first reference value. Wherein, the first reference value is a multiple of the standard deviation of the slope difference of the voltage estimation equation for the plurality of battery cells included in the battery rack.

2. The battery malfunction diagnostic device according to claim 1, wherein, When the slope difference is greater than or equal to the first reference value, the diagnostic unit diagnoses the battery cell as having an abnormal idle voltage after charging when the starting voltage of the battery cell during the idle period is greater than a preset second reference value, and diagnoses the battery cell as having an abnormal idle voltage after discharging when the starting voltage of the battery cell during the idle period is less than or equal to the second reference value.

3. The battery malfunction diagnostic device according to claim 2, wherein, The second reference value is determined to be the voltage corresponding to a state of charge (SOC) of 50% for the battery cell.

4. The battery malfunction diagnostic device according to claim 1, wherein, When the slope difference is greater than or equal to the first reference value, the diagnostic unit diagnoses the battery cell as having an abnormal idle voltage after charging when the current of the battery cell flows in the first direction, and diagnoses the battery cell as having an abnormal idle voltage after discharging when the current of the battery cell flows in the second direction opposite to the first direction.

5. The battery malfunction diagnostic device according to claim 1, wherein, The analysis unit calculates the voltage estimation equation during the idle period after the battery cell has been charged or discharged.

6. The battery anomaly diagnostic device according to claim 1, further comprising a notification unit, wherein the notification unit generates a warning notification when the diagnostic unit determines that an anomaly has occurred in the battery cell.

7. A method for diagnosing battery malfunctions, comprising: Obtain the voltage of a single battery cell; Estimation information for estimating the voltage of the battery is calculated by analyzing the voltage of the individual battery cells, wherein the estimation information includes a voltage estimation equation related to the voltage of the individual battery cells, and wherein the voltage estimation equation is calculated by performing regression analysis on the obtained voltage of the individual battery cells; and The abnormality of the battery cell is diagnosed based on the slope difference relative to time in the voltage estimation equation. The diagnosis of abnormalities in the battery cells includes: When the slope difference is less than a first reference value, the battery cell is diagnosed as having an abnormal long-term idle relaxation; and When the slope difference is greater than or equal to the first reference value, the battery cell is diagnosed as having an abnormal idle voltage after charging or discharging. Wherein, the first reference value is a multiple of the standard deviation of the slope difference of the voltage estimation equation for the plurality of battery cells included in the battery rack.

8. The battery anomaly diagnosis method according to claim 7, wherein, The diagnosis of abnormalities in the battery cell includes: when the slope difference is greater than or equal to the first reference value, the battery cell is diagnosed as having an abnormal idle voltage after charging when the starting voltage of the idle period of the battery cell is greater than a preset second reference value, and the battery cell is diagnosed as having an abnormal idle voltage after discharging when the starting voltage of the idle period of the battery cell is less than or equal to the second reference value.

9. The battery anomaly diagnosis method according to claim 7, wherein, The diagnosis of abnormalities in the battery cell includes: when the slope difference is greater than or equal to the first reference value, diagnosing the battery cell as having an abnormal idle voltage after charging when the current of the battery cell flows in a first direction, and diagnosing the battery cell as having an abnormal idle voltage after discharging when the current of the battery cell flows in a second direction opposite to the first direction.

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